Comparison of Time to Detection of MMO-MUG (Colilert®) with and without phycoccolloids. CFU (colony forming units), NTO (non-target organisms), Neg (negative)
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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.
\\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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IntechOpen and Knowledge Unlatched formed a partnership to support researchers working in engineering sciences by enabling an easier approach to publishing Open Access content. Using the Knowledge Unlatched crowdfunding model to raise the publishing costs through libraries around the world, Open Access Publishing Fee (OAPF) was not required from the authors.
\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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It is a complex subject, involving the use of many interdisciplinary modern sciences and technologies that became art, science and business. Revolutionary developments in plant genetics and genomics and coupling plant "omics" achievements with advances on computer science and informatics, as well as laboratory robotics further resulted in unprecedented developments in modern plant breeding, enriching the traditional breeding practices with precise, fast, efficient and cost-effective breeding tools and approaches. The objective of this Plant Breeding book is to present some of the recent advances of 21st century plant breeding, exemplifying novel views, approaches, research efforts, achievements, challenges and perspectives in breeding of some crop species. The book chapters have presented the latest advances and comprehensive information on selected topics that will enhance the reader\'s knowledge of contemporary plant breeding.',isbn:null,printIsbn:"978-953-307-932-5",pdfIsbn:"978-953-51-4381-9",doi:"10.5772/1389",price:139,priceEur:155,priceUsd:179,slug:"plant-breeding",numberOfPages:366,isOpenForSubmission:!1,isInWos:1,isInBkci:!0,hash:"00fb30196097697f0e1211ce27ba426d",bookSignature:"Ibrokhim Y. Abdurakhmonov",publishedDate:"January 11th 2012",coverURL:"https://cdn.intechopen.com/books/images_new/880.jpg",numberOfDownloads:89224,numberOfWosCitations:208,numberOfCrossrefCitations:91,numberOfCrossrefCitationsByBook:3,numberOfDimensionsCitations:246,numberOfDimensionsCitationsByBook:3,hasAltmetrics:1,numberOfTotalCitations:545,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"February 15th 2011",dateEndSecondStepPublish:"March 15th 2011",dateEndThirdStepPublish:"July 20th 2011",dateEndFourthStepPublish:"August 19th 2011",dateEndFifthStepPublish:"December 17th 2011",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,8,9",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"213344",title:"Prof.",name:"Ibrokhim Y.",middleName:null,surname:"Abdurakhmonov",slug:"ibrokhim-y.-abdurakhmonov",fullName:"Ibrokhim Y. Abdurakhmonov",profilePictureURL:"https://mts.intechopen.com/storage/users/213344/images/system/213344.jpg",biography:"Ibrokhim Y. Abdurakhmonov received his B.S. (1997) in biotechnology from the National University, M.S. in plant breeding\n(2001) from Texas A&M University of USA, Ph.D. (2002) in molecular genetics, Doctor of Science (2009) in genetics, and full professorship (2011) in molecular genetics and molecular biotechnology from Academy of Sciences of Uzbekistan. He founded (2012)\nthe Center of Genomics and Bioinformatics of Uzbekistan. He\nreceived the 2010 TWAS prize, and “ICAC Cotton Researcher of the Year 2013” for\nhis outstanding contribution to cotton genomics and biotechnology. He was elected\nas The World Academy of Sciences (TWAS) Fellow (2014) and as a member (2017)\nof the Academy of Sciences of Uzbekistan. 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\r\n\tThe solution to many real-world problems lies in optimizing processes, parameters, or techniques, among many others. However, these optimizations usually mean dealing with immense search spaces, so exhaustive methods that may evaluate all possible solutions looking for the global optimum are intractable. Besides, many local optima may exist in the search space, so simple techniques may get stuck in them. Evolutionary algorithms and, more concrete, genetic algorithms are metaheuristic techniques inspired by Darwin's natural selection of species theory to solve search-based optimization problems, which has been demonstrated to effectively deal with complex search spaces. Genetic algorithms employ a population of individuals, each representing a full or partial solution to the problem, bred and reproduced looking for optimal individuals. Then, according to a fitness function, these individuals are evaluated, which determines how a given individual adapts to the problem at hand.
\r\n\r\n\tIn recent years, genetic algorithms have advanced by proposing novel algorithmic flows, representations, or specific techniques inside the main structure of the algorithm. As a result, genetic algorithms have been successfully applied to solve many real-world problems (engineering, smart cities, and energy). They have also helped to improve many machine learning (classification, regression, or hyperparameter optimization) and data mining (data preprocessing, pattern mining, or feature selection) techniques.
\r\n\r\n\tThis book intends to provide the reader with a comprehensive overview of the current state-of-the-art and advances in genetic algorithms and present the fields in which they have been applied throughout the years.
",isbn:"978-1-80355-178-4",printIsbn:"978-1-80355-177-7",pdfIsbn:"978-1-80355-179-1",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,isSalesforceBook:!1,hash:"f4b901b86a55bdb037d1d941db8868fa",bookSignature:"Dr. Sebastian Ventura Soto, Dr. José M. Luna and Dr. Jose M. Moyano",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/10694.jpg",keywords:"Evolutionary Algorithms, Smart Mobility, Smart Cities, Data Mining, Machine Learning, Hyper-Parameter Optimization, Architecture Optimization, Data Preprocessing, Pattern Mining, Feature Selection, Genetic Operators, Genetic Encoding",numberOfDownloads:28,numberOfWosCitations:0,numberOfCrossrefCitations:0,numberOfDimensionsCitations:0,numberOfTotalCitations:0,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"August 25th 2021",dateEndSecondStepPublish:"September 22nd 2021",dateEndThirdStepPublish:"November 21st 2021",dateEndFourthStepPublish:"February 9th 2022",dateEndFifthStepPublish:"April 10th 2022",remainingDaysToSecondStep:"8 months",secondStepPassed:!0,currentStepOfPublishingProcess:5,editedByType:null,kuFlag:!1,biosketch:'A researcher in Artificial Intelligence and Computing Sciences, Dr. Ventura has authored more than ten books and over 300 articles in journals and scientific conferences(H-index of 37)and is a holder of a patent "Remote Control System for People with Disabilities". He is the head of the KDIS research group and a Senior Member of IEEE Computer, the IEEE Computational Intelligence, and the IEEE Systems, Man, and Cybernetics Society, and the ACM.',coeditorOneBiosketch:"A pioneering researcher in the use of Evolutionary Computation on Pattern Mining, Dr. Luna obtained his Ph.D. with a grade of summa cum laude in Computer Science and with a grant from the Spanish Ministry of Education. For his exceptional research efforts, Dr. Luna has also been awarded a JdC - training PostDoc grant financed by the Ministry of economy and competitiveness (Government of Spain).",coeditorTwoBiosketch:"An enthusiastic researcher in Machine Learning and Evolutionary Computation Models whose doctoral thesis was developed enrolled in a dual Ph.D. program at both University of Córdoba (Spain) and Virginia Commonwealth University (USA), and supervised by Eva L. Gibaja, Krzysztof J. Cios, and Sebastián Ventura. 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One barrier to the utilization of new methods has been the need for an 18 to 24 hour incubation time. One form of the MMO-MUG, Colilert-18®, has a shorter incubation time than the original but requires an inconvenient and time consuming pre-heating step. Employing a new strategy that fosters the development of biofilm by incorporation of inert natural particles in the sample was reported to significantly reduce the incubation time of the MMO-MUG drinking water tests and other microbiological analyses.
The natural particles (see Figure 1) are made as a dried hydrophilic colloid extract obtained from
The particles are a heterogeneous natural mixture:
High resolution photomicrograph of the phycocolloid particles (Colloidands®, Pilots Point LLC, Sarasota, FL)
A study was conducted with the original MMO-MUG (Colilert®) to determine if from cold water < 8°C the incorporation of the particles could significantly reduce detection time of total coliforms and
In order to establish that the particles were acting as a physical catalyst, the Colisure® variation of the MMO-MUG test was used. This test uses a yellow/gold beta-galactosidase substrate that becomes red/magenta when positive. Accordingly, the exact physical location of the beginning of the development of color could be directly determined photographically.
Colloidands® particles (Pilots Point LLC, Sarasota, FL) were added to the Colisure® test at 10 grams per liter. Both the standard Idexx
Figure 2 and Figure 3 describe the complete protocol by which the MMO-MUG (Colilert®) was examined for its ability to detect 1 total coliform and 1
Test Protocol Part I for the detection of 1 total coliform
Test Protocol Part II for the detection of 1 total coliform
Analysis was made both by visual observation and also by an instrument. Visual observation: Yellow color development (for total coliforms and
Instrumented Analysis: Figure 4 presents the Pilots Point Monitor (Pilots Point LLC, Sarasota, FL) that was used. This instrument utilizes white light sent through a sample and determines the change in three parameters: Luminosity, or white to black (a measure of turbidity), called the “L” value; a change from red to green (called the “a” value), and a change from blue to yellow (called the “b” value). See Figure 5. Measurements are made every 15 minutes. The instrument can measure light changes from 365 nm through the visible spectrum therefore it can detect both the color change produced by total coliforms and the fluorescence produced by
Pilots Point Monitor® (PPM60®)
Principle of Pilots Point Instrument
Lake source water from the supply to the Regional Water Authority (New Haven, CT) was obtained. While protected from human intrusion, there are abundant animal life, particular deer, rabbit, and small animals. This is the same water source that was used in the original certification of the MMO-MUG test [4].
The same protocol as for the quality control bacteria described in the protocol (see Figure 2 and Figure 3) was used. To avoid possible enhancement of enzyme stimulation by the substrates present in the MMO-MUG formula, the source water samples were processed by the classical membrane filtration method as described in Standard Methods [5]. Bacteria consistent with total coliforms and
Figure 6 presents the results of the Colloidands® particle analysis. The top tube is inoculated with Idexx
Growth of total coliform
Table 1 and Graph 1 present the visual observation of the Colilert® test with and without phycocolloid particles at low numbers of
\n\t\t\t\t | \n\t\t
Comparison of Time to Detection of MMO-MUG (Colilert®) with and without phycoccolloids. CFU (colony forming units), NTO (non-target organisms), Neg (negative)
\n\t\t\t\t | \n\t\t
Comparison of Time to Detection of MMO-MUG (Colilert®) with and without phycoccolloids with
\n\t\t\t\t | \n\t\t
Comparison of Time to Detection of MMO-MUG (Colilert®) with and without phycoccolloids with
\n\t\t\t\t | \n\t\t
Comparison of Time to Detection of MMO-MUG (Colilert®) with and without phycoccolloids with
Figure 7 presents the actual pictures of the replicates of the analysis of the Colilert® test to detect 1 bacterium per 100 mL. As can be seen, each of the 100 mL samples was clearly positive. As shown in Figure 6, the particle layer at the bottom of the water collection vessel is densely colored. The liquid is also clearly positive.
Figure 8 and Figure 9 present the results of the testing shown in Figure 7 as follows: from the 100 mL samples in Figure 7, 1 mL of supernatant was added to a 13 x 100 mm polystyrene test tube and placed in the PPM instrument. Readings in the PPM instrument were taken and a definite change in the “L”, “a”, and “b” values can be seen which indicate positive results for both quality control Idexx
In all configurations – 1 mL in a test tube and 100 mL in a water collection vessel – the phycocolloids significantly decreases the time to detect the quality control Idexx total coliform
Replicate Testing with Idexx Quality Control
PPM Readings of 10 Quality Control
PPM Readings of 10 Quality Control
Figure 10 and Figure 11 present 1 mL duplicate data from the PPM instrument on detection of 10 bacteria per mL of Idexx
Actual PPM Data for detection of Idexx
Actual PPM Data for detection of Idexx
Since the introduction of the MMO-MUG (Colilert®) test in 1989 for the simultaneous detection of total coliforms and
The two types of bacteria that generally exist are describes as either sessile (a unit that attaches to a surface or exist in a biofilm) or planktonic (existing freely in bulk solution). Antonie van Leuwenhoek described biofilms in 1674 as “animalcules” through observation of material scraped from human tooth surfaces with his microscope, but with advances in technology, biofilms can more accurately be described [6]. Biofilms can be described as microbial communities that are sessile and grow on surfaces surrounded by a matrix of extracellular polymeric substances; microcolonies are distinct communities of bacterial cells of one or many different species that are surrounded by a matrix. The advantages of biofilm formation by bacteria is that it provides protection against antibiotics, disinfectants, and environments that are constantly changing [7]. The key to the catalyst activity of the phycocolloids is their ability to interact with the bacteria and the attendant production of microcolonies. The bacteria multiply much faster when attached to the particles as microcolony biofilm.
The micro particles increase the surface area in the liquid broth and allow microbes that multiply in vitro to establish a biofilm. In effect, the micro particles act in an analogous way as a catalyst does in a chemical reaction. In the microbiology area, the micro particles provide multiple attachment surfaces for the microbes to "establish residence". Microbes prefer surfaces on which to grow and multiply rather than being free in a liquid environment. For example, the microbes may experience quorum sensing, which accelerates the generation of a biofilm. The biofilm is produced when the microbes multiply, and it yields colonies of microbes that are held together by external capsules, pili, and glycocalyxes of the microbes which, in the broad context, are surface components, such as polysaccharides, proteins and/or mixtures thereof. The micro particles are static, in that they are not consumed but serve as a physical structure that provides shelter and attachment and promotes the multiplication and expression of the target microbe. There may be attached nutritive elements on the micro particles that serve to stimulate the development of the bacterial nidus. The micro particles may be colloidal, in suspension, or a combination. Any materials or structures that encourage the growth of microbes on a biofilm are highly preferred for use in this invention. Supporting the catalytic activity of the phycocolloids is the observation that growth starts first at the bottom of the test tubes, where particles have gravitationally settled and microbial biofilms have developed, attached to the particles. Additional particles are distributed with the remainder of the admixture, but have not yet been associated with metabolizable substrate creating a color change. The image of the test tubes illustrates well how the particles expedite the detection of the bacteria (i.e.,
This report demonstrates that phycocolloids introduced into the classical Colilert® formula significantly decreases the time to a positive. By visual observation with both standard quality control
The 16 hour benchmark is particularly important for laboratory work flow. It provides the ability to perform a 4 to 8 test – in by 4 pm, finished by 8 am, the optimum for the work flow. Further enhancing the time to detection is the use of the PPM instrument. With it, detection of 1 total coliform and 1
A recent survey was taken in the UK, reported 4,884 deaths from a brain tumor and about 11,633 deaths from breast cancer. The tumor detection is complicated and earlier detection leads to better chances of effective treatment, thereby increasing the survival rate. In the last decade, the concept of imaging has raised by the discovery of the X- ray radiography technique. The imaging techniques are highly meant for diagnostic applications in medical field. Different parts of a body have different range of absorption level hence the penetration of propagating light photon level varies for each and every organ, whereas this is the major concept considered for imaging. The imaging trend started with the X- ray radiography [1], it provides a one-dimensional image of the bony structures in a photographic film which could give the visualization of bony defects and the soft tissue tracks are identified only after the administration of contrast agents or dyes. The advanced version of the X- ray radiography is the Digital Radiography system which also provides a single plane image and it has the additional features such as data collection system, processing, display and storage system. Here the data obtained can be stored in a memory for future use. The limitation is even after the dye usage only the large variations in soft tissues can be identified.
In X - ray computed tomography the imaging of the organ is done in various angles and the reconstruction is demonstrated mathematically over the computer and displayed on the monitor. For the soft tissue examination, the dye fluids are pumped into the ventricles for providing the variation or contrast in the image. Here the noise increases inherently over the square root of the dose as the dose must be increased to preserve the same amount of noise. Therefore, over dosage leads to the side effects such as skin allergy, then came the existence the nuclear imaging.
Nuclear Medical Imaging (NMI) [1] systems utilize the radioisotopes for imaging. The small amount of radioactive chemicals is injected into the arm vein or inhaled through, and then the amount of radioactivity of the organ is examined using the radiation detectors. NMI includes Emission Computed Tomography which displays the single plane slice of the object with radioactivity, insisting same as.
X - ray computed tomography. In Single Positron Emission Tomography, gamma camera is used to create a three-dimensional representation of the radioisotope injected organ. Positron Emission Tomography (PET) imaging provides the cross- sectional images of positron emitting isotopes, which demonstrate the biological function and even physiological and pathological characteristics. The injected radioisotope may create allergic reactions and it takes hours to get clear from the blood and it’s a time-consuming process.
Magnetic Resonance Imaging (MRI) uses a magnetic field and high radio frequency signals to obtain anatomical information about the human body as cross- sectional images. The imaging technique needs the subject to be still while imaging, when there occurs a move and it blurs the output image. Radiations utilized here are highly ionized which causes harm and it is a tremendous time consuming and cost inefficient process for early tumor detection. The Ultrasonic imaging system is used for obtaining images of an almost entire range of internal organs in the abdomen. While it is completely reflected at boundaries with gas and there is a serious restriction in investigation of and through gas containing structures. The ultrasonic waves could not penetrate the bony structures hence imaging the brain is impossible.
Diffuse Optical Tomography (DOT) [2, 3] employs near infra-red light of range 700-1000 nm [4] which is non-invasive and non-ionizing radiation, therefore causes no harm or side effects. It has its main application of imaging the soft tissue organs such as the brain and breast for diagnosing tumor using the biological parameters [5, 6] such as oxygenation etc. The brain and breast tumor or lesion can be detected by examining the oxygenated, deoxygenated hemoglobin, water and lipids (proteins). DOT imaging [7] provides a number of advantages, such as reduced size setup in turn lead to portability, real-time imaging, low instrumental cost and less time consumption when compared to the other imaging techniques but is generally known to have a low image resolution which limits its further clinical application. Table 1: Compares Biomedical Imaging Modalities- Diffuse optical tomography evaluated with Computer Tomography (CT), Magnetic Resonance Imaging (MRI), and Positron Emission Tomography (PET). The parameters namely cost, imaging time, size, sensitivity and specificity are compared.
Parameters | DOT | CT | MRI | PET |
---|---|---|---|---|
$150,000 | $300,000 | $1,000,000 | $1,446,546 | |
15–20 mins | 45–60 mins | 45–70 mins | 75–90 mins | |
60 x 45 cm | 50 x 50 cm | 4x4m | 25x36x17cm | |
50% | 90% | 91% | 93% | |
100% | 56% | 71% | 70% |
Comparison of biomedical imaging modalities.
The main absorbers of near-infrared (NIR) light in blood-perfused tissues are Oxy-hemoglobin, deoxyhemoglobin, Lipids (Bulk proteins) and water. NIR Spectral Window absorption spectra are between 650 and 1000 NM are shown in Figure 1 is obtained from compiled absorption data for water [8] and hemoglobin [9]. Hence, light in this spectral window penetrates deeply into tissues, thus allowing for non-invasive investigations. The NIR light penetration depth into tissues is limited, by the hemoglobin absorption at shorter wavelengths and by the water absorption at longer wavelengths.
Absorption spectra of deoxy-hemoglobin (Hb), oxy-hemoglobin (HbO2), lipids and water.
Different systems in DOT are Continuous Wave (CW) imaging [6], Time Domain (TD) and Frequency Domain (FD). Continuous imaging is the study of hemodynamic and oxygenation changes in superficial tissues. It requires a source of constant intensity modulated at low frequency. Measuring the intensity of light transmitted between two points on the surface of the tissue is economical. Optimum sensitivity is achieved by a number of distinct sources and detectors. Intensity measurements are sensitive and are unable to distinguish between the absorption and scattering effects. Time Domain (TD) system uses photon counting detectors, slow but highly sensitive. The temporal distribution of photons is produced in short duration. Short pulses of light are transmitted through a highly scattering medium known as a Temporal Point Spread Function (TPSF). Frequency Domain (FD) [9] system is relatively inexpensive, easy to develop and provides fast temporal sampling up to 50HZ.The system acquires quick measurements regarding the amplitude and phase of scattering and absorption in the frequency domain at high detected intensities.
The NIR light propagates within the biological tissue in a turbid medium [5]. Light particles scatters with cell particles and the medium either absorbs or scatter the light. The positions and orientations of scatters are described by mesoscopic and macroscopic. In mesoscopic the particles in turbid media of dense concentration and light transport are modeled by Radiative Transport Equation (RTE) [3]. In macroscopic photon transport on mean free path, diffusion approximation holds good for turbid media. Therefore, the isotropic scattering effect and light transport within the tissues is described by the diffusion Equation.
Light transport in tissues derived using RTE, assumes the energy particles do not change in collisions hence refractive index is constant with the medium [8]. RTE is used to describe anisotropic field and the photon propagation in tissue, is given by
I(r,
f (
where θ is the angle between the two directions ŝ and ŝ’, and g is the anisotropy factor which is used to characterize the angular distribution of tissue scattering.
The fluence at point r modulation frequency ω and in the direction ŝ is defined by
The Monte Carlo Method is used to solve the radiative transfer Equation.
The directional flux magnitude is less compared to isotropic fluence magnitude within the tissue. The light field ‘diffuses’ means the scattering interaction dominates over absorption. The diffusion equation [10] approximation is given as
Diffusion coefficient is described as
Where the reduced scattering coefficient is
Analytical model has fast computation and the Green’s function is applied for modeling the diffusion equation or RTE analysis. The Green’s function provides a solution when the source is a spatial and temporal function. It is commonly used to solve the forward problem for image reconstruction, specifically for fast imaging techniques. Optical properties are modeled by a green’s function [3] for a slab representing the homogeneous background; with an additional perturbation term represent the spherical insertion.
Models the individual photon with Poisson error incorporated in the model. Monte Carlo method is a gold standard statistical technique in diffuse optics. The geometry of the model is defined by μa, μs, the refractive index and the photon trajectories. Light propagation in non- diffusive domains is calculated by Monte Carlo techniques. Random walk theory provides a distinct approach in which photon transport is modeled as a series of steps on the discrete cubic lattice. Random walk theory [9] is particularly suited to model time-domain measurements. The random walk extension technique has been developed for modeling media with anisotropic optical properties, maintaining the cubic lattice.
Numerical techniques have the potential for modeling complex geometries. Finite Element Method (FEM) [8] is used to represent the inhomogeneous distribution [12] of optical properties in an arbitrary geometry. Boundary Element Method (BEM) [3], Finite Difference Method (FDM) and Finite Volume Method (FVM) are applied in more specialized applications. Finite Element Method divides the reconstruction domain into finite element meshes. The optimal computational efficiency of FEM depends on the smallest number of elements to represent the internal field by a finite element mesh. Adaptively refine the mesh by placing more elements when the field changes rapidly.
The ill-condition inverse problem [5] in image reconstruction provides poor localization of imaging in localized or sparse regions. To overcome the ill posed problem in inverse model, regularization is applied in inverse model. The various forms of regularization are standard/Tikhonov regularization, exponential/spatial regularization, generalized least mean square regularization, adaptive regularization and model-based regularization [8, 11, 13, 14, 15].
Standard regularization [16] or constant regularization is of Tikhonov type. Here the regularization is based on the already available information that may be the noise characteristics [11] or structural information [17] of the data, more prior information [13] usage leads to a better outcome of reconstruction procedure or robustness to the noise in the data.
λ is a regularization parameter (i.e.) constant chosen to stabilize the solution and its value varies from 1e-6 to 10.
The ill posed problem with inverse model is solved by adding the penalty term to the objective function.
y = ln (A) is the measured experimental data here A specifies the amplitude, G (μa) modeled data and penalty term is P(μa) removes the high frequency components. Iteratively linearization minimizes “Ω” by
L is the dimensionless matrix and μ0 is prior estimate. The penalty term minimization scheme along with linearization leads to the updated equation (Gauss-Newton update equation)
‘J’ is a Jacobian ∂G (μa) / ∂ (μa) gives the rate of change with modeled data with respect to μa and I represent the Identity matrix. The diffuse optical tomography inverse problem sets a least square problem, which is solved by matching experimentally measured boundary data with modeled data iteratively.
Linearization of the as in (7) leads to an updated equation.
The
In adaptive regularization [15] the regularization parameter λ varies with respect to the projection error [18]. Projection error Φ is defined as the difference in measured data in the modeled data which is expressed as in (12).
The regularization parameter λ is denoted as
The regularization parameter λ varies in the range from 1/3 to 1/2. As in (13) ‘e’ represents the exponential function and ∆Φ representing the change in projection error. A penalty term for projection error-based regularization is expressed as
Linearization leads to an updated equation.
As in Eq. (15) ∆μ represents the change in absorption coefficient. Projection error determines the accuracy, while JJT is denoted as the Hessian matrix with diagonal elements.
Exponential regularization is otherwise called as spatially varying regularization [14] or wavelength chromophore specific regularization, which is based on the physics of the problem. This simplicity makes it widely used for solving inverse problems especially in the cases where the prior information is not available. λ(r) is spatially varying regularization parameter, where r represents the position spatially. The spatial variation is attained by an exponential function in the form
As in (16) the radius of imaging domain is R, λc, λe are the regularization parameters at the edge and center of the location. The spatially varying regularization has exponential term with low value at the center and large value near the boundary of the imaging domain in-order to neutralize the hypersensitivity near the boundary, which appears due to detectors located at the boundary. In order to determine the regularization parameter λ(r), the generalized objective function is given as,
As in (17) L is a dimensionless regularization matrix and μ0 is the prior estimate the of properties, while the penalty term for exponential regularization is represented as
Linearizing (17) leads to a Jacobian updated equation as
Exponential Regularization captures the hessian matrix diagonal as JTJ.
Model based regularization utilizes the combination of model resolution matrix [19] and data resolution matrix. The objective is to match the modeled data with the observed data. By this method of regularization, the spatial resolution of the reconstructed image is improved [18].
Expanding using Taylor series gives the equation
Jacobian matrix J = G′ (μa) and Hessian matrix H = G″ (μa).
Linearizing (21) then
using y - G (μa0) = δ and
Change in absorption coefficient (Δμa) is derived as in (18) as
In the case of λ = 0
Regularization term is linearized using the model resolution matrix, which depends on the forward model and regularization but not on data. Because of the ill posed nature of the problem as in (25) λ > 0, then
As in Eq. (24) leads to a model resolution matrix.
As in (27) M has the dimension of NN x NN and it purely depends on JTJ and the regularization term used. Linearization of as in (27) leads to an updated Jacobian matrix. λ varies from 0 to 1.
The regularization parameter of a model resolution matrix is given as
The model resolution matrix can be applied for deriving the linearization as in (26) for both constant and spatially varying regularization parameters. The matrix varies for constant and spatially varying regularization. The model resolution matrix main aim is to provide the better resolution characteristics without depending on data.
The data resolution matrix concentrates only on the data not on the image characteristics [21]. It defines that how well the estimated Δμa fits the observed data, hence it is important to consider data too in order to improve the resolution characteristics.
Data resolution matrix is derived using the Jacobian matrix (J) and the regularization technique which is used for reconstruction. It is evaluated by matching the predicted data with the obtained data [22].
The data-resolution matrix does not depend on a specific data (y) or error in it but are exclusively the properties of J and the regularization (λ) used. The closer it is to the identity matrix, the smaller are the prediction errors for δ, where δ` as in (31) representing the data misfit.
Data resolution matrix D is given as
Linearizing (31) leads to an updated equation
The regularization parameter of a data resolution matrix is given as
As in (26) and as in (34) the regularization parameter of the model-based regularization λi is given as
Penalty term for the regularization scheme is given as
Where c provides the weight for penalty term and it is a constant term.
Newton - Raphson iterative method to find the optical parameter μa, μs by solving the minimum objective function.
Φm and Φc are calculated and measured radiance at the detectors. λ is regularization parameter, μ, μ0 are current and initial estimates of optical properties at each node.
The initial values of absorption and scattering properties were estimated homogenously [23]. Update
∆μ Optical parameter update vector, Hmax maximum main diagonal element value of the matrix JJT. J is Jacobian matrix for inverse problem plots the variation in log amplitude and phase for both absorption and diffusion modification in every node.
Jacobian matrix J has the size as number of measurements NM by the number of FEM nodes NN i.e. NM x NN is calculated using ad joint method. Limit the Jacobian [23, 24] to the measured amplitude data and optical absorption. Jacobian links a change in log amplitude, at the boundary with a change in absorption coefficient μa.
The size of the Jacobian matrix is reduced by calculating the total sensitivity throughout the imaging domain and a new Jacobian
‘j’ corresponds to a node number within the domain. Reduction of Jacobian matrix improves the computational speed and efficiency of image reconstruction.
Ill posed condition of DOT problem, the solution is robust. To overcome this problem a priori information is incorporated constraint in the space of unknowns. Bayesian approach proposes an algorithm for spatial physiological prior [26]. High resolution anatomical image is segmented into sub-images. Each image is assigned a mean value with a prior probability density function of the image. ‘Confidence level’ is defined in the form of an image variance formulation to allow local variations within sub-images. MAP (Maximum a posteriori) estimates of the image [26, 27] is formed based on the formulation of the image’s probability density function.
p(y/x) is log likelihood function; p(x) is a probability density function.
Alternating minimization algorithm sequentially updates the unknown parameters, solves the optimization problem. Probability density function of the ith sub-image is defined in the spatial prior as
M is number of sub regions, Ni is number of voxels in the ith sub image, xi is the unknown sub image, Ci is chromosphere mean concentration,
The confidence level is incorporated into the statistical reconstruction procedure, the sub-image variance.
The practical setup of image acquisition as shown in Figure 2 includes optical components, electrical components, control, data acquisition and image reconstruction [28].
The practical imaging system.
The optical Multiplexer has three parts namely the motor, drive and Black box (PMT) Photon multiplier tube. Driver rotates the optical multiplexer to guide the energy to PMT, which converts light to electrical signals. The signal is amplified by an Amplifier and preprocessed electrical signals are given to Data acquisition card. Data acquisition software samples the raw data, post process and controls the hardware. The personal computer delivers commands to alter the fiber switch (source channel) sequentially. 16 X 16 input and output fibers constitutes to 256 sources – detector pairs. Image is reconstructed using inverse modeling such as Jacobian reduction with FEM.
The optical Multiplexer has three parts namely the motor, drive and Black box (PMT) Photon multiplier tube. Driver rotates the optical multiplexer to guide the energy to PMT, which converts light to electrical signals. The signal is amplified by an Amplifier and preprocessed electrical signals are given to Data acquisition card. Data acquisition software samples the raw data, post process and controls the hardware. The personal computer delivers commands to alter the fiber switch (source channel) sequentially. 16 X 16 input and output fibers constitutes to 256 sources – detector pairs. Image is reconstructed using inverse modeling such as Jacobian reduction with FEM.
Artificial Neural Network (ANN) is data structure accurately approximates a nonlinear relationship between a set of input and output parameters. It maps the input optical properties for spatial frequency domain in inverse modeling. Perform Monte Carlo simulation and fit it to ANN to output the data. Neural Network is trained to predict the tissue reflectance for strongly and weakly absorbing media.
The parallel Back propagation neural network distinguishes nonlinear relationship between spatial location of tumors and light intensity around the boundary of the tissue [29]. The neural network is trained for fast reconstruction in diffuse optical tomography. Location and spacing of optical sources and detectors are optimized using neural network. To improve the resolution of DOT images in inverse model Fixed Grid Wavelet Network [30] image segmentation is applied to extract a smooth boundary in tumor images.
Reconstruction of optical in homogeneities embedded in turbid medium using diffuse optical tomography. The optimization problem is solved by using genetic algorithm minimizing objective function [31, 32]. This approach is applied for full non- linear range of quantitative reconstruction. Crosstalk near the source detector artifacts are the major inaccuracies in diffuse optical tomography images [33]. This problem can be solved by a global optimization method namely genetic algorithm for estimating the optical parameters.
Adaptive Neuro fuzzy Inference system can be used for optical imaging, solving the non-linear ill posed problem with accurate qualitative and quantitative optical image reconstruction. The proposed method using ANFIS architecture will provide fast and accurate optical image reconstruction hence can achieve classification accuracy, volume and the layer thickness measurement of tumor.
The simulation software for modeling diffuse optical tomography is CULA, NIRFAST NETGEN and MIMICS. CULA is GPU Accelerated Linear Algebra which has a parallel computing architecture to dramatically improve the computation speed of sophisticated mathematics and also contains routines for systems solvers, singular value decompositions and Eigen problems. For reconstruction in diffuse optical tomography it facilitates singular value decomposition, matrix multiplication, matrix inversion etc.
NIRFAST is Near Infrared Fluorescence and Spectroscopy Tomography [33, 34] which is an FEM based software package designed for modeling Near Infrared Frequency domain [35] light transport in tissue.
NETGEN [36] is an automatic 3D tetrahedral mesh generator which accepts input from Constructive Solid Geometry (CSG) or Boundary Representation (BR) from the STL (Stereo Lithography) file format. It contains modules for mesh optimization and hierarchical mesh refinement and it is also open-source software available for Unix/Linux and Windows.
MIMICS is software specially developed for medical image processing. The ROI (Region of Interest) is selected in the segmentation process which is converted to a 3D surface model using an adapted marching cubes algorithm that takes the partial volume effect into account, leading to very accurate 3D model. The 3D files are represented in the STL format.
The Diffuse Optical Tomography (DOT) imaging experimental setup has three kinds of noise namely thermal noise, shot noise and relatively intensity noise. The shot noise from dark current of photodetector has Poisson statistics, solved by using Bayesian network in inverse problem. DOT has undetermined problem due less measured data in the forward model compared to the pixels reconstructed in inverse model. The forward problem solved by FEM and regularization techniques to improve the spatial resolution of DOT images. Diffuse Optical Tomography (DOT) has significant advancement since it becomes faster, more robust, less susceptible to error, and able to acquire data at a number of wavelengths with more source–detector combinations. Images reconstructed in 3D, uses more sophisticated techniques, which can be adapted by incorporating prior information and by compensating for some of the unavoidable sources of measurement error. DOT imaging is still a laboratory-based technique, yet to progress to develop a handheld for detection of tumor in morphological tissues in clinical applications. Qualitative and quantitative accuracy has to be improved in DOT, both of which are limited by poor spatial resolution. Improved image quality is achievable by adopting the optimization techniques namely Artificial Neural Networks, Genetic Algorithm and Adaptive Neuro Fuzzy Inference System. Enhancement of DOT can also achieve higher performance using multimodal imaging techniques. DOT is as a low-cost, portable imaging system to be developed at the bedside. The best modeling and reconstruction methods provide an ideal DOT instrumentation.
The research was carried out in Department of Electronics and Communication and Department of Mechanical Engineering in SRM TRP Engineering College, Trichy, Tamil Nadu, India. We express our gratitude to our management, faculty and research scholars in SRM TRP Engineering College, Trichy, Tamil Nadu, India, who provided skill and proficiency that completely helped in the development of an optimized DOT instrument for detection of sarcoma cells. We are very grateful to Radiation Oncology Centre at Trichy SRM Medical College Hospital & Research Centre, Tiruchirappalli for providing the insights on tumor detection.
Our project promotes the social awareness on early tumor detection at cellular level. Diffuse Optical Tomography (DOT) provides harmless non-invasive detection of tumor cells. Today around 70% of people are suffering from sarcoma in soft tissue. Detection at earlier stage helps the patient for early diagnosis and prevents them from clinical pathology. We are interested to promote our review based on diffuse optical tomography instrumentation without any conflicts of interest as review article.
Disclosure of potential conflicts of interests.
Conflict of Interest: The authors declare that they have no conflict of interest.
Research involving human participants and/ or animals.
Ethical approval: “This chapter does not contain any studies with human participants or animals performed by any of the authors.”
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Shohel"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},subject:{topic:{id:"1394",title:"Applied Physics",slug:"applied-physics",parent:{id:"20",title:"Physics",slug:"physics"},numberOfBooks:4,numberOfSeries:0,numberOfAuthorsAndEditors:57,numberOfWosCitations:15,numberOfCrossrefCitations:12,numberOfDimensionsCitations:22,videoUrl:null,fallbackUrl:null,description:null},booksByTopicFilter:{topicId:"1394",sort:"-publishedDate",limit:12,offset:0},booksByTopicCollection:[{type:"book",id:"10082",title:"Accelerators and Colliders",subtitle:null,isOpenForSubmission:!1,hash:"7774bddf707cc21601de7051625e30b6",slug:"accelerators-and-colliders",bookSignature:"Ozan Artun",coverURL:"https://cdn.intechopen.com/books/images_new/10082.jpg",editedByType:"Edited by",editors:[{id:"255462",title:"Associate Prof.",name:"Ozan",middleName:null,surname:"Artun",slug:"ozan-artun",fullName:"Ozan Artun"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"8434",title:"Modern Applications of Electrostatics and Dielectrics",subtitle:null,isOpenForSubmission:!1,hash:"de3cc628456ab823927d4c8b640eee7f",slug:"modern-applications-of-electrostatics-and-dielectrics",bookSignature:"Dengming Xiao and Krishnaswamy Sankaran",coverURL:"https://cdn.intechopen.com/books/images_new/8434.jpg",editedByType:"Edited by",editors:[{id:"18115",title:"Dr.",name:"Dengming",middleName:null,surname:"Xiao",slug:"dengming-xiao",fullName:"Dengming Xiao"}],equalEditorOne:{id:"266293",title:"Dr.",name:"Krishnaswamy",middleName:null,surname:"Sankaran",slug:"krishnaswamy-sankaran",fullName:"Krishnaswamy Sankaran",profilePictureURL:"https://mts.intechopen.com/storage/users/266293/images/system/266293.jpeg",biography:"Dr. Krishnaswamy Sankaran is the Chief Executive Officer of Radical Innovations Group AB, a clean energy and circular economy infrastructure development company based in Finland. He is the winner of the 2020 Mission Innovation Champion Award under the flagship of 24 countries around the world plus European Commission for his pioneering work in Clean Energy and Circular Economy. He is an established industrialist and entrepreneur with several years of demonstrated track record in energy, utilities, infrastructure, manufacturing, and recycling industries. He has served in various operational and leadership roles in industries, the World Economic Forum, and the European Commission in more than sixteen countries and four continents. He is nominated by the Government of Finland for the prestigious 2020 Mission Innovation Champion Award, a global recognition for clean energy innovation (http://mission-innovation.net/)\n\nDr. Sankaran received a doctorate in Engineering Sciences from the Swiss Federal Institute of Technology ETH Zurich, Switzerland, a master’s degree from Karlsruhe Institute of Technology KIT, Germany, and a joint executive master’s degree in Organisational Development and Leadership from Wharton School, Columbia University, INSEAD, and London Business School. He has several years of training in yoga and Advaita Vedanta, an Indian traditional system of philosophy.",institutionString:"Radical Innovations Group - RIG",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"0",institution:null},equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"9202",title:"Novel Imaging and Spectroscopy",subtitle:null,isOpenForSubmission:!1,hash:"ac4eacbe6141ecaf009845bdaea0c0fa",slug:"novel-imaging-and-spectroscopy",bookSignature:"Jinfeng Yang",coverURL:"https://cdn.intechopen.com/books/images_new/9202.jpg",editedByType:"Edited by",editors:[{id:"263321",title:"Associate Prof.",name:"Jinfeng",middleName:null,surname:"Yang",slug:"jinfeng-yang",fullName:"Jinfeng Yang"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6140",title:"Accelerator Physics",subtitle:"Radiation Safety and Applications",isOpenForSubmission:!1,hash:"f68c778ce6d0271e05997c75618cd6b6",slug:"accelerator-physics-radiation-safety-and-applications",bookSignature:"Ishaq Ahmad and Maaza Malek",coverURL:"https://cdn.intechopen.com/books/images_new/6140.jpg",editedByType:"Edited by",editors:[{id:"25524",title:"Prof.",name:"Ishaq",middleName:null,surname:"Ahmad",slug:"ishaq-ahmad",fullName:"Ishaq Ahmad"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}],booksByTopicTotal:4,seriesByTopicCollection:[],seriesByTopicTotal:0,mostCitedChapters:[{id:"69493",doi:"10.5772/intechopen.89029",title:"Diffraction by a Rectangular Hole in a Thick Conducting Screen",slug:"diffraction-by-a-rectangular-hole-in-a-thick-conducting-screen",totalDownloads:771,totalCrossrefCites:2,totalDimensionsCites:4,abstract:"The phenomenon of diffraction by a rectangular hole in a thick conducting screen is investigated for various structural parameters (aperture sizes, aspect ratios, and screen thicknesses) and some incident angles by making use of the exact solution based on the Kobayashi potential (KP) when an electromagnetic (EM) plane wave with any polarization is impinged on the aperture. Since the KP method yields an eigenfunction expansion of the present geometry, the solution satisfies the proper edge condition as well as all the boundary conditions, and therefore we can obtain highly accurate and fast-convergent results. Many numerical results, which are useful for scientists and engineers, are provided for various physical quantities, such as the far-field diffracted pattern, transmission coefficients (normalized transmitted power), and aperture electric field distributions, and by using these numerical results, we examine the convergent property of the KP solution and discuss the effect of the hole size and shape, screen thickness, and incident polarization on the transmission property of the rectangular hole.",book:{id:"9202",slug:"novel-imaging-and-spectroscopy",title:"Novel Imaging and Spectroscopy",fullTitle:"Novel Imaging and Spectroscopy"},signatures:"Hirohide Serizawa",authors:[{id:"301504",title:"Prof.",name:"Hirohide",middleName:null,surname:"Serizawa",slug:"hirohide-serizawa",fullName:"Hirohide Serizawa"}]},{id:"72188",doi:"10.5772/intechopen.92545",title:"Investigation of the Production of Medical Ir-192 Used in Cancer Therapy via Particle Accelerator",slug:"investigation-of-the-production-of-medical-ir-192-used-in-cancer-therapy-via-particle-accelerator",totalDownloads:559,totalCrossrefCites:0,totalDimensionsCites:3,abstract:"To investigate the production of medical Ir-192 radionuclide used in brachytherapy on Os targets in the energy range of Eparticle = 100 → 1 MeV, we calculated the cross-section results for charged particle-induced reactions. The calculation was done via TALYS code and simulated activity and yield of product of each reaction process in the irradiation time of 1 h with constant beam current of 1 μA. The calculated results were compared with experimental data in the literature. Moreover, based on the calculated cross-section data and the mass stopping powers obtained from X-PMSP program, the integral yield results of all the reaction processes to produce Ir-192 on Os targets were presented as a function of incident particle energy. The obtained results were discussed to recommend appropriate reaction processes and targets for the production of Ir-192.",book:{id:"10082",slug:"accelerators-and-colliders",title:"Accelerators and Colliders",fullTitle:"Accelerators and Colliders"},signatures:"Ozan Artun",authors:[{id:"255462",title:"Associate Prof.",name:"Ozan",middleName:null,surname:"Artun",slug:"ozan-artun",fullName:"Ozan Artun"}]},{id:"68360",doi:"10.5772/intechopen.88352",title:"Development of a Corona Discharge Ionizer Utilizing High-Voltage AC Power Supply Driven by PWM Inverter for Highly Efficient Electrostatic Elimination",slug:"development-of-a-corona-discharge-ionizer-utilizing-high-voltage-ac-power-supply-driven-by-pwm-inver",totalDownloads:1239,totalCrossrefCites:3,totalDimensionsCites:3,abstract:"The corona discharge ionizer has been widely used to eliminate electrostatic charges on insulators in a variety of manufacturing industries for the prevention of electrostatic discharge (ESD) problems. High-speed electrostatic elimination is conventionally required for ionizer performance. Because of the high sensitivity of recent electronic devices to ESD damage, an extremely low-offset voltage (ion balance) is required for the performance of electrostatic eliminators. Long-term performance stability is required to maintain the quality of the products, but the short cleaning interval of the unit increases the operating cost. The efficiency is also affected by the waveform of the applied voltage. The optimization of the applied voltage is an important factor in achieving long-term performance stability. In this study, an intermittent pulse voltage AC power supply was developed to achieve a highly efficient electrostatic elimination with long-term stability high-speed electrostatic elimination and an excellent ion balance.",book:{id:"8434",slug:"modern-applications-of-electrostatics-and-dielectrics",title:"Modern Applications of Electrostatics and Dielectrics",fullTitle:"Modern Applications of Electrostatics and Dielectrics"},signatures:"Katsuyuki Takahashi, Koichi Takaki, Isao Hiyoshi, Yosuke Enomoto, Shinichi Yamaguchi and Hidemi Nagata",authors:[{id:"11890",title:"Prof.",name:"Koichi",middleName:null,surname:"Takaki",slug:"koichi-takaki",fullName:"Koichi Takaki"},{id:"211922",title:"Dr.",name:"Katsuyuki",middleName:null,surname:"Takahashi",slug:"katsuyuki-takahashi",fullName:"Katsuyuki Takahashi"},{id:"298263",title:"Dr.",name:"Isao",middleName:null,surname:"Hiyoshi",slug:"isao-hiyoshi",fullName:"Isao Hiyoshi"},{id:"298264",title:"Mr.",name:"Yosuke",middleName:null,surname:"Enomoto",slug:"yosuke-enomoto",fullName:"Yosuke Enomoto"},{id:"298265",title:"Mr.",name:"Shinichi",middleName:null,surname:"Yamaguchi",slug:"shinichi-yamaguchi",fullName:"Shinichi Yamaguchi"},{id:"298266",title:"Mr.",name:"Hidemi",middleName:null,surname:"Nagata",slug:"hidemi-nagata",fullName:"Hidemi Nagata"}]},{id:"58023",doi:"10.5772/intechopen.71022",title:"X-Ray Diffraction Detects D-Periodic Location of Native Collagen Crosslinks In Situ and Those Resulting from Non- Enzymatic Glycation",slug:"x-ray-diffraction-detects-d-periodic-location-of-native-collagen-crosslinks-in-situ-and-those-result",totalDownloads:1377,totalCrossrefCites:3,totalDimensionsCites:3,abstract:"Synchrotron based X-ray diffraction experiments can be highly effective in the study of mammalian connective tissues and related disease. It has been employed here to observe changes in the structure of Extra-Cellular Matrix (ECM), induced in an ex vivo tissue based model of the disease process underlying diabetes. Pathological changes to the structure and organization of the fibrillar collagens within the ECM, such as the formation of non-enzymatic crosslinks in diabetes and normal aging, have been shown to play an important role in the progression of such maladies. However, without direct, quantified and specific knowledge of where in the molecular packing these changes occur, development of therapeutic interventions has been impeded. In vivo, the result of non-enzymatic glycosylation i.e. glycation, is the formation of sugar-mediated crosslinks, aka advanced glycation end-products (AGEs), within the native D-periodic structure of type I collagen. The locations for the formation of these crosslinks have, until now, been inferred from indirect or comparatively low resolution data under conditions likely to induce experimental artifacts. We present here X-ray diffraction derived data, collected from whole hydrated and intact isomorphously derivatized tendons, that indicate the location of both native (existing) and AGE crosslinks in situ of D-periodic fibrillar collagen.",book:{id:"6140",slug:"accelerator-physics-radiation-safety-and-applications",title:"Accelerator Physics",fullTitle:"Accelerator Physics - Radiation Safety and Applications"},signatures:"Rama Sashank Madhurapantula and Joseph P.R.O. Orgel",authors:[{id:"212413",title:"Prof.",name:"Joseph",middleName:null,surname:"Orgel P.R.O.",slug:"joseph-orgel-p.r.o.",fullName:"Joseph Orgel P.R.O."},{id:"212416",title:"Dr.",name:"Rama Sashank",middleName:null,surname:"Madhurapantula",slug:"rama-sashank-madhurapantula",fullName:"Rama Sashank Madhurapantula"}]},{id:"71156",doi:"10.5772/intechopen.91215",title:"Surface Plasmons and Optical Dynamics on Vanadium Dioxide",slug:"surface-plasmons-and-optical-dynamics-on-vanadium-dioxide",totalDownloads:894,totalCrossrefCites:0,totalDimensionsCites:1,abstract:"We report on plasmonic resonances on VO2 nanodot arrays and associated optical dynamics. The plasmon excitations based on electric field interactions lead to red shifts of the plasmon resonances to lower photon energy with increasing nanodot size. The spectral linewidths of plasmon peaks gradually become narrow with increasing nanodot size. This is related to a reduction in plasmon damping with respect to the electronic band structure of VO2. This specific band structure of VO2 affects the optical dynamics of plasmon resonances at the sub-picosecond scale. The optical excitations of VO2 comprise intraband and interband transitions. The existence of plasmon bands induces long-lived lifetimes on decay processes. Intraband transitions in the conduction band (C.B.) play an important role in producing long lifetimes, attributing to free carriers in the C.B. By contrast, interband transitions related to bound electrons contribute to plasmon damping. The dynamic optical responses are closely related to the electronic band structures of VO2.",book:{id:"9202",slug:"novel-imaging-and-spectroscopy",title:"Novel Imaging and Spectroscopy",fullTitle:"Novel Imaging and Spectroscopy"},signatures:"Hiroaki Matsui",authors:[{id:"7227",title:"Dr.",name:"Hiroaki",middleName:null,surname:"Matsui",slug:"hiroaki-matsui",fullName:"Hiroaki Matsui"}]}],mostDownloadedChaptersLast30Days:[{id:"68360",title:"Development of a Corona Discharge Ionizer Utilizing High-Voltage AC Power Supply Driven by PWM Inverter for Highly Efficient Electrostatic Elimination",slug:"development-of-a-corona-discharge-ionizer-utilizing-high-voltage-ac-power-supply-driven-by-pwm-inver",totalDownloads:1238,totalCrossrefCites:3,totalDimensionsCites:3,abstract:"The corona discharge ionizer has been widely used to eliminate electrostatic charges on insulators in a variety of manufacturing industries for the prevention of electrostatic discharge (ESD) problems. High-speed electrostatic elimination is conventionally required for ionizer performance. Because of the high sensitivity of recent electronic devices to ESD damage, an extremely low-offset voltage (ion balance) is required for the performance of electrostatic eliminators. Long-term performance stability is required to maintain the quality of the products, but the short cleaning interval of the unit increases the operating cost. The efficiency is also affected by the waveform of the applied voltage. The optimization of the applied voltage is an important factor in achieving long-term performance stability. In this study, an intermittent pulse voltage AC power supply was developed to achieve a highly efficient electrostatic elimination with long-term stability high-speed electrostatic elimination and an excellent ion balance.",book:{id:"8434",slug:"modern-applications-of-electrostatics-and-dielectrics",title:"Modern Applications of Electrostatics and Dielectrics",fullTitle:"Modern Applications of Electrostatics and Dielectrics"},signatures:"Katsuyuki Takahashi, Koichi Takaki, Isao Hiyoshi, Yosuke Enomoto, Shinichi Yamaguchi and Hidemi Nagata",authors:[{id:"11890",title:"Prof.",name:"Koichi",middleName:null,surname:"Takaki",slug:"koichi-takaki",fullName:"Koichi Takaki"},{id:"211922",title:"Dr.",name:"Katsuyuki",middleName:null,surname:"Takahashi",slug:"katsuyuki-takahashi",fullName:"Katsuyuki Takahashi"},{id:"298263",title:"Dr.",name:"Isao",middleName:null,surname:"Hiyoshi",slug:"isao-hiyoshi",fullName:"Isao Hiyoshi"},{id:"298264",title:"Mr.",name:"Yosuke",middleName:null,surname:"Enomoto",slug:"yosuke-enomoto",fullName:"Yosuke Enomoto"},{id:"298265",title:"Mr.",name:"Shinichi",middleName:null,surname:"Yamaguchi",slug:"shinichi-yamaguchi",fullName:"Shinichi Yamaguchi"},{id:"298266",title:"Mr.",name:"Hidemi",middleName:null,surname:"Nagata",slug:"hidemi-nagata",fullName:"Hidemi Nagata"}]},{id:"71156",title:"Surface Plasmons and Optical Dynamics on Vanadium Dioxide",slug:"surface-plasmons-and-optical-dynamics-on-vanadium-dioxide",totalDownloads:887,totalCrossrefCites:0,totalDimensionsCites:1,abstract:"We report on plasmonic resonances on VO2 nanodot arrays and associated optical dynamics. The plasmon excitations based on electric field interactions lead to red shifts of the plasmon resonances to lower photon energy with increasing nanodot size. The spectral linewidths of plasmon peaks gradually become narrow with increasing nanodot size. This is related to a reduction in plasmon damping with respect to the electronic band structure of VO2. This specific band structure of VO2 affects the optical dynamics of plasmon resonances at the sub-picosecond scale. The optical excitations of VO2 comprise intraband and interband transitions. The existence of plasmon bands induces long-lived lifetimes on decay processes. Intraband transitions in the conduction band (C.B.) play an important role in producing long lifetimes, attributing to free carriers in the C.B. By contrast, interband transitions related to bound electrons contribute to plasmon damping. The dynamic optical responses are closely related to the electronic band structures of VO2.",book:{id:"9202",slug:"novel-imaging-and-spectroscopy",title:"Novel Imaging and Spectroscopy",fullTitle:"Novel Imaging and Spectroscopy"},signatures:"Hiroaki Matsui",authors:[{id:"7227",title:"Dr.",name:"Hiroaki",middleName:null,surname:"Matsui",slug:"hiroaki-matsui",fullName:"Hiroaki Matsui"}]},{id:"69532",title:"Dielectric Analysis Model for Measurement of Soil Moisture Water Content Using Electrical Capacitance Volume Tomography",slug:"dielectric-analysis-model-for-measurement-of-soil-moisture-water-content-using-electrical-capacitanc",totalDownloads:789,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Electromagnetic methods have been widely used in the measurement of the water content of the soil. These methods utilize the permittivity as electrical properties of the soil, to determine the moisture content of the soil. Since the measurements are carried out indirectly, a calibration between permittivity and the water content of the soil is needed. Generally, the calibration method is generated by using an empirical and mixing model. This study presents a proposed model of calibration by using a normalization approach to calibrate the value of the permittivity of the water content of the soil. Then the model was applied using electrical capacitance volume tomography (ECVT) to image soil water content during infiltration of water in a soil column. Granular and silty sand were used as soil material in the experiments. The result showed that the model for measuring moisture water content can be seen in each layer during soil water infiltration in the soil column.",book:{id:"8434",slug:"modern-applications-of-electrostatics-and-dielectrics",title:"Modern Applications of Electrostatics and Dielectrics",fullTitle:"Modern Applications of Electrostatics and Dielectrics"},signatures:"Mukhlisin Muhammad and Saputra Almushfi",authors:[{id:"306980",title:"Prof.",name:"Muhammad",middleName:null,surname:"Mukhlisin",slug:"muhammad-mukhlisin",fullName:"Muhammad Mukhlisin"},{id:"306981",title:"MSc.",name:"Almushfi",middleName:null,surname:"Saputra",slug:"almushfi-saputra",fullName:"Almushfi Saputra"}]},{id:"71074",title:"Electrostatic Friction Displays to Enhance Touchscreen Experience",slug:"electrostatic-friction-displays-to-enhance-touchscreen-experience",totalDownloads:649,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Touchscreens are versatile devices that can display visual content and receive touch input, but they lack the ability to provide programmable tactile feedback. This limitation has been addressed by a few approaches generally called surface haptics technology. This technology modulates the friction between a user’s fingertip and a touchscreen surface to create different tactile sensations when the finger explores the touchscreen. This functionality enables the user to see and feel digital content simultaneously, leading to improved usability and user experiences. One major approach in surface haptics relies on the electrostatic force induced between the finger and an insulating surface on the touchscreen by supplying high AC voltage. The use of AC also induces a vibrational sensation called electrovibration to the user. Electrostatic friction displays require only electrical components and provide uniform friction over the screen. This tactile feedback technology not only allows easy and lightweight integration into touchscreen devices but also provides dynamic, rich, and satisfactory user interfaces. In this chapter, we review the fundamental operation of the electrovibration technology as well as applications have been built upon.",book:{id:"8434",slug:"modern-applications-of-electrostatics-and-dielectrics",title:"Modern Applications of Electrostatics and Dielectrics",fullTitle:"Modern Applications of Electrostatics and Dielectrics"},signatures:"Reza Haghighi Osgouei",authors:[{id:"286114",title:"Dr.",name:"Reza",middleName:null,surname:"Haghighi Osgouei",slug:"reza-haghighi-osgouei",fullName:"Reza Haghighi Osgouei"}]},{id:"69493",title:"Diffraction by a Rectangular Hole in a Thick Conducting Screen",slug:"diffraction-by-a-rectangular-hole-in-a-thick-conducting-screen",totalDownloads:766,totalCrossrefCites:2,totalDimensionsCites:4,abstract:"The phenomenon of diffraction by a rectangular hole in a thick conducting screen is investigated for various structural parameters (aperture sizes, aspect ratios, and screen thicknesses) and some incident angles by making use of the exact solution based on the Kobayashi potential (KP) when an electromagnetic (EM) plane wave with any polarization is impinged on the aperture. Since the KP method yields an eigenfunction expansion of the present geometry, the solution satisfies the proper edge condition as well as all the boundary conditions, and therefore we can obtain highly accurate and fast-convergent results. 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She obtained a BSc from the University of Derby, England, a master’s degree from Technische Universität München, Germany, and a Ph.D. from the University of Nottingham. She undertook a post-doctoral research fellowship in the School of Medicine before accepting tenure in Veterinary Medicine and Science. Dr. Rutland also obtained an MMedSci (Medical Education) and a Postgraduate Certificate in Higher Education (PGCHE). She is the author of more than sixty peer-reviewed journal articles, twelve books/book chapters, and more than 100 research abstracts in cardiovascular biology and oncology. She is a board member of the European Association of Veterinary Anatomists, Fellow of the Anatomical Society, and Senior Fellow of the Higher Education Academy. 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He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:"Polytechnic University of Timişoara",institution:{name:"Polytechnic University of Timişoara",country:{name:"Romania"}}},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. 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. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:null},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"241400",title:"Prof.",name:"Mohammed",middleName:null,surname:"Bsiss",slug:"mohammed-bsiss",fullName:"Mohammed Bsiss",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241400/images/8062_n.jpg",biography:null,institutionString:null,institution:null},{id:"276128",title:"Dr.",name:"Hira",middleName:null,surname:"Fatima",slug:"hira-fatima",fullName:"Hira Fatima",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/276128/images/14420_n.jpg",biography:"Dr. Hira Fatima\nAssistant Professor\nDepartment of Mathematics\nInstitute of Applied Science\nMangalayatan University, Aligarh\nMobile: no : 8532041179\nhirafatima2014@gmal.com\n\nDr. Hira Fatima has received his Ph.D. degree in pure Mathematics from Aligarh Muslim University, Aligarh India. Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. She is a member of Indian Mathematical Society.",institutionString:null,institution:null},{id:"414880",title:"Dr.",name:"Maryam",middleName:null,surname:"Vatankhah",slug:"maryam-vatankhah",fullName:"Maryam Vatankhah",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Borough of Manhattan Community College",country:{name:"United States of America"}}},{id:"414879",title:"Prof.",name:"Mohammad-Reza",middleName:null,surname:"Akbarzadeh-Totonchi",slug:"mohammad-reza-akbarzadeh-totonchi",fullName:"Mohammad-Reza Akbarzadeh-Totonchi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Ferdowsi University of Mashhad",country:{name:"Iran"}}},{id:"414878",title:"Prof.",name:"Reza",middleName:null,surname:"Fazel-Rezai",slug:"reza-fazel-rezai",fullName:"Reza Fazel-Rezai",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"American Public University System",country:{name:"United States of America"}}},{id:"302698",title:"Dr.",name:"Yao",middleName:null,surname:"Shan",slug:"yao-shan",fullName:"Yao Shan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Dalian University of Technology",country:{name:"China"}}},{id:"125911",title:"Prof.",name:"Jia-Ching",middleName:null,surname:"Wang",slug:"jia-ching-wang",fullName:"Jia-Ching Wang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"National Central University",country:{name:"Taiwan"}}},{id:"357085",title:"Mr.",name:"P. Mohan",middleName:null,surname:"Anand",slug:"p.-mohan-anand",fullName:"P. Mohan Anand",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"356696",title:"Ph.D. Student",name:"P.V.",middleName:null,surname:"Sai Charan",slug:"p.v.-sai-charan",fullName:"P.V. Sai Charan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"357086",title:"Prof.",name:"Sandeep K.",middleName:null,surname:"Shukla",slug:"sandeep-k.-shukla",fullName:"Sandeep K. Shukla",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"356823",title:"MSc.",name:"Seonghee",middleName:null,surname:"Min",slug:"seonghee-min",fullName:"Seonghee Min",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Daegu University",country:{name:"Korea, South"}}},{id:"353307",title:"Prof.",name:"Yoosoo",middleName:null,surname:"Oh",slug:"yoosoo-oh",fullName:"Yoosoo Oh",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:"Yoosoo Oh received his Bachelor's degree in the Department of Electronics and Engineering from Kyungpook National University in 2002. He obtained his Master’s degree in the Department of Information and Communications from Gwangju Institute of Science and Technology (GIST) in 2003. In 2010, he received his Ph.D. degree in the School of Information and Mechatronics from GIST. In the meantime, he was an executed team leader at Culture Technology Institute, GIST, 2010-2012. In 2011, he worked at Lancaster University, the UK as a visiting scholar. In September 2012, he joined Daegu University, where he is currently an associate professor in the School of ICT Conver, Daegu University. Also, he served as the Board of Directors of KSIIS since 2019, and HCI Korea since 2016. From 2017~2019, he worked as a center director of the Mixed Reality Convergence Research Center at Daegu University. From 2015-2017, He worked as a director in the Enterprise Supporting Office of LINC Project Group, Daegu University. His research interests include Activity Fusion & Reasoning, Machine Learning, Context-aware Middleware, Human-Computer Interaction, etc.",institutionString:null,institution:{name:"Daegu Gyeongbuk Institute of Science and Technology",country:{name:"Korea, South"}}},{id:"262719",title:"Dr.",name:"Esma",middleName:null,surname:"Ergüner Özkoç",slug:"esma-erguner-ozkoc",fullName:"Esma Ergüner Özkoç",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Başkent University",country:{name:"Turkey"}}},{id:"346530",title:"Dr.",name:"Ibrahim",middleName:null,surname:"Kaya",slug:"ibrahim-kaya",fullName:"Ibrahim Kaya",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"419199",title:"Dr.",name:"Qun",middleName:null,surname:"Yang",slug:"qun-yang",fullName:"Qun Yang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Auckland",country:{name:"New Zealand"}}},{id:"351158",title:"Prof.",name:"David W.",middleName:null,surname:"Anderson",slug:"david-w.-anderson",fullName:"David W. Anderson",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Calgary",country:{name:"Canada"}}}]}},subseries:{item:{id:"41",type:"subseries",title:"Water Science",keywords:"Water, Water resources, Freshwater, Hydrological processes, Utilization, Protection",scope:"