Specific thermal conductivity for different materials [5, 6].
\\n\\n
These books synthesize perspectives of renowned scientists from the world’s most prestigious institutions - from Fukushima Renewable Energy Institute in Japan to Stanford University in the United States, including Columbia University (US), University of Sidney (AU), University of Miami (USA), Cardiff University (UK), and many others.
\\n\\nThis collaboration embodied the true essence of Open Access by simplifying the approach to OA publishing for Academic editors and authors who contributed their research and allowed the new research to be made available free and open to anyone anywhere in the world.
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\n\nInitially, the partnership supported engineering research, but it soon grew to include physical and life sciences, attracting more researchers to the advantages of Open Access publishing.
\n\n\n\nThese books synthesize perspectives of renowned scientists from the world’s most prestigious institutions - from Fukushima Renewable Energy Institute in Japan to Stanford University in the United States, including Columbia University (US), University of Sidney (AU), University of Miami (USA), Cardiff University (UK), and many others.
\n\nThis collaboration embodied the true essence of Open Access by simplifying the approach to OA publishing for Academic editors and authors who contributed their research and allowed the new research to be made available free and open to anyone anywhere in the world.
\n\nTo celebrate the 50 books published, we have gathered them at one location - just one click away, so that you can easily browse the subjects of your interest, download the content directly, share it or read online.
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This book provides a comprehensive overview of the various types of muscular dystrophies, genes associated with each subtype, disease diagnosis, management as well as available treatment options. Though each different type and subtype of muscular dystrophy is associated with a different causative gene, the majority of them have overlapping clinical presentations, making molecular diagnosis inevitable for both disease diagnosis as well as patient management. This book discusses the currently available diagnostic approaches that have revolutionized clinical research. Pathophysiology of the different muscular dystrophies, multifaceted functions of the involved genes as well as efforts towards diagnosis and effective patient management, are also discussed. Adding value to the book are the included reports on ongoing studies that show a promise for future therapeutic strategies.",isbn:null,printIsbn:"978-953-51-0603-6",pdfIsbn:"978-953-51-6994-9",doi:"10.5772/1242",price:159,priceEur:175,priceUsd:205,slug:"muscular-dystrophy",numberOfPages:556,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"d6d8a96e17938c02e9611481a3b4bff8",bookSignature:"Madhuri Hegde\tand Arunkanth Ankala",publishedDate:"May 9th 2012",coverURL:"https://cdn.intechopen.com/books/images_new/734.jpg",numberOfDownloads:83523,numberOfWosCitations:39,numberOfCrossrefCitations:24,numberOfCrossrefCitationsByBook:3,numberOfDimensionsCitations:55,numberOfDimensionsCitationsByBook:3,hasAltmetrics:0,numberOfTotalCitations:118,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"March 8th 2011",dateEndSecondStepPublish:"April 5th 2011",dateEndThirdStepPublish:"August 10th 2011",dateEndFourthStepPublish:"September 9th 2011",dateEndFifthStepPublish:"January 7th 2012",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"87795",title:"Dr.",name:"Madhuri",middleName:null,surname:"Hegde",slug:"madhuri-hegde",fullName:"Madhuri Hegde",profilePictureURL:"https://mts.intechopen.com/storage/users/87795/images/2548_n.png",biography:"Dr. Hegde is an Associate Professor/ Scientific Director at Emory Genetics Laboratory in the Department of Human Genetics. 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Later, he moved on to perform post-doctoral studies at Emory University School of Medicine in the department of Human Genetics. The primary focus of his clinical research work has been the elucidation of mechanisms underpinning the high frequency of intragenic deletions and duplications in human DMD gene causing Duchenne Muscular Dystrophy. His broader research interest has been the discovery of new disease causing genes associated with different muscular dystrophies especially congenital muscular dystrophies and limb-girdle muscular dystrophies. 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Heat exchangers are used to transfer heat energy from one to another medium without intermixing them. There are different types available like plate, bundled tube or rotary heat exchangers. Figure 1 shows an example of a conventional plate heat exchanger.
Setup of a conventional plate heat exchanger [
In addition, heat exchangers also differ in their working principle (counterflow, direct flow, or cross flow) and can consist of differently shaped plates or tubes with, for example, smooth, buckled, or rippled surfaces. A typical wall thickness reaches from 0.4 to 2.5 mm and is mainly designed to withstand blockage, corrosion, active pressure, or abrasive media. Such heat exchangers are very cost-effective.
In conventional heat exchangers, a lot of restrictions and disadvantages exist, concerning the realizable geometry, the operating temperature, as well as the manufacturing costs:
Heat exchanger manufactured by the combination of different planar parts is limited in the realizable design and compactness (the ratio between heat exchanging surface and total volume).
The assembly of the different parts can result in assembly failures.
The realization of mechanical and fluidic interfaces is very challenging (often, the cross-flow principle is realized instead of the superiorly counterflow principle because of the feeding system for the different fluid channels).
The joining of the different parts is often realized by brazing. But the brazing material limits the operating temperature, and the brazing process can result in leakage.
Because of the used standardized geometries for the parts as well as the whole heat exchanger components, their outer geometry can hardly be individualized. Furthermore, no adjustment of the outer geometry on the shape of the surrounding system can be realized.
Some examples for ceramic-based heat exchangers for high temperature or high corrosive or abrasion applications exist, but their design is limited because of the ceramic shaping and finishing technologies. Furthermore, the operation temperature is limited because of the needed joining additives (e.g., solders or brazes) for the different ceramic parts.
Additive manufacturing (AM) is a new class of manufacturing technologies, which has been developed for polymers, metals, and ceramics during the last three decades and keeps evolving. Based on computer-aided design (CAD) files in 3D, typically a layer-wise manufacturing process follows, which allows the realization of component designs as well as inner and outer geometries which were previously regarded as not producible. Concerning the manufacturing of heat exchanger, AM technologies open the door to overcome all of the restrictions mentioned above:
The manufacturing of the heat exchanger as one component with integrated mechanical and fluidic interfaces becomes possible.
No joining steps are needed, and the same properties are available in the whole component.
Very complex designs can be realized, and the ratio between the heat exchanging surfaces to the total volume of the heat exchanger can be increased significantly. The increased performance allows the miniaturization of the heat exchanger.
The adjustment of the outer geometry becomes possible, and the required volume for the implementation of heat exchanger and the surrounding system can be decreased.
AM of ceramics opens the door for complex heat exchangers for demanding applications concerning operation temperature, abrasion, or corrosion.
Thus, heat exchangers seem to be very interesting for AM while prices are falling especially for AM of metal components [3]. Also, an integrated manufacturing process for heat exchangers seems to be positive on their pressure resistance and against leakage. Today, only a few designs are described or commercially available. EOS and 3TRPD have designed a heat exchanger, which was manufactured with laser beam melting (Figure 2). Unfortunately, they have not published any performance data for comparison.
Additively manufactured heat exchanger by EOS and 3TRPD [
Furthermore, at Fraunhofer IFAM, a counterflow heat exchanger was developed to improve the efficiency of a micro-gas turbine system (Figure 3). In this case study, the hot exhaust gas should heat up the inflowing cold air to improve the overall combustion efficiency of the system. The heat exchanger was particularly designed for laser beam melting, so there was no conventional way to manufacture the part. The heat exchanger combines 18 layers of channels in the limited design space. Furthermore, the complex inner channels were designed in a wave shape combined with a very small spacing to each other in order to maximize the surface for heat transfer (Figure 3). With the special design for laser beam melting, it was possible to reduce the required time and costs for postprocessing. It was only necessary to machine the inlet and outlet at the side toward the build platform after the LBM process [C4].
Counterflow heat exchanger manufactured by LBM; left: manufactured component [
But still, a lot of challenges exist, which have to be overcome, to allow the AM of high-performance heat exchanger.
Design stage:
designing and dimensioning of the heat exchanger;
generation of the CAD files;
modeling and simulation of the fluid flow and heat flux;
providing software tools for the different tasks, coupling, and automatization of all tasks.
Manufacturing stage:
enhancement of the material portfolios for the different AM technologies;
increasing productivity (higher building speed, larger building space with more components manufactured simultaneously, less reject rate) will result in decreasing manufacturing costs.
To overcome the current restrictions, we are working on all links of the process chain. In this chapter, we want to introduce different AM technologies for metals (Laser beam Melting—LBM) and ceramics (Fused Filament Fabrication—FFF and Lithography-based Ceramic Manufacturing—LCM) as well as two different approaches for designing and creating the CAD files, one based on conventional software tools and one based on mathematical algorithms. In addition, the specification of the operation conditions of a solid oxide fuel cell system with an operation temperature of 850°C and higher will exemplarily illustrate the requirements for heat exchangers suitable for high-temperature applications and will justify the need for AM of high-temperature materials like ceramics.
For additively manufactured heat exchangers, a high heat exchange capacity is essential. It is represented by the heat flow, which can be calculated from the thermal conductivity
Material | Thermal conductivity |
---|---|
Silver | 429 |
Copper | 401 |
Aluminum | 237 |
High alloyed steel | ∼20 |
Low alloyed steel | ∼30 |
Usually, the temperature gradient
In this work, principle insights into the design of structures with a high heat exchange capability and coincident low pressure drop shall be given. Therefore, simulation of the flow is inevitable, and the structures were designed using CAD tools. The aim is to obtain a structure, which can be individualized at its outer geometry and optimizes the flow problems inside of the structure.
On the basis of the constraints explained before, basic sketches were developed and compared on its contour length of all the channels that will be involved in the heat transfer. To enhance the performance of the heat exchanger, the aim is to maximize the surface for the heat transfer. Therefore, the contour length of the channels is maximized in each evolution of the sketches by retaining the hydraulic diameter. Basic sketches were made and afterwards extruded in height with a helical-shaped structure for generating a longer streamline and for maximizing the heat transfer area. All in all, seven basic sketches were defined with nine resulting structures, as shown in Figure 4. Structures 1 and 2 show a simple geometry, which could also be produced with conventional manufacturing processes. Structures 3–5 are very complicated in terms of connecting geometries. Structures 6.1 and 6.2 are highly optimized for production with straight walls which can be efficiently produced with LBM with special slicer options. At last, structures 7.1 and 7.2 are optimized for production and fluid flow by using special slicer options and not having sharp edges like structures 6.1 and 6.2 which lead to a higher pressure drop.
Different designs of inner structures for heat transfer.
A comparison of the geometrical and heat flow characteristics of these structures is given in Table 2. Also, the structures show a surface roughness as build. This roughness is assumed to be the same value for all side surfaces since they are all in the same build direction (same as the orientation of the pictures).
Compactness | Heat flow | Performance per volume | Pressure drop [Pa] | |
---|---|---|---|---|
1 | 267 | 270 | 38.20 | 0.05 |
2 | 243 | 170 | 24.05 | 0.06 |
3 | 664 | 200 | 28.29 | 0.06 |
4 | 651 | 350 | 49.51 | 0.50 |
5 | 1576 | 420 | 59.42 | 0.15 |
6.1 | 1471 | 520 | 65.47 | 0.10 |
6.2 | 550 | 0.20 | ||
7.1 | 1264 | 750 | 50.71 | |
7.2 | 1246 | 60.86 |
Simulation results for the different designed structures (compactness, heat flow, performance per volume and pressure drop; possible choice highlighted).
As stated above, connecting structures for fluid guidance inside the heat exchanging structure are important, but rather complex and difficult to design. As a first attempt for structures 5 and 6.2, connecting structures are shown in Figure 5, which were derived from biomimetic role models like fennel.
Exemplary connecting structures for designed structures 5 and 6.2.
To avoid such a complexity of the connecting structures and at the same time to enable the engineer to model them economically, a new approach was chosen. The design process now starts with the connecting structures, and the inner geometry is optimized afterwards. The design ideas were adopted from nature, too. Some possible basic structures are shown in Figure 6. The purpose of these structures is to transform a round connector with a 6-mm diameter to any amount of complex-shaped inner structures like tubes. In addition, the flow has to be equally distributed in all inner tubes, and heat transfer should also start within the connecting structure to minimize losses. Certainly, manufacturability has to be guaranteed as well by allowing a minimum angle of 45° to the building plane. For the same reason, gaps inside the structures have to be avoided, and the connecting structures have to be as narrow as possible.
Sampled possible structures for connecting geometries adopted from nature.
It is obvious that from these connecting structures, such immersed structures like those shown in Figure 4 (structures 6 and 7) cannot be accessed. This means that ideally nestable inner structures are preferred, which can be enveloped with one larger outer channel to gain a tube-in-tube-like design known from conventional heat exchangers.
Designing the inner structures, which are applicable to the previous connecting structures, is the next step. The profile shape may not be too complex due to terms of a steady connection to connecting structures. Furthermore, analytical calculation cannot be used for dimensioning these structures since they should all have the same hydraulic diameter. Therefore, fluid simulation was used for dimensioning. To validate these findings, experimental parameter evaluation should be conducted in further investigations. In Figure 7, some possible designed inner structures are compared. Herein, the lowest pressure drop per performance as indicating value was used to choose the optimal inner structure. These profiles are based on mathematical algorithms after Sierpinski (left profile) and Hilpert (right profile).
Comparison between inner structures with the same hydraulic diameter and optimal designs selected using fluid simulation.
Furthermore, the heat exchanging volume has to be filled with the inner structures using optimal arrangement options to fill the volume using curves, planes, or lines.
For combining the presented structures to a whole heat exchanger, a connecting structure has to be chosen and specified. In Figure 8, the possible structures emerged from biomimetic structures of Figure 3 are preselected in terms of producibility, compactness, and capability. The final selection was done by simulating the connecting structures with CFD using Ansys CFX to gain a uniform flow distribution over all profiles and minimum losses in flow distribution.
Selection of an optimal connecting structure.
Finally, three different complete heat exchanging structures were designed for comparison and to gain an optimal structure. The structures were combined to a whole exchanger geometry, and the capability of the models was simulated as shown in Figure 9.
Whole heat exchanger structures and flow in inner and outer channels.
As depicted, a uniform flow distribution can be achieved in the inner flow. The outer flow, however, shows a highly turbulent and uneven distribution especially in designs 2 and 3, leading to a high pressure drop. The obtained values from these structures are depicted in Table 3. The different values for design no. 1 are based on different lengths of the inner structure (50, 100, and 150 mm).
1 | 2 | 3 | |
---|---|---|---|
Compactness [m2/m3] | 736–1291– | 735 | 1161 |
Heat flow | 3465–6202– | 4482 | 6985 |
Capacity per volume | 376– | 139 | 272 |
Pressure drop | 1.87–1.95–2.50 |
Calculated values for designed heat exchangers (outstanding values highlighted).
It can be seen that the compactness is highly dependent on the length of the structure (design no. 1) because the influence of connecting structures decreases with an increasing length. With this example, a good scalability with different performances can be achieved, especially in terms of individualization. All in all, individualized and complex-shaped heat exchanging structures can be obtained for optimized production with additive manufacturing. But still, optimization has to be done to increase the performance and to lower the pressure drop. Also, experimental validation of the simulation has to be carried out even since the convergence in simulation was not satisfying.
In the following section, a new approach to generate efficient design structures for heat exchangers is presented. This new approach is one of the main topics of the instaf project.
Fractal macrostructures are used to generate a large inner surface, which implicates a better energy transfer between the heat-exchanging fluids. The creation of microstructures with roughness (with respect to the process-based roughness of AM), induced by partial Brownian motions, leads to turbulences. This raises the performance even more.
Two irreconcilable goals define the design scope. On the one hand, the surface for heat exchanging should be maximal and the fluids should remain in the heat exchanger as long as possible. But on the other hand, the restrictions concerning the manufacturing process (e.g., minimal wall thickness, resolution, waiver of support structures, etc.) and the operation as heat exchanger (e.g., pressure drop, mechanical strength, etc.) have to be considered as well.
To generate a maximum heat exchange surface, the so-called fractals were studied. Fractals are inspired by nature and are a branch of research essentially introduced to mathematics by Benoit Mandelbrot [7]. Stochastic fractals can be found in lung alveoli and other breathing organs or in the capillaries in the fin of whales with a heat- and energy-saving component.
For the design of the macrostructures, our special focus lies on the construction of space-filling curves, which belong to the group of FASS curves. The acronym FASS stands for space-filling, self-avoiding, simple, and self-similar. This class of curves traverses every vertex of a polygonal grid so that every point is reached once. Because they are not allowed to cut themselves, they separate to areas perfectly and are therefore well suited for the construction of heat exchangers.
A Lindenmayer system (L-system) was used to generate the curves. An L-system is a way to describe a repetitive structure with a small number of rules. It is a character-based rewriting system, which consists of constants. These are representing draw commands and variables, which are replaced in every iteration step through a replacement rule. In Figure 10, the system is visualized by means of the Hilbert curve with the variables X, Y, the constants F (straight line), −(clockwise rotation), and +(counterclockwise rotation) with a starting value of X. The rules are X → +YF − XFX − FY+ and Y → −XF + YFY + FX−.
A visualization of the Lindenmayer-code demonstrated by means of the Hilbert Curve.
A process was developed to generate a large number of different curves with a small number of basic motifs considering only 2 × 2- and 3 × 3 grids in order to investigate the best properties. There are four ways to traverse through these grids, which leads to seven basic motifs, paying attention to reflection. Every motif can also be used as a mapping structure. Therefore, it represents the connecting pieces of the following iteration step. Figure 11 shows a curve where the basic motif of a Peano curve (represented by the purple lines) and the mapping structure of the Hilbert curve (represented by the green lines) are combined. The ratio of curve length to the surface area or in higher dimension from surface to volume is always the same for the same grid size. Therefore, the criteria of evaluation are turbulences in flow and the velocity of the fluids so as the basic conditions of the used AM technology.
One possible combination of the motifs.
To construct a three-dimensional structure, successive iteration steps of a curve were placed in a predefined distance. They were combined with an NURBS-based (non-uniform rational basic spline) surface. The surface is lofted over the curves and defines a closed structure in combination with the outer skin. Figure 12 illustrates the process for the first four iteration steps of a Peano curve. Since separate areas should always be consistent, the offset must be adjusted. As the curve gets longer in each iteration step, the selected offset also decreases. Figure 13 demonstrates the result, visualizing one of the two separate liquids.
The first four iteration steps of the Peano curve. They lead to a feeding structure for which we combined the four layers with an NURBS-based surface.
Rendering of the dispersion of one fluid in a feeding structure designed with a Peano curve down to the fourth iteration step.
In the illustrated structure, the thickness of the partition wall decreases from 4.5 to 0.2 mm, which corresponds to a factor of 22.5. The length of the partition wall increases in the same range, simultaneously. In addition, the extrusion of the final geometry results in a heat exchanger with a compactness of about 3000 m2/m3, which can be operated as a counterflow heat exchanger. The structure was created using the CAD software Rhinoceros 3D. In Figure 13, some renderings of the fluid paths are shown.
Another structure for a heat exchanger is presented in Figure 14. In this case, a curve was chosen, which can be closed. It can be used without an outer wrapping, and this is why it could also be used as an immersion heater. For a better view into the internal structure, it is presented cut open. The outer structure could be represented by a cuboid. The curves are constructed with the end points of the elements as control points. This makes the curves even longer and smoothens them evenly.
Alternative structure as a concept for a heat exchanger. From left to right: a 5/8 cutout to show the inner structure; the whole component (lying); the curves used for designing the structure.
The LBM process has a lot of different specific names such as LaserCUSING®, selective laser melting (SLM®), direct metal laser sintering (DMLS®), and direct metal printing, to name only a few. All of these names describe the powder bed-based laser process, where a part is manufactured by means of thin layers of a powder material, which are applied by a scraper and molten selectively by laser energy.
The digital process chain begins with the 3D CAD file (*.stl) of the part, which has to be manufactured. This file is transferred to a software program where the support generation and the positioning in the building chamber of the machine are done. Afterwards, the so-called build job is sliced into layers of 20–100 μm, dependent on the material and the laser parameters and carried over to the machine [8]. A principle schematic of an LBM machine is shown in Figure 15.
A principle schematic of an LBM machine.
To avoid oxidation, the process itself as well as the preparation and postprocessing of the powder has to be done under inert gas atmosphere. Overhanging structures have to be supported by supporting structures which have to be produced as well for stabilizing the model and to improve the dissipation of heat below these geometries [9].
The process is suitable for producing individual and highly complex parts and hollow structures such as topology-optimized components as shown in Figure 16. Also, very fine structures like lattice structures can be produced, which is also depicted therein.
Complexly designed skateboard trunk manufactured with LBM.
After the manufacturing process, the part is separated from the build platform, and the support structure is removed. To adjust the mechanical properties of the part, a heat treatment can be applied. Other conventional methods like machining or polishing can be utilized to achieve a better surface quality, dependent on the requirements.
Depending on slicing and scanning strategy, the quality of manufactured parts can widely vary, concerning cracks, pores, residual stresses, distortions, tightness, and fatigue properties. However, LBM processes are becoming relevant in series and tool production, while the reliability of such manufacturing technologies and the resulting component quality are of high importance [10].
At Fraunhofer IWU, a counterflow heat exchanger was specially developed for the LBM process with the focus on a low pressure drop, flexible, as well as compact design (Figure 17). To reduce the pressure drop and validate the best version, a fluid analysis was executed on each design. To get a maximum heat transfer and integrated insulation to the outer atmosphere, the cold channel is wrapped around the hot channel within the heat exchanger (heat exchange surface/volume: 405 m2/m3; performance: 36.2 W/cm3). Also, the wall between the cold and the hot channel system is reduced to a minimum of 0.8 mm to enhance the heat transfer. As a result of the special design for the laser beam melting process, no support structure and postprocessing were needed to manufacture the heat exchanger. The pressure drop (0.20 bar) as well as heat flow (1.3 kW) of the final design was calculated with flow simulations using Ansys CFX. The propagated heat exchanger shows one imperfection since it produces a thermal short circuit in the area of the connection geometries.
A counterflow heat exchanger with a low pressure drop and compact, flexible design.
The next step will be to avoid the thermal short circuit and to implement the designs described before within the metal heat exchanger in consideration of the general conditions of LBM.
The research and development of new technologies is sometimes limited by the availability of commercial peripheral components. These new technologies change the requirements on state-of-the-art products.
One of those new technologies is the fuel cell. A fuel cell has the benefit of directly converting chemical energy to electrical power without the conventional process steps in between. This reduces the losses on the whole conversion path. Fuel cells are available in various types with different characteristics (Figure 5). The low-temperature fuel cells are mostly used for portable or mobile applications because of the high power density, for example, as a battery charger for mobile devices. High-temperature fuel cells are typically used for stationary applications like power and heat supply for households and facilities [11].
Most of the low-temperature fuel cells like the PEFC (polymer electrolyte fuel cell) need pure hydrogen or at least “clean” fuel. Not allowed substances like carbon monoxide have to be filtered before operation. The high-temperature solid oxide fuel cell (SOFC) is designed to generate electrical and/or thermal power with a high efficiency based on the usage of worldwide available fuels such as natural gas and LPG (liquefied petroleum gas). These fuels are reformed to a gas mixture of hydrogen and carbon monoxide directly inside the SOFC System. In contrast to most of the common fuel cells, an SOFC can also generate electrical power by carbon monoxide conversion (Figure 18).
An overview of fuel cell technologies, including temperatures, reactions, and allowed and not allowed chemical components.
In order to achieve this high efficiency, high temperatures are necessary. The standard operation temperature of an SOFC is above 700°C. As mentioned before, these systems have different gas processing steps included [12], which is illustrated in Figure 19 as well:
the reforming process (REF),
the conversion of hydrogen and carbon monoxide to water and carbon dioxide inside the fuel cell itself, and
furthermore, a postprocessing step typically called tail gas oxidation (TOX).
An overview of SOFC system with integrated components.
The fuel cell itself cannot convert 100% of the fuel for various reasons, which will not be further explained in this context but are discussed in [13]. The rest of the fuel has to be oxidized in order to avoid emission of hydrogen and carbon monoxide. This kind of reaction leads to temperatures of 900°C and higher.
The different reactors REF and SOFC have different requirements on heat treatment. The REF needs heat for a high efficiency. The SOFC receives the reaction products of the REF with a temperature of approx. 800°C on the anode side. On the cathode side, typically air is used. In order to avoid thermal stress and to realize the necessary operating temperature of the SOFC, this air has to be preheated.
The realization of the heat treatment requires a rather complex packaging of all components. This packaging is realized in the HotBox. The efficiency of all steps is based on a minimum of losses inside the system. Therefore, an adapted heat exchange from TOX to air and an overall packaging for optimal heat management are necessary.
Commercial heat exchangers are not aware of these requirements. The used materials and/or joining technologies cannot handle this high temperature, and due to the standard design on commercial heat exchangers, especially plate heat exchangers, the integration of such components inside the HotBox is complicated and space-consuming.
In order to achieve the highest possible efficiency of such systems, heat exchangers that combine an adaptable design with high-temperature resistance are indispensable.
Fused filament fabrication (FFF) is a thermoplastic AM technology which bases on nearly endless filaments which are used as a semi-finished products and which are melted and deposited under a heated nozzle. To generate ceramic components, particle-filled filaments are used to manufacture the so-called green bodies additively [14]. These green bodies have to be debinded, to remove all organic materials, and sintered to densify the microstructure and to achieve the typical ceramic properties. The benefits of this AM technology are the high productivity and the large building space of the available devices. The existing challenges of FFF of ceramic components are the development of highly particle-filled filaments and the defect-free debinding and sintering of the components [14].
SiC filaments were developed to allow the AM of large volume SiC heat exchanger, which can be used for operation temperatures of 1000°C and higher. Figure 20 shows some ceramic test components and demonstrators manufactured by FFF.
Different ceramic demonstrators additively manufactured by FFF; left: SiC (green state); right: various ceramics (sintered state).
The next steps will be the investigation of FFF with SiC filaments concerning the realizable geometries and the tightness of the sintered structures.
The LCM technology was developed and commercialized by Lithoz GmbH, Austria [15]. As a special kind of stereolithography, free radical polymerization of the binder system takes place with light of a defined wavelength, causing the suspension to solidify. Via a DLP module, the suspension is selectively irradiated with a blue light, whereby all areas to be cross-linked on a given plane are exposed at the same time. The ceramic particles dispersed in the suspensions are fixed in the solid polymer matrix (green body). A final debinding and sintering step is necessary for this AM technologies for ceramics, as well [16].
The LCM technology impresses with a very high resolution (wall thickness down to 100 μm possible) [16] and very good surface properties (Ra < 1 μm) of the sintered components. The challenges are the small building area ((76 ×43 × 150) mm3) and the low productivity, both resulting in relatively high manufacturing costs as well as the cleaning and the debinding process for the green components [17].
Both FASS structures which were described before were additively manufactured via LCM technology and Al2O3 suspension of Lithoz. The sintering occurred at 1650°C which allows operation temperatures of significantly more than 1000°C. Figure 21 shows the feeding structure at the sintered state (left) and the alternative heat exchanger structure (green state).
The FASS structures as ceramic component in the sintered (left; 35 × 35 × 35 mm3) or green state (right), additively manufactured via LCM technology.
The rapid development of AM technologies enables a radical paradigm shift in the construction of heat exchangers. In place of a layout limited to the use of planar or tubular starting materials, heat exchangers can now be optimized, reflecting their function and application in a particular environment. The investigations show the potential of the technologies concerning increasing heat exchanging surface and compactness as well as the designing of the fluidic systems. The AM of ceramics will pave the way to realize heat exchanger for operation temperatures highly above 1000°C.
The new approach for designing can also be used for bent structures. They provide more potential than the straight heat exchangers and open a wider field of possible technical applications. A possible, curved geometry is shown in Figure 22.
A computer-aided designed curved heat exchanger. Its geometry bases on FASS.
To increase the inner surface even more, rough surfaces, which induce beneficial turbulences, can be generated by modeling partial Brownian motion.
The authors would like to thank the German Federal Ministry of Education and Research (BMBF) for funding the project “
There are no conflicts of interest and nothing else to declare.
Visual object tracking (VOT), commonly referred to as target tracking, is an open problem in computer vision; this is due to a broad range of possible applications and potential tracking challenges. Thus, it has been divided into sub-challenges according to several factors, which include: the number of targets of interest, the number of cameras, the type of data (i.e., medical, depth, thermal, or RGB images), static or moving camera, offline or online (real-time) processing.
Visual object tracking is the process of estimating and locating a target over time in a video sequence and assigning a consistent label to the tracked object across each video sequence frame. VOT algorithms have been utilized as a building block in more complex applications of computer vision such as traffic flow monitoring [1], human-machine interaction [2], medical systems [3], intelligent cinematography [4], automated surveillance [5], autonomous social navigation [6] and activity recognition [7]. Real-time visual target tracking is the process of locating and associating the target of interest in consecutive video frames while the action is taking place in real-time. Real-time visual target tracking plays an inevitable role in time-sensitive applications such as autonomous mobile robot control to keep track of the target of interest while the viewpoint is changing due to the movement of the target or the robot. In such a scenario, the tracking algorithm must be accurate and fast enough to detect sudden changes in the observed environment and act accordingly to prevent losing track of the quickly moving target of interest.
Since the start of the Visual-Object-Tracking(VOT) Real-time challenge in 2017, Siamese network-based tracking algorithms have achieved top performance and won in the VOT real-time challenge with a considerable margin over the rest of the trackers. Nearly all top ten trackers applied the siamese network, and also the winners. The dominant methodology in real-time tracking, therefore, appears to be associated. A siamese network aims to learn a similarity function. It has a Y-shaped network architecture that takes two input images and returns similarity as an output. Siamese networks are utilized to compare the similarity between the template and the candidate images to determine if the two input images have an identical pattern(similarity). In the past few years, a series of state-of-the-art siamese-based trackers have been proposed, and all of them utilize embedded features by employing CNN to compute similarity and produce various types of output, such as similarity score(probability measure), response map(two-dimensional similarity score map), and bounding box location of the target.
Luca Bertinetto et al. [8] proposed Siamese fully convolutional network (SiameseFC) to addresses the broad similarity learning between a target image and search image, as presented in Figure 1. According to the VOT winner rules, the winning real-time tracker of the VOT2017 [9] was SiamFC. SiamFC applies a fully-convolutional siamese network trained offline to locate an exemplar (template) image inside a larger search image Figure 1. The network is fully convolutional w.r.t search image: dense and efficient sliding window evaluation is achieved with a bilinear layer that computes the cross-correlation of two inputs. The deep convolutional network is trained offline with” ILSVRC VID” dataset [10] to address a general similarity learning problem and maximize target discrimination power. During tracking, SiamFC takes two images and infers a response map using the learned similarity function. The new target position is determined at the maximum value on the response map, where it depicts a maximum similarity Figure 1. As improvement in Siamese based tracking methods, Qiang Wang et al. [11] proposed SiamMask aiming to improve the ability of the SiamFC network to differentiate between the background and the foreground by augmenting their loss with a binary segmentation task. SiamMask is a depth-wise cross-correlation operation performed on a channel-by-channel basis, to keep the number of channels unchanged. The result of the depth-with cross-correlation indicated as RoW (response of candidate window), then distributed into three branches, respectively segmentation, regression, and classification branches Figure 2.
Fully-convolutional Siamese architecture. The output is a scalar-valued score map whose dimension depends on the size of the search image [
An illustration of SiamMask with three branches, respectively segmentation, regression, and classification branches; where
Seven of the top ten realtime trackers (SiamMargin [12], SiamDWST [13], SiamMask [11], SiamRPNpp [14], SPM [15] and SiamCRF-RT) are based on siamese correlation combined with bounding box regression. In contrast, the top performers of the VOT2019 Real-time challenge are from the class of classical siamese correlation trackers, and siamese trackers with region proposals [16]. Although these methods showed a significant improvement, there was small attention on how to carefully update the template of the target as time goes from the start of the tracking. In all top performers, the target template is initialized in the first frame and then kept fixed during the tracking process. However, diverse variations regarding the target usually occur in the process of tracking, i.e., camera orientation, illumination change, self-rotation, self-deformation, scale, and appearance change. Thus, failing to update the target template leads to the early failure of the tracker. In such scenarios, it is crucial to adapt the target template model to the current target appearance. In addition to this, most of the tracking methods fail when motion-blurred frames or frames with low-resolution appear in the video sequence, as depicted in Figures 3 and 4. We believe that this case arguably arises from the complete lack of similar training samples. Therefore one must incorporate a data-augmentation strategy to consider both motion-blur and low-resolution during training to significantly increase the diversity of datasets available for training without actually gathering new data.
An example of SiamMask failure due to motion-blur, green and yellow bounding box indicates ground truth and predicted target respectively.
An example of SiamMask failure due to low resolution, green and yellow bounding box indicates ground truth and predicted target respectively.
The problem of establishing a correspondence between a single target in consecutive frames can be affected by factors such as initializing a track, updating it robustly, and ending the track. The tracking algorithm receives an input frame from the camera module and performs the visual tracking over a frame following a siamese network-based tracking approach. Since developing a new tracking algorithm from scratch is beyond the scope of this chapter, a state-of-the-art siamese-based tracking algorithm called siammask [11], one of the top performers in the VOT2019 real-time challenge, is used as a backbone of our tracking algorithm.
To mitigate the limitations associated with Siamese-based tracking methods. This section presents two improvements on top of the SiamMask implementation.
As mentioned in the introduction, the siamese-based tracker fails when motion-blurred frames or frames with low-resolution appear in the video sequence, as depicted in Figures 3 and 4. Therefore to address the problems, a tracking algorithm should incorporate a data-augmentation strategy to consider both motion-blur and low-resolution during training. Since data augmentation is a strategy that significantly increases the diversity of datasets available for training without actually gathering new data, it will require implementing the data augmentation techniques explained through the following sub-sections.
Kernel filters are a prevalent technique in image processing to blur images. These filters work by sliding an
An example of motion blurred frame (left image) generated from original frame (right image) using the developed data-augmentation for motion-blur technique.
We followed a Zhangyang Wang et al. [18] approach to generate a low-resolution dataset. During training, the original (High Resolution) images are first downscaled by
An illustrates on how the low-resolution data augmentation generation are performed (from (a) to (c)).
The target template update mechanism is an essential step, and its robustness has become a crucial factor influencing the quality of the tracking algorithm. To tackle this problem, more recent Siamese trackers [19, 20, 21] have implemented a simple linear update strategy using a running average with a constant learning rate. However, A simple linear update is often inadequate to cope with the changes needed and to generalize to all potentially encountered circumstances. Lichao Zhang et al. [22] proposes to replace the hand-crafted update function with a method that learns to update, using a convolutional neural network called
One can argue the importance of the original initial and supplementary updatable templates, which incorporate the up-to-date target information. To this end, we have incorporated a template updates strategy that utilizes both the initial template (ground truth template)
Overview on how the target similarity score (red) varies under different occlusion scenario during tracking process. The similarity score is indicated in red color in the top left of each frame, VOT2019 road dataset. Where blue: Ground truth, red: Tracking result.
Overview on how the target similarity score varies under different occlusion scenario during tracking process, VOT2019 girl dataset. Where blue: Ground truth, red: Tracking result.
Target template update strategy: Where T_G is the ground truth template, T_i is an updatable template,
In 2.2 the target template update strategy considers the target appearance only from the previous frame. However, in this section, we introduce an alternative template update strategy that considers both the target appearance from the previous frame and the target appearance in the future frame, which incorporates future information of the target appearance by updating the updatable template T_i described in 2.2. The template updating mechanism is shown in Figure 10. During online tracking, the template updating and the tracking procedure works as follows:
Tracking procedure on the next frame
Updatable template T_i is updated using the predicted target from the next frame to incorporate a piece of future information about the target.
Tracking procedure again on the current frame is applied using both the updated future target template T_i + 1 and the ground truth target template T_G.
Updating with a previous and a future template, where T_G is ground truth target template, T_i is previous target template and T_i + 1 is future target template. Where green: Ground truth template, yellow: Updatable template, blue: Tracking result.
First, a tracking procedure is applied using both the previous target template in T_i and the ground truth template T_G to perform tracking on the next frame. Then the updatable template T_i is updated using the predicted target on the next frame incorporating a piece of future information about the target. Finally, a tracking procedure is again applied to the current frame using both the updated future target template T_i + 1 and the ground truth template T_G.
The SiamMask implementation was trained using 4 Tesla V100 GPUs. In this experiment, only the refinement module of the mask branch is trained. The training process was carried out using COCO3 and Youtube-vos4 Datasets: The training was performed over ten epochs using mini-batches of 32 samples. The data augmentation techniques described in 2.1.1 and 2.1.2 were utilized for generating datasets with motion-blur and low-resolution, respectively.
During tracking, the tracking algorithm is evaluated once per frame. The output mask is selected from the location attaining the maximum score in the classification branch and creating an optimized bounding box. Finally, the highest scoring output of the box branch is used as a reference to crop the next search frame.
As object tracking has gotten significant attention in the last few decades, the number of publications on tracking-related problems has made it difficult to follow the developments in the field. One of the main reasons is that there was a lack of commonly accepted annotated datasets and standardized evaluation protocols that allowed an objective comparison of different tracking methods. To address this issue, the Visual Object Tracking (VOT) workshop was organized in association with ICCV20135. Researchers from the industry and academia were invited to participate in the first VOT2013 challenge, which was aimed at model-free single-object visual trackers. In contrast to related attempts in tracker benchmarking, the dataset is labeled per-frame by visual properties such as occlusion, motion change, illumination change, scale, and camera motion, offering a more systematic comparison of the trackers [23]. VOT focused on short-term tracking (no re-detection) until the VOT2017 challenge, where a new”real-time challenge” was introduced. In the Real-time challenge, the tracker constantly receives images at real-time speed. If the tracker does not respond after the new frame becomes available, the last bounding box from the previous frame is reported as the tracking result in the current frame.
The VOT challenges applies a reset-based methodology. Whenever a zero overlap between the predicted bounding box and the ground truth occurs, a failure is detected, and the tracker is re-initialized five frames after the failure. There are three primary metrics used to analyze the tracking performance in visual object tracking challenge benchmark: Accuracy (A), Robustness (R), and Expected Average Overlap (EAO) [9].
Accuracy is calculated as the average overlap between the predicted and ground truth bounding boxes during successful tracking periods [23]. The tracking accuracy at time-step t is defined as the overlap between the tracker predicted bounding box
Robustness measures how often the tracker loses/fails the target, i.e., a zero overlap between the predicted and the ground truth bounding boxes during tracking. The protocol specifies an overlap threshold to determine tracking failure. The number of failed tracked frames are then divided by the total number of frames, as depicted in Eq. (2):
Where
For the purpose of ranking tracking algorithms, it is better to have a single metric. Thus, in 2015 the VOT challenge introduced Expected Average Overlap (EAO), which combines both Accuracy and Robustness. EAO estimates the average overlap that a tracker is expected to achieve on a large collection of short-term sequences with the same visual properties as the given dataset.
The EAO metric can be found by calculating the average of
This first experiment is dedicated to evaluating the impact of the low-resolution data-augmentation technique. The data augmentation technique described in 2.1.2 was applied to generate datasets with low-resolution during the training process of the refinement module of the network.
The performance of the developed method: incorporating low-resolution datasets using data augmentation technique during training has been evaluated using the VOT evaluation metrics on the VOT2018, VOT2019 datasets. The overall Evaluation results are shown in Table 1.
VOT2018 | VOT2019 | ||||
---|---|---|---|---|---|
VOT Metrics | SiamMask | Ours | SiamMask | Ours | |
EAO | 0.380 | 0.280 | |||
Accuracy | 0.589 | 0.586 | |||
Robustness | 0.279 | 0.522 |
Comparison between SiamMask and the developed method (incorporating low-resolution data during training), under the VOT metric (EAO, Accuracy, Robustness) on VOT2018 (left) and VOT2019 (right), best results are marked in Bold.
The term
In Table 1, we compare our approach against the state-of-the-art SiamMask tracker on the VOT2018 and VOT2019 benchmarks, respectively. It can be clearly observed that the data augmentation technique for incorporating low-resolution datasets has contributed to robustness improvements. The tracker’s failure has decreased from 60 to 53 and from 104 to 93 in VOT2018 and VOT2019, respectively. Improvements are clearly shown especially in a video sequence with low-resolution, i.e.
Qualitative comparison between SiamMask and developed data-augmentation technique for incorporating low-resolution datasets during training. Where blue: Ground truth, red: Tracking result.
The results obtained in Table 1 confirm that the developed methodology significantly improved the overall performance of the tracker. This approach outperforms the original SiamMask achieving a relative gain of 2.6% and 0.4% in EAO on VOT2018 and VOT2019, respectively. Most significantly, a gain of around 3
As it is depicted in Figure 11, The data-augmentation for incorporating low-resolution datasets during training has contributed to enhancing the tracker robustness. Thus, the tracker becomes robust against low-resolution frames during inference in relative to the original SiamMask tracker.
In this experiment, the data-augmentation technique for incorporating motion-blurred datasets described in 2.1.1 was applied for generating datasets with motion-blur during the training process of the refinement module of the network.
The performance of the tracking algorithm incorporating the motion-blur data augmentation technique has been evaluated using the VOT evaluation metrics on the VOT2018, VOT2019 datasets. The Overall Evaluation results are shown in Table 2.
VOT2018 | VOT2019 | ||||
---|---|---|---|---|---|
VOT Metrics | SiamMask | Ours | SiamMask | Ours | |
EAO | 0.380 | 0.280 | |||
Accuracy | 0.609 | 0.610 | 0.610 | ||
Robustness | 0.279 | 0.522 |
Comparison between SiamMask and the developed method (incorporating motion-blurred dataset during training), under the VOT metric (EAO, accuracy, robustness) on VOT2018 (left) and VOT2019 (right).
The data augmentation technique for incorporating motion-blurred datasets has contributed to the overall enhancement of the tracker performance. They are clear improvements in terms of Robustness in multiple video sequences relative to SiamMask. From Table 2, it can be concluded that the data augmentation technique for incorporating motion-blurred datasets has contributed to the improvement in Robustness of the tracker, especially in a video sequence with a motion-blur, i.e.,
Figure 12 presents a visual comparison between SiamMask and the developed improvement incorporating motion-blurred datasets during training using data-augmentation. From Figure 12 it can be clearly observed that the data-augmentation for incorporating motion-blurred dataset during training has contributed to enhancing the tracker Robustness. Thus, the tracker has become robust against motion-blurred video frames during inference in relative to the original SiamMask tracker.
Qualitative comparison between SiamMask and developed data-augmentation technique: Incorporating motion-blurred datasets during training. Where blue: Ground truth, red: Tracking result.
When it comes to updating the target template, the question is how and when to update the target. The parameter
This set of experiments compares the effect of the target template updating strategy by varying the score threshold of
VOT-Metrics | |||||
---|---|---|---|---|---|
S | EAO | Accuracy | Robustness | FPS | |
0.65 | 0.377 | 0.602 | 0.267 | 57 | 25 |
0.7 | 0.371 | 0.602 | 0.267 | 57 | 27 |
0.75 | 0.385 | 0.600 | 0.248 | 53 | 28 |
0.8 | 0.387 | 0.603 | 0.258 | 55 | 31 |
0.85 | 0.388 | 0.243 | 52 | 32 | |
0.9 | 0.393 | 0.602 | 0.239 | 51 | 35 |
0.95 | 0.602 |
Determining the optimal score threshold (
VOT-metrics | |||||
---|---|---|---|---|---|
S | EAO | Accuracy | Robustness | FPS | |
0.65 | 0.276 | 0.598 | 0.497 | 99 | 25 |
0.7 | 0.278 | 0.601 | 0.497 | 99 | 26 |
0.75 | 0.278 | 0.601 | 0.497 | 99 | 27 |
0.8 | 0.278 | 0.601 | 0.497 | 99 | 27 |
0.85 | 0.274 | 0.601 | 0.512 | 102 | 32 |
0.9 | 0.278 | 0.600 | 0.512 | 102 | 36 |
0.95 |
Determining the optimal score threshold (
An illustration on the effect of the tracking performance, with a template update strategy by varying the score threshold
Visual illustration on how the target template update strategy decides whether to update the template or not based on the similarity score under different occlusion scenario during tracking process, VOT2019 girl dataset. Where blue: Ground truth, red: Tracking result.
Visual illustration on how the target template update strategy decides whether to update the template or not based on the similarity score under different occlusion scenario during tracking process, VOT2019 girl dataset. Where blue: Ground truth, red: Tracking result.
Figures 14 and 15 are an illustration of how the template update strategy decides when to update the updatable template. For instance in Figure 15a the target is not occluded; as a result the score is high, thus
Table 5 presents a comparison between no-update SiamMask and incorporating the developed template update strategy: it can be observed that a relative gain of 0.7% and 2.0% in Robustness has been achieved by incorporating template update strategy. Thus, the tracker has encountered less failure than the no-update SiamMask, decreasing from 60 to 58 and 104 to 100 in VOT2018 and VOT2019 benchmarks, respectively. The robustness of the tracker is the crucial element for applications such as automatic robotic cameras where there is no human assistance.
VOT2018 | VOT2019 | ||||
---|---|---|---|---|---|
SiamMask | Ours | SiamMask | Ours | ||
EAO | 0.380 | 0.351 | 0.280 | 0.268 | |
Accuracy | 0.609 | 0.593 | 0.610 | 0.593 | |
Robustness | 0.279 | 0.522 | |||
# Lost | 60 | 104 | |||
FPS | 44 | 40 | 44 | 40 |
Comparison between no-update SiamMask and incorporating target template update under VOT2018 (left) and VOT2019 (right) benchmarks.
This experiment dedicated to examine the strength and weakness of the” updating with a previous and future frame” template update strategy described in 2.2.1. As can be seen from Table 6, the method”updating with previous and a future template” has achieved a relative gain of around 0.7% and 2.5% in Robustness value w.r.t SiamMask in both VOT2018 and VOT2019 benchmark, respectively. This indicates that the”Updating with Previous and Future template” strategy has enhanced the tracker’s Robustness, which is the most crucial in automated tracking applications. However, this can not be used for real-time applications as the processing speed is very slow, around 12 FPS on a laptop equipped with NVIDIA GEFORCE GTX1060. The main computational burden on the tracker is related to the target template feature extraction network. Thus, the tracking algorithm processing speed becomes very slow when the target template is updated with the previous and future template, resulting in a poor FPS.
VOT2018 | VOT2019 | ||||
---|---|---|---|---|---|
SiamMask | Ours | SiamMask | Ours | ||
EAO | 0.380 | 0.357 | 0.280 | 0.274 | |
Accuracy | 0.609 | 0.597 | 0.610 | 0.597 | |
Robustness | 0.279 | 0.522 | |||
# Lost | 60 | 104 | |||
FPS | 12 | 12 |
Comparison between no-update SiamMask and incorporating target template updating with previous and future template on VOT2018 (left) and VOT2019 (right) benchmark.
This section compares our tracking framework called VPU_SiamM with other state-of-the-art trackers SiamRPN, SiamMask in the VOT2018 and SiamRPN++, SiamMask in VOT2019.
To take advantage of the incorporated improvements, a tracker named VPU_SiamM has been developed. VPU_SiamM has been trained based on the data augmentation technique incorporating both motion-blur and low-resolution, and during online inference, a target template update strategy is applied.
We have tested our VPU_SiamM tracker on the VOT2018 dataset in comparison with state-of-the-art methods. We compare with the top trackers SiamRPN (winner of the VOT2018 real-time challenge) and SiamMask among the top performer in the VOT2019 challenge. Our tracker obtained a significant relative gain of
VOT2018 | |||
---|---|---|---|
Tracker | EAO | Accuracy | Robustness |
SiamRPN [21] | 0.383 | 0.586 | 0.276 |
SiamMask [11] | 0.38 | 0.609 | 0.279 |
VPU_SiamM | 0.602 |
Comparison of our tracker VPU_SiamM with the state-of-the-art trackers SiamRPN and SiamMask in terms of expected average overlap (EAO), accuracy, and robustness (failure rate) on the VOT2018 benchmark.
Following previous VOT evaluation, we have evaluated our VPU_SiamM tracker on VOT2019 datasets, which contains 60 challenging testing sequences. As shown in Table 8, our VPU_SiamM also achieves the best tracking results on VOT2019 in EAO and Accuracy metrics compared to state-of-the-art trackers SiamMask and SiamRPN++. More specifically, our approach improves the EAO by around 1%.
VOT2019 | |||
---|---|---|---|
Tracker | EAO | Accuracy | Robustness |
SiamRPN++ [14] | 0.282 | 0.598 | 0.482 |
SiamMask [11] | 0.287 | 0.594 | |
VPU_SiamM | 0.482 |
Comparison of our tracker VPU_SiamM with the state-of-the-art trackers SiamRPN++ and SiamMask in terms of expected average overlap (EAO), accuracy, and robustness (failure rate) on the VOT2019 benchmark.
In this chapter, one of the state-of-the-art tracking algorithms based on siamese networks called SiamMask has been used as a backbone, and two improvements have been affixed, each addressing different aspects of the tracking task.
The developed data augmentation technique for incorporating low-resolution and motion-blur has been evaluated separately and jointly, achieving state-of-the-art results in the VOT2018 and VOT2019 benchmarks. From the evaluation results, it is clear to conclude that the data augmentation technique has played an essential role in improving the overall performance of the tracking algorithm. It has outperformed the SiamMask results in both VOT2018 and VOT2019 benchmarks. In contrast, among the three data augmentation techniques, the data augmentation technique for incorporating both motion-blur and low-resolution outperforms the rest in terms of EAO in VOT2018 and VOT2019 benchmarks. Nevertheless, the data-augmentation for incorporating only motion-blur has achieved a top performance according to the Accuracy metric in both VOT2018 and VOT2019 benchmarks. However, the Accuracy is less significant as it only considers the IOU during a successful tracking. According to the VOT ranking method, the EAO value is used to rank tracking methods. Therefore the data augmentation technique for incorporating both motion-blur and low-resolution is ranked top among the others. This indicates that the data-augmentation technique has contributed to the improvement of the overall tracker performance.
Comparable results on VOT2018 and VOT2019 benchmarks confirm that the robust target template update strategy that utilizes both the initial ground truth template and a supplementary updatable template and avoiding template updates during severe occlusion can significantly improve the tracker’s performance with respect to SiamMask results while running at 41 FPS.
A tracker named VPU_SiamM was trained based on the presented approach, and it was ranked
This work has been partially supported by the Spanish Government through its TEC2017-88169-R MobiNetVideo project.
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Thompson",authors:[{id:"43567",title:"Prof.",name:"Nick",middleName:null,surname:"Birbilis",slug:"nick-birbilis",fullName:"Nick Birbilis"},{id:"32486",title:"Prof.",name:"Anthony",middleName:"E",surname:"Hughes",slug:"anthony-hughes",fullName:"Anthony Hughes"},{id:"43568",title:"Prof.",name:"Arjan",middleName:null,surname:"Mol",slug:"arjan-mol",fullName:"Arjan Mol"},{id:"43569",title:"Prof.",name:"Santiago",middleName:null,surname:"Garcia Espallargas",slug:"santiago-garcia-espallargas",fullName:"Santiago Garcia Espallargas"},{id:"43570",title:"Prof.",name:"Xiaorang",middleName:null,surname:"Zhou",slug:"xiaorang-zhou",fullName:"Xiaorang Zhou"},{id:"83528",title:"Prof.",name:"George",middleName:null,surname:"Thompson",slug:"george-thompson",fullName:"George Thompson"}]}],mostDownloadedChaptersLast30Days:[{id:"12751",title:"Contemporary Forming Methods of the Structure and Properties of Cast Magnesium Alloys",slug:"contemporary-forming-methods-of-the-structure-and-properties-of-cast-magnesium-alloys",totalDownloads:3109,totalCrossrefCites:0,totalDimensionsCites:0,abstract:null,book:{id:"27",slug:"magnesium-alloys-design-processing-and-properties",title:"Magnesium Alloys",fullTitle:"Magnesium Alloys - Design, Processing and Properties"},signatures:"Leszek A. Dobrzański, Tomasz Tański, Szymon Malara, Mariusz Król and Justyna Domagała-dubiel",authors:[{id:"15700",title:"Prof.",name:"Tomasz Arkadiusz",middleName:null,surname:"Tański",slug:"tomasz-arkadiusz-tanski",fullName:"Tomasz Arkadiusz Tański"},{id:"15880",title:"Prof.",name:"Leszek A.",middleName:null,surname:"Dobrzański",slug:"leszek-a.-dobrzanski",fullName:"Leszek A. Dobrzański"},{id:"15882",title:"MSc.",name:"Szymon",middleName:null,surname:"Malara",slug:"szymon-malara",fullName:"Szymon Malara"},{id:"15883",title:"Dr.",name:"Mariusz",middleName:null,surname:"Król",slug:"mariusz-krol",fullName:"Mariusz Król"},{id:"142678",title:"Dr.",name:"Justyna",middleName:null,surname:"Domagała-Dubiel",slug:"justyna-domagala-dubiel",fullName:"Justyna Domagała-Dubiel"}]},{id:"74167",title:"Solidification of Metals and Alloys",slug:"solidification-of-metals-and-alloys",totalDownloads:1211,totalCrossrefCites:2,totalDimensionsCites:2,abstract:"In order to analyse the process of solidification of metals and alloys critically, it is most pertinent to understand the different modes of nucleation and the uneven rates of growth throughout the melt. It is also important to take a note of the constraints in the growth process that definitely influence the crystal structure and the structure related properties of the casting. The freezing pattern of the liquid melt decides the feeding of the mould which is instrumental in producing a complete and compact casting. For pure metals and even in case of alloys with a narrow freezing range a well defined solid–liquid macro-interface exists. Here feeding of the solidifying casting is the easiest, by the common lowering of the liquid metal surface in the mould. However, in many instances, a well defined interface is not witnessed. The solid–liquid interface could be discrete and not continuous. Here process of feeding the solidification sites that witness considerable shrinkages, may become complicated. On grounds of above it is implied, the process of solidification constitutes an important aspects in the production of a defect free casting.",book:{id:"10432",slug:"casting-processes-and-modelling-of-metallic-materials",title:"Casting Processes and Modelling of Metallic Materials",fullTitle:"Casting Processes and Modelling of Metallic Materials"},signatures:"Upendra Kumar Mohanty and Hrushikesh Sarangi",authors:[{id:"328540",title:"Prof.",name:"Hrushikesh",middleName:null,surname:"Sarangi",slug:"hrushikesh-sarangi",fullName:"Hrushikesh Sarangi"},{id:"328543",title:"Prof.",name:"Upendra Kumar",middleName:null,surname:"Mohanty",slug:"upendra-kumar-mohanty",fullName:"Upendra Kumar Mohanty"}]},{id:"48856",title:"Silicon Carbide in Microsystem Technology — Thin Film Versus Bulk Material",slug:"silicon-carbide-in-microsystem-technology-thin-film-versus-bulk-material",totalDownloads:2887,totalCrossrefCites:4,totalDimensionsCites:10,abstract:"This chapter looks at the role of silicon carbide (SiC) in microsystem technology. It starts with an introduction into the wide bandgap (WBG) materials and the properties that make them potential candidates to enable the development of harsh environment microsystems. The future commercial success of WBG microsystems depends mainly on the availability of high-quality materials, well-established microfabrication processes, and economic viability. In such aspects SiC platform, in relation to other WBG materials, provides a clear and competitive advantage. The reasons for this will be detailed. Furthermore, the current status of the SiC thin film and bulk material technologies will also be discussed. Both SiC material forms have played important roles in different microsystem types.",book:{id:"4721",slug:"advanced-silicon-carbide-devices-and-processing",title:"Advanced Silicon Carbide Devices and Processing",fullTitle:"Advanced Silicon Carbide Devices and Processing"},signatures:"Mariana Amorim Fraga, Matteo Bosi and Marco Negri",authors:[{id:"9292",title:"Dr.",name:"matteo",middleName:null,surname:"bosi",slug:"matteo-bosi",fullName:"matteo bosi"},{id:"38456",title:"Dr.",name:"Mariana",middleName:null,surname:"Amorim Fraga",slug:"mariana-amorim-fraga",fullName:"Mariana Amorim Fraga"},{id:"175671",title:"MSc.",name:"Marco",middleName:null,surname:"Negri",slug:"marco-negri",fullName:"Marco Negri"}]},{id:"46237",title:"Corrosion Resistance Through the Application of Anti- Corrosion Coatings",slug:"corrosion-resistance-through-the-application-of-anti-corrosion-coatings",totalDownloads:7398,totalCrossrefCites:11,totalDimensionsCites:32,abstract:null,book:{id:"3817",slug:"developments-in-corrosion-protection",title:"Developments in Corrosion Protection",fullTitle:"Developments in Corrosion Protection"},signatures:"Api Popoola, OE Olorunniwo and OO Ige",authors:[{id:"169258",title:"Dr.",name:"Patricia",middleName:null,surname:"Popoola",slug:"patricia-popoola",fullName:"Patricia Popoola"}]},{id:"46235",title:"Corrosion Detection for Automated Visual Inspection",slug:"corrosion-detection-for-automated-visual-inspection",totalDownloads:3578,totalCrossrefCites:18,totalDimensionsCites:32,abstract:null,book:{id:"3817",slug:"developments-in-corrosion-protection",title:"Developments in Corrosion Protection",fullTitle:"Developments in Corrosion Protection"},signatures:"Francisco Bonnin-Pascual and Alberto Ortiz",authors:[{id:"124589",title:"Prof.",name:"Alberto",middleName:null,surname:"Ortiz",slug:"alberto-ortiz",fullName:"Alberto Ortiz"},{id:"169256",title:"Ph.D. Student",name:"Francisco",middleName:null,surname:"Bonnin-Pascual",slug:"francisco-bonnin-pascual",fullName:"Francisco Bonnin-Pascual"}]}],onlineFirstChaptersFilter:{topicId:"944",limit:6,offset:0},onlineFirstChaptersCollection:[{id:"82118",title:"Surface Hardening of Stainless Steel",slug:"surface-hardening-of-stainless-steel",totalDownloads:24,totalDimensionsCites:0,doi:"10.5772/intechopen.105036",abstract:"The addition of nitrogen to stainless steel improves mechanical and corrosion properties. Nitrogen-bearing stainless steel (HNSS) is a new corrosion-resistant alloy class exhibiting better tribological properties. High-pressure and powder metallurgy techniques were developed for the fabrication of HNSS. Solid-state routes allow nitrogen introduction through thermochemical, implantation, or plasma surface treatments. High-temperature gas nitriding (HTGN), carried out in an N2 atmosphere in the 1000°C range, allows N uptake, obtaining thick, ~0.5–1.0 wt.% N austenitic cases. HTGN is different from conventional nitriding, performed in the 500°C range, where intense CrxNy precipitation occurs, impairing the corrosion resistance. Low-temperature plasma nitriding (LTPN) introduces more N in solution, and colossal supersaturated expanded phases (~45 at.%N) are formed. N supersaturation and compressive stresses increase the hardness of the surface layer to 10–14 GPa. Ferritic, martensitic, duplex, and precipitation-hardened stainless steels can be surface-treated by LTPN, obtaining expanded ferrite and martensite. However, single LTPN stainless steel may prematurely fail when submitted to high loading, as the thin and hard expanded layers collapse due to lack of load-bearing capacity. Duplex-nitriding treatment (HTGN + LTPN) results in a thick nitrogen-rich hardened austenite substrate layer, granting mechanical support and adhesion to the expanded austenite layer.",book:{id:"11076",title:"Stainless Steels",coverURL:"https://cdn.intechopen.com/books/images_new/11076.jpg"},signatures:"André Paulo Tschiptschin and Carlos Eduardo Pinedo"},{id:"81579",title:"Welding Based Additive Manufacturing: Fundamentals",slug:"welding-based-additive-manufacturing-fundamentals",totalDownloads:31,totalDimensionsCites:0,doi:"10.5772/intechopen.104768",abstract:"Additive Manufacturing (AM) has drawn abundant attention over the past decades in the manufacturing and fabrication industries, especially to make part models and prototypes. This chapter introduces a potential welding based AM process called Wire Arc Additive Manufacturing (WAAM) for the fabrication of near-net shaped metal components including stainless steel components. To start with traditional AM processes, various fundamental traditional AM for the fabrication of components have been presented. Wire Arc Additive Manufacturing (WAAM) has been explained with its variants, synonyms, different welding processes to suit WAAM particularly to weld stainless steel metal; primary process selections for working with WAAM, important metals, and alloys that could be used in WAAM have been elaborated. A case study for WAAM fabrication of AISI 316 L stainless steel plate is included to introduce the fabrication of metal components using WAAM. Further, the most common defects which possibly play a vital role in WAAM components fabrication and a few of the future challenges regarding WAAM development are discussed. Fundamental information covered in this chapter could be more beneficial to beginners for the understanding of WAAM process generally including stainless steel component fabrication in a lucid tactic.",book:{id:"11076",title:"Stainless Steels",coverURL:"https://cdn.intechopen.com/books/images_new/11076.jpg"},signatures:"Maruthasalam Sowrirajan, Selvaraj Vijayan and Munusamy Arulraj"},{id:"80664",title:"Dependence of Corrosion Resistance of Austenitic Chromium-Nickel Steels on the Magnetic State of Austenite",slug:"dependence-of-corrosion-resistance-of-austenitic-chromium-nickel-steels-on-the-magnetic-state-of-aus",totalDownloads:59,totalDimensionsCites:0,doi:"10.5772/intechopen.102388",abstract:"Corrosive behavior of austenitic chromium-nickel steels from the magnetic state (parameter χ0) of austenite, pre-formed to interact with aggressive media are research. Correlation between the rate K of pitting corrosion and the specific magnetic susceptibility χ0 of austenite was experimentally established. It is experimentally established that the corrosion resistance of austenitic steels AISI304, 08Cr18Ni10, AISI 321, 08Cr18Ni10Тi (containing a low amount of δ-ferrite ∼0.005…0.5%) depends on the magnetic state of austenite: the corrosion rate of steel decreases with increases χ0 austenite. The tendency of change in the corrosion rate of austenitic alloy with a high nickel content 06Crh28NiMoCuTi (not contain δ-ferrite) has the opposite character: with increasing χ0, the corrosion rate of the alloy increases is revealed. For austenitic chromium-nickel steels, the corrosion rates of the individual (austenite (A), δ-ferrite (F), strain-induced α′-martensite (M)) and total (A + F, A + M and A + F + M) phases are determined. It is proposed to predict corrosion according to the specific magnetic susceptibility χ0 of austenite and the amount δ-ferrite.",book:{id:"11076",title:"Stainless Steels",coverURL:"https://cdn.intechopen.com/books/images_new/11076.jpg"},signatures:"Gennadii Snizhnoi"},{id:"80199",title:"The Evaluation of the Comparative Corrosion Behaviour of Conventional and Low-Nickel Austenitic Stainless Steel: Hercules™ Alloy",slug:"the-evaluation-of-the-comparative-corrosion-behaviour-of-conventional-and-low-nickel-austenitic-stai",totalDownloads:55,totalDimensionsCites:0,doi:"10.5772/intechopen.102381",abstract:"Austenitic stainless steels require approximately 8% Ni to maintain austenitic microstructure at room temperature for alloys such as 304 stainless steel (304SS). Ni contributes approximately 60% of the total material cost and its price fluctuates, making the cost of austenitic stainless steel unpredictable. The use of low-nickel austenitic stainless steels as a substitute has been considered in order to remedy costs associated with Ni price fluctuations. Alloying elements such as Mn and N have been considered, however they have been found to reduce corrosion resistance. A new alloy namely Hercules™ has been developed with reduced Ni content (1.8–2% Ni). This chapter presents a comparative study of the corrosion behavior of Hercules™ and 304SS in different solutions. The alloys were evaluated using cyclic polarisation technique and immersion tests. The results demonstrated that the corrosion resistance of Hercules™ is comparable to that of 304SS. This presents the alloys as potential industrial substitutes of each other.",book:{id:"11076",title:"Stainless Steels",coverURL:"https://cdn.intechopen.com/books/images_new/11076.jpg"},signatures:"Duduzile Nkomo and Nomsombuluko Masia"},{id:"80346",title:"Nitrogen Supersaturation of AISI316 Base Stainless Steels at 673 K and 623 K for Hardening and Microstructure Control",slug:"nitrogen-supersaturation-of-aisi316-base-stainless-steels-at-673-k-and-623-k-for-hardening-and-micro",totalDownloads:59,totalDimensionsCites:1,doi:"10.5772/intechopen.102387",abstract:"The high-density plasma nitriding at 673 K and 623 K was employed to make 10% of nitrogen supersaturation on AISI316 base austenitic stainless steels. The processing parameters and nitrogen-hydrogen gas flow ratio were optimized to increase the yield of N2+ ion and NH-radical for efficient nitriding. The nitrided AISI316 specimens were prepared for multidimensional analysis to describe the fundamental features of low-temperature plasma nitriding. First, macroscopic evaluation revealed that nitrogen supersaturation induced the γ-lattice expansion and the higher nitrogen content than 4% of mass in depth. The mesoscopic analysis describes the holding temperature and initial grain-size effects on the microstructure changes. Plastic straining, grain-size refinement, and nitrogen zone-boundary diffusion processes advance with nitrogen supersaturation to drive the inner nitriding behavior. The microscopic analysis explains the microstructure refinement, the two-phase structuring, and the microstructure modification. Through this multi-dimensional analysis, the essential characteristics of the low-temperature plasma nitriding of 316 austenitic stainless steels were precisely understood to extend the engineering treatise on the bulk nitrogen stainless steels for surface modification and treatment of stainless steels by nitriding. This plasma nitriding was applied to strengthen and harden the AISI316 wire surfaces toward its application on surgery wires.",book:{id:"11076",title:"Stainless Steels",coverURL:"https://cdn.intechopen.com/books/images_new/11076.jpg"},signatures:"Tatsuhiko Aizawa, Tomomi Shiratori, Tomoaki Yoshino, Yohei Suzuki and Takafumi Komatsu"},{id:"79904",title:"Corrosion Resistance, Evaluation Methods, and Surface Treatments of Stainless Steels",slug:"corrosion-resistance-evaluation-methods-and-surface-treatments-of-stainless-steels",totalDownloads:106,totalDimensionsCites:1,doi:"10.5772/intechopen.101430",abstract:"Stainless steels are widely recognized and find applications in many engineering industries and companies due to their excellent properties including high resistance to corrosion as a result of their minimum 10.5% chromium content, exceptional strength and durability, temperature resistance, high recyclability, and easy formability. In the present book chapter, the basic concepts of stainless steel including its applications, classifications, and corrosion properties will first be discussed. Thereafter, their corrosion behaviour will then be explained. The various methods by which the corrosion resistance behaviour can be significantly improved including surface treatments such as coatings/electrodepositions, alloying, mechanical treatment, and others will be discussed in detail.",book:{id:"11076",title:"Stainless Steels",coverURL:"https://cdn.intechopen.com/books/images_new/11076.jpg"},signatures:"Temitope Olumide Olugbade"}],onlineFirstChaptersTotal:8},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:8,limit:8,total:0},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:90,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:107,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:33,numberOfPublishedChapters:330,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:14,numberOfPublishedChapters:145,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:9,numberOfPublishedChapters:139,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:122,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:112,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:21,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:10,numberOfOpenTopics:1,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!0},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:"2753-6580",doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}},{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}}]},series:{item:{id:"14",title:"Artificial Intelligence",doi:"10.5772/intechopen.79920",issn:"2633-1403",scope:"Artificial Intelligence (AI) is a rapidly developing multidisciplinary research area that aims to solve increasingly complex problems. In today's highly integrated world, AI promises to become a robust and powerful means for obtaining solutions to previously unsolvable problems. This Series is intended for researchers and students alike interested in this fascinating field and its many applications.",coverUrl:"https://cdn.intechopen.com/series/covers/14.jpg",latestPublicationDate:"July 5th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:9,editor:{id:"218714",title:"Prof.",name:"Andries",middleName:null,surname:"Engelbrecht",slug:"andries-engelbrecht",fullName:"Andries Engelbrecht",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRNR8QAO/Profile_Picture_1622640468300",biography:"Andries Engelbrecht received the Masters and PhD degrees in Computer Science from the University of Stellenbosch, South Africa, in 1994 and 1999 respectively. He is currently appointed as the Voigt Chair in Data Science in the Department of Industrial Engineering, with a joint appointment as Professor in the Computer Science Division, Stellenbosch University. Prior to his appointment at Stellenbosch University, he has been at the University of Pretoria, Department of Computer Science (1998-2018), where he was appointed as South Africa Research Chair in Artifical Intelligence (2007-2018), the head of the Department of Computer Science (2008-2017), and Director of the Institute for Big Data and Data Science (2017-2018). In addition to a number of research articles, he has written two books, Computational Intelligence: An Introduction and Fundamentals of Computational Swarm Intelligence.",institutionString:null,institution:{name:"Stellenbosch University",institutionURL:null,country:{name:"South Africa"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:6,paginationItems:[{id:"22",title:"Applied Intelligence",coverUrl:"https://cdn.intechopen.com/series_topics/covers/22.jpg",isOpenForSubmission:!0,editor:{id:"27170",title:"Prof.",name:"Carlos",middleName:"M.",surname:"Travieso-Gonzalez",slug:"carlos-travieso-gonzalez",fullName:"Carlos Travieso-Gonzalez",profilePictureURL:"https://mts.intechopen.com/storage/users/27170/images/system/27170.jpeg",biography:"Carlos M. Travieso-González received his MSc degree in Telecommunication Engineering at Polytechnic University of Catalonia (UPC), Spain in 1997, and his Ph.D. degree in 2002 at the University of Las Palmas de Gran Canaria (ULPGC-Spain). He is a full professor of signal processing and pattern recognition and is head of the Signals and Communications Department at ULPGC, teaching from 2001 on subjects on signal processing and learning theory. His research lines are biometrics, biomedical signals and images, data mining, classification system, signal and image processing, machine learning, and environmental intelligence. He has researched in 52 international and Spanish research projects, some of them as head researcher. He is co-author of 4 books, co-editor of 27 proceedings books, guest editor for 8 JCR-ISI international journals, and up to 24 book chapters. He has over 450 papers published in international journals and conferences (81 of them indexed on JCR – ISI - Web of Science). He has published seven patents in the Spanish Patent and Trademark Office. He has been a supervisor on 8 Ph.D. theses (11 more are under supervision), and 130 master theses. He is the founder of The IEEE IWOBI conference series and the president of its Steering Committee, as well as the founder of both the InnoEducaTIC and APPIS conference series. He is an evaluator of project proposals for the European Union (H2020), Medical Research Council (MRC, UK), Spanish Government (ANECA, Spain), Research National Agency (ANR, France), DAAD (Germany), Argentinian Government, and the Colombian Institutions. He has been a reviewer in different indexed international journals (<70) and conferences (<250) since 2001. He has been a member of the IASTED Technical Committee on Image Processing from 2007 and a member of the IASTED Technical Committee on Artificial Intelligence and Expert Systems from 2011. \n\nHe has held the general chair position for the following: ACM-APPIS (2020, 2021), IEEE-IWOBI (2019, 2020 and 2020), A PPIS (2018, 2019), IEEE-IWOBI (2014, 2015, 2017, 2018), InnoEducaTIC (2014, 2017), IEEE-INES (2013), NoLISP (2011), JRBP (2012), and IEEE-ICCST (2005)\n\nHe is an associate editor of the Computational Intelligence and Neuroscience Journal (Hindawi – Q2 JCR-ISI). He was vice dean from 2004 to 2010 in the Higher Technical School of Telecommunication Engineers at ULPGC and the vice dean of Graduate and Postgraduate Studies from March 2013 to November 2017. He won the “Catedra Telefonica” Awards in Modality of Knowledge Transfer, 2017, 2018, and 2019 editions, and awards in Modality of COVID Research in 2020.\n\nPublic References:\nResearcher ID http://www.researcherid.com/rid/N-5967-2014\nORCID https://orcid.org/0000-0002-4621-2768 \nScopus Author ID https://www.scopus.com/authid/detail.uri?authorId=6602376272\nScholar Google https://scholar.google.es/citations?user=G1ks9nIAAAAJ&hl=en \nResearchGate https://www.researchgate.net/profile/Carlos_Travieso",institutionString:null,institution:{name:"University of Las Palmas de Gran Canaria",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"23",title:"Computational Neuroscience",coverUrl:"https://cdn.intechopen.com/series_topics/covers/23.jpg",isOpenForSubmission:!0,editor:{id:"14004",title:"Dr.",name:"Magnus",middleName:null,surname:"Johnsson",slug:"magnus-johnsson",fullName:"Magnus Johnsson",profilePictureURL:"https://mts.intechopen.com/storage/users/14004/images/system/14004.png",biography:"Dr Magnus Johnsson is a cross-disciplinary scientist, lecturer, scientific editor and AI/machine learning consultant from Sweden. \n\nHe is currently at Malmö University in Sweden, but also held positions at Lund University in Sweden and at Moscow Engineering Physics Institute. \nHe holds editorial positions at several international scientific journals and has served as a scientific editor for books and special journal issues. \nHis research interests are wide and include, but are not limited to, autonomous systems, computer modeling, artificial neural networks, artificial intelligence, cognitive neuroscience, cognitive robotics, cognitive architectures, cognitive aids and the philosophy of mind. \n\nDr. Johnsson has experience from working in the industry and he has a keen interest in the application of neural networks and artificial intelligence to fields like industry, finance, and medicine. \n\nWeb page: www.magnusjohnsson.se",institutionString:null,institution:{name:"Malmö University",institutionURL:null,country:{name:"Sweden"}}},editorTwo:null,editorThree:null},{id:"24",title:"Computer Vision",coverUrl:"https://cdn.intechopen.com/series_topics/covers/24.jpg",isOpenForSubmission:!0,editor:{id:"294154",title:"Prof.",name:"George",middleName:null,surname:"Papakostas",slug:"george-papakostas",fullName:"George Papakostas",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002hYaGbQAK/Profile_Picture_1624519712088",biography:"George A. Papakostas has received a diploma in Electrical and Computer Engineering in 1999 and the M.Sc. and Ph.D. degrees in Electrical and Computer Engineering in 2002 and 2007, respectively, from the Democritus University of Thrace (DUTH), Greece. Dr. Papakostas serves as a Tenured Full Professor at the Department of Computer Science, International Hellenic University, Greece. Dr. Papakostas has 10 years of experience in large-scale systems design as a senior software engineer and technical manager, and 20 years of research experience in the field of Artificial Intelligence. Currently, he is the Head of the “Visual Computing” division of HUman-MAchines INteraction Laboratory (HUMAIN-Lab) and the Director of the MPhil program “Advanced Technologies in Informatics and Computers” hosted by the Department of Computer Science, International Hellenic University. He has (co)authored more than 150 publications in indexed journals, international conferences and book chapters, 1 book (in Greek), 3 edited books, and 5 journal special issues. His publications have more than 2100 citations with h-index 27 (GoogleScholar). His research interests include computer/machine vision, machine learning, pattern recognition, computational intelligence. \nDr. Papakostas served as a reviewer in numerous journals, as a program\ncommittee member in international conferences and he is a member of the IAENG, MIR Labs, EUCogIII, INSTICC and the Technical Chamber of Greece (TEE).",institutionString:null,institution:{name:"International Hellenic University",institutionURL:null,country:{name:"Greece"}}},editorTwo:null,editorThree:null},{id:"25",title:"Evolutionary Computation",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",isOpenForSubmission:!0,editor:{id:"136112",title:"Dr.",name:"Sebastian",middleName:null,surname:"Ventura Soto",slug:"sebastian-ventura-soto",fullName:"Sebastian Ventura Soto",profilePictureURL:"https://mts.intechopen.com/storage/users/136112/images/system/136112.png",biography:"Sebastian Ventura is a Spanish researcher, a full professor with the Department of Computer Science and Numerical Analysis, University of Córdoba. Dr Ventura also holds the positions of Affiliated Professor at Virginia Commonwealth University (Richmond, USA) and Distinguished Adjunct Professor at King Abdulaziz University (Jeddah, Saudi Arabia). Additionally, he is deputy director of the Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) and heads the Knowledge Discovery and Intelligent Systems Research Laboratory. He has published more than ten books and over 300 articles in journals and scientific conferences. Currently, his work has received over 18,000 citations according to Google Scholar, including more than 2200 citations in 2020. In the last five years, he has published more than 60 papers in international journals indexed in the JCR (around 70% of them belonging to first quartile journals) and he has edited some Springer books “Supervised Descriptive Pattern Mining” (2018), “Multiple Instance Learning - Foundations and Algorithms” (2016), and “Pattern Mining with Evolutionary Algorithms” (2016). He has also been involved in more than 20 research projects supported by the Spanish and Andalusian governments and the European Union. He currently belongs to the editorial board of PeerJ Computer Science, Information Fusion and Engineering Applications of Artificial Intelligence journals, being also associate editor of Applied Computational Intelligence and Soft Computing and IEEE Transactions on Cybernetics. Finally, he is editor-in-chief of Progress in Artificial Intelligence. He is a Senior Member of the IEEE Computer, the IEEE Computational Intelligence, and the IEEE Systems, Man, and Cybernetics Societies, and the Association of Computing Machinery (ACM). Finally, his main research interests include data science, computational intelligence, and their applications.",institutionString:null,institution:{name:"University of Córdoba",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"26",title:"Machine Learning and Data Mining",coverUrl:"https://cdn.intechopen.com/series_topics/covers/26.jpg",isOpenForSubmission:!0,editor:{id:"24555",title:"Dr.",name:"Marco Antonio",middleName:null,surname:"Aceves Fernandez",slug:"marco-antonio-aceves-fernandez",fullName:"Marco Antonio Aceves Fernandez",profilePictureURL:"https://mts.intechopen.com/storage/users/24555/images/system/24555.jpg",biography:"Dr. Marco Antonio Aceves Fernandez obtained his B.Sc. (Eng.) in Telematics from the Universidad de Colima, Mexico. 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He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. 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Saxena",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRET3QAO/Profile_Picture_2022-05-10T10:10:26.jpeg",institutionString:"King George's Medical University",institution:{name:"King George's Medical University",institutionURL:null,country:{name:"India"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null}]},subseriesFiltersForPublishedBooks:[{group:"subseries",caption:"Bacterial Infectious Diseases",value:3,count:2},{group:"subseries",caption:"Parasitic Infectious Diseases",value:5,count:4},{group:"subseries",caption:"Viral Infectious Diseases",value:6,count:7}],publicationYearFilters:[{group:"publicationYear",caption:"2022",value:2022,count:2},{group:"publicationYear",caption:"2021",value:2021,count:4},{group:"publicationYear",caption:"2020",value:2020,count:3},{group:"publicationYear",caption:"2019",value:2019,count:3},{group:"publicationYear",caption:"2018",value:2018,count:1}],authors:{paginationCount:229,paginationItems:[{id:"318170",title:"Dr.",name:"Aneesa",middleName:null,surname:"Moolla",slug:"aneesa-moolla",fullName:"Aneesa Moolla",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/318170/images/system/318170.png",biography:"Dr. Aneesa Moolla has extensive experience in the diverse fields of health care having previously worked in dental private practice, at the Red Cross Flying Doctors association, and in healthcare corporate settings. She is now a lecturer at the University of Witwatersrand, South Africa, and a principal researcher at the Health Economics and Epidemiology Research Office (HE2RO), South Africa. Dr. Moolla holds a Ph.D. in Psychology with her research being focused on mental health and resilience. In her professional work capacity, her research has further expanded into the fields of early childhood development, mental health, the HIV and TB care cascades, as well as COVID. She is also a UNESCO-trained International Bioethics Facilitator.",institutionString:"University of the Witwatersrand",institution:{name:"University of the Witwatersrand",country:{name:"South Africa"}}},{id:"419588",title:"Ph.D.",name:"Sergio",middleName:"Alexandre",surname:"Gehrke",slug:"sergio-gehrke",fullName:"Sergio Gehrke",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000038WgMKQA0/Profile_Picture_2022-06-02T11:44:20.jpg",biography:"Dr. Sergio Alexandre Gehrke is a doctorate holder in two fields. The first is a Ph.D. in Cellular and Molecular Biology from the Pontificia Catholic University, Porto Alegre, Brazil, in 2010 and the other is an International Ph.D. in Bioengineering from the Universidad Miguel Hernandez, Elche/Alicante, Spain, obtained in 2020. In 2018, he completed a postdoctoral fellowship in Materials Engineering in the NUCLEMAT of the Pontificia Catholic University, Porto Alegre, Brazil. He is currently the Director of the Postgraduate Program in Implantology of the Bioface/UCAM/PgO (Montevideo, Uruguay), Director of the Cathedra of Biotechnology of the Catholic University of Murcia (Murcia, Spain), an Extraordinary Full Professor of the Catholic University of Murcia (Murcia, Spain) as well as the Director of the private center of research Biotecnos – Technology and Science (Montevideo, Uruguay). Applied biomaterials, cellular and molecular biology, and dental implants are among his research interests. He has published several original papers in renowned journals. In addition, he is also a Collaborating Professor in several Postgraduate programs at different universities all over the world.",institutionString:null,institution:{name:"Universidad Católica San Antonio de Murcia",country:{name:"Spain"}}},{id:"342152",title:"Dr.",name:"Santo",middleName:null,surname:"Grace Umesh",slug:"santo-grace-umesh",fullName:"Santo Grace Umesh",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/342152/images/16311_n.jpg",biography:null,institutionString:null,institution:{name:"SRM Dental College",country:{name:"India"}}},{id:"333647",title:"Dr.",name:"Shreya",middleName:null,surname:"Kishore",slug:"shreya-kishore",fullName:"Shreya Kishore",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/333647/images/14701_n.jpg",biography:"Dr. Shreya Kishore completed her Bachelor in Dental Surgery in Chettinad Dental College and Research Institute, Chennai, and her Master of Dental Surgery (Orthodontics) in Saveetha Dental College, Chennai. She is also Invisalign certified. She’s working as a Senior Lecturer in the Department of Orthodontics, SRM Dental College since November 2019. She is actively involved in teaching orthodontics to the undergraduates and the postgraduates. Her clinical research topics include new orthodontic brackets, fixed appliances and TADs. She’s published 4 articles in well renowned indexed journals and has a published patency of her own. Her private practice is currently limited to orthodontics and works as a consultant in various clinics.",institutionString:null,institution:{name:"SRM Dental College",country:{name:"India"}}},{id:"323731",title:"Prof.",name:"Deepak M.",middleName:"Macchindra",surname:"Vikhe",slug:"deepak-m.-vikhe",fullName:"Deepak M. Vikhe",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/323731/images/13613_n.jpg",biography:"Dr Deepak M.Vikhe .\n\n\t\n\tDr Deepak M.Vikhe , completed his Masters & PhD in Prosthodontics from Rural Dental College, Loni securing third rank in the Pravara Institute of Medical Sciences Deemed University. He was awarded Dr.G.C.DAS Memorial Award for Research on Implants at 39th IPS conference Dubai (U A E).He has two patents under his name. He has received Dr.Saraswati medal award for best research for implant study in 2017.He has received Fully funded scholarship to Spain ,university of Santiago de Compostela. He has completed fellowship in Implantlogy from Noble Biocare. \nHe has attended various conferences and CDE programmes and has national publications to his credit. His field of interest is in Implant supported prosthesis. Presently he is working as a associate professor in the Dept of Prosthodontics, Rural Dental College, Loni and maintains a successful private practice specialising in Implantology at Rahata.\n\nEmail: drdeepak_mvikhe@yahoo.com..................",institutionString:null,institution:{name:"Pravara Institute of Medical Sciences",country:{name:"India"}}},{id:"204110",title:"Dr.",name:"Ahmed A.",middleName:null,surname:"Madfa",slug:"ahmed-a.-madfa",fullName:"Ahmed A. Madfa",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/204110/images/system/204110.jpg",biography:"Dr. Madfa is currently Associate Professor of Endodontics at Thamar University and a visiting lecturer at Sana'a University and University of Sciences and Technology. He has more than 6 years of experience in teaching. His research interests include root canal morphology, functionally graded concept, dental biomaterials, epidemiology and dental education, biomimetic restoration, finite element analysis and endodontic regeneration. Dr. Madfa has numerous international publications, full articles, two patents, a book and a book chapter. Furthermore, he won 14 international scientific awards. Furthermore, he is involved in many academic activities ranging from editorial board member, reviewer for many international journals and postgraduate students' supervisor. Besides, I deliver many courses and training workshops at various scientific events. Dr. Madfa also regularly attends international conferences and holds administrative positions (Deputy Dean of the Faculty for Students’ & Academic Affairs and Deputy Head of Research Unit).",institutionString:"Thamar University",institution:null},{id:"210472",title:"Dr.",name:"Nermin",middleName:"Mohammed Ahmed",surname:"Yussif",slug:"nermin-yussif",fullName:"Nermin Yussif",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/210472/images/system/210472.jpg",biography:"Dr. Nermin Mohammed Ahmed Yussif is working at the Faculty of dentistry, University for October university for modern sciences and arts (MSA). Her areas of expertise include: periodontology, dental laserology, oral implantology, periodontal plastic surgeries, oral mesotherapy, nutrition, dental pharmacology. She is an editor and reviewer in numerous international journals.",institutionString:"MSA University",institution:null},{id:"204606",title:"Dr.",name:"Serdar",middleName:null,surname:"Gözler",slug:"serdar-gozler",fullName:"Serdar Gözler",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/204606/images/system/204606.jpeg",biography:"Dr. Serdar Gözler has completed his undergraduate studies at the Marmara University Faculty of Dentistry in 1978, followed by an assistantship in the Prosthesis Department of Dicle University Faculty of Dentistry. Starting his PhD work on non-resilient overdentures with Assoc. Prof. Hüsnü Yavuzyılmaz, he continued his studies with Prof. Dr. Gürbüz Öztürk of Istanbul University Faculty of Dentistry Department of Prosthodontics, this time on Gnatology. He attended training programs on occlusion, neurology, neurophysiology, EMG, radiology and biostatistics. In 1982, he presented his PhD thesis \\Gerber and Lauritzen Occlusion Analysis Techniques: Diagnosis Values,\\ at Istanbul University School of Dentistry, Department of Prosthodontics. As he was also working with Prof. Senih Çalıkkocaoğlu on The Physiology of Chewing at the same time, Gözler has written a chapter in Çalıkkocaoğlu\\'s book \\Complete Prostheses\\ entitled \\The Place of Neuromuscular Mechanism in Prosthetic Dentistry.\\ The book was published five times since by the Istanbul University Publications. Having presented in various conferences about occlusion analysis until 1998, Dr. Gözler has also decided to use the T-Scan II occlusion analysis method. Having been personally trained by Dr. Robert Kerstein on this method, Dr. Gözler has been lecturing on the T-Scan Occlusion Analysis Method in conferences both in Turkey and abroad. Dr. Gözler has various articles and presentations on Digital Occlusion Analysis methods. He is now Head of the TMD Clinic at Prosthodontic Department of Faculty of Dentistry , Istanbul Aydın University , Turkey.",institutionString:"Istanbul Aydin University",institution:{name:"Istanbul Aydın University",country:{name:"Turkey"}}},{id:"256417",title:"Associate Prof.",name:"Sanaz",middleName:null,surname:"Sadry",slug:"sanaz-sadry",fullName:"Sanaz Sadry",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/256417/images/8106_n.jpg",biography:null,institutionString:null,institution:{name:"Istanbul Aydın University",country:{name:"Turkey"}}},{id:"240870",title:"Ph.D.",name:"Alaa Eddin Omar",middleName:null,surname:"Al Ostwani",slug:"alaa-eddin-omar-al-ostwani",fullName:"Alaa Eddin Omar Al Ostwani",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/240870/images/system/240870.jpeg",biography:"Dr. Al Ostwani Alaa Eddin Omar received his Master in dentistry from Damascus University in 2010, and his Ph.D. in Pediatric Dentistry from Damascus University in 2014. Dr. Al Ostwani is an assistant professor and faculty member at IUST University since 2014. \nDuring his academic experience, he has received several awards including the scientific research award from the Union of Arab Universities, the Syrian gold medal and the international gold medal for invention and creativity. Dr. Al Ostwani is a Member of the International Association of Dental Traumatology and the Syrian Society for Research and Preventive Dentistry since 2017. He is also a Member of the Reviewer Board of International Journal of Dental Medicine (IJDM), and the Indian Journal of Conservative and Endodontics since 2016.",institutionString:"International University for Science and Technology.",institution:{name:"Islamic University of Science and Technology",country:{name:"India"}}},{id:"42847",title:"Dr.",name:"Belma",middleName:null,surname:"Işik Aslan",slug:"belma-isik-aslan",fullName:"Belma Işik Aslan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/42847/images/system/42847.jpg",biography:"Dr. Belma IşIk Aslan was born in 1976 in Ankara-TURKEY. After graduating from TED Ankara College in 1994, she attended to Gazi University, Faculty of Dentistry in Ankara. She completed her PhD in orthodontic education at Gazi University between 1999-2005. Dr. Işık Aslan stayed at the Providence Hospital Craniofacial Institude and Reconstructive Surgery in Michigan, USA for three months as an observer. She worked as a specialist doctor at Gazi University, Dentistry Faculty, Department of Orthodontics between 2005-2014. She was appointed as associate professor in January, 2014 and as professor in 2021. Dr. Işık Aslan still works as an instructor at the same faculty. She has published a total of 35 articles, 10 book chapters, 39 conference proceedings both internationally and nationally. Also she was the academic editor of the international book 'Current Advances in Orthodontics'. She is a member of the Turkish Orthodontic Society and Turkish Cleft Lip and Palate Society. She is married and has 2 children. Her knowledge of English is at an advanced level.",institutionString:"Gazi University Dentistry Faculty Department of Orthodontics",institution:null},{id:"202198",title:"Dr.",name:"Buket",middleName:null,surname:"Aybar",slug:"buket-aybar",fullName:"Buket Aybar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/202198/images/6955_n.jpg",biography:"Buket Aybar, DDS, PhD, was born in 1971. She graduated from Istanbul University, Faculty of Dentistry, in 1992 and completed her PhD degree on Oral and Maxillofacial Surgery in Istanbul University in 1997.\r\nDr. Aybar is currently a full-time professor in Istanbul University, Faculty of Dentistry Department of Oral and Maxillofacial Surgery. She has teaching responsibilities in graduate and postgraduate programs. Her clinical practice includes mainly dentoalveolar surgery.\r\nHer topics of interest are biomaterials science and cell culture studies. She has many articles in international and national scientific journals and chapters in books; she also has participated in several scientific projects supported by Istanbul University Research fund.",institutionString:null,institution:{name:"Marmara University",country:{name:"Turkey"}}},{id:"178412",title:"Associate Prof.",name:"Guhan",middleName:null,surname:"Dergin",slug:"guhan-dergin",fullName:"Guhan Dergin",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/178412/images/6954_n.jpg",biography:"Assoc. Prof. Dr. Gühan Dergin was born in 1973 in Izmit. He graduated from Marmara University Faculty of Dentistry in 1999. He completed his specialty of OMFS surgery in Marmara University Faculty of Dentistry and obtained his PhD degree in 2006. In 2005, he was invited as a visiting doctor in the Oral and Maxillofacial Surgery Department of the University of North Carolina, USA, where he went on a scholarship. Dr. Dergin still continues his academic career as an associate professor in Marmara University Faculty of Dentistry. He has many articles in international and national scientific journals and chapters in books.",institutionString:null,institution:{name:"Marmara University",country:{name:"Turkey"}}},{id:"178414",title:"Prof.",name:"Yusuf",middleName:null,surname:"Emes",slug:"yusuf-emes",fullName:"Yusuf Emes",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/178414/images/6953_n.jpg",biography:"Born in Istanbul in 1974, Dr. Emes graduated from Istanbul University Faculty of Dentistry in 1997 and completed his PhD degree in Istanbul University faculty of Dentistry Department of Oral and Maxillofacial Surgery in 2005. He has papers published in international and national scientific journals, including research articles on implantology, oroantral fistulas, odontogenic cysts, and temporomandibular disorders. Dr. Emes is currently working as a full-time academic staff in Istanbul University faculty of Dentistry Department of Oral and Maxillofacial Surgery.",institutionString:null,institution:{name:"Istanbul University",country:{name:"Turkey"}}},{id:"192229",title:"Ph.D.",name:"Ana Luiza",middleName:null,surname:"De Carvalho Felippini",slug:"ana-luiza-de-carvalho-felippini",fullName:"Ana Luiza De Carvalho Felippini",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/192229/images/system/192229.jpg",biography:null,institutionString:"University of São Paulo",institution:{name:"University of Sao Paulo",country:{name:"Brazil"}}},{id:"256851",title:"Prof.",name:"Ayşe",middleName:null,surname:"Gülşen",slug:"ayse-gulsen",fullName:"Ayşe Gülşen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/256851/images/9696_n.jpg",biography:"Dr. Ayşe Gülşen graduated in 1990 from Faculty of Dentistry, University of Ankara and did a postgraduate program at University of Gazi. \nShe worked as an observer and research assistant in Craniofacial Surgery Departments in New York, Providence Hospital in Michigan and Chang Gung Memorial Hospital in Taiwan. \nShe works as Craniofacial Orthodontist in Department of Aesthetic, Plastic and Reconstructive Surgery, Faculty of Medicine, University of Gazi, Ankara Turkey since 2004.",institutionString:"Orthodontist, Assoc Prof in the Department of Aesthetic, Plastic and Reconstructive Surgery, Faculty of Medicine, University of Gazi",institution:null},{id:"255366",title:"Prof.",name:"Tosun",middleName:null,surname:"Tosun",slug:"tosun-tosun",fullName:"Tosun Tosun",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/255366/images/7347_n.jpg",biography:"Graduated at the Faculty of Dentistry, University of Istanbul, Turkey in 1989;\nVisitor Assistant at the University of Padua, Italy and Branemark Osseointegration Center of Treviso, Italy between 1993-94;\nPhD thesis on oral implantology in University of Istanbul and was awarded the academic title “Dr.med.dent.”, 1997;\nHe was awarded the academic title “Doç.Dr.” (Associated Professor) in 2003;\nProficiency in Botulinum Toxin Applications, Reading-UK in 2009;\nMastership, RWTH Certificate in Laser Therapy in Dentistry, AALZ-Aachen University, Germany 2009-11;\nMaster of Science (MSc) in Laser Dentistry, University of Genoa, Italy 2013-14.\n\nDr.Tosun worked as Research Assistant in the Department of Oral Implantology, Faculty of Dentistry, University of Istanbul between 1990-2002. \nHe worked part-time as Consultant surgeon in Harvard Medical International Hospitals and John Hopkins Medicine, Istanbul between years 2007-09.\u2028He was contract Professor in the Department of Surgical and Diagnostic Sciences (DI.S.C.), Medical School, University of Genova, Italy between years 2011-16. \nSince 2015 he is visiting Professor at Medical School, University of Plovdiv, Bulgaria. \nCurrently he is Associated Prof.Dr. at the Dental School, Oral Surgery Dept., Istanbul Aydin University and since 2003 he works in his own private clinic in Istanbul, Turkey.\u2028\nDr.Tosun is reviewer in journal ‘Laser in Medical Sciences’, reviewer in journal ‘Folia Medica\\', a Fellow of the International Team for Implantology, Clinical Lecturer of DGZI German Association of Oral Implantology, Expert Lecturer of Laser&Health Academy, Country Representative of World Federation for Laser Dentistry, member of European Federation of Periodontology, member of Academy of Laser Dentistry. Dr.Tosun presents papers in international and national congresses and has scientific publications in international and national journals. He speaks english, spanish, italian and french.",institutionString:null,institution:{name:"Istanbul Aydın University",country:{name:"Turkey"}}},{id:"260116",title:"Dr.",name:"Mehmet",middleName:null,surname:"Yaltirik",slug:"mehmet-yaltirik",fullName:"Mehmet Yaltirik",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/260116/images/7413_n.jpg",biography:"Birth Date 25.09.1965\r\nBirth Place Adana- Turkey\r\nSex Male\r\nMarrial Status Bachelor\r\nDriving License Acquired\r\nMother Tongue Turkish\r\n\r\nAddress:\r\nWork:University of Istanbul,Faculty of Dentistry, Department of Oral Surgery and Oral Medicine 34093 Capa,Istanbul- TURKIYE",institutionString:null,institution:{name:"Istanbul University",country:{name:"Turkey"}}},{id:"171887",title:"Prof.",name:"Zühre",middleName:null,surname:"Akarslan",slug:"zuhre-akarslan",fullName:"Zühre Akarslan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/171887/images/system/171887.jpg",biography:"Zühre Akarslan was born in 1977 in Cyprus. She graduated from Gazi University Faculty of Dentistry, Ankara, Turkey in 2000. \r\nLater she received her Ph.D. degree from the Oral Diagnosis and Radiology Department; which was recently renamed as Oral and Dentomaxillofacial Radiology, from the same university. \r\nShe is working as a full-time Associate Professor and is a lecturer and an academic researcher. \r\nHer expertise areas are dental caries, cancer, dental fear and anxiety, gag reflex in dentistry, oral medicine, and dentomaxillofacial radiology.",institutionString:"Gazi University",institution:{name:"Gazi University",country:{name:"Turkey"}}},{id:"272237",title:"Dr.",name:"Pinar",middleName:"Kiymet",surname:"Karataban",slug:"pinar-karataban",fullName:"Pinar Karataban",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/272237/images/8911_n.png",biography:"Assist.Prof.Dr.Pınar Kıymet Karataban, DDS PhD \n\nDr.Pınar Kıymet Karataban was born in Istanbul in 1975. After her graduation from Marmara University Faculty of Dentistry in 1998 she started her PhD in Paediatric Dentistry focused on children with special needs; mainly children with Cerebral Palsy. She finished her pHD thesis entitled \\'Investigation of occlusion via cast analysis and evaluation of dental caries prevalance, periodontal status and muscle dysfunctions in children with cerebral palsy” in 2008. She got her Assist. Proffessor degree in Istanbul Aydın University Paediatric Dentistry Department in 2015-2018. ın 2019 she started her new career in Bahcesehir University, Istanbul as Head of Department of Pediatric Dentistry. In 2020 she was accepted to BAU International University, Batumi as Professor of Pediatric Dentistry. She’s a lecturer in the same university meanwhile working part-time in private practice in Ege Dental Studio (https://www.egedisklinigi.com/) a multidisciplinary dental clinic in Istanbul. Her main interests are paleodontology, ancient and contemporary dentistry, oral microbiology, cerebral palsy and special care dentistry. She has national and international publications, scientific reports and is a member of IAPO (International Association for Paleodontology), IADH (International Association of Disability and Oral Health) and EAPD (European Association of Pediatric Dentistry).",institutionString:null,institution:null},{id:"172009",title:"Dr.",name:"Fatma Deniz",middleName:null,surname:"Uzuner",slug:"fatma-deniz-uzuner",fullName:"Fatma Deniz Uzuner",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/172009/images/7122_n.jpg",biography:"Dr. Deniz Uzuner was born in 1969 in Kocaeli-TURKEY. After graduating from TED Ankara College in 1986, she attended the Hacettepe University, Faculty of Dentistry in Ankara. \nIn 1993 she attended the Gazi University, Faculty of Dentistry, Department of Orthodontics for her PhD education. After finishing the PhD education, she worked as orthodontist in Ankara Dental Hospital under the Turkish Government, Ministry of Health and in a special Orthodontic Clinic till 2011. Between 2011 and 2016, Dr. Deniz Uzuner worked as a specialist in the Department of Orthodontics, Faculty of Dentistry, Gazi University in Ankara/Turkey. In 2016, she was appointed associate professor. Dr. Deniz Uzuner has authored 23 Journal Papers, 3 Book Chapters and has had 39 oral/poster presentations. She is a member of the Turkish Orthodontic Society. 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Finally, the tissue engineering subcategory will support topics such as the fundamentals of stem cells and progenitor cells and their proliferation, differentiation, bioreactors for three-dimensional culture and studies of phenotypic changes, stem and progenitor cells, both short and long term, ex vivo and in vivo implantation both in preclinical models and also in clinical trials.",annualVolume:11405,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/9.jpg",editor:{id:"126286",title:"Dr.",name:"Luis",middleName:"Jesús",surname:"Villarreal-Gómez",fullName:"Luis Villarreal-Gómez",profilePictureURL:"https://mts.intechopen.com/storage/users/126286/images/system/126286.jpg",institutionString:null,institution:{name:"Autonomous University of Baja California",institutionURL:null,country:{name:"Mexico"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"35539",title:"Dr.",name:"Cecilia",middleName:null,surname:"Cristea",fullName:"Cecilia Cristea",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYQ65QAG/Profile_Picture_1621007741527",institutionString:null,institution:{name:"Iuliu Hațieganu University of Medicine and Pharmacy",institutionURL:null,country:{name:"Romania"}}},{id:"40735",title:"Dr.",name:"Gil",middleName:"Alberto Batista",surname:"Gonçalves",fullName:"Gil Gonçalves",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYRLGQA4/Profile_Picture_1628492612759",institutionString:null,institution:{name:"University of Aveiro",institutionURL:null,country:{name:"Portugal"}}},{id:"211725",title:"Associate Prof.",name:"Johann F.",middleName:null,surname:"Osma",fullName:"Johann F. 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