Autonomous tractor concepts being developed by various companies world-wide.
\\n\\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\\n"}]',published:!0,mainMedia:{caption:"Highly Cited",originalUrl:"/media/original/117"}},components:[{type:"htmlEditorComponent",content:'IntechOpen is proud to announce that 191 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\nThroughout the years, the list has named a total of 261 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\nReleased this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
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Due to the intense use of herbicides and their great importance in weed management, research in this area is fundamental to ensure the continuous, effective, and safe use of herbicides while minimizing harmful impacts on ecosystems. The physicochemical properties of herbicides are fundamental to understanding their behavior in plants to effective agronomic of weed control and soil behavior, which also assesses environmental impact. Subjects concerning herbicide-resistant weeds and application technology, mechanism of action and physiology of herbicides on plants, and behavior and fate of herbicides in the environment are accepted in this book.
\r\n\r\n\tGiven the above, this book hopes to cover many valuable and up-to-date research topics in the field of herbicide science, making it a complete and up-to-date book in the field of international weed science for all interested professionals.
",isbn:"978-1-80356-108-0",printIsbn:"978-1-80356-107-3",pdfIsbn:"978-1-80356-109-7",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,isSalesforceBook:!1,isNomenclature:!1,hash:"eb3830b8176caf3d1fd52c32313c5168",bookSignature:"Ph.D. Kassio Ferreira Mendes",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11610.jpg",keywords:"Target-Site Resistance, Non-Target-Site Resistance, Adjuvants, Tank-Mixing, Droplet Size, Variable Rate Application, Mode of Action, Absorption, Translocation, Degradation, Volatilization, Residual Effect",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"January 27th 2022",dateEndSecondStepPublish:"February 24th 2022",dateEndThirdStepPublish:"April 25th 2022",dateEndFourthStepPublish:"July 14th 2022",dateEndFifthStepPublish:"September 12th 2022",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"4 months",secondStepPassed:!0,areRegistrationsClosed:!0,currentStepOfPublishingProcess:4,editedByType:null,kuFlag:!1,biosketch:"Dr. Mendes is an experienced researcher in the field of herbicide science with more than 100 papers published in this field. He was awarded a research fellowship at the University of Minnesota, the USA in 2016, Twin Cities Campus - College of Food and Agricultural Sciences in the Department of Soil, Water, and Climate and the United States Department of Agriculture - Agricultural Research Service (USDA - ARS). He is a member of the Brazilian Society of Weed Science.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"197720",title:"Ph.D.",name:"Kassio",middleName:null,surname:"Ferreira Mendes",slug:"kassio-ferreira-mendes",fullName:"Kassio Ferreira Mendes",profilePictureURL:"https://mts.intechopen.com/storage/users/197720/images/system/197720.png",biography:"Kassio Ferreira Mendes is Professor of Biology and Integrated Management of Weeds, Department of Agronomy, Federal University of Viçosa, Brazil. 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The scientific literature contains numerous articles describing various technologies that were evaluated, challenges that were encountered, conceptualizations of what future autonomous agricultural machines (AAMs) might look like, and issues (both technical and non-technical) in need of redress. In the late 1990s, the “agricultural ergonomics laboratory” was established at the University of Manitoba based on the hypothesis that engineers would continue to incorporate increasing levels of technology into agricultural machines in pursuit of the ultimate goal of the fully autonomous machine. Based on the lessons learned when automation was introduced to other industry settings, the human operator would experience a changing role. Thus, there was a need to view agricultural guidance technologies from an ergonomic perspective.
Unlike two decades ago, it is now possible to find autonomous tractors that are either available for sale to farmers or are in final stages of field testing. Conceptually, there are still at least four distinct designs being promoted (Table 1). There are advantages associated with each of these four distinct types of AAMs. Those which retain the operator station provide flexibility to the farmer for those instances when it is desired that the human operator be physically present on the AAM; this is perhaps most critical in the early days when AAMs are being introduced to the market. AAMs that resemble current tractors (except for the operator cab) and attach to implements in the same manner as existing tractors will reduce the capital cost associated with transitioning to autonomous agricultural production because the farmer will be able to continue to use existing implements. The integrated tractor reflects the situation where the engineer will be able to optimize the design of the tractor-implement system; it potentially enables design opportunities not present with the current paradigm of a tractor pulling an implement (which is a hold-over from the early concept of a horse pulling an implement). The downside, of course, is that a whole new set of implements will be required as the farmer’s existing implements will be incompatible with the integrated tractor. The swarm or fleet concept perhaps reflects the most radical concept, reversing the decades-long trend of building bigger agricultural machines. Perhaps inspired by the insect world, the concept is that a fleet of many small AAMs working in an organized manner can outperform a small number of large-sized AAMs. It is too early to predict whether a single concept will emerge as the industry standard, or whether all of these concepts will survive either in niche applications or in direct competition with one another.
Concept | Example | Main Features |
---|---|---|
Retain operator station | Monarch Tractor |
|
Eliminate operator station | CNH, John Deere, Kubota, Autonomous Tractor Corporation |
|
Integrated tractor | DOT |
|
Swarm/Fleet | Fendt Xaver |
|
Autonomous tractor concepts being developed by various companies world-wide.
Regardless of how the AAM industry evolves, it would be foolish for designers to neglect how these autonomous machines will interact within the larger human-autonomy system. It is inevitable that the AAM will need to interact with a human supervisor to receive instruction and to request assistance when problems cannot be self-corrected by the AAM. Appropriate principles from the discipline of human factors engineering will be essential to the successful integration of AAMs into production agriculture.
Supervision is an activity that is undertaken for the purpose of ensuring that a task is done in such a way that it meets our approval (in terms of safety, in accordance with rules, etc.). We would find it absurd to hire a junior employee and not provide some means for supervision of their work. Even senior employees require supervision to ensure that they are held accountable for their performance. The same need for supervision applies to the AAMs currently being developed by engineers. Autonomous machines, though independent, still require human supervision [1, 2] to help minimize any catastrophe that may arise in case of unexpected situations such as system failure or malfunction that exceeds the capability of the machine [3]. Furthermore, since it is currently difficult to automate high-level reasoning and tasks, it is also beneficial that the human remains in the decision-making loop to assist with planning field operations, allocating resources, and coordinating the autonomous machines. Generally, involving the human (as a supervisor) in an autonomous system has been reported to increase the overall reliability and performance of the system [4].
Supervision can be carried out in proximity (where the supervisor and the system being supervised are collocated) or remotely (where the supervisor performs his/her roles from a distant location without being physically present in the work zone). Currently, supervision of agricultural field machines is mainly performed in proximity (i.e., with the operator seated in a cab on the machine), but it is envisioned that future AAMs will be supervised remotely due to farm labour shortages (i.e., enabling one person to supervise multiple AAMs) and to enhance the overall efficiency of the farmer (i.e., enabling the farmer to complete other farm management tasks while supervising AAMs in the field).
Remote supervision is not novel and has been practiced for decades in different sectors. There is evidence of remote supervision being used in non-agricultural sectors such as military, space exploration, marine, industrial applications, and rescue operations [5, 6, 7, 8]. As an example, robots that are used to inspect pipelines for cracks are monitored remotely during operation [9] since these areas are not accessible by humans. Search and rescue robots and military drones have been monitored remotely [6, 10]. In both cases, supervisors make use of some type of interface (which may be portable or stationary) to monitor the robot and to receive status updates. In agriculture, remote supervision has been used in livestock husbandry, crop production, and crop storage [8]. Unmanned aerial vehicles (commonly known as drones) have been remotely monitored while using them to determine weed infested regions on the field. In a hog barn environment, the physiology of pigs (body temperature) and environmental conditions of the barn (air temperature, humidity, and concentration of carbon dioxide, hydrogen sulfide, and ammonia) have been remotely monitored to minimize contact with the pigs and to assist the farmer with decision-making from any location [11].
Several remote supervision concepts for autonomous agricultural field machines have been proposed by academic researchers and manufacturers alike. These concepts differ with respect to the type of human involvement, autonomy level, proximity of the remote supervisor to the autonomous machine, and number of autonomous machines being supervised simultaneously [12]. For example, [13] envisioned the human to only monitor autonomous machines, whereas [14] expected the farmer to both manually operate a field machine while supervising another autonomous machine (which may or may not be the same type of machine). A third supervision concept involved manually controlling the actual operation of a field machine remotely (i.e., teleoperation) [15]. Some researchers [2, 16] proposed that the human would monitor just one machine while others [17, 18] envisioned the supervisor to monitor several machines simultaneously.
Edet and Mann [12] described four remote supervision concepts based on the location of the remote supervisor in relation to the AAM: 1) in-field supervision, 2) edge-of-field supervision, 3) supervision from the farm office, and 4) supervision from outside the farm site. A practical example of the ‘in-field’ supervision concept is the human-machine, master–slave interaction that involves having both an AAM and a human-driven machine working simultaneously on the same field. Supervision of the AAM would be done from an interface located in the cab of the human-driven machine. In the ‘edge-of-field’ remote supervision concept, the farmer is not operating any of the machines. This gives the farmer the opportunity to also be involved with the logistics of the operation such as bringing supplies to the field, making repairs, and responding to alerts. The ‘supervision from the farm office’ concept, on the other hand, makes it more challenging for the farmer to respond to in-field demands in a timely manner; the advantage is that the farmer can attend to other non-field related tasks rather than focusing on monitoring the AAM alone. Supervision from outside the farm site would theoretically allow a farmer to remain engaged in field operations while physically away from the farm for personal or vocational reasons, although it would be challenging to address system malfunctions. This role would need to be delegated to someone else, potentially contracted to an agency that would monitor and service AAMs for a fee.
Each remote supervision concept has corresponding benefits and shortcomings. For example, the ‘in-field’ concept would likely have the shortest response time, however, if the AAM breaks down or requires assistance, the entire field operation may come to a standstill since the manually-operated machine will also be stopped as its’ operator handles the problem. In the ‘edge-of-field’ and ‘from the farm office’ remote supervision concepts, the farmer would not be controlling any of the AAMs in operation. Hence, the farmer is available to manage both i) malfunctions that are beyond the capability of the AAM and ii) other logistics associated with the operation without assistance from other farm workers. Of these two remote supervision concepts, ‘edge-of-field’ supervision may be preferred over ‘from the farm office’ supervision because of the closer physical presence to the AAM which, in theory, should allow for faster response to malfunctions that require human intervention. Remote supervision concepts that rely on servicing of AAMs being done by professional service technicians in a fee-for-service arrangement may not be accepted by many farmers due to a preference for self-sufficiency and the timely manner in which many farm operations need to be completed.
Generally, a suitable remote supervision concept should: i) require minimal labour to function, ii) enable the farmer to monitor and understand the status of the operating machine in the field, iii) not restrict the movement of the farmer, iv) allow the farmer to perform other farm tasks, iv) enable the farmer to attend to in-field problems in a timely manner, and vi) be cost effective. Other factors that may influence the choice of remote supervision for monitoring the operation of AAMs include the size of the farm, ease of use of the automation interface, type of field operation being conducted, business structure of the farm, the farmer’s preference, and future legislation that might relate to the supervision of AAMs. Based on an unranked paired comparison analysis of the concepts, the ‘edge-of-field’ remote supervision concept was determined to be the most viable remote supervision concept for broadacre grain producers [19].
It can also be deduced that remote supervision of AAMs requires an automation interface since it is the communication link that enables the human supervisor to interact with the AAM. Edet [19] generated the following list of functional requirements for an automation interface; the remote supervisor should be able to:
Instruct the AAM to commence operation.
Monitor telemetrics of the AAM.
See key elements of the AAM in real-time.
Visualize the position of the AAM within the field.
Receive notifications of important events and anomalies from the AAM.
Query the AAM about planned actions.
Instruct the AAM to stop or shut down, or to alter plans.
In 2017, an important article entitled “From here to autonomy: lessons learned from human-automation research” was published by a leading expert in human-autonomy teams [20]. The key to a successful human-autonomy team is to assume that there will be instances where the autonomous system will require input from the human supervisor who is part of the human-autonomy team, and to ensure that the autonomous system is designed to most effectively share critical information with the human member of the human-autonomy team. In essence, [20] recommended that there should be shared situation awareness within the human-autonomy team where the human supervisor fully understands the actions being taken by the autonomous system so that appropriate actions can be taken by the human supervisor at any instant. Designing to support shared situation awareness is a non-trivial undertaking for the design engineer. Most autonomous systems require substantial complexity to fully automate the various tasks associated with the overall functioning of the machine. Passive monitoring of automation creates a high workload for the farmer [21] – this likely contradicts one of the reasons for using AAMs in production agriculture in the first place (i.e., to reduce the workload for the farmer). In her “human-autonomy oversight model”, [20] recommended that a transparent automation interface be designed so that the human responsible for supervision of the automation will be able to successfully navigate from periods of passive supervision to periods requiring intervention. The next section of the chapter will focus specifically on the automation interface.
For decades, virtually all textbooks that have been written on the topic of ergonomics or human factors engineering have had chapters devoted to the design of displays and the design of controls. Displays must be designed well to clearly convey machine status information to the operator. The design and arrangement of controls is essential to allow efficient communication of instructions from the operator to the machine. When dealing with an autonomous machine, there is perhaps limited reason for the supervisor to need to communicate short-term actions to the autonomous machine. It is more reasonable to expect that communication in this direction will be reserved primarily to high-level management decisions. However, the flow of information from the autonomous machine to the human supervisor is anticipated to remain important.
The key to a successful system comprised of an autonomous machine and a human supervisor is a well-designed interface that allows for the exchange of information between the autonomous machine and the human supervisor. There are several papers published over the past two decades that touted the importance of an automation interface and have postulated on the features essential to an automation interface. In a paper published two decades ago, [22] explained their expectation that the farm manager would be responsible for overseeing the coordinating process from a computer located in the farm office. They proposed the term of ‘tractor mimic display’ for the automation interface that would be used to display telemetric data from the tractor unit, show the position of the tractor unit on a map, and display real-time video as seen through steerable cameras placed on the tractor unit. In the same year, [16] published a paper that investigated how humans can supervise AAMs. These authors discussed the challenges associated with designing an autonomous system that avoids both false positives and false negatives. Although they stated the desire to design such to err on the side of false positives (i.e., where a machine sees a problem where there are none), they further suggested the use of humans as ‘remote troubleshooters’ to classify positives as either true or false. Their system was designed to transmit images of the scene whenever the tractor detects an obstacle in its way; the images were presented to the remote troubleshooter using a ‘remote operator interface’. In addition to sharing telemetric data and live video, the interface provided a warning when an obstacle was detected and explained what portion of the image was being classified as an obstacle. In a more recent paper, [23] described work completed to develop a team of robotic tractors for autonomous peat moss harvesting. In manual peat moss harvesting, a team leader supervises a team of three of more tractor operators using radio and/or hand signals. The autonomous peat moss harvesting system mimicked the manual harvesting system in that the human team leader communicated with the autonomous harvesters through a ‘team leader user interface’. In this instance, the interface displayed telemetric information from each of a team of autonomous harvesters. Furthermore, a map was used to show the position of each harvester and to provide a visual representation of harvesting progress. Moorehead et al. [24] described a system of autonomous tractors for orchard maintenance. The autonomous system was comprised of tractors (equipped with perception systems and capable of driving autonomously) and a remote supervisor who assigns tasks, responds to requests when the perception system is unable to decide how to deal with a detected obstacle, and tracks the fleet of autonomous tractors. Although the tractors were equipped with cameras and the remote supervisor’s interface was designed to display video, it was not intended that the supervisor should monitor the real-time video continuously. Rather, a warning message appears when an obstacle is detected and the tractor has stopped forward motion; the supervisor must then review the available video and decide whether a worker needs to be sent to remove the obstacle or if the warning is a false positive meaning that the tractor may proceed safely.
Based on this brief review of automation interfaces that have been reported in the published literature, there are several common elements that are envisioned for an effective ‘automation interface’. First, it is anticipated that the automation interface will provide telemetric data related to the autonomous agricultural machine; such information is necessary to assure the human supervisor that the machine is functioning within normal operating parameters. Second, there is a need to show the location of the autonomous machine within the context of its operating environment (i.e., field, orchard, peat bog, etc). Third, it is envisioned that the autonomous machine will, at times, experience situations which will require human intervention. In these instances, a warning message will be displayed for the supervisor. The autonomous machine will stop until the issue has been resolved by the supervisor and the machine is cleared to resume operation. To enable the supervisor to be able to see what is happening, cameras are necessary on the AAM to transmit real-time video which is viewed on the automation interface.
If the automation interface contains irrelevant information, this may result in overcrowding that could reduce the effectiveness of the interface. On the other hand, omitting essential information may impede the supervisor’s ability to perform his or her role effectively. Thus, providing the supervisor with the right information is central in designing an effective user interface [25]. Identifying the right information can be achieved through the completion of a requirement analysis which involves identifying and understanding the goals of the task as well as the role of the user [26]. Endsley [27] noted that the supervisor should have a high situation awareness (i.e., “the perception of the elements in the environment within a volume of time and space, the comprehension of their meaning, and the projection of their status in the near future”) of the automated machine to be able to take necessary action in a timely manner. This awareness includes: i) machine location awareness, ii) activity awareness, iii) status awareness, iv) surrounding awareness, and v) overall mission awareness [28].
The results of a requirement analysis that was conducted for the task of supervising an agricultural sprayer have been included to demonstrate this process. Both users and designers were consulted to inform the design of an automation interface for an autonomous agricultural sprayer. Table 2 provides a summary of the information arising from a survey of the farming community [8] which was structured to determine the types of information that should be included on an automation interface in order to remotely supervise an autonomous agricultural sprayer. Parameters listed under the ‘very useful’ column were recommended by at least 75% of the respondents; [8] concluded that these pieces of information should be included in an automation interface. In further work towards the requirement analysis, [19] consulted with expert designers of AAMs. Parameters such as fuel level, tire pressure battery status, current location, global field (coverage map), tank level, spray pressure, application rate, nozzle status, and boom height were ranked as being essential information for an automation interface by the majority of designers interviewed.
Information | Descriptions | |||
---|---|---|---|---|
Very useful | Useful | Least useful | Other suggestions/ comments | |
Machine status | Engine temperature, engine speed, fuel level, oil pressure, hose leakage, boom folding (open/close), and agitator | Tire pressure | Auto-steer status, GPS status, slippage | |
Spraying functions | Boom height, nozzle status, area covered, spray pressure, application rate, travel speed, wind speed, and wind direction | Daily temperature, skip/double application, delivery rate, current task | Humidity and altitude | Field condition, tank level, chemical mix of what is in the tank, sectional control, gallon per hour sprayed, acres covered, area sprayed per coverage, number of fills, and droplet size |
Navigation features | Route taken, current location, and overhead view | Distance travel | Compass | Planned route, and coverage map |
Warning and notifications | Plugged nozzle, machine breakdown, Obstacle detection, loss of GPS signal, and unexpected shutdown | Tank level drop, fuel level drop, and route change | Task completed, and skip/double application | Emergency shutdown, |
Interface requirements as determined by the farming community through survey. >75: Very useful, 51–75%: Useful, 25–50%: Least useful, and < 25: Not at all useful (adapted from [8]).
A majority of the users and designers consulted in the completion of the requirement analysis indicated that live video footage of the autonomous sprayer should be made available to the remote supervisor [8, 19]. Panfilov and Mann [29] had previously investigated the importance of live video footage to the remote supervisor of an autonomous sprayer in an experimental study completed using a simulator in a lab environment. They reported that live video provided a sense of security to the supervisor, but was not typically used to detect malfunctions. They also noted that the supervisor spent only 30% of their time viewing the video. In their experimental study, participants spent the majority of their time monitoring telemetric data displayed using traditional display elements (i.e., gauges, dials, etc.). Finally, they suggested that it might be appropriate to provide real-time video on-demand. Edet [8] reported that some respondents felt that providing only one view of the sprayer was not enough to properly understand the entire spraying operation – they suggested having multiple views of the machine during operation available through an automation interface.
The previous section established the need to provide the remote supervisor of an AAM with real-time video showing the machine and its environment [8, 29]. Real-time video helps the supervisor to better understand abnormalities within the AAM [29]. Blackmore [22] also noted that the presence of live video will enable the remote supervisor to understand the machine’s environment. These statements are evident in studies carried out by [2, 16, 28, 30, 31]. With these potential benefits, the challenge is to determine where the cameras should be placed to maximize the benefit of the real-time visual information.
Operators of conventional tractor-seeding machines visually monitor seven distinct areas of the machine and its environment (termed ‘look zones’) [32]. These areas included: i) forward, ii) right side, iii) planter, iv) planter edge, v) display X (located at the top right corner from the operator’s seating position), vi) display Y (located close to the arm rest of the operator), and vii) other (located close to the front-left tire of the tractor). Other researchers [33] identified four sectors: i) field ahead, ii) left boom, iii) right boom, and iv) the light bar while investigating the “workload associated with operating an agricultural sprayer equipped with a navigation device.” Hence, it can be inferred from these studies that the visual information that is useful to operators can be derived primarily from i) displays located inside the machine’s cab, ii) external field cues, and iii) the implement.
Although these studies identified the different regions of importance, they did not describe what information was gained by viewing those regions. Hence, a study was conducted to identify what visual information about the machine and its environment would assist the remote supervisor to make decisions [34]; the primary focus of this study was the high-clearance sprayer. GoPro cameras were mounted at difference locations on a sprayer to record the sprayer and its environment while in operation (Figure 1). After collection of this video footage, 29 experienced operators (defined as having at least two years experience as a sprayer operator) were recruited and presented with 10 distinct video clips of the high-clearance sprayer in operation (Figure 2). For each video clip, the operators were asked i) to describe what they saw in each video clip, ii) to describe the information gained from the viewing the video clip, and iii) to rank the importance of the visual information perceived using a 5-point Likert scale.
A schematic showing the various camera positions on the high-clearance sprayer during the spraying operation (a) plan view (b) side view. This figure was originally published in [
Screen shots of clips 1–10. This figure was originally published in [
Not all video clips were equally effective at providing information that was relevant to the spraying operation. Among the 10 clips, clips 1 and 2 were considered very important and extremely important, respectively, by the operators while clips 3 through 7 did not provide much information that was considered relevant to the operators. The results of data analysis revealed that experienced operators generally preferred the view from the i) boom and nozzles, ii) the view ahead of the sprayer (front view), and iii) an aerial view of the sprayer. These regions enable them to determine the field/crop variability or conditions, upcoming field information (e.g., headland, obstacles) as well as assess if the sprayer is functioning properly and spraying effectively. Specifically, the information that was perceived from these views included the spray pattern, nozzle height and status (plugged or not), spray pattern/drift, obstacles in front and beside sprayer, poor areas in the field (i.e., crop condition), wet spots, approximate travel speed, headlands, type of crop being sprayed, weather (windy and sunny), location of sprayer in the field, overall picture of the field (aerial view), and if the sprayer was moving and following the right path (i.e., moving straight). This result was found to be independent of how frequently a particular view (or information) was presented. A visual representation of the information gained from the operator’s ‘look zones’ is shown in Figure 3.
Visual representation of the information gained from the operator’s seated position in each of the look zones. This figure is adapted from a figure originally published in [
Camera angle and position influenced what information the operators perceived from the video clips [34]. Participants tended to describe features that were more prominent within the frame of the camera in comparison to less-prominent features. For example, many participants described features that were associated with the spray boom in clip 2 since the clip focused mainly on the right boom. Similarly, clip 9 emphasized the field and correspondingly most participants focused on the relevant information that was gained from the field. This finding suggests that designers can influence which features the user will perceive by positioning the camera such that those specific features are prominent in the camera’s field of view.
One of the most suggested views was to have a camera at one end of the boom facing forward. However, when analyzing the videos, this view was found to have minimal difference from the forward view for a sprayer with a long boom. Other views that were suggested included i) a close-up view of the nozzle and its tip, ii) a view from under the sprayer facing backward to see the spray pattern behind the sprayer and wheels, iii) dashboard/displays, and iv) a camera that would focus on the wheel to show how well the sprayer was either following old tire tracks or steering within the rows of a crop.
The importance of real-time visual information in the autonomous interface has been demonstrated in the previous sections, however, it is also necessary to consider how camera placement (i.e., camera height and camera tilt angle) influences the usefulness of this visual information. Previous research by [35] investigated the impact of camera placement on guidance performance for a manual guidance task in which the tractor operator relied on visual information provided by an implement-mounted camera that was displayed on a monitor close to the operator’s seat. Tang and Mann [35] described a phenomenon that they called ‘image velocity’ which quantified the rate at which the visual information scrolled across the monitor from top to bottom as the tractor drove forward through the field. Image velocity is based on the camera’s optical parameters, placement of the camera on the implement (height and tilt angle), and the tractor velocity. The reader is directed to [35] for a thorough description of how the parameter of image velocity was calculated.
The results published by [35] did not provide definitive evidence of a relationship between image velocity and lateral guidance error, however, trends were observed with lateral error increasing with image velocity. Test participants self-evaluated their performance following each trial; these results showed a decreasing linear trend with increasing image velocity. Participants preferred a tilt angle of 20° below horizontal as this gave them the best look-ahead view (i.e., the greatest look-ahead distance); however, the 30° tilt angle yielded the statistically smallest guidance error. It is unknown how the prior research by [35] will inform the current task of placing cameras on an AAM for the purpose of remotely supervising the machine on an automation interface because their research was focused primarily on trying to minimize lateral error associated with a manual guidance task. Nevertheless, their prior research inspired subsequent studies intended to determine the impact of camera placement on the usability of the visual information for the task of remotely supervising an AAM.
A lab experiment was conducted in which test participants were asked to watch pre-recorded video clips as a means of obtaining real-time visual information from the field (simulating the task of remotely supervising an AAM) [36]. Video footage was pre-recorded for nine unique combinations of camera placement, namely three camera tilt angles (20, 30, and 40°) and three camera heights (0.5, 1.0, and 1.5 m), to yield nine different look-ahead situations. Participants, some of whom were inexperienced agricultural machinery operators recruited from the university student population and some of whom were farmers experienced in operating agricultural machines, were asked to complete two distinct experimental tasks. First, they were asked to choose their preferred look-ahead position after watching two unique video clips playing side-by-side on the screen (Figure 4). Second, the participants responded to questions that would help determine the effect of camera placement on the difficulty of detecting and interpreting the randomly-placed frisbees in the video clips watched (Figure 5).
Screenshot of look-ahead videos side by side (part one).
Screenshot of video footage with frisbees appearing on the soil (part two).
An unranked pairwise comparison was used to analyze the data from part one of this study. This is a decision-making tool in which alternatives are compared to each other, one at a time, to arrive at the best choice. Each alternative is considered relative to other options available, with a value of one assigned to the more desirable option and a value of zero assigned to the less desirable option to arrive at alternative choice coefficients for each option being considered [37, 38]. Using this methodology, participants made pairwise comparisons for all nine look-ahead combinations. For both groups of participants (i.e., university students and experienced sprayer operators), look-ahead videos of 30° were the highest ranked of the nine combinations of height and tilt angle (Figure 6).
Alternative choice coefficients calculated based on the unranked paired comparisons of look-ahead videos.
In the second part of the experimental study, participants were asked to rate each video clip based on i) the level of difficulty associated with detecting randomly placed frisbees and ii) the level of difficulty associated with interpreting randomly placed frisbees (each on a four-point Likert scale with one indicating low difficulty). Look-ahead views associated with a camera tilt angle of 30° were the look-ahead views perceived as creating the least degree of difficulty (Figures 7 and 8). Overall, the results of the experimental work completed by [36] suggest that forward-facing cameras on AAMs should be mounted such that they are 30° below horizontal to provide the most useful look-ahead visual information for remote supervision of AAMs.
Rated difficulty in detecting frisbees.
Rated difficulty in interpreting frisbees.
With reference to an earlier section, the reader is reminded that previous researchers identified the need to warn the supervisor when the AAM experiences an abnormality which it cannot resolve itself. In such situations, there should be a means to communicate the problem to the remote supervisor immediately to increase the operational safety of the system. Different methods have been adopted in non-agricultural devices for similar purposes. They primarily make use of visual, auditory, and tactile (haptic) modalities [39]. Other modalities include olfactory (smell) and gustatory (taste) [39]. Visual, tactile, and auditory modalities have also been adopted in agriculture to inform operators about abnormalities in current agricultural machines. For example, both auditory and visual modalities have been used to notify operators about plugged nozzles while tactile and visual modality, respectively, have been used to inform operators about lateral deviation of the machine from its desired path.
Visual stimulus can be presented as text, graphics or flashing light [40] while auditory warning can be a continuous or periodic tone or tones (sounds), auditory icon (natural or symbolic), or verbal message [40, 41]. Tactile stimulus, on the other hand, communicates information through the skin (i.e., touch). Each modality has its benefits and shortcomings. For example, auditory modalities are omnidirectional unlike visual modalities that are more effective when the user is stationary. However, it may impede the user’s ability to perceive the source of auditory warning. Tactile information is valuable in an environment where noise must be limited [42], but may be less effective if there is minimal contact between the tactile medium and the user’s skin. One method that is widely used to assess the effectiveness of these modalities to communicate information to the user is reaction (response) time [43, 44]. This is the time interval between when the warning is communicated (using one or more modalities) to when the user reacts to the warning. A shorter reaction time would imply that the warning is more effective than a longer reaction time. Reaction times have been reported to vary with age, gender, experience, education level, culture, personality types, and intelligence of the user [45].
Researchers [46, 47, 48] have also shown that there are benefits to using multiple modalities in comparison to single ones, especially in situations where the primary task or environmental condition overloads one sensory modality. For example, [49] found that drivers responded faster when presented with multimodal warnings in comparison to unimodal warnings when evaluating driver’s response time under different situational urgency while [50] noted that unimodal warnings yielded longer reaction time responses in comparison to multiple modalities while investigating the effectiveness of seven warning methods (visual, auditory, tactile, visual and auditory, visual and tactile, auditory and tactile, and no warning) under three different types of interference (in-vehicle device, audio noise, and vibration of the vehicle). On the other hand, no significant differences were experienced between unimodal and bimodal warnings when informative tactile warning and audio-tactile warnings were compared [51] – suggesting that single warning methods can be as effective as multiple warnings, depending on how they are designed or presented to the supervisor. Hence, as agricultural machinery moves towards full automation, it would be useful to distinguish which of these modalities (single or multiple) would be the most effective in alerting the remote supervisor about a problem with the machine – since these modalities vary in their ability to draw the attention of the supervisor.
A study was conducted to assess which of the seven modalities (visual, auditory, tactile, audio-visual, audio-tactile, visual-tactile, visual–auditory-tactile) would be the most effective in providing feedback to the remote supervisor of an autonomous sprayer [52]. They modified an autonomous agricultural machine control interface (AAMCI) simulator that was designed by [29] to include the different warning methods. Their experiment involved participants playing a game on the secondary screen, monitoring the operation of the autonomous sprayer through the AAMCI simulator, and clicking an ‘Alert Perceived’ button when they are notified of any error. Response time was used to determine the effectiveness of each modality (single or multiple).
One of their sessions was conducted in a quiet environment without having participants play the game. The remaining sessions were conducted i) in a quiet environment, ii) with tractor background noise and iii) with office (call center) background noise, respectively, to replicate the various scenarios of the four remote supervision concepts that were described by [12]. The experimental setup is shown in Figure 9. Further details of the experimental procedure can be found in [52]. They noticed that all seven warning modalities were able to accurately warn the participants of the errors, but varied in their effectiveness (i.e., response time). Overall, the visual and tactile (visual-tactile) warning method was found to be the most effective warning among all the seven warning methods since it had the lowest response time regardless of the background noise or environment (Figure 10). However, this observation was only statistically significant for the tractor background noise (p < 0.05).
Experimental setup for the alert study.
Effectiveness of the warning methods as a function of response time for participants exposed to tractor noise, quiet environment, and office/call center background noise, respectively (a = audio, T = tactile, and V = visual).
The response time obtained when participants were continuously monitoring the autonomous sprayer through the AAMCI was also compared with those obtained when participants had to play the game and monitor the simulation in a quiet environment. Their findings revealed that for all warning methods, participants responded faster when they were monitoring the simulated sprayer (i.e., the interface) continuously in comparison to intermittent monitoring (Figure 11). This result was found to be statistically significant (t-test, α = 0.05). Despite this result, it was noted that most participants experienced boredom due to low mental workload during the ‘No-Game’ session (i.e., continuous monitoring) as demonstrated either through yawning, frequent eye blinking, and body posture adjustment.
Comparison of participants’ response time in relation to the monitoring levels (a = audio, T = tactile, and V = visual).
Overall, the findings from the study may be biased by the fact that the simulation and game may have lacked the type of complexity and workload a remote supervisor may experience while monitoring an actual AAM. Hence, engineers must conduct further analysis during prototype testing to ensure that these results apply in an actual situation of remote supervision of an AAM.
Real-time visual information originates from cameras mounted on AAMs and must be transmitted to the automation interface, perhaps located at the edge of the field, to enable ‘edge-of-field’ remote supervision. This will require the transference of data through some method of wireless transmission. Conversion of visual data into electronic signals and the time required for data to propagate incurs latency, or delay.
Latency can be described as the difference in time between an action and a response and in the context of autonomous vehicle surveillance can refer to several delay measurements. Glass-to-glass, or capture-to-display, latency is among the most typical to consider for a video being delivered to a user, and refers to the full latency from the occurrence of an event in front of a camera to the time the event can be recognized in the display used to monitor the machine [53]. Delays measured from the beginning of the encoding process to the end of decoding are also critical and are simpler to measure, as they require fewer external tools to evaluate than for glass-to-glass latency. Delays induced by the network, encoding and decoding, camera capture and video display, and the queueing of data packets can all be said to be important elements which comprise transmission latency [54].
The selected method of encoding and decoding is a significant source of latency for video. Networks tend to place restrictions on available bandwidth which must be mitigated to provide consistent video streams for a viewer. Coder-decoder (CODEC) formats, such as the widely used H.264 standard, compress and simplify video streams based on a range of algorithms and protocols. While this compression results in a significant reduction in the size of transmitted information, a trade-off is present where the computations required to reduce the size take varying amounts of time to complete. Compression can tend to be somewhat lossy such as in the case of H.264 [55], sacrificing what is considered an acceptable amount of visual information to produce a reasonably complete image for a viewer. Alternative transmission formats such as MJPEG instead send the video as a steady stream of captured JPEG video frames without such reductions due to compression, which correspondingly reduces image encoding time while resulting in significantly higher bitrates, resulting in demonstrably lower latencies in some comparative experimentation [56]. H.264 has been supplanted somewhat by H.265 video encoding [55], which promises faster rates of encoding and more efficient compression due to larger block sizes for the selection mechanisms used to simplify existing video frames, but still makes up a significant amount of the market today, used by 92% of developers in 2018 [57].
Transmission over the network is a key element of latency. If the required bitrate of video cannot be adequately accommodated by the allotted bandwidth it can result in increasing latency, as successive frames must wait for already queued frames to be received. This latency will theoretically approach infinity or some arbitrary limit, and frames of video will be dropped due to overflow of buffers used in the video stream to hold incoming video frames. The network path taken by video will inevitably introduce further delay, with longer paths with more frequent hops resulting in an increasing latency due to the travel time for data packets. Selection of the transmission level protocol used for the two devices to communicate will also have significant implications for overall latency. While the widely used TCP/IP communication protocol will eventually successfully transmit frames of video, the required two-way acknowledgement of data reception places significant time constraints. As frames are lost due to travel through the network this latency induced due to TCP can steadily increase as successive frames are forced to wait for complete transmission of earlier data [58]. In comparison, a transmission protocol such as UDP makes no guarantees of successful reception due to lacking this same handshake mechanism, but delivers video frames with lower latency due to the reductions in time as a result of not requiring the handshaking process with each transmitted data packet.
Latency has been measured using a range of methods for various applications, which vary depending on the specific delay that is to be measured. Kaknjo [56] measured latency during transmission for a robot utilizing the common method of placing a pulse per second enabled LED in front of a camera to act as an event recognizable by the system. This direct test of the camera system was coupled with utilization of timestamps to measure latency when transmitting video over a larger network. A customized application for WebRTC communication [59] transmits specialized video frames containing a spinning object and a continuously counting timestamp to measure latency between users.
An investigation of transmission latency in an agricultural setting was undertaken at the University of Manitoba [60]. A Raspberry Pi 4 was configured using the GStreamer multimedia application to be able to selectively stream video over cellular internet and a direct radio connection. The Pi 4 was fitted with a cellular header and connected via Ethernet to the radio system and mounted to a riding mower. Open-source GStreamer libraries were then used to overlay timestamps into the video feed from the Raspberry Pi, which could then be decoded and extracted by a laptop acting as a receiver and compared against the laptop time to measure the latency experienced.
In a subsequent experimental study, video transmission latency was measured for three transmission distances (200, 400 & 600 m) and for three resolutions of video (480p20fps@400kbit, 480p25fps@500kbit & 576p20fps@600kbit) using two transmission modes (cellular and radio). Data were collected at four geographical locations within 1 h (driving time) from the university campus. Complete details of the experimental procedure and results can be found in [60].
For the relatively short transmission distances tested (which were selected as representative of the ‘edge-of-field’ remote supervision concept proposed by [12] there were no obvious differences or trends in transmission latency for either transmission mode (cellular or radio) with a couple of exceptions which can likely be explained by the presence of trees adjacent to one of the test sites which may have interfered with radio transmission. Figure 12 shows the results of data collection at the Glenlea, Sanford, and university campus testing locations.
Graphical depiction of experimental mean latency measurement results.
As was expected, transmission latency increased with increasing video resolution for both transmission modes (cellular and radio), but with the transmission times below 300 ms in most cases. Despite the more direct transmission path for radio transmission, measured latencies were less for cellular transmission at test sites with strong signal strength. It was observed, however, that a couple of the test sites had poor cellular coverage. At one site, cellular transmission of video was not feasible with transmission latencies up to 86 s observed.
Overall, [60] concluded that it should be feasible to transmit real-time video from an AAM to an automation interface located at the edge of the field using either cellular or radio transmission. Latencies measured fell within acceptable international telecommunications union recommendations for acceptable one-way delay of less than 400 ms. These values were also in line with experiments for a telerobotic surgery simulator [61], where below 300 ms it was observed that performance of surgical tasks did not tend to degrade much with increasing latency. In locations where adequate cellular signal strength exists, cellular transmission is recommended as it causes less transmission latency and would give a greater overall range. Radio transmission of real-time video is recommended only in locations where there is poor cellular coverage.
Despite the promising results reported by [60] related to latency of real-time video transmission, there are several questions that warrant further investigation. First, research is warranted to determine the impact of transmission latency on the usability of the automation interface. Assuming constant latency, is there a magnitude beyond which it becomes impossible to remotely supervise an AAM? A related question is to determine the effect of varying latency on the usability of the automation interface. A second question worthy of further investigation is to determine the quality of video that is required for remote supervision of an AAM. [60] have reported that transmission latency increases with increasing video resolution, suggesting that it is beneficial to use low-resolution video for this application. The effect of video resolution on the usability of the automation interface must be determined. It is anticipated that the optimum video resolution for real-time supervision of AAMs will be a compromise between transmission latency and usability. A third issue is that the techniques and equipment used for transmitting video data have not yet been optimized. With the implementation of elements such as dedicated specific hardware, adaptive bitrate encoding and H.265 compression, it would likely be possible to further reduce latency by reducing the time required for encoding and decoding. Similar studies have been able to obtain latencies under 200 ms with Raspberry Pis [62] in different environments. It is important for developers and product manufacturers to consider these various aspects of video transmission to be able to provide low latency video feeds for end users. CODEC mechanisms should be selected to balance the requirements of bandwidth and latency and appropriate transmission protocols utilized to keep video streams loss tolerant while keeping latency low. Implementing the appropriate mechanisms in video streams will minimize delay for the AAM supervisor.
This section presents a case study where knowledge gained from prior research activity related to the role of real-time visual information to the task of remote supervision has been applied to the design of an automation interface for an autonomous plot sprayer. The desire to design an automation interface for this specific machine was initiated by a group of undergraduate students interested in developing an AAM for the agBOT Challenge sponsored by Purdue University. To meet the objectives of the agBOT Challenge, the students would need to design and build an autonomous machine that was designed to autonomously navigate through a cornfield, detect and distinguish between weeds and corn plants, and automatically spray the corn plants with fertilizer while spraying the weeds with herbicide (both in real-time). The students modified a CanAm ATV to navigate autonomously (Figure 13). Weed detection was achieved using a ground-facing camera mounted on the front of the ATV feeding data to image processing applications. Modifications were made to a Setter plot sprayer that would allow individual nozzles to be activated to apply herbicide to be applied when weeds were detected. The students desired an automation interface that could be used to remotely supervise the autonomous sprayer during the agBOT Challenge.
CanAM ATV and setter plot sprayer used by a group of undergraduate University of Manitoba students to produce an autonomous sprayer for the agBOT challenge in 2019.
The autonomous agricultural sprayer is outfitted with four cameras (one of which is used for the weed and corn detection task) and a variety of sensors for the navigation and spraying tasks. The sensor input is processed by multiple onboard computers. One of these devices is dedicated to processing the visual input for the plant detection task, while the others process the remaining sensors and control actuators that allow the machine to move and spray the plants. The on-board computers communicate with each other through a middleware known as the Robot Operating System (ROS). The computers are also connected to a web server, through the internet, where they dump sensor data in real-time while the machine is running.
The automation interface for the autonomous agricultural sprayer was designed to display both sensor data and live video for a supervisor at a remote location. To enable remote supervision of the machine from anywhere in the world with internet connectivity, the interface is connected to the machine through a web server. The automation interface is shown in Figure 14.
The automation interface designed for an autonomous plot-sized agricultural sprayer.
From top to bottom, the interface is divided into three prominent sections: the toolbar, the video feeds, and the indicators (icons and graphical elements). The toolbar includes the start button and the emergency stop button. Since all other elements were designed for monitoring purposes, the start and stop buttons serve as the primary controls that the remote supervisor has over the machine. In the current iteration of the interface, the start button initiates the machine’s autonomous operations, while the stop button terminates autonomous operations. The notification bar keeps the user informed about the status of the machine, its sensors, and its environment. The text-based notifications are enhanced by a color-coded status indicator – green, yellow, and red – to indicate the corresponding severity.
Three video feeds were included in the automation interface following the recommendations made by [63]. The videos provide visual and auditory information, although at a lower fidelity than experienced when inside a tractor. The middle video provides a view ahead of the autonomous sprayer to show what is coming. The videos on the left and right sides are from rearward-facing cameras that show the left and right booms of the plot sprayer. These videos allow the remote supervisor to monitor both the machine and the spraying operation and take quick action in the case of an emergency.
Below the video feeds are the icons and graphical elements that display information regarding the state of the vehicle, sprayer, and the environment. The indicators were organized according to two main goals: i) monitoring the machine and ii) monitoring the sprayer, with the most important information placed towards the center of the display. Towards the far right of the interface is a group of indicators for monitoring the vehicle, including the vehicle speed, the engine speed, and a coverage map. In addition to providing up to level 3 situation awareness, the design of the speed indicators follows common design patterns for such indicators in most vehicles and is expected to fit the mental model of most users. The coverage map provides global situation awareness of the spraying operation.
The rest of the indicators, including the tank level, application rate and boom height, are related to the sprayer. The tank level indicates the amount of liquid that is currently in each tank, while the application rate provides information about how much liquid is being sprayed per area of the field from all the nozzles connected to the tank. While the application rate indicator supports only level 1 situation awareness, the tank level indicator was designed to support up to level 3 situation awareness by utilizing a digital display and color-coded value bar. Finally, towards the center of the display is an indicator, which was designed to provide an intuitive understanding of the state of the sprayer boom and the 6 nozzles attached to it. This indicator moves up and down in a similar fashion to the movement of the boom to indicate the height of the boom above the ground. The state of the nozzle is indicated by a green triangle (for an active nozzle) and a red square (for a blocked nozzle). Weather information is also included, which in addition to the information provided by other indicators, allows the remote supervisor to make judgments about the quality of the spraying operation, and project this judgment into the future (e.g., through available weather forecast) to take timely action.
Auditory information can be extremely useful to a human operator, even one with minimal experience, and can provide information about changes in parameters being independently monitored via sensors (rpm, load, etc.) [64]. There is opportunity to consider what role auditory information might play in the task of remotely supervising an AAM through an automation interface.
Based on anecdotal information, it was recognized that machinery operators are often able to detect existing or impending problems from the changes in sound produced by the mechanical components of the machine. Karimi [65] reported that the addition of auditory cues did not improve steering performance (in a simulated agricultural vehicle) perhaps because steering is a purely visual task, however, auditory cues did improve the monitoring task. Donmez [64] investigated the use of sonifications (continuous auditory alerts) during the control of unmanned aerial vehicles and found that visual information supported by sonifications yielded faster reaction times than visual information supported by discrete auditory signals. Though an autonomous controller may not use or interpret sound in the same way as a human does, it is important to evaluate its potential use in control applications given its value in monitoring non-autonomous machine operation.
Though auditory information alone may not provide sufficient information for automated control, it can provide qualitative information on changing parameters, or be an indicator of a change in state. This information can be used directly to trigger certain responses, or can be used in a training set to become a single indicator of a specific state, replacing several other parameters that may have to be combined to glean the same information. Capturing high quality auditory information is generally simple and inexpensive with modern technology and can be captured from multiple locations within a machine or system, making it a good option for a variety of applications.
Classification of sounds with machine learning is already prevalent in music. There are a number of applications available to consumers to classify songs to both organize music and provide recommendations based on previous listening history. These applications use various classification algorithms (Fourier Transform, Mel Frequency Cepstrum Coefficients, etc.) to provide this service. The existence of these classification services implies that machine sounds could be classified in a similar manner to determine the state of operation, unexpected variations in parameters (i.e., malfunctions), and more. In the case where humans are controlling a machine with assistance from automation, sonifications have been shown to be very effective at helping the human operator predict the future state of the machine, and therefore react accordingly [64]. Thus, automation via audio feedback has the potential to not only improve human-machine interaction in semi-autonomous applications, but also to provide input to prompt automated responses in fully autonomous applications.
Classification is a pattern recognition problem. If a classifier can be built to recognize specific characteristics of an input signal that identify, within a certain level of confidence, what grouping or ‘state’ that input belongs to [66], it can then be classified, and this information can be used to produce an appropriate response. These specific characteristics are referred to as ‘features’ and can be comprised of any distinctive measurement or structural component of the signal that can be extracted. Multiple features may be needed for classification, but analysis can be performed to determine which features in which combinations produce the quickest classification algorithm with the highest level of confidence.
Two features that have been explored in experimentation are the spectral centroid and formant (dominant) frequency. The spectral centroid is used to detect the ‘center of mass’ of the spectrum (distribution of values) representing the frequency [67]. Sub band spectral centroids have been used successfully in speech recognition applications [68] and so are a good starting point for machinery audio classification. The formant frequency of a signal represents the concentration of acoustic energy (peak), and has also been used successfully in speech recognition, as well as biomedical signal analysis and musical instrumentation analysis [69].
A classification experiment was performed using video collected from the rear of an S680 John Deere combine harvester near the straw chopper [70]. The video was recorded using a GoPro Hero Session during harvest of canola in a Manitoba field during the 2017 harvest season. From this video, audio clips were extracted corresponding to the operational sounds of the machine. The audio was sampled at a rate of 48 kHz with AAC compression and automatic gain control and converted to.wav file format for analysis. Sound samples underwent a Fourier transform, and then eight features were extracted from each segment for analysis, all based around frequency characteristics. Features in each segment were analyzed to both build and then test a feedforward, pattern recognition neural network. Samples were divided into those used for training (70%), validation (15%), and testing (15%), and three operating modes were selected for classification: 1) Engine running with no threshing, 2) Engine running and threshing engaged, and 3) Engine running, and threshing engaged at 80% capacity.
By varying parameters such as segment size, accuracies of 88–100% were obtained with larger segment sizes (over 2048 segments) producing a consistent classification accuracy of 99%. This sample size allowed for a total of 1970 samples which is sufficient to declare a high degree of confidence in the result. The results of this experiment show that a relatively basic model with audio as a sole input can successfully be used to classify machinery operating modes in real-time. These results are promising enough to justify further study to better understand how to optimally apply this technique in a practical application.
The current study focuses on identifying three broad classes of operation based on a single audio input. However, it is possible that there are a number of operational modes, or even specific events, scenarios, or changes in conditions that can be classified through auditory input. Further research is required to understand what other audio inputs (location and type of sound recording), or combination of audio inputs can be used for classification of a broader range of machinery parameters. It is also critical to understand how various conditions (wind, crop type, machine parameters, etc.) impact classification and what types of calibrations or modifications may be necessary to account for variation in operating conditions. The previous study focused on a single crop type with all recordings taken under identical operating conditions. A robust field prototype would need to account for changing environmental conditions in order to be reliable. It would also be beneficial to investigate other methods of recording and processing sound along with how this input is used to build the classifier.
The current study used manual inspection for feature extraction from raw audio, but it is likely that efficiencies could be gained through automated feature extraction or some level of sound processing to enhance various aspects of the audio that may be more useful for classification. There are many ways to build and train a classification system, and it is likely that a practical system could be optimized with further investigation. One follow-up study that was conducted with the same data explored the use of a 7-layer convolutional neural network (CNN) as a classifier [71]. Through this method, greater accuracies could be achieved when lower numbers of audio samples were used compared with a conventional neural network analysis. Using 5000 samples of audio segments resulted in an accuracy of 95% compared with 78% accuracy achieved with a neural network with the same samples.
It is likely that further investigation would provide insight into optimal audio sampling techniques and feature extraction and analysis to classify a greater variety of operating modes under more variable conditions.
The purpose of this chapter is to provide an overview of recent research that has been conducted to understand how to design an effective automation interface for the task of remotely supervising an autonomous agricultural machine (AAM). First of all, it has been assumed that the existence of an automation interface is essential because the owner of the AAM will always want to have some means of monitoring the status of the machine in the field and, in some instances, human input may be required to diagnose problems and/or to make management decisions. Secondly, it has been assumed that the automation interface needs to include real-time visual information showing the AAM within the field environment to complement telemetric data that is displayed using conventional means. Experimental data has supported the important role that is played by real-time visual information, and has provided insight on related issues such as i) where the cameras should be pointed to provide information that supports the supervisory task, ii) how the cameras should be positioned to yield useful look-ahead information, and iii) how to alert the supervisor of system problems, and iv) the latency associated with wireless transmission of live video. Early research results suggest that it may also be possible to use auditory information to provide additional information to the supervisor through the automation interface.
The authors would like to acknowledge the financial support from i) the Natural Sciences and Engineering Research Council of Canada (NSERC), ii) the Bell MTS Innovations in Agriculture Graduate Student Fund administered through the Faculty of Agricultural & Food Sciences, University of Manitoba, and iii) the Canadian Agricultural Partnership (CAP) administered by Ag Action Manitoba.
The authors declare no conflict of interest.
The research on fuel sprays of Internal Combustion Engines has been drawing attention for last century. As for Diesel Engines, spray evolution, which includes the jet breakup, fuel atomization, air entrainment, and mixture formation processes, is regarded as one of the determinants of engine performance and emission formation. Furthermore, nozzle geometry can directly affect the characteristics of the complicated internal flow patterns inside the nozzles, such as the cavitated turbulence. As a result, in order to improve the quality of the atomization and mixture homogeneity, researchers have spared no effort to investigate the internal flow [1, 2, 3] and spray behaviors [4, 5, 6], and many fundamental and classic theories were formed over the past decades. Originally, due to the simple structure and the easiness of applying diagnostic techniques and arranging instruments surrounding the nozzle and the spray plume, single-hole nozzle was widely used in fundamental research. Consequently, spray and combustion models, which are adopted in the numerical simulation study are usually developed from the experimental results of the single-hole nozzle spray.
On the other hand, it is known that multi-hole nozzles, which can emerge several spray plumes simultaneously, are generally applied in the engineering field of practical Diesel Engines. In this case, the orifices are normally aligned around the sac symmetrically and located off-axis to the nozzle axis. As a result, the optical access to the complex configuration and the mutual interference between the spray plumes create a difficulty for scholars to explore the internal flow and spray characteristics of multi-hole nozzles.
In recent years, there is a trend that considerable efforts have been exerted to conduct an experimental and computational study about the internal flow and sprays of the multi-hole nozzles. Different kinds of verisimilar scaled-up or real-size multi-hole nozzle models were designed to reveal the flow pattern properties inside the nozzles and the initial emerging spray dynamics [7, 8, 9, 10, 11, 12]. The application of the synchrotron x-ray sources with high energy pulses has also been extended to the study of fuel sprays during the last decade [13, 14]. At the same time, a series of studies using the three-dimensional computational fluid dynamics simulations were also conducted to link the experimental results to the numerical calculation [15, 16, 17, 18]. Based on all the approaches mentioned above, the vortex flow and string-type cavitation inside the sac, the counter-rotating vortices, film-type and string-type cavitation inside the hole volume, the needle lateral oscillation effect, and the unstable spray behaviors were found in succession.
Moreover, smaller hole diameter and more holes, accompanied by higher injection pressure are becoming prevalent in dealing with the strict emission regulations and economic demand [19, 20], because it is proven to be able to generate better fuel atomization and more homogeneous fuel/air mixture [21, 22]. In the conventional study, hole diameter is usually larger than 0.10 mm. Even though a few researchers applied the micro-hole nozzle to conduct the fundamental experimental study about the mixture formation and combustion processes, mainly single-hole nozzles were used in their experiments. As a result, the limited nozzle types and experimental conditions hindered a more satisfactory situation in understanding the flow dynamics of the real multi-hole nozzles under practical operating conditions thoroughly. There is rare information about the spray properties of multi-hole nozzles with micro orifices in the current archives, and it is worthwhile to carry out a monographic study on this issue.
A comparison between the spray properties of the nozzles with different hole diameter is made in the present chapter to provide deep insights into the multi-hole nozzles sprays, which are formed in the real scenario of Diesel Engines, and sufficient analyses about the effect of the hole diameter were conducted systematically as well. In addition, the CFD simulation results for these different nozzle configurations were also presented in this chapter with the aim of correlating the observed spray behaviors to the internal flow properties inside the nozzles.
High-speed video camera observations based on the Mie scattering were made for the sprays injected by the multi-hole injectors, and the specific experimental apparatus is shown in Figure 1. Figure 1(a) presents the global experimental arrangement, including the high-pressure chamber, fuel injection system, and optical system. A common rail injection system could generate the injection pressure up to 220 MPa, and high-pressure constant volume vessels with optically accessible quartz windows were employed to create the high-pressure ambient environment of Diesel fuel injection. A delay pulse generator (Stanford Inc., DG535) and an electronic control unit (ECU) were applied to control the image timing, injection time, and injection quantity. The optical path layout is shown in Figure 1(a). A xenon lamp (USHIO Corp., SX-UID501XAMQ) and two high-speed video cameras (Nac MEMRECAM HX-3, Photron FASTCAM-APX RS) were used to record the fuel injection processes.
Experimental apparatus.
When it comes to the installation of the multi-hole injectors, the detailed information about the specially designed chamber head is shown in Figure 1(b). It is well known that the observation of the multi-hole nozzle sprays is difficult due to the conical structure formed by the plumes. In this study, the multi-hole injector was installed into this specialized chamber cover obliquely, as shown in Figure 1(c), to prevent spray interference. An appropriate angle between the axis of the multi-hole nozzle and the horizontal plane was designed to maintain that one of the spray plumes could be observed as vertically as possible.
The experimental apparatus for the injection rate measurement are presented in Figure 2.
Schematic of injection rate measurement experiment apparatus.
In this study, the Bocsh rate of injection meter [23] was applied. The experimental conditions corresponded to the spray observation experiments, which will be introduced in the upcoming sections. The timing of the start of injection was determined by comparing the injection pause signal with the injection rate curve signal recorded in the oscilloscope.
Figure 3 shows the schematics of the nozzles applied in this study, the two multi-hole nozzles (10 holes) have the same configuration except for the hole diameter (D = 0.10 and 0.07 mm). The experimental conditions, which are shown in detail in Table 1, were determined in consideration of the real operation conditions of small Diesel engines.
Schematic of different nozzles applied in experiments.
Injection Conditions | |
Fuel (Diesel JIS#2) | Density (20°C,1 atm): ∼830 kg/m3 Boiling Point (1 atm): ∼273°C Kinetic Viscosity (20°C,1 atm): ∼3.86 (10−6) m2/s Cetane Index: ≥45 Sulfur: 10 ppm |
Injector | Multi-Hole Nozzle |
Injection Quantity | 2.0 |
Rail Pressure | 120 |
Hole Diameter | 0.07 0.10* |
Injection Duration: △ | 1.26 0.84* |
Ambient Conditions | |
Ambient Gas | Air |
Ambient Pressure | 1.5 |
Ambient Temperature | 300 |
Ambient Density | 17.4 |
High-Speed Video Camera Conditions | |
Recording Rate (fps) | 10,000 100,000 |
Exposing Time (s) | 1/10000 1/100000 |
Resolution | 512 × 512,384 × 200 |
Experimental conditions.
Baseline Condition.
The setting of cameras is also presented in Table 1, and the experimental measurement was conducted at least 10 times for each condition. The test fuel was the JIS #2 diesel. The injection quantity was 2 mm3/hole. In order to keep the ambient gas density similar to that of the combustion conditions, for fundamental spray research of non-evaporation conditions, the ambient temperature and pressure were 300 K and 1.5 MPa, respectively.
The typical image processing processes and the definitions of spray properties in the current study are shown in Figure 4. The same processing method was applied to the spray images of different nozzles. The spray image taken under the baseline condition is shown here as an example. The central spray of each frame was characterized as the spray tip penetration (i.e., the maximum penetration distance of the spray,
Image processing for spray properties measurement.
The spray images were processed to calculate their properties by the following steps. First, each frame was converted to an effective image by subtracting the background images taken without the spray injection. After that, the spray edge could be detected by using the binarization image, which is converted by a threshold algorithm. The colored edges of different recording times show that the spray contour and the temporal variations can be well captured spatially. The spray tip penetration of the central spray plume is determined by scanning the contours from the corresponding orifice point. In this way, the morphological algorithm could also be used to extract the parameters of spray cone angle and the spray angle. The near-field spray properties around the nozzle exit region were also captured by the same method introduced above.
One of the most important factors that can introduce uncertainty into the measurement results is the selection of the threshold. Compared with the single-hole nozzle, the hole-to-hole variation and the cycle-to-cycle variation of multi-hole nozzle sprays cause the image processing to be more sensitive to the algorithm. Hence, the assessment of the threshold value is necessary for the current study. Principles that are suitable for the threshold selection are summarized as (1) The threshold should ensure that the spray profiles are as similar to the raw images as possible; (2) The threshold should remove the background noises in the images; (3) The error should be within the cycle-to-cycle injection variations. As a result, the intensity threshold of 5 (the maximum intensity: 255) was selected in this study after a series of statistics.
In the current study, to aid the interpretation of the experimental results, the influences of the micro-hole diameter on the internal flow and cavitation characteristics have been numerically investigated by the commercial CFD Code FIRE Version 2017 (AVL). Figure 5 shows the computational meshes of the multi-hole nozzle with ten holes, and only one-tenth of the entire volumetric domain was selected considering the geometric periodicity, symmetry, and calculation timing.
Computational meshes.
The specific settings for this computation have been listed in Table 2. The same setting was applied to the two different nozzle configurations to make comparisons between the internal flow patterns. The Reynolds Averaged Navier–Stokes Simulation (RANS) model and a four-equation
Item | Classification | Setting/Value | |
---|---|---|---|
Model selection and Initial values | Turbulence model | ||
Turbulence energy (m2/s2) | 0.1 | ||
Turbulence length scale (m) | 0.000001 | ||
Cavitation model | Linear cavitation model | ||
Cavitation bubble density number | 1.5 × 1018 | ||
Diesel saturated vapor pressure (Pa) | 892 | ||
Initial boundary | Inlet boundary | Injection Pressure (MPa) | 120 |
Export boundary | Ambient Pressure (MPa) | 1.5 | |
Mesh information | Needle-holder gap (mm) | 0.002 | |
The minimum cell size in the hole region (mm) | 4.413 × 10−3 | ||
The maximum grid number (cells) | 132,796 |
Computational setting.
Validation was conducted by taking the experimental results published by Blessing et al. [25] as the criteria, in which the characteristics of nozzles and boundary conditions covered many features of the current study, and the turbulence and cavitation models were proved reasonable before further computational studies. Moreover, the effect of mesh size was also taken into the consideration by making comparison between the different computational results from the meshes with different mesh sizes (7.769, 4.413, and 2.896 μm). During all the verification processes, it was proven that the distribution and occurrence of the cavitation could be predicted accurately relatively by this simulation.
Furthermore, aiming to make comparisons, the same transient needle-lift curve, as shown in Figure 6, measured from a similar type of multi-hole injector was applied to the two nozzle meshes.
Needle lift curve.
Figure 7 shows the injection rate results of the two different nozzles under the conditions of Qinj = 2.0 mm3/hole. These two curves present apparent distinctions. It can be seen that the micro-hole conspicuously changes the previous regularity of the fuel injection. The injection rate of the micro-hole (0.07 mm) nozzle is much lower than that of the nozzle with 0.10 mm hole diameter when maintaining the same injection quantity per hole. While the injection duration of the micro-hole nozzle is prolonged a lot. Moreover, the initial stage of the injection duration attracts attention to analysis in detail, which is emphasized and enlarged in Figure 7. The injection rate of the nozzle with a micro-orifice is a little higher than that of the other one with larger orifices in the initial stage of injection. In fact, it is known that the fuel injection velocity and the effective flow area alter the injection rate simultaneously. Furthermore, the fuel injection velocity mainly depends on the upstream pressure in the sac, and the effective flow area is affected by the hole numbers, hole diameter, and the discharge coefficient. The theoretical flow area of the micro-hole nozzle, whose diameter is 0.07 mm, is much smaller than that of the normal one (0.10 mm), and its sac pressure discharge rate should also be much lower than that of the nozzle with normal holes. As a result, all the phenomena described above reveal that the effect of micro-holes plays entirely different roles in the injection rate at different injection stages. Specifically, the higher sac pressure is mainly caused by the relatively lower sac pressure discharge rate at the initial stage of injection, and the injection rate of this stage is dominated by the consequent higher flow velocity inside the micro-holes. However, at the middle and post-stage injection, the relatively larger effective flow area and the consequent higher mass flow rate inside the nozzle with 0.10 mm hole diameter mainly dominate the injection rate of the nozzles.
The injection rate of different injectors.
Typical false-colored and temporal spray images of different nozzles are shown in Figure 8. According to the theoretical foundation of Mie scattering, the scattered light intensity is a symbolic characteristic of the droplet size and fuel concentration. The spray contours can help elucidate the effects of ambient gas entrainment and interactions between spray plumes [26].
False-colored spray images of different injectors.
As analyzed before, even the total injection mass per hole is held constant, the fuel injection quantity of the 0.10 mm hole is larger than that from the micro-hole at the same timing ASOI. Based on the Mie-scattering principle, the intensity is in proportion to the droplet size and concentration. Hence, the global intensity of the central sprays of the multi-hole nozzle with normal hole diameter, which are shown in Figure 8(a), is much higher than that of the micro one, particularly at the beginning stage of fuel injection. The high-intensity area can even extend to the downstream region of the central spray. It follows that the fuel concentration of the micro-hole condition is leaner, and the atomization effect is better [27].
As for the spray morphology, the edges of the spray of 0.10 mm holes are irregular compared with the micro-hole one, and the hole spray plumes are flanked by evident wavelike contours. In the case of micro holes, the edges of the spray upstream regions are neater and more orderly than those of nozzles with larger hole diameters.
Moreover, central sprays show a large eccentricity in the spray tip around the end of injection (0.8 and 1.0 ms ASOI) under the larger-hole nozzle condition, and the adjacent two plumes also present asymmetrical morphology. The low-pressure regime between the sprays generated by the air entrainment can enhance the sprawling diffusion of the multi-hole nozzle sprays. The Coanda effect [28] plays significant role in these phenomena. However, under the 0.07 mm hole diameter condition, the sprays have well symmetry. Therefore, it is safe to say that decreasing the hole diameter can supposedly reduce the uncontrollability and instability of the sprays emerging from multi-hole nozzles. A more specific investigation and discussion about this phenomenon will be introduced in the upcoming sections.
It is known that the spray propagation distance is governed by the upstream pressure and the ambient conditions. The calculated sac pressure and the measured spray tip penetration variation of different nozzles is shown in Figure 9. The Bernoulli equation is used to calculate the corresponding averaged sac pressure variations based on the injection rate measurement results in Figure 7. The equation is written as below, where
Calculated sac pressure and spray pemetration variation of different injectors.
As for
However, it is still difficult to get accurate quantitative results from the internal flow of a practical Diesel multi-hole nozzle, which is usually high pressure, high velocity, turbulent, and micro size. The theory developed under the quasi-steady condition was attempted to be expanded to the transient condition in the current study, and a comparative analysis was made between the different nozzles qualitatively to provide a reference for explaining different spray behaviors.
Throughout the injection duration, the pressure in the sac of the nozzle with micro-holes is all higher than that in the nozzle with normal holes. The different effective flow area, caused by the different hole diameter plays a significant role in this issue. As for the corresponding penetration result, it is in accordance with the injection rate variations analyzed previously. As the color arrows emphasize, the micro-hole nozzle spray tip penetration is longer at the initial stage. As the time elapses, the penetration of 0.10 mm hole nozzle passes over the micro-hole nozzle spray tip penetration. In different injection stages, it is the different factors (effective flow area or sac pressure) that dominate the spray propagation of nozzles with different holes. In the calibration processes of combustion system of Diesel engines, the fuel injection quantity, injection timing, and injection times/cycle are usually adjusted as the fuel supply strategy. The diffusion and deceleration of the multi-hole nozzle spray are usually associated with the transfer of the spray momentum to the turbulence energy [31]. Consequently, when concerning the optimization of the Diesel engine preference, effects of the micro-hole on fuel injection of multi-hole nozzles should be given attention emphatically.
Figure 10 shows the temporal variation of the spray angle and spray cone angle. It is evident that the spray angle is wider under the 0.1 mm hole condition. The maximum deviation appears at 0.1 ms ASOI, up to 11°. Furthermore, it seems that the micro-hole can exert more influence on the spray angle reduction compared with that on the spray tip penetration. On the other hand, different from the spray tip penetration results, no overlap happens among the two spray angle curves of nozzles with different holes. The simulation results in the upcoming section can be used to explain this phenomenon in depth.
Spray angle and cone angle variation of different injectors.
The difference between the spray cone angles of the nozzles with different holes is also evident. It should be noted that the penetration of the larger-hole nozzle is shorter than 100 times the hole diameter at 0.1 ms ASOI; hence, only the spray angle can be measured, as shown in the figure. Because the position (10 mm) of 100 times of hole diameter is around the spray tip area of the 0.10 mm hole, it results in a small value of spray cone angle, and the spray cone angle difference between the two nozzles is not too much at 0.2 ms ASOI. After that, when the spray penetrates long enough, attributed to the more completed internal flow inside the larger holes [32], the 0.10 mm hole nozzle spray cone angle increases a great deal suddenly.
When it comes to the micro-hole condition, the value of the spray cone angle is much smaller and the variation is steadier. This can be explained like that since the cavitation collapse and turbulence flow inside different nozzles are two of the major mechanisms of the spray primary break-up [31, 33], the fuel jet enters the chamber with a less cavitation level, reduced mass flow rate, momentum, and less turbulence caused by the increased ratio of nozzle hole length to diameter, which can result in the narrower spray cone angle.
According to the above discussion, because of the unique geometric structure, the micro-hole nozzle has a lower injection rate, higher sac pressure, and wider spray angle and spray cone angle compared to those of the nozzle with normal holes. Combing these phenomena with the interlaced relationship between the trends of the spray tip penetration of different nozzles, it is concluded that the effect of the micro-hole on different spray properties is discrepant.
In order to investigate the spray behaviors near the nozzle tip region in detail, high-speed imaging of 100,000 fps was applied to take a close-up view of this regime. The Higher spatial and temporal resolutions allowed a more detailed observation of the very emergence of the fuel from the nozzle orifice. Figure 11 shows the close-up gradient spray images of different nozzles, respectively.
Close-up view of sprays injected from different injectors.
According to the images of typical timings, the normal-hole nozzle sprays pulsate out from the nozzle tip to the radial direction, and the edges of them fluctuate seriously. The perturbation of the spray is marked and emphasized by different color arrows in the figure. On the other hand, since the injection duration is longer under the micro orifices condition when maintaining the same injection quantity, the selection for the typical timing of the images is a little different. With the same results under the imaging rate of 10,000 fps, the spray illumination intensity becomes weaker under the micro-hole condition. Of interest is that the spray pulsating phenomenon almost disappears, and the profiles of the sprays become much neater and more stable.
The angle, determined by 10 times the hole diameter away from the nozzle tip, is defined as the spray dispersion angle. The average spray dispersion angle and the single-shot results are shown in Figure 12. Generally, the spray dispersion angle under the hole diameter of 0.10 mm condition is much wider than that of the micro-hole one. As for the single-shot result, corresponding to the pulsating phenomenon of the near-field spray, as the capital letters and color arrows indicate in the figures, the spray dispersion angle curve waves and fluctuates strongly, especially in the initial stage of the injection (0.1–0.25 ms ASOI). The integrated speculations and reasonable explanations for this phenomenon can be excavated by linking the previous results [34] and the current study.
Close-up spray behaviors injected from different injectors.
Different from the single-hole nozzle, due to the off-axis arrangement of the orifices, there is usually vortex flow inside the sac of multi-hole nozzles, especially under the condition of low needle lift. Moreover, with the needle moving, the location variation of the unstable vortex core results in the unstable spiraling flow pattern emerging through the hole with the vortex. During these processes, there is usually the generation of string-type cavitation in the sac and hole flow field. All the properties, only belonging to the internal flow of multi-hole nozzles, play significant roles in the phenomenon of near filed spray pulsating [7, 35]. When the hole diameter is reduced to 0.07 mm, the fluctuation of the spray dispersion angle curve decreases dramatically, and the angle becomes much narrower than that of the normal hole diameter condition. The reduced flow transverse can suppress the cavitation and vortex level under the micro-hole condition, and it is also impeded the fuel to enter into the micro-holes from the sac volume of the multi-hole nozzle. These could be used to explain the reason why the micro-hole multi-hole nozzle has a relatively narrower spray width and steady spray morphology.
The computational study is used to illustrate the different internal flow characteristics between the two nozzles. In this transient simulation analysis, according to the needle lift curve applied in the study, three typical timings (0.1, 0.318, and 0.5 ms ASOI) are selected to represent the initial, full needle lift, and post stages of the injection, respectively.
Figure 13 shows the pressure variation inside different nozzles at the typical injection stages. The time-resolved averaged sac pressure variation of the two nozzles is also plotted in this figure. Attention should be paid to the nozzle with micro holes. Its sac and hole pressures are all higher than those of the one with larger orifices throughout the injection duration, which coincides with the experimental analysis shown in Figure 9. The lower theoretical effective flow area and sac pressure discharge rate of the micro-hole nozzle are mainly attributed to this issue.
Pressure distribution inside the nozzles at the typical timings during the injection duration.
The temporal velocity variation on the inlet and outlet sections of the two nozzles is shown in Figure 14. Four monitoring points (P1, P2, P3, and P4) were set along the horizontal diameter line (Line A-B) symmetrically.
Temporal variation of fuel velocity at the monitoring points on the hole sections.
The injection velocity on the outlet of the micro-hole nozzle is higher than that of the normal-hole one, especially in the initial stage of injection, which agrees with the discussion about the injection rate and sprays penetration results in the experiments. Furthermore, no matter on the inlet or on the outlet sections, the flow velocity fluctuation of the nozzle with larger orifices is the most intense one, which corresponds with the spray pulsating instance. Moreover, a reverse variation tendency appears at the symmetrical monitoring points with the needle moving up, which implies that there is a spiral and asymmetrical flow pattern inside the hole. However, under the micro-hole diameter conditions, the amplitude of the velocity wave decreases dramatically, which coincides with the neater spray profiles and the reduced spray pulsating phenomenon discussed in the experimental results.
The streamlines inside different holes, which are shown in Figure 15, can interpret the instance analyzed in the optical experiments. There are much more complicated streamlines with stronger curvatures and counter-rotating flow inside the hole volume under the larger orifice condition. The vorticity distributions results along the orthogonal orifice lines also show higher stream-wise vorticity under 0.1 mm hole diameter conditions. This spiral flow is also observed by Gavaises and Andriotis [11], Lai et al. [32], and Hayashi et al. [35]. It has been proven that there are close correlations between this swirling motion and the wider spray cone angle. However, when attention is paid to the nozzles with micro-orifices, the vorticity decreases, and the streamline is stable and smooth relatively. This agrees with the reduced fluctuation of its spray behaviors observed in the experiments.
Streamline and streamwise vorticity distribution along the horizontal and vertical diameter lines on the outlets of different multi-hole nozzles at full needle lift timing.
As shown in Figure 16, the velocity resolution of fuel jet injection on the hole exit section of the multi-hole nozzle is conducted, and
Distribution of the ratio of velocity components (
The temporal variations of the liquid volume fraction are shown in Figure 17. Affected by its special configuration, the cavitation distribution in the multi-hole nozzle is asymmetrical. Under the low need lift condition, when the injection starts, the film-type cavitation generates at a lower field of the hole inlet because of the aspects changing the flow direction. With the needle lifting up, the cavitation moves to the upper flow field and gradually develops into the string-type cavitation, which is mainly affected by the spiral and streamwise counter-rotating vortices flow structure inside the hole. Finally, the string-type cavitation can even reach the central area of the exit section, where intense mass and momentum transfer happens in the downstream region. The issues discussed above are all conducive to the wider spray cone angle [36]. However, under the micro-hole diameter condition, the cavitation intensity is much smaller, which is attributed to the higher pressure and smoother flow structure inside the hole volume of the nozzle.
Temporal variation of liquid volume fraction distribution inside different nozzle holes.
The turbulence intensity increases with the enhancement of the dissipation of the spray momentum transferring to the turbulence energy, resulting in more intense liquid/gas interactions, lower spray velocity, and wider spray diffusion [37]. Figure 18 shows the turbulence kinetic energy (TKE) distribution along the horizontal hole diameter line of different nozzles at the typical timing. The gradient of this value between the hole boundary locations and the hole central area of different nozzles is all prominent during the injection durations. However, they present different relations in the three injection stages. Initially, affected by the higher pressure increasing rate in the sac and the consequent higher velocity in the hole, the TKE value in the boundary location of the micro-hole is a little higher than that of the normal hole, but it is lower in the central area of the hole. After that, the TKE value under the normal-hole diameter condition increases a lot, and maintains a high level. However, the TKE value under the micro-hole diameter condition does not increase so much in the following injection stages, which indicates that the spray behaviors of the micro-hole nozzle would be more stable, resulting in the narrower spray angle and cone angle observed in the experiments.
Distribution of turbulence kinetic energy along the horizontal diameter of the exit of different nozzles at typical timings.
According to the results of the internal flow of the different nozzles, except for the aerodynamic factors, it is the hydrodynamic factors and the unique properties of the internal flow in different nozzles that dominate their spray behaviors. The different characteristics of the flow patterns inside different nozzles mainly contribute to the deviation between their spray properties.
In the current work, the differences in the spray morphology between the two realistic multi-hole diesel nozzles under different hole diameter conditions were analyzed by the high-speed video observation method during the transient injection processes. The relationship between the internal flow, cavitation variation, and spray behaviors was investigated by the numerical simulations. The main conclusions are summarized as follows:
Different from normal single-hole nozzles, which are usually adopted in fundamental fuel injection research, unique and unstable spray behaviors of the multi-hole nozzles are observed in the experiments. The pulsating spray instance, and the wide spray angle and spray cone angle of multi-hole nozzles imply that the spray development can be affected greatly by its complex nozzle configurations. Sprays from the multi-hole nozzles are mainly dominated by the sac pressure, vortex flow in the sac, complicated spiral, and turbulent flow structure inside the hole except for the spray to spray interaction. The injection rate and spray tip penetration have a strong relationship with the pressure-increasing rate in the sac and the effective flow area of the nozzles.
The numerical simulation results about the internal flow of multi-hole nozzles with different hole diameters show that the increasing rate of sac pressure is faster inside micro-hole nozzles. Compared with the micro-hole, larger holes of the multi-hole nozzle can enhance the generation of dense swirling motion, where the string-type cavitation usually forms. Consequently, stronger vorticity, higher turbulence, and larger velocity components at hole exits are produced by these complex flow patterns, and the corresponding enhanced interfacial instability and wider spray propagation are observed in the optical experiments.
Influence of hole diameter on the internal flow, injection processes, and spray development of multi-hole nozzles is prominent. The reduced effective flow area suppresses the cavitation and turbulence flow, alters the injection rate, and prolongs the injection duration. Moreover, the effect of hole diameter plays different roles in the spray properties (penetration, spray angle, and cone angle) of the multi-hole nozzles. The implications of these results have practical significance when considering the diesel fuel spray trajectory within the combustion chamber.
This research was supported by the Basic Research Operation Program of Dalian University of Technology (grant number 82232029).
The authors would like to thank the Mazda Corporation for technical support and AVL-Japan for providing the numerical software.
IntechOpen celebrates Open Access academic research of women scientists: Call Opens on February 11, 2018 and closes on March 8th, 2018.
",metaTitle:'Call for Applications: "IntechOpen Women in Science 2018" Book Collection',metaDescription:"IntechOpen celebrates Open Access academic research of women scientists: Call Opens on February 11, 2018 and closes on March 8th, 2018.",metaKeywords:null,canonicalURL:"/page/women-in-science-book-collection-2018/",contentRaw:'[{"type":"htmlEditorComponent","content":"On February 9th, 2018, which marks the official celebration of UNESCO’s International Day of Women and Girls in Science, we have announced we are seeking contributors for the upcoming “IntechOpen Women in Science 2018” Book Collection. The program aims to support women scientists worldwide whose academic needs include quality assurance, peer-review, fast publishing, collaboration among complementary authors, immediate exposure, and post-publishing citations reporting.
\\n\\nAPPLYING FOR THE “INTECHOPEN WOMEN IN SCIENCE 2018” OPEN ACCESS BOOK COLLECTION
\\n\\nWomen scientists can apply for one book topic, either as an editor or with co-editors, for a publication of an OA book in any of the scientific categories that will be evaluated by The Women in Science Book Collection Committee, led by IntechOpen’s Editorial Board. Submitted proposals will be sent to designated members of the IntechOpen Editorial Advisory Board who will evaluate proposals based on the following parameters: the proposal’s originality, the topic’s relation to recent trends in the corresponding scientific field, and significance to the scientific community.
\\n\\nThe submissions are now closed. All applicants will be notified on the results in due time. Thank you for participating!
\\n"}]'},components:[{type:"htmlEditorComponent",content:"On February 9th, 2018, which marks the official celebration of UNESCO’s International Day of Women and Girls in Science, we have announced we are seeking contributors for the upcoming “IntechOpen Women in Science 2018” Book Collection. The program aims to support women scientists worldwide whose academic needs include quality assurance, peer-review, fast publishing, collaboration among complementary authors, immediate exposure, and post-publishing citations reporting.
\n\nAPPLYING FOR THE “INTECHOPEN WOMEN IN SCIENCE 2018” OPEN ACCESS BOOK COLLECTION
\n\nWomen scientists can apply for one book topic, either as an editor or with co-editors, for a publication of an OA book in any of the scientific categories that will be evaluated by The Women in Science Book Collection Committee, led by IntechOpen’s Editorial Board. Submitted proposals will be sent to designated members of the IntechOpen Editorial Advisory Board who will evaluate proposals based on the following parameters: the proposal’s originality, the topic’s relation to recent trends in the corresponding scientific field, and significance to the scientific community.
\n\nThe submissions are now closed. All applicants will be notified on the results in due time. Thank you for participating!
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On the other hand, there are non-wood fibers such as flax, hemp, jute, kenaf, cotton, sisal, and abaca with properties as good as or much better than softwood materials.",book:{id:"6245",slug:"pulp-and-paper-processing",title:"Pulp and Paper Processing",fullTitle:"Pulp and Paper Processing"},signatures:"Zhong Liu, Huimei Wang and Lanfeng Hui",authors:[{id:"218005",title:"Prof.",name:"Zhong",middleName:null,surname:"Liu",slug:"zhong-liu",fullName:"Zhong Liu"},{id:"220665",title:"Prof.",name:"Lanfeng",middleName:null,surname:"Hui",slug:"lanfeng-hui",fullName:"Lanfeng Hui"},{id:"220666",title:"Dr.",name:"Huimei",middleName:null,surname:"Wang",slug:"huimei-wang",fullName:"Huimei Wang"}]},{id:"62258",doi:"10.5772/intechopen.79015",title:"Different Solvents for Organosolv Pulping",slug:"different-solvents-for-organosolv-pulping",totalDownloads:1648,totalCrossrefCites:10,totalDimensionsCites:18,abstract:"Organosolv pulping is a two-stage process involving hydrolysis (decomposition of wood by use of a catalyst) and removal of lignin with an organic solvent (usually a mixture of alcohol and water). The main disadvantage of using an alcohol is its low boiling point, which requires operating at a high pressure and hence using special equipment that is expensive to purchase and operate. One solution to this problem is using alternative organic solvents that afford operation at pressure levels similar to those of classic pulping processes (e.g., the Kraft process). This chapter provides a comprehensive literature review on the organosolv-based production of cellulose pulp by using alternative solvents such as glycols, phenols, esters, organic acids, acetone and amines.",book:{id:"6245",slug:"pulp-and-paper-processing",title:"Pulp and Paper Processing",fullTitle:"Pulp and Paper Processing"},signatures:"Alejandro Rodríguez, Eduardo Espinosa, Juan Domínguez-Robles,\nRafael Sánchez, Isabel Bascón and Antonio Rosal",authors:[{id:"218209",title:"Dr.",name:"Alejandro",middleName:null,surname:"Rodríguez",slug:"alejandro-rodriguez",fullName:"Alejandro Rodríguez"},{id:"221719",title:"Mr.",name:"Eduardo",middleName:null,surname:"Espinosa",slug:"eduardo-espinosa",fullName:"Eduardo Espinosa"},{id:"221720",title:"Dr.",name:"Juan",middleName:null,surname:"Domínguez-Robles",slug:"juan-dominguez-robles",fullName:"Juan Domínguez-Robles"},{id:"221722",title:"Dr.",name:"Rafael",middleName:null,surname:"Sánchez",slug:"rafael-sanchez",fullName:"Rafael Sánchez"},{id:"221723",title:"Mrs.",name:"Isabeñ",middleName:null,surname:"Bascón",slug:"isaben-bascon",fullName:"Isabeñ Bascón"},{id:"221724",title:"Dr.",name:"Antonio",middleName:null,surname:"Rosal",slug:"antonio-rosal",fullName:"Antonio Rosal"}]},{id:"63362",doi:"10.5772/intechopen.79749",title:"Pulping of Non-Woody Biomass",slug:"pulping-of-non-woody-biomass",totalDownloads:2015,totalCrossrefCites:9,totalDimensionsCites:14,abstract:"The use of trees for paper production has contributed to the problem of deforestation with radical negative impact on the environment thereby causing an imbalance in the ecosystem. An increase in the demand and consumption of paper has also induced depletion of woods resources for paper production, thus resulting in limited availability of the raw materials. This work examined the use of non-woody biomasses as alternative raw materials, which are accessible and convertible into pulp and paper of the same quality as those obtained from wood.",book:{id:"6245",slug:"pulp-and-paper-processing",title:"Pulp and Paper Processing",fullTitle:"Pulp and Paper Processing"},signatures:"Mayowa Akeem Azeez",authors:[{id:"197473",title:"Dr.",name:"Mayowa Akeem",middleName:null,surname:"Azeez",slug:"mayowa-akeem-azeez",fullName:"Mayowa Akeem Azeez"}]},{id:"51034",doi:"10.5772/63744",title:"Evaporative Drying of Low-Rank Coal",slug:"evaporative-drying-of-low-rank-coal",totalDownloads:2263,totalCrossrefCites:11,totalDimensionsCites:14,abstract:"Low-rank coals including the brown and the subbituminous coals are commonly known to contain high moisture content (up to 65%, wet basis), which limits their utilization around the world in spite of their low cost. Today, the most of the drying technologies are based on the evaporation of the water from the moist product. In this chapter, the most effective parameters on the evaporative coal-drying process are investigated with the data in the recent literature. The effective parameters are evaluated in three categories as follows: (1) the parameters about the drying media (the type of the media, the temperature, the pressure, the velocity and the relative humidity), (2) the coal parameters (the type of the coal and the size) and (3) the drying method.",book:{id:"5266",slug:"sustainable-drying-technologies",title:"Sustainable Drying Technologies",fullTitle:"Sustainable Drying Technologies"},signatures:"Saban Pusat, Mustafa Tahir Akkoyunlu and Hasan Hüseyin Erdem",authors:[{id:"181675",title:"Dr.",name:"Saban",middleName:null,surname:"Pusat",slug:"saban-pusat",fullName:"Saban Pusat"},{id:"181676",title:"MSc.",name:"Mustafa Tahir",middleName:null,surname:"Akkoyunlu",slug:"mustafa-tahir-akkoyunlu",fullName:"Mustafa Tahir Akkoyunlu"},{id:"181677",title:"Dr.",name:"Hasan Hüseyin",middleName:null,surname:"Erdem",slug:"hasan-huseyin-erdem",fullName:"Hasan Hüseyin Erdem"}]},{id:"51561",doi:"10.5772/64191",title:"Sustainable Drying Technologies for the Development of Functional Foods and Preservation of Bioactive Compounds",slug:"sustainable-drying-technologies-for-the-development-of-functional-foods-and-preservation-of-bioactiv",totalDownloads:2419,totalCrossrefCites:8,totalDimensionsCites:11,abstract:"Nowadays, the sustainability of a product, a process or a system is assessed according to three dimensions: environmental, social and economic. Sustainability challenges occur at all stages in the food system from production through processing, distribution and retailing to consumption and waste disposal. The promotion of organic and local food is not the only way to reach the sustainability. There is other possibility that implies to continue the production hegemony. Increasing research is being focused on the development of healthy, quality and safety food products adapted to consumer’s needs and more environment-friendly processes, that is, processes consuming energy more efficiently, generating less waste and emitting less greenhouse effect gases. Drying technology is applied in the food industry not only for preservation but also to manufacture foods with certain characteristics. Drying technology operations need to be precisely controlled and optimized in order to produce a good-quality product with the highest level of nutrient retention and flavor together with microbial safety. This chapter contains detailed information about some measurements taken by the food industry to ensure the supply of bioactive nutrients to as many individuals as possible, assuring the global sustainability. More specifically, the contribution of some drying techniques employed in the development of functional foods to increase the sustainability of the feeding process is discussed.",book:{id:"5266",slug:"sustainable-drying-technologies",title:"Sustainable Drying Technologies",fullTitle:"Sustainable Drying Technologies"},signatures:"Ester Betoret, Laura Calabuig-Jiménez, Cristina Barrera and Marco\nDalla Rosa",authors:[{id:"182749",title:"Ph.D.",name:"Ester",middleName:null,surname:"Betoret",slug:"ester-betoret",fullName:"Ester Betoret"},{id:"190053",title:"MSc.",name:"Laura",middleName:null,surname:"Calabuig-Jiménez",slug:"laura-calabuig-jimenez",fullName:"Laura Calabuig-Jiménez"},{id:"190056",title:"Dr.",name:"Cristina",middleName:null,surname:"Barrera",slug:"cristina-barrera",fullName:"Cristina Barrera"},{id:"190058",title:"Dr.",name:"Marco",middleName:null,surname:"Dalla Rosa",slug:"marco-dalla-rosa",fullName:"Marco Dalla Rosa"}]}],mostDownloadedChaptersLast30Days:[{id:"62223",title:"Pulping and Papermaking of Non-Wood Fibers",slug:"pulping-and-papermaking-of-non-wood-fibers",totalDownloads:3960,totalCrossrefCites:23,totalDimensionsCites:40,abstract:"In general, the main raw materials of pulp and papermaking industry can be classified into three categories: wood, non-wood, and non-plant (mainly wastepaper), of which non-wood fiber material is an important fiber source in the areas where forest resources are scarce. Nowadays, in the total pulp consumption of the world, the proportions of wood pulp, wastepaper pulp, and non-wood pulp are 63, 34, and 3%, respectively. The effective use of non-wood fiber resources, especially grasses, cereal straws, corn stalks, bamboo, and bagasse, would play a major role in optimizing papermaking raw materials. On the other hand, there are non-wood fibers such as flax, hemp, jute, kenaf, cotton, sisal, and abaca with properties as good as or much better than softwood materials.",book:{id:"6245",slug:"pulp-and-paper-processing",title:"Pulp and Paper Processing",fullTitle:"Pulp and Paper Processing"},signatures:"Zhong Liu, Huimei Wang and Lanfeng Hui",authors:[{id:"218005",title:"Prof.",name:"Zhong",middleName:null,surname:"Liu",slug:"zhong-liu",fullName:"Zhong Liu"},{id:"220665",title:"Prof.",name:"Lanfeng",middleName:null,surname:"Hui",slug:"lanfeng-hui",fullName:"Lanfeng Hui"},{id:"220666",title:"Dr.",name:"Huimei",middleName:null,surname:"Wang",slug:"huimei-wang",fullName:"Huimei Wang"}]},{id:"59931",title:"Abrasive for Chemical Mechanical Polishing",slug:"abrasive-for-chemical-mechanical-polishing",totalDownloads:2519,totalCrossrefCites:5,totalDimensionsCites:9,abstract:"Chemical mechanical polishing (CMP) is one of the most essential processes in semiconductor manufacturing. Its importance becomes highly underscored at the advanced device toward sub 14 nm scaling. The fundamental mechanism of CMP is to create soften surface layer by chemical reaction and then, mechanical force by abrasive particles remove soften layer. The role of CMP is not only material removal, but also planarization, surface smoothening, uniformity control, defect reduction and more. Moreover, semiconductor yield enhancement is sensitively influenced by CMP processing. Surface scratching, which is generated by CMP in nature, is considered as ‘killer defect’ in semiconductor manufacturing. Hence, to achieve proper CMP performance without surface scratching, understanding and development of abrasive particles are crucially important. In this chapter, CMP fundamentals, applications and challenges associated with abrasive particle technology including synthesis (up to nanoparticle scale), tribochemical reaction, abrasive surface zeta potential behavior, particle size and its distribution will be discussed.",book:{id:"6736",slug:"abrasive-technology-characteristics-and-applications",title:"Abrasive Technology",fullTitle:"Abrasive Technology - Characteristics and Applications"},signatures:"Hong Jin Kim",authors:[{id:"235449",title:"Dr.",name:"Hong Jin",middleName:null,surname:"Kim",slug:"hong-jin-kim",fullName:"Hong Jin Kim"}]},{id:"68532",title:"Application of the Fourth Industrial Revolution for High Volume Production in the Rail Car Industry",slug:"application-of-the-fourth-industrial-revolution-for-high-volume-production-in-the-rail-car-industry",totalDownloads:1016,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Some recent technological advances in line with the fourth industrial revolution (4IR) are rapidly transforming the industrial sector. This work explores the prospect of robotic and additive manufacturing solutions for mass production in the rail industry. It proposes a dual arm, 12-axis welding robot with advance sensors, camera, and algorithm as well as intelligent control system. The computer-aided design (CAD) of the robotic system was done in the Solidworks 2017 environment and simulated using the adaptive neuro-fuzzy interference system (ANFIS) in order to determine the kinematic motion of the robotic arm and the angles of joint. The simulation results showed the smooth motion of the robot and its suitability to carry out the welding operations for mass production of components during rail car manufacturing. In addition, the ability to fabricate several physical models directly from digital data through additive manufacturing (AM) is a key factor to ensuring rapid product development cycle. Given that AM is embedded in a digitally connected environment, flow of information as well as data processing and transmission in real time will be useful for massive turnout during mass production.",book:{id:"9278",slug:"mass-production-processes",title:"Mass Production Processes",fullTitle:"Mass Production Processes"},signatures:"Daniyan Ilesanmi, Oyesola Moses, Mpofu Khumbulani and Nwankwo Samuel",authors:[{id:"11921",title:"Prof.",name:"Khumbulani",middleName:null,surname:"Mpofu",slug:"khumbulani-mpofu",fullName:"Khumbulani Mpofu"},{id:"260269",title:"Dr.",name:"Ilesanmi Afolabi",middleName:null,surname:"Daniyan",slug:"ilesanmi-afolabi-daniyan",fullName:"Ilesanmi Afolabi Daniyan"},{id:"308892",title:"Mr.",name:"Moses",middleName:null,surname:"Oyesola",slug:"moses-oyesola",fullName:"Moses Oyesola"},{id:"308893",title:"Mr.",name:"Samuel",middleName:null,surname:"Nwankwo",slug:"samuel-nwankwo",fullName:"Samuel Nwankwo"}]},{id:"72044",title:"Applications of Machine Learning in Healthcare",slug:"applications-of-machine-learning-in-healthcare",totalDownloads:997,totalCrossrefCites:5,totalDimensionsCites:5,abstract:"Machine learning techniques in healthcare use the increasing amount of health data provided by the Internet of Things to improve patient outcomes. These techniques provide promising applications as well as significant challenges. The three main areas machine learning is applied to include medical imaging, natural language processing of medical documents, and genetic information. Many of these areas focus on diagnosis, detection, and prediction. A large infrastructure of medical devices currently generates data but a supporting infrastructure is oftentimes not in place to effectively utilize such data. The many different forms medical information exist in also creates some challenges in data formatting and can increase noise. We examine a brief history of machine learning, some basic knowledge regarding the techniques, and the current state of this technology in healthcare.",book:{id:"10150",slug:"smart-manufacturing-when-artificial-intelligence-meets-the-internet-of-things",title:"Smart Manufacturing",fullTitle:"Smart Manufacturing - When Artificial Intelligence Meets the Internet of Things"},signatures:"Christopher Toh and James P. Brody",authors:[{id:"313941",title:"Ph.D. Student",name:"Christopher",middleName:null,surname:"Toh",slug:"christopher-toh",fullName:"Christopher Toh"},{id:"314005",title:"Dr.",name:"James",middleName:null,surname:"Brody",slug:"james-brody",fullName:"James Brody"}]},{id:"64172",title:"Application of Six Sigma in Semiconductor Manufacturing: A Case Study in Yield Improvement",slug:"application-of-six-sigma-in-semiconductor-manufacturing-a-case-study-in-yield-improvement",totalDownloads:1851,totalCrossrefCites:3,totalDimensionsCites:6,abstract:"The purpose of this chapter is to outline systematic implementation of the Six Sigma DMAIC methodology as a case study in solving the problem of poor wafer yields in semiconductor manufacturing. The chapter also describes well-known industry standard business processes to be implemented and benchmarked in a semiconductor wafer fabrication facility to manage defect and yield issues while executing a Six Sigma project. The execution of Six Sigma enabled identification of the key process factors, root cause analysis, desired performance levels, and Cpk improvement opportunities. Implementing multilevel factorial design of experiments (DOE) study revealed critical input parameters on process tools contributing to defect formation. Improvement performed on these process tools resulted in in-line defect reduction and ultimately improving final yields.",book:{id:"7460",slug:"applications-of-design-for-manufacturing-and-assembly",title:"Applications of Design for Manufacturing and Assembly",fullTitle:"Applications of Design for Manufacturing and Assembly"},signatures:"Prashant Reddy Gangidi",authors:[{id:"248796",title:"Mr.",name:"Prashant",middleName:null,surname:"Gangidi",slug:"prashant-gangidi",fullName:"Prashant Gangidi"}]}],onlineFirstChaptersFilter:{topicId:"1356",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:8,limit:8,total:0},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:89,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:104,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:31,numberOfPublishedChapters:315,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:11,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:141,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:129,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:113,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:105,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:2,numberOfUpcomingTopics:1,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:5,numberOfOpenTopics:1,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!0},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:14,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. 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",coverUrl:"https://cdn.intechopen.com/series/covers/3.jpg",latestPublicationDate:"May 13th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:8,editor:{id:"419588",title:"Ph.D.",name:"Sergio",middleName:"Alexandre",surname:"Gehrke",slug:"sergio-gehrke",fullName:"Sergio Gehrke",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000038WgMKQA0/Profile_Picture_2022-06-02T11:44:20.jpg",biography:"Dr. Sergio Alexandre Gehrke is a doctorate holder in two fields. The first is a Ph.D. in Cellular and Molecular Biology from the Pontificia Catholic University, Porto Alegre, Brazil, in 2010 and the other is an International Ph.D. in Bioengineering from the Universidad Miguel Hernandez, Elche/Alicante, Spain, obtained in 2020. In 2018, he completed a postdoctoral fellowship in Materials Engineering in the NUCLEMAT of the Pontificia Catholic University, Porto Alegre, Brazil. He is currently the Director of the Postgraduate Program in Implantology of the Bioface/UCAM/PgO (Montevideo, Uruguay), Director of the Cathedra of Biotechnology of the Catholic University of Murcia (Murcia, Spain), an Extraordinary Full Professor of the Catholic University of Murcia (Murcia, Spain) as well as the Director of the private center of research Biotecnos – Technology and Science (Montevideo, Uruguay). Applied biomaterials, cellular and molecular biology, and dental implants are among his research interests. He has published several original papers in renowned journals. In addition, he is also a Collaborating Professor in several Postgraduate programs at different universities all over the world.",institutionString:null,institution:{name:"Universidad Católica San Antonio de Murcia",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:2,paginationItems:[{id:"1",title:"Oral Health",coverUrl:"https://cdn.intechopen.com/series_topics/covers/1.jpg",isOpenForSubmission:!0,editor:{id:"173955",title:"Prof.",name:"Sandra",middleName:null,surname:"Marinho",slug:"sandra-marinho",fullName:"Sandra Marinho",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRGYMQA4/Profile_Picture_2022-06-01T13:22:41.png",biography:"Dr. Sandra A. Marinho is an Associate Professor and Brazilian researcher at the State University of Paraíba (Universidade Estadual da Paraíba- UEPB), Campus VIII, located in Araruna, state of Paraíba since 2011. She holds a degree in Dentistry from the Federal University of Alfenas (UNIFAL), while her specialization and professional improvement in Stomatology took place at Hospital Heliopolis (São Paulo, SP). Her qualifications are: a specialist in Dental Imaging and Radiology, Master in Dentistry (Periodontics) from the University of São Paulo (FORP-USP, Ribeirão Preto, SP), and Doctor (Ph.D.) in Dentistry (Stomatology Clinic) from Hospital São Lucas of the Pontifical Catholic University of Rio Grande do Sul (HSL-PUCRS, Porto Alegre, RS). She held a postdoctoral internship at the Federal University from Jequitinhonha and Mucuri Valleys (UFVJM, Diamantina, MG). She is currently a member of the Brazilian Society for Dental Research (SBPqO) and the Brazilian Society of Stomatology and Pathology (SOBEP). Dr. Marinho's experience in Dentistry mainly covers the following subjects: oral diagnosis, oral radiology; oral medicine; lesions and oral infections; oral pathology, laser therapy and epidemiological studies.",institutionString:null,institution:{name:"State University of Paraíba",institutionURL:null,country:{name:"Brazil"}}},editorTwo:null,editorThree:null},{id:"2",title:"Prosthodontics and Implant Dentistry",coverUrl:"https://cdn.intechopen.com/series_topics/covers/2.jpg",isOpenForSubmission:!0,editor:{id:"179568",title:"Associate Prof.",name:"Wen Lin",middleName:null,surname:"Chai",slug:"wen-lin-chai",fullName:"Wen Lin Chai",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRHGAQA4/Profile_Picture_2022-05-23T14:31:12.png",biography:"Professor Dr. Chai Wen Lin is currently a lecturer at the Department of Restorative Dentistry, Faculty of Dentistry of the University of Malaya. She obtained a Master of Dental Science in 2006 and a Ph.D. in 2011. Her Ph.D. research work on the soft tissue-implant interface at the University of Sheffield has yielded several important publications in the key implant journals. She was awarded an Excellent Exchange Award by the University of Sheffield which gave her the opportunity to work at the famous Faculty of Dentistry of the University of Gothenburg, Sweden, under the tutelage of Prof. Peter Thomsen. In 2016, she was appointed as a visiting scholar at UCLA, USA, with attachment in Hospital Dentistry, and involvement in research work related to zirconia implant. In 2016, her contribution to dentistry was recognized by the Royal College of Surgeon of Edinburgh with her being awarded a Fellowship in Dental Surgery. She has authored numerous papers published both in local and international journals. She was the Editor of the Malaysian Dental Journal for several years. Her main research interests are implant-soft tissue interface, zirconia implant, photofunctionalization, 3D-oral mucosal model and pulpal regeneration.",institutionString:null,institution:{name:"University of Malaya",institutionURL:null,country:{name:"Malaysia"}}},editorTwo:{id:"479686",title:"Dr.",name:"Ghee Seong",middleName:null,surname:"Lim",slug:"ghee-seong-lim",fullName:"Ghee Seong Lim",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003ScjLZQAZ/Profile_Picture_2022-06-08T14:17:06.png",biography:"Assoc. Prof Dr. Lim Ghee Seong graduated with a Bachelor of Dental Surgery from University of Malaya, Kuala Lumpur in 2008. He then pursued his Master in Clinical Dentistry, specializing in Restorative Dentistry at Newcastle University, Newcastle, UK, where he graduated with distinction. He has also been awarded the International Training Fellowship (Restorative Dentistry) from the Royal College of Surgeons. His passion for teaching then led him to join the faculty of dentistry at University Malaya and he has since became a valuable lecturer and clinical specialist in the Department of Restorative Dentistry. He is currently the removable prosthodontic undergraduate year 3 coordinator, head of the undergraduate module on occlusion and a member of the multidisciplinary team for the TMD clinic. He has previous membership in the British Society for Restorative Dentistry, the Malaysian Association of Aesthetic Dentistry and he is currently a lifetime member of the Malaysian Association for Prosthodontics. Currently, he is also the examiner for the Restorative Specialty Membership Examinations, Royal College of Surgeons, England. He has authored and co-authored handful of both local and international journal articles. 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He is also a faculty member in the Molecular Oncology Program. He obtained his MSc and Ph.D. at Oregon State University and Texas Tech University, respectively. He pursued his postdoctoral studies at Rutgers University Medical School and the National Institutes of Health (NIH/NIDDK), USA. His research focuses on biochemistry, biophysics, genetics, molecular biology, and molecular medicine with specialization in the fields of drug design, protein structure-function, protein folding, prions, microRNA, pseudogenes, molecular cancer, epigenetics, metabolites, proteomics, genomics, protein expression, and characterization by spectroscopic and calorimetric methods.",institutionString:"University of Health Sciences",institution:null},{id:"180528",title:"Dr.",name:"Hiroyuki",middleName:null,surname:"Kagechika",slug:"hiroyuki-kagechika",fullName:"Hiroyuki Kagechika",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/180528/images/system/180528.jpg",biography:"Hiroyuki Kagechika received his bachelor’s degree and Ph.D. in Pharmaceutical Sciences from the University of Tokyo, Japan, where he served as an associate professor until 2004. He is currently a professor at the Institute of Biomaterials and Bioengineering (IBB), Tokyo Medical and Dental University (TMDU). From 2010 to 2012, he was the dean of the Graduate School of Biomedical Science. Since 2012, he has served as the vice dean of the Graduate School of Medical and Dental Sciences. He has been the director of the IBB since 2020. Dr. Kagechika’s major research interests are the medicinal chemistry of retinoids, vitamins D/K, and nuclear receptors. He has developed various compounds including a drug for acute promyelocytic leukemia.",institutionString:"Tokyo Medical and Dental University",institution:{name:"Tokyo Medical and Dental University",country:{name:"Japan"}}},{id:"268659",title:"Ms.",name:"Xianquan",middleName:null,surname:"Zhan",slug:"xianquan-zhan",fullName:"Xianquan Zhan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/268659/images/8143_n.jpg",biography:"Dr. Zhan received his undergraduate and graduate training in the fields of preventive medicine and epidemiology and statistics at the West China University of Medical Sciences in China during 1989 to 1999. He received his post-doctoral training in oncology and cancer proteomics for two years at the Cancer Research Institute of Human Medical University in China. In 2001, he went to the University of Tennessee Health Science Center (UTHSC) in USA, where he was a post-doctoral researcher and focused on mass spectrometry and cancer proteomics. Then, he was appointed as an Assistant Professor of Neurology, UTHSC in 2005. He moved to the Cleveland Clinic in USA as a Project Scientist/Staff in 2006 where he focused on the studies of eye disease proteomics and biomarkers. He returned to UTHSC as an Assistant Professor of Neurology in the end of 2007, engaging in proteomics and biomarker studies of lung diseases and brain tumors, and initiating the studies of predictive, preventive, and personalized medicine (PPPM) in cancer. In 2010, he was promoted to Associate Professor of Neurology, UTHSC. Currently, he is a Professor at Xiangya Hospital of Central South University in China, Fellow of Royal Society of Medicine (FRSM), the European EPMA National Representative in China, Regular Member of American Association for the Advancement of Science (AAAS), European Cooperation of Science and Technology (e-COST) grant evaluator, Associate Editors of BMC Genomics, BMC Medical Genomics, EPMA Journal, and Frontiers in Endocrinology, Executive Editor-in-Chief of Med One. He has\npublished 116 peer-reviewed research articles, 16 book chapters, 2 books, and 2 US patents. His current main research interest focuses on the studies of cancer proteomics and biomarkers, and the use of modern omics techniques and systems biology for PPPM in cancer, and on the development and use of 2DE-LC/MS for the large-scale study of human proteoforms.",institutionString:null,institution:{name:"Xiangya Hospital Central South University",country:{name:"China"}}},{id:"40482",title:null,name:"Rizwan",middleName:null,surname:"Ahmad",slug:"rizwan-ahmad",fullName:"Rizwan Ahmad",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/40482/images/system/40482.jpeg",biography:"Dr. Rizwan Ahmad is a University Professor and Coordinator, Quality and Development, College of Medicine, Imam Abdulrahman bin Faisal University, Saudi Arabia. Previously, he was Associate Professor of Human Function, Oman Medical College, Oman, and SBS University, Dehradun. Dr. Ahmad completed his education at Aligarh Muslim University, Aligarh. He has published several articles in peer-reviewed journals, chapters, and edited books. His area of specialization is free radical biochemistry and autoimmune diseases.",institutionString:"Imam Abdulrahman Bin Faisal University",institution:{name:"Imam Abdulrahman Bin Faisal University",country:{name:"Saudi Arabia"}}},{id:"41865",title:"Prof.",name:"Farid A.",middleName:null,surname:"Badria",slug:"farid-a.-badria",fullName:"Farid A. Badria",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/41865/images/system/41865.jpg",biography:"Farid A. Badria, Ph.D., is the recipient of several awards, including The World Academy of Sciences (TWAS) Prize for Public Understanding of Science; the World Intellectual Property Organization (WIPO) Gold Medal for best invention; Outstanding Arab Scholar, Kuwait; and the Khwarizmi International Award, Iran. He has 250 publications, 12 books, 20 patents, and several marketed pharmaceutical products to his credit. He continues to lead research projects on developing new therapies for liver, skin disorders, and cancer. Dr. Badria was listed among the world’s top 2% of scientists in medicinal and biomolecular chemistry in 2019 and 2020. He is a member of the Arab Development Fund, Kuwait; International Cell Research Organization–United Nations Educational, Scientific and Cultural Organization (ICRO–UNESCO), Chile; and UNESCO Biotechnology France",institutionString:"Mansoura University",institution:{name:"Mansoura University",country:{name:"Egypt"}}},{id:"329385",title:"Dr.",name:"Rajesh K.",middleName:"Kumar",surname:"Singh",slug:"rajesh-k.-singh",fullName:"Rajesh K. Singh",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/329385/images/system/329385.png",biography:"Dr. Singh received a BPharm (2003) and MPharm (2005) from Panjab University, Chandigarh, India, and a Ph.D. (2013) from Punjab Technical University (PTU), Jalandhar, India. He has more than sixteen years of teaching experience and has supervised numerous postgraduate and Ph.D. students. He has to his credit more than seventy papers in SCI- and SCOPUS-indexed journals, fifty-five conference proceedings, four books, six Best Paper Awards, and five projects from different government agencies. He is currently an editorial board member of eight international journals and a reviewer for more than fifty scientific journals. He received Top Reviewer and Excellent Peer Reviewer Awards from Publons in 2016 and 2017, respectively. He is also on the panel of The International Reviewer for reviewing research proposals for grants from the Royal Society. He also serves as a Publons Academy mentor and Bentham brand ambassador.",institutionString:"Punjab Technical University",institution:{name:"Punjab Technical University",country:{name:"India"}}},{id:"142388",title:"Dr.",name:"Thiago",middleName:"Gomes",surname:"Gomes Heck",slug:"thiago-gomes-heck",fullName:"Thiago Gomes Heck",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/142388/images/7259_n.jpg",biography:null,institutionString:null,institution:{name:"Universidade Regional do Noroeste do Estado do Rio Grande do Sul",country:{name:"Brazil"}}},{id:"336273",title:"Assistant Prof.",name:"Janja",middleName:null,surname:"Zupan",slug:"janja-zupan",fullName:"Janja Zupan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/336273/images/14853_n.jpeg",biography:"Janja Zupan graduated in 2005 at the Department of Clinical Biochemistry (superviser prof. dr. Janja Marc) in the field of genetics of osteoporosis. Since November 2009 she is working as a Teaching Assistant at the Faculty of Pharmacy, Department of Clinical Biochemistry. In 2011 she completed part of her research and PhD work at Institute of Genetics and Molecular Medicine, University of Edinburgh. She finished her PhD entitled The influence of the proinflammatory cytokines on the RANK/RANKL/OPG in bone tissue of osteoporotic and osteoarthritic patients in 2012. From 2014-2016 she worked at the Institute of Biomedical Sciences, University of Aberdeen as a postdoctoral research fellow on UK Arthritis research project where she gained knowledge in mesenchymal stem cells and regenerative medicine. She returned back to University of Ljubljana, Faculty of Pharmacy in 2016. She is currently leading project entitled Mesenchymal stem cells-the keepers of tissue endogenous regenerative capacity facing up to aging of the musculoskeletal system funded by Slovenian Research Agency.",institutionString:null,institution:{name:"University of Ljubljana",country:{name:"Slovenia"}}},{id:"357453",title:"Dr.",name:"Radheshyam",middleName:null,surname:"Maurya",slug:"radheshyam-maurya",fullName:"Radheshyam Maurya",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/357453/images/16535_n.jpg",biography:null,institutionString:null,institution:{name:"University of Hyderabad",country:{name:"India"}}},{id:"418340",title:"Dr.",name:"Jyotirmoi",middleName:null,surname:"Aich",slug:"jyotirmoi-aich",fullName:"Jyotirmoi Aich",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000038Ugi5QAC/Profile_Picture_2022-04-15T07:48:28.png",biography:"Biotechnologist with 15 years of research including 6 years of teaching experience. Demonstrated record of scientific achievements through consistent publication record (H index = 13, with 874 citations) in high impact journals such as Nature Communications, Oncotarget, Annals of Oncology, PNAS, and AJRCCM, etc. Strong research professional with a post-doctorate from ACTREC where I gained experimental oncology experience in clinical settings and a doctorate from IGIB where I gained expertise in asthma pathophysiology. A well-trained biotechnologist with diverse experience on the bench across different research themes ranging from asthma to cancer and other infectious diseases. An individual with a strong commitment and innovative mindset. Have the ability to work on diverse projects such as regenerative and molecular medicine with an overall mindset of improving healthcare.",institutionString:"DY Patil Deemed to Be University",institution:null},{id:"349288",title:"Prof.",name:"Soumya",middleName:null,surname:"Basu",slug:"soumya-basu",fullName:"Soumya Basu",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000035QxIDQA0/Profile_Picture_2022-04-15T07:47:01.jpg",biography:"Soumya Basu, Ph.D., is currently working as an Associate Professor at Dr. D. Y. Patil Biotechnology and Bioinformatics Institute, Dr. D. Y. Patil Vidyapeeth, Pune, Maharashtra, India. With 16+ years of trans-disciplinary research experience in Drug Design, development, and pre-clinical validation; 20+ research article publications in journals of repute, 9+ years of teaching experience, trained with cross-disciplinary education, Dr. Basu is a life-long learner and always thrives for new challenges.\r\nHer research area is the design and synthesis of small molecule partial agonists of PPAR-γ in lung cancer. She is also using artificial intelligence and deep learning methods to understand the exosomal miRNA’s role in cancer metastasis. Dr. Basu is the recipient of many awards including the Early Career Research Award from the Department of Science and Technology, Govt. of India. She is a reviewer of many journals like Molecular Biology Reports, Frontiers in Oncology, RSC Advances, PLOS ONE, Journal of Biomolecular Structure & Dynamics, Journal of Molecular Graphics and Modelling, etc. She has edited and authored/co-authored 21 journal papers, 3 book chapters, and 15 abstracts. She is a Board of Studies member at her university. She is a life member of 'The Cytometry Society”-in India and 'All India Cell Biology Society”- in India.",institutionString:"Dr. D.Y. Patil Vidyapeeth, Pune",institution:{name:"Dr. D.Y. Patil Vidyapeeth, Pune",country:{name:"India"}}},{id:"354817",title:"Dr.",name:"Anubhab",middleName:null,surname:"Mukherjee",slug:"anubhab-mukherjee",fullName:"Anubhab Mukherjee",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0033Y0000365PbRQAU/ProfilePicture%202022-04-15%2005%3A11%3A18.480",biography:"A former member of Laboratory of Nanomedicine, Brigham and Women’s Hospital, Harvard University, Boston, USA, Dr. Anubhab Mukherjee is an ardent votary of science who strives to make an impact in the lives of those afflicted with cancer and other chronic/acute ailments. He completed his Ph.D. from CSIR-Indian Institute of Chemical Technology, Hyderabad, India, having been skilled with RNAi, liposomal drug delivery, preclinical cell and animal studies. He pursued post-doctoral research at College of Pharmacy, Health Science Center, Texas A & M University and was involved in another postdoctoral research at Department of Translational Neurosciences and Neurotherapeutics, John Wayne Cancer Institute, Santa Monica, California. In 2015, he worked in Harvard-MIT Health Sciences & Technology as a visiting scientist. He has substantial experience in nanotechnology-based formulation development and successfully served various Indian organizations to develop pharmaceuticals and nutraceutical products. He is an inventor in many US patents and an author in many peer-reviewed articles, book chapters and books published in various media of international repute. Dr. Mukherjee is currently serving as Principal Scientist, R&D at Esperer Onco Nutrition (EON) Pvt. Ltd. and heads the Hyderabad R&D center of the organization.",institutionString:"Esperer Onco Nutrition Pvt Ltd.",institution:null},{id:"319365",title:"Assistant Prof.",name:"Manash K.",middleName:null,surname:"Paul",slug:"manash-k.-paul",fullName:"Manash K. Paul",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/319365/images/system/319365.png",biography:"Manash K. Paul is a Principal Investigator and Scientist at the University of California Los Angeles. He has contributed significantly to the fields of stem cell biology, regenerative medicine, and lung cancer. His research focuses on various signaling processes involved in maintaining stem cell homeostasis during the injury-repair process, deciphering lung stem cell niche, pulmonary disease modeling, immuno-oncology, and drug discovery. He is currently investigating the role of extracellular vesicles in premalignant lung cell migration and detecting the metastatic phenotype of lung cancer via machine-learning-based analyses of exosomal signatures. Dr. Paul has published in more than fifty peer-reviewed international journals and is highly cited. He is the recipient of many awards, including the UCLA Vice Chancellor’s award, a senior member of the Institute of Electrical and Electronics Engineers (IEEE), and an editorial board member for several international journals.",institutionString:"University of California Los Angeles",institution:{name:"University of California Los Angeles",country:{name:"United States of America"}}},{id:"311457",title:"Dr.",name:"Júlia",middleName:null,surname:"Scherer Santos",slug:"julia-scherer-santos",fullName:"Júlia Scherer Santos",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/311457/images/system/311457.jpg",biography:"Dr. Júlia Scherer Santos works in the areas of cosmetology, nanotechnology, pharmaceutical technology, beauty, and aesthetics. Dr. Santos also has experience as a professor of graduate courses. Graduated in Pharmacy, specialization in Cosmetology and Cosmeceuticals applied to aesthetics, specialization in Aesthetic and Cosmetic Health, and a doctorate in Pharmaceutical Nanotechnology. Teaching experience in Pharmacy and Aesthetics and Cosmetics courses. She works mainly on the following subjects: nanotechnology, cosmetology, pharmaceutical technology, aesthetics.",institutionString:"Universidade Federal de Juiz de Fora",institution:{name:"Universidade Federal de Juiz de Fora",country:{name:"Brazil"}}},{id:"219081",title:"Dr.",name:"Abdulsamed",middleName:null,surname:"Kükürt",slug:"abdulsamed-kukurt",fullName:"Abdulsamed Kükürt",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/219081/images/system/219081.png",biography:"Dr. Kükürt graduated from Uludağ University in Turkey. He started his academic career as a Research Assistant in the Department of Biochemistry at Kafkas University. In 2019, he completed his Ph.D. program in the Department of Biochemistry at the Institute of Health Sciences. He is currently working at the Department of Biochemistry, Kafkas University. He has 27 published research articles in academic journals, 11 book chapters, and 37 papers. He took part in 10 academic projects. He served as a reviewer for many articles. He still serves as a member of the review board in many academic journals.",institutionString:"Kafkas University",institution:{name:"Kafkas University",country:{name:"Turkey"}}},{id:"178366",title:"Associate Prof.",name:"Volkan",middleName:null,surname:"Gelen",slug:"volkan-gelen",fullName:"Volkan Gelen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/178366/images/system/178366.jpg",biography:"Volkan Gelen is a Physiology specialist who received his veterinary degree from Kafkas University in 2011. Between 2011-2015, he worked as an assistant at Atatürk University, Faculty of Veterinary Medicine, Department of Physiology. In 2016, he joined Kafkas University, Faculty of Veterinary Medicine, Department of Physiology as an assistant professor. Dr. Gelen has been engaged in various academic activities at Kafkas University since 2016. There he completed 5 projects and has 3 ongoing projects. He has 60 articles published in scientific journals and 20 poster presentations in scientific congresses. His research interests include physiology, endocrine system, cancer, diabetes, cardiovascular system diseases, and isolated organ bath system studies.",institutionString:"Kafkas University",institution:{name:"Kafkas University",country:{name:"Turkey"}}},{id:"418963",title:"Dr.",name:"Augustine Ododo",middleName:"Augustine",surname:"Osagie",slug:"augustine-ododo-osagie",fullName:"Augustine Ododo Osagie",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/418963/images/16900_n.jpg",biography:"Born into the family of Osagie, a prince of the Benin Kingdom. I am currently an academic in the Department of Medical Biochemistry, University of Benin. Part of the duties are to teach undergraduate students and conduct academic research.",institutionString:null,institution:{name:"University of Benin",country:{name:"Nigeria"}}},{id:"192992",title:"Prof.",name:"Shagufta",middleName:null,surname:"Perveen",slug:"shagufta-perveen",fullName:"Shagufta Perveen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/192992/images/system/192992.png",biography:"Prof. Shagufta Perveen is a Distinguish Professor in the Department of Pharmacognosy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia. Dr. Perveen has acted as the principal investigator of major research projects funded by the research unit of King Saud University. She has more than ninety original research papers in peer-reviewed journals of international repute to her credit. 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He graduated from the Semashko Moscow Medical Institute (Semashko National Research Institute of Public Health) with a degree in Medicine (1998), the Clinical Department of Dermatovenerology (2000), and received a second higher education in Psychology (2009). Professor A.V. Grechko held the position of Сhief Physician of the Central Clinical Hospital in Moscow. He worked as a professor at the faculty and was engaged in scientific research at the Medical University. Starting in 2013, he has been the initiator of the creation of the Federal Scientific and Clinical Center for Intensive Care and Rehabilitology, Moscow, Russian Federation, where he also serves as Director since 2015. 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She has been a Professor since 1996. Currently, she is the Head of the Laboratory of Metabolism, a division of the Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology, Moscow, Russian Federation. N.V. Beloborodova has many years of clinical experience in the field of intensive care and surgery. She studies infectious complications and sepsis. She initiated a series of interdisciplinary clinical and experimental studies based on the concept of integrating human metabolism and its microbiota. Her scientific achievements are widely known: she is the recipient of the Marie E. Coates Award \\"Best lecturer-scientist\\" Gustafsson Fund, Karolinska Institutes, Stockholm, Sweden, and the International Sepsis Forum Award, Pasteur Institute, Paris, France (2014), etc. Professor N.V. Beloborodova wrote 210 papers, five books, 10 chapters and has edited four books.',institutionString:"Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology",institution:null},{id:"354260",title:"Ph.D.",name:"Tércio Elyan",middleName:"Azevedo",surname:"Azevedo Martins",slug:"tercio-elyan-azevedo-martins",fullName:"Tércio Elyan Azevedo Martins",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/354260/images/16241_n.jpg",biography:"Graduated in Pharmacy from the Federal University of Ceará with the modality in Industrial Pharmacy, Specialist in Production and Control of Medicines from the University of São Paulo (USP), Master in Pharmaceuticals and Medicines from the University of São Paulo (USP) and Doctor of Science in the program of Pharmaceuticals and Medicines by the University of São Paulo. Professor at Universidade Paulista (UNIP) in the areas of chemistry, cosmetology and trichology. Assistant Coordinator of the Higher Course in Aesthetic and Cosmetic Technology at Universidade Paulista Campus Chácara Santo Antônio. Experience in the Pharmacy area, with emphasis on Pharmacotechnics, Pharmaceutical Technology, Research and Development of Cosmetics, acting mainly on topics such as cosmetology, antioxidant activity, aesthetics, photoprotection, cyclodextrin and thermal analysis.",institutionString:null,institution:{name:"University of Sao Paulo",country:{name:"Brazil"}}},{id:"334285",title:"Ph.D. Student",name:"Sameer",middleName:"Kumar",surname:"Jagirdar",slug:"sameer-jagirdar",fullName:"Sameer Jagirdar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/334285/images/14691_n.jpg",biography:"I\\'m a graduate student at the center for biosystems science and engineering at the Indian Institute of Science, Bangalore, India. I am interested in studying host-pathogen interactions at the biomaterial interface.",institutionString:null,institution:{name:"Indian Institute of Science Bangalore",country:{name:"India"}}},{id:"329248",title:"Dr.",name:"Md. Faheem",middleName:null,surname:"Haider",slug:"md.-faheem-haider",fullName:"Md. Faheem Haider",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/329248/images/system/329248.jpg",biography:"Dr. Md. Faheem Haider completed his BPharm in 2012 at Integral University, Lucknow, India. In 2014, he completed his MPharm with specialization in Pharmaceutics at Babasaheb Bhimrao Ambedkar University, Lucknow, India. He received his Ph.D. degree from Jamia Hamdard University, New Delhi, India, in 2018. He was selected for the GPAT six times and his best All India Rank was 34. Currently, he is an assistant professor at Integral University. Previously he was an assistant professor at IIMT University, Meerut, India. He has experience teaching DPharm, Pharm.D, BPharm, and MPharm students. He has more than five publications in reputed journals to his credit. Dr. Faheem’s research area is the development and characterization of nanoformulation for the delivery of drugs to various organs.",institutionString:"Integral University",institution:{name:"Integral University",country:{name:"India"}}},{id:"329795",title:"Dr.",name:"Mohd Aftab",middleName:"Aftab",surname:"Siddiqui",slug:"mohd-aftab-siddiqui",fullName:"Mohd Aftab Siddiqui",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/329795/images/15648_n.jpg",biography:"Dr. Mohd Aftab Siddiqui is currently working as Assistant Professor in the Faculty of Pharmacy, Integral University, Lucknow for the last 6 years. He has completed his Doctor in Philosophy (Pharmacology) in 2020 from Integral University, Lucknow. He completed his Bachelor in Pharmacy in 2013 and Master in Pharmacy (Pharmacology) in 2015 from Integral University, Lucknow. He is the gold medalist in Bachelor and Master degree. He qualified GPAT -2013, GPAT -2014, and GPAT 2015. His area of research is Pharmacological screening of herbal drugs/ natural products in liver and cardiac diseases. He has guided many M. Pharm. research projects. 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He has presented his research works at numerous local and international conferences such as the European Association for Cardiothoracic Surgery (EACTS) and the European Society of Cardiovascular Surgery (ESCVS), to name a few. He has also won many awards for his research presentations at meetings and conferences like the prestigious International Invention, Innovation & Technology Exhibition (ITEX); Design, Research and Innovation Exhibition, the National Conference on Medical Sciences and the Annual Scientific Meetings of the Malaysian Association for Thoracic and Cardiovascular Surgery. He was awarded the Darjah Setia Pangkuan Negeri (DSPN) by the Governor of Penang in July, 2015.",institutionString:null,institution:{name:"Monash University Malaysia",country:{name:"Malaysia"}}},{id:"30568",title:"Prof.",name:"Madhu",middleName:null,surname:"Khullar",slug:"madhu-khullar",fullName:"Madhu Khullar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/30568/images/system/30568.jpg",biography:"Dr. Madhu Khullar is a Professor of Experimental Medicine and Biotechnology at the Post Graduate Institute of Medical Education and Research, Chandigarh, India. She completed her Post Doctorate in hypertension research at the Henry Ford Hospital, Detroit, USA in 1985. She is an editor and reviewer of several international journals, and a fellow and member of several cardiovascular research societies. 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Currently, he is a full professor at Central South University and Shandong First Medical University, and an advisor to MS/PhD students and postdoctoral fellows. He is also a fellow of the Royal Society of Medicine and European Association for Predictive Preventive Personalized Medicine (EPMA), a national representative of EPMA, and a member of the American Society of Clinical Oncology (ASCO) and the American Association for the Advancement of Sciences (AAAS). He is also the editor in chief of International Journal of Chronic Diseases & Therapy, an associate editor of EPMA Journal, Frontiers in Endocrinology, and BMC Medical Genomics, and a guest editor of Mass Spectrometry Reviews, Frontiers in Endocrinology, EPMA Journal, and Oxidative Medicine and Cellular Longevity. 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He is currently working on the following subjects: Aluminium toxicity, Neuroinflammation, Oxidative stress and Purinergic system. Since 2011 he has presented more than 80 abstracts in scientific proceedings of national and international meetings. Since 2014, he has published more than 20 peer reviewed papers (including 4 reviews, 3 in Portuguese) and 2 book chapters. 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Among them are those associated with pollution, resource extraction and overexploitation, loss of biodiversity, soil degradation, disorderly land occupation and planning, and many others. These anthropic effects could potentially be caused by any inadequate management of the environment. However, ecosystems have a resilience that makes them react to disturbances which mitigate the negative effects. It is critical to understand how ecosystems, natural and anthropized, including urban environments, respond to actions that have a negative influence and how they are managed. It is also important to establish when the limits marked by the resilience and the breaking point are achieved and when no return is possible. 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