Variables for the environmental quality/Health index in Eq. 1.
\r\n\tThis book written by prominent scholars, researchers, and scientists provides updates and new perspectives on Capsicum biology, origin, taxonomy, germplasm characteristics, biochemistry, chemosystematics, toxicology, genetics, genomics, breeding, cultural practices, management, indigenous knowledge, responses to biotic and abiotic stresses, resistance and tolerance to pathogens, processing, utilization, industry, and global markets. This inclusive book on Capsicum is indispensable reference material to students, researchers, academicians, culinary enthusiasts, policymakers, and stakeholders involved in Capsicum utilization, processing, development, research, and instruction.
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Urban Savanna",doi:"10.5772/intechopen.71908",slug:"the-corbusier-dream-and-frank-lloyd-wright-vision-cliff-detritus-vs-urban-savanna",body:'For the last 50 years, investigators have been seeking quantitative methods to predict and assess the visual and environmental quality of the landscape. The literature on this subject is vast. Mo
During this timeframe, Lu
As an extension of Lu’s
Michigan is located in the Great Lakes Region of the United States of America. Michigan is the only state to consist of two peninsulas. These two peninsulas are linked by the Mackinac Bridge. The Upper Peninsula is separated from the Lower Peninsula by the Straits of Mackinac. The Lower Peninsula whose shape looks like a mitten was chosen as the study area. The area of this research is known as Southern Michigan, which is no further north than N. 44.2 in latitude (Figure 1). The majority of people live in this southern portion of Michigan containing many more people than the other part of Michigan. Cities in the study area include: Grand Rapids, Battle Creek, Benton Harbor, Jackson, Kalamazoo, Flint, Pontiac, Bay City, Midland, Holland, Saginaw, Muskegon, East Lansing, Ann Arbor, and Metropolitan Detroit.
Location of the study area and related study areas (north is at the top of the figure).
Le Corbusier’s Unité d’Habitation of Nantes-Rezé, France was built in 1955 [7]. Nantes is a French port along the Loire River, in western France. The structure contains a school at the top level. From this basic idea emerged in Shanghai a vast collection of towers, many multi-function. The architectural towers emerged over 100 years after the a French Concession trading port south of the Chang Jiang (Yangtze River), along the sea coast was established. Since the 1990s, Shanghai has experienced extensive redevelopment with towers extending sometimes as far as the eyes can see (Figure 2).
A model of the central urban core of shanghai in 2007 copyright © 2007, Jon Bryan burley, all rights reserved, used by permission.
The methodology to evaluate large areas of urban and rural landscape was similar to Lu
where (See Table 1):
HEALTH | environmental quality index |
---|---|
X1 | perimeter of immediate vegetation |
X2 | perimeter of intermediate non-vegetation |
X3 | perimeter of distant vegetation |
X4 | area of intermediate vegetation |
X6 | area of distant non-vegetation |
X7 | area of pavement |
X8 | area of building |
X9 | area of vehicle |
X10 | area of humans |
X11 | area of smoke |
X14 | area of wildflowers in foreground |
X15 | area of utilities |
X16 | area of boats |
X17 | area of dead foreground vegetation |
X19 | area of wildlife |
X30 | open landscapes = X2 + X4 + (2 × (X3 + X6)) |
X31 | closed landscapes = X2 + X4 + (2 × (X1 + X17)) |
X32 | openness = X30 − X31 |
X34 | mystery = X30 × X1 × X7/1140 |
X52 | noosphericness = X7 + X8 + X9 + X15 + X16 |
Variables for the environmental quality/Health index in Eq. 1.
The test statistics are provided in Eqs. 2 and 3. The statistics are based upon rankings of treatment scores across rows. In this case the rows are pairs of images between two treatments: the predicted score for a randomly chosen site in the study area and the actual score from a photograph taken at that location. There are 30 rows (pairs of scores) for this study (n = 30) The treatments are the columns (m = 2). The rankings are summed and squared, to compute Kendall’s W value Eq. (2). (Rj)2 is the sum of the squares of the rankings for a column in computing the Kendall’s W value [8, 9].
Kendall’s W value is a number ranging between 0 and 1. When W is near 0, there is no strong overall trend of agreement among the respondents. If W is near 1, then the responses could be regarded as close to unanimous in their agreement. The W test statistic approximates a Chi-square distribution with n−1 degrees of freedom (Eq. 3). If computed values for Chi-square (Eq. 3) are greater than significant values in a Chi-square table for n−1 degrees of freedom (in this case 29 = 30–1), then there is a high level of agreement/concordance—the predicted scores and the actual scores are in agreement.
The sample of images gathered in the investigation include forested lands (Figure 3), agricultural lands (Figure 4), residential environments (Figure 5) (known as urban savanna), downtown-like environments (Figure 6) (know as cliff detritus) and industrial sites (Figure 7) [12].
Image of sample number 26 of a forested landscape in southern Michigan (visual score of 54.40120) — Copyright © 2011, Yuemin Jin, all rights reserved, used by permission.
Image of sample number 16 of a farmland landscape in southern Michigan (visual score of 59.12320) — Copyright © 2011, Yuemin Jin, all rights reserved, used by permission.
An image of a residential landscape (urban savanna with visual quality score of 61.58117), sample number 10 — Copyright © 2011, Yuemin Jin, all rights reserved, used by permission.
An image of sample number 12 of a downtown environment (cliff detritus with a visual score of 69.28333) — Copyright © 2011, Yuemin Jin, all rights reserved, used by permission.
An image of sample number 22 of an industrial environmental (with a visual score of 86.56068) — Copyright © 2011, Yuemin Jin, all rights reserved, used by permission.
Table 2 presents the rankings of the images from the study. The predicted ranks are scores generated by developing a map of the study area. The actual scores are values taken and measured from a random site in the study area. Kendall’s Concordance analysis revealed a Chi-square score of 51.8 (see Min for details) [8]. This value is larger than 49.58788 (a 99% confidence level (p ≤ 0.01) for 29 degrees of freedom. Since 51.8 is larger than 49.58788, the predicted scores and the actual scores are in agreement at a 99% confidence level (p < 0.01). These results suggest that it is possible to construct an environmental/visual quality map of Southern Michigan that is relatively reliable (Figure 8).
Property | Predicted Ranking | Images from Set Number 2 | Actual Score | Set 2 Ranking |
---|---|---|---|---|
Industrial | 3 | 55 | 107.80 | 1 |
Downtown | 8 | 42 | 89.68 | 2 |
Industrial | 3 | 52 | 83.12 | 3 |
Industrial | 3 | 51 | 82.92 | 4 |
Commercial | 13 | 31 | 82.12 | 5 |
Downtown | 8 | 45 | 81.84 | 6 |
Downtown | 8 | 41 | 77.91 | 7 |
Industrial | 3 | 54 | 77.12 | 8 |
Commercial | 13 | 33 | 76.05 | 9 |
Downtown | 8 | 43 | 75.23 | 10 |
Commercial | 13 | 32 | 74.15 | 11 |
Downtown | 8 | 44 | 74.04 | 12 |
Residential | 23 | 39 | 73.41 | 13 |
Commercial | 13 | 35 | 72.92 | 14 |
Industrial | 3 | 53 | 67.91 | 15 |
Commercial | 13 | 34 | 66.76 | 16 |
Farmland | 18 | 46 | 66.15 | 17 |
Residential | 23 | 36 | 65.50 | 18 |
Residential | 23 | 38 | 62.66 | 19 |
Farmland | 18 | 47 | 62.13 | 20 |
Residential | 23 | 37 | 61.68 | 21 |
Residential | 23 | 40 | 61.64 | 22 |
Forested | 28 | 58 | 55.1 | 23 |
Forested | 28 | 59 | 55.09 | 24 |
Farmland | 18 | 49 | 54.74 | 25 |
Forested | 28 | 60 | 54.71 | 26 |
Forested | 28 | 56 | 53.83 | 27 |
Forested | 28 | 57 | 53.74 | 28 |
Farmland | 18 | 48 | 53.27 | 29 |
Farmland | 18 | 50 | 51.94 | 30 |
The predicted rankings of sites across Michigan and the actual scores and ranking of images on those sites.
A map of the predicted environmental/visual quality of southern Michigan.
While maps as artifacts are interesting to inspect, we were interested in examining the environmental quality transformation of the environment in our study area, especially the Detroit metropolitan area. The Detroit metropolitan area is in the southeast portion of the study area (Figure 7). The area is comprised of numerous communities with the city of Detroit at its core. The area can be characterized as containing competing communities, distributed, and entrepreneurial. Using the middle-ages as a metaphor, the Detroit metropolitan area can be described as having a weak monarchy and ailing centralized authority (Detroit proper), with strong nobility and robust vassal states (the suburbs). Instead of one dominant business district, there are many competing commercial centers, industrial zones, and visions for urban organization [13, 14, 15, 16]. The expansive metropolitan area is quite vibrant, enterprising, active, and engaging, at the cost of its core. While Detroit proper is suffering, the suburbs are thriving. Visitors to the Detroit metropolitan area are often surprised how normal, active, and busy the suburban communities are, because in the news, the perception is that the area is ailing. However, it is primarily the core that is failing and the rings around the core are thriving. It is in this setting that we desired to examine urban transformation.
We applied our results in this study to a 2008 land-use map of the Detroit metropolitan area, supplied by SEMCOG (Southeast Michigan Council of Governments) [17]. The result was a map of the generalized environmental/visual quality for the Detroit metropolitan region (Figure 9). We then applied our results to a map from the 1800s containing pre-settlement land cover data [18]. This resulted in a map of the generalized and estimated environmental/visual quality from 200 years ago (Figure 10).
A map of the 2008 predicted environmental/visual quality of the seven county Detroit metropolitan area, divide each value by 10 to obtain the correct decimal reading.
A map of the predicted environmental/visual quality of the seven county Detroit metropolitan area for the 1800s, divide each value by 10 to obtain the correct decimal reading.
The values (integers) in the legend for Figures 9 and 10, must be divided by 10 to obtain the environmental quality score (an artifact of the GIS software employed, where no floating point decimal was used). To interpret the scores, Burley notes that scores in the 30s indicate highly preferred environments. Scores in the 50s and 60s are often modestly preferred environments. Scores in the 70 are less preferred and scores near 100 are not preferred [19]. The 95% confidence interval for any scores is +5 points [20]. Thus it takes a separation of 10 points for any pairs of images to be notably different as perceived by respondents.
We subtracted the scores from Figure 9 with the scores from Figure 10, producing Figure 11. This map (Figure 11) represents the expected change environmental/visual quality for the last 200 years. The light gray areas indicate the landscape where the greatest negative change occurred, meaning where the environmental/visual quality became worse. Some areas actually improved in visual quality (Figure 12). The improvement primarily took place on grassland and dunes that become vegetated with woody plants.
A map of change/transformation in environmental/visual quality over 200 years. The light gray areas indicate where the change tended towards less preferred environments. The mid-gray levels indicate no detectible change and the dark gray areas indicate a slight improvement in environmental/visual quality.
A map of change/transformation in environmental/visual quality over 200 years. The blue areas indicate zones with a slight improvement in environmental/visual quality.
The largest transformations (as much as 30 points) came from landscapes that were forested to environments that became industrial areas, downtowns, and large multi-unit housing complexes, often comprising the cliff detritus. Most of the cliff detritus is centered around and in Detroit proper, representing an evolution of transformations as the urban area grew. Cliff detritus allows planners and designers to provide higher densities of human populations and activities. The idea is that creating density is less expensive, offering affordable solutions and preserving more countryside [21]. The problem is that cliff detritus, whether in Paris, France, San Francisco, California, or Detroit, Michigan is considered relatively marginal as a place to live when compared to the Loire River Valley, France, Marin County, California, or Charelvoix, Michigan. The environmental preference models employed in this study only reconfirm the obvious but often unstated. Packing people into less preferred cliff detritus environments may potentially be an inhuman planning and design choice.
Smaller transformations near zero or only modest changes (statistically insignificant transformations), can found in the change from woodland (55) to urban savanna (61) (note the change must be great than 10 points to be statistically notable). Much of the land transformation has been from woodland (55) to agriculture (61) to urban savanna (61). The change actually took place with the felling of trees and installation of agriculture. Transforming the agriculture to urban savanna produced predominantly no change. For us, this in an interesting observation as urban sprawl is often portrayed as an undesirable effect. Yet, urban savanna with its highly diverse and productive gardens are environmentally/visually acceptable, high in wildlife diversity, productive in biomass growth, diverse in vegetation composition, and extensive food production, meaning that the urban savanna has some positive attributes [12, 22]. The urban savanna represents a relatively new and evolving ecology, possibly being equal in value and contribution to greenways and other efforts to preserve natural areas in the urban fabric. We are not proposing the urban savanna replace greenways, rather we are suggesting that the urban savanna has been undervalued. In addition, the pre-settlement landscape of the study area did not consist of landscape with strong visually pleasing environments (scores in the 20s, 30, and 40s) such as those in the American mountain west. Therefore the measured changes from woodland to agriculture to urban savanna were not drastic.
Recently planners, designers, citizens, and public employees have been embracing ideas first presented by Frank Lloyd Wright concerning the distributed and savanna-like character of the urban fabric [23, 24]. Long held notions about transforming landscape into extensive cliff detritus are being reconsidered. Figures 13 and 14 are images from L Corbusier’s project in Rezé-Nantes. Figure 13 scores 73.4 and Figure 14 scores over 110 (the upper limit for the regression line predicting environmental quality). These scores indicate the environment is much less preferred than much of the environment in Detroit. In addition, Figures 15 and 16are images from the tower urbanscape of Shanghai. Figure 15 scores 78.41 and Figure 16 scores 79.12, similar to a score for Figure 13. The expanse of towers is much less preferred than the urban savanna of metropolitan Detroit. The pastoral urban savanna is being given a renewed look. Our study provides some insight into why this fresh approach is being explored in the Detroit Metropolitan area. If these reinventions of the Detroit metropolitan area’s cliff detritus are successful, we could imagine the environmental/visual quality scores of these areas to significantly improve (20 to 30 points) over the next generation. We encourage other investigators to employ this approach to study other areas of the world.
This is an image of the le Corbusier structure in Rezé-Nantes. This building is popular for artists and architect to live within — Copyright © 2012, Jon Bryan Burley, all rights reserved, used by permission.
This is an image of the ground floor area le Corbusier structure in Rezé-Nantes and illustrates the realities of urban structures — Copyright © 2012, Jon Bryan Burley, all rights reserved, used by permission.
A view from an urban dwelling across the shanghai towers — Copyright © 2017, Haoxuan Xu, all rights reserved, used by permission.
Another view of the shanghai urbanscape, even with the sea of urban trees, the image does not score well — Copyright © 2017, Haoxuan Xu, all rights reserved, used by permission.
Predictive, respondent based models have been constructed to measure environmental and visual quality. This work is based upon over 50 years of research by investigators in the social, recreational, and planning and design disciplines/profession. The attributes of the landscape can be measured to form reliable maps of environmental/visual quality, providing a metric to assess landscapes, including urban landscapes. We were able to produce such a metric map for southern Michigan. Then, we applied our approach to study landscape transformation in the Detroit metropolitan area. We discovered that from the 1880s until 2008, much of the area had only modest change from woodland, to agriculture to urban savanna. Some small areas even improved. The predominant areas with degraded environments were in the large cliff detritus complex near and within Detroit. Much of this cliff detritus is being transformed again to resemble a pastoral urban savanna, similar to visions for the urban fabric as originally expressed by Frank Lloyd Wright. Numerous authorities, planners, and designers have developed visions concerning the creation of urban environments, from densely packed skyscrapers to pastoral living spaces. We believe our approach allows investigators to evaluate these visions and assess, measure, and quantify the environmental perceptions of these visions.
Hysterectomy is the surgical procedure to remove the uterus surgically. The word ‘Hysterectomy’ is invented based on Ancient Greek hustéra, “womb” and ektomía-“a cutting out of,” and, thus, means the removal of the uterus. Hysterectomies can be performed by open incision, vaginally, or minimally invasively—either by laparoscopy or robotically. Around 600,000 hysterectomies are performed in the United States annually [1]. Out of them, 85% are for non-cancerous lesions [2]. The traditional open approach to perform hysterectomies involves making a large incision around 10–15 cm above the pubic bone horizontally or vertically. Studies have demonstrated that hysterectomies with open approaches have higher blood loss, increased average length of hospital stay, and more postoperative complications in comparison to minimal invasive approach, including laparoscopic and robotic. The laparoscopic approach has been used for more than three decades and has become standard of care for many gynecological procedures. In 2005, the US Food and Drug Administration approved the use of the da Vinci robotic system for gynecologic surgeries. The use of this technology has allowed surgeons to perform gynecologic procedures with improvements in visualization, including 3D stereoscopic visualization, increased range of motion with enhanced wrist movements, and improved ergonomics with excellent dexterity compared to conventional laparoscopic techniques [3, 4]. However, studies have not shown any difference in operative or postoperative outcomes for patients undergoing robotic hysterectomies compared to laparoscopic hysterectomies [5, 6]. The robotic approach, indeed, has longer operative times [7] for certain operations and is more expensive, not exclusively limited to only operative cost (6–25% more than laparoscopy) [8] but also initial acquisition cost and maintenance cost compared to the standard laparoscopic approach [9]. The da Vinci system requires an initial investment of $1.5 to $2.5 million, depending on the model and configuration. Ongoing costs include annual service contracts (ranging in price from $150 to $170 K), instrument and accessory costs (ranging from $700–$3,500 per procedure).
Despite all shortcomings, surgeons still appreciate excellent visualization providing [6] more precision in surgery and better ergonomics, allowing them to do certain complex tasks, which would be very difficult with standard laparoscopic procedure. Many studies have shown the utility of the robotic platform with better outcomes and safety profiles for various benign conditions, including robotic myomectomies [10] for fibroids, robotic-assisted laparoscopic sacrocolpopexy for pelvic organ prolapse, endometriosis, benign ovarian tumors, etc. [7, 10]. The role of minimally invasive surgery for endometrial cancer has been well established by LAP 2 study [11, 12]. In addition, the role of robotic platform for other gynecological cancer including early cervical and ovarian cancer have been investigated as well [13]. In 2012, the Clinical Practice Robotics Task Force of the Society of Gynecologic Oncology stated that robotic-assisted surgery in the field of gynecology-oncology provides an advantage over traditional methods, including conventional laparoscopic approaches and laparotomies [14]. The use of robotic platform has been well established in many gynecological procedures and in other specialties like general surgery, urology, cardiothoracic surgery, etc. However, with higher acquisition and maintenance costs and with no difference in reimbursement compared to the standard laparoscopic procedure, many small community hospitals that initially acquired a robotic platform by using all cash reserves are struggling to keep it going, and many are rolling back on their decision in 1–3 years [8, 15]. In addition to a higher financial burden, many other factors are roadblocks for widespread implementation or failures of robotic programs. In this article, we would like to expand further on these roadblocks and provide reasonable, evidence-based solutions.
Prior to the acquisition of highly expensive robotic technology, ‘Need Assessment’ is an imperative step for hospitals, especially small community hospitals with limited cash reserve. Despite the rapid rise of robotic surgery, its usefulness, mainly attributed to cost concern in gynecological surgeries, has been questioned by many [16]. However, to compete with the current market and other hospitals, regional hospitals have to enter into a ‘medical arms race” to acquire a robotic platform [17]. Since more and more trainees graduating from residency programs are trained on a robotic platform, small community hospitals view da Vinci as a survival tool to retain and/or recruit surgeons which will keep them in business. It is not an uncommon belief among administrators that a robotic platform can be used as a marketing tool to attract more patients. Medicare in the US helps to absorb the partial cost of robotic systems for critical access hospitals based on the number of the patients on Medicare using those facilities. However, that partial cost may still be too much for the small community hospital with scarce resources to spend. Therefore, they should have to have a thorough ‘need assessment’ to determine whether the purchase of a robotic system is worth a ‘buy.’ ‘Need Assessment’ is a standard industry procedure routinely being carried out in large businesses to analyze the ‘need,’ which is the gap between the current condition and the desired condition. Need assessment to acquire costly surgical instruments is a multistep process [18] including confirmation of necessity or define the need to acquire technology from surgeons based on evidence-based science, research the market, budget, projected rise in revenue, and room for a potential marketing strategy to increase payer mix. It is essential that hospitals should investigate the readiness of their surgeons to get trained, or hospitals should be recruiting new surgeons who are already trained. Many hospitals hire independent agencies to perform market research and viability analysis to find a sweet spot. Regardless, market research involving a rise in case volume by getting new patients who may otherwise travel far to undergo robotic procedure and internal research to determine the proportion of current surgeries which can be performed using a robotic platform are two extremely important data points in decision making. Balancing resource spending and budgeting is an integral part of the financial health of any institution, and, especially, small community hospitals walking on the thin and sharp edge of the sword. In addition to cost-effectiveness, hospitals should focus on hammering down the training program not only limited to surgeons but the entire operating room team. Finally, quite often, a hospital system which acquires the da Vinci should understand that marketing is the key to success for the program [19]. The absence of a marketing plan in place often becomes the reason for the failure of the program [20]. Therefore, research performed well in advance to investigate potential avenues of marketing strategies addressing demography or geographical needs must be well thought out prior to acquiring the system in the need assessment phase. Need Assessment phase is not only limited to investigating and analyzing the need for the da Vinci system (Figure 1) but also the initial planning and strategy development phase, so that when the system is acquired, administration and the entire team have a clear vision and direction of how they will be developing the program moving forward.
Important factors for need assessment.
Teams in the operating room have conventionally been trained in traditional open or laparoscopic surgery where the flow of the surgery is largely directed by surgeons. The mere presence of the da Vinci platform in the operating room changes many aspects of surgery as we know it, including the dynamics of the operating room along with the order of events preoperatively, intraoperatively, and postoperatively. In robotic surgery, the surgeon sits on a robotic console almost 5–10 feet away from the patient. The absence of the surgeon at the patient’s bedside adds additional complexity and anxiety in the operating room among the team members. These new arrangements, including surgeon console, robotic arms, and robotic tower, require an operating room with a surgical team that is well-trained and understands the intricacies that go along with robotic surgeries, as well as the ability to share the burden of problem-solving and troubleshooting any issues that may arise throughout the process. The robotic platform brings unique challenges for the team. For instance, in nonrobotic surgery, surgeons often communicate with their team by signaling or often using not more than a single word [21]. Many a time, assistants understand the need before the surgeon even utters a word. However, in a robotic procedure, communication involves more detailed and clear instructions like pilots communicating with each other or with a control room, and everything needs to be loud and clear. The team needs to be trained to have effective bilateral communication and acknowledgment of all the instructions given by the surgeon or other way around. While traditional surgery has somewhat painted operating rooms as very strict and technical with the surgeon as the chief of events, the robotics platform enforces more of a team approach with a unique chronology of events. Thus, building an efficient team is very crucial for the success of a robotic program. This aspect can often be overlooked by either the hospital administration, the surgeon, or the operating room team. This may be overlooked because the territory of minimally invasive surgery seems familiar, but there remains the aspect of the robotic platform, which is not so familiar including the change in dynamics of the operating room with the integration of robotics. Therefore, the ability to have a successful robotic program depends not only on a surgeon who is well-versed in these technologies and surgical processes, but also a team made of members who feel like they too are an integral part of the robotic program.
Adoption of properly designed curriculum-based training is extremely important. This training should be subjected to all team members, including console surgeon, anesthesiologist, bedside assistance, assistance holding the uterine manipulator, and circulator. Initial training should include set up, docking, undocking, emergency shut down, and both mechanical and electrical troubleshooting [22]. Further training should be procedure-specific, and surgeons need to be involved in training the staff [23]. Some challenges come into play when trying to effectively build a team capable of performing these robotic procedures correctly and efficiently. For one, the surgeon must play the role of both the leader of the surgical procedure along with the leader who can effectively troubleshoot any problems which may arise through the process and can optimize operating with advanced technology. Moreover, the surgical team, including the surgeon and team members, must be willing to embrace this new technology and new approach to surgery after many years of training and practicing in ways that are totally different. A study published in Harvard Business Review by Edmonson compared 16 institutions that employed a minimally invasive approach to cardiac surgery. This study showed that some of these institutions were better able to use their experience for their advantage than others. The study demonstrated that motivation to learn was the most consistent characteristic with the ability to build a successful team, not the conventional predictors like case volume or experience level [24]. Personality traits of members of a successful team are not limited to openness to change, willingness to seek and elicit feedback, and readiness to recognize when they make a mistake. On the contrary, less successful programs employed leaders who were not as open to change and were not as effective at creating an environment conducive to learning. While this study primarily focused on cardiac surgery, the same parameters should apply to gynecologic procedures [25]. Thus, this idea of team building serves as an important cornerstone in the advancement of robotic procedures in the field of gynecologic surgery.
The Institute of Medicine identifies patient safety as one of the key issues that are critical for health care delivery [26]. Changes to practice patterns that are well-established and proven to be effective always raise concerns about how they affect the safety of the patient. The same is true, to maybe an even higher degree, in the process of implementing complex and advanced technologies like robotic-assisted surgical procedures. These concerns come from healthcare personnel in every aspect of the patients’ care, including operating room staff, perioperative nursing staff, anesthesia team members, and many others. While these concerns may be unfounded and unproven, they could affect morale and consequently patient outcomes [27]. Often, many hospitals implement Enhanced Recovery After Surgery (ERAS) program with robotic procedures. Many surgeons discharge robotic hysterectomy in a few hours after surgery. Nursing staff who are traditionally trained to keep minimal invasive surgery patients at least one-night inpatient may feel a little less safe to operate Enhanced Recovery After Surgery (ERAS) program and help to discharge patients home in few hours after major surgery. Studies have found that teamwork and collaboration, meetings to provide opportunities for clarification [28, 29], and staff education [30, 31] are key elements for the success of ERAS, which again supports our argument to develop an adequate culture of safety by proper communications with all stakeholders involved in postoperative care, including patients. Similarly, this has been shown in several studies that have shown that scoring higher on questions about teamwork and better communication/co-ordination is correlated with shorter length of stay and associated postoperative morbidities and mortalities. A study by Hughes et al. highlighted that 40% of US hospital nursing staff think that making changes to make improvements is difficult most of the time or all the time, which is very relevant to the implementation of advanced technologies in medical practice [32]. Recognizing that errors are sometimes inevitable, incorporating nonpunitive error reporting and analysis systems, a platform for open discussion, a willingness to learn from errors, and identifying latent threats are all characteristics of strong cultures of safety.
Three vital organizational factors are responsible for a strong environment of culture of safety: (1) environmental structures and processes within the organization, (2) the attitudes and perceptions of workers, and (3) the safety-related behaviors of individuals [33]. Institute of Medicine (US) Committee on the Work Environment for Nurses and Patient Safety narrated the following essential elements of an effective safety culture. These include a commitment of leadership to safety, empowerment and engagement of all employees in ongoing vigilance, communication, non-hierarchical decision making, constrained improvisation, training, confidential error reporting, fair and just responses to reported errors, reporting near misses as well as errors, etc. [34]. Two major barriers have been identified in adopting culture of safety. First is ‘A nursing culture that fosters unrealistic expectations of clinical perfection.’ Nurses are trained to believe that there is no alternative to clinical perfection, and error is the result of their carelessness that makes them less than good nurses. Higher standards and error-free care are always appreciated, but when that belief becomes counterproductive, it affects the overall care and goals of any program. Therefore, it is imperative to communicate with nurses that error is a systemic problem and not an individual one. Their minds need to be trained not to think any less of their colleagues when they make errors. Second is ‘litigation and regulatory barriers.’ Unfortunately, regulatory boards and the court of law or peer review processes at hospitals again reinforce the idea of clinical perfection. Therefore, it is very difficult for nursing staff to deviate from the routine practice and adopt changes that come with new technology. The culture of safety will play a large role in the outcomes of robotic-assisted surgeries, and therefore, it is both necessary and vital to address the changes that come with the implementation of novel technology. To develop a successful robotic program, it is important to implement frequent reviews of outcomes, multidisciplinary discussions, development of parameter-based new postoperative care protocols, and consideration of recommendations and management strategies from all the team members. This is a crucial part of the process of building a gynecologic surgical robotic program, and it requires commitment from members at all levels in the health care delivery system with a strong sense of culture of safety.
In 1885, German psychologist Herman Ebbinghaus described the concept of the learning curve, saying, “By a sufficient number of repetitions their final mastery is ensured [35]”. In 1936, Wright endorsed the concept of the learning curve by hypothesizing that by increasing production one achieves perfection and, consequently, requires less time to produce aircrafts. Over 1,200 robotic programs have been established across the United States, with over 1,500 gynecologic surgeons being trained in the technology. Along with this training, there obviously comes a learning curve. This phenomenon is well-established with robotic surgery in all specialties, and multiple studies have been published to discuss the learning curve and minimum cases require to surpass the learning curve [36, 37]. The learning curve could be different for surgeons with advanced surgical skills [38] and variable for different portions of the same surgical procedure [39]. Acquisition and maintenance of a robotic program is a costly venture [16]. Not including initial acquisition, robotic hysterectomies cost roughly $2000 more than laparoscopic hysterectomies. This increased cost difference is attributed to the cost of instruments (Intuitive surgical has restricted the number of instruments in use), the costs of operating room time, costs of staffing, costs of training, and costs of personal egos. Out of these, the learning curve certainly accounts for the costs of increased operating room time, costs of personal egos, costs of the number of instruments used, costs associated with complications, etc. Therefore, before adopting a robotic program, surgeons and hospital administration should have proper understanding of the phenomenon of ‘the learning curve,” and its implications on the balance sheet of the hospitals. Typically, the learning curve has been described as an S-curve or sigmoid shape (Figure 2A). The Y-axis represents learning, and the x-axis represents experience. Classical sigmoid behavior represents an initially slow, then rapid, and subsequently slow improvement [40]. In most medical studies of learning curves, the statistical approach discretizes cases into groups and uses standard statistical methods to compare the variables. This methodology provides the statistical significance values, but it is not always the optimal way to assess the learning curve which is a dynamic process in which improvement occurs on a case-to-case basis.
Learning curve. A - S curve; B, C, D - different type of hypothetical CUSUM curve.
A sensitive way to portray surgical failures that are indicative of both the early learning curve and the post-learning curve is the cumulative sum failure analysis (CUSUM) [41, 42, 43]. This technique not only recognizes time as an important, hidden variable in these studies, but it also prevents the decreased statistical significance that can sometimes accompany repeat testing. For these reasons, both the standard statistical method and cumulative sum analysis are recommended to fully assess new teams with accurate and objective feedback. The following formula is used to plot the cumulative sum curve: Sn = Σ(Xi–Xo) where Xi = 0 means success and Xi = 1 means failure. Xo represents the predicted risk of major adverse events. The X-axis portrays the number of cases, while the Y-axis represents the sum of failure. This is shown in the figure (Figure 2B). The line that trends above the baseline portrays the learning curve or a performance that does not meet expectations. Contrarily, the line trending toward or below the baseline portrays the performance that is improving or the post-learning curve, respectively. The line trending below the baseline and away from the baseline shows adequate experience or performance that is either better or equivocal. Examples of these graphs are represented in Figures 2B–D. Figure 2A shows the analysis of a hypothetical CUSUM analysis of any successful procedure as explained above. Figure 2C has a curve above and moving away from the baseline. This could represent an example of either an unsuccessful procedure or a surgeon not passing the learning curve. Figure 2D shows the curve representing either a surgeon with excellent skills from the beginning or having escaped the learning curve that happens when skillful laparoscopic surgeons start performing robotic cases. The assessment of learning not only plays a critical role in development of an effective robotics program to assess the initial learning curve, but it also provides continued monitoring by assessing the state of the learning curve of the entire division from time-to-time which is a critical part of a robotic program [44].
The most important step in acquiring technology is the financial willingness of administration to invest in advanced technology. Therefore, understanding the business model associated with a robotic program is critical. Unlike other industries, the healthcare industry has not experienced a paradigm shift from long-term strategies to transient gain primarily due to the lengthy process that new medical and surgical advancements must undergo to be accepted as a new standard of care. To keep steady profits, companies employ many strategies. One of the strategies is to reduce costs by increasing production and providing the most cost-effective products to market. They often use the theory of “planned obsolescence” [45] by making products with reduced artificial lifespan and, thereby, get repeat sales. One of the most effective strategies is eliminating the competition, so companies can dictate the prices to their buyers. At present, Intuitive Inc. is the only company that produces viable robotic technology approved for human use and unilaterally decides the production cost, maintenance cost, cost of equipment and other accessories, etc. Therefore, administrators have only limited room to save money by reducing operating time, turn-over time, and the costs associated with readmissions and complications. On average, 150 to 300 cases annually are required for at least six years to offset the initial and ongoing costs of the da Vinci System [46]. Figure 3 shows five industry-tested steps are important to understand in implementation of a robotic program from a business standpoint. It is also important for administrators to understand that competitive advantage is not sustainable, and therefore, requires an evolution in business strategies over time. Thus, it is important to both monitor and incentivize the upscaling phase along with maximizing both the exploitation and reconfiguration stages to further optimize return on investment (ROI) in advanced surgical technology.
Five important steps in implementation of a robotic program from business standpoint.
Recently, a study analyzed 180,230 women who underwent laparoscopic or robotic-assisted laparoscopic hysterectomies for either benign or malignant indications (specifically endometrial cancer) from 2006 to 2012 [47]. This study demonstrated that the cost of robotic-assisted hysterectomy remained high, but this cost is offset by increased procedure volume. The use of robotic assisted technology was also found to decrease cost for oncology cases but not in benign gynecological surgeries. The cost difference between hysterectomies performed by three different modalities was analyzed by Bell and colleagues [48]. Data reveals that on average, compared to robotic procedures, the total cost for hysterectomies with staging was approximately 30–40% higher in the procedures completed by laparotomy (P < .005), but robotic was 10% more expensive than laparoscopic surgeries (P=NS). It can be hypothesized that during the phase of the learning curve, there would be major cost burdens associated with the time of the operation, turn over time, initial complications, prolonged hospital stays for some cases, conversions to open laparotomy, and overhead costs associated with the initial cost of acquisition. Due to these increased cost burdens, this would potentially minimize the cost advantage of robotic-assisted surgeries over the traditional laparotomy throughout the learning period.
After studying various case studies and industry best practices, we proposed a three-stage business model for a robotic program: 1) Negative earning, 2) Zero sum, and 3) Positive earnings (Figure 4). The stage of negative earnings coincides with the initial learning curve stage. Hospital administrators should have strategies in place to overcome the expected financial losses during this time. The most important strategies include low-risk case selections (which would typically offer better outcomes and minimize risks of potential losses) and thereby ensuring excellent patient satisfaction (which would lead to popularity and recognition of the program and strengthen the morale of the surgical staff) and continuous monitoring of the learning curve by various parameters such as operating time (used by surgeons), pre-docking and post-docking time (typically used by nursing and anesthesia), turn over time (time required from the end of one case to the beginning of next case), complications, length of stay, etc. In the zero sum stage, transitioning from the learning stage to the experience stage, it should be vital to market the program with positive patient outcomes. Studies have shown [49] that more than 80% of internet users perform research to use information to make decisions regarding their health care choices, especially surgeries. After the learning curve has been conquered and the program is in the stage of positive earning, administrators can expect to acquire advantages such as expanding the payer mix, which will include more private payers in addition to Medicare and Medicaid. Robotic surgery is associated with an early return to work. Private employers may be more likely to appreciate an employee’s early return to work after a surgical procedure. That may provide leverage to hospitals to negotiate contracts that can bring to higher reimbursement for those procedures. Periodically, a review of outcomes and protocols associated with credentialing and recredentialing should always be performed by a multidisciplinary team to maintain safety standards and to avoid ‘negligent credentialing claims’ which has been increasing in the last decades in the court of law [50]. In current, profit-driven health care economics, disciplined planning, efficient strategy, and forecasting business models are the foundation for successful robotic program.
Hypothetical business model demonstrating sensitivity of revenue stream to learning curve.
In conclusion, the adoption of a widespread robotics program for gynecological surgeries has barriers to overcome. The proposed article outlines those barriers and solutions based on literature review and our own experience. It is imperative for hospital administrators and surgeons to understand those barriers to avoid premature frustrations and proper planning for a successful robotic program to avoid the risk of suboptimal patient care and closure of the program before even it starts generating the revenue. With current health care economics, return on investment is an important concept when funds are limited, and, unlike large hospital systems with deep pockets, administrators and surgeons of small community hospital needs to understand above facts and take baby steps accordingly. Robotic platform in gynecology has continued to emerge as a very legitimate challenger to both traditional laparotomy and simple laparoscopic procedures by providing improved ergonomics and maneuvering capabilities. By overcoming the barriers outlined above, there is hope that robotic-assisted procedures will provide another legitimate option to improve outcomes for patients in the future of gynecologic operations.
IntechOpen has always supported new and evolving ideas in scholarly publishing. We understand the community we serve, but to provide an even better service for our IntechOpen Authors and Academic Editors, we have partnered with leading companies and associations in the scientific field and beyond.
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I am also a member of the team in charge for the supervision of Ph.D. students in the fields of development of silicon based planar waveguide sensor devices, study of inelastic electron tunnelling in planar tunnelling nanostructures for sensing applications and development of organotellurium(IV) compounds for semiconductor applications. I am a specialist in data analysis techniques and nanosurface structure. I have served as the editor for many books, been a member of the editorial board in science journals, have published many papers and hold many patents.",institutionString:null,institution:{name:"Sheffield Hallam University",country:{name:"United Kingdom"}}},{id:"12392",title:"Mr.",name:"Alex",middleName:null,surname:"Lazinica",slug:"alex-lazinica",fullName:"Alex Lazinica",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/12392/images/7282_n.png",biography:"Alex Lazinica is the founder and CEO of IntechOpen. 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Today his focus is on defining the growth and development strategy for the company.",institutionString:null,institution:{name:"TU Wien",country:{name:"Austria"}}},{id:"19816",title:"Prof.",name:"Alexander",middleName:null,surname:"Kokorin",slug:"alexander-kokorin",fullName:"Alexander Kokorin",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/19816/images/1607_n.jpg",biography:"Alexander I. Kokorin: born: 1947, Moscow; DSc., PhD; Principal Research Fellow (Research Professor) of Department of Kinetics and Catalysis, N. Semenov Institute of Chemical Physics, Russian Academy of Sciences, Moscow.\r\nArea of research interests: physical chemistry of complex-organized molecular and nanosized systems, including polymer-metal complexes; the surface of doped oxide semiconductors. He is an expert in structural, absorptive, catalytic and photocatalytic properties, in structural organization and dynamic features of ionic liquids, in magnetic interactions between paramagnetic centers. The author or co-author of 3 books, over 200 articles and reviews in scientific journals and books. He is an actual member of the International EPR/ESR Society, European Society on Quantum Solar Energy Conversion, Moscow House of Scientists, of the Board of Moscow Physical Society.",institutionString:null,institution:{name:"Semenov Institute of Chemical Physics",country:{name:"Russia"}}},{id:"62389",title:"PhD.",name:"Ali Demir",middleName:null,surname:"Sezer",slug:"ali-demir-sezer",fullName:"Ali Demir Sezer",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/62389/images/3413_n.jpg",biography:"Dr. Ali Demir Sezer has a Ph.D. from Pharmaceutical Biotechnology at the Faculty of Pharmacy, University of Marmara (Turkey). He is the member of many Pharmaceutical Associations and acts as a reviewer of scientific journals and European projects under different research areas such as: drug delivery systems, nanotechnology and pharmaceutical biotechnology. Dr. Sezer is the author of many scientific publications in peer-reviewed journals and poster communications. Focus of his research activity is drug delivery, physico-chemical characterization and biological evaluation of biopolymers micro and nanoparticles as modified drug delivery system, and colloidal drug carriers (liposomes, nanoparticles etc.).",institutionString:null,institution:{name:"Marmara University",country:{name:"Turkey"}}},{id:"64434",title:"Dr.",name:"Angkoon",middleName:null,surname:"Phinyomark",slug:"angkoon-phinyomark",fullName:"Angkoon Phinyomark",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/64434/images/2619_n.jpg",biography:"My name is Angkoon Phinyomark. I received a B.Eng. degree in Computer Engineering with First Class Honors in 2008 from Prince of Songkla University, Songkhla, Thailand, where I received a Ph.D. degree in Electrical Engineering. My research interests are primarily in the area of biomedical signal processing and classification notably EMG (electromyography signal), EOG (electrooculography signal), and EEG (electroencephalography signal), image analysis notably breast cancer analysis and optical coherence tomography, and rehabilitation engineering. I became a student member of IEEE in 2008. During October 2011-March 2012, I had worked at School of Computer Science and Electronic Engineering, University of Essex, Colchester, Essex, United Kingdom. In addition, during a B.Eng. I had been a visiting research student at Faculty of Computer Science, University of Murcia, Murcia, Spain for three months.\n\nI have published over 40 papers during 5 years in refereed journals, books, and conference proceedings in the areas of electro-physiological signals processing and classification, notably EMG and EOG signals, fractal analysis, wavelet analysis, texture analysis, feature extraction and machine learning algorithms, and assistive and rehabilitative devices. I have several computer programming language certificates, i.e. Sun Certified Programmer for the Java 2 Platform 1.4 (SCJP), Microsoft Certified Professional Developer, Web Developer (MCPD), Microsoft Certified Technology Specialist, .NET Framework 2.0 Web (MCTS). I am a Reviewer for several refereed journals and international conferences, such as IEEE Transactions on Biomedical Engineering, IEEE Transactions on Industrial Electronics, Optic Letters, Measurement Science Review, and also a member of the International Advisory Committee for 2012 IEEE Business Engineering and Industrial Applications and 2012 IEEE Symposium on Business, Engineering and Industrial Applications.",institutionString:null,institution:{name:"Joseph Fourier University",country:{name:"France"}}},{id:"55578",title:"Dr.",name:"Antonio",middleName:null,surname:"Jurado-Navas",slug:"antonio-jurado-navas",fullName:"Antonio Jurado-Navas",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",biography:"Antonio Jurado-Navas received the M.S. degree (2002) and the Ph.D. degree (2009) in Telecommunication Engineering, both from the University of Málaga (Spain). 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The Fourth Industrial Revolution will send a ripple effect of far-reaching repercussions throughout the labor-intensive field of agriculture. Combining artificial intelligence and big data will evolve into a high-tech industry that operates itself. These technologies allow for precision agriculture, such as yield monitoring, diagnosing insect pests, measuring soil moisture, diagnosing harvest time, and monitoring crop health status. In particular, the Internet of things (IoT) will measure the temperature, humidity, and amount of sunlight in production farms, making it possible for remote control via mobile devices. It will not only boost the production of the farms but also add to their value.",book:{id:"6265",slug:"automation-in-agriculture-securing-food-supplies-for-future-generations",title:"Automation in Agriculture",fullTitle:"Automation in Agriculture - Securing Food Supplies for Future Generations"},signatures:"Jehoon Sung",authors:[{id:"210240",title:"Dr.",name:"Jehoon",middleName:null,surname:"Sung",slug:"jehoon-sung",fullName:"Jehoon Sung"}]},{id:"59242",doi:"10.5772/intechopen.73622",title:"Review of Variable-Rate Sprayer Applications Based on Real- Time Sensor Technologies",slug:"review-of-variable-rate-sprayer-applications-based-on-real-time-sensor-technologies",totalDownloads:2079,totalCrossrefCites:12,totalDimensionsCites:15,abstract:"Precision variable rate spray is one of the research hotspots in the field of modern agriculture spraying applications. Variable rate spraying of the canopy allows growers to apply adjusted volume rate of pesticides to the target, based on canopy size, and to apply plant protection products in an economical and environmentally sound manner. In the field of pesticide application, knowledge of the geometrical characteristics of plantations will guarantee a better adjustment of the dosage of the agrochemicals applied. This technology is integrated with intelligent real-time sensors, which have a high potential for agricultural precision spray applications. This book chapter presents the foundations and applications in agriculture of the primary systems used for real-time spray target detection of the geometrical characterization of tree plantations. Systems based on infrared, ultrasonic, light detection and ranging (LIDAR), and stereo vision sensors were discussed, respectively, on their performances to detect spray targets. Among them, laser scanners and stereo vision systems are probably the most promising and complementary techniques for achieving three-dimensional (3D) pictures and maps of plants and canopies. The advantages of data fusion applied in real-time target detection and its accuracy in density estimation of the plants were stressed.",book:{id:"6265",slug:"automation-in-agriculture-securing-food-supplies-for-future-generations",title:"Automation in Agriculture",fullTitle:"Automation in Agriculture - Securing Food Supplies for Future Generations"},signatures:"Zhihong Zhang, Xiaoyang Wang, Qinghui Lai and Zhaoguo Zhang",authors:[{id:"227982",title:"Dr.",name:"Zhihong",middleName:null,surname:"Zhang",slug:"zhihong-zhang",fullName:"Zhihong Zhang"},{id:"239622",title:"Mr.",name:"Xiaoyang",middleName:null,surname:"Wang",slug:"xiaoyang-wang",fullName:"Xiaoyang Wang"},{id:"239624",title:"Prof.",name:"Qinghui",middleName:null,surname:"Lai",slug:"qinghui-lai",fullName:"Qinghui Lai"},{id:"239625",title:"Prof.",name:"Zhaoguo",middleName:null,surname:"Zhang",slug:"zhaoguo-zhang",fullName:"Zhaoguo Zhang"}]},{id:"71024",doi:"10.5772/intechopen.91133",title:"Implication of Urban Agriculture and Vertical Farming for Future Sustainability",slug:"implication-of-urban-agriculture-and-vertical-farming-for-future-sustainability",totalDownloads:1850,totalCrossrefCites:5,totalDimensionsCites:9,abstract:"Urban agriculture (UA) is defined as the production of agricultural goods (crop) and livestock goods within urban areas like cities and towns. In the modern days, the urbanization process has raised a question on the sustainable development and growing of urban population. UA has been claimed to contribute to urban waste recycling, efficient water use and energy conservation, reduction in air pollution and soil erosion, urban beautification, climate change adaptation and resilience, disaster prevention, and ecological and social urban sustainability. Therefore, UA contributes to the sustainability of cities in various ways—socially, economically, and environmentally. An urban farming technology that involves the large-scale agricultural production in the urban surroundings is the vertical farming (VF) or high-rise farming technology. It enables fast growth and production of the crops by maintaining the environmental conditions and nutrient solutions to crop based on hydroponics technology. Vertical farms are able to grow food year-round because they maintain consistent growing conditions regardless of the weather outside and are much less vulnerable to climate changes. This promises a steady flow of products for the consumers and a consistent income for growers. Various advantages of VF over traditional farming, such as reduced farm inputs and crop failures and restored farmland, have enabled scientists to implement VF on a large scale.",book:{id:"8939",slug:"urban-horticulture-necessity-of-the-future",title:"Urban Horticulture",fullTitle:"Urban Horticulture - Necessity of the Future"},signatures:"Anwesha Chatterjee, Sanjit Debnath and Harshata Pal",authors:[{id:"312477",title:"Dr.",name:"Harshata",middleName:null,surname:"Pal",slug:"harshata-pal",fullName:"Harshata Pal"},{id:"316680",title:"Dr.",name:"Anwesha",middleName:null,surname:"Chatterjee",slug:"anwesha-chatterjee",fullName:"Anwesha Chatterjee"},{id:"316681",title:"Dr.",name:"Sanjit",middleName:null,surname:"Debnath",slug:"sanjit-debnath",fullName:"Sanjit Debnath"}]},{id:"64696",doi:"10.5772/intechopen.82450",title:"Date Palm Value Chain Analysis and Marketing Opportunities for the Gulf Cooperation Council (GCC) Countries",slug:"date-palm-value-chain-analysis-and-marketing-opportunities-for-the-gulf-cooperation-council-gcc-coun",totalDownloads:3554,totalCrossrefCites:3,totalDimensionsCites:7,abstract:"In order to develop a sustainable date palm production system in the Gulf Cooperation Council (GCC) countries of the Arabian Peninsula, an analysis of the date value chain in these countries was undertaken. Through the mapping of the chain, the overall objective was to identify the processes where values are created and how they are distributed among stakeholders along the entire date palm value chain. The method used in this analysis was based on an assessment of the data gathered from the multi-stakeholder surveys implemented in the three case studies of the GCC countries: Kingdom of Saudi Arabia (KSA), Oman, and Kuwait. The empirical findings reveal several problems and constraints that might affect the future of the GCC date palm sector. Therefore, development of a competitive supply date palm chain (both market and agribusiness development) could provide a greater contribution to the GCC economy if producers paid more attention to marketing of this very important food commodity. Hence, date palm production is no longer a way of life but nowadays is considered as an investment option and source of revenues for many stakeholders if the GCC region.",book:{id:"8308",slug:"agricultural-economics-current-issues",title:"Agricultural Economics",fullTitle:"Agricultural Economics - Current Issues"},signatures:"Boubaker Dhehibi, Mohamed Ben Salah and Aymen Frija",authors:[{id:"197434",title:"Dr.",name:"Boubaker",middleName:null,surname:"Dhehibi",slug:"boubaker-dhehibi",fullName:"Boubaker Dhehibi"},{id:"268347",title:"Dr.",name:"Mohamed",middleName:null,surname:"Ben Salah",slug:"mohamed-ben-salah",fullName:"Mohamed Ben Salah"},{id:"268348",title:"Dr.",name:"Aymen",middleName:null,surname:"Frija",slug:"aymen-frija",fullName:"Aymen Frija"}]},{id:"59402",doi:"10.5772/intechopen.73861",title:"Robotic Harvesting of Fruiting Vegetables: A Simulation Approach in V-REP, ROS and MATLAB",slug:"robotic-harvesting-of-fruiting-vegetables-a-simulation-approach-in-v-rep-ros-and-matlab",totalDownloads:2786,totalCrossrefCites:6,totalDimensionsCites:7,abstract:"In modern agriculture, there is a high demand to move from tedious manual harvesting to a continuously automated operation. This chapter reports on designing a simulation and control platform in V-REP, ROS, and MATLAB for experimenting with sensors and manipulators in robotic harvesting of sweet pepper. The objective was to provide a completely simulated environment for improvement of visual servoing task through easy testing and debugging of control algorithms with zero damage risk to the real robot and to the actual equipment. A simulated workspace, including an exact replica of different robot manipulators, sensing mechanisms, and sweet pepper plant, and fruit system was created in V-REP. Image moment method visual servoing with eye-in-hand configuration was implemented in MATLAB, and was tested on four robotic platforms including Fanuc LR Mate 200iD, NOVABOT, multiple linear actuators, and multiple SCARA arms. Data from simulation experiments were used as inputs of the control algorithm in MATLAB, whose outputs were sent back to the simulated workspace and to the actual robots. ROS was used for exchanging data between the simulated environment and the real workspace via its publish-and-subscribe architecture. Results provided a framework for experimenting with different sensing and acting scenarios, and verified the performance functionality of the simulator.",book:{id:"6265",slug:"automation-in-agriculture-securing-food-supplies-for-future-generations",title:"Automation in Agriculture",fullTitle:"Automation in Agriculture - Securing Food Supplies for Future Generations"},signatures:"Redmond R. Shamshiri, Ibrahim A. Hameed, Manoj Karkee and\nCornelia Weltzien",authors:[{id:"182449",title:"Prof.",name:"Ibrahim",middleName:"A.",surname:"Hameed",slug:"ibrahim-hameed",fullName:"Ibrahim Hameed"},{id:"203413",title:"Dr.",name:"Redmond R.",middleName:null,surname:"Shamshiri",slug:"redmond-r.-shamshiri",fullName:"Redmond R. Shamshiri"},{id:"241193",title:"Dr.",name:"Manoj",middleName:null,surname:"Karkee",slug:"manoj-karkee",fullName:"Manoj Karkee"},{id:"241194",title:"Dr.",name:"Cornelia",middleName:null,surname:"Weltzien",slug:"cornelia-weltzien",fullName:"Cornelia Weltzien"}]}],mostDownloadedChaptersLast30Days:[{id:"59402",title:"Robotic Harvesting of Fruiting Vegetables: A Simulation Approach in V-REP, ROS and MATLAB",slug:"robotic-harvesting-of-fruiting-vegetables-a-simulation-approach-in-v-rep-ros-and-matlab",totalDownloads:2786,totalCrossrefCites:6,totalDimensionsCites:7,abstract:"In modern agriculture, there is a high demand to move from tedious manual harvesting to a continuously automated operation. This chapter reports on designing a simulation and control platform in V-REP, ROS, and MATLAB for experimenting with sensors and manipulators in robotic harvesting of sweet pepper. The objective was to provide a completely simulated environment for improvement of visual servoing task through easy testing and debugging of control algorithms with zero damage risk to the real robot and to the actual equipment. A simulated workspace, including an exact replica of different robot manipulators, sensing mechanisms, and sweet pepper plant, and fruit system was created in V-REP. Image moment method visual servoing with eye-in-hand configuration was implemented in MATLAB, and was tested on four robotic platforms including Fanuc LR Mate 200iD, NOVABOT, multiple linear actuators, and multiple SCARA arms. Data from simulation experiments were used as inputs of the control algorithm in MATLAB, whose outputs were sent back to the simulated workspace and to the actual robots. ROS was used for exchanging data between the simulated environment and the real workspace via its publish-and-subscribe architecture. Results provided a framework for experimenting with different sensing and acting scenarios, and verified the performance functionality of the simulator.",book:{id:"6265",slug:"automation-in-agriculture-securing-food-supplies-for-future-generations",title:"Automation in Agriculture",fullTitle:"Automation in Agriculture - Securing Food Supplies for Future Generations"},signatures:"Redmond R. Shamshiri, Ibrahim A. Hameed, Manoj Karkee and\nCornelia Weltzien",authors:[{id:"182449",title:"Prof.",name:"Ibrahim",middleName:"A.",surname:"Hameed",slug:"ibrahim-hameed",fullName:"Ibrahim Hameed"},{id:"203413",title:"Dr.",name:"Redmond R.",middleName:null,surname:"Shamshiri",slug:"redmond-r.-shamshiri",fullName:"Redmond R. Shamshiri"},{id:"241193",title:"Dr.",name:"Manoj",middleName:null,surname:"Karkee",slug:"manoj-karkee",fullName:"Manoj Karkee"},{id:"241194",title:"Dr.",name:"Cornelia",middleName:null,surname:"Weltzien",slug:"cornelia-weltzien",fullName:"Cornelia Weltzien"}]},{id:"70662",title:"Automation and Robotics Used in Hydroponic System",slug:"automation-and-robotics-used-in-hydroponic-system",totalDownloads:2809,totalCrossrefCites:1,totalDimensionsCites:2,abstract:"Hydroponic system requires periodic labor, a systematic approach, repetitive motion and a structured environment. Automation, robotics and IoT have allowed farmers to monitoring all the variables in plant, root zone and environment under hydroponics. This research introduces findings in design with real time operating systems based on microcontrollers; pH fuzzy logic control system for nutrient solution in embed and flow hydroponic culture; hydroponic system in combination with automated drip irrigation; expert system-based automation system; automated hydroponics nutrition plants systems; hydroponic management and monitoring system for an intelligent hydroponic system using internet of things and web technology; neural network-based fault detection in hydroponics; additional technologies implemented in hydroponic systems and robotics in hydroponic systems. The above advances will improve the efficiency of hydroponics to increase the quality and quantity of the produce and pose an opportunity for the growth of the hydroponics market in near future.",book:{id:"8939",slug:"urban-horticulture-necessity-of-the-future",title:"Urban Horticulture",fullTitle:"Urban Horticulture - Necessity of the Future"},signatures:"Alejandro Isabel Luna Maldonado, Julia Mariana Márquez Reyes, Héctor Flores Breceda, Humberto Rodríguez Fuentes, Juan Antonio Vidales Contreras and Urbano Luna Maldonado",authors:[{id:"105774",title:"Prof.",name:"Alejandro Isabel",middleName:null,surname:"Luna Maldonado",slug:"alejandro-isabel-luna-maldonado",fullName:"Alejandro Isabel Luna Maldonado"},{id:"215230",title:"Dr.",name:"Juan Antonio",middleName:null,surname:"Vidales Contreras",slug:"juan-antonio-vidales-contreras",fullName:"Juan Antonio Vidales Contreras"},{id:"220744",title:"MSc.",name:"Héctor",middleName:null,surname:"Flores Breceda",slug:"hector-flores-breceda",fullName:"Héctor Flores Breceda"},{id:"252026",title:"Dr.",name:"Humberto",middleName:null,surname:"Rodríguez-Fuentes",slug:"humberto-rodriguez-fuentes",fullName:"Humberto Rodríguez-Fuentes"},{id:"299825",title:"Dr.",name:"Julia Mariana",middleName:null,surname:"Márquez Reyes",slug:"julia-mariana-marquez-reyes",fullName:"Julia Mariana Márquez Reyes"},{id:"303920",title:"Prof.",name:"Urbano",middleName:null,surname:"Luna Maldonado",slug:"urbano-luna-maldonado",fullName:"Urbano Luna Maldonado"}]},{id:"77112",title:"Advancements of Spraying Technology in Agriculture",slug:"advancements-of-spraying-technology-in-agriculture",totalDownloads:639,totalCrossrefCites:1,totalDimensionsCites:1,abstract:"Plant protection activities are most important practices during crop production. Application of maximum pesticide products with the sprayer. The application of fungicides, herbicides, and insecticides is one of the most recurrent and significant tasks in agriculture. Conventional agricultural spraying techniques have made the inconsistency between economic growth and environmental protection in agricultural production. Spraying techniques continuously developed in recent decades. For pesticide application, it is not the only sprayer that is essential, but all the parameters like the type and area of the plant canopy, area of a plant leaf, height of the crop, and volume of plants related to plant protection product applications are very important for obtaining better results. From this point of view, the advancement in agriculture sprayer has been started in last few decades. Robotics and automatic spraying technologies like variable rate sprayers, UAV sprayers, and electrostatic sprayers are growing to Increase the utilization rate of pesticides, reduce pesticide residues, real-time, cost-saving, high compatibility of plant protection products application. These technologies are under the “umbrella” of precision agriculture. The mechanized spraying system, usually implemented by highly precise equipment or mobile robots, which, makes possible the selective targeting of pesticide application on desire time and place. These advanced spraying technologies not only reduces the labour cost but also effective in environmental protection. Researchers are conducting experimental studies on the design, development and testing of precision spraying technologies for crops and orchards.",book:{id:"10454",slug:"technology-in-agriculture",title:"Technology in Agriculture",fullTitle:"Technology in Agriculture"},signatures:"Fiaz Ahmad, Aftab Khaliq, Baijing Qiu, Muhammad Sultan and Jing Ma",authors:[{id:"199381",title:"Prof.",name:"Muhammad",middleName:null,surname:"Sultan",slug:"muhammad-sultan",fullName:"Muhammad Sultan"},{id:"338219",title:"Dr.",name:"Fiaz",middleName:null,surname:"Ahmad",slug:"fiaz-ahmad",fullName:"Fiaz Ahmad"},{id:"346652",title:"MSc.",name:"Aftab",middleName:null,surname:"Khaliq",slug:"aftab-khaliq",fullName:"Aftab Khaliq"},{id:"349757",title:"Prof.",name:"Qiu",middleName:null,surname:"Baijing",slug:"qiu-baijing",fullName:"Qiu Baijing"},{id:"349778",title:"Dr.",name:"Jing",middleName:null,surname:"Ma",slug:"jing-ma",fullName:"Jing Ma"}]},{id:"77058",title:"Solar Technology in Agriculture",slug:"solar-technology-in-agriculture",totalDownloads:627,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Promotion of sustainable agriculture is one of the most priority development goal set by United Nations for achieving the food security to meet the ever-increasing global population food demand. Because of extreme importance of agriculture sector, significant technological developments have been made that played pivotal role for sustainable agriculture by value addition in agricultural products and meeting energy demands for machinery and irrigation. These developments include improved cultivation practices, processing units for agricultural products and operation of machinery and irrigation systems based on solar energy. Moreover, the emergence of new technologies and climate smart solutions with reduced carbon footprints have significantly addressed the ever-increasing fuel costs and changing climate needs. PV based solar irrigation pumps and agricultural machinery is typical example of this. Because, awareness of these technological development is essential to overcome energy issues, availability of energy to perform agricultural activities for sustainable agriculture at farm level and socioeconomic uplift of farming community to meet food requirements needs in the future. Therefore, this chapter attempts at providing the introduction of technologies for direct and indirect use of solar energy in the agriculture sector. The typical examples of direct use of solar energy like greenhouses or tunnel farming for cultivation of crops and vegetables and use of solar dryers for drying agricultural products have been comprehensively discussed. Similarly, the solar powered tubewells, tractors, and lights, etc. are few important examples of indirect use of solar energy and have also been discussed in this chapter. The indirect use is made possible by converting solar energy into electrical energy with the help of photovoltaic devices, called “solar cells”. Also radio frequency (RF)-controlled seed sowing and spreading machines are discussed, which provide an eco-friendly method. Moreover, comprehensive discussion is made on solar based technologies in general as well regional context in view of their potential to scale-up and to address anticipated issues. The use of photovoltaics in agriculture is expected to be significant contribution in the near future that require urgent planning for the potential benefits and efficient use at the farm level. Therefore, the co-existence of “agrovoltaics” will be essential for the developments of agriculture and agroindustry.",book:{id:"10454",slug:"technology-in-agriculture",title:"Technology in Agriculture",fullTitle:"Technology in Agriculture"},signatures:"Ghulam Hasnain Tariq, Muhammad Ashraf and Umar Sohaib Hasnain",authors:[{id:"324017",title:"Dr.",name:"Muhammad",middleName:null,surname:"Ashraf",slug:"muhammad-ashraf",fullName:"Muhammad Ashraf"},{id:"343829",title:"Dr.",name:"Ghulam Hasnain",middleName:null,surname:"Tariq",slug:"ghulam-hasnain-tariq",fullName:"Ghulam Hasnain Tariq"},{id:"415545",title:"Mr.",name:"Umar Sohaib",middleName:null,surname:"Hasnain",slug:"umar-sohaib-hasnain",fullName:"Umar Sohaib Hasnain"}]},{id:"79822",title:"Stored Grain Pests and Current Advances for Their Management",slug:"stored-grain-pests-and-current-advances-for-their-management",totalDownloads:253,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"During the offseason, when fresh food is not available, humans have to consume stored grain food. Unfortunately, these stored grains are later infested with many pests. Foods stored in bags and bins are very much susceptible to infestation with several pests which can cause extensive post-harvest losses, spoilage, and less demand in markets, causing a huge economic crisis. Hence, successful management of stored grain pests becomes necessary to prevent these from insect pests. Current approaches for their management are one of the promising goals, as it includes preventive practices, monitoring, sanitation, and identification of main pathogens. Different management strategies of all the common stored grain pests viz. grain weevils, grain borers, grain moths, flour moths, mealworms, grain and flour beetles, booklice, mites, and parasites are enlisted here.",book:{id:"10899",slug:"postharvest-technology-recent-advances-new-perspectives-and-applications",title:"Postharvest Technology",fullTitle:"Postharvest Technology - Recent Advances, New Perspectives and Applications"},signatures:"Rayees Ahmad, Shafiya Hassan, Showkat Ahmad, Syed Nighat, Yendrambamb K. Devi, Kounser Javeed, Salma Usmani, Mohammad Javed Ansari, Sait Erturk, Mustafa Alkan and Barkat Hussain",authors:[{id:"319667",title:"Dr.",name:"Barkat",middleName:null,surname:"Hussain",slug:"barkat-hussain",fullName:"Barkat Hussain"},{id:"444975",title:"Dr.",name:"Rayees",middleName:null,surname:"Ahmad",slug:"rayees-ahmad",fullName:"Rayees Ahmad"},{id:"444976",title:"Dr.",name:"Shafiya",middleName:null,surname:"Hassan",slug:"shafiya-hassan",fullName:"Shafiya Hassan"},{id:"444977",title:"Dr.",name:"Showkat",middleName:null,surname:"Ahmad",slug:"showkat-ahmad",fullName:"Showkat Ahmad"},{id:"444978",title:"Dr.",name:"Syed",middleName:null,surname:"Nighat",slug:"syed-nighat",fullName:"Syed Nighat"},{id:"444979",title:"Dr.",name:"Yendrambamb",middleName:null,surname:"K. Devi",slug:"yendrambamb-k.-devi",fullName:"Yendrambamb K. Devi"},{id:"444980",title:"Dr.",name:"Kounser",middleName:null,surname:"Javeed",slug:"kounser-javeed",fullName:"Kounser Javeed"},{id:"444981",title:"Dr.",name:"Salma",middleName:null,surname:"Usmani",slug:"salma-usmani",fullName:"Salma Usmani"},{id:"444982",title:"Dr.",name:"Mohd Javid",middleName:null,surname:"Ansari",slug:"mohd-javid-ansari",fullName:"Mohd Javid Ansari"},{id:"444983",title:"Dr.",name:"Sait",middleName:null,surname:"Erturk",slug:"sait-erturk",fullName:"Sait Erturk"},{id:"444984",title:"Dr.",name:"Mustafa",middleName:null,surname:"Alkan",slug:"mustafa-alkan",fullName:"Mustafa Alkan"}]}],onlineFirstChaptersFilter:{topicId:"26",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:87,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:99,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:27,numberOfPublishedChapters:289,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:9,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:139,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:129,numberOfOpenTopics:0,numberOfUpcomingTopics:2,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!1},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:108,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:104,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:12,numberOfOpenTopics:2,numberOfUpcomingTopics:1,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:0,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!1},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:12,numberOfOpenTopics:4,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}},{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}}]},series:{item:{id:"14",title:"Artificial Intelligence",doi:"10.5772/intechopen.79920",issn:"2633-1403",scope:"Artificial Intelligence (AI) is a rapidly developing multidisciplinary research area that aims to solve increasingly complex problems. In today's highly integrated world, AI promises to become a robust and powerful means for obtaining solutions to previously unsolvable problems. This Series is intended for researchers and students alike interested in this fascinating field and its many applications.",coverUrl:"https://cdn.intechopen.com/series/covers/14.jpg",latestPublicationDate:"May 18th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:9,editor:{id:"218714",title:"Prof.",name:"Andries",middleName:null,surname:"Engelbrecht",slug:"andries-engelbrecht",fullName:"Andries Engelbrecht",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRNR8QAO/Profile_Picture_1622640468300",biography:"Andries Engelbrecht received the Masters and PhD degrees in Computer Science from the University of Stellenbosch, South Africa, in 1994 and 1999 respectively. He is currently appointed as the Voigt Chair in Data Science in the Department of Industrial Engineering, with a joint appointment as Professor in the Computer Science Division, Stellenbosch University. Prior to his appointment at Stellenbosch University, he has been at the University of Pretoria, Department of Computer Science (1998-2018), where he was appointed as South Africa Research Chair in Artifical Intelligence (2007-2018), the head of the Department of Computer Science (2008-2017), and Director of the Institute for Big Data and Data Science (2017-2018). In addition to a number of research articles, he has written two books, Computational Intelligence: An Introduction and Fundamentals of Computational Swarm Intelligence.",institutionString:null,institution:{name:"Stellenbosch University",institutionURL:null,country:{name:"South Africa"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:6,paginationItems:[{id:"22",title:"Applied Intelligence",coverUrl:"https://cdn.intechopen.com/series_topics/covers/22.jpg",isOpenForSubmission:!0,annualVolume:11418,editor:{id:"27170",title:"Prof.",name:"Carlos",middleName:"M.",surname:"Travieso-Gonzalez",slug:"carlos-travieso-gonzalez",fullName:"Carlos Travieso-Gonzalez",profilePictureURL:"https://mts.intechopen.com/storage/users/27170/images/system/27170.jpeg",biography:"Carlos M. Travieso-González received his MSc degree in Telecommunication Engineering at Polytechnic University of Catalonia (UPC), Spain in 1997, and his Ph.D. degree in 2002 at the University of Las Palmas de Gran Canaria (ULPGC-Spain). He is a full professor of signal processing and pattern recognition and is head of the Signals and Communications Department at ULPGC, teaching from 2001 on subjects on signal processing and learning theory. His research lines are biometrics, biomedical signals and images, data mining, classification system, signal and image processing, machine learning, and environmental intelligence. He has researched in 52 international and Spanish research projects, some of them as head researcher. He is co-author of 4 books, co-editor of 27 proceedings books, guest editor for 8 JCR-ISI international journals, and up to 24 book chapters. He has over 450 papers published in international journals and conferences (81 of them indexed on JCR – ISI - Web of Science). He has published seven patents in the Spanish Patent and Trademark Office. He has been a supervisor on 8 Ph.D. theses (11 more are under supervision), and 130 master theses. He is the founder of The IEEE IWOBI conference series and the president of its Steering Committee, as well as the founder of both the InnoEducaTIC and APPIS conference series. He is an evaluator of project proposals for the European Union (H2020), Medical Research Council (MRC, UK), Spanish Government (ANECA, Spain), Research National Agency (ANR, France), DAAD (Germany), Argentinian Government, and the Colombian Institutions. He has been a reviewer in different indexed international journals (<70) and conferences (<250) since 2001. He has been a member of the IASTED Technical Committee on Image Processing from 2007 and a member of the IASTED Technical Committee on Artificial Intelligence and Expert Systems from 2011. \n\nHe has held the general chair position for the following: ACM-APPIS (2020, 2021), IEEE-IWOBI (2019, 2020 and 2020), A PPIS (2018, 2019), IEEE-IWOBI (2014, 2015, 2017, 2018), InnoEducaTIC (2014, 2017), IEEE-INES (2013), NoLISP (2011), JRBP (2012), and IEEE-ICCST (2005)\n\nHe is an associate editor of the Computational Intelligence and Neuroscience Journal (Hindawi – Q2 JCR-ISI). He was vice dean from 2004 to 2010 in the Higher Technical School of Telecommunication Engineers at ULPGC and the vice dean of Graduate and Postgraduate Studies from March 2013 to November 2017. He won the “Catedra Telefonica” Awards in Modality of Knowledge Transfer, 2017, 2018, and 2019 editions, and awards in Modality of COVID Research in 2020.\n\nPublic References:\nResearcher ID http://www.researcherid.com/rid/N-5967-2014\nORCID https://orcid.org/0000-0002-4621-2768 \nScopus Author ID https://www.scopus.com/authid/detail.uri?authorId=6602376272\nScholar Google https://scholar.google.es/citations?user=G1ks9nIAAAAJ&hl=en \nResearchGate https://www.researchgate.net/profile/Carlos_Travieso",institutionString:null,institution:{name:"University of Las Palmas de Gran Canaria",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"23",title:"Computational Neuroscience",coverUrl:"https://cdn.intechopen.com/series_topics/covers/23.jpg",isOpenForSubmission:!0,annualVolume:11419,editor:{id:"14004",title:"Dr.",name:"Magnus",middleName:null,surname:"Johnsson",slug:"magnus-johnsson",fullName:"Magnus Johnsson",profilePictureURL:"https://mts.intechopen.com/storage/users/14004/images/system/14004.png",biography:"Dr Magnus Johnsson is a cross-disciplinary scientist, lecturer, scientific editor and AI/machine learning consultant from Sweden. \n\nHe is currently at Malmö University in Sweden, but also held positions at Lund University in Sweden and at Moscow Engineering Physics Institute. \nHe holds editorial positions at several international scientific journals and has served as a scientific editor for books and special journal issues. \nHis research interests are wide and include, but are not limited to, autonomous systems, computer modeling, artificial neural networks, artificial intelligence, cognitive neuroscience, cognitive robotics, cognitive architectures, cognitive aids and the philosophy of mind. \n\nDr. Johnsson has experience from working in the industry and he has a keen interest in the application of neural networks and artificial intelligence to fields like industry, finance, and medicine. \n\nWeb page: www.magnusjohnsson.se",institutionString:null,institution:{name:"Malmö University",institutionURL:null,country:{name:"Sweden"}}},editorTwo:null,editorThree:null},{id:"24",title:"Computer Vision",coverUrl:"https://cdn.intechopen.com/series_topics/covers/24.jpg",isOpenForSubmission:!0,annualVolume:11420,editor:{id:"294154",title:"Prof.",name:"George",middleName:null,surname:"Papakostas",slug:"george-papakostas",fullName:"George Papakostas",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002hYaGbQAK/Profile_Picture_1624519712088",biography:"George A. Papakostas has received a diploma in Electrical and Computer Engineering in 1999 and the M.Sc. and Ph.D. degrees in Electrical and Computer Engineering in 2002 and 2007, respectively, from the Democritus University of Thrace (DUTH), Greece. Dr. Papakostas serves as a Tenured Full Professor at the Department of Computer Science, International Hellenic University, Greece. Dr. Papakostas has 10 years of experience in large-scale systems design as a senior software engineer and technical manager, and 20 years of research experience in the field of Artificial Intelligence. Currently, he is the Head of the “Visual Computing” division of HUman-MAchines INteraction Laboratory (HUMAIN-Lab) and the Director of the MPhil program “Advanced Technologies in Informatics and Computers” hosted by the Department of Computer Science, International Hellenic University. He has (co)authored more than 150 publications in indexed journals, international conferences and book chapters, 1 book (in Greek), 3 edited books, and 5 journal special issues. His publications have more than 2100 citations with h-index 27 (GoogleScholar). His research interests include computer/machine vision, machine learning, pattern recognition, computational intelligence. \nDr. Papakostas served as a reviewer in numerous journals, as a program\ncommittee member in international conferences and he is a member of the IAENG, MIR Labs, EUCogIII, INSTICC and the Technical Chamber of Greece (TEE).",institutionString:null,institution:{name:"International Hellenic University",institutionURL:null,country:{name:"Greece"}}},editorTwo:null,editorThree:null},{id:"25",title:"Evolutionary Computation",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",isOpenForSubmission:!0,annualVolume:11421,editor:{id:"136112",title:"Dr.",name:"Sebastian",middleName:null,surname:"Ventura Soto",slug:"sebastian-ventura-soto",fullName:"Sebastian Ventura Soto",profilePictureURL:"https://mts.intechopen.com/storage/users/136112/images/system/136112.png",biography:"Sebastian Ventura is a Spanish researcher, a full professor with the Department of Computer Science and Numerical Analysis, University of Córdoba. Dr Ventura also holds the positions of Affiliated Professor at Virginia Commonwealth University (Richmond, USA) and Distinguished Adjunct Professor at King Abdulaziz University (Jeddah, Saudi Arabia). Additionally, he is deputy director of the Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) and heads the Knowledge Discovery and Intelligent Systems Research Laboratory. He has published more than ten books and over 300 articles in journals and scientific conferences. Currently, his work has received over 18,000 citations according to Google Scholar, including more than 2200 citations in 2020. In the last five years, he has published more than 60 papers in international journals indexed in the JCR (around 70% of them belonging to first quartile journals) and he has edited some Springer books “Supervised Descriptive Pattern Mining” (2018), “Multiple Instance Learning - Foundations and Algorithms” (2016), and “Pattern Mining with Evolutionary Algorithms” (2016). He has also been involved in more than 20 research projects supported by the Spanish and Andalusian governments and the European Union. He currently belongs to the editorial board of PeerJ Computer Science, Information Fusion and Engineering Applications of Artificial Intelligence journals, being also associate editor of Applied Computational Intelligence and Soft Computing and IEEE Transactions on Cybernetics. Finally, he is editor-in-chief of Progress in Artificial Intelligence. He is a Senior Member of the IEEE Computer, the IEEE Computational Intelligence, and the IEEE Systems, Man, and Cybernetics Societies, and the Association of Computing Machinery (ACM). Finally, his main research interests include data science, computational intelligence, and their applications.",institutionString:null,institution:{name:"University of Córdoba",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"26",title:"Machine Learning and Data Mining",coverUrl:"https://cdn.intechopen.com/series_topics/covers/26.jpg",isOpenForSubmission:!0,annualVolume:11422,editor:{id:"24555",title:"Dr.",name:"Marco Antonio",middleName:null,surname:"Aceves Fernandez",slug:"marco-antonio-aceves-fernandez",fullName:"Marco Antonio Aceves Fernandez",profilePictureURL:"https://mts.intechopen.com/storage/users/24555/images/system/24555.jpg",biography:"Dr. Marco Antonio Aceves Fernandez obtained his B.Sc. (Eng.) in Telematics from the Universidad de Colima, Mexico. 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