\r\n\tThe protection of biodiversity is a major target of the European Union Marine Strategy Framework Directive, requiring an assessment of the status of biodiversity on the level of species, habitats, and ecosystems including genetic diversity and the role of biodiversity in food web structure and functioning. The restoration of marine ecosystems can support the productivity and reliability of goods and services that the ocean provides to humankind, to maintain ecosystem integrity and stability. Some of the goods produced by the marine ecosystem services are fish harvests, wild plant and animal resources, water, some of the services provided recreation, tourism, breeding and nursery habitats, water transport, carbon sequestration, erosion control, and habitat provision.
",isbn:"978-1-83968-460-9",printIsbn:"978-1-83968-459-3",pdfIsbn:"978-1-83968-544-6",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,isSalesforceBook:!1,isNomenclature:!1,hash:"727e7eb3d4ba529ec5eb4f150e078523",bookSignature:"Dr. Ana M.M. Marta Gonçalves",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/10845.jpg",keywords:"Non-indigenous Species, Dynamics, Ecosystem Maturation, Ecological Succession, Water Quality, Recovery, Biodiversity, Environmental Status, Ecosystem Services, Goods Production, Carbohydrates, Carrageenan",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"April 14th 2022",dateEndSecondStepPublish:"June 22nd 2022",dateEndThirdStepPublish:"August 21st 2022",dateEndFourthStepPublish:"November 9th 2022",dateEndFifthStepPublish:"January 8th 2023",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"16 days",secondStepPassed:!0,areRegistrationsClosed:!1,currentStepOfPublishingProcess:3,editedByType:null,kuFlag:!1,biosketch:"Dr. Ana Marta Gonçalves (h-index 19) holds a Ph.D. in Biology, from the University of Coimbra, Portugal, in collaboration with Ghent University, in 2011. During her research career obtained several grants is highly international competitive calls, including the MARS award for young scientists funded by The Royal Netherlands Institute for Sea Research (NIOZ) and the Foundation for Science and Technology (FCT, Portugal) grants.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"320124",title:"Dr.",name:"Ana M.M.",middleName:"Marta",surname:"Gonçalves",slug:"ana-m.m.-goncalves",fullName:"Ana M.M. Gonçalves",profilePictureURL:"https://mts.intechopen.com/storage/users/320124/images/system/320124.jpg",biography:"Ana Marta Gonçalves obtained a Ph.D. in Biology with a specialization in Ecology from the University of Coimbra, Portugal, in collaboration with Ghent University, Belgium, in 2011. Currently, she is an auxiliary researcher at the Marine and Environmental Sciences Center (MARE), Portugal, where she is also a member of the Directive Board. Since 2016, she has been a member of the Scientific Council of the Institute for Interdisciplinary Research, University of Coimbra (IIIUC). Dr. Gonçalves holds various administrative and management positions in international networks, societies (e.g., Society of Environmental Toxicology and Chemistry, AIL), and associations (e.g., PROAQUA). She is an editorial board member and reviewer for several indexed journals. She has published more than 70 journal articles, 50 book chapters, and 165 communications in international scientific events. She participated as a member and/or coordinator in more than twenty-five national and international projects and is currently the coordinator of four research projects. She has supervised more than ninety-five national and international undergraduate and graduate students. She has experience as a teacher of university courses and in accredited training sessions for teachers. Additionally, she has coordinated several ocean literacy and environmental education activities for kindergarten and school students. During her research career, Dr. Gonçalves obtained several grants and a MARS award for young scientists funded by The Royal Netherlands Institute for Sea Research (NIOZ).\n\nShe has expertise in biosafety, biochemical pathways, and impacts of stressors in aquatic species. Her research focus is on the valorization of marine resources and their applications in the industrial sector, such as the food and pharmaceutical industries. Her studies also highlight the application of biomarker tools for monitoring and managing aquatic systems",institutionString:"University of Coimbra",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"University of Coimbra",institutionURL:null,country:{name:"Portugal"}}}],coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"12",title:"Environmental Sciences",slug:"environmental-sciences"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"278926",firstName:"Ivana",lastName:"Barac",middleName:null,title:"Ms.",imageUrl:"https://mts.intechopen.com/storage/users/278926/images/8058_n.jpg",email:"ivana.b@intechopen.com",biography:"As an Author Service Manager my responsibilities include monitoring and facilitating all publishing activities for authors and editors. From chapter submission and review, to approval and revision, copyediting and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. 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On the other hand, the shortage of drought and varieties of geographical possibilities justifies the approach to developing offshore wind farms.
The offshore wind farms are wind turbines that are built several kilometers offshore in the ocean or sea for more efficient utilization of wind energy. Although this method is already very costly, increasing technological advances in turbines materials and bases, composite structures, as well as the construction of multimegawatt generators accelerate the deployment of offshore wind farms and make them a huge part of future energy production [1, 2, 3].
This chapter starts with introduction to the wind energy resource. After that, the global ocean wind energy resource is presented. Ocean wind energy technologies are explained in the next section. Then, the possible structure of offshore wind turbine is considered. Finally, challenges of offshore wind power are discoursed.
One of the renewable energy resources that can be used to generate electricity is ocean wind. Two-thirds of the Earth’s surface is water; this potential could be used to generate electricity in different parts of the planet. However, using the ocean wind source varies depending on the geographical conditions and seasons. Currently, the UK has the world’s leading outsourcing of 51% of its offshore power plants. Denmark with 21% of the total offshore power plants in the world is in the second place. Other countries such as the USA, the Netherlands, Belgium, China, and Japan are also active in this field [4]. Figure 1 shows the items that need to be considered in the market for the production and sale of electricity through ocean wind energy. The most critical issues regarding the wind ocean project are foundation type and water depth which are based on geographic information in the region.
Essential issues in assessing ocean wind power plant.
Over the past few decades, large countries like China and Japan have been using ocean wind energy for electricity production. According to wind energy reports at the World Wind Energy Council, China’s investment in this area is more than the total European Union and is about 3.4 GW [5].
East Asia has a high potential for exploiting ocean wind energy, and many projects in this area, specifically in China, South Korea, and Japan, have been carried out and implemented. Among Asian countries, China has more shares in the use of wind energy. China was the first country in the Asia-Pacific region which used wind ocean energy. Table 1 shows several offshore wind energy projects in Asia [5, 6].
Country | Planned capacity | Project name | |
---|---|---|---|
1 | China | 1.5 MW | Bohai Suizhong, LiaoDong Bay |
2 | China | 20 MW | Dongshan Island |
3 | China | 50 MW | Hebei |
4 | China | 100 MW | Nan’ao, southeast of Guangdong |
5 | China | 25 MW | Shanghai Dong Mai |
6 | China | 102 MW | Shanghai Dong Mai |
7 | China | 100 MW | Fengxian No. 1 |
8 | China | 300 MW | Fengxian No. 2 |
9 | China | 400 MW | Nanhui |
10 | China | 200 MW | Hengsha |
11 | Hong Kong | 200 MW | Hong Kong offshore |
12 | Japan | 2 × 600 KW | Setana, Hokkaido |
13 | South Korea | 500 MW | Limjado, Jeonnam Province |
14 | Taiwan | 4 MW | Ferry |
China had installed more than 3.4 GW of ocean wind capacity at the end of 2016 and should end up with around 900 GW more by the end of 2030. According to China’s Five-Year Plan, five gigawatts will be added to the country’s electricity grid by 2020 [4]. Taiwan also has the potential to produce electricity from ocean wind energy, and according to the plan of the Ministry of Energy, by 2025, it will be the top among the active countries in Asia that use this energy [7]. Today there are only two ocean turbines operating in the country, and two projects in a total of 320 MW are due to be installed by 2020. Japan has only 61 MW of installed energy for ocean wind energy by the end of 2016, given that it has more access to the ocean. South Korea has so far only mustered a couple of ocean wind prototypes and a single demonstration project, in a total of 35 MW [7].
The European continent has many potentials for electric power generation through ocean wind energy. It is revealed that this energy will play an important role to produce electricity for Europe in the future [8].
The Netherlands started to work on offshore wind farms after Denmark [9]. Also, two ocean wind farms were built up in the Netherlands with two different capacity levels of 108 MW and 120 MW in 2006. Two new ocean wind farms were build up in Sweden by 2001 and 2002. Ireland constructed its first ocean wind farm in 2004 wind turbines of 3.5 MW. Moreover, Germany’s first ocean wind farm was constructed with 20,000 MW capacity. The UK used ocean wind energy by 2000 with 3.8 MW capacity. France started to use ocean wind energy in 2005, but the construction of wind power plants for economic reasons was postponed to 2009. Table 2 shows several offshore wind energy projects in Europe [8, 9, 10].
Country | Planned capacity | Project name | |
---|---|---|---|
1 | Denmark | 4.95 MW | Vindeby |
2 | The Netherlands | 2 MW | Lely |
3 | Denmark | 40 MW | Middelgrunden |
4 | Denmark | 160 MW | Horns Rev |
5 | The UK | 60 MW | North Hoyle |
6 | The UK | 60 MW | Scroby Sands |
7 | The Netherlands | 108 MW | Egmond ann Zee |
8 | Sweden | 110 MW | Lillgrund |
9 | Netherland | 120 MW | Princess Amalia |
10 | The UK | 90 MW | Inner Dowsing |
11 | Germany | 2.5 MW | Breitling |
12 | Ireland | 25.2 MW | Arklow Bank |
13 | Sweden | 10 MW | Yttre Stengrund |
14 | Italy | 0.08 MW | Brindisi |
According to the EWEA1, The European countries target is determining 20% of its power from sustainable sources by 2030. EWEA has set an objective to achieve 40 GW and 150 GW of ocean wind energy by 2020 and 2030, respectively. Additionally, through 2030, EWEA estimates yearly establishments of ocean wind energy will be equal to 13,700 MW. Ocean wind energy will support 13.9% of total EU demand [10].
Africa’s wind energy resources are focused along the coastal area and mainland shelves. These regions ordinarily have high onshore and offshore wind energy possibilities. In 2004, the African Development Bank investigated to create a wind atlas of Africa and create a quantitative guide of wind speeds over the African continents [11]. Outcomes from the investigation showed that Africa’s best wind energy is found in countries adjusted along the western, northern, eastern, and southern shores of the African continent. The special cases are landlocked countries such as Chad and Ethiopia where the topographical highlights of the land are responsible for the high wind speeds in some high-elevation zones. Additionally, according to research conducted in 2007, eight countries (Egypt, Somalia, Mauritania, Sudan, Libya, Chad, Kenya, and Madagascar) have high potential for onshore wind energy and five countries (Mozambique, Tanzania, Angola, South Africa, and Namibia) have high potential for ocean wind energy [11].
The United States has vast ocean-wide areas such the Great Lakes, Hawaii, Alaska, and Gulf Coast with potential to use offshore wind energy to produce electricity [12]. As a result, the US Department of Energy’s, Wind Energy Technologies Office has conducted many studies on various technologies to facilitate electricity generation from wind.
According to the US Department of Energy, the USA will have 3 GW, 22 GW, and 86 GW of ocean wind by 2020, 2030, and 2050, respectively. Therefore, the USA will utilize 5.5% of its accessible ocean wind resources. The US Bureau of Energy anticipated ocean wind improvement along both the Gulf of Mexico and West and East Coasts, in the Great Lakes, by 2050. Table 3 shows several ocean wind energy projects in the USA [12, 13].
Country | Planned capacity | Project name | |
---|---|---|---|
1 | The USA | 30 MW | Block Island (RI) |
2 | The USA | 468 MW | Cape Wind (MA) |
3 | The USA | 500 MW | US Wind (MD) |
4 | The USA | 1000 MW | DONG Energy (MA) |
5 | The USA | 1000 MW | Deepwater ONE (RI/MA) |
6 | The USA | 2000 MW | Dominion Virginia Power (VA) |
7 | The USA | 450 MW | Blue Water’s Mid-Atlantic Wind Park |
8 | The USA | 400 MW | Offshore MW (MA) |
In the last few decades, the technology used to exploit ocean wind energy for generating electricity has been increased day by day. These technologies depend on the geographic region, the depth of water, and the wind speed. The main parts of the ocean wind power plant include [14]:
Tower
Blades
Gearbox
Power electronic components
Transmission system (cables)
Generator
The blades of the ocean wind turbine are one of the unique parts of the wind turbine structure. They have unique mechanical and aerodynamic characteristics. Moreover, the technology of manufacturing wind turbine blades has undergone new developments in both process fields and materials used in them. As a result, manufacturers of these blades are trying to optimize mechanical properties in the aerodynamic blades by design optimization and using new materials. Composite fibers and various resins, including various materials, have been used in the production of wind turbine blade rotor.
Extraction of kinetic energy from the wind is carried out by wind turbine blades. Therefore, having an optimal design to get the most energy out of the wind is very important. Wind turbine blade design consists of two main parts. In the first step, the aerodynamic design is performed to achieve the required power rating according to the turbine wind turbine and to obtain the highest electric power factor. In the second step, changes should be made to the blades so that the amount of aerodynamic noise generated by the blades is within the permissible range.
Wind turbine tower is the most significant, heaviest, and most expensive part of the wind turbine. Regarding the safety level, its failure can cause the entire wind turbine to fail. Proper design of the wind turbine tower significantly reduces the cost and increases the life of the wind turbine.
The tower is a cone-shaped steel structure with four segments mounted on each other by screws and flanges. The tower design includes the following main steps [15]:
Connector analysis
Shell strength analysis (static analysis, bending, and aging)
Vibration analysis
Design and selection of all internal components of the tower (entrance door, ladder, elevator, and internal platforms)
The purpose of using a gearbox is to transmit relatively large forces, change the torque or change the direction of rotation, or change the angle of the rotation axis. Gearboxes are increasing the nominal speed of a rotor from a small amount (a few tens of rpm) to a high value (at a rate of several hundred or several thousand rpm), which is suitable for triggering a standard generator. Ideally, the resultant value is constant in the torque at the inlet and outlet of the gearbox, but due to the energy losses in a mechanical device, torque is reduced in the output axis. In a wind turbine, the power transfer from the main rotor to the generator is usually done in three ways [16].
In this method, the transmission is not used from the gearbox, and the torque is directly inputted from the main rotor to the generator. So, instead of using the gearbox and extending the main rotor, a generator with more poles is used. To accommodate more poles on the generator, the diameter should be increased. One of the benefits of using this design is to reduce the cost of the gearbox maintenance as well as reduce gearbox shocks and increase efficiency.
In this method, the power output is transmitted by a conventional gearbox to the generator. The gears used in this gearbox can be simple or spiral. To increase the upper period, it may be possible to use two or more rounds. In parallel shaft gearbox, the bearings are used to keep the gear shaft on the main body. In this type of gearbox, a helical gear is used, so in addition to radial force, the bearings must also bear a large axial force.
Using this type of gearbox is very common in wind turbines. The gearbox uses three types of gears, the Sun gear in the middle, the Planetary gear, and the Ring gear, which is an internal gear. The division of force into planetary planes, reduced gearbox size, reduced slip between the gear and the planet, and increased efficiency relative to other gearboxes are benefits of the planetary gearbox.
Wind turbine blades convert wind energy into rotational energy in the transmission system, and in the next step, the generator transfers the turbine’s energy to the grid. The most types of electric generator part in wind turbines are asynchronous and synchronous generators. Also, DC generators have been used for some smaller turbines. Table 4 shows the different structure of ocean wind energy conversion [17].
Different topologies of wind energy conversion systems.
In general, generators used to convert energy from offshore wind farms can be divided into two main categories, which can be described as follows:
Synchronous generator
Induction generator
A.Squirrel cage induction generator
B.Wound rotor induction generator
The construction of wind farms requires a large space. Therefore, the best option for removing this limitation is the construction of these power plants in the ocean. Because the distance between offshore wind farms and the distribution network is high, it is better to use high-voltage direct current (HVDC) to transmit energy produced. The suitable transmission for ocean wind farms based on HVDC is line-commutated HVDC and voltage source converter (VSC-HVDC) [18, 19, 20]. If the length of the transmission lines is less than 50 kilometers, the use of high voltage alternating current transmission systems is not recommended. In the HVDC technology to control active power, reactive power, and voltage thyristors is replacing with IGBT (Figure 2a and b).
(a) Structure of thyristor-HVDC and (b) structure of IGBT-HVDC.
The HVAC transmission network is divided into different types, each with its advantages and disadvantages. The low-frequency AC transmission (LFACT) and fractional frequency transmission system (FFTS) are new transmission systems which have been used for the wind farm as a solution to cover the disadvantages of conventional AC transmission line. Figure 3 shows a different type of AC transmission line of the ocean wind farm.
Different types of AC transmission line of ocean wind farm.
Recently, one of the most eco-friendly and accessible renewable energy sources (RESs) being utilized all across the world is wind energy [21]. Considering the beneficial characteristic of clean energy resources such as flexible control and regulation, RESs’ expansion programs and sustainable growth to reduce the greenhouse gas emissions are the main purposes of European Commission in Energy Road map 2050 [22]. Regarding the necessity of employing renewable energies, and also the remarkable global growth in the use of such energy sources, wind energy has important advantages such as zero-emission energy production and low operating costs. In spite of these benefits, there is a severe uncertainty in predicting wind speed as a big challenge for such system’s integration [23]. Various machines are used in wind turbines including permanent magnet synchronous generator (PMSG), squirrel cage induction generator (SCIG), and doubly fed induction generator (DFIG). Hence, the DFIG is one of the most significant types of generators being installed in wind turbines. In DFIG, both stator and rotor are connected to the main power grid directly and by power electronic converters, respectively [24, 25, 26, 27, 28]. As it can be seen in Figure 1, the typical circuit of a doubly fed induction generator DFIG is specified, by taking into consideration the several important parts including maximum power point tracking (MPPT), rotor and grid side controllers and power electronic converters, and pulse wide modulation PWM. Both windings of the stator and rotor of the induction machine are connected to the grid directly and by power converters, respectively. To active and reactive power control, several different types of controller have been evaluated in pervious, research works. For instance, Ref. [29] uses sliding mode (SM) and PI controller, for controlling the stability and also to track reference power and remove fluctuations or active and reactive powers’ disturbances. After pointing out the performance of the PI controller in the output, the obtained results are compared with a SM controller. It has been revealed that the PI controller has a more desired performance than SM controller from the output responses of the controllers’ point of view. In [30], a neural-type-1 fuzzy controller is used to produced powers of wind turbine; the derived results are compared to a PI controller, specifying that the neural-fuzzy controller operates better than the PI controller. Refs. [31, 32] have used fuzzy-PI and sliding mode and also robust fuzzy-sliding mode controller (F-SMC) to control and better manage the generated Ps and Qs of the wind turbine system output. Hence, comparing of controllers’ performance indicates that the output responses of the fuzzy-proportional integration controller are better than sliding mode controller. All the controllers used in the literature have been used to enhance the stability and to eliminate the fluctuation and disturbances as well as improve the reference power tracking. Furthermore, each control method has modified the pervious approaches and also improved the active and reactive powers extraction of DFIG. Another type of controller employed in DFIG generator is the fuzzy-sliding mode controller. In fact, the F-SMC is a controller which finds the best numerical values for the scaling factor of the sliding mode. Due to the presence of fuzzy controller, all gain coefficient value is more accurate. Wind turbine operation is affected by uncertainty due to the uncertainty in the wind speed forecasts; thus the abovementioned controllers are not appropriate as they are not capable of dealing with severe uncertainties. It is noteworthy that the PI controller is point to point and type-1 fuzzy controller is able to only cover a small range of uncertainty in its outputs. By considering the high uncertainty in the wind speed, it is needed to design a controller with the capability of covering severe uncertainties. According to the control methods used in the literature, and also in order to improve and enhance the power control (Ps & Qs) in wind turbines systems, a new control method based on type-2 fuzzy logic control laws is presented. In this research, all parameters and equations are linear enabling the system designer to use MAMDANI inference system. The T2FL controller is a suitable alternative for the controlling of the powers in DFIG to deal with severe uncertainty.
Indeed, the DFIG is an induction machine which its stator and rotor is interfaced to the main power grid. The connection of the stator and electrical energy transmission from its windings to the main power grid is carried out by 3-phase power transmission lines from wind turbine to the grid. On the other hand, the rotor wounds of the induction machine are fed through the AC-DC/DC-AC back to back power converters, which received the electrical energy from 3-phase power transmission lines between stator and the main power grid. In this section, a general model is presented within a dynamic framework, by considering the variation parameters of the wind turbine based on induction machine. In this regard, the mathematical and dynamic equations are expressed as currents, voltages, and flux relations in q-d-0 reference frame and also the electromagnetic and mechanical torque. Figure 1 illustrates the wind turbine circuit loop general operation process with controllers, in particular the rotor-side one [30, 33].
By taking into consideration the rate of wind speed at the different times and also due to the coefficient
wherein
where
With regard to the relation (1), the input mechanical torque of the wind turbine is obtained by following:
Generally, there are three states or significant vector models, which are used to design an induction machine called as
Figures 4 and 5 represent the vector diagram of the DFIG PARK’s model and 2-phase reference frame, respectively. In these figures the conversion system from (a, b, c) reference rotating frame to (q-d-0) reference frame has been shown [32].
Doubly fed induction generator PARK’s model [
The DFIG in the 2-phase reference frame [
DFIG’s voltage equations of the stator and rotor in 2-phase reference system are defined as follows [34, 37]:
where
Also, the induction machine’s currents are in 2-phase reference frame, which are calculated as follows:
By considering current Eqs. (7) and (8), the parameters
In addition, by taking into consideration the current and flux parameters in 2-phase reference frames of the rotor and stator of the induction generator, the torques can be obtained as (11) and (12):
where
In (12), the parameters
The active and reactive power control strategy is that the fuzzy controller by receiving error signals and derivative of the error and also, after a control process, the signals generated through the controller is delivered to the power electronic converters and DFIG’s rotor and to the active and reactive output power control of the wind turbine. The relationships of
T-2 fuzzy controller is a developed controller in that its operation strategy is under the uncertainty. Therefore, this type of controller is appropriate for systems with high uncertainty such as wind or solar power plants, which the generation is exactly under the pure uncertainty. The performance of the T2FLC because of covering a large scale of high uncertainty to control the wind turbine parameters is more desired than the T1 fuzzy or another controller technique. Structurally, both T1 and T2 fuzzy controllers are the same, but with this difference in the interior structure of T2FLC, due to the presence of uncertainty, there is a section as type reducer (TR). The calculation and the conversion of the type of fuzzy from type 2 to type 1 are the important functions of the TR section. Depending upon the linearity and nonlinearity of the model, two types of inference system exist in T2FLC. The MAMDANI inference system is used for the systems with linear equations, and TSK inference system is employed for the systems with nonlinear equations.
Generally, T2 fuzzy sets are extended of type-1 fuzzy sets. On the other hand, T2FS is a fuzzy set with membership degree of fuzzy. Type-2 fuzzy sets can compensate the limitation of type-1 fuzzy sets in covering uncertainties as a new method with its specific advantages. Forasmuch as fuzzy sets are defined based on linguistic variables, thus the T2FS is appropriate to model uncertainty process using linguistic variable. The primary membership grade in T1FSs is a crisp number in [0, 1], whereas the primary membership grade in T2FSs is a T1FSs in range of [0, 1] and the secondary membership is a crisp number in [0, 1] as well [17, 22]. Figure 6 represents T2FSs with its upper, lower, and footprint ranges of the uncertainty.
The general circuit of a DFIG and its connection to the grid.
As shown in Figure 7, A T2FS consists of foot printing of uncertainty (FOU), upper membership function (UMF), lower membership function (LMF), and embedded fuzzy system wherein the FOU and embedded FS have been shown as blue lines. If all membership grades of FT2 sets are the same in the secondary part of FT2 sets, the sets of FT2 are the internal type, otherwise the general type. With respect to the uncertainty in the membership function of FT2 sets, the general concept of type-2 fuzzy set is defined by the relations below [37, 38].
Type-2 fuzzy set with FOU and embedded FS and lower and upper memberships.
A type-2 fuzzy set is characterized in a function (H) and is described as follows:
wherein
In order to reduce the computational complexity, the interval fuzzy sets (IFSs) are proposed as an alternative to the general fuzzy sets (GFSs). Hence, a set
The performance of fuzzy inference engine is under the considered rules. With seven membership functions, 49 of the commands written to form IF-THEN have been considered as represented in Table 1 [37, 38, 39, 40, 41, 42]. The relation of footprint ofuncertainty is as follows:
According to the impacts of the uncertainty in FT2 sets, the bound of FT2 sets includes two fuzzy type-1 set membership functions as upper membership function (UMF) and lower membership function LMF. The embedded fuzzy sets in the set of
The general performance of T2FLC is based on rules and relationships which have been considered for it. As it can be seen in Figure 8, the principle process of type-2 and type-1 fuzzy control systems are the same, but with this difference that the FT2 control system has a unit called fuzzy type reducer. FT2 system comprises five important parts in that the first part is the fuzzifier unit, while the inputs of [0, 1] interval are converted to fuzzy sets. The second part is the inference engine unit wherein; all fuzzy sets are inferred by rule base unit, simultaneously. Depending upon linearity or nonlinearity of the fuzzy control inputs and the equations, the inference system in (T2FLS) control system can be MAMDANI or TSK. The next part after the inference engine taken into consideration the most important part of FT2 logic system is the rule base unit. All fuzzy inference calculations are according to the human knowledge and written in the frame of IF-THEN. The fourth section of FT2 system is the type reducer. Since the FT2 sets are based on the uncertainty and due to the high computational burden of the fuzzy system, this is not possible for the system output to be converted to [0, 1] directly. First, all the sets of the FT2 are converted to FT1 sets using the type reducer and then applied to the defuzzifier unit and converted to [0, 1] in the output. The last part of the FT2 system is the defuzzifier unit in that its performance is in the opposite way of the fuzzifier system and converts all fuzzy sets to [0, 1] [38, 39, 40].
Overall process of FT2 logic system.
By taking into consideration the significant parts of type-2 fuzzy topology, the process of inference is expressed in the form of mathematical, which is denoted as follows:
subject to
And the minimum and maximum computational of type reducer can be expressed in the fractional functions as follows:
Finally, defuzzification is the next step after the type reduction unit which in order to achieve the controller’s output is done by:
Generally, Figure 9 shows the process of the data inference, analyze and conversion them from crisp system input [0, 1] to the type-2 fuzzy system and again transform to the crisp system output [0, 1]. According to the main system’s input equations, the design of FT2 controller has been done using the FT2 toolbox. The FT2 controller detail, such as error, change of error that is gain input (KP, KD), fuzzy inference system unit, output gain (KU) with its intervals, the number of considered membership functions for inputs and output, some of its laws, and, also, the type of inference, is expressed in the form of a toolbox. Given the linearity of the equations of DFIG, the MAMDANI inference system with Gaussian membership functions has been considered for the FT2 controller [39]. The main part of type-2 controller is the fuzzy inference (FIS) section, in which all operating levels of fuzzy sets can be done by this part. Since this work is focused on the rotor-side controller RSC and also by considering the presence of uncertainty in the wind speed, elimination of the oscillation (overshot), as well as stability enhancement of the output powers Ps & Qs of the wind turbine based on DFIG, is the principal target of this essay. With regard to Figure 1 that indicated the general structure of the DFIG, hence, as it can be seen, the type-2 fuzzy controller input parameters are the active and reactive powers, and its output is the voltage of the rotor in the q-d-0 reference frame. The performance of fuzzy inference engine is under the considered rules. With seven membership functions, 49 of the commands written to form IF-THEN have been considered as represented in Table 1 [37, 38, 40]. To better indicate the concept of the type-2 toolbox and its application to T2FL controller design, the general scheme of an interval type-2 toolbox with MAMDANI inference strategy and also the type of inputs and output membership functions with its ranges are depicted in Figures 5 and 7, respectively. As shown in Figure 8, the structure of type-2 fuzzy logic controller is composed of input gains (KP, KD), type-2 fuzzy inference unit, output gain (KU), and plant as well. Indeed, the plant section is a mathematical transfer function. Since the type-2 fuzzy inference section is the main part of T2 controller and on the other hand its function is directly based on the IT2 toolbox, thus, under such conditions, it is required that all parameters’ information about the type-2 controller system, such as input and output scaling factors, number of rules and command, membership functions, and its ranges, are defined in the toolbox as well. All sections of the T2 fuzzy logic controller are shown in Figure 10.
Type-2 fuzzy logic toolbox.
Input and output Gaussian membership functions with its intervals.
E/COE | NB | NM | NS | ZO | PS | PM | PB |
---|---|---|---|---|---|---|---|
NB | NB | NB | NB | NM | ZERO | ZERO | ZERO |
NM | NB | NB | NB | NM | ZERO | ZERO | ZERO |
NS | NB | NB | NB | NM | ZERO | ZERO | ZERO |
ZO | NM | NM | NM | ZERO | PM | PM | PM |
PS | ZERO | ZERO | ZERO | PB | PB | PB | PB |
PM | NB | NM | NS | PM | PB | PB | PB |
PB | PS | PM | PB | PB | PM | PB | PB |
Type-2 fuzzy rule chart.
As shown in Figure 11, the structure of type-2 fuzzy logic controller is composed of input gains (KP, KD), type-2 fuzzy inference unit, output gain (KU), and plant as well. Indeed, the plant section is a mathematical transfer function. Since the type-2 fuzzy inference section is the main part of T2 controller and on the other hand its function is directly based on the IT2 toolbox, thus, under such conditions, it is required that all parameters’ information about the type-2 controller system, such as input and output scaling factors, number of rules and command, membership functions, and its ranges, are defined in the toolbox as well. All sections of the T2 fuzzy logic controller are shown in Figure 11.
The main structure of the type-2 fuzzy logic controller simulation.
Each of letters in Table 1 has a special meaning. For example, negative big is the meaning of NB, and ZO is the abbreviation of zero, while the following describes the fuzzy rules:
If error is
PSO is one of the most popular optimization algorithms which is operated according to the social treatment of birds and aquatics movement. The process of optimization in the algorithm ends whenever using the pre-defined stop criteria [43, 44]. In this article, (PSO) algorithm is used to tuning the input and output scaling factors of the controller. To optimize the output powers (Ps & Qs) of the wind turbine through the T2 fuzzy controller, it is required to properly tune the input and output gains of the controller [45, 46, 47]. Under such conditions, each of the input and output scaling factors of the type-2 controller will have a suitable number, in which its numerical amounts are determined by PSO algorithm. In the presence of uncertainty and due to the complexity and the large number of the FT2 equations, it would be very difficult or even impossible to choose an optimal number or enter values manually into the input and output gains. Accordingly, PSO algorithm has been used in this paper to accelerate adjusting the coefficients to get the proper number and more accurate response to regulate the input and output scaling factors of the controller. The PSO algorithm is based on the particles? behavior including the velocity and the location of particles [48, 49, 50, 51, 52, 53]. Taking into consideration the general structure of the PSO algorithm, the process of coefficients regulation of the FT2 controller’s input and output gains using PSO algorithm is defined in three steps. At the first step, a general cost function is created including the names of the controller’s gains characteristic; the name of the main system that the type-2 fuzzy controller is considered for, i.e., a DFIG-based wind turbine; and the sum of error and the change of the error. In the second step, the main values such as the number of parameters, the minimum and maximum values of the input and output of the FT2 controller gains (KP, KD, KU), the name of the cost function, the number of maximum iteration, as well as all parameters relating to the PSO algorithm are defined. In the third step, the best numerical value of the FT2 controller gains is determined by running the PSO algorithm. By considering a larger number of iteration loops in the algorithm to adjust the gains of the controller, the output response will be improved. The general structure process of the type-2 controller’s gain regulation has been depicted in Figure 12. As shown in Figure 9 and also with the presence of the T2 fuzzy controller in this system, the PSO algorithm adjusts all scaling factors of the T2FL controller by receiving the error and change of error (E, COE) as the input and then chooses the best value for each gain of the controller (KP, KD, KU) in the output. To better understand the optimization procedure by the PSO algorithm, all the algorithms’ steps are described as a flowchart in Figure 13.
Tuning of fuzzy type-2 controller gain process using PSO algorithm.
Flowchart of the PSO algorithm.
Function H= Cost Function-FCN (KP, KD, KU)
Sim (‘DFIG’)
H=Sum ((e. ^ 2) + (De. ^ 2))
End
This part expresses the simulation results obtained using the presented framework. In this regard, the obtained results using the proposed FT2 controller are compared with those obtained by the FT1 controller. Figure 14(a) and (b) shows the error and change of error surfaces of the FT1 and FT2 controllers, respectively. In this regard, the FT2 controller has a smoother surface than FT1 due to the covering uncertainty in a large and different ranges and high computational burden. This paper is focused on the power (P & Q) control using the RSC. According to the circuit loop of doubly fed induction machine, the general power control process in the DFIG-based wind turbine can be stated in multiple stages. At the first stage, after entering the value of the measured power (the generated power by the DFIG in the initial moment without controller’s function), reference power is compared by the type-2 fuzzy controller. Regarding the transfer function considered for the T2 FLC, the output signal of the controller is the rotor voltage in
(a) and (b), The FT1 and FT2 control surface.
(a) and (b). The output results of the active power (a) and reactive power (b), controlled using the FT1 controller.
(a) and (b). The active power (a) and reactive power (b) output control using the FT2 controller.
Parameters | Acronyms | Numerical values |
---|---|---|
Frequency | (F) | 60 |
Stator line voltage | ( | |
Stator resistance | ( | 3.35 |
Rotor resistance | ( | 1.99 |
Stator leakage inductance | ( | |
Rotor leakage inductance | ( | |
Magnetic inductance | ( | 163.73 |
Moment inertia | (J) | 0.1 |
Number of pole | (P) | 4 |
Numerical values of the main parameters of the DFIG with its acronyms.
With regard to Figure 15(a) and (b), both powers
Figure 16 demonstrates the active and reactive powers outputs. Therefore, as shown, the performance of T2 controller is better than T1 controller; in other words, the powers have improved in its transient mood by considering the presence of the uncertainty, and on the one hand, T2FLC has a smoother surface in its control of the output powers. Since the computational burden of the mathematical theory of the type-2 fuzzy strategy is high, the output response of the FT2 controller until the stable state is associated with a time delay of several seconds. Due to the capability of the FT2 controller in covering a large range of the uncertainty, fluctuations have been removed, and it presents a smoother behavior in its transient state. In this paper, as previously described, with a little time delay, both P & Q power outputs of the FT1 and FT2 controller are stabilized at the value of 400 W. The stability of the active and reactive powers at the reference value has been depicted in Figure 16(a) and (b), respectively. Ps and Q powers output response of T1FLC indicates the controlled output power stability at the pre-defined reference value in Figure 13. As specified in Figure 16(a), it has been shown that the active power is stabilized at the value of 400 W. By taking into consideration the type-1 and type-2 controller functions, the major difference between them is to cover the uncertainty. The T1 controller cannot cover uncertainty, or in other words, it just controls the powers over a small specified range, while the T2 fuzzy controller can cover the uncertainty in large scales.
Both active power and reactive power output response of the type-1 FLC indicate the controlled output power stability at the pre-defined reference value in Figure 16. In Figure 16(a), it has been shown that the active power is stabilized at the value of 400 W. Regarding the functions of type-1 and type-2 fuzzy controllers, the major difference between them is to cover the uncertainty. The T1 controller cannot cover uncertainty, or in other words, it just controls the powers over a small specified range, while the T2 fuzzy controller can cover the uncertainty in large scales.
In this section, the results of 3-phase voltage and currents between DFIG’s stator and the main power grid through the power transmission lines have been investigated. Hence, the results of the stator 3-phase voltages are characterized in the frame of [
(a) and (b). 3-phase voltages from grid to the stator in (a, b, c) reference frame with the sinusoidal waveform.
(a) and (b). 3-phase currents of the stator in (a, b, c) reference frame with sinusoidal waveform.
The input of the PWM is the voltage in [
(a) and (b). 3-phase rotor voltage with sinusoidal waveform.
In general, the structure of ocean wind farms can be divided into two main categories:
From the perspective of the foundation used for construction
From the depth of water view
This chapter addresses the above issues.
Offshore turbines are placed in the water and have more complexity to install on a turbine mounted on the land. Figure 20 shows the different foundations for ocean wind turbines. Additionally, offshore wind turbine foundation must withstand harsh condition as well. This explains the wide variety of foundation developed over the years for offshore turbines, some more proven than others [54].
The different foundations for ocean wind turbines.
The layout of offshore wind farm changes based on the geographic area, the structure of the wind turbine, and the depth of water. The structure of water turbines in shallow water, deepwater, and floating has been investigated.
For areas with a water depth of fewer than 40 m, the use of offshore wind farms is appropriate.
Figure 21 shows the typical structure of shallow water wind turbines:
Gravity base
Mono-plie
Mono-caisson
Multi-pile
Multi-caisson
Models of ocean wind turbines in shallow water.
For areas with a water depth of more than 40 m, the use of low wind turbine is appropriate. Figure 22 shows the typical structure of deepwater wind turbines:
Tripod tube steel
Guyed tube
Spaceframe
Talisman energy concept
Models of ocean wind turbines in deepwater.
Floating wind turbines are constructed on a floating structure on water, which is kept in different ways on the ocean floor. This method is used in areas where it is not possible to make a foundation for them. Figure 23 shows three types of floating structures in an offshore wind turbine.
Tension leg mooring systems
Catenary mooring systems
Ballasted catenary configuration
Three types of engineered design for anchoring floating structures.
The design of offshore wind farms should be considered from three crucial points. Figure 24 shows the design process for a typical ocean wind turbine.
The design process for a typical ocean wind turbine.
In general, two types of offshore wind power plant structures are challenging, (i) fixed offshore wind turbine and (ii) floating offshore wind turbine. Also, important issues that are being considered as the current challenge in offshore wind farms are the turbine layout and the way electricity is transmitted from the ocean to the shore [55].
Offshore installations currently consist of only a small percentage of the renewable energy market. However, due to the advancement of technology in the design and evaluation of these types of energy resources, it is expected that much progress will be made shortly. Offshore wind farms are in the early stages of their commercialization. They demand a higher cost of capital than onshore wind farms, but this can be compensated by higher capacity factors [56]. Offshore wind farms allow more widespread utilization of wind energy potentials. The reason for the higher capacity factors and the possibility of more use of offshore wind energy are as follows:
There are no obstacles and restrictions for installing wind turbines for offshore turbines.
It is possible to build sizeable enormous wind farms offshore.
In places where the wind speed is average, it can be constructed.
Offshore turbines have more extended and higher blades, leading to more swept areas and higher electricity outputs.
The offshore turbines are designed for use in offshore. Due to the lack of focus on such issues as shaking and impulse, noise, and visual contamination, there is a relatively different technical path. Although the issue of increasing turbine size for offshore turbines is a problem, this will increase the profit but also increase the operating costs. In this regard, the changing of the design and the ability to consider considerations are likely to provide better conditions in the design of offshore turbines.
Now, new turbines have a power of at least 5 MW. Therefore, a 1000 MW power plant can be achieved by installing 200 turbines [56]. Increase in the cost of the offshore wind turbine installation in the sea and the transfer of energy to the coast are most significant problems which need to be considered. Researchers are still trying to find the ways to reduce the cost of ocean wind farm.
Another challenge in the construction of offshore wind farms is the shortage of large ships that can carry large and heavy parts such as turbines. Also, another challenge in the field of offshore wind farms is the incentive to participate in the electricity market. Power transfer from the plant to the power grid using suitable infrastructures is also challenging for the use of this future energy. There are many other challenges that need to be addressed with the availability of sufficient technology in the world and companies who are active in wind turbine production [57]. Currently, the number of companies specialized in this field is insufficient, and it is expected that the number of these companies will increase shortly. Finally, to expand the use of this energy source, the training of a specialist who can build and operate offshore wind farms is another issue that should be addressed by electricity companies.
Regarding the abovementioned explanation, the major challenges of offshore wind technology are the high cost of offshore wind provision, lack of current infrastructure to support the fabrication such as installation, operation interconnection, maintenance of the system, and the challenges related to the lack of site data and lack of experience.
Figure 25 shows the lifecycle of an offshore power plant. According to this diagram, to solve the first challenge, it should be possible to reduce the impact of this problem in the long-term reports, with the development of industries and the reduction of installation costs and increased reliability of the system.
The lifecycle of an offshore power plant.
Nowadays, installation of ocean wind turbines requires specialized vessels, grid interconnections, purpose-built portside infrastructure, and robust undersea electricity transmission lines will be useful from the financial point of view. Regarding the last challenge, ocean wind projects confront new and untested allowing processes, which contributes to the uncertainty and risk faced by potential project developers and financiers.
Goat farming in South Africa (and other parts of Africa) has been the most extensive agricultural sector since the beginning of the 19th century. It is believed that goat population grows along with the human population. One of the reasons for a growing population of goat farming in Africa is that it is a farming sector that does not require intensive investment. For that reason, most South African farmers see goat farming as one of the strategies to curb food insecurity, for it is in high demand in the informal market.
However, the surprising thing is that goat farming is regarded as a poor man’s trade. It is characterized by informality, lack of industry determination, value addition, and modern distribution channels. Very few farmers sell their goats through abattoirs, because most producers rely on consumers who are driven by cultural and traditional beliefs.
This chapter presents the factors affecting goat farmers’ market participation and the extent of commercialization. The chapter is set out as follows; the next section defines the problem, followed by the methodology. After that, the discussion of results are presented, followed by the conclusion.
There are very few large scale commercial goat farmers in Africa, and most of them are found in South Africa [1]. In South Africa, a large number of indigenous goats are owned by small-scale farmers found mainly in communal areas [2]. The white commercial farmers mainly rear Boer and Angora goats [3]. The goat resource in South Africa, which is mainly owned by non-commercial farmers and mostly of indigenous breeds is large enough to ensure a consistent supply of product to the market.
Goats significantly contribute to the country’s goat population as it is approximately 63% [4]. Goat commercial farming is predominant in the Eastern Cape, followed by Limpopo then Kwa-Zulu Natal (KZN) Provinces of South Africa. Eastern Cape has more goats in South Africa accounting for 38% of the total flock followed by Limpopo with 18% and KwaZulu–Natal with 13% [5]. However, there is a potential to develop goat production in KZN as according to [6], more than 50% of cattle, 19% of sheep, and 74% of goats are on communal lands in the KZN province.
It is noteworthy that, goat marketing remains very low and informal in South Africa and this is exacerbated by low participation of goat farmers in formal markets [7]. One of the contributing factors to low market participation is that most goat farmers are mostly in rural areas where goats depend on the natural forage under extensive conditions throughout the year without nutritional supplements during the winter dry season. In general, smallholder farmers’ productivity is low due to factors such as lack of information, lack of market access, and poor access to support services [8, 9, 10].
These factors are challenges in the improvement of smallholder production and thus smallholder producers are finding difficulties in commercializing their production. The major challenge to commercialization is how smallholders can penetrate and participate in markets [11]. [12] also found out that participation in the commercialization process has been difficult for smallholder farmers because of inappropriate policies, insufficient access to technology, institutional obstacles, weak infrastructure, and unfortunate links to markets. In the past 18 years, the South African government implemented several policies and programmes and increased the agricultural sector’s budget by supporting emerging farmers [13, 14, 15]. However, very little is known about smallholder goat farmers or goat production in general. The resistant nature of goats to disease and internal parasites, its adaptability to harsh conditions, less production cost, and easy increase of production because of the high possibility of twining makes goats more sustainable livestock to produce by smallholders thus demanding a commercial approach from farmers.
According to [16], smallholder commercialization is part of an agricultural transformation process in which individual farms shift from a highly smallholder-oriented production towards more specialized production targeting markets for their input procurement and output supply. According to [17] agricultural commercialization is the basis of economic development and integration of farm household into rural economy and society as an integral part of the process. Furthermore, [18] also assert that the transition from subsistence to commercial agriculture represents a key ingredient for low-income countries’ economic development. Therefore achieving goat commercialization will enhance the welfare as well as economic development for smallholder farmers. Notable, commercialization as an agricultural transformation will therefore have a substantial impact on agricultural production, food security, poverty alleviation, and economic contribution to the smallholder farmer at a household and a national level.
Goats are predominantly sold live for cultural and religious ceremonies and traditionally goats have served as a means of ready cash and a reserve against economic and agricultural production hardship [19]. However, the evolution in the meat industry and consumer health requirements are slowly creating an entrance for goats in the formal market since goat meat is now available in some retail stores in Eastern Cape, Gauteng, and in very few outlets in KZN [4]. Most goat products are exported to countries like Asia where they are mostly used and are in high demand than in local use [20, 21]. Despite the exporting marketing opportunities, smallholder farmers still have no access to these markets because of various production and marketing constraints they face. Producing for the formal market requires production resources such as land, water, on farm and off-farm infrastructure, labour force, capital, and good management skills [15, 22]. Poor access to these resources by household farmers affects how they may benefit from opportunities in agricultural markets hence lack of resources also hinders the commercial approach in goat production and marketing.
Globally, livestock production systems are undergoing rapid changes in response to population growth, urbanization, and increasing incomes [23]. The demand for livestock is largely influenced by socio-economic factors such as human health concerns, constantly changing socio-cultural values and rapidly increasing population. As such the increasing demand for the animal products is expected to improve the income and livelihood of smallholder farmers who account for the bulk of production in developing countries [23, 24]. However, most of the increasing livestock production is taking place outside the smallholder sector, which is the same trend with goat production. Goat meat matches consumer preferences for low-fat meat and consumer concerns on health [20, 21]. Therefore goats have the potential for being a diverse reservoir for future use if commercialization is achieved.
The problem investigated in this study relate to the farmers’ choice to participate in goat selling and goat commercialization. Commercialization means a change from a subsistence type of production to a market-oriented to profit maximization [25]. Therefore, commercialization can transform smallholder goat farmers by shifting production practices from current consumption-oriented towards market-oriented thus achieving economic development through income growth. The question which can be asked is whether the household farmers do participate in marketing goats, the level of participation, and which market do they use to sell goats. Therefore, this chapter aim at identifying the factors affecting farmers’ choice to participate in the marketing of goats and determine the extent of goat commercialization in the study area.
This study was conducted in Zululand district municipality, (ZDM) which is situated in the northeastern part of KZN. Zululand District Municipality is the biggest district in the province, making up 16% of its geographical area. The ZDM covers 14810km2 and consisting of 803576 population size in total and 102982 people of the entire population are unemployed hence the level of poverty in the area is very high amounting to 33, 02% [26]. Approximately half of the area is under traditional authorities’ jurisdiction while the remainder is divided between commercially owned farmers and conservation areas [26]. The ZDM district municipality comprises five local municipalities: Ulundi, Abaqulusi, Edumbe, Nongoma, and Pongola.
The target population of the study was the household goat farmers in Zululand district in KZN province. Purposive sampling was performed in this study. One hundred and seventy-five goat farmers were randomly selected from the five local municipalities with 35 goat farmers from each municipality. Structured questionnaires were used to collect data through face-to-face interviews with goat farmers in the Zululand district. As household farmers did not have records, this study counted on farmer’s recall for information.
Frequency and econometric analyses were done to analyze the data. Percentages were used to analyze the demographics of farmers. This study’s socio-economic characteristics include gender, age, race, marital status, level of education, and employment status.
A Probit model was used to estimate the factors affecting the choice of commercialization. [27] asserted that when the Probit model is used to analyze the farmers’ decision to participate in the output market, it has to be estimated as follows:
Where:
Yi is dependent variable, which is the choice to participate or not. It can take 1 if the farmer participate in commercialization and 2 if otherwise.
In order to analyze the factors affecting the extent of commercialization, Tobit regression model was used. This Tobit model was developed by Tobin in 1958. Tobit was chosen because it uses censored dependent variable as the information is available for certain respondents. Some studies have used the Heckman model to fulfil the same objective; however, Heckman is not efficient compared to the maximum likelihood of the Tobit Model. Tobit Model specification is as follows:
Where Yi presents the number of traded goats.
This section presents the results first and foremost. The objective was to assess the factors affecting household goat farmers’ market participation and the extent of commercialization. The first sub-section presents the socio-economic profile of the goat farmers in the study area. The second section provides the empirical results, where tobit and marginal effect results are discussed.
The significant of demographic information in academic research cannot be overemphasized. The socio-economic factors exert pressure on the decision making behaviour of a household. This study’s socio-economic factors are gender, age, marital status, level of education, race, experience, and membership status in the farmers’ association (see Table 1).
Variable | Percentage | |
---|---|---|
Gender | Male | 75% |
Female | 25% | |
Age group | 16–20 | 2.4% |
21–25 | 6.5% | |
26–30 | 5.9% | |
31–35 | 7.6% | |
36–40 | 7.1% | |
41–50 | 18.8% | |
51–60 | 28.8% | |
61 and older | 22.9% | |
Marital status | Single | 38% |
Married | 59% | |
Widowed | 3% | |
Level of education | Never been to school | 19.4% |
Grade R to 8 | 33.5% | |
Grade 9 to 11 | 22.4% | |
Matriculated | 18.2% | |
Tertiary education | 5.9% | |
Race | African | 98% |
White | 2% | |
Number of years farming | Less than five years | 17.6% |
Five to ten years | 25.3% | |
10 to 20 years | 24.1% | |
More than 20 years | 32.4% | |
Membership to an association | Yes | 12% |
No | 88% |
Socio-economic factors.
Source: Author’s computation (2021).
The Zululand population is predominantly black/African. For that reason, most respondents in the study area were Africans (98%), while the remaining 2% was made up of white respondents (see Table 1). Majority of African farmers were producing for subsistence purposes, while the white farmers were solely producing for commercial purposes.
It is important to note that in most African settings, male gender usually likes to keep livestock compared to females. Females predominantly look after crop production. Hence the results presented in Table 1 reveal that Zululand farmers are made up of 75% male, and 25% females. The findings reveal that goat farming is dominated by males than females in the study area. Furthermore, the greater number of male respondents could also be attributed to the cultural ideology that males are the heads of the families and therefore own livestock and are often the ones answering questions in the survey despite the possibility of a wife being the owner of the goats in the household farm.
This study also reveals that older farmers are dominating goat farming when compared to the younger generation. 53% of respondents were between the ages 50 to 61, while the 31 to 40 age category comprised 33% and 13.5% were in the category of 18 to 25 years. Generally, young people are more likely to migrate in search of non-agricultural jobs whilst older people remain at home and do agricultural activities. Furthermore, the author assumes that youth with higher educational qualifications are always hesitant to engage in agriculture as a primary means of livelihood unless commercially available. In addition, climate change and the rapid increasing population demand for the transfer of food production activities and knowledge to young and literate society members. However, the limited participation of youth in goat farming is a concern for sustainable goat productivity and commercialization considering the level of chronic illnesses threatening the aging farmers and the high rate of youth unemployment.
Though education impacts farming, it is clear in this study that household farmers take it for granted, particularly with goat production as an average number of respondents without formal education participate in goat farming. Most (33,5%) of the respondents of goat farmers in the study area attended primary school, followed by secondary education with 22%, while 18% of the study population had matric and only 6% had tertiary education. 19% of the study population did not have formal education. These findings further confirm that most South African smallholder farmers have limited education and the lack of awareness among rural farmers can be attributed to the high level of illiteracy.
Regarding employment, less than 10% of the respondent were employed, the majority (64%) are getting state grants and not employed, followed by 26% who are unemployed. From these findings, it is clear that unemployment is one of the challenges facing rural goat farmers.
Marital status affects decision making in any household. In most cases, married farmers usually have children to take care of, which affects their decision because they have to invest in their families’ future. This is why most goat farmers in Zulaland are 59% of the Zululand married farmers, while 38% single, followed by those who are widowed (3%). Membership in a farmers’ organization is essential for every farmer’s development. A farmers’ organization is vital because it is where challenges facing farmers are mostly discussed. Results presented in Table 1 show that most farmers in Zululand are not members of an organization.
Table 2 shows the factors affecting goat farmers’ choice to commercialize in the KZN area. These factors range from gender, age, marital status education level, market channels among others.
Variables | Coefficient | Standard error | Z | P > |z| |
---|---|---|---|---|
Gender | −.6785077 | .298715 | −2.27 | 0.023** |
Age | −.0049891 | .0075028 | −0.66 | 0.506 |
a3_race | .2548782 | .843632 | 0.30 | 0.763 |
Marital status | −.168734 | .2115477 | −0.80 | 0.425 |
Education level | .2442871 | .1204557 | −2.03 | 0.043** |
b12b_livestock_goats_number | −.0026207 | .0015519 | −1.69 | 0.001 *** |
c49_market_channels | .4065917 | .405533 | 1.00 | 0.016 ** |
a10_farmers_association | −.0068096 | .393273 | −0.02 | 0.006*** |
c56_determine_price | −.0962389 | .183803 | −0.52 | 0.601 |
_cons | 1.950179 | 1.976423 | 0.99 | 0.324 |
Number of observation: 150 | ||||
LR chi2(8) 14.84 | ||||
Prob > chi2 0.0953 | ||||
Pseudo R2 0.1050 | ||||
Wald chi2(6) | ||||
Log likelihood |
Factors affecting the goat farmers’ choice to commercialize.
Note: *** = 1% significance level, ** = 5‰ and * = 10‰ significance level.
Source: Author’s computation (2021).
Gender plays a crucial role in the decision of whether to produce for commercial purposes or subsistence. This is because of the distribution of economic roles within a household. For example, roles that require physical strength are given to men while those that do not, are given to a females. The results revealed a significant relationship between gender and the decision to commercialize at p < 0.05 (see Table 2). African cultural norms that perpetuate the perception that livestock ownership is a responsibility of men also contribute to this finding. Therefore livestock gender ownership greatly influence goat commercialization.
Furthermore, the results revealed that education level significantly affects commercialization choice at 5%, positively. The influence of education in adopting new technologies by farmers is generally prominent [28]. On the same note, [29] argued that education is one of the most significant demographic characteristics for decision-making among farmers, for it directly improves knowledge capacity, the ability to understand and instantly make sense of information. The higher the level of education the more the chances of adopting new technology [30]. In this case, it is clear that the high literacy level can strengthen or enhance goat production because literate communities are more likely to take risks and thus more inclined to commercialize and quickly adopt new technologies.
This study’s findings further reveal that the number of goats owned by the household was observed to be an important factor influencing the commercialization of goat for meat production with a statistical significance of P < 0.001. Households with large herds sold significantly more goats on average than those with medium and small herds. Such households presented a significant source of goats for the market and they could, therefore, be a target group for commercialization. These findings are in line with [31]‘s arguments who noted that the insufficient number of goats amongst farmers with small herds restrict sale.
The results also revealed a significant relationship (P < 0.05) between the market channel type and commercialization choice. Thus, large numbers of goats are sold through informal market directly to the available consumer by the household farmer thus allowing the farmer to retain 100% of the selling price in the absence of a formal market. The large use of the informal market for goat sales in this study is not uncommon. There is nevertheless an enormous potential for the sale of goat meat as an additional source of income on farms. According to [24] despite the economic importance of goats, particularly in the sustenance of household food security in rural areas of developing countries, marketing of goats and chevon is not as formalized as that of other livestock.
Tobit results are presented in Table 3, with marginal effect.
Sell goats | Coef. | Std. Err. | T | P > |t| | dy/dx |
---|---|---|---|---|---|
Gender | .0928731* | .0506815 | 1.83 | 0.071 | .0928731 |
Age | .0238155* | .0136858 | 1.74 | 0.086 | .0238155 |
Education | .0428948** | .0215988 | 1.99 | 0.051 | .0428948 |
If yes number | .0098008 | .0225234 | 0.44 | 0.665 | .0098008 |
Duration farming | −.0088377 | .0192465 | −0.46 | 0.647 | −.0088377 |
Transport to market | −.0115561 | .0224159 | −0.52 | 0.608 | −.0115561 |
Time of year | −.0321768* | .0190296 | −1.69 | 0.095 | −.0321768 |
Constant | .7903371 | .1592653 | 4.96 | 0.000 | |
LR chi2(7) = 11.47 | |||||
Prob > chi2 = 0.1195 | |||||
Pseudo R2 = −0.3077 | |||||
Log likelihood = 24.364345 |
Tobit results and marginal effects.
Note: *** = 1% significance level, ** = 5‰ and * = 10‰ significance level.
Source: Author’s computation (2021).
Tobit results presented in Table 3 above indicate that gender was statistically significant at 10% with a positive influence on the extent of commercialization amongst the farmers. This positive relationship between gender and the extent of commercialization is inconclusive since any of the gender can commercialize. The marginal effect presents that gender affects the level of commercialization by about 9%. Age was also found to affect the level of commercialization at 10% positively. These results imply that an increase in age of a farmer has a high probability of increasing the extent of commercialization by 23.8% (presented by marginal effect). Many studies have concluded that age signifies the level of experience of a farmer. Moreover, farmers with more experience tend to participate in the market.
Levels of education significantly affect the extent of commercialization at 5%. The positive coefficient shows that the more educated a farmer becomes, the high possibility of commercializing their goat production. The results are in line with [24] who stated that educated farmers are more likely to participate in marketing of their products. This is because educated farmers are more likely to know the available marketing channels. Similarly, [32] attest that illiteracy affects one’s ability to access important agricultural market information (such as price updates) and fair marketing commitments. Illiteracy does not involve the inability to read and write only, but also inability to interpret agricultural market information. It is acknowledged that farmers with basic education are more likely to adopt new production technology and this impacts the number of goats produced and consequently market participation. [33] indicate that most of the farmers in South Africa have 5 years of education (an equivalent of grade 5). The modern production technologies needed to increase agricultural production tend to be composite for the illiterate farmers, who are, therefore, less likely to adopt them. Therefore, the level of education has major implications for agriculture production since it is going through a series of innovations and development demanding a better-educated farmer. In addition, education influences the ability of farmers to adopt new marketing information and technology.
The time of the year presented in Table 3 above signifies the season. It is significant at 10% but has a negative influence on the extent of commercialization of goat. The results are in agreement with the fact that goat meat is usually in high demand during traditional ceremonies. These traditional ceremonies usually take place during the holidays of April, June, and December. For that reason, most farmers do not sell their goats when they are not in demand. Domestic consumption of fresh goat meat for only traditional and religious ceremonies is the primary challenge for goat farmers as they are unable to sell throughout the year.
Socio-economic factors have an impact on both farmers’ choice and the extent of commercialization in the study. The study reveals that older farmers with experience are the ones likely to participate in the market. Educated farmers are also highly likely to participate in the market because they can access and be able to interpret marketing information. Age and level of education affect the number of goats owned and market participation. Level of education and experience enables the farmer to effectively manage goats thus achieving high productivity, as it is also easy for educated farmers to adopt new technologies that will improve production. Therefore there is a great positive relationship between productivity and market participation which consequently influences commercialization. It is noted in the study that the farmers use the informal market to sell their goats live and socio-economic issues largely influence the marketing as goats are sold in certain specific months which is the period where certain cultural, tradition or religious ceremonies are performed. There are no formal markets for goats and goats products, this is an issue as farmers depend on the available informal market which is not structured thus farmers in the study area have no choice to whom they sell their goats to.
The study reveals that a skilled and educated goat farmer participates in the market. Therefore, government programs that will train and skill goat farmers must be established to increase productivity and market participation. Market information is an important aspect of agricultural development as it enhances market performance and knowledge of market actors. Furthermore, training programs are important for adopting production and marketing technologies, thus enhancing rural goat farmers’ productivity. Through the training programs, effective goat marketing strategies could be developed to inform consumers about attributes of goats to address the sociocultural stigma attached to goat and allow goat products to be accepted as an alternative protein source and this will allow goat sales to be throughout the year consequently achieving sustainable commercialization of goats. The goat product potential that is somehow overshadowed by cattle, sheep, and pig products will be illuminated by establishing formal markets. Training programs will also assist farmers in understanding the demand, price trend, and dynamics in consumer preferences. The study further reveals a positive relationship between market participation and productivity, therefore it appears that the quantity of goats is among the leading significant drivers thus efforts to increase production abilities are very important to promote commercialization of household farmers.
This study recommends that a pathway be created to support household goat farmers so that viable conditions to shift from subsistence farming to market-oriented farming are established. Government support for goat farmers will be imperative in this regard. The study also recommends establishing formal market structures where goat farmers can sell their goats and goat produce to promote market participation and, consequently, increase food security and poverty alleviation for rural farmers. Government support in establishing the formal market for goats will be of high importance as in return revenue could be collected from farmers thus contributing to the country’s economy. The increasing evolution in consumer preferences and health consciousness is important for diffusion innovation and exploitation of new markets for goat products thus achieving commercialization. Climate change makes goat husbandry the main feasible economic and productive activity in mountain areas of South Africa, where the climatic and soil conditions hinder the sustainability of other livestock-rearing activities. Goats can effectively provide environmental and socio-economic services sustainable if well managed and also if there is a structured market for goats. It is noteworthy that the economic value of goats can be realized through commercial production and marketing of goat as well as through value-adding to goat products. There is therefore a need to explore vast marketing opportunities both local and international and at the same time improving goat production towards a commercial approach so as to ensure reliable supply and sustainability of these new markets.
The authors wish to thank their respective institutions for the material used and intellectual support.
The authors declare no conflict of interest.
All authors contributed in writing the paper.
This research received no external funding.
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His studies in robotics lead him not only to a PhD degree but also inspired him to co-found and build the International Journal of Advanced Robotic Systems - world's first Open Access journal in the field of robotics.",institutionString:null,institution:{name:"TU Wien",country:{name:"Austria"}}},{id:"441",title:"Ph.D.",name:"Jaekyu",middleName:null,surname:"Park",slug:"jaekyu-park",fullName:"Jaekyu Park",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/441/images/1881_n.jpg",biography:null,institutionString:null,institution:{name:"LG Corporation (South Korea)",country:{name:"Korea, South"}}},{id:"465",title:"Dr.",name:"Christian",middleName:null,surname:"Martens",slug:"christian-martens",fullName:"Christian Martens",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Rheinmetall (Germany)",country:{name:"Germany"}}},{id:"479",title:"Dr.",name:"Valentina",middleName:null,surname:"Colla",slug:"valentina-colla",fullName:"Valentina Colla",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/479/images/358_n.jpg",biography:null,institutionString:null,institution:{name:"Sant'Anna School of Advanced Studies",country:{name:"Italy"}}},{id:"494",title:"PhD",name:"Loris",middleName:null,surname:"Nanni",slug:"loris-nanni",fullName:"Loris Nanni",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/494/images/system/494.jpg",biography:"Loris Nanni received his Master Degree cum laude on June-2002 from the University of Bologna, and the April 26th 2006 he received his Ph.D. in Computer Engineering at DEIS, University of Bologna. On September, 29th 2006 he has won a post PhD fellowship from the university of Bologna (from October 2006 to October 2008), at the competitive examination he was ranked first in the industrial engineering area. He extensively served as referee for several international journals. He is author/coauthor of more than 100 research papers. He has been involved in some projects supported by MURST and European Community. 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Delac received his B.Sc.E.E. degree in 2003 and is currentlypursuing a Ph.D. degree at the University of Zagreb, Faculty of Electrical Engineering andComputing. His current research interests are digital image analysis, pattern recognition andbiometrics.",institutionString:null,institution:{name:"University of Zagreb",country:{name:"Croatia"}}},{id:"557",title:"Dr.",name:"Andon",middleName:"Venelinov",surname:"Topalov",slug:"andon-topalov",fullName:"Andon Topalov",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/557/images/1927_n.jpg",biography:"Dr. Andon V. Topalov received the MSc degree in Control Engineering from the Faculty of Information Systems, Technologies, and Automation at Moscow State University of Civil Engineering (MGGU) in 1979. He then received his PhD degree in Control Engineering from the Department of Automation and Remote Control at Moscow State Mining University (MGSU), Moscow, in 1984. From 1985 to 1986, he was a Research Fellow in the Research Institute for Electronic Equipment, ZZU AD, Plovdiv, Bulgaria. In 1986, he joined the Department of Control Systems, Technical University of Sofia at the Plovdiv campus, where he is presently a Full Professor. He has held long-term visiting Professor/Scholar positions at various institutions in South Korea, Turkey, Mexico, Greece, Belgium, UK, and Germany. And he has coauthored one book and authored or coauthored more than 80 research papers in conference proceedings and journals. His current research interests are in the fields of intelligent control and robotics.",institutionString:null,institution:{name:"Technical University of Sofia",country:{name:"Bulgaria"}}},{id:"585",title:"Prof.",name:"Munir",middleName:null,surname:"Merdan",slug:"munir-merdan",fullName:"Munir Merdan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/585/images/system/585.jpg",biography:"Munir Merdan received the M.Sc. degree in mechanical engineering from the Technical University of Sarajevo, Bosnia and Herzegovina, in 2001, and the Ph.D. degree in electrical engineering from the Vienna University of Technology, Vienna, Austria, in 2009.Since 2005, he has been at the Automation and Control Institute, Vienna University of Technology, where he is currently a Senior Researcher. 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Aalborg University has Two Satellite Campuses, one in Copenhagen (Aalborg University Copenhagen) and the other in Esbjerg (Aalborg University Esbjerg).\n· He is a member of prestigious IEEE (Institute of Electrical and Electronics Engineers), and IAENG (International Association of Engineers) organizations. \n· He is the chief Editor of the Journal of Software Engineering.\n· He is the member of the Editorial Board of International Journal of Computer Science and Software Technology (IJCSST) and International Journal of Computer Engineering and Information Technology. \n· He is also the Editor of Communication in Computer and Information Science CCIS-20 by Springer.\n· Reviewer For Many Conferences\nHe is the lead person in making collaboration agreements between Aalborg University and many universities of Pakistan, for which the MOU’s (Memorandum of Understanding) have been signed.\nProfessor Akbar is working in Academia since 1990, he started his career as a Lab demonstrator/TA at the University of Sussex. After finishing his P. hD degree in 1992, he served in the Industry as a Scientific Officer and continued his academic career as a visiting scholar for a number of educational institutions. In 1996 he joined National University of Science & Technology Pakistan (NUST) as an Associate Professor; NUST is one of the top few universities in Pakistan. In 1999 he joined an International Company Lineo Inc, Canada as Manager Compiler Group, where he headed the group for developing Compiler Tool Chain and Porting of Operating Systems for the BLACKfin processor. The processor development was a joint venture by Intel and Analog Devices. In 2002 Lineo Inc., was taken over by another company, so he joined Aalborg University Denmark as an Assistant Professor.\nProfessor Akbar has truly a multi-disciplined career and he continued his legacy and making progress in many areas of his interests both in teaching and research. 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Küden and Ali Küden",coverURL:"https://cdn.intechopen.com/books/images_new/10900.jpg",editedByType:"Edited by",publishedDate:"July 6th 2022",editors:[{id:"200365",title:"Prof.",name:"Ayzin B.",middleName:"B.",surname:"Küden",slug:"ayzin-b.-kuden",fullName:"Ayzin B. Küden"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},subject:{topic:{id:"828",title:"Reliability Engineering",slug:"reliability-engineering",parent:{id:"123",title:"System Engineering",slug:"system-engineering"},numberOfBooks:7,numberOfSeries:0,numberOfAuthorsAndEditors:143,numberOfWosCitations:56,numberOfCrossrefCitations:78,numberOfDimensionsCitations:106,videoUrl:null,fallbackUrl:null,description:null},booksByTopicFilter:{topicId:"828",sort:"-publishedDate",limit:12,offset:0},booksByTopicCollection:[{type:"book",id:"10384",title:"Practical Applications in Reliability Engineering",subtitle:null,isOpenForSubmission:!1,hash:"377d3c041a06cfcfc99bd906fdbbbf46",slug:"practical-applications-in-reliability-engineering",bookSignature:"Muhammad Zubair",coverURL:"https://cdn.intechopen.com/books/images_new/10384.jpg",editedByType:"Edited by",editors:[{id:"320007",title:"Associate 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by"}}],booksByTopicTotal:7,seriesByTopicCollection:[],seriesByTopicTotal:0,mostCitedChapters:[{id:"57936",doi:"10.5772/intechopen.71926",title:"Power System Reliability: Mathematical Models and Applications",slug:"power-system-reliability-mathematical-models-and-applications",totalDownloads:2802,totalCrossrefCites:5,totalDimensionsCites:10,abstract:"This chapter deals with power systems reliability including technical, economical, and decisional aspects. Knowing that almost 90% of failures occur in the distribution systems, great interest was dedicated to this part of the system, and the first work was oriented to reliability indices defined as objectives to attempt and as performance measures in the electricity market. Some works deal with the managers’ behavior, and the customers reactions are modeled using economic criteria in uncertain future and inspired from game theory. When studying components, degradation models were introduced and combined with the effects of socks to study the reliability changing during system operation. In some works, the correlation between maintenance policies and reliability aspects was highlighted. In a recent work, considering the importance of new technologies integration and renewable energy insertion to power systems, it was revealed that reliability aspects and energy sustainability are two fundamental issues of progress in a given society.",book:{id:"6024",slug:"system-reliability",title:"System Reliability",fullTitle:"System Reliability"},signatures:"Rabah Medjoudj, Hassiba Bediaf and Djamil Aissani",authors:[{id:"182165",title:"Dr.",name:"Rabah",middleName:null,surname:"Medjoudj",slug:"rabah-medjoudj",fullName:"Rabah Medjoudj"},{id:"182167",title:"Prof.",name:"Djamil",middleName:null,surname:"Aissani",slug:"djamil-aissani",fullName:"Djamil Aissani"},{id:"208149",title:"Ms.",name:"Hassiba",middleName:null,surname:"Bediaf",slug:"hassiba-bediaf",fullName:"Hassiba Bediaf"}]},{id:"56062",doi:"10.5772/intechopen.69721",title:"A Decision Support System for Planning and Operation of Maintenance and Customer Services in Electric Power Distribution Systems",slug:"a-decision-support-system-for-planning-and-operation-of-maintenance-and-customer-services-in-electri",totalDownloads:1705,totalCrossrefCites:4,totalDimensionsCites:7,abstract:"This chapter aims to present the design and development of a decision support system (DSS) for the analysis, simulation, planning, and operation of maintenance and customer services in electric power distribution system (EPDS). The main objective of the DSS is to improve the decision‐making processes through visualization tools and simulation of real cases in the EPDS, in order to allow better planning in the short, medium, and long term. Therefore, the DSS helps managers and decision‐makers to reduce maintenance and operational costs, to improve system reliability, and to analyze new scenarios and conditions for system expansion planning. First, we introduce the key challenges faced by the decision‐makers in the planning and operation of maintenance and customer services in EPDS. Next, we discuss the benefits and the requirements for the DSS design and development, including use cases modeling and the software architecture. Afterwards, we present the capabilities of the DSS and discuss important decisions made during the implementation phases. We conclude the chapter with a discussion about the obtained results, pointing out the possible enhancements of the DSS, future extensions, and new use cases that may be addressed.",book:{id:"6024",slug:"system-reliability",title:"System Reliability",fullTitle:"System Reliability"},signatures:"Carlos Henrique Barriquello, Vinícius Jacques Garcia, Magdiel\nSchmitz, Daniel Pinheiro Bernardon and Júlio Schenato Fonini",authors:[{id:"180154",title:"Dr.",name:"Daniel",middleName:"P",surname:"Bernardon",slug:"daniel-bernardon",fullName:"Daniel Bernardon"},{id:"180657",title:"Dr.",name:"Vinicius Jacques",middleName:"Jacques",surname:"Garcia",slug:"vinicius-jacques-garcia",fullName:"Vinicius Jacques Garcia"},{id:"203699",title:"Dr.",name:"Carlos",middleName:null,surname:"Barriquello",slug:"carlos-barriquello",fullName:"Carlos Barriquello"},{id:"206560",title:"Mr.",name:"Magdiel",middleName:null,surname:"Schmitz",slug:"magdiel-schmitz",fullName:"Magdiel Schmitz"},{id:"206562",title:"BSc.",name:"Júlio",middleName:null,surname:"Schenato Fonini",slug:"julio-schenato-fonini",fullName:"Júlio Schenato Fonini"}]},{id:"66913",doi:"10.5772/intechopen.85571",title:"Reliability Evaluation of Power Systems",slug:"reliability-evaluation-of-power-systems",totalDownloads:2019,totalCrossrefCites:3,totalDimensionsCites:7,abstract:"Reliability evaluation of electric power systems is an essential and vital issue in the planning, designing, and operation of power systems. An electric power system consists of a set of components interconnected with each other in some purposeful and meaningful manner. The object of a reliability evaluation is to derive suitable measures, criteria, and indices of reliable and dependable performance based on component outage data and configuration. For evaluating generated reliability, the components of interest are the generating units and system configuration, which refer to the specific unit(s) operated to serve the present or future load. The indices used to measure the generated reliability are probabilistic estimates of the ability of a particular generation configuration to supply the load demand. These indices are better understood as an assessment of system-wide generation adequacy and not as absolute measures of system reliability. The indices are sensitive to basic factors like unit size and unit availability and are most useful when comparing the relative reliability of different generation configurations. The system is deemed to operate successfully if there is enough generation capacity (adequate reserve) to satisfy the peak load (maximum demand). Firstly, generation model and load model are convolved (mutually combined) to yield the risk of supply shortages in the system. Secondly, probabilistic estimates of shortage risk are used as indices of bulk power system reliability evaluation for the considered configuration.",book:{id:"7687",slug:"reliability-and-maintenance-an-overview-of-cases",title:"Reliability and Maintenance",fullTitle:"Reliability and Maintenance - An Overview of Cases"},signatures:"Abdullah M. Al-Shaalan",authors:[{id:"274935",title:"Prof.",name:"Abdullah",middleName:"Mohammed",surname:"Al-Shaalan",slug:"abdullah-al-shaalan",fullName:"Abdullah Al-Shaalan"}]},{id:"56115",doi:"10.5772/intechopen.69440",title:"Mixed-Mode Delamination Failures of Quasi-Isotropic Quasi- Homogeneous Carbon/Epoxy Laminated Composite",slug:"mixed-mode-delamination-failures-of-quasi-isotropic-quasi-homogeneous-carbon-epoxy-laminated-composi",totalDownloads:1358,totalCrossrefCites:5,totalDimensionsCites:5,abstract:"This chapter characterised the delamination behaviour of a quasi-isotropic quasi-homogeneous (QIQH) multidirectional carbon/epoxy-laminated composite. The delaminated surface constituted of 45°//0 layers. Specimens were tested using mode I double cantilever beam (DCB), mode II end-notched flexure (ENF) and mixed-mode I+II mixed-mode flexure (MMF) tests at constant crosshead speed of 1 mm/min. Results showed that the fracture toughness increased with the mode II component. Specifically, the mode I, mode II and mixed-mode I+II fracture toughness were 508.17, 1676.26 and 927.52 N/m, respectively. When the fracture toughness values were fitted using the Benzeggagh-Kenane (BK) criterion, it was found that the best-fit material parameter, η, was attained at 1.21. Furthermore, fibre bridging was observed in DCB specimens, where the steady-state fracture toughness was approximately 80% higher compared to the mode I fracture toughness. Finally, through scanning electron micrographs, it was found that there was resin-rich region at the crack tip of the specimens. In addition, fibre debonding of the 45°layer was found to be dominant in the DCB specimens. Significant shear cusps were noticed in the ENF specimens. As for the MMF specimens, matrix cracking and fibre debonding of the 0°layer were observed to be the major failure mechanisms.",book:{id:"5720",slug:"failure-analysis-and-prevention",title:"Failure Analysis and Prevention",fullTitle:"Failure Analysis and Prevention"},signatures:"Mahzan Johar, King Jye Wong and Mohd Nasir Tamin",authors:[{id:"196884",title:"Prof.",name:"Mohd Nasir",middleName:null,surname:"Tamin",slug:"mohd-nasir-tamin",fullName:"Mohd Nasir Tamin"},{id:"197028",title:"Dr.",name:"King Jye",middleName:null,surname:"Wong",slug:"king-jye-wong",fullName:"King Jye Wong"},{id:"203971",title:"Dr.",name:"Mahzan",middleName:null,surname:"Johar",slug:"mahzan-johar",fullName:"Mahzan Johar"}]},{id:"55938",doi:"10.5772/intechopen.69286",title:"Imperfect Maintenance Models, from Theory to Practice",slug:"imperfect-maintenance-models-from-theory-to-practice",totalDownloads:2159,totalCrossrefCites:3,totalDimensionsCites:6,abstract:"The role of maintenance in the industrial environment changed a lot in recent years, and today, it is a key function for long-term profitability in an organization. Many contributions were recently written by researchers on this topic. A lot of models were proposed to optimize maintenance activities while ensuring availability and high-quality requirements. In addition to the well-known classification of maintenance activities—preventive and corrective—in the last decades, a new classification emerged in the literature regarding the degree of system restoration after maintenance actions. Among them, the imperfect maintenance is one of the most studied maintenance types: it is defined as an action after which the system lies in a state somewhere between an “as good as new” state and its pre-maintenance condition “as bad as old.” Most of the industrial companies usually operate with imperfect maintenance actions, even if the awareness in actual industrial context is limited. On the practical definition side, in particular, there are some real situations of imperfect maintenance: three main specific cases were identified, both from literature analysis and from experience. Considering these three implementations of imperfect maintenance actions and the main models proposed in the literature, we illustrate how to identify the most suitable model for each real case.",book:{id:"6024",slug:"system-reliability",title:"System Reliability",fullTitle:"System Reliability"},signatures:"Filippo De Carlo and Maria Antonietta Arleo",authors:[{id:"161657",title:"Dr.",name:"Filippo",middleName:null,surname:"De Carlo",slug:"filippo-de-carlo",fullName:"Filippo De Carlo"},{id:"171361",title:"Dr.",name:"Maria Antonietta",middleName:null,surname:"Arleo",slug:"maria-antonietta-arleo",fullName:"Maria Antonietta Arleo"}]}],mostDownloadedChaptersLast30Days:[{id:"50094",title:"Reliability of Systems",slug:"reliability-of-systems",totalDownloads:3450,totalCrossrefCites:1,totalDimensionsCites:0,abstract:"Many objects consist of more components. The mutual arrangement of the individual elements influences the resultant reliability. The formulae are shown for the resultant reliability of series arrangement, as well as for parallel and combined arrangement. The possibility of reliability increasing by means of redundancy is explained, and also the principle of optimal allocation of reliabilities to individual elements. Everything is illustrated on examples.",book:{id:"5317",slug:"concise-reliability-for-engineers",title:"Concise Reliability for Engineers",fullTitle:"Concise Reliability for Engineers"},signatures:"Jaroslav Menčík",authors:[{id:"142710",title:"Prof.",name:"Jaroslav",middleName:null,surname:"Menčík",slug:"jaroslav-mencik",fullName:"Jaroslav Menčík"}]},{id:"50095",title:"Time to Failure of Deteriorating Objects",slug:"time-to-failure-of-deteriorating-objects",totalDownloads:1690,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"This chapter explains the prediction of the time to failure in the following cases: fatigue of metallic components under cyclic loading or in the presence of cracks, static fatigue, wear and creep, variable loading (damage accumulation). Prediction of the time to failure based on monitoring of the changing response. Probabilistic aspects of the lifetime prediction. The determination of the time to failure is illustrated on examples.",book:{id:"5317",slug:"concise-reliability-for-engineers",title:"Concise Reliability for Engineers",fullTitle:"Concise Reliability for Engineers"},signatures:"Jaroslav Menčík",authors:[{id:"142710",title:"Prof.",name:"Jaroslav",middleName:null,surname:"Menčík",slug:"jaroslav-mencik",fullName:"Jaroslav Menčík"}]},{id:"66913",title:"Reliability Evaluation of Power Systems",slug:"reliability-evaluation-of-power-systems",totalDownloads:2013,totalCrossrefCites:3,totalDimensionsCites:6,abstract:"Reliability evaluation of electric power systems is an essential and vital issue in the planning, designing, and operation of power systems. An electric power system consists of a set of components interconnected with each other in some purposeful and meaningful manner. The object of a reliability evaluation is to derive suitable measures, criteria, and indices of reliable and dependable performance based on component outage data and configuration. For evaluating generated reliability, the components of interest are the generating units and system configuration, which refer to the specific unit(s) operated to serve the present or future load. The indices used to measure the generated reliability are probabilistic estimates of the ability of a particular generation configuration to supply the load demand. These indices are better understood as an assessment of system-wide generation adequacy and not as absolute measures of system reliability. The indices are sensitive to basic factors like unit size and unit availability and are most useful when comparing the relative reliability of different generation configurations. The system is deemed to operate successfully if there is enough generation capacity (adequate reserve) to satisfy the peak load (maximum demand). Firstly, generation model and load model are convolved (mutually combined) to yield the risk of supply shortages in the system. Secondly, probabilistic estimates of shortage risk are used as indices of bulk power system reliability evaluation for the considered configuration.",book:{id:"7687",slug:"reliability-and-maintenance-an-overview-of-cases",title:"Reliability and Maintenance",fullTitle:"Reliability and Maintenance - An Overview of Cases"},signatures:"Abdullah M. Al-Shaalan",authors:[{id:"274935",title:"Prof.",name:"Abdullah",middleName:"Mohammed",surname:"Al-Shaalan",slug:"abdullah-al-shaalan",fullName:"Abdullah Al-Shaalan"}]},{id:"58172",title:"X-Ray Techniques",slug:"x-ray-techniques",totalDownloads:2443,totalCrossrefCites:1,totalDimensionsCites:3,abstract:"This chapter reviewed existing X-ray techniques that can be used for the analysis of materials, inclusive of those used as engineering and structural components. These techniques are X-ray fluorescence (XRF) spectrometry, proton-induced X-ray emission (PIXE) spectrometry, and X-ray diffraction (XRD). These analytical techniques provide qualitative and quantitative information on the composition and structure of materials with precision. XRD gives information on the crystalline forms and amorphous content of materials, which could be quite useful in failure analysis if the type of failure brings about morphological changes in the material under investigation. PIXE and XRF provide information on the types of elements present in a sample material and their concentrations. PIXE is however preferable to XRF due to its higher sensitivity to trace elements and lower atomic number elements as well as its faster analysis. XRF and XRD are more commonly used than PIXE which is a powerful, high-tech method that is relatively new in the field of chemical research. In this chapter, the theory and principles of these analytical techniques are explained, and diagrams showing the components of spectrometers and diffractometers are provided with descriptions of how they function.",book:{id:"5720",slug:"failure-analysis-and-prevention",title:"Failure Analysis and Prevention",fullTitle:"Failure Analysis and Prevention"},signatures:"Clementina Dilim Igwebike-Ossi",authors:[{id:"219931",title:"Dr.",name:"Clementina",middleName:null,surname:"Igwebike-Ossi",slug:"clementina-igwebike-ossi",fullName:"Clementina Igwebike-Ossi"}]},{id:"57936",title:"Power System Reliability: Mathematical Models and Applications",slug:"power-system-reliability-mathematical-models-and-applications",totalDownloads:2799,totalCrossrefCites:5,totalDimensionsCites:10,abstract:"This chapter deals with power systems reliability including technical, economical, and decisional aspects. Knowing that almost 90% of failures occur in the distribution systems, great interest was dedicated to this part of the system, and the first work was oriented to reliability indices defined as objectives to attempt and as performance measures in the electricity market. Some works deal with the managers’ behavior, and the customers reactions are modeled using economic criteria in uncertain future and inspired from game theory. When studying components, degradation models were introduced and combined with the effects of socks to study the reliability changing during system operation. In some works, the correlation between maintenance policies and reliability aspects was highlighted. 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Heshmati",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/313921/images/system/313921.jpg",biography:"Dr. Hassan Massoud Heshmati is an endocrinologist with 46 years of experience in clinical research in academia (university-affiliated hospitals, Paris, France; Mayo Foundation, Rochester, MN, USA) and pharmaceutical companies (Sanofi, Malvern, PA, USA; Essentialis, Carlsbad, CA, USA; Gelesis, Boston, MA, USA). His research activity focuses on pituitary tumors, hyperthyroidism, thyroid cancers, osteoporosis, diabetes, and obesity. He has extensive knowledge in the development of anti-obesity products. Dr. Heshmati is the author of 299 abstracts, chapters, and articles related to endocrinology and metabolism. He is currently a consultant at Endocrinology Metabolism Consulting, LLC, Anthem, AZ, USA.",institutionString:"Endocrinology Metabolism Consulting, LLC",institution:null},{id:"76477",title:"Prof.",name:"Mirza",middleName:null,surname:"Hasanuzzaman",slug:"mirza-hasanuzzaman",fullName:"Mirza Hasanuzzaman",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/76477/images/system/76477.png",biography:"Dr. Mirza Hasanuzzaman is a Professor of Agronomy at Sher-e-Bangla Agricultural University, Bangladesh. He received his Ph.D. in Plant Stress Physiology and Antioxidant Metabolism from Ehime University, Japan, with a scholarship from the Japanese Government (MEXT). Later, he completed his postdoctoral research at the Center of Molecular Biosciences, University of the Ryukyus, Japan, as a recipient of the Japan Society for the Promotion of Science (JSPS) postdoctoral fellowship. He was also the recipient of the Australian Government Endeavour Research Fellowship for postdoctoral research as an adjunct senior researcher at the University of Tasmania, Australia. Dr. Hasanuzzaman’s current work is focused on the physiological and molecular mechanisms of environmental stress tolerance. Dr. Hasanuzzaman has published more than 150 articles in peer-reviewed journals. He has edited ten books and written more than forty book chapters on important aspects of plant physiology, plant stress tolerance, and crop production. According to Scopus, Dr. Hasanuzzaman’s publications have received more than 10,500 citations with an h-index of 53. He has been named a Highly Cited Researcher by Clarivate. He is an editor and reviewer for more than fifty peer-reviewed international journals and was a recipient of the “Publons Peer Review Award” in 2017, 2018, and 2019. He has been honored by different authorities for his outstanding performance in various fields like research and education, and he has received the World Academy of Science Young Scientist Award (2014) and the University Grants Commission (UGC) Award 2018. He is a fellow of the Bangladesh Academy of Sciences (BAS) and the Royal Society of Biology.",institutionString:"Sher-e-Bangla Agricultural University",institution:{name:"Sher-e-Bangla Agricultural University",country:{name:"Bangladesh"}}},{id:"187859",title:"Prof.",name:"Kusal",middleName:"K.",surname:"Das",slug:"kusal-das",fullName:"Kusal Das",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSBDeQAO/Profile_Picture_1623411145568",biography:"Kusal K. Das is a Distinguished Chair Professor of Physiology, Shri B. M. Patil Medical College and Director, Centre for Advanced Medical Research (CAMR), BLDE (Deemed to be University), Vijayapur, Karnataka, India. Dr. Das did his M.S. and Ph.D. in Human Physiology from the University of Calcutta, Kolkata. His area of research is focused on understanding of molecular mechanisms of heavy metal activated low oxygen sensing pathways in vascular pathophysiology. He has invented a new method of estimation of serum vitamin E. His expertise in critical experimental protocols on vascular functions in experimental animals was well documented by his quality of publications. He was a Visiting Professor of Medicine at University of Leeds, United Kingdom (2014-2016) and Tulane University, New Orleans, USA (2017). For his immense contribution in medical research Ministry of Science and Technology, Government of India conferred him 'G.P. Chatterjee Memorial Research Prize-2019” and he is also the recipient of 'Dr.Raja Ramanna State Scientist Award 2015” by Government of Karnataka. He is a Fellow of the Royal Society of Biology (FRSB), London and Honorary Fellow of Karnataka Science and Technology Academy, Department of Science and Technology, Government of Karnataka.",institutionString:"BLDE (Deemed to be University), India",institution:null},{id:"243660",title:"Dr.",name:"Mallanagouda Shivanagouda",middleName:null,surname:"Biradar",slug:"mallanagouda-shivanagouda-biradar",fullName:"Mallanagouda Shivanagouda Biradar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/243660/images/system/243660.jpeg",biography:"M. S. Biradar is Vice Chancellor and Professor of Medicine of\nBLDE (Deemed to be University), Vijayapura, Karnataka, India.\nHe obtained his MD with a gold medal in General Medicine and\nhas devoted himself to medical teaching, research, and administrations. He has also immensely contributed to medical research\non vascular medicine, which is reflected by his numerous publications including books and book chapters. Professor Biradar was\nalso Visiting Professor at Tulane University School of Medicine, New Orleans, USA.",institutionString:"BLDE (Deemed to be University)",institution:{name:"BLDE University",country:{name:"India"}}},{id:"289796",title:"Dr.",name:"Swastika",middleName:null,surname:"Das",slug:"swastika-das",fullName:"Swastika Das",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/289796/images/system/289796.jpeg",biography:"Swastika N. Das is Professor of Chemistry at the V. P. Dr. P. G.\nHalakatti College of Engineering and Technology, BLDE (Deemed\nto be University), Vijayapura, Karnataka, India. She obtained an\nMSc, MPhil, and PhD in Chemistry from Sambalpur University,\nOdisha, India. Her areas of research interest are medicinal chemistry, chemical kinetics, and free radical chemistry. She is a member\nof the investigators who invented a new modified method of estimation of serum vitamin E. She has authored numerous publications including book\nchapters and is a mentor of doctoral curriculum at her university.",institutionString:"BLDEA’s V.P.Dr.P.G.Halakatti College of Engineering & Technology",institution:{name:"BLDE University",country:{name:"India"}}},{id:"248459",title:"Dr.",name:"Akikazu",middleName:null,surname:"Takada",slug:"akikazu-takada",fullName:"Akikazu Takada",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/248459/images/system/248459.png",biography:"Akikazu Takada was born in Japan, 1935. After graduation from\nKeio University School of Medicine and finishing his post-graduate studies, he worked at Roswell Park Memorial Institute NY,\nUSA. He then took a professorship at Hamamatsu University\nSchool of Medicine. In thrombosis studies, he found the SK\npotentiator that enhances plasminogen activation by streptokinase. He is very much interested in simultaneous measurements\nof fatty acids, amino acids, and tryptophan degradation products. By using fatty\nacid analyses, he indicated that plasma levels of trans-fatty acids of old men were\nfar higher in the US than Japanese men. . He also showed that eicosapentaenoic acid\n(EPA) and docosahexaenoic acid (DHA) levels are higher, and arachidonic acid\nlevels are lower in Japanese than US people. By using simultaneous LC/MS analyses\nof plasma levels of tryptophan metabolites, he recently found that plasma levels of\nserotonin, kynurenine, or 5-HIAA were higher in patients of mono- and bipolar\ndepression, which are significantly different from observations reported before. In\nview of recent reports that plasma tryptophan metabolites are mainly produced by\nmicrobiota. He is now working on the relationships between microbiota and depression or autism.",institutionString:"Hamamatsu University School of Medicine",institution:{name:"Hamamatsu University School of Medicine",country:{name:"Japan"}}},{id:"137240",title:"Prof.",name:"Mohammed",middleName:null,surname:"Khalid",slug:"mohammed-khalid",fullName:"Mohammed Khalid",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/137240/images/system/137240.png",biography:"Mohammed Khalid received his B.S. in Chemistry in July 2000, and his Ph.D. in Physical Chemistry in 2007 from the University of Khartoum, Sudan. In 2009 he joined the Dr. Ron Clarke research group at the School of Chemistry, Faculty of Science, University of Sydney, Australia as a postdoctoral fellow where he worked on the Interaction of ATP with the phosphoenzyme of the Na+, K+-ATPase, and Dual mechanisms of allosteric acceleration of the Na+, K+-ATPase by ATP. He then worked as Assistant Professor at the Department of Chemistry, University of Khartoum, and in 2014 was promoted to Associate Professor ranking. In 2011 he joined the staff of the Chemistry Department at Taif University, Saudi Arabia, where he is currently active as an Assistant Professor. His research interests include:\r\n(1) P-type ATPase Enzyme Kinetics and Mechanisms; (2) Kinetics and Mechanism of Redox Reactions; (3) Autocatalytic reactions; (4) Computational enzyme kinetics; (5) Allosteric acceleration of P-type ATPases by ATP; (6) Exploring of allosteric sites of ATPases and interaction of ATP with ATPases located in the cell membranes.",institutionString:"Taif University",institution:{name:"Taif University",country:{name:"Saudi Arabia"}}},{id:"63810",title:"Prof.",name:"Jorge",middleName:null,surname:"Morales-Montor",slug:"jorge-morales-montor",fullName:"Jorge Morales-Montor",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/63810/images/system/63810.png",biography:"Dr. Jorge Morales-Montor was recognized with the Lola and Igo Flisser PUIS Award for best graduate thesis at the national level in the field of parasitology. He received a fellowship from the Fogarty Foundation to perform postdoctoral research stay at the University of Georgia. He has 153 journal articles to his credit. He has also edited several books and published more than fifty-five book chapters. He is a member of the Mexican Academy of Sciences, Latin American Academy of Sciences, and the National Academy of Medicine. He has received more than thirty-five awards and has supervised numerous bachelor’s, master’s, and Ph.D. students. Dr. Morales-Montor is the past president of the Mexican Society of Parasitology.",institutionString:"National Autonomous University of Mexico",institution:{name:"National Autonomous University of Mexico",country:{name:"Mexico"}}},{id:"217215",title:"Dr.",name:"Palash",middleName:null,surname:"Mandal",slug:"palash-mandal",fullName:"Palash Mandal",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/217215/images/system/217215.jpeg",biography:null,institutionString:"Charusat University",institution:null},{id:"49739",title:"Dr.",name:"Leszek",middleName:null,surname:"Szablewski",slug:"leszek-szablewski",fullName:"Leszek Szablewski",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49739/images/system/49739.jpg",biography:"Leszek Szablewski is a professor of medical sciences. He received his M.S. in the Faculty of Biology from the University of Warsaw and his PhD degree from the Institute of Experimental Biology Polish Academy of Sciences. He habilitated in the Medical University of Warsaw, and he obtained his degree of Professor from the President of Poland. Professor Szablewski is the Head of Chair and Department of General Biology and Parasitology, Medical University of Warsaw. Professor Szablewski has published over 80 peer-reviewed papers in journals such as Journal of Alzheimer’s Disease, Biochim. Biophys. Acta Reviews of Cancer, Biol. Chem., J. Biomed. Sci., and Diabetes/Metabol. Res. Rev, Endocrine. He is the author of two books and four book chapters. He has edited four books, written 15 scripts for students, is the ad hoc reviewer of over 30 peer-reviewed journals, and editorial member of peer-reviewed journals. Prof. Szablewski’s research focuses on cell physiology, genetics, and pathophysiology. He works on the damage caused by lack of glucose homeostasis and changes in the expression and/or function of glucose transporters due to various diseases. He has given lectures, seminars, and exercises for students at the Medical University.",institutionString:"Medical University of Warsaw",institution:{name:"Medical University of Warsaw",country:{name:"Poland"}}},{id:"173123",title:"Dr.",name:"Maitham",middleName:null,surname:"Khajah",slug:"maitham-khajah",fullName:"Maitham Khajah",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/173123/images/system/173123.jpeg",biography:"Dr. Maitham A. Khajah received his degree in Pharmacy from Faculty of Pharmacy, Kuwait University, in 2003 and obtained his PhD degree in December 2009 from the University of Calgary, Canada (Gastrointestinal Science and Immunology). Since January 2010 he has been assistant professor in Kuwait University, Faculty of Pharmacy, Department of Pharmacology and Therapeutics. His research interest are molecular targets for the treatment of inflammatory bowel disease (IBD) and the mechanisms responsible for immune cell chemotaxis. He cosupervised many students for the MSc Molecular Biology Program, College of Graduate Studies, Kuwait University. Ever since joining Kuwait University in 2010, he got various grants as PI and Co-I. He was awarded the Best Young Researcher Award by Kuwait University, Research Sector, for the Year 2013–2014. He was a member in the organizing committee for three conferences organized by Kuwait University, Faculty of Pharmacy, as cochair and a member in the scientific committee (the 3rd, 4th, and 5th Kuwait International Pharmacy Conference).",institutionString:"Kuwait University",institution:{name:"Kuwait University",country:{name:"Kuwait"}}},{id:"195136",title:"Dr.",name:"Aya",middleName:null,surname:"Adel",slug:"aya-adel",fullName:"Aya Adel",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/195136/images/system/195136.jpg",biography:"Dr. Adel works as an Assistant Lecturer in the unit of Phoniatrics, Department of Otolaryngology, Ain Shams University in Cairo, Egypt. Dr. Adel is especially interested in joint attention and its impairment in autism spectrum disorder",institutionString:"Ain Shams University",institution:{name:"Ain Shams University",country:{name:"Egypt"}}},{id:"94911",title:"Dr.",name:"Boulenouar",middleName:null,surname:"Mesraoua",slug:"boulenouar-mesraoua",fullName:"Boulenouar Mesraoua",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/94911/images/system/94911.png",biography:"Dr Boulenouar Mesraoua is the Associate Professor of Clinical Neurology at Weill Cornell Medical College-Qatar and a Consultant Neurologist at Hamad Medical Corporation at the Neuroscience Department; He graduated as a Medical Doctor from the University of Oran, Algeria; he then moved to Belgium, the City of Liege, for a Residency in Internal Medicine and Neurology at Liege University; after getting the Belgian Board of Neurology (with high marks), he went to the National Hospital for Nervous Diseases, Queen Square, London, United Kingdom for a fellowship in Clinical Neurophysiology, under Pr Willison ; Dr Mesraoua had also further training in Epilepsy and Continuous EEG Monitoring for two years (from 2001-2003) in the Neurophysiology department of Zurich University, Switzerland, under late Pr Hans Gregor Wieser ,an internationally known epileptologist expert. \n\nDr B. Mesraoua is the Director of the Neurology Fellowship Program at the Neurology Section and an active member of the newly created Comprehensive Epilepsy Program at Hamad General Hospital, Doha, Qatar; he is also Assistant Director of the Residency Program at the Qatar Medical School. \nDr B. Mesraoua's main interests are Epilepsy, Multiple Sclerosis, and Clinical Neurology; He is the Chairman and the Organizer of the well known Qatar Epilepsy Symposium, he is running yearly for the past 14 years and which is considered a landmark in the Gulf region; He has also started last year , together with other epileptologists from Qatar, the region and elsewhere, a yearly International Epilepsy School Course, which was attended by many neurologists from the Area.\n\nInternationally, Dr Mesraoua is an active and elected member of the Commission on Eastern Mediterranean Region (EMR ) , a regional branch of the International League Against Epilepsy (ILAE), where he represents the Middle East and North Africa(MENA ) and where he holds the position of chief of the Epilepsy Epidemiology Section; Dr Mesraoua is a member of the American Academy of Neurology, the Europeen Academy of Neurology and the American Epilepsy Society.\n\nDr Mesraoua's main objectives are to encourage frequent gathering of the epileptologists/neurologists from the MENA region and the rest of the world, promote Epilepsy Teaching in the MENA Region, and encourage multicenter studies involving neurologists and epileptologists in the MENA region, particularly epilepsy epidemiological studies. \n\nDr. Mesraoua is the recipient of two research Grants, as the Lead Principal Investigator (750.000 USD and 250.000 USD) from the Qatar National Research Fund (QNRF) and the Hamad Hospital Internal Research Grant (IRGC), on the following topics : “Continuous EEG Monitoring in the ICU “ and on “Alpha-lactoalbumin , proof of concept in the treatment of epilepsy” .Dr Mesraoua is a reviewer for the journal \"seizures\" (Europeen Epilepsy Journal ) as well as dove journals ; Dr Mesraoua is the author and co-author of many peer reviewed publications and four book chapters in the field of Epilepsy and Clinical Neurology",institutionString:"Weill Cornell Medical College in Qatar",institution:{name:"Weill Cornell Medical College in Qatar",country:{name:"Qatar"}}},{id:"282429",title:"Prof.",name:"Covanis",middleName:null,surname:"Athanasios",slug:"covanis-athanasios",fullName:"Covanis Athanasios",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/282429/images/system/282429.jpg",biography:null,institutionString:"Neurology-Neurophysiology Department of the Children Hospital Agia Sophia",institution:null},{id:"190980",title:"Prof.",name:"Marwa",middleName:null,surname:"Mahmoud Saleh",slug:"marwa-mahmoud-saleh",fullName:"Marwa Mahmoud Saleh",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/190980/images/system/190980.jpg",biography:"Professor Marwa Mahmoud Saleh is a doctor of medicine and currently works in the unit of Phoniatrics, Department of Otolaryngology, Ain Shams University in Cairo, Egypt. She got her doctoral degree in 1991 and her doctoral thesis was accomplished in the University of Iowa, United States. Her publications covered a multitude of topics as videokymography, cochlear implants, stuttering, and dysphagia. She has lectured Egyptian phonology for many years. Her recent research interest is joint attention in autism.",institutionString:"Ain Shams University",institution:{name:"Ain Shams University",country:{name:"Egypt"}}},{id:"259190",title:"Dr.",name:"Syed Ali Raza",middleName:null,surname:"Naqvi",slug:"syed-ali-raza-naqvi",fullName:"Syed Ali Raza Naqvi",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259190/images/system/259190.png",biography:"Dr. Naqvi is a radioanalytical chemist and is working as an associate professor of analytical chemistry in the Department of Chemistry, Government College University, Faisalabad, Pakistan. Advance separation techniques, nuclear analytical techniques and radiopharmaceutical analysis are the main courses that he is teaching to graduate and post-graduate students. In the research area, he is focusing on the development of organic- and biomolecule-based radiopharmaceuticals for diagnosis and therapy of infectious and cancerous diseases. Under the supervision of Dr. Naqvi, three students have completed their Ph.D. degrees and 41 students have completed their MS degrees. He has completed three research projects and is currently working on 2 projects entitled “Radiolabeling of fluoroquinolone derivatives for the diagnosis of deep-seated bacterial infections” and “Radiolabeled minigastrin peptides for diagnosis and therapy of NETs”. He has published about 100 research articles in international reputed journals and 7 book chapters. Pakistan Institute of Nuclear Science & Technology (PINSTECH) Islamabad, Punjab Institute of Nuclear Medicine (PINM), Faisalabad and Institute of Nuclear Medicine and Radiology (INOR) Abbottabad are the main collaborating institutes.",institutionString:"Government College University",institution:{name:"Government College University, Faisalabad",country:{name:"Pakistan"}}},{id:"58390",title:"Dr.",name:"Gyula",middleName:null,surname:"Mozsik",slug:"gyula-mozsik",fullName:"Gyula Mozsik",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/58390/images/system/58390.png",biography:"Gyula Mózsik MD, Ph.D., ScD (med), is an emeritus professor of Medicine at the First Department of Medicine, Univesity of Pécs, Hungary. He was head of this department from 1993 to 2003. His specializations are medicine, gastroenterology, clinical pharmacology, clinical nutrition, and dietetics. His research fields are biochemical pharmacological examinations in the human gastrointestinal (GI) mucosa, mechanisms of retinoids, drugs, capsaicin-sensitive afferent nerves, and innovative pharmacological, pharmaceutical, and nutritional (dietary) research in humans. He has published about 360 peer-reviewed papers, 197 book chapters, 692 abstracts, 19 monographs, and has edited 37 books. He has given about 1120 regular and review lectures. He has organized thirty-eight national and international congresses and symposia. He is the founder of the International Conference on Ulcer Research (ICUR); International Union of Pharmacology, Gastrointestinal Section (IUPHAR-GI); Brain-Gut Society symposiums, and gastrointestinal cytoprotective symposiums. He received the Andre Robert Award from IUPHAR-GI in 2014. Fifteen of his students have been appointed as full professors in Egypt, Cuba, and Hungary.",institutionString:"University of Pécs",institution:{name:"University of Pecs",country:{name:"Hungary"}}},{id:"277367",title:"M.Sc.",name:"Daniel",middleName:"Martin",surname:"Márquez López",slug:"daniel-marquez-lopez",fullName:"Daniel Márquez López",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/277367/images/7909_n.jpg",biography:"Msc Daniel Martin Márquez López has a bachelor degree in Industrial Chemical Engineering, a Master of science degree in the same área and he is a PhD candidate for the Instituto Politécnico Nacional. His Works are realted to the Green chemistry field, biolubricants, biodiesel, transesterification reactions for biodiesel production and the manipulation of oils for therapeutic purposes.",institutionString:null,institution:{name:"Instituto Politécnico Nacional",country:{name:"Mexico"}}},{id:"196544",title:"Prof.",name:"Angel",middleName:null,surname:"Catala",slug:"angel-catala",fullName:"Angel Catala",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/196544/images/system/196544.jpg",biography:"Angel Catalá studied chemistry at Universidad Nacional de La Plata, Argentina, where he received a Ph.D. in Chemistry (Biological Branch) in 1965. From 1964 to 1974, he worked as an Assistant in Biochemistry at the School of Medicine at the same university. From 1974 to 1976, he was a fellow of the National Institutes of Health (NIH) at the University of Connecticut, Health Center, USA. From 1985 to 2004, he served as a Full Professor of Biochemistry at the Universidad Nacional de La Plata. He is a member of the National Research Council (CONICET), Argentina, and the Argentine Society for Biochemistry and Molecular Biology (SAIB). His laboratory has been interested for many years in the lipid peroxidation of biological membranes from various tissues and different species. Dr. Catalá has directed twelve doctoral theses, published more than 100 papers in peer-reviewed journals, several chapters in books, and edited twelve books. He received awards at the 40th International Conference Biochemistry of Lipids 1999 in Dijon, France. He is the winner of the Bimbo Pan-American Nutrition, Food Science and Technology Award 2006 and 2012, South America, Human Nutrition, Professional Category. In 2006, he won the Bernardo Houssay award in pharmacology, in recognition of his meritorious works of research. Dr. Catalá belongs to the editorial board of several journals including Journal of Lipids; International Review of Biophysical Chemistry; Frontiers in Membrane Physiology and Biophysics; World Journal of Experimental Medicine and Biochemistry Research International; World Journal of Biological Chemistry, Diabetes, and the Pancreas; International Journal of Chronic Diseases & Therapy; and International Journal of Nutrition. He is the co-editor of The Open Biology Journal and associate editor for Oxidative Medicine and Cellular Longevity.",institutionString:"Universidad Nacional de La Plata",institution:{name:"National University of La Plata",country:{name:"Argentina"}}},{id:"186585",title:"Dr.",name:"Francisco Javier",middleName:null,surname:"Martin-Romero",slug:"francisco-javier-martin-romero",fullName:"Francisco Javier Martin-Romero",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSB3HQAW/Profile_Picture_1631258137641",biography:"Francisco Javier Martín-Romero (Javier) is a Professor of Biochemistry and Molecular Biology at the University of Extremadura, Spain. He is also a group leader at the Biomarkers Institute of Molecular Pathology. Javier received his Ph.D. in 1998 in Biochemistry and Biophysics. At the National Cancer Institute (National Institute of Health, Bethesda, MD) he worked as a research associate on the molecular biology of selenium and its role in health and disease. After postdoctoral collaborations with Carlos Gutierrez-Merino (University of Extremadura, Spain) and Dario Alessi (University of Dundee, UK), he established his own laboratory in 2008. The interest of Javier's lab is the study of cell signaling with a special focus on Ca2+ signaling, and how Ca2+ transport modulates the cytoskeleton, migration, differentiation, cell death, etc. He is especially interested in the study of Ca2+ channels, and the role of STIM1 in the initiation of pathological events.",institutionString:null,institution:{name:"University of Extremadura",country:{name:"Spain"}}},{id:"198499",title:"Dr.",name:"Daniel",middleName:null,surname:"Glossman-Mitnik",slug:"daniel-glossman-mitnik",fullName:"Daniel Glossman-Mitnik",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/198499/images/system/198499.jpeg",biography:"Dr. Daniel Glossman-Mitnik is currently a Titular Researcher at the Centro de Investigación en Materiales Avanzados (CIMAV), Chihuahua, Mexico, as well as a National Researcher of Level III at the Consejo Nacional de Ciencia y Tecnología, México. His research interest focuses on computational chemistry and molecular modeling of diverse systems of pharmacological, food, and alternative energy interests by resorting to DFT and Conceptual DFT. He has authored a coauthored more than 270 peer-reviewed papers, 32 book chapters, and 4 edited books. He has delivered speeches at many international and domestic conferences. He serves as a reviewer for more than eighty international journals, books, and research proposals as well as an editor for special issues of renowned scientific journals.",institutionString:null,institution:null},{id:"217323",title:"Prof.",name:"Guang-Jer",middleName:null,surname:"Wu",slug:"guang-jer-wu",fullName:"Guang-Jer Wu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/217323/images/8027_n.jpg",biography:null,institutionString:null,institution:null},{id:"148546",title:"Dr.",name:"Norma Francenia",middleName:null,surname:"Santos-Sánchez",slug:"norma-francenia-santos-sanchez",fullName:"Norma Francenia Santos-Sánchez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/148546/images/4640_n.jpg",biography:null,institutionString:null,institution:null},{id:"272889",title:"Dr.",name:"Narendra",middleName:null,surname:"Maddu",slug:"narendra-maddu",fullName:"Narendra Maddu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/272889/images/10758_n.jpg",biography:null,institutionString:null,institution:null},{id:"242491",title:"Prof.",name:"Angelica",middleName:null,surname:"Rueda",slug:"angelica-rueda",fullName:"Angelica Rueda",position:"Investigador Cinvestav 3B",profilePictureURL:"https://mts.intechopen.com/storage/users/242491/images/6765_n.jpg",biography:null,institutionString:null,institution:null},{id:"88631",title:"Dr.",name:"Ivan",middleName:null,surname:"Petyaev",slug:"ivan-petyaev",fullName:"Ivan Petyaev",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Lycotec (United Kingdom)",country:{name:"United Kingdom"}}},{id:"428313",title:"Dr.",name:"Sambangi",middleName:null,surname:"Pratyusha",slug:"sambangi-pratyusha",fullName:"Sambangi Pratyusha",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"CGIAR",country:{name:"France"}}},{id:"423869",title:"Ms.",name:"Smita",middleName:null,surname:"Rai",slug:"smita-rai",fullName:"Smita Rai",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Integral University",country:{name:"India"}}},{id:"424024",title:"Prof.",name:"Swati",middleName:null,surname:"Sharma",slug:"swati-sharma",fullName:"Swati Sharma",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Integral University",country:{name:"India"}}},{id:"439112",title:"MSc.",name:"Touseef",middleName:null,surname:"Fatima",slug:"touseef-fatima",fullName:"Touseef Fatima",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Integral University",country:{name:"India"}}}]}},subseries:{item:{id:"15",type:"subseries",title:"Chemical Biology",keywords:"Phenolic Compounds, Essential Oils, Modification of Biomolecules, Glycobiology, Combinatorial Chemistry, Therapeutic peptides, Enzyme Inhibitors",scope:"Chemical biology spans the fields of chemistry and biology involving the application of biological and chemical molecules and techniques. In recent years, the application of chemistry to biological molecules has gained significant interest in medicinal and pharmacological studies. This topic will be devoted to understanding the interplay between biomolecules and chemical compounds, their structure and function, and their potential applications in related fields. Being a part of the biochemistry discipline, the ideas and concepts that have emerged from Chemical Biology have affected other related areas. This topic will closely deal with all emerging trends in this discipline.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/15.jpg",hasOnlineFirst:!0,hasPublishedBooks:!0,annualVolume:11411,editor:{id:"441442",title:"Dr.",name:"Şükrü",middleName:null,surname:"Beydemir",slug:"sukru-beydemir",fullName:"Şükrü Beydemir",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003GsUoIQAV/Profile_Picture_1634557147521",biography:"Dr. Şükrü Beydemir obtained a BSc in Chemistry in 1995 from Yüzüncü Yıl University, MSc in Biochemistry in 1998, and PhD in Biochemistry in 2002 from Atatürk University, Turkey. He performed post-doctoral studies at Max-Planck Institute, Germany, and University of Florence, Italy in addition to making several scientific visits abroad. He currently works as a Full Professor of Biochemistry in the Faculty of Pharmacy, Anadolu University, Turkey. Dr. Beydemir has published over a hundred scientific papers spanning protein biochemistry, enzymology and medicinal chemistry, reviews, book chapters and presented several conferences to scientists worldwide. He has received numerous publication awards from various international scientific councils. He serves in the Editorial Board of several international journals. Dr. Beydemir is also Rector of Bilecik Şeyh Edebali University, Turkey.",institutionString:null,institution:{name:"Anadolu University",institutionURL:null,country:{name:"Turkey"}}},editorTwo:{id:"13652",title:"Prof.",name:"Deniz",middleName:null,surname:"Ekinci",slug:"deniz-ekinci",fullName:"Deniz Ekinci",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYLT1QAO/Profile_Picture_1634557223079",biography:"Dr. Deniz Ekinci obtained a BSc in Chemistry in 2004, MSc in Biochemistry in 2006, and PhD in Biochemistry in 2009 from Atatürk University, Turkey. He studied at Stetson University, USA, in 2007-2008 and at the Max Planck Institute of Molecular Cell Biology and Genetics, Germany, in 2009-2010. Dr. Ekinci currently works as a Full Professor of Biochemistry in the Faculty of Agriculture and is the Head of the Enzyme and Microbial Biotechnology Division, Ondokuz Mayıs University, Turkey. He is a member of the Turkish Biochemical Society, American Chemical Society, and German Genetics society. Dr. Ekinci published around ninety scientific papers, reviews and book chapters, and presented several conferences to scientists. He has received numerous publication awards from several scientific councils. Dr. Ekinci serves as the Editor in Chief of four international books and is involved in the Editorial Board of several international journals.",institutionString:null,institution:{name:"Ondokuz Mayıs University",institutionURL:null,country:{name:"Turkey"}}},editorThree:null,series:{id:"11",title:"Biochemistry",doi:"10.5772/intechopen.72877",issn:"2632-0983"},editorialBoard:[{id:"219081",title:"Dr.",name:"Abdulsamed",middleName:null,surname:"Kükürt",slug:"abdulsamed-kukurt",fullName:"Abdulsamed Kükürt",profilePictureURL:"https://mts.intechopen.com/storage/users/219081/images/system/219081.png",institutionString:null,institution:{name:"Kafkas University",institutionURL:null,country:{name:"Turkey"}}},{id:"241413",title:"Dr.",name:"Azhar",middleName:null,surname:"Rasul",slug:"azhar-rasul",fullName:"Azhar Rasul",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRT1oQAG/Profile_Picture_1635251978933",institutionString:null,institution:{name:"Government College University, Faisalabad",institutionURL:null,country:{name:"Pakistan"}}},{id:"178316",title:"Ph.D.",name:"Sergey",middleName:null,surname:"Sedykh",slug:"sergey-sedykh",fullName:"Sergey Sedykh",profilePictureURL:"https://mts.intechopen.com/storage/users/178316/images/system/178316.jfif",institutionString:null,institution:{name:"Novosibirsk State University",institutionURL:null,country:{name:"Russia"}}}]},onlineFirstChapters:{paginationCount:10,paginationItems:[{id:"82196",title:"Multi-Features Assisted Age Invariant Face Recognition and Retrieval Using CNN with Scale Invariant Heat Kernel Signature",doi:"10.5772/intechopen.104944",signatures:"Kamarajugadda Kishore Kumar and Movva Pavani",slug:"multi-features-assisted-age-invariant-face-recognition-and-retrieval-using-cnn-with-scale-invariant-",totalDownloads:6,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Pattern Recognition - New Insights",coverURL:"https://cdn.intechopen.com/books/images_new/11442.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}},{id:"82063",title:"Evaluating Similarities and Differences between Machine Learning and Traditional Statistical Modeling in Healthcare Analytics",doi:"10.5772/intechopen.105116",signatures:"Michele Bennett, Ewa J. 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