Transformative algorithm parameters of GA.
\r\n\t
",isbn:"978-1-80356-336-7",printIsbn:"978-1-80356-335-0",pdfIsbn:"978-1-80356-337-4",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,isSalesforceBook:!1,hash:"c13b60a29b20349f816a6ab71ba35e42",bookSignature:"Prof. Mingzhou Yu",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11497.jpg",keywords:"Lab-on-a-Chip, Microfluidics and Nanofluidic Platforms, Micro and Nanoscale Phenomena, Mass and Heat Transport, Multiphase Flow, Nanoparticle-Laden Flows, New Unit-Operation, Theoretical Model, Numerical Method, Experiment, Application, Engineering",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"February 17th 2022",dateEndSecondStepPublish:"April 21st 2022",dateEndThirdStepPublish:"June 20th 2022",dateEndFourthStepPublish:"September 8th 2022",dateEndFifthStepPublish:"November 7th 2022",remainingDaysToSecondStep:"25 days",secondStepPassed:!0,currentStepOfPublishingProcess:3,editedByType:null,kuFlag:!1,biosketch:"A pioneering researcher selected for the Alexander von Humboldt research fellowship and previously affiliated with the Karlsruhe Institute of Technology as a postdoc researcher. Dr. Yu is a holder of 90 journal papers, with an h index of 21, is a member of A& WA (USA) and AAAR (USA), and is the holder of 24 registered patents.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"188972",title:"Prof.",name:"Mingzhou",middleName:null,surname:"Yu",slug:"mingzhou-yu",fullName:"Mingzhou Yu",profilePictureURL:"https://mts.intechopen.com/storage/users/188972/images/system/188972.jpg",biography:"Mingzhou Yu is now a Professor at China Jiliang University and a Guest Professor at Key Laboratory of Aerosol Chemistry and Physics, Chinese Academy of Science. He received his PhD degree from Zhejiang University in 2008 with the major fluid mechanism. During the time period between 2009 and 2012, he moved to Karlsruhe Institute of Technology, Germany, as a Alexander von Humboldt researcher where he worked with Prof. Gerhard Kasper and Dr. Martin Seipenbusch. Since 2013, he joined Prof. Junji Cao's research group as a guest Professor at Key Laboratory of Aerosol Chemistry and Physics, Chinese Academy of Science. During the time period between 2013 and 2016, he worked in The Hongkong Polytechnic University and Universidad Autónoma de Madrid, Spain, as a research associate or postdoc researcher. He is now leading a Aerosol Science and Technology Laboratory supported by Zhejiang Special Provincial Support in CJLU. 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The serial robots structure acquire large space, lack of precision and low load handling capability are its major drawbacks. Parallel manipulators was introduced by the researchers to reduce the disadvantages of series manipulators [1, 2].
The performance of parallel manipulator has become more advance in the recent scenario as compared to the series manipulator. The parallel manipulator has so many benefits as compared to series like precision, load handling ability, accuracy and many more. The parallel manipulators are used in aerodynamics [3], medical surgery [4, 5, 6, 7], machine equipment’s [8, 9], and object pick and place [10, 11].
A parallel manipulator consist of a movable plate connected with a fixed plate with hinged legs which is controlled by a dc motor separately. The number of orientation of legs is considered as degrees of freedom (DOF) of movable plate with respect to fixed plate, this type of arrangement is called as coupling systems.
The parallel robotic arm generally provides high and smooth speed, acceleration with accurate path tracking. For tracking continuous path, parallel manipulator must satisfied following specifications like error-free tracking, minimum settling time and robustness against uncertainties [12].
Almas shintemirov
Damien six
Soheil zarkandi [15] had proposed a parallel manipulator for CNC machine, used for object holding in the 4-axis. This manipulator has two degree-of-freedom i.e. translational and rotational. It consist of two translational DOF and one rotational DOF.
Guilherme sartori Natal
Bikash kumar Sarkar [17], had shown the reproduction concentrate over the using pressurized water activated 2DOF equal controller pondered to the posture (hurl and pitch) control application. The framework model is pondered to the ease pressure driven part setups like corresponding valve with dead band, low speed water powered chamber and so forth. The streamlined numerical model of the controller has been created in this investigation. To examine the control execution by a model free fluffy tuned feed forward inclination PID regulator for present control application, this model has been utilized.
Yogesh singh
Jiantao Yao
The industrial robots were broadly used in various fields like automotive and aircraft industries and many more. The use of industrial robots, generally carry out repeated tasks such as pick and place, welding, assembling, etc. Their adaptability and capability to perform complex tasks in a significant workspace makes them useful in SME (small and medium enterprise). The characteristic advantages they offer in machine applications like prototyping, cleaning and pre-machining of cast parts as well as in end-machining of middle tolerance parts, have increased their usage rapidly.
An input is produced in the control system of the robotic manipulators by trajectory generation for executing the required task with satisfactory performance since a path-constrained motion is followed by the robotic manipulator. The path of the robotic trajectories is assembled offline at first, and later it is assembled online by the end-effectors. There are two approaches in offline trajectory - hand level and joint level. By using Jacobian transformation, these joint coordinates are transformed into Cartesian coordinates for each sampling.
By using opposite kinematics, the Cartesian coordinates are transformed into joint coordinates. Joint level approach costs less expensive in terms of computational complexity than other approaches while controlling the robotic manipulators. Moreover, this joint level approach has an added advantage of considering only the kinematic constraints during the trajectory generation, while ignoring the dynamic constraints that increase the computational effort.
An Optimal Trajectory Generation Algorithm (OTGA) [20] is developed to generate smooth motion trajectories with minimum time for Dof parallel manipulators. For optimal trajectory generation, the Gray Wolf technique is employed with constraints and objective functions, this proposed OTG algorithm uses minimal tracking error. Moreover, for smooth continuous motion of the robotic manipulators, joint speed, acceleration and jerks were also considered along with it. So by using both objective constraints, the Gray Wolf optimization technique selects an optimal trajectory at every iteration as shown in Figure 1.
The schematic diagram of OTGA.
A reference trajectory is created by using the developed Optimal Trajectory Generation [21] manipulators. The path constraint motion of the industrial robots plays a vital role in welding, cutting, surgery and machining applications. A sample reference trajectory with 15 segments is shown below in Figure 2.
Reference trajectory.
Based on the reference trajectory, the design of 6 DOF robotic manipulator is analyzed. For analysis, primary trajectory is approximately created and then optimized using Gray Wolf optimization algorithm. The primary trajectory is calculated for each segment starting from the ‘Start’ segment to the ‘End’ segment on the reference trajectory.
In this section, the Gray Wolf Optimization (GWO) algorithm is employed for the optimal trajectory generation [21, 22, 23, 24, 25, 26]. Here, initially the joint coordinates of the parallel robotic arms are obtained using opposite kinematic approach. Then this sets of joint coordinates, they are optimally fixed by minimizing the path tracing error. After this, the manipulator joint coordinates like speed, acceleration and jerk are calculated by utilizing the finest set if joint angles. The flowchart for the GWO methodology is described below in Figure 3.
GWO flow chart.
For selecting and tracking of a continuous path with minimal tracking error is the prime function of the developed OTG method. This tracking error function can be framed as,
Where,
Such as,
On Basis of minimum tracking error, during each recurrence, joint velocity (jv), joint acceleration (Ja) and joint jerk (Jj) obtained for each set of manipulator joint.
The Gray Wolf Optimization (GWO) is an effective optimization method which emulates the leadership grading, trapping protocol and hunting mechanism of gray wolves in nature. In GWO, the process of optimal trajectory tracking is performed by four gray wolves namely; alpha, beta, delta and omega wolves. Decisions about hunting, time and place are being made by the alpha, The beta and gamma wolves is basically considered as subordinate wolves that help the alpha in decision making, the timid part of the gray wolves hierarchy is being represented by omega only.
Following steps are there to evaluate the fitness function as written below.
Mathematical approach for search operation:
In GWO, the
In the above Eq. (4),
Here ‘
Where, ‘
Where,
Based on the above Eqs. (10)-(12), the solution for next iteration will be obtained as follows:
The process of updating of wolf current positions takes place continuously until the maximum iteration is reached. If the overall optimum solution is does not reached to its maximum, or likewise the new solution will be updated for which the best feasible solution take place and hence based on the best suitable solution the next updates will be executed continuously. Due to this, the optimal continuous path is selected with error-free tracking path.
Genetic Algorithm (GA) is ordered among three distinct parts for example multiplication, hybrid and change and it is expounded momentarily in couple of steps [27]. The chromosome shaped by six factors of lattice
Algorithm Parameters | Outcome |
---|---|
Variables counts | 6 [ |
Maximum Generation | 250 |
Population Size | 60 |
Encoding | Binary |
Selection | Uniform |
Crossover | 0.7 |
Mutation | 0.3 |
Total number of counts | 258 |
Transformative algorithm parameters of GA.
In this section, the analysis for the developed GWO based OTG method and GA for optimal planning of the trajectory for designing the 6 DOF Robotic manipulator. The applied methods are implemented by MATLAB.
A 3-degree-of-freedom (3-DOF) planar parallel manipulator performing high-speed, high-acceleration, and high-accuracy trajectory tracking as similar to the novel experimental pick-and-place manipulator is designed and constructed. At the time of trajectory tracking, multiple closed-loop performance specifications like tracking accuracy, settling time, control effort, and robustness to parameter uncertainty must be satisfied simultaneously. Commonly, closed loop requirement is clashing, i.e., when one requirement is improved, others may break down.
An Optimal Trajectory Generation Algorithm (OTGA) is created for producing least time smooth movement directions for 6 DOF equal controllers. The proposed OTGA utilizes the Gray Wolf enhancement procedure for the ideal direction age utilizing numerous goal capacities. Alongside this, to follow the smooth movement of mechanical controllers, the joint speed, joint increasing speed and joint jerks requires optimal value. At each cycle, the proposed Gray Wolf improvement method chooses the ideal directions utilizing the goal limitations.
The below graph 1 to 6 in Figure 4 shows, the comparison of joint velocity for all active joints angles
Comparison plot for time segment vs. velocity for proposed and existing method.
The below graph 1 to 6 in Figure 5 shows, the comparison of joint acceleration for all active joints angles
Comparison plot for time segment vs. acceleration for projected and existing method.
The below graph 1 to 6 in Figure 6 shows, the comparison of joint jerks for all active joints angles
Comparison plot for time segment vs. jerk for proposed and existing method.
The above figures show that the comparison between projected GWO technique, existing GA and default methods for trajectory generation. We have taken three measurements named as acceleration, jerk and velocity in which all these are going to be compare with different time segments. It is clearly shows that the proposed method achieves minimum effective value as compared to the exiting techniques.
An optimal trajectory generation methodology is proposed which generates errorless continuous path motion with fast converging the Gray Wolf Optimization (GWO) method. The proposed OTG method using GWO algorithm is compared with the GA (Genetic Algorithm) based trajectory generation method and a traditional trajectory generation method.
The mean, maximum and minimum acceleration value is also less for the proposed OTG with GWO method when compared to the existing methods. The least acceleration value is attained for the joint angle. Finally, the Joint jerk value is also calculated for all the joint angles using proposed and exiting methods with 15 segments.
The comparison of joint velocity, joint acceleration and joint jerks for all active joints angles
Comparison results can be summarized as follows:
The maximum average velocity of the proposed GWO based OTG is observed 1.75 times lesser than GA based OTG and 1.01 times greater than non-optimize method.
The acceleration maximum average value of the proposed GWO based OTG is observed that 4.03 times and 3.92 times lesser than GA based OTG and non-optimize method.
The jerk maximum average value of the proposed GWO based OTG is observed that 2.41 times and 2.04 times lesser than GA based OTG and non-optimize method.
Proposed OTG GWO generates minimum 118.4% and maximum 236.1% better velocity, minimum 156.4% and maximum 592% better acceleration, and minimum 108.7% and maximum 310.7% better jerk.
The efficiency of projected methodology has been analyzed with the actual research works. The experimental result shows that a good optimization of developed OTG method in terms of shared speed, joint speed ripples, and joint lurching move measures. This proves that the proposed OTG algorithm works effectively to follow the optimal trajectory with less tracking error and smooth continuous path motion.
Globally, it is a critical time to act on climate change either through developing appropriate policies, focused research or implementing sustainable and green strategies across various sectors. The report by United Nations Environment Programme (UNEP) and International Energy Agency (IEA) [1] indicates that by 2056, globally, there is going to be a rapid increase by five-fold in the economic activity and by three-fold in energy consumption compared to the current numbers. Furthermore, there would be a population increase by 50% and a drastic rise in global manufacturing activities imposing further pressure on the resources and planet. Buildings alone are responsible for 40% of the GHG emissions [2, 3]. As a consequence of the rapid growth in economic activities, urbanization, and growing population, the impact of the built environment sector on the planet is anticipated to worsen further. The building industry’s exhaustively growing consumption of energy through the construction to operation phase is considered as a major contributor to environmental pollution, producing an enormous amount of waste [4, 5, 6, 7, 8].
However, the building industry also demonstrates high potential and has capabilities to contribute towards significant emissions reduction [9, 10]. As stated by the United Nations Environment Programme [2], “the solution that sits at the intersection of urbanisation and climate change which can cut carbon emissions, boost productivity, and enhance the health and wellbeing of people is a green building.” The outcomes and commitments of the built environment sector have also been recognized as a critical sector at COP26 at Glasgow demonstrating leadership, resilience, and social inclusiveness for climate action [11]. However, a “sustainable” or “green building” is a broad and complex concept, which is still quite perplexing for the building industry. Sustainability is a concept that is built upon three key aspects, namely environmental, economic, and social sustainability. These three aspects need to be incorporated collectively and cannot be targeted individually to achieve expected results [4, 6, 7]. Jenson [12] states that it is when all these aspects fit together in the planning and governance strategies, one can deliver buildings that perform as desired and are truly sensitive to our environment. This is a challenge continually encountered by design, construction, and building management practitioners. The objectives primarily established are mostly only incremental changes; however, what is required is a step-change in these design and management approaches being currently followed to acknowledge the veritable potential of buildings.
Supporting this concept, many recent studies have argued the potential of buildings for delivering significant cuts in emissions at no cost or little extra cost, reducing harmful environmental effects, and acting as the backbone of any economy [3, 6, 8]. There is immense potential for this as the building industry employs more than 10% of the global workforce [1, 3, 6, 10], resulting in gains in social outcomes as well. Underpinned by this argument, this chapter discusses the key concepts of sustainability in buildings and recommends a best practice model to close the gap between actual versus expected performance taking “Green Star” rated tertiary education institutions in Melbourne, Australia as case studies. Green Star is the internationally recognised sustainability rating and certification of the Green Building Council of Australia (GBCA). This is cross-referenced in Section 2 – Background (p4) with further information. The results of the study presented assists the design community to deploy strategies that not only meet a building’s energy and savings targets but also respond to occupants’ requirements of space comfort and use, creating an overall efficient system for users and building managers alike, thus achieving all three components of sustainability – reduction of environmental impacts, increased social outcomes, and reduced economic costs.
The two aspects of the overall building purpose and operation are not necessarily always in sync as has been demonstrated to date by the way the industry has approached this problem in the form of split incentives [13]. Many organisations feel that just complying with the environmental norms or national regulations is enough to meet user needs, and their work is completed once they manage to deliver a building as per such guidelines. Examining the performance of a building is also mostly restricted to evaluating the operation of a building with respect to energy consumption and energy efficiency. Most initiatives taken by facility managers and senior management are to ensure that the utilities, that is, electricity, gas, and water consumption of the building meet the standards overlooking other key concepts of performance management, such as incorporating the occupant’s perception and outlook in building management, performance evaluation through a building’s life cycle, and other such social considerations beyond the environmental. However, a building in operation is a complex system and its management should not be restricted only to the knowledge of facility managers. It should focus on more integrated and holistic approaches, where the organisational objectives, knowledge of facility managers, review by the external stakeholders, and occupant perceptions should all be considered together to be satisfactory and present optimum results for these stakeholders.
As indicated earlier with green buildings, the assessments have generally been restricted to the measurement of energy being the key focus for most organizations when aiming to reduce the emissions or overall carbon footprints. When including other aspects of building performance, many studies [14, 15, 16, 17, 18, 19] have discussed the significance of monitoring design and other internal building features, with a focus primarily on indoor environmental quality (IEQ) and thermal comfort conditions. However, not much focus and practical exploration have been undertaken to consider occupant satisfaction for evaluating overall building performance and closing the loop between the occupants and building management to achieve holistic green outcomes [20, 21].
Tertiary education institutions have a critical role in the current decade to innovate, excel, and set an example in meeting the needs of the changing environment [22]. The strategic vision of universities needs to be one that accounts for the rapidly changing world, and to be flexible enough to recalibrate and refresh as conditions around them change. Universities globally are investing billions of dollars into building construction that showcases their sustainability commitment [23] designed for being used as science laboratories to incubate innovative green technologies facilitating academic and research activities. Universities are constantly upgrading to sustainable standards leading through design, innovation, and adapting to new reforms and requirements by the industry around the globe. Such reforms are formulated to cultivate a population that is knowledgeable and active towards their crucial role in sustainable development and combating climate change.
Over the last several years there has also been a shift away from a prescriptive approach to sustainable design towards the evidence-based evaluation of actual performance through life cycle assessments (LCAs). While LCAs are not yet a consistent requirement of green building rating systems and codes, there is a trend towards requiring LCAs and improving the methods for conducting them [24]. Here is where green building assessment tools play a role in guiding the design professionals towards green approaches and eliminating bad performing buildings from the building industry. Building assessment tools are in a continuous state of evolution and continue to be refined to reflect new standards and goals for achieving ever-higher levels of sustainability [24, 25]. Therefore, it is essential to investigate the most current versions of these tools to gain an understanding of the requirements that must be met to achieve optimal results.
Globally, sustainable building rating systems started about 30 years ago after the development of Building Research Establishment Environmental Assessment Methodology (BREEAM) in 1990. Since then, there is an emergence of several environment rating tools for buildings, such as Leadership in Energy and Environmental Design (LEED) in the U.S.A, Eco-Quantum in the Netherlands, Promise in Finland, Eco-Pro in Germany, Haute Qualité Environnementale (HQE) in France, Comprehensive Assessment System for Built Environment Efficiency (CASBEE) in Japan, and Athena in Canada, to name a few. The assessment methods for these rating tools vary from the perspective of scope, structure, format, and complexity. Apart from the most commonly used rating tools, such as LEED and BREEAM, other assessment tools fall into the category of qualitative and life cycle assessments, including the Sustainable Building Tool; Green Star, Hong Kong Building Environmental Assessment Method (HK BEAM) or tools adapted to specific countries, such as LEED adapted for Canada and Australian Green Star adapted for New Zealand and South Africa. In some instances, the tools have developed into a new tool, for example, the Building Assessment Tool (SBAT) influenced by BREEAM and LEED.
Although most of the existing building rating systems are voluntary, in some countries, such as Australia, it is a mandatory requirement for minimum energy requirements of new office buildings and major refurbishments as per the National Construction Code Building Code of Australia maintained by the Australian Building and Construction Board [26]. Development and uptake of such rating schemes are promoted in Australia at a national level, as the detrimental effects of buildings account for approximately a quarter of the nation’s greenhouse gas emissions and two-thirds of electricity consumption [27]. Currently, two voluntary national accreditation programs exist to measure and report on the environmental performance of office tenancies and assist in guiding best practice office fit-outs. These Australian building rating systems are mandatory requirements for minimum energy requirements of new buildings and major refurbishment [28]. The two rating systems, that is, NABERS and Green Star, currently available in Australia promote sustainable building development in the commercial space. Green Star is Australia’s only national, voluntary, holistic rating system for sustainable buildings and communities [29]. The Green Building Council of Australia (GBCA) developed Green Star, which is a design-based rating system that provides no guarantee of, or commitment to, a specific level of performance and confines itself to the intent of the design and to some extent the provision of the process to achieve that intent [30, 31]. The Green Star rating system is a much broader rating scheme than NABERS and assesses both environmental and liveability factors throughout a building’s lifecycle [29]. Green Star has now achieved sufficient market penetration and may be considered to be part of procurement practice by industry.
This study used Green Star rated buildings. Green Star started with three rating classifications, that is, “As Design,” “As Built,” and “Green Star Communities.” Recently a fourth component of “As Performance” [32] has been added to the rating system, with each classification having versions as and when updated.
There are several versions of each Green-Star tool that have been updated since the tool was first created. Rating buildings as per the design and built outcome to interiors, performance, and communities, Green Star supports deploying innovative practices to optimise sustainability outcomes through an array of options [33]. All the versions of the Green Star rating scheme started with a pilot version to understand the limitations and continued refinements based on changing global, national, and industry requirements. As the evaluation of the case study buildings were conducted over the period 2014–2019, the buildings used were all Green-Star buildings certified for As Design (v1) at the start of the data collection period. A total of 86 academic buildings/projects in Australia were certified As Design (v1). Of which, 35 projects were in Victoria. 37 buildings/projects were certified following As Built (v1) with 6 projects located in Victoria.
Concurrently, what is also required is to constantly upgrade university governance models for long-term sustainability. The governance strategies for most universities are focused on shaping their respective campuses, creating innovative learning spaces, and a student precinct, which supports a rich and rewarding student experience. Universities aim at developing teaching and research facilities, which by their very nature, encourage interdisciplinary collaboration and industry engagement, and explore options for campus development to accommodate increasing scale in both teaching and research. Formulating appropriate strategic plans to incorporate such outcomes is crucial and provides a framework within which to develop, implement and modify practices, associated investments, and action plans.
For the purpose of selecting study buildings for the research, a detailed evaluation of four recently constructed Green-Star rated academic buildings in Australia was carried out to observe their performance and management structure in reality. Four tertiary academic institutions were selected in Melbourne, Australia as case study buildings, incorporating post-occupancy evaluation techniques and appropriate project management strategies. The buildings were completed within the 2010–2014 period. The key features (Building Type, Academic Faculty, Green Star Certification Score, Volume, Area, and number of Floors) of the study buildings are described in Table 1. The buildings are denoted as Buildings A, B, C, and D. The results provide a model framework for design stakeholders to achieve desired building performance targets for green buildings, as they are designed to perform as per specific standards but can be applicable to conventional or non-green buildings as well, drawing upon lessons learned from this study.
Study Buildings | Building Type | Faculty | Green Star Certification (Education Design v1) | Volume | Gross Floor Area | No of Floors |
---|---|---|---|---|---|---|
Building A | New Build, Refurbished | Architecture and Design | Certified – 5 Star Green Star, 2011 | 16,040 m2 | 13,000 m2 | 10 |
Building B | New Build | Design and Manufacturing | Certified – 6 Star Green Star, 2013 | 21,000 m2 | 10,000 m2 | 11 |
Building C | New Build | Construction | Certified – 5 Star Green Star, 2014 | 17,500 m2 | 11, 861 m2 | 3 |
Building D | New Build | Architecture and Design | Certified – 6 Star Green Star, 2014 | 17,673 m2 | 14,528 m2 | 7 |
Description of case study buildings.
The study has adopted a mixed-methods approach utilizing both quantitative and qualitative techniques. For quantitative data, survey research has been deployed. Surveys have been used to evaluate occupant satisfaction levels in the case study buildings.
Currently, Building User Survey (BUS) and Building Occupants Survey System Australia (BOSSA) are the only two officially accredited post-occupancy evaluation (POE) instruments within the National Australian Built Environment Rating System (NABERS) for commercial buildings used in Australia [34]. These surveys are robust and accessible Australian alternatives to other surveys currently in use by NABERS and Green Star Performance rating tools [35]. However, BOSSA has wider applications, BUS surveys were used in this study due to the narrower scope, more-wider presence globally and acceptance of the respective survey, and the license rights available with or for the case study buildings [28, 34]. Apart from the BUS itself, an online survey deployed through Survey Monkey (cloud-based interface) was used by one of the case study buildings. Although the survey used was different for one building, their project managers allowed the researcher to add or modify survey questions as required before they were finally deployed. Hence, to ensure comparative study across all the buildings, their questionnaire was modified, and questions were added or removed to match the themes of the BUS format. So, four buildings used BUS and one building used an additional online survey as well as the standard BUS. BUS is available as hard copy survey and online; the buildings used the online survey rather than hard copy.
The surveys were used to evaluate the feedback of case study buildings, focusing on staff rather than staff and students. This was because staff spend more hours in a building either for teaching, research, or undertaking other professional activities. The BUS surveys used a 5-point Likert scale for measurement with 1 rating the highest dissatisfaction to 5 being the highest level of satisfaction. Statistical analysis of the occupant satisfaction survey data was carried out using SPSS Statistics (version 26) analysing via one-way ANOVA. Many studies [36, 37, 38] have proved that the Likert scale data can be analysed using parametric tests, as the analysis can vary based on how the responses are formulated. For example, in this research, the distance between each item category is considered “equivalent,” and when a Likert scale is assumed to present symmetry of variables and is equidistant, it behaves more like an interval-level measurement in practice, being suitable for parametric tests [37, 38]. In this study, the distance between each item category is “equivalent” and the Likert scale was used to run parametric tests on the data collected. The other key primary criteria were to assess if the data were normally distributed within all groups. Hence, the Descriptive and Levine’s Test for Homogeneity of Variances was carried out for all variables [36, 37]. The output displayed normal distribution using the mean values as the measure of central tendency, that is, the probability distribution. Correspondingly, as the data represented a Gaussian population (normally distributed), one-way ANOVA was used to determine the statistical significance of data [36, 37].
In addition to the surveys, qualitative tools in the form of walk-in discussions, stakeholder interviews with the building facilities department and design stakeholders, and focus group discussions were undertaken. The walk-in discussions assessed occupant’s (including building’s staff and students) responses in a more informal manner, followed by the outcomes from the stakeholder interviews, assessing the role and responses of management and finally the focus group results. The focus group discussions were conducted to share the preliminary results and discuss preliminary results of the actual versus expected outcomes with key management stakeholders. These qualitative results assist in understanding and validating the occupant survey findings and facility management perspectives concerning sustainable and green building concepts. The study hence adopted an “Action Research” framework for data analysis. The steps involved in the data collection are summarized in Figure 1.
Data collection approach.
The categories and sub-categories of the Green-Star As Design (v1) rating tool were used. Each sub-category has certain scores available that when combined form the maximum score available for that Green-Star category. The specific scores attained and statements made by the study buildings in the original Green Star application documents assist in determining the original design intention by a building.
Green-Star performance of case study buildings was analysed by utilising the Green-Star applications submitted by the respective institutions as an expression of interest for creating these buildings. The scores achieved by each building assists in understanding the commitments of the respective institutions. The mixed-method techniques deployed assisted in evaluating and validating how well these case study buildings performed in relation to the targets they laid out in their respective applications. The scores achieved by each case study building against the nine categories of the Green-Star As Design (v1) rating system are shown in Table 2.
Green Star As Design v1 Categories | Available Points | Points scored by Building A | Points scored by Building B | Points scored by Building C | Points scored by Building D |
---|---|---|---|---|---|
Management | 14 | 12 | 12 | 13 | 14 |
IEQ | 25 | 13 | 11 | 16 | 17 |
Energy | 29 | 14 | 14 | 18 | 14 |
Transport | 13 | 12 | 12 | 13 | 12 |
Water | 13 | 10 | 10 | 16 | 14 |
Materials | 20 | 12 | 12 | 14 | 14 |
Land use and ecology | 7 | 4 | 4 | 2 | 4 |
Emissions | 13 | 9 | 9 | 6 | 8 |
Innovation | 5 | 0 | 0 | 0 | 10 |
Total | 140 | 65 – 5 Star | 63 – 5 Star | 76 – 6 Star | 83 – 6 Star |
Scores achieved by each case study building across the nine Green-Star As Design (v1) categories.
As shown in Table 2, all the case study buildings scored high under the first five categories, namely – (i) Management – achieving score on factors, such as external and internal building commissioning, delivering appropriate management practices, evaluating user satisfaction, technical and physical performance; (ii) IEQ – for improved technologies for providing better IEQ services; (iii) Energy – achieving energy efficiency, carbon footprint reduction; (iv) Transport; and (v) Water – using water-efficient technologies. The buildings scored moderate on materials, land use, ecology, and emission and no score on innovation, except Building D, which attained double the maximum score available for innovation, due to commitment in design and technologies promised.
The BUS surveys used to assess the staff responses towards these newly built Green Star rated buildings evaluated user comfort, indoor environment quality, wellbeing and productivity, and communication with management. In relation to the surveys, the effective population size (N) for each case study building is described in Table 3.
Building Name | Total no. of staff | No. of responses |
---|---|---|
Building A | 54 | 37 |
Building B | 42 | 30 |
Building C | 60 | 42 |
Building D | 131 | 60 |
Case study building sample size.
The key findings to emerge from the surveys were occupant responses towards three main themes – (i) impact of various design and work environment conditions (office/desk design, thermal comfort, acoustics, personal control, etc.) on their overall behaviour; (ii) their overall comfort and perceived productivity; and (iii) dissatisfied engagement levels from the management level
The user’s perspective towards the impact of various design and work environment conditions on overall behaviour showed that 69% of users in Building A, 66% in Building B, 55% in Building C, and 58% in Building D rated the conditions in the building affected their behaviour personally (with colleagues) and professionally (in terms of work and productivity). Most users commented that the overall comfort or productivity was drastically affected, leading to changes in the work schedule and activities. Using Pearson (
Variables | Correlation between variables | |||
---|---|---|---|---|
Building A | Building B | Building C | Building D | |
Building meets user needs and comfort | 0.821 | 0.786 | 0.705 | 0.993 |
Overall comfort and perceived productivity | - | 0.904 | 0.775 | - |
Perceived productivity and perceived health | 0.913 | 0.747 | 0.863 | 0.797 |
Pearson correlation coefficient (
On rating the engagement of management, the mean of responses on the satisfaction scale of 1–5 for Building D for two variables were – 4.25 for: (i) facilities meet user needs, and (ii) speed of response for staff complaints, and 3.24 for the effectiveness of response. The results for Building D were the highest when compared to other buildings, stating the highest level of satisfaction for the occupants of Building D. The other buildings also had mean scores close to or more than 3 on facilities meeting user needs and effectiveness of the response, demonstrating moderate levels of satisfaction. The occupants for all buildings rated lowest on the speed of response to a request to change, demonstrating lower levels of satisfaction. This particular aspect was also observed in the open-ended comments, where the occupants (average of 42% in study buildings) expressed their discontent towards the attitude of the facilities for not acting upon their requests or complaints on time. When the variables under this category were compared, a high correlation between two variables in each building was observed. The highest correlation (significant at p < 0.01) was observed in Building B followed by Building D demonstrating a high positive relationship. This suggests that for the users in Buildings B and D, the positive response for one variable affected the other directly. The correlation results are presented in Table 5.
Variables | Correlation between variables | |
---|---|---|
Building B | Building D | |
Facility meeting user needs and effectiveness | 0.955 | 0.738 |
Facilities meeting user needs with speed of response | 0.929 | 0.681 |
Pearson correlation coefficient (
On completion of occupant feedback survey analysis, it was observed that the occupants of the study buildings had mixed feelings about the facility. As primary occupants of the buildings, the staff were reasonably satisfied with the overall building, but not fully satisfied that it met their expectations specifically in relation to their office space and comfort. However, as per the occupant’s perspective, the facilities were designed very efficiently and effectively for its students, with management’s key focus being on providing a comfortable and desirable environment for the students over the staff.
Nonetheless, for all four buildings, the occupants on average showed high satisfaction (87%) towards the building design and Green Star attainment, medium/neutral satisfaction (57%) towards maintained temperature conditions, lighting levels, and comfort, and low satisfaction (42%) towards noise levels, office space, perceived productivity and health, and personal control over physical factors. This level of lower rating can be associated with several factors, including a shift to open-plan offices, sustainability initiatives not working well, and a lack of appropriate occupant engagement by the management, as per the occupant’s open-ended comments provided in the surveys. Upon comparison between the four buildings, it was observed that Building D outperformed all other study buildings with the highest occupant satisfaction (89%) and Building C rating the lowest levels of occupant satisfaction towards most measured variables (54%).
Summarizing the responses, the quantitative results assisted in understanding the extent to which the study buildings met their occupant’s needs and expectations, and how well have the facility managers succeeded in providing the building services to the occupants. On an average (43%), the results implied an overall low satisfaction of occupants with respect to their workspace environment and factors, demonstrating that the study buildings lack the ability to meet the primary objective of fulfilling occupant needs and improving their comfort and productivity. These quantitative results were triangulated with the qualitative results to eliminate any bias and understand the occupant-management relationships, and management’s perspective in the study buildings for arriving at the final recommendations and conclusions.
The qualitative results obtained via walk-in discussions, stakeholder interviews, and focus group discussions re-emphasized the “missing link” or lack of communication loop between building occupants and the management, ultimately affecting the overall building performance. The management’s priority is to achieve the University targets, whereas the occupants want a good indoor space to work, in addition to being able to express their needs and wants. Both managers and occupants’ perspectives are individually valid and justified but do not complement due to low or negligible stakeholder prioritization and engagement in the management strategies. Hence, this chapter highlights the learnings from the case study buildings and develops a model using the best practices for improved execution in future projects.
The stakeholder interviews and focus group further assisted in triangulating the study’s outcomes in correspondence to Green Star aspiration results. The results demonstrated that buildings could achieve certification, but the operation can still be poor in terms of low occupant satisfaction levels towards their workplace productivity and comfort. Major concerns observed in the walk-in discussions and stakeholder interviews were the lack of occupant engagement and consultations by the facility management officials during the building design and construction phase; none to extremely low involvement of design officials after building in use; and the limited focus on short term benefits over life cycle performance. The discussions with facility and building managers reiterated the key aspiration for the building’s senior management was to achieve overall energy efficiency and make student-friendly facilities, rather than creating a productive workplace for the staff. The results also demonstrated that although the buildings scored high against the “management” and “energy” categories of the Green Star applications, most sub-categories were not satisfied in the operation phase. The management and design stakeholders primarily associated this non-functionality with technical defaults or cost-related issues.
The analysis reported in this chapter demonstrates that the development of the case study buildings has some success from an environmental, sustainability, and financial perspective. However, lacked drastically from an occupant (social) perspective. There are lessons that can be drawn upon for future developments to improve outcomes further. The analysis of survey responses and interviews highlights that it is crucial to close the loop between the performance measurement and performance management of buildings to achieve sustainability. Moreover, it is recommended to integrate stakeholder engagement and management at each phase of any project, to optimize the potential for all the stakeholders, and create an output beneficial and satisfactory for all.
The best practice model hence recommended by the study serves as a guidance document, providing structure and direction for the design professionals, and facility and building managers to prepare and implement their actions strategically, to achieve the desired performance of their buildings along with building occupant satisfaction. The model is represented in Figure 2.
Recommended ‘Best Practice Model’ for achieving sustainable building outcomes. Source: Authors.
Figure 2 demonstrates the structure of the key factors of the “best practice model” recommended by the study, based on the gaps identified earlier on and learnings from the study findings. It represents a continuing sequence along with the direction flow of the stages, tasks, or events in a circular flow, with each stage having the same level of importance, to ultimately achieve project success and performance management throughout the life cycle. This model has been derived based on the analysis of green-rated tertiary education buildings; however, it can be adopted by all commercial building types as it informs a general structural change required in an organization’s management practice, to deliver required and appropriate governance strategies achieving all business outcomes and creating productive workplaces for the users. The key recommendations of the model can be summarized as a model that includes:
Identification and prioritization of key building stakeholders
Mapping the effects of building performance on different stakeholder groups and measuring the satisfaction of occupants (annually) using and being affected the most by building operation and function
Closing the loop of communication between the design team (internal and external) and building users by raising information
Collaboration across different organizations and agencies. This is because organizations or agencies often collect and manage their own data/research and have little or no incentive to share it with others. Without a culture of collaboration and knowledge sharing, attempts to understand and analyze interrelated building performance and sustainability issues are unlikely to succeed
A strong government mandate and institutional frameworks can provide a much-needed push
Routine (half-yearly or annually) performance monitoring of buildings as per the national guidelines for non-green or rating systems if certified to become mandatory for buildings. For example, the case study buildings were Green-Star rated (As Design) which does not mandate the buildings to evaluate performance once the certification is received, even when applying for re-certification. The recent version of the standard has been updated to mandate such assessments but the buildings previously certified are exempted, creating a gap in performance evaluation. This is a gap that needs to be closed by making evaluation techniques mandatory for buildings as per the desired or required standards
Appropriate incentive structure and practical arrangements for handling the information generated so that it becomes attractive and feasible to develop a set of good practices
Retaining and sharing the knowledge and lessons learned, then capitalizing and converting this to insights for future projects will be challenging, considering the flux in many organizations in these increasingly uncertain times. Nonetheless, incorporating ongoing performance evaluation, stakeholder engagement practices and understanding the need for reporting and getting the reporting relationship right in any organization becomes an important consideration.
The framework defined in this chapter is primarily based on the stakeholder engagement principles and is a three-step pyramid process. At the lower level or the base, the framework determines “Strategic Management” perspective, which simply means identifying organisational targets and priorities, enhancing decision-making processes, and ensuring stakeholder identification, prioritization, and engagement towards design, processes, and outcomes, followed by “Ethical” perspective illustrating maintaining harmony between stakeholder groups and identifying socio-behavioural aspects, and the higher level or apex constituting the “Opportunity” perspective illustrating knowledge sharing. The contribution of the research (based on the framework) to the knowledge will be the development of a best practice model for the built environment sector (applied/inspired from the academic sector) using a “holistic” or “integrated design” approach. Hence, the paper intends to recommend that being energy conservers and managing financial sustainability, the organization still needs to focus on engaging with all the stakeholders constructively.
Finally, the paper discusses the strategies to ensure replication of the respective best practice model to develop a supporting policy framework and build up capacity of building managers. The outputs generated by the paper are consistent with and instrumental to the achievement of the objectives that contribute to creating enabling environments for integrated sustainability strategies into building design and management.
The chapter presents an analysis of the gap between actual and expected performance in four Green Star institutions in Melbourne, Australia, and how POE generated results assisted in achieving this objective. Outcomes include the development of clear assessment mechanisms for establishing links between performance measurement and performance management with an understanding of how occupants view its value and description of a better performing building as compared to the others. The comparison was carried out on how well the building has been managed in conjunction with the sustainable building targets.
As observed by analysis of POE results of the case study buildings, it has been clearly indicated that the building users (mainly academic and non-academic staff) are not satisfied, and their needs have not been considered in the initial design brief. However, after triangulating the outcomes and studying the broader context, all four buildings have met their key parameters in terms of Green Star certification utility targets. What worked well for all buildings have been exceptional teaching and learning spaces, student study areas and institution image. Building variables that did not work well were lack of consultation with end-users and basic design faults or technical issues. This signifies that it is important to realize that the organizational facilities function cannot exist in isolation if the organization is to effectively exploit its entire asset base to best support the delivery of core services. Making constructive use of performance measurement results is critical if the organization is to improve the performance of its assets. At both individual and organisational levels, a better understanding of the relationship between what is being done and how well the organization succeeds needs to be developed. Based on the analysis, senior management and facility managers are seen to have a direct impact on building operations and performance. They can also adjust or redirect their strategies or identify new strategies for the organization.
Following the lead by the European Union since early 2021, there is a global momentum that is currently shifting towards Nearly Zero Energy Buildings, that is, high performing buildings utilising nearly zero or extremely low amounts of energy being met by renewable sources. While new commercial buildings in the US and Canada are now required to follow these principles, Australia is taking initiatives in the residential sector as well to achieve the same. Significantly, understanding the applications and potential of the building sector to effectively achieve overall sustainable outcomes. The outcomes of this study highlight that focusing on issues of building sustainability are not sufficient for a building’s success. Being “green” is only one important feature of building success, but other aspects of building performance (user needs and engagement) must be considered as well. The focus on the green or sustainability aspect has detracted the construction industry from other equally important design issues relative to overall building performance. Understanding and taking the triple bottom line approach of being economically viable, environmentally responsible, and socially inclusive is important rather than simply aiming to be rated as “green” or sustainable. Furthermore, being sustainable and green should be translated to high-performance buildings for optimal benefits. Supporting this argument, the outcomes of this study are noteworthy for individual buildings be they academic or otherwise, and benefits wider government, non-government and market audiences seeking new knowledge about performance development.
Zero-energy programs often build on these frameworks supporting a variety of non-energy benefits relative to standard buildings, such as improved comfort, improved occupant health and productivity, enhanced indoor environment quality, and higher occupancy rates. Therefore, this study concludes that in making building codes, policies and management approaches more stringent, prioritisation and engagement of building stakeholders, and increased interest in decarbonisation, would assist in encouraging and assisting buildings that are truly zero-energy and zero-energy-ready.
Analysis of Variance Building Research Establishment Environmental Assessment Methodology Building Occupants Survey System of Australia Building User Survey Comprehensive Assessment System for Built Environment Efficiency Conference of Parties Green Building Council of Australia Greenhouse Gas Hong Kong Building Environmental Assessment Method Haute Qualité Environnementale International Energy Agency Indoor Environmental Quality Life Cycle Assessment National Australian Building and Energy Rating Scheme Leadership in Energy and Environmental Design Nearly Zero-Energy Buildings Post Occupancy Evaluation Sustainable Building Assessment Tool Statistical Package for the Social Sciences United Nations Environment Programme
Supporting women in scientific research and encouraging more women to pursue careers in STEM fields has been an issue on the global agenda for many years. But there is still much to be done. And IntechOpen wants to help.
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\n\nWe aim to publish 100 books in our Women in Science program over the next three years. We are looking for books written, edited, or co-edited by women. Contributing chapters by men are welcome. As always, the quality of the research we publish is paramount.
\n\nAll project proposals go through a two-stage peer review process and are selected based on the following criteria:
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\n\n“My scientific path has given me the opportunity to work with colleagues all over Europe, including Germany, France, and Norway. Editing the book Graph Theory: Advanced Algorithms and Applications with IntechOpen emphasized for me the importance of providing valuable, Open Access literature to our scientific colleagues around the world. So I am highly enthusiastic about the Women in Science book collection, which will highlight the outstanding accomplishments of women scientists and encourage others to walk the challenging path to becoming a recognized scientist." Beril Sirmacek, TU Delft, The Netherlands
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Radiotherapy and Nuclear Medicine Technology has always been my aspiration and my life. As years passed I accumulated a tremendous amount of skills and knowledge in Radiotherapy and Nuclear Medicine, Conventional Radiology, Radiation Protection, Bioinformatics Technology, PACS, Image processing, clinically and lecturing that will enable me to provide a valuable service to the community as a Researcher and Consultant in this field. My method of translating this into day to day in clinical practice is non-exhaustible and my habit of exchanging knowledge and expertise with others in those fields is the code and secret of success.",institutionString:null,institution:{name:"Majmaah University",country:{name:"Saudi Arabia"}}},{id:"313277",title:"Dr.",name:"Bartłomiej",middleName:null,surname:"Płaczek",slug:"bartlomiej-placzek",fullName:"Bartłomiej Płaczek",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/313277/images/system/313277.jpg",biography:"Bartłomiej Płaczek, MSc (2002), Ph.D. (2005), Habilitation (2016), is a professor at the University of Silesia, Institute of Computer Science, Poland, and an expert from the National Centre for Research and Development. His research interests include sensor networks, smart sensors, intelligent systems, and image processing with applications in healthcare and medicine. He is the author or co-author of more than seventy papers in peer-reviewed journals and conferences as well as the co-author of several books. He serves as a reviewer for many scientific journals, international conferences, and research foundations. Since 2010, Dr. Placzek has been a reviewer of grants and projects (including EU projects) in the field of information technologies.",institutionString:"University of Silesia",institution:{name:"University of Silesia",country:{name:"Poland"}}},{id:"35000",title:"Prof.",name:"Ulrich H.P",middleName:"H.P.",surname:"Fischer",slug:"ulrich-h.p-fischer",fullName:"Ulrich H.P Fischer",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/35000/images/3052_n.jpg",biography:"Academic and Professional Background\nUlrich H. P. has Diploma and PhD degrees in Physics from the Free University Berlin, Germany. He has been working on research positions in the Heinrich-Hertz-Institute in Germany. Several international research projects has been performed with European partners from France, Netherlands, Norway and the UK. He is currently Professor of Communications Systems at the Harz University of Applied Sciences, Germany.\n\nPublications and Publishing\nHe has edited one book, a special interest book about ‘Optoelectronic Packaging’ (VDE, Berlin, Germany), and has published over 100 papers and is owner of several international patents for WDM over POF key elements.\n\nKey Research and Consulting Interests\nUlrich’s research activity has always been related to Spectroscopy and Optical Communications Technology. Specific current interests include the validation of complex instruments, and the application of VR technology to the development and testing of measurement systems. He has been reviewer for several publications of the Optical Society of America\\'s including Photonics Technology Letters and Applied Optics.\n\nPersonal Interests\nThese include motor cycling in a very relaxed manner and performing martial arts.",institutionString:null,institution:{name:"Charité",country:{name:"Germany"}}},{id:"341622",title:"Ph.D.",name:"Eduardo",middleName:null,surname:"Rojas Alvarez",slug:"eduardo-rojas-alvarez",fullName:"Eduardo Rojas Alvarez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/341622/images/15892_n.jpg",biography:null,institutionString:null,institution:{name:"University of Cuenca",country:{name:"Ecuador"}}},{id:"215610",title:"Prof.",name:"Muhammad",middleName:null,surname:"Sarfraz",slug:"muhammad-sarfraz",fullName:"Muhammad Sarfraz",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/215610/images/system/215610.jpeg",biography:"Muhammad Sarfraz is a professor in the Department of Information Science, Kuwait University, Kuwait. His research interests include optimization, computer graphics, computer vision, image processing, machine learning, pattern recognition, soft computing, data science, and intelligent systems. Prof. Sarfraz has been a keynote/invited speaker at various platforms around the globe. He has advised/supervised more than 110 students for their MSc and Ph.D. theses. He has published more than 400 publications as books, journal articles, and conference papers. He has authored and/or edited around seventy books. Prof. Sarfraz is a member of various professional societies. He is a chair and member of international advisory committees and organizing committees of numerous international conferences. He is also an editor and editor in chief for various international journals.",institutionString:"Kuwait University",institution:{name:"Kuwait University",country:{name:"Kuwait"}}},{id:"32650",title:"Prof.",name:"Lukas",middleName:"Willem",surname:"Snyman",slug:"lukas-snyman",fullName:"Lukas Snyman",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/32650/images/4136_n.jpg",biography:"Lukas Willem Snyman received his basic education at primary and high schools in South Africa, Eastern Cape. He enrolled at today's Nelson Metropolitan University and graduated from this university with a BSc in Physics and Mathematics, B.Sc Honors in Physics, MSc in Semiconductor Physics, and a Ph.D. in Semiconductor Physics in 1987. After his studies, he chose an academic career and devoted his energy to the teaching of physics to first, second, and third-year students. After positions as a lecturer at the University of Port Elizabeth, he accepted a position as Associate Professor at the University of Pretoria, South Africa.\r\n\r\nIn 1992, he motivates the concept of 'television and computer-based education” as means to reach large student numbers with only the best of teaching expertise and publishes an article on the concept in the SA Journal of Higher Education of 1993 (and later in 2003). The University of Pretoria subsequently approved a series of test projects on the concept with outreach to Mamelodi and Eerste Rust in 1993. In 1994, the University established a 'Unit for Telematic Education ' as a support section for multiple faculties at the University of Pretoria. In subsequent years, the concept of 'telematic education” subsequently becomes well established in academic circles in South Africa, grew in popularity, and is adopted by many universities and colleges throughout South Africa as a medium of enhancing education and training, as a method to reaching out to far out communities, and as a means to enhance study from the home environment.\r\n\r\nProfessor Snyman in subsequent years pursued research in semiconductor physics, semiconductor devices, microelectronics, and optoelectronics.\r\n\r\nIn 2000 he joined the TUT as a full professor. Here served for a period as head of the Department of Electronic Engineering. Here he makes contributions to solar energy development, microwave and optoelectronic device development, silicon photonics, as well as contributions to new mobile telecommunication systems and network planning in SA.\r\n\r\nCurrently, he teaches electronics and telecommunications at the TUT to audiences ranging from first-year students to Ph.D. level.\r\n\r\nFor his research in the field of 'Silicon Photonics” since 1990, he has published (as author and co-author) about thirty internationally reviewed articles in scientific journals, contributed to more than forty international conferences, about 25 South African provisional patents (as inventor and co-inventor), 8 PCT international patent applications until now. Of these, two USA patents applications, two European Patents, two Korean patents, and ten SA patents have been granted. A further 4 USA patents, 5 European patents, 3 Korean patents, 3 Chinese patents, and 3 Japanese patents are currently under consideration.\r\n\r\nRecently he has also published an extensive scholarly chapter in an internet open access book on 'Integrating Microphotonic Systems and MOEMS into standard Silicon CMOS Integrated circuitry”.\r\n\r\nFurthermore, Professor Snyman recently steered a new initiative at the TUT by introducing a 'Laboratory for Innovative Electronic Systems ' at the Department of Electrical Engineering. The model of this laboratory or center is to primarily combine outputs as achieved by high-level research with lower-level system development and entrepreneurship in a technical university environment. Students are allocated to projects at different levels with PhDs and Master students allocated to the generation of new knowledge and new technologies, while students at the diploma and Baccalaureus level are allocated to electronic systems development with a direct and a near application for application in industry or the commercial and public sectors in South Africa.\r\n\r\nProfessor Snyman received the WIRSAM Award of 1983 and the WIRSAM Award in 1985 in South Africa for best research papers by a young scientist at two international conferences on electron microscopy in South Africa. He subsequently received the SA Microelectronics Award for the best dissertation emanating from studies executed at a South African university in the field of Physics and Microelectronics in South Africa in 1987. In October of 2011, Professor Snyman received the prestigious Institutional Award for 'Innovator of the Year” for 2010 at the Tshwane University of Technology, South Africa. This award was based on the number of patents recognized and granted by local and international institutions as well as for his contributions concerning innovation at the TUT.",institutionString:null,institution:{name:"University of South Africa",country:{name:"South Africa"}}},{id:"317279",title:"Mr.",name:"Ali",middleName:"Usama",surname:"Syed",slug:"ali-syed",fullName:"Ali Syed",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/317279/images/16024_n.png",biography:"A creative, talented, and innovative young professional who is dedicated, well organized, and capable research fellow with two years of experience in graduate-level research, published in engineering journals and book, with related expertise in Bio-robotics, equally passionate about the aesthetics of the mechanical and electronic system, obtained expertise in the use of MS Office, MATLAB, SolidWorks, LabVIEW, Proteus, Fusion 360, having a grasp on python, C++ and assembly language, possess proven ability in acquiring research grants, previous appointments with social and educational societies with experience in administration, current affiliations with IEEE and Web of Science, a confident presenter at conferences and teacher in classrooms, able to explain complex information to audiences of all levels.",institutionString:null,institution:{name:"Air University",country:{name:"Pakistan"}}},{id:"75526",title:"Ph.D.",name:"Zihni Onur",middleName:null,surname:"Uygun",slug:"zihni-onur-uygun",fullName:"Zihni Onur Uygun",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/75526/images/12_n.jpg",biography:"My undergraduate education and my Master of Science educations at Ege University and at Çanakkale Onsekiz Mart University have given me a firm foundation in Biochemistry, Analytical Chemistry, Biosensors, Bioelectronics, Physical Chemistry and Medicine. After obtaining my degree as a MSc in analytical chemistry, I started working as a research assistant in Ege University Medical Faculty in 2014. In parallel, I enrolled to the MSc program at the Department of Medical Biochemistry at Ege University to gain deeper knowledge on medical and biochemical sciences as well as clinical chemistry in 2014. In my PhD I deeply researched on biosensors and bioelectronics and finished in 2020. Now I have eleven SCI-Expanded Index published papers, 6 international book chapters, referee assignments for different SCIE journals, one international patent pending, several international awards, projects and bursaries. In parallel to my research assistant position at Ege University Medical Faculty, Department of Medical Biochemistry, in April 2016, I also founded a Start-Up Company (Denosens Biotechnology LTD) by the support of The Scientific and Technological Research Council of Turkey. Currently, I am also working as a CEO in Denosens Biotechnology. The main purposes of the company, which carries out R&D as a research center, are to develop new generation biosensors and sensors for both point-of-care diagnostics; such as glucose, lactate, cholesterol and cancer biomarker detections. My specific experimental and instrumental skills are Biochemistry, Biosensor, Analytical Chemistry, Electrochemistry, Mobile phone based point-of-care diagnostic device, POCTs and Patient interface designs, HPLC, Tandem Mass Spectrometry, Spectrophotometry, ELISA.",institutionString:null,institution:{name:"Ege University",country:{name:"Turkey"}}},{id:"246502",title:"Dr.",name:"Jaya T.",middleName:"T",surname:"Varkey",slug:"jaya-t.-varkey",fullName:"Jaya T. Varkey",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/246502/images/11160_n.jpg",biography:"Jaya T. Varkey, PhD, graduated with a degree in Chemistry from Cochin University of Science and Technology, Kerala, India. She obtained a PhD in Chemistry from the School of Chemical Sciences, Mahatma Gandhi University, Kerala, India, and completed a post-doctoral fellowship at the University of Minnesota, USA. She is a research guide at Mahatma Gandhi University and Associate Professor in Chemistry, St. Teresa’s College, Kochi, Kerala, India.\nDr. Varkey received a National Young Scientist award from the Indian Science Congress (1995), a UGC Research award (2016–2018), an Indian National Science Academy (INSA) Visiting Scientist award (2018–2019), and a Best Innovative Faculty award from the All India Association for Christian Higher Education (AIACHE) (2019). She Hashas received the Sr. Mary Cecil prize for best research paper three times. She was also awarded a start-up to develop a tea bag water filter. \nDr. Varkey has published two international books and twenty-seven international journal publications. She is an editorial board member for five international journals.",institutionString:"St. Teresa’s College",institution:null},{id:"250668",title:"Dr.",name:"Ali",middleName:null,surname:"Nabipour Chakoli",slug:"ali-nabipour-chakoli",fullName:"Ali Nabipour Chakoli",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/250668/images/system/250668.jpg",biography:"Academic Qualification:\r\n•\tPhD in Materials Physics and Chemistry, From: Sep. 2006, to: Sep. 2010, School of Materials Science and Engineering, Harbin Institute of Technology, Thesis: Structure and Shape Memory Effect of Functionalized MWCNTs/poly (L-lactide-co-ε-caprolactone) Nanocomposites. Supervisor: Prof. Wei Cai,\r\n•\tM.Sc in Applied Physics, From: 1996, to: 1998, Faculty of Physics & Nuclear Science, Amirkabir Uni. of Technology, Tehran, Iran, Thesis: Determination of Boron in Micro alloy Steels with solid state nuclear track detectors by neutron induced auto radiography, Supervisors: Dr. M. Hosseini Ashrafi and Dr. A. Hosseini.\r\n•\tB.Sc. in Applied Physics, From: 1991, to: 1996, Faculty of Physics & Nuclear Science, Amirkabir Uni. of Technology, Tehran, Iran, Thesis: Design of shielding for Am-Be neutron sources for In Vivo neutron activation analysis, Supervisor: Dr. M. Hosseini Ashrafi.\r\n\r\nResearch Experiences:\r\n1.\tNanomaterials, Carbon Nanotubes, Graphene: Synthesis, Functionalization and Characterization,\r\n2.\tMWCNTs/Polymer Composites: Fabrication and Characterization, \r\n3.\tShape Memory Polymers, Biodegradable Polymers, ORC, Collagen,\r\n4.\tMaterials Analysis and Characterizations: TEM, SEM, XPS, FT-IR, Raman, DSC, DMA, TGA, XRD, GPC, Fluoroscopy, \r\n5.\tInteraction of Radiation with Mater, Nuclear Safety and Security, NDT(RT),\r\n6.\tRadiation Detectors, Calibration (SSDL),\r\n7.\tCompleted IAEA e-learning Courses:\r\nNuclear Security (15 Modules),\r\nNuclear Safety:\r\nTSA 2: Regulatory Protection in Occupational Exposure,\r\nTips & Tricks: Radiation Protection in Radiography,\r\nSafety and Quality in Radiotherapy,\r\nCourse on Sealed Radioactive Sources,\r\nCourse on Fundamentals of Environmental Remediation,\r\nCourse on Planning for Environmental Remediation,\r\nKnowledge Management Orientation Course,\r\nFood Irradiation - Technology, Applications and Good Practices,\r\nEmployment:\r\nFrom 2010 to now: Academic staff, Nuclear Science and Technology Research Institute, Kargar Shomali, Tehran, Iran, P.O. Box: 14395-836.\r\nFrom 1997 to 2006: Expert of Materials Analysis and Characterization. Research Center of Agriculture and Medicine. Rajaeeshahr, Karaj, Iran, P. O. Box: 31585-498.",institutionString:"Atomic Energy Organization of Iran",institution:{name:"Atomic Energy Organization of Iran",country:{name:"Iran"}}},{id:"248279",title:"Dr.",name:"Monika",middleName:"Elzbieta",surname:"Machoy",slug:"monika-machoy",fullName:"Monika Machoy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/248279/images/system/248279.jpeg",biography:"Monika Elżbieta Machoy, MD, graduated with distinction from the Faculty of Medicine and Dentistry at the Pomeranian Medical University in 2009, defended her PhD thesis with summa cum laude in 2016 and is currently employed as a researcher at the Department of Orthodontics of the Pomeranian Medical University. She expanded her professional knowledge during a one-year scholarship program at the Ernst Moritz Arndt University in Greifswald, Germany and during a three-year internship at the Technical University in Dresden, Germany. She has been a speaker at numerous orthodontic conferences, among others, American Association of Orthodontics, European Orthodontic Symposium and numerous conferences of the Polish Orthodontic Society. She conducts research focusing on the effect of orthodontic treatment on dental and periodontal tissues and the causes of pain in orthodontic patients.",institutionString:"Pomeranian Medical University",institution:{name:"Pomeranian Medical University",country:{name:"Poland"}}},{id:"252743",title:"Prof.",name:"Aswini",middleName:"Kumar",surname:"Kar",slug:"aswini-kar",fullName:"Aswini Kar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/252743/images/10381_n.jpg",biography:"uploaded in cv",institutionString:null,institution:{name:"KIIT University",country:{name:"India"}}},{id:"204256",title:"Dr.",name:"Anil",middleName:"Kumar",surname:"Kumar Sahu",slug:"anil-kumar-sahu",fullName:"Anil Kumar Sahu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/204256/images/14201_n.jpg",biography:"I have nearly 11 years of research and teaching experience. I have done my master degree from University Institute of Pharmacy, Pt. Ravi Shankar Shukla University, Raipur, Chhattisgarh India. I have published 16 review and research articles in international and national journals and published 4 chapters in IntechOpen, the world’s leading publisher of Open access books. I have presented many papers at national and international conferences. I have received research award from Indian Drug Manufacturers Association in year 2015. My research interest extends from novel lymphatic drug delivery systems, oral delivery system for herbal bioactive to formulation optimization.",institutionString:null,institution:{name:"Chhattisgarh Swami Vivekanand Technical University",country:{name:"India"}}},{id:"253468",title:"Dr.",name:"Mariusz",middleName:null,surname:"Marzec",slug:"mariusz-marzec",fullName:"Mariusz Marzec",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/253468/images/system/253468.png",biography:"An assistant professor at Department of Biomedical Computer Systems, at Institute of Computer Science, Silesian University in Katowice. Scientific interests: computer analysis and processing of images, biomedical images, databases and programming languages. He is an author and co-author of scientific publications covering analysis and processing of biomedical images and development of database systems.",institutionString:"University of Silesia",institution:null},{id:"212432",title:"Prof.",name:"Hadi",middleName:null,surname:"Mohammadi",slug:"hadi-mohammadi",fullName:"Hadi Mohammadi",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/212432/images/system/212432.jpeg",biography:"Dr. Hadi Mohammadi is a biomedical engineer with hands-on experience in the design and development of many engineering structures and medical devices through various projects that he has been involved in over the past twenty years. Dr. Mohammadi received his BSc. and MSc. degrees in Mechanical Engineering from Sharif University of Technology, Tehran, Iran, and his PhD. degree in Biomedical Engineering (biomaterials) from the University of Western Ontario. He was a postdoctoral trainee for almost four years at University of Calgary and Harvard Medical School. He is an industry innovator having created the technology to produce lifelike synthetic platforms that can be used for the simulation of almost all cardiovascular reconstructive surgeries. He’s been heavily involved in the design and development of cardiovascular devices and technology for the past 10 years. He is currently an Assistant Professor with the University of British Colombia, Canada.",institutionString:"University of British Columbia",institution:{name:"University of British Columbia",country:{name:"Canada"}}},{id:"254463",title:"Prof.",name:"Haisheng",middleName:null,surname:"Yang",slug:"haisheng-yang",fullName:"Haisheng Yang",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/254463/images/system/254463.jpeg",biography:"Haisheng Yang, Ph.D., Professor and Director of the Department of Biomedical Engineering, College of Life Science and Bioengineering, Beijing University of Technology. He received his Ph.D. degree in Mechanics/Biomechanics from Harbin Institute of Technology (jointly with University of California, Berkeley). Afterwards, he worked as a Postdoctoral Research Associate in the Purdue Musculoskeletal Biology and Mechanics Lab at the Department of Basic Medical Sciences, Purdue University, USA. He also conducted research in the Research Centre of Shriners Hospitals for Children-Canada at McGill University, Canada. Dr. Yang has over 10 years research experience in orthopaedic biomechanics and mechanobiology of bone adaptation and regeneration. He earned an award from Beijing Overseas Talents Aggregation program in 2017 and serves as Beijing Distinguished Professor.",institutionString:"Beijing University of Technology",institution:null},{id:"255757",title:"Dr.",name:"Igor",middleName:"Victorovich",surname:"Lakhno",slug:"igor-lakhno",fullName:"Igor Lakhno",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/255757/images/system/255757.jpg",biography:"Lakhno Igor Victorovich was born in 1971 in Kharkiv (Ukraine). \nMD – 1994, Kharkiv National Medical Univesity.\nOb&Gyn; – 1997, master courses in Kharkiv Medical Academy of Postgraduate Education.\nPhD – 1999, Kharkiv National Medical Univesity.\nDSc – 2019, PL Shupik National Academy of Postgraduate Education \nLakhno Igor has been graduated from an international training courses on reproductive medicine and family planning held in Debrecen University (Hungary) in 1997. Since 1998 Lakhno Igor has worked as an associate professor of the department of obstetrics and gynecology of VN Karazin National University and an associate professor of the perinatology, obstetrics and gynecology department of Kharkiv Medical Academy of Postgraduate Education. Since June 2019 he’s a professor of the department of obstetrics and gynecology of VN Karazin National University and a professor of the perinatology, obstetrics and gynecology department of Kharkiv Medical Academy of Postgraduate Education . He’s an author of about 200 printed works and there are 17 of them in Scopus or Web of Science databases. Lakhno Igor is a rewiever of Journal of Obstetrics and Gynaecology (Taylor and Francis), Informatics in Medicine Unlocked (Elsevier), The Journal of Obstetrics and Gynecology Research (Wiley), Endocrine, Metabolic & Immune Disorders-Drug Targets (Bentham Open), The Open Biomedical Engineering Journal (Bentham Open), etc. He’s defended a dissertation for DSc degree \\'Pre-eclampsia: prediction, prevention and treatment”. Lakhno Igor has participated as a speaker in several international conferences and congresses (International Conference on Biological Oscillations April 10th-14th 2016, Lancaster, UK, The 9th conference of the European Study Group on Cardiovascular Oscillations). His main scientific interests: obstetrics, women’s health, fetal medicine, cardiovascular medicine.",institutionString:"V.N. Karazin Kharkiv National University",institution:{name:"Kharkiv Medical Academy of Postgraduate Education",country:{name:"Ukraine"}}},{id:"89721",title:"Dr.",name:"Mehmet",middleName:"Cuneyt",surname:"Ozmen",slug:"mehmet-ozmen",fullName:"Mehmet Ozmen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/89721/images/7289_n.jpg",biography:null,institutionString:null,institution:{name:"Gazi University",country:{name:"Turkey"}}},{id:"243698",title:"M.D.",name:"Xiaogang",middleName:null,surname:"Wang",slug:"xiaogang-wang",fullName:"Xiaogang Wang",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/243698/images/system/243698.png",biography:"Dr. Xiaogang Wang, a faculty member of Shanxi Eye Hospital specializing in the treatment of cataract and retinal disease and a tutor for postgraduate students of Shanxi Medical University, worked in the COOL Lab as an international visiting scholar under the supervision of Dr. David Huang and Yali Jia from October 2012 through November 2013. Dr. Wang earned an MD from Shanxi Medical University and a Ph.D. from Shanghai Jiao Tong University. Dr. Wang was awarded two research project grants focused on multimodal optical coherence tomography imaging and deep learning in cataract and retinal disease, from the National Natural Science Foundation of China. He has published around 30 peer-reviewed journal papers and four book chapters and co-edited one book.",institutionString:"Shanxi Eye Hospital",institution:{name:"Shanxi Eye Hospital",country:{name:"China"}}},{id:"242893",title:"Ph.D. Student",name:"Joaquim",middleName:null,surname:"De Moura",slug:"joaquim-de-moura",fullName:"Joaquim De Moura",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/242893/images/7133_n.jpg",biography:"Joaquim de Moura received his degree in Computer Engineering in 2014 from the University of A Coruña (Spain). In 2016, he received his M.Sc degree in Computer Engineering from the same university. He is currently pursuing his Ph.D degree in Computer Science in a collaborative project between ophthalmology centers in Galicia and the University of A Coruña. His research interests include computer vision, machine learning algorithms and analysis and medical imaging processing of various kinds.",institutionString:null,institution:{name:"University of A Coruña",country:{name:"Spain"}}},{id:"267434",title:"Dr.",name:"Rohit",middleName:null,surname:"Raja",slug:"rohit-raja",fullName:"Rohit Raja",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRZkkQAG/Profile_Picture_2022-05-09T12:55:18.jpg",biography:null,institutionString:null,institution:null},{id:"294334",title:"B.Sc.",name:"Marc",middleName:null,surname:"Bruggeman",slug:"marc-bruggeman",fullName:"Marc Bruggeman",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/294334/images/8242_n.jpg",biography:"Chemical engineer graduate, with a passion for material science and specific interest in polymers - their near infinite applications intrigue me. \n\nI plan to continue my scientific career in the field of polymeric biomaterials as I am fascinated by intelligent, bioactive and biomimetic materials for use in both consumer and medical applications.",institutionString:null,institution:null},{id:"244950",title:"Dr.",name:"Salvatore",middleName:null,surname:"Di Lauro",slug:"salvatore-di-lauro",fullName:"Salvatore Di Lauro",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0030O00002bSF1HQAW/ProfilePicture%202021-12-20%2014%3A54%3A14.482",biography:"Name:\n\tSALVATORE DI LAURO\nAddress:\n\tHospital Clínico Universitario Valladolid\nAvda Ramón y Cajal 3\n47005, Valladolid\nSpain\nPhone number: \nFax\nE-mail:\n\t+34 983420000 ext 292\n+34 983420084\nsadilauro@live.it\nDate and place of Birth:\nID Number\nMedical Licence \nLanguages\t09-05-1985. Villaricca (Italy)\n\nY1281863H\n474707061\nItalian (native language)\nSpanish (read, written, spoken)\nEnglish (read, written, spoken)\nPortuguese (read, spoken)\nFrench (read)\n\t\t\nCurrent position (title and company)\tDate (Year)\nVitreo-Retinal consultant in ophthalmology. Hospital Clinico Universitario Valladolid. Sacyl. National Health System.\nVitreo-Retinal consultant in ophthalmology. Instituto Oftalmologico Recoletas. Red Hospitalaria Recoletas. Private practise.\t2017-today\n\n2019-today\n\t\n\t\nEducation (High school, university and postgraduate training > 3 months)\tDate (Year)\nDegree in Medicine and Surgery. University of Neaples 'Federico II”\nResident in Opthalmology. Hospital Clinico Universitario Valladolid\nMaster in Vitreo-Retina. IOBA. University of Valladolid\nFellow of the European Board of Ophthalmology. Paris\nMaster in Research in Ophthalmology. University of Valladolid\t2003-2009\n2012-2016\n2016-2017\n2016\n2012-2013\n\t\nEmployments (company and positions)\tDate (Year)\nResident in Ophthalmology. Hospital Clinico Universitario Valladolid. Sacyl.\nFellow in Vitreo-Retina. IOBA. University of Valladolid\nVitreo-Retinal consultant in ophthalmology. Hospital Clinico Universitario Valladolid. Sacyl. National Health System.\nVitreo-Retinal consultant in ophthalmology. Instituto Oftalmologico Recoletas. Red Hospitalaria Recoletas. \n\t2012-2016\n2016-2017\n2017-today\n\n2019-Today\n\n\n\t\nClinical Research Experience (tasks and role)\tDate (Year)\nAssociated investigator\n\n' FIS PI20/00740: DESARROLLO DE UNA CALCULADORA DE RIESGO DE\nAPARICION DE RETINOPATIA DIABETICA BASADA EN TECNICAS DE IMAGEN MULTIMODAL EN PACIENTES DIABETICOS TIPO 1. Grant by: Ministerio de Ciencia e Innovacion \n\n' (BIO/VA23/14) Estudio clínico multicéntrico y prospectivo para validar dos\nbiomarcadores ubicados en los genes p53 y MDM2 en la predicción de los resultados funcionales de la cirugía del desprendimiento de retina regmatógeno. Grant by: Gerencia Regional de Salud de la Junta de Castilla y León.\n' Estudio multicéntrico, aleatorizado, con enmascaramiento doble, en 2 grupos\nparalelos y de 52 semanas de duración para comparar la eficacia, seguridad e inmunogenicidad de SOK583A1 respecto a Eylea® en pacientes con degeneración macular neovascular asociada a la edad' (CSOK583A12301; N.EUDRA: 2019-004838-41; FASE III). Grant by Hexal AG\n\n' Estudio de fase III, aleatorizado, doble ciego, con grupos paralelos, multicéntrico para comparar la eficacia y la seguridad de QL1205 frente a Lucentis® en pacientes con degeneración macular neovascular asociada a la edad. (EUDRACT: 2018-004486-13). Grant by Qilu Pharmaceutical Co\n\n' Estudio NEUTON: Ensayo clinico en fase IV para evaluar la eficacia de aflibercept en pacientes Naive con Edema MacUlar secundario a Oclusion de Vena CenTral de la Retina (OVCR) en regimen de tratamientO iNdividualizado Treat and Extend (TAE)”, (2014-000975-21). Grant by Fundacion Retinaplus\n\n' Evaluación de la seguridad y bioactividad de anillos de tensión capsular en conejo. Proyecto Procusens. Grant by AJL, S.A.\n\n'Estudio epidemiológico, prospectivo, multicéntrico y abierto\\npara valorar la frecuencia de la conjuntivitis adenovírica diagnosticada mediante el test AdenoPlus®\\nTest en pacientes enfermos de conjuntivitis aguda”\\n. National, multicenter study. Grant by: NICOX.\n\nEuropean multicentric trial: 'Evaluation of clinical outcomes following the use of Systane Hydration in patients with dry eye”. Study Phase 4. Grant by: Alcon Labs'\n\nVLPs Injection and Activation in a Rabbit Model of Uveal Melanoma. Grant by Aura Bioscience\n\nUpdating and characterization of a rabbit model of uveal melanoma. Grant by Aura Bioscience\n\nEnsayo clínico en fase IV para evaluar las variantes genéticas de la vía del VEGF como biomarcadores de eficacia del tratamiento con aflibercept en pacientes con degeneración macular asociada a la edad (DMAE) neovascular. Estudio BIOIMAGE. IMO-AFLI-2013-01\n\nEstudio In-Eye:Ensayo clínico en fase IV, abierto, aleatorizado, de 2 brazos,\nmulticçentrico y de 12 meses de duración, para evaluar la eficacia y seguridad de un régimen de PRN flexible individualizado de 'esperar y extender' versus un régimen PRN según criterios de estabilización mediante evaluaciones mensuales de inyecciones intravítreas de ranibizumab 0,5 mg en pacientes naive con neovascularización coriodea secunaria a la degeneración macular relacionada con la edad. CP: CRFB002AES03T\n\nTREND: Estudio Fase IIIb multicéntrico, randomizado, de 12 meses de\nseguimiento con evaluador de la agudeza visual enmascarado, para evaluar la eficacia y la seguridad de ranibizumab 0.5mg en un régimen de tratar y extender comparado con un régimen mensual, en pacientes con degeneración macular neovascular asociada a la edad. CP: CRFB002A2411 Código Eudra CT:\n2013-002626-23\n\n\n\nPublications\t\n\n2021\n\n\n\n\n2015\n\n\n\n\n2021\n\n\n\n\n\n2021\n\n\n\n\n2015\n\n\n\n\n2015\n\n\n2014\n\n\n\n\n2015-16\n\n\n\n2015\n\n\n2014\n\n\n2014\n\n\n\n\n2014\n\n\n\n\n\n\n\n2014\n\nJose Carlos Pastor; Jimena Rojas; Salvador Pastor-Idoate; Salvatore Di Lauro; Lucia Gonzalez-Buendia; Santiago Delgado-Tirado. Proliferative vitreoretinopathy: A new concept of disease pathogenesis and practical\nconsequences. Progress in Retinal and Eye Research. 51, pp. 125 - 155. 03/2016. DOI: 10.1016/j.preteyeres.2015.07.005\n\n\nLabrador-Velandia S; Alonso-Alonso ML; Di Lauro S; García-Gutierrez MT; Srivastava GK; Pastor JC; Fernandez-Bueno I. Mesenchymal stem cells provide paracrine neuroprotective resources that delay degeneration of co-cultured organotypic neuroretinal cultures.Experimental Eye Research. 185, 17/05/2019. DOI: 10.1016/j.exer.2019.05.011\n\nSalvatore Di Lauro; Maria Teresa Garcia Gutierrez; Ivan Fernandez Bueno. Quantification of pigment epithelium-derived factor (PEDF) in an ex vivo coculture of retinal pigment epithelium cells and neuroretina.\nJournal of Allbiosolution. 2019. ISSN 2605-3535\n\nSonia Labrador Velandia; Salvatore Di Lauro; Alonso-Alonso ML; Tabera Bartolomé S; Srivastava GK; Pastor JC; Fernandez-Bueno I. Biocompatibility of intravitreal injection of human mesenchymal stem cells in immunocompetent rabbits. Graefe's archive for clinical and experimental ophthalmology. 256 - 1, pp. 125 - 134. 01/2018. DOI: 10.1007/s00417-017-3842-3\n\n\nSalvatore Di Lauro, David Rodriguez-Crespo, Manuel J Gayoso, Maria T Garcia-Gutierrez, J Carlos Pastor, Girish K Srivastava, Ivan Fernandez-Bueno. A novel coculture model of porcine central neuroretina explants and retinal pigment epithelium cells. Molecular Vision. 2016 - 22, pp. 243 - 253. 01/2016.\n\nSalvatore Di Lauro. Classifications for Proliferative Vitreoretinopathy ({PVR}): An Analysis of Their Use in Publications over the Last 15 Years. Journal of Ophthalmology. 2016, pp. 1 - 6. 01/2016. DOI: 10.1155/2016/7807596\n\nSalvatore Di Lauro; Rosa Maria Coco; Rosa Maria Sanabria; Enrique Rodriguez de la Rua; Jose Carlos Pastor. Loss of Visual Acuity after Successful Surgery for Macula-On Rhegmatogenous Retinal Detachment in a Prospective Multicentre Study. Journal of Ophthalmology. 2015:821864, 2015. DOI: 10.1155/2015/821864\n\nIvan Fernandez-Bueno; Salvatore Di Lauro; Ivan Alvarez; Jose Carlos Lopez; Maria Teresa Garcia-Gutierrez; Itziar Fernandez; Eva Larra; Jose Carlos Pastor. Safety and Biocompatibility of a New High-Density Polyethylene-Based\nSpherical Integrated Porous Orbital Implant: An Experimental Study in Rabbits. Journal of Ophthalmology. 2015:904096, 2015. DOI: 10.1155/2015/904096\n\nPastor JC; Pastor-Idoate S; Rodríguez-Hernandez I; Rojas J; Fernandez I; Gonzalez-Buendia L; Di Lauro S; Gonzalez-Sarmiento R. Genetics of PVR and RD. Ophthalmologica. 232 - Suppl 1, pp. 28 - 29. 2014\n\nRodriguez-Crespo D; Di Lauro S; Singh AK; Garcia-Gutierrez MT; Garrosa M; Pastor JC; Fernandez-Bueno I; Srivastava GK. Triple-layered mixed co-culture model of RPE cells with neuroretina for evaluating the neuroprotective effects of adipose-MSCs. Cell Tissue Res. 358 - 3, pp. 705 - 716. 2014.\nDOI: 10.1007/s00441-014-1987-5\n\nCarlo De Werra; Salvatore Condurro; Salvatore Tramontano; Mario Perone; Ivana Donzelli; Salvatore Di Lauro; Massimo Di Giuseppe; Rosa Di Micco; Annalisa Pascariello; Antonio Pastore; Giorgio Diamantis; Giuseppe Galloro. Hydatid disease of the liver: thirty years of surgical experience.Chirurgia italiana. 59 - 5, pp. 611 - 636.\n(Italia): 2007. ISSN 0009-4773\n\nChapters in books\n\t\n' Salvador Pastor Idoate; Salvatore Di Lauro; Jose Carlos Pastor Jimeno. PVR: Pathogenesis, Histopathology and Classification. Proliferative Vitreoretinopathy with Small Gauge Vitrectomy. Springer, 2018. ISBN 978-3-319-78445-8\nDOI: 10.1007/978-3-319-78446-5_2. \n\n' Salvatore Di Lauro; Maria Isabel Lopez Galvez. Quistes vítreos en una mujer joven. Problemas diagnósticos en patología retinocoroidea. Sociedad Española de Retina-Vitreo. 2018.\n\n' Salvatore Di Lauro; Salvador Pastor Idoate; Jose Carlos Pastor Jimeno. iOCT in PVR management. OCT Applications in Opthalmology. pp. 1 - 8. INTECH, 2018. DOI: 10.5772/intechopen.78774.\n\n' Rosa Coco Martin; Salvatore Di Lauro; Salvador Pastor Idoate; Jose Carlos Pastor. amponadores, manipuladores y tinciones en la cirugía del traumatismo ocular.Trauma Ocular. Ponencia de la SEO 2018..\n\n' LOPEZ GALVEZ; DI LAURO; CRESPO. OCT angiografia y complicaciones retinianas de la diabetes. PONENCIA SEO 2021, CAPITULO 20. (España): 2021.\n\n' Múltiples desprendimientos neurosensoriales bilaterales en paciente joven. Enfermedades Degenerativas De Retina Y Coroides. SERV 04/2016. \n' González-Buendía L; Di Lauro S; Pastor-Idoate S; Pastor Jimeno JC. Vitreorretinopatía proliferante (VRP) e inflamación: LA INFLAMACIÓN in «INMUNOMODULADORES Y ANTIINFLAMATORIOS: MÁS ALLÁ DE LOS CORTICOIDES. RELACION DE PONENCIAS DE LA SOCIEDAD ESPAÑOLA DE OFTALMOLOGIA. 10/2014.",institutionString:null,institution:null},{id:"265335",title:"Mr.",name:"Stefan",middleName:"Radnev",surname:"Stefanov",slug:"stefan-stefanov",fullName:"Stefan Stefanov",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/265335/images/7562_n.jpg",biography:null,institutionString:null,institution:null},{id:"318905",title:"Prof.",name:"Elvis",middleName:"Kwason",surname:"Tiburu",slug:"elvis-tiburu",fullName:"Elvis Tiburu",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Ghana",country:{name:"Ghana"}}},{id:"336193",title:"Dr.",name:"Abdullah",middleName:null,surname:"Alamoudi",slug:"abdullah-alamoudi",fullName:"Abdullah Alamoudi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Majmaah University",country:{name:"Saudi Arabia"}}},{id:"318657",title:"MSc.",name:"Isabell",middleName:null,surname:"Steuding",slug:"isabell-steuding",fullName:"Isabell Steuding",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Harz University of Applied Sciences",country:{name:"Germany"}}},{id:"318656",title:"BSc.",name:"Peter",middleName:null,surname:"Kußmann",slug:"peter-kussmann",fullName:"Peter Kußmann",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Harz University of Applied Sciences",country:{name:"Germany"}}},{id:"338222",title:"Mrs.",name:"María José",middleName:null,surname:"Lucía Mudas",slug:"maria-jose-lucia-mudas",fullName:"María José Lucía Mudas",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Carlos III University of Madrid",country:{name:"Spain"}}},{id:"147824",title:"Mr.",name:"Pablo",middleName:null,surname:"Revuelta Sanz",slug:"pablo-revuelta-sanz",fullName:"Pablo Revuelta Sanz",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Carlos III University of Madrid",country:{name:"Spain"}}}]}},subseries:{item:{id:"24",type:"subseries",title:"Computer Vision",keywords:"Image Analysis, Scene Understanding, Biometrics, Deep Learning, Software Implementation, Hardware Implementation, Natural Images, Medical Images, Robotics, VR/AR",scope:"The scope of this topic is to disseminate the recent advances in the rapidly growing field of computer vision from both the theoretical and practical points of view. Novel computational algorithms for image analysis, scene understanding, biometrics, deep learning and their software or hardware implementations for natural and medical images, robotics, VR/AR, applications are some research directions relevant to this topic.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/24.jpg",hasOnlineFirst:!0,hasPublishedBooks:!1,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,series:{id:"14",title:"Artificial Intelligence",doi:"10.5772/intechopen.79920",issn:"2633-1403"},editorialBoard:[{id:"1177",title:"Prof.",name:"Antonio",middleName:"J. 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This group of bio-inspired metaheuristics solves multiple optimization problems by applying the metaphor of natural selection. It so far has solved problems such as resource allocation, routing, schedule planning, and engineering design. Moreover, in the field of machine learning, evolutionary computation has carved out a significant niche both in the generation of learning models and in the automatic design and optimization of hyperparameters in deep learning models. This collection aims to include quality volumes on various topics related to evolutionary algorithms and, alternatively, other metaheuristics of interest inspired by nature. For example, some of the issues of interest could be the following: Advances in evolutionary computation (Genetic algorithms, Genetic programming, Bio-inspired metaheuristics, Hybrid metaheuristics, Parallel ECs); Applications of evolutionary algorithms (Machine learning and Data Mining with EAs, Search-Based Software Engineering, Scheduling, and Planning Applications, Smart Transport Applications, Applications to Games, Image Analysis, Signal Processing and Pattern Recognition, Applications to Sustainability).",annualVolume:11421,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",editor:{id:"136112",title:"Dr.",name:"Sebastian",middleName:null,surname:"Ventura Soto",fullName:"Sebastian Ventura Soto",profilePictureURL:"https://mts.intechopen.com/storage/users/136112/images/system/136112.png",institutionString:null,institution:{name:"University of Córdoba",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"111683",title:"Prof.",name:"Elmer",middleName:"P.",surname:"Dadios",fullName:"Elmer Dadios",profilePictureURL:"https://mts.intechopen.com/storage/users/111683/images/system/111683.jpg",institutionString:"De La Salle University",institution:{name:"De La Salle University",institutionURL:null,country:{name:"Philippines"}}},{id:"106873",title:"Prof.",name:"Hongwei",middleName:null,surname:"Ge",fullName:"Hongwei Ge",profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institutionString:null,institution:{name:"Dalian University of Technology",institutionURL:null,country:{name:"China"}}},{id:"171056",title:"Dr.",name:"Sotirios",middleName:null,surname:"Goudos",fullName:"Sotirios Goudos",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bS9IuQAK/Profile_Picture_1622623673666",institutionString:null,institution:{name:"Aristotle University of Thessaloniki",institutionURL:null,country:{name:"Greece"}}},{id:"15895",title:"Assistant Prof.",name:"Takashi",middleName:null,surname:"Kuremoto",fullName:"Takashi Kuremoto",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYLrqQAG/Profile_Picture_1625656196038",institutionString:null,institution:{name:"Nippon Institute of Technology",institutionURL:null,country:{name:"Japan"}}},{id:"125844",title:"Prof.",name:"Wellington",middleName:"Pinheiro Dos",surname:"Santos",fullName:"Wellington Santos",profilePictureURL:"https://mts.intechopen.com/storage/users/125844/images/4878_n.jpg",institutionString:null,institution:{name:"Federal University of Pernambuco",institutionURL:null,country:{name:"Brazil"}}}]},{id:"26",title:"Machine Learning and Data Mining",keywords:"Intelligent Systems, Machine Learning, Data Science, Data Mining, Artificial Intelligence",scope:"The scope of machine learning and data mining is immense and is growing every day. It has become a massive part of our daily lives, making predictions based on experience, making this a fascinating area that solves problems that otherwise would not be possible or easy to solve. This topic aims to encompass algorithms that learn from experience (supervised and unsupervised), improve their performance over time and enable machines to make data-driven decisions. It is not limited to any particular applications, but contributions are encouraged from all disciplines.",annualVolume:11422,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/26.jpg",editor:{id:"24555",title:"Dr.",name:"Marco Antonio",middleName:null,surname:"Aceves Fernandez",fullName:"Marco Antonio Aceves Fernandez",profilePictureURL:"https://mts.intechopen.com/storage/users/24555/images/system/24555.jpg",institutionString:null,institution:{name:"Autonomous University of Queretaro",institutionURL:null,country:{name:"Mexico"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"43680",title:"Prof.",name:"Ciza",middleName:null,surname:"Thomas",fullName:"Ciza Thomas",profilePictureURL:"https://mts.intechopen.com/storage/users/43680/images/system/43680.jpeg",institutionString:null,institution:{name:"Government of Kerala",institutionURL:null,country:{name:"India"}}},{id:"16614",title:"Prof.",name:"Juan Ignacio",middleName:null,surname:"Guerrero Alonso",fullName:"Juan Ignacio Guerrero Alonso",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002g6HB8QAM/Profile_Picture_1627901127555",institutionString:null,institution:{name:"University of Seville",institutionURL:null,country:{name:"Spain"}}},{id:"3095",title:"Prof.",name:"Kenji",middleName:null,surname:"Suzuki",fullName:"Kenji Suzuki",profilePictureURL:"https://mts.intechopen.com/storage/users/3095/images/1592_n.jpg",institutionString:null,institution:{name:"University of Chicago",institutionURL:null,country:{name:"United States of America"}}},{id:"214067",title:"Dr.",name:"W. 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The area covers many techniques that offer solutions to emerging problems in robotics and enterprise-level software systems. Collaborative intelligence is highly and effectively achieved with multi-agent systems. Areas of application include swarms of robots, flocks of UAVs, collaborative software management. Given the level of technological enhancements, the popularity of machine learning in use has opened a new chapter in multi-agent studies alongside the practical challenges and long-lasting collaboration issues in the field. It has increased the urgency and the need for further studies in this field. We welcome chapters presenting research on the many applications of multi-agent studies including, but not limited to, the following key areas: machine learning for multi-agent systems; modeling swarms robots and flocks of UAVs with multi-agent systems; decision science and multi-agent systems; software engineering for and with multi-agent systems; tools and technologies of multi-agent systems.",annualVolume:11423,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/27.jpg",editor:{id:"148497",title:"Dr.",name:"Mehmet",middleName:"Emin",surname:"Aydin",fullName:"Mehmet Aydin",profilePictureURL:"https://mts.intechopen.com/storage/users/148497/images/system/148497.jpg",institutionString:null,institution:{name:"University of the West of England",institutionURL:null,country:{name:"United Kingdom"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"275140",title:"Dr.",name:"Dinh Hoa",middleName:null,surname:"Nguyen",fullName:"Dinh Hoa Nguyen",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRbnKQAS/Profile_Picture_1622204093453",institutionString:null,institution:{name:"Kyushu University",institutionURL:null,country:{name:"Japan"}}},{id:"20259",title:"Dr.",name:"Hongbin",middleName:null,surname:"Ma",fullName:"Hongbin Ma",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRhDJQA0/Profile_Picture_2022-05-02T08:25:21.jpg",institutionString:null,institution:{name:"Beijing Institute of Technology",institutionURL:null,country:{name:"China"}}},{id:"28640",title:"Prof.",name:"Yasushi",middleName:null,surname:"Kambayashi",fullName:"Yasushi Kambayashi",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYOQxQAO/Profile_Picture_1625660525470",institutionString:null,institution:{name:"Nippon Institute of Technology",institutionURL:null,country:{name:"Japan"}}}]}]}},libraryRecommendation:{success:null,errors:{},institutions:[]},route:{name:"profile.detail",path:"/profiles/116865",hash:"",query:{},params:{id:"116865"},fullPath:"/profiles/116865",meta:{},from:{name:null,path:"/",hash:"",query:{},params:{},fullPath:"/",meta:{}}}},function(){var e;(e=document.currentScript||document.scripts[document.scripts.length-1]).parentNode.removeChild(e)}()