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In tune with the increasing importance and relevance of machine learning models, algorithms, and their applications, and with the emergence of more innovative uses–cases of deep learning and artificial intelligence, the current volume presents a few innovative research works and their applications in real-world, such as stock trading, medical and healthcare systems, and software automation. The chapters in the book illustrate how machine learning and deep learning algorithms and models are designed, optimized, and deployed. The volume will be useful for advanced graduate and doctoral students, researchers, faculty members of universities, practicing data scientists and data engineers, professionals, and consultants working on the broad areas of machine learning, deep learning, and artificial intelligence.",isbn:"978-1-83969-485-1",printIsbn:"978-1-83969-484-4",pdfIsbn:"978-1-83969-486-8",doi:"10.5772/intechopen.94615",price:119,priceEur:129,priceUsd:155,slug:"machine-learning-algorithms-models-and-applications",numberOfPages:152,isOpenForSubmission:!1,isSalesforceBook:!1,isNomenclature:!1,hash:"6208156401c496e0a4ca5ff4265324cc",bookSignature:"Jaydip Sen",publishedDate:"December 22nd 2021",coverURL:"https://cdn.intechopen.com/books/images_new/10651.jpg",keywords:null,numberOfDownloads:1869,numberOfWosCitations:0,numberOfCrossrefCitations:2,numberOfDimensionsCitations:3,numberOfTotalCitations:5,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"February 9th 2021",dateEndSecondStepPublish:"March 9th 2021",dateEndThirdStepPublish:"May 8th 2021",dateEndFourthStepPublish:"July 27th 2021",dateEndFifthStepPublish:"September 25th 2021",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"a year",secondStepPassed:!0,areRegistrationsClosed:!0,currentStepOfPublishingProcess:5,editedByType:"Edited by",kuFlag:!1,biosketch:"Prof. Sen is a leading scientist in the area of artificial intelligence, machine learning, and cybersecurity, who is listed among the top 2 percent most-cited scientists in the world by Stanford University, USA.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"4519",title:"Prof.",name:"Jaydip",middleName:null,surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen",profilePictureURL:"https://mts.intechopen.com/storage/users/4519/images/system/4519.jpeg",biography:"Jaydip Sen is associated with Praxis Business School, Kolkata, India, as a professor in the Department of Data Science. His research areas include security and privacy issues in computing and communication, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. 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Venkateswarlu",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",editedByType:"Edited by",editors:[{id:"58592",title:"Dr.",name:"Arun",surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"46699",title:"Adaptive Speckle Filtering in Radar Imagery",doi:"10.5772/58593",slug:"adaptive-speckle-filtering-in-radar-imagery",body:'Historically, foundations in the domain of radar speckle properties have been laid down from the 1940’s to the 1980’s. Decisive theoretical advances were made by teams led by Professor Fawwaz Ulaby at the University of the Michigan (USA), by Professor Christopher Oliver at the Defence Research Agency in Great Malvern (UK), and by Professor Keith Raney at the Canadian Centre of Remote Sensing (Canada) since the 1970’s. Then, the domain of speckle filtering in SAR images matured in the period 1976-2000, mostly under the impulsion of Dr. Jong Sen Lee of the Naval Research Center, Washington D.C. (USA). Since 1986, the team led by Dr. Armand Lopès at the Centre d\'Etude Spatiale des Rayonnements in Toulouse (France), has carried out and then inspired the development of the most efficient speckle filters existing today. Since 2000, with speckle filters having reached a satisfactory level of performance, no significant advances have been made. Nevertheless, in this period, the use of speckle filters in a wide range of applications using SAR imagery has become generalized.
A radar wave can be considered, with a good approximation, as plane, coherent and monochromatic. It is emitted by an antenna towards a target. The target backscatters partially the radar wave in the direction of a receiving antenna. In the vast majority of spaceborne Synthetic Aperture Radars (SAR), a single antenna assumes the two functions of emission and reception (monostatic radar).
The complete radar measurement is the combination of the horizontally (H) and vertically (V) linearly polarised radar waves, at emission and at reception after backscattering by the observed target. After signal calibration, this measurement, affected by noise, enables to restitute for each resolution cell a polarimetric backscattering matrix
whose coefficients
Let consider the interaction of the radar wave with an extended random surface,
This detected signal intensity
Carrying the radiometric information with regard to the sensed target, σ° is a function of the frequency of the radar wave, of its angle of incidence upon the target, and of the configuration of polarisation. In terms of physical meaning, the radar backscattering coefficient is analogous to the bidirectional reflectance
Nevertheless, detected radar images look visually very noisy, exhibiting a very characteristic salt-and-pepper appearance with strong tonal variations from a pixel to the next. Indeed, since radar imaging systems are time-coherent, radar measurements over random rough surfaces are corrupted by "speckle" noise due to the random modulation of waves reflected by the elementary scatterers randomly located in the resolution cell. Then, coherent summation of the phases of elementary scatterers within the resolution cell results in a random phase of the complex pixel value.
This speckle "noise" makes both photo-interpretation and the estimation of
Therefore, speckle filtering and radar reflectivity restoration are among the main fields of interest in radar images processing for remote sensing. Speckle filtering is a pre-processing aiming at the restoration of
Therefore, an ideal speckle filter must satisfy to the following specifications:
Preserve accurately the local mean value of the radar reflectivity (
Smooth as much as possible homogeneous image areas and therefore reduce the speckle to increase the Equivalent Number of Looks (ENL) of the radar image (
Preserve texture as much as possible where it exists in the image (forests, non-homogeneous fields, etc.) to avoid confusions among radiometrically similar areas exhibiting different texture. Therefore, a speckle filter must be able to discriminate heterogeneity effects due to texture from those due to speckle.
Both preserve and denoise image structures (contours, lines) as well as the quasi-deterministic responses due to corner reflector effects within strongly textured areas such as urban environments. Indeed, the energy of artificial radar reflectors responses must be preserved to enable radiometric calibration, in particular when calibration targets are dispersed in the radar image.
Minimise, and whenever possible prevent loss in useful spatial resolution during the speckle filtering process.
In this section, the statistical properties of speckle in images produced by coherent imaging systems such as imaging radars, lidars or sonars, are exposed. Since a good speckle filter must restore the texture of the scene imaged by the radar, the statistical properties of texture in radar images are examined as well. This analysis intentionally restrains to the first order statistical properties, since only these are generally used by the estimation techniques involved in speckle reduction methods. Explicit use of second order statistical properties of both the speckle and the imaged scene in the filtering process is adressed in Section 4.
First, let consider a natural target with radar backscattering coefficient
The radar imaging system is linear, spatially invariant, and can be characterised at each image pixel (
If the number of individual scatterers within a resolution cell is large enough and none of them has absolute predominance in scattering the radar wave [2] [3], speckle can be modelled in output of the radar processor by a circular complex gaussian random process
These complex data in output of the radar processor are called a "1-look complex" image or equivalently, a "Single-Look-Complex" (SLC) image.
For a homogeneous area where
where
Owing to the particular character of the speckle phenomenon in coherent imagery, which is the case of radar imagery, information extraction from a radar image results in a statistical estimation problem. It is therefore mandatory to have an as complete as possible statistical speckle model. The statistical model of the fully developed speckle has proven perfectly adapted to SAR images, at the spatial resolutions / wavelength frequencies combinations actually used in radar remote sensing. Note that this speckle model emphasises the importance of wave phase information under the condition that the phase has not been lost during signal detection.
Goodman hypotheses [2] [5] enable to calculate speckle statistics before (
where E[.] denotes the mean expectation and
Besides, the in-phase and the out-of-phase components
with a phase of the complex radar signal
Since
It is important to note that, since E[
The two first first-order moments of this pdf can be expressed as a function of its standard-deviation as follows:
To characterise the strength of speckle in radar images, it is convenient to consider the normalised coefficient of variation of the intensity,
The value of the coefficient of variation of speckle only, sometimes called "contrast index", is a constant for every type of radar image product. Equation (9) means that, in a radar image, the dispersion (variance) of radiometry increases as the mean signal backscattered by the target increases. This justifies in part the qualification of "multiplicative noise" given to the speckle.
Clearly, with a signal-to-noise ratio of 1, the radiometric degradation due to speckle makes very difficult the discrimination of two homogeneous targets with very different radar backscattering coefficients. As an example, a theoretical computation [10] demonstrates that two textureless target classes of homogeneous radar reflectivities (
Therefore, a first radiometric enhancement is needed to achieve a reduction of the coefficient of variation of the speckle over homogeneous areas. It corresponds to an enhancement of the signal-to-noise ratio and to a preliminary speckle "noise" reduction.
A first method of speckle reduction consists in averaging incoherently
The goal of this method is to reduce speckle enough to make radar image photo-interpretation possible. Indeed, experience has shown that
This operation is realised by splitting the Doppler bandwidth of the backscattered signal into
Over the same target, the mean intensity resulting from this operation remains the same mean intensity of each of the individual looks. If the
It is important to note that multilook radar image formation is at the expense of the spatial resolution in azimuth. In practice, the value of
If the individual looks are uncorrelated with each other, the pdf of the speckle, which is the sum of
If the
The
Hence, the pdf of the speckle in intensity can be approximated, by extension of Equation (12), for whatever value of
which is rigorously equivalent to Equation (12) when
All speckle models for multilook images (
Let us consider that the
For the intensity image resulting of the averaging of the
The exact pdf of the average intensity
Since the radar backscattering coefficient
Arsenault and April [15] [17] [19] demonstrated that, after this transformation, the pdf of the speckle for a multilook radar image, Equation (14), becomes a Fisher-Tippett distribution:
with
The first order statistical moments of this distribution are as follows [15]:
1) Mean <
Equation (18) shows that the logarithmic transformation causes a signal distortion, increasing with decreasing number
2) Variance
Lopès [20] has shown that for N independent
Texture concerns the spatial distribution of grey levels. It is important in the analysis of SAR images for a wide range of applications (
As seen above, within a homogeneous area image of a detected radar image, one can consider the observed speckle
In most remote sensing applications, it is reasonable to consider the imaged scene as an arrangement of discrete objects superimposed to a background with mean reflectivity E[
If
E[
E[
The spatial structure of actual imaged scenes, called "texture", induces a mesurable spatial structure (after the properties of
To characterise a given class
Considering the scene texture model of [25] in Equation (21), it is possible [27] [28] to model the radar image intensity at pixel of coordinates (
This relationship is valid as long as the spatial variations of
The variance of the intensity
Since the fluctuations of
and:
Therefore, E[
Introducing the coefficients of variation (
which characterises scene texture in terms of heterogeneity, with
For a better description of the scene, one must use the pdfs of its diverse classes (distribution of the random variable
where
To produce a SAR image, speckle samples at the output of the SAR processor are correlated through the SAR impulse response to obtain a sampling rate (pixel size) of about half the spatial resolution of the radar sensor, thus avoiding aliasing effects. Using the multiplicative noise model and Equations (24) and (25) [27] [28], the correlation coefficient
can be related to the scene correlation coefficient
Therefore, if
Using the simplified multiplicative noise model for the speckle
In practice,
Below the
The coefficient of variation
homogeneous areas with neither texture, nor structures.
areas with low or moderate heterogeneity where the presence of structures is improbable.
strongly heterogeneous areas where one must search for the possible presence of structures (contour, line, strong scatterers).
This section is dedicated to a theoretical analysis of the most common and more efficient speckle filtering techniques developed for Synthetic Aperture Radar (SAR) images, and of their corresponding estimation techniques. These filters use variants of the statistical speckle model exposed in the preceding Section 1. They also use diverse statistical estimators to restore the radar reflectivity (in the sense of the CEOS’s (Committee for Earth Observation Satellites) "radar brightness"). These statistical estimators are, either Minimum Mean Square Error estimators (
The SAR image model considered by [30] is as follows:
where
To estimate the radar reflectivity
The MMSE least-squares solution is valid for homogeneous areas for which
where
The impulse response of the filter is calculated adopting an autoregressive process model for
These hypotheses enable to define an optimal MMSE filter (Wiener filter) with impulse response
with:
where
The final Frost
The behaviour of the filter depends on the values of the locally observed coefficient of variation,
Extremely homogeneous areas, for which
Very strong scatterers (extreme heterogeneity), where
Between these two situations, in textured natural areas, when
Considering the requirements for an ideal speckle filter, the filter should:
Restore the mean intensity value over homogeneous areas, where
Preserve the observed intensity when the value of
Since it is impossible to fulfil simultaneously these two conditions (
The radar image
Kuan
where
The local statistics of the scene
Since the variance of the additive noise
It is noteworthy that, since the image model does not assume independence of the noise
Lee uses the unit-mean uncorrelated multiplicative speckle modele (
This approximation enables to transform Equation (33) into a weighted sum of the signal and of a noise independant on the signal. The linear MMSE estimator, and Equations (26) and (27) that are consequences of the multiplicative speckle model, enable to establish the Lee filter [33], historically the first speckle filter designed to be adaptive to local radar image statistics:
It is noteworthy that, assuming the independence of noise and signal in the model used by the Kuan
The linear MMSE speckle filters of Lee and of Kuan
with:
and
Both methods perform a linearly weighted average of the local mean of the intensity and of the observed pixel intensity. In both cases, weights depend on the ratio of the coefficients of variation of the observed intensity and of the noise [7] [40]. As for the Frost
Homogeneous areas where
Very stong scatterers (extreme heterogeneity) where
Between these two extreme situations, the weight of the observed value of the pixel intensity increases with the heterogeneity of its neighbourhood.
Nevertheless, note that the weight on the estimated mean intensity remains significant for high values of the coefficient of variation. Thus, responses of small impulse targets are cut-off by these filters and image structures suffer some amount of smoothing. To correct this drawback, Lopès
Inversely, when
The linear MMSE filters differ from the Wiener filters by the fact that the A Priori mean and variance, <
It is remarkable that the often used MMSE estimation ([33] [43] [44] [45] and [41] [32], among others) is nothing else than the mean of the conditional A Posteriori pdf P(
As an effect, this linearization restrains the validity of the linear MMSE estimator to situations where the noise level is not too high (multilook images with high values of
The Bayesian MAP approach [47] [48] consists in characterising the imaged scene and the speckle "noise" by their statistical description, using their associated pdfs.
In the Bayesian perspective, the theory of probabilities is extended to the logics of probabilistic inference. Probabilities are seen as a relationship between a formal hypothesis and a possible conclusion. This relationship corresponds to a certain degree of rational credibility and is limited only by the extreme relationships of certitude and impossibility [49]. The classic deductive logics considering only these extreme relationships (
As a general consequence, the theory of probabilities cannot base on the sole concepts of classic logics (frequentist as in the MMSE or in Wiener’s approaches). In particular, the relationship of probability cannot be defined in terms of certitude, since certitude is viewed as a particular case of probability. The frequentist definition of probabilities based on relations of certitude related to the knowledge of a number of parameters (<
In this context, probabilities are used to describe stochastically an incomplete information on a global phenomenon (here, the radar reflectivity and the superimposed speckle), rather than to describe only the noise randomness that corrupts its comprehension. Probability relationships are viewed as being conditional to the context. This way, the pdf of the speckle
The least error-cost inference mechanism leading from the observed intensity
P(
In theory, the MAP method enables to avoid direct estimation of the mean of the conditional A Posteriori pdf, which is necessary to the MMSE estimation. This feature is of great interest in the resolution of non-linear problems where the evaluation of the conditional mean is, either difficult, or impossible [51].
The Maximum A Posteriori (MAP) estimation of
P(
P(
there is no particular justification to prefer the MMSE estimation by minimisation of the mean quadratic error implicitly assuming a symmetrical P(
It is of interest to notice that the "Maximum Likelihood" estimation is nothing more than a particular case of Maximum A Posteriori, in the situation where the conditional A Posteriori and A Priori pdf’s are equal: P(
Once the first-order statistical speckle model P(
The NMNV scene model [32] enables to solve locally, in an analytic manner, the estimation of
Since the logarithm function is a monotonically increasing function, Bayes’s formula ([47] [48]; Equation (46)) can be rewritten as:
which gives the local MAP estimation of
with:
P(
Then, the general equation of the MAP speckle filter becomes, locally:
The first term of Equation (50), the Maximum Likelihood term, accounts for the effects of the whole imaging system on the radar image and describes the detected radar intensity once the speckle statistical model is known. The second term, the Maximum A Priori term, represents the prior statistical knowledge with regard to the imaged scene.
In the Bayesian approach, probabilities are used to describe incomplete information rather than randomness. As Equation (50) shows, in the Bayesian inference process, induction is influenced by the prior expectations allowed by the prior knowledge of P(
The pdf of the speckle in intensity for a
The Maximum A Priori term must be calculated according to the scene model chosen as A Priori knowledge, hypothesis, or belief.
The hypothesis of Gaussian-distributed scene has been adopted as a natural hypothesis by a large number of authors who had worked, either on images from optical sensors, or on images from passive/active microwave sensors. These authors are comforted in this hypothesis by both the force of habit and by the mathematical ease in manipulating a Gaussian distribution.
Kuan
Therefore, one must preferably take into account a positive pdf as a realistic scene model. For reasons that are both experimental and theoretical, in the case of natural extended targets as it is most often the case dealt with in remote sensing, a Gamma distributed scene model is better appropriate.
Natural textures observed, either by coherent radar imagery, or by incoherent optical imagery are due to a common contribution corresponding to the variability in spatial distribution of the objects within the scene. Even if the interaction mechanisms between the electromagnetic wave and the observed medium are very different in either case, the natural arrangement of the scene makes the second-order statistics very similar in either kind of imagery [55] [56]. At the scale of a large number of resolution cells, the pdfs of the cross-section variables corresponding to either mechanism belong to the same family of distributions, at least for the high radar frequencies in bands Ku, X, and C for which wave penetration into natural media is limited. This point is more arguable for radar bands L and P.
In a wide range of radar backscattering situations, the Gamma distribution is experimentally the one that best fits, not only the distribution of the radar backscattering coefficient [21] [57], but also the distribution of radiometries observed in incoherent optical images [55]. This scene model has been successfully used also for radar images of the sea [58] [59] [60].
The local pdf of a scene statistically described by a Gamma distribution, has the form:
with
Note that assuming a Gamma-distributed
Nevertheless, in an illustration of the so-called "Cromwell’s rule" [62], even hard A Priori conviction that the scene presents a Gamma-distributed texture must not be insensitive to counter-evidence. Therefore, the complete MAP filter is a set of three filters adapted to diverse situations locally encountered in a radar image: the application of this or that filter is decided depending on the degree of heterogeneity of the image part under processing, that is on the locally estimated value of the coefficient of variation
Assuming that the pdf of the scene is a Gamma distribution, the Maximum A Priori term is locally equal to:
This second-degree equation admits only one real positive solution
The integration of a heterogeneity/texture detector based on the coefficient de variation and of specific detectors (ratio-of-amplitudes – RoA; [66] [7]) for contours, linear structures and strong scatterers in the filtering process is described by the general algorithm presented in [63] [64] [10]. The integration of texture and structure detectors using second-order statistics (autocorrelation functions) of both the speckle and the radar reflectivity of the scene [67] is presented in Section 4. In all cases, mage areas identified as textured are filtered using Equation (54).
In the particular case of a perfectly homogeneous (textureless) scene, with
This distribution is the limit of Gamma distributions when
This case is taken into account when the local statistics calculated in the neighbourhood of the processed pixel show a nearly perfect homogeneity of the scene.
The other extreme case regards strong scatterers, when speckle is no longer fully developed. The considerations that led to consider the Gamma pdf as an A Priori model for a textured natural scene are no longer valid: we no longer have any A Priori information about the scene. In this situation, the information content of every grey level of the image being A Priori the same, the pdf of the imaged scene can be represented by an uniform distribution:
with undetermined extreme values
If the resolution cell contains only one isolated strong scatterer, the response (value
SAR images of dense tropical forest, urban areas, or very strong and rapidly varying topography often show very strong or mixed textures. This is also the case of high-and very-high spatial resolution SAR images. In these situations, it may be hazardous to make an assumption about the probability density function of the radar reflectivity.
Indeed, the MAP technique does not account for any uncertainty in the value of the parameters of the A Priori pdf chosen as a Gamma distribution once it has been locally estimated on a given image area. Hence, in the presence of mixed (forests with underlying structures, for example) or rapidly varying (strongly textured area located on strong slopes, or very-high spatial resolution radar images, for example) texture, the MAP estimator will underestimate the variance of the predictive distribution. Indeed, this predictive distribution can hardly take into account the fact that it results of a compound of a mix of different distributions.
In this context, the A Priori knowledge with regard to the observed scene can hardly be an analytical first order statistical model, chosen on the base of prior scene knowledge. However, to retrieve local statistical scene knowledge directly from SAR image data, Datcu & Walessa [68] [69] proposed to introduce the local entropy of the radar reflectivity,
Because the radar reflectivities
For a single detected SAR image, the conditional pdf of the speckle can be, as long as speckle is fully developed, modelled as a Gamma distribution:
Incorporating these scene and speckle models, the Gamma/Distribution-Entropy MAP (Gamma-DE MAP) speckle filter for single-channel detected SAR images is the solution of the following equation [71]:
The radar reflectivites
Note that the local DE MAP estimation of
The DE-MAP filters adapt to a much larger range of textures than the other MAP filters ([10] [11] [72] [73]) developed under the assumption of K-distributed SAR intensity (
Compared to those of the other MAP filters, performances in terms of speckle reduction are identical. However, texture restoration and structures or point targets preservation, identical for moderate textures, are superior in strongly textured areas. These filters have proven a remarkable efficiency in operational remote sensing (
The local MAP estimate is the mode of the local A Posteriori pdf of the radar reflectivity
In the presence of texture, the estimator takes into account the non-linear effects in getting from
Nevertheless, in the presence of structures, the NMNV model may be used abusively on an inappropriate neighbourhood of the pixel under processing and therefore the local statistics <
The assumptions usually made by adaptive speckle filters ([76] [30] [32] [10]) with regard to the first order statistics of the speckle are:
the multiplicative speckle model;
the pdf of the speckle which reflects only incompletely the spatial correlation of the speckle through the ENL.
The assumptions regarding the imaged scene are:
Local wide-sense stationarity and ergodicity;
A formal Non-stationary Mean Non-stationary Variance (NMNV) model accounting for the spatial variation of the first order statistical properties [32];
For the Maximum A Posteriori (MAP) filter, the general form of the pdf of the scene radar cross-section [10].
The main consequences of these assumptions are that:
The formal NMNV model justifies local treatment (processing window) using the local statistics;
Assuming spatially uncorrelated speckle leads to the design of scalar (single-point) filters;
Local adaptivity to tonal properties (mean intensity <
The major drawbacks of these assumptions are that:
The coefficients of variation are statistically [10] sensitive to texture and speckle strength [40], but do not provide direct information on spatial correlation properties and texture directionality. Locally estimated, they can also be biased if speckle samples are not independent (
Compliance with the ergodicity and stationarity hypothesis requires a preliminary identification of the structural elements of the scene to fully exploit the NMNV model and to correctly estimate the local mean reflectivity around the pixel under processing;
In this Section, local second order properties, describing spatial relationships between pixels are introduced into single-point speckle adaptive filtering processes, in order to account for the effects of speckle and scene spatial correlations. To this end, texture measures originating from the local autocorrelation functions (ACF) are used to refine the evaluation of the non-stationary first order local statistics as well as to detect the structural elements of the scene [75].
In practice, the usual single-point filters do preserve texture, only due to the spatial variation of the local first order statistics, using the NMNV formal model [32]. Fairly good preservation of textural properties and structural elements (edges, lines, strong scatterers) can be achieved by associating constant false alarm rate structure detectors such as the directional Ratio-Of-Amplitudes (RoA) detectors; ([7] [66] [10] [63] [64]) to the speckle filtering process. The combination of detection and speckle filtering allows to preserve scene structures, and to enhance scene texture estimation on a shape adaptive neighborhood of the pixel under consideration. When the conditions for which they have been developed (especially spatially uncorrelated or low-correlated speckle) are fulfilled, the best single-point adaptive speckle filters and their structure retaining associated processes based on RoA detectors retain enough scene texture to allow its use as an additional discriminator ([23] [24] [63] [64]).
However, the performances of the usual single-point filters, even when refined with associated RoA structure detectors, degrade when the actual spatial correlation of speckle samples becomes significant [77],
As an example of the effects of speckle spatial correlation, the case of structure detection using the RoA detectors [10] implemented in the Gamma-Gamma MAP filter is illustrated in [67]. Detection is successfully performed when the correlation of speckle is low between pixels. However, the performance of RoA detectors substantially degrades when the spatial correlation of speckle samples becomes significant. It has been shown theoretically in [67] that spatial speckle correlation results in an increasing detection of non-existing structures,
Therefore, second order statistical properties must also be considered, including both scene texture and resolution/sampling related properties, to achieve a more complete restoration of the radar reflectivity.
A possible solution is the implementation of vector (multiple-points) filters ([32] [79]) where the spatial covariance matrices of the speckle and of the scene are taken into account. The development of a filtering method using second order statistics,
To avoid the mathematical complexity and the heavy computational burden of multiple-point filters, an alternative solution is to introduce an appropriate description of both speckle correlation properties and spatial relations between resolution cells into a single-point filter.
Second order statistics have explicitly been used in the past, following the scheme proposed by Woods & Biemond [80] implemented later by Quelle & Boucher [81] in the adaptive Frost speckle (single-point) filter [30]. The filter, which belongs to the family of Wiener filters, is established using Yaglom\'s method [38], where a frequency characteristic is determined, instead of an impulse transfer function, which actually exists only within wide-sense stationary areas. This frequency characteristic is determined in the speckled image at a distance of one pixel only in range and azimuth, thus mainly limiting the description of correlation properties to those of the speckle.
Considering the NMNV model [32], a much better solution is to introduce locally estimated second order statistics to refine the computation of the local NMNV first order statistics. In this way, speckle correlation properties can be taken into account for filtering. In addition, the local mean radar reflectivity E[
Spatial relations between pixels are well described by the intensity ACF, defined by a set of correlation coefficients
The local estimates for the normalised intensity ACF,
or, equivalently, directly computed within the domain of interest
These estimates have the attractive property that their mean square error is generally smaller than that of other estimators; considerations on the estimation accuracy can be found in Rignot & Kwok [82].
The contribution of scene texture must be separated from that of the speckle for all displacements Δ
where
where
The computation of a local non-stationary estimate of E(
for all
This means that, along a direction
The implementation of this operator, which estimates the local non-stationary E[
in homogeneous areas, Equation (67) acts as a smoothing operator:
for a strong scatterer, it acts as a Laplacian:
if a perfect step edge between two homogeneous areas is present in the neighbourhood (correlations=1,0,-1), it acts as a gradient and automatically stops weighting further pixels. This indicates structure detection capability;
in all other cases,
This concept of "texture fields", based on the analysis of second order statistical properties, generalises image processing concepts such as filtering and detection, which are usually considered as distinct. It provides the possibility to perform simultaneously structure detection and image pre-filtering. Structural elements such as edges are detected (value of the estimate of the correlation coefficient becoming less than 1/e) when the distance from the pixel under processing (central pixel of the processing window) to the edge is reached, going in the direction of the edge. Therefore, the position of the edge is known as soon as the edge enters the “field of view” of the processing window.
The local mean radar reflectivity estimation takes now into account the textural properties of the imaged scene (spatial variability of
The whole process acts as an adaptive focusing process in addition to the filtering process, since emphasis is put on the restoration and the enhancement of the small-spatial-scale fluctuations of the radar reflectivity. Full profit is taken of the useful resolution offered by the compound sensor and processing systems. Thus, speckle related features and thin scene elements (scene short-scale texture and thin structures) are automatically differentiated. The latter are restored with enhanced spatial accuracy, according to the local statistical context.
There is no geometrisation of the scene structural elements, as when using templates-based detectors used in structure retaining speckle filters ([76] [63] [64] [10]). The neighbourhood on which the NMNV local statistics are estimated is delimited by the estimates of
Since the launch of ERS-1 satellite in 1991 temporal series of calibrated SAR images have been made available. This has stimulated the development of multichannel ("vector") filters especially dedicated to filter the speckle in a series of images, taking into account the correlation of the SAR signal between image acquisitions, thus opening the way to furher developments of change detection techniques specific to SAR series of images.
Interest in multichannel adaptive speckle filtering arises from their ability to combine both multi-image diversity through the exploitation of correlation between speckle and scene between images, and spatial diversity through the locally adaptive averaging of pixel values in the spatial domain. The objectives of this combination are the simultaneously achievement of both, a better restoration of existing texture, and a stronger speckle smoothing in textureless areas.
Although numerous work with regard to multi-channel speckle filtering in SAR images had already being done in a remote past, the introduction of A Priori knowledge or A Priori guess which implies the use of Bayesian methods in the processing of multi-SAR’s images, multi-date SAR images or SAR and optical images began only in 1992. Bayesian MAP vector speckle filters developed for multi-channel SAR images incorporate statistical descriptions of the scene and of the speckle in multi-channel SAR images. These models are able to account for the scene and system effects, which result in a certain amount of correlation between the different channels.
To account for the effects due to the spatial correlation of both the speckle and the scene in SAR images, estimators originating from the local ACF’s (
In the case of multi-channel detected SAR images, let define the vector quantities of interest:
where P(
For each individual detected SAR image
P(
For multi-channel detected SAR images, MAP filtering is a vector filtering method. For every channel
The MAP speckle filtering process acts as a data fusion process, since the information content of the whole image series is exploited to restore the radar reflectivity in each individual image. Among other advantages, this allows a better detection and restoration of thin scene details.
To describe the first order statistical properties of a natural scene viewed at the spatial resolution and at the wavelength frequency of a radar remote sensing sensor, it has been shown that a Gamma pdf would be a suitable representation (
However, to describe the first order statistical properties of a natural scene as viewed by diverse radar sensors (different physical scene features), or at different dates (scene evolution over time), there is no analytic multivariate Gamma pdf available under closed-form. Therefore, for the sake of mathematical tractability, a multivariate Gaussian pdf is used as analytic "ersatz" of a multi-channel scene statistical model:
This statistical scene model is convenient to preserve the mathematical tractability of the problem. In addition, the Gaussian model, commonly used to describe the statistical properties of natural scenes in processing of optical imagery, is appropriate as a first-order statistical description of moderate, not too heterogeneous, textures.
However, when scene texture becomes very heterogeneous, this multivariate Gaussian scene model is not any longer reliable, and in the absence of specific prior knowledge about the distribution of scene texture, its model has to be directly estimated from the SAR image.
Let consider the case of a series of
Under this assumption, since each one of the SARs senses slightly different physical properties of the same scene, the joint conditional pdf of the fully developed speckle, P(
where the
The first MAP filtering algorithm for multi-channel detected SAR images results in a set of
where (1
The introduction of coupling between the scene statistical representations leads to a data fusion process taking profit of the correlation between texture as it is observed in all the images in the series. Indeed, replacing speckle noise model by optical noise (or film grain noise, or any other appropriate noise model) in some of the
To filter series of images originating, either from the same SAR system operating in repeat-pass mode, or from different SAR systems with relatively close properties, a second speckle filtering algorithm has been developed. The different SARs may be close in terms of frequency, angle of incidence, spatial resolution and sampling, geometry of images, with difference in polarisation configuration only, or small differences in incidence angle, for example. In such cases, speckle correlation between individual SAR images must be taken into account to deal optimally with system effects on the SAR images series.
Taking into consideration speckle correlation between image channels, the joint conditional pdf of the fully developed speckle P(
To solve this problem, Lee’s assumption [33] is adopted: for multilook SAR images (more than 3 looks), the joint conditional pdf of the speckle can be reasonably approximated by a Gaussian distribution. Therefore, for convenience, P(
where
It is noteworthy that
At this point, the second MAP filtering algorithm for multi-channel detected multilook SAR images results in a set of
where
Including a coupled speckle model (Equation (71)) and a coupled scene model (Equation (74)), this speckle filter takes profit of both speckle and scene texture correlations, thus restoring the radar reflectivity through a complete data fusion process.
In the presence of very strong or mixed textures, eventually combined with the presence of strong topographic relief, it may be hazardous to make an A Priori assumption about the pdf of the radar reflectivity. This situation is often the case in SAR images of dense tropical forest or of urban environments located in slanted terrain with rapidly varying slopes and counter-slopes.
This is also often the case in high-and very-high spatial resolution SAR images, where strong texture is omnipresent. In addition, at such very fine scale, the textural properties of the scene vary strongly within the timeframe elapsed between successive image acquisitions by the same SAR, and exhibit strong differences when imaged by different SARs or using different SAR configurations in terms of wavelength, polarisation, or angle of incidence, for example.
As mentioned precedently (
The entropy of the scene texture [68] [69] [70] is introduced (on a sample of
Because the radar reflectivities
Under this assumption, the Gaussian/Distribution-Entropy MAP (Gaussian-DE MAP) filter for multi-channel multilook detected SAR images (
where (l
To estimate P(
Note that this filter does not need to introduce implicitly scene texture correlation. Indeed, the restoration of the radar reflectivity in each image channel bases only on the A Priori knowledge retrieved from the speckled image channel. Nevertheless, the filter takes profit of speckle correlation between image channels. An application of this filter is illustrated in Figure 1.
TerraSAR-X 4-looks SAR images (HH and VV polarisations) acquired on August 10, 2007, over Oberpfaffenhofen, Germany (Credits: Astrium and InfoTerra; filtered images: Privateers NV, using ®SARScape).
Note that if speckle is not correlated between the
A number of advantages and improvements these filters offer is listed in this section. Most of these advantages arise from the use of the covariance matrices of the speckle and of the imaged scene (
In a series of SAR (but not only...) images, the resolution cells never overlap perfectly between the different individual images. The covariance matrix of the speckle
In addition, the simultaneous attempt to detect images structures and targets in all radar image channels improves the probability to detect such structures. As shown in Figure 1, such an improvement is already very substantial using only two SAR images.
In series of radar images acquired over time, the covariance matrix of the scene
In a series of SAR images acquired by (not too...) different SAR’s, the covariance matrix of the scene enables the detection of more aspects of the scene, as it is viewed by more SAR sensors.
Let consider the mathematical form of the set of Equations (73), (75) and (79). Indeed, their formulation is that of a control system, since both equations can be rewritten under the form of Riccati’s [86] continuous time algebraic matricial equations:
Equation (10) represents the optimal state controlled reconstruction at constant gain of linear invariant processes (
In addition, it is highly remarkable that Riccati’s theorem [86] stipulates the existence of a unique positive definite solution for Equation (10). Therefore, this property holds also for the MAP Equations (73), (75) and (79).
The extension of this noise filtering technique to the case of SAR and optical images set is straightforward, as mentioned in § 5.3. It is also noticeable that, extending this method to the case of complex SAR images, this technique presents a very interesting potential for super-resolution. Such methodologies can be found in the literature (
A major interest of control systems is that they offer wide possibilities for the choice and design of additional commands (statistical and physical models) for further data exploitation. In this view, speckle filtering should be regarded as a first step of integrated application oriented control systems.
SLC images are complex valued images. Hence, every image pixel is assigned a complex value, its complex amplitude
Whereas the intensity
Therefore, the quantity of interest to restore in SLC images through speckle filtering is the radar reflectivity
In SLC radar data the spatial correlation of the speckle can be dealt with by taking into account the spatial covariance matrix of the speckle in the filtering process. Indeed, the joint pdf of a local sample
where
In high and very-high spatial resolution SLC SAR images, which often exhibit strong textural properties, it becomes difficult to consider any theoretical statistical model as a reliable A Priori knowledge about scene texture. In such a situation, it seems reasonable to retrieve statistical scene knowledge directly from the SAR image data [68] [69]Introducing the local entropy of the radar reflectivity as A Priori scene knowledge [70] (
where
An example of application of this filter is shown in Figure 2.
RADARSAT-2 1-look SAR image (HH polarisation) acquired on April 30, 2009, over Capetown, South Africa (Credits: Canadian Space Agency and MDA; filtered images: Privateers NV, using ®SARScape).
Interest in adaptive speckle filtering of SLC image series arises from their ability to combine both temporal or spectral diversity, and spatial diversity. The objective is to obtain a multilook radar reflectivity image, where additional speckle reduction is obtained in the spatial domain by averaging pixel values through locally adaptive filtering.
The final objective is to obtain very strong speckle smoothing in textureless areas and to reach an ENL high enough (
A SAR sensor can produce series of SLC SAR images in three different situations:
In the case of a non-interferometric 1-look complex SAR data set, the individual SAR SLC images acquired independently of each other show low or inexistent speckle correlation between images.
However, in the case of interferometric 1-look complex SAR data, speckle correlation is close to 1 (corresponding to perfect correlation) or very high, since speckle correlation between SAR data acquisitions is exactly the fundamental requirement for interferometry.
As a consequence of these three possible configurations of a series of SLC images, a speckle filter dealing with the whole series must be able to take into account the complex correlation of speckle between the different images. The local complex covariance matrix
Considering the whole set of SLC images, the measurement vector for each pixel is
where
In the case of separate complex looks corresponding to the same SAR data acquisition, or of series of SLC images acquired over time by the same SAR over a time-invariant scene, it is quite reasonable to assume that the textural properties of the scene are similar in all the SLC’s.
Therefore, scene texture may be locally modelled for all SLCs in the series, as well as in the detected multilook image formed by incoherent pixel-per-pixel averaging, by the same Gamma pdf with parameters E[
In this situation, the Complex-Gaussian/Gamma MAP (CGs-Gamma MAP) filter for separate complex looks (
Note that when the SLC images or the separate looks are independent,
Finally, it is noteworthy that the ENL
This relationship may prove useful if SLC images are incoherently summed to produce a
High and very-high spatial resolution SLC SAR images often exhibit strong textural properties. As exposed above, in such a situation, statistical scene knowledge is estimated from the radar data [68] [69]Introducing the local entropy of the radar reflectivity as A Priori scene knowledge [70] (
where
An application of this filter to a series of 18 (3x6) SLC SAR images is shown in Figure 3.
Series of 18 (3x6) COSMO-SkyMed 1-look spotlight SAR images (HH and VV polarisations) acquired between February 2 and September 30, 2009, over Perito Moreno in Patagonia, Argentina (Credits: original images: Italian Space Agency; filtered images: Privateers NV, using ®SARScape).
A polarimetric radar system produces, for each pixel location, a scattering measurement matrix, which is the scattering matrix
The first polarimetric speckle filter ever developed [92] resulted in an optimal summation of the intensities
where
However, Equation (87) clearly shows that the ENL achieved in the span image will barely reach 3, which remains largely insufficient to meet the noise reduction requirements of remote sensing applications. Besides, the physical interpretation of
Lee
Nevertheless, the ultimate aim of polarimetric speckle filtering is to restore the full polarimetric scattering matrix
Under the assumption of reciprocity,
This representation puts emphasis on the radar reflectivities
If the polarimetric measurement is made by a monostatic radar system, the covariance matrix ΣS of the actual polarimetric radar measurement is the speckle-corrupted version of CS.
It is noteworthy that it is possible to produce multilook polarimetric data (
For convenience, the polarimetric covariance matrix is often expressed, without changing its overall information content, under the form of a real valued vector, called the "polarimetric feature vector", or "polarimetric vector"
Two quantities of great interest in polarimetric SAR applications can be obtained from the polarimetric vector:
1) The Phase Differences Δ
2) The (complex) Degrees of Coherences
However, in the actual polarimetric radar measurement, the observations Δ
In the case of polarimetric radar data, ΣS is the actually observed polarimetric covariance matrix, and CS is the unspeckled polarimetric covariance matrix,
where
Using physical backscattering models, assuming (as a rough approximation) that texture is identical in all polarizations, we get the following approximation [72]:
where
The characterisation of scene heterogeneity by only one textural random variable
Introducing the first-order statistical models for fully-polarimetric speckle (Equation (93)) and the polarimetric texture parameter
where Tr(.) denotes the trace of a matrix.
Finally, the restored (speckle filtered) version of the covariance matrix C
In high and very-high spatial resolution polarimetric SAR data, strong and/or mixed textural properties justify to estimate statistical scene knowledge from the data themselves, rather than assuming a A Priori theoretical model. Assuming that textural properties are identical in all configurations of polarisation, the entropy constraint on scene texture ([68] [69] [70]) becomes:
In this case, the complex Wishart/Distribution-Entropy MAP (CW-DE MAP) filter for polarimetric multilook SAR data is expressed as [71]:
E[CS] is obtained using the maximum likelihood estimator (Equation (97)) described in Lopès
ALOS-PALSAR 6-looks polarimetric SAR imagery acquired on June 30, 2006 over Bavaria, Germany (Credits: JAXA and MITI; filtered images: Privateers NV, using ®SARScape).
The texture parameters
Although these fully polarimetric MAP filters assume identical texture properties in the HH, HV, and VV channels, which has been shown both experimentally [96] and theoretically [97] inexact, they have nevertheless been shown to preserve polarimetric signatures [98]. Fully polarimetric speckle filtering is illustrated in Figure 4.
ACF: spatial AutoCorrelation Function (of a signal)
DE: Distribution-Entropy (statistical distribution)
ENL: Equivalent Number of Looks (of a radar image)
LMMSE: Linear Minimum Mean Square Error (estimation)
MAP: Maximum A Posteriori (statistical estimation)
MMSE: Minimum Mean Square Error (estimation)
NMNV: Non-stationary Mean Non-stationary Variance (model)
pdf: Probability Density Function (random variable distribution)
Pfa: Probability of False Alarm (detection)
PSF: Point Spread Function (of an imaging system)
RoA: Ratio Of Amplitudes (structure detector)
SAR: Synthetic Aperture Radar (imaging sensor)
SLC: Single-Look-Complex (radar image)
Wearable technology has seen a great spike in development over the past decade [1, 2, 3] in the form of fabric integrated sensors (heart rate, chemical gas, etc.), information transfer lines and even energy harvesting (piezoelectric). This comes with the need to develop flexible and durable devices that can effectively power them [4, 5]. Energy storage devices typically consist of current collectors (for transfer of current to and from the electrodes), high surface area electrodes (for actively storing energy in the form of ions), insulating separators (for preventing shorting between electrodes) and an electrolyte. High surface area carbon such as graphite and activated carbon has become the standard electrode for many mainstream energy storage applications. However, metals (copper, steel and aluminum) are still heavily relied upon for taking on the role of current collector. This is a major issue for wearable devices as metals very easily succumb to fatigue through bend cycles and are also prone to oxidation. In addition, metal electrodes substantially add to the total weight of the device. Care must be taken to prevent the metal from having direct contact with electrolyte as this would cause unwanted oxidation reactions and subsequent deterioration of the device. All these factors combined make it necessary to find an alternative to the metal current collectors for developing wearable energy storage devices.
\nCarbon based nanomaterials have emerged as promising candidates for the role of a flexible and durable current collector [6]. They boast very high theoretical specific surface area [7, 8, 9, 10, 11] reaching up to 3100 m2 g−1 for graphene [11]. Some of the materials also have very high strength and conductivities owing to their sp2 bonds [12]. All these properties are valuable when it comes to energy storage. Further, most of carbon-based nanomaterials can be synthesized employing non-expensive and scalable processes, making them an ideal alternative to metals. These materials can even be tuned and equipped to function differently depending on the application and need (energy vs. power) represented in the Ragone plot in Figure 1a [13].
\n(a) Ragone plot of specific power vs. specific energy for different energy storing devices—reproduced from [
All the mechanisms discussed above can be taken advantage of by using carbon-based nanomaterials to make them adapt to a wearable form. Energy storage in the form of wearable devices has seen considerable development in recent years and has achieved 3 major milestones (methods).
Introduction of sp2 bonded carbon nanomaterials.
Employment of dip coating and its optimization.
Synthesis of fiber-based devices.
The intention of this chapter is to give a concise view of the progress that the wearable energy storage research has achieved, to discuss the advantages and drawbacks of each milestone and finally to introduce our approach for fabricating integrated energy storage devices.
\nConventional fabric materials do not inherently have the ability to store energy. Thus, the materials that functionalize and allow textile fabric to become energy storage devices are of high importance. It is necessary to explore and develop these materials, mainly carbonaceous, to best suit the application. Owing to this, there has been extensive research conducted on the synthesis/fabrication and characterization of carbon nanomaterials.
\nThe most simplistic form of carbon nanomaterials is the exfoliation of coal to create
SEM images of: (a) activated carbon, reprinted with permission from [
It is seen that sp2 bonded carbon nanomaterials such as CNTs and graphene have the best suitable properties—high surface area, conductivity and strength—to elevate energy storage in the wearable format. Thus, they lend themselves as a pivotal milestone in the development of fabric-based energy storage devices.
\nPrior to establishing the norm of using carbon nanomaterials as conductive pathways/current collectors,
Textile fabric materials made by weaving synthetic or natural fibers are highly flexible and possess high surface area. This makes them ideal templates for housing active materials that can store energy. Dip coating takes advantage of this characteristic by applying CNTs or graphene on the surface of the textile fibers via dipping in an aqueous solution that contains a dispersion of the active material (Figure 3a and b). Drying the fabric results in a coated material that is ready to be used as a flexible electrode. Cotton, owing to its strength and hydrophilicity, is primarily used for this process as it involves an aqueous solution. Hu et al., utilized this process to make CNT coated cotton fabric electrodes [46] (Figure 3a and b). They achieved high active loading of 8 mg/cm2 resulting in a capacitance of 120 F/g. The impregnation and consequent coating is highly dependent on the permeability/retention ability of the textile used in this process. This renders dip coating a non-versatile and non-reproducible process. The density of packing is also affected making the material not highly conductive. To overcome these issues, screen printing was introduced. By the simple employment of a screen resist on top of the fabric before the application of a thick slurry of the active material, a binder-active material solution can be very evenly coated to the surface of the fabric textiles [46]. This allows for good control over exactly how much of active material is loaded depending on the concentration and volume of the slurry used. The method allows for multiple repetitions as an easy way to increase the mass loading. This way, a reproducible capacitance of 90 F/g was achieved [46].
\n(a) Schematic of screen printed CNT-cotton fibers and (b) picture of the dip coating process with cotton fabric. Reprinted with permission from [
However, there is an upper limit to the amount of active material that can be added because of the shrinking porosity of the fabric skeleton with impregnation. As a consequence, there is a maximum for the capacitance values that can be achieved. One factor that can be easily changed to better the properties is the active material. Pseudocapacitive materials can be used as active material known for their higher theoretical specific capacitance (F/g). Thus, with the same mass loading, much higher capacitances can be achieved. Yu et al. explored electrodeposition to coat manganese oxide onto graphene coated textile fibers [47], as shown in Figure 4a, which successfully increased the capacitance to 350 F/g. The same approach can be adopted to deposit other pseudocapacitive material, such as ruthenium oxide or conductive polymers. An asymmetrical device with high energy densities can be fabricated by carefully choosing the electrodes based on their working reduction potential ranges. Changing the crystallinity and nanostructure of the deposited material by controlling the deposition parameters and composition can also yield better properties. The alpha phase of the manganese oxide is more conductive and electrochemically stable than its beta and amorphous forms. Thus, a very fine nanorod-structured deposition of alpha phase manganese oxide can greatly increase the energy density. Another option for the device property improvement is exploring more electrochemically active materials such as lithium metal oxides, sulfur, etc. Thus, with the use of a polymer electrolyte matrix separator, a flexible battery device can be fabricated.
\n(a) Schematic of electrodeposition of manganese oxide on graphene coated textile fibers; (b) half-cell cyclic voltammetry of manganese oxide—graphene—fabric electrode; (c) capacitance vs. scan rate curves. Reprinted with permission from [
As demonstrated in the cyclic voltammetry curves in Figure 4b and c, there is still a very non-capacitive (rectangular) nature to the fabric devices. This is in part a contribution from the low loading of conductive material—CNT or graphene. The other active materials (pseudocapacitive or battery) are not very conductive in nature and highly rely upon the carbon-base material for their electron transfer requirements. Thus, there are heavy losses in terms of power density in such materials. This can be avoided with the use of metals as current collectors, however making the device non-flexible.
\nThe most promising advantage of the discussed dip coating is the low production cost and time consumption. However, further improvement of the carbon coating material needs to be realized to progress in this fabrication method. An alternative is a fully core to shell design made completely of conductive carbon material and coated active material. This would result in a 100% mass loading of active material and would give more energy per unit gram of fabric.
\nElectrodes in the form of yarns that can be readily stitched as a textile fabric has the potential to overcome many of the disadvantages discussed in the previous section. The research in fiber/yarn-based electrodes began with dip coating techniques and as discussed in the sections before, some challenges have emerged. The conductivity and active loading of the material was low, and the related research eventually moved towards more promising approaches. One of them is the possibility to realize a fully active material loaded fiber form.
\nA conductive carbon-based core that provides the strength, conductivity and flexibility with an outer shell of active material that secures high energy density has been explored. CNTs dispersed in acid and extruded in the form of a fibers which have been easily fabricated. These porous fibers act as a current collector and housing for the active material. Vertically aligned CNT arrays can be used to spin long and porous fibers. These are produced in a more pristine format and hence can be easily processed and react less with electrolytes. These full core-shell carbon structures have very high surface area ~1400 m2/g, which gives the opportunity to take advantage of the ELDC characteristic of these fibers [48]. Novel fiber structures utilizing higher surface area graphene have also been fabricate. RGO based fibers that are highly porous and boasting surface area up to 2400 m2/g have been reported, which results in a very high energy density of 400 F/g [49] (Figure 5ia–c). Hybrids involving both CNTs and graphene have been synthesized, utilizing the high surface area of both material to create a sponge like fiber material [48] (Figure 5iia–c). Flexible fibers were successfully woven into a fabric and its performance remained consistent through exposure to bending stress. The major drawback of these high energy storage materials is their strength. Although their Young’s modulus is appreciable, which allows them to be flexible, their tensile strain to failure is quite low. This makes them prone to breakage and unfit to survive as a self-supporting fabric patch. Addition of any active material to the fiber would make them too brittle to handle.
\n(a) SEM image of electrode base material; (b) cyclic voltammetry graph of the working device; (c) picture of full device. (i) RGO fiber reprinted with permission from [
Carbon fibers, which are a very sturdy and high strength materials, haves been used as a substrate to house pseudocapacitive manganese oxide [50] (Figure 5v a-c). The resulting fiber proved to be quite strong and showed appreciable energy storage values. However, the electrical conductivity of the material is still a concern. Conventional carbon nanotube fibers have also been used as conductive substrate for housing manganese oxide [51] (Figure 5iv a–c). The resulting composite was wound like a spring and encapsulated in a gel polymer, showing no losses in energy storage properties for tensile strains of up to 100%.
\nA polymer core with carbon nanomaterials grown/deposited across the surface derives most of its strength from the elastic polymer and can sustain higher tensile strains. Active material can then be successfully decorated on the surface [52] (Figure 5v a–c). This however suffers from the loss of conductivity and requires an additional current collector in the form of a multiplied metal yarn structure.
\nFibers made completely out of electrochemically active material such as poly(3,4-ethylenedioxythiophene) (PEDOT) have also been developed [53]. The biscrolled PEDOT with the CNT matrix makes the composite quite easy to scale up. Further, due to the high electrical contact between the current collector and active material, the device shows good performance at 1 mV/s scan rate. The greatly twisted fiber boasts very high active material loading and high volumetric capacitance.
\nThere are some challenges to the development of these forms of devices. They have the potential to be composed completely of active material leading to unsurpassed energy storage capabilities, however, the loss in strength of the material needs to be countered. A fiber that possess both great tensile strain, strength and high loading of active material could pave way to the next generation of wearable devices. We believe that the key lies in highly densified CNT fibers with modified surfaces.
\nBelow are presented experimental results on ionic liquid-based fabric capacitors obtained by our team. A factor that is often ignored when it comes to wearable devices is the evaluation of their properties as a function of the weight of the materials. In these cases, most used is the area of the material or only the weight of the active material is taken into consideration. This becomes a limitation when scaling to industry production as bulky materials will not be suitable for powering fabric-based devices. Most of literature data still relies on textile fibers to provide the structural and flexible skeleton for their electrodes. This requires the usage of two layers of fabrics (electrodes) that adds unnecessary weight to the full device which is mostly never reported. An aspect to consider is the synthesis approach. The more structured the active synthesized material, the higher the surface area and therefore gives a higher specific capacitance. A drawback of this is the cost—both monetary and time consuming—that scales exponentially with the structure complexity. The other major consideration that is overlooked is the practical feasibility of the devices fulfilling certain applications. Most wearable energy storage devices have adopted gel-based polymer electrolyte systems to create a flexible separator. However, they still rely upon aqueous electrolytes such as phosphoric acid, potassium hydroxide, etc. This caps the voltage window for conventional devices with high cyclability to a low value of 0.8 V. However, even LEDs require around 1.3 V to operate. The non-conventional asymmetrical devices can push the envelope to around 1.6 V, but beyond that they suffer from heavy capacitance losses. In this section, we hope to provide a solution based on our work to these practical challenges.
\nAqueous electrolytes, although inexpensive and stable, are limited by their low reduction potentials with most conventional carbon materials. Anything beyond voltage window of 1 V results in irrecoverable losses in both the electrode material and the electrolyte. This limitation comes mainly from the presence of water. Thus, a change from aqueous to organic solutions results in a drastic change in the voltage window stability range. Commonly explored solutions are ethanol with suitable salts such as lithium perchlorate dissolved in them. Devices made with this electrolyte can expand the operation window from 1 V to around 2.2 V. This window decreases with introduction of pseudocapacitive materials to around 1.2 V, which is much higher than the 0.8 V offered by aqueous electrolytes. A device with asymmetrical electrodes can increase this window up to 2.2 V. To achieve a higher voltage window more expensive and less explored materials need to be considered. The latter are known as ionic liquids (ILs). These are a highly reactive group of electrolytes that are a combination of an organic cation with a very electronegative anion. Some of them—1-ethyl-3-methylimidazolium tetrafluoroborate (EMIMBF4)—have a very large and stable working voltage window, going as high as 4.5 V. They find usage as catalysts for higher voltage reduction reactions, however there is an emerging interest in their utilization in energy storage applications. ILs are most commonly combined with polyvinylidene fluoride-hexafluoropropylene (PVDF-HFP) to create a gel polymer electrolyte separator matrix.
\nWe introduce here a novel way to incorporate the IL EMIMBF4 into any fabric material (from stretchable polyester sports-wear to sturdy military fabric) that utilizes only the essential amount of fabric material. For our tests we procured normal Bucky paper (BP) from General Nano, LLC which is a matrix of single walled carbon nanotubes under no alignment. Our procedure includes using the fabric as a separator to house the gel electrolyte and eventually be sandwiched between symmetrical BP electrodes (Figure 6a). Initially, polyvinyl alcohol (PVA)-sulfuric acid gel matrix was used. The gel electrolyte (1 g of PVA in 10 ml 0.1 M sulfuric acid) was dropped into the fabric. The soaked fabric was then allowed to dry till it reached a gel-like consistency. The electrodes were then applied on top of the electrolyte and allowed to further dry until they became integrated into the fabric electrolyte structure. This device was tested electrochemically using a Potentiostat Interface 1000, Gamry Instruments and showed results comparable to conventional devices made without the fabric separator. A similar gel polymer concentration was utilized for the IL (3 ml EMIMBF4 in 10 ml acetone with 1 g PVDF). The same methodology was adopted to create the gel fabric. However, the electrochemical results with the device were not comparable with average values of conventional devices. This was not an indication of the limit of the electrode as the sulfuric acid device gave appreciable values. We added a further step to the device fabrication, which included first soaking the electrode in a solution of the IL plus acetone, and then incorporating it into the fabric structure. This resulted in an increase of the device energy density (Table 1 and Figure 6b–d). Since acetone is fast evaporating solvent, it did not allow for the electrode to be fully penetrated with the electrolyte before drying. The described soaking procedure ensured complete utilization of the electrode surface area and thus increased the stored energy.
\n(a) Schematic of creating gel fabric structure with Bucky paper electrode pressed on top; (b) cyclic voltammetry curves at 200 mV/s for normal BP electrode and BP electrode pre-soaked in IL solution; (c) different scan rate cyclic voltammetry curves of IL-soaked device; and (d) charge and discharge curves of the fabricated device obtained at different current densities.
Gel electrolyte | \nSpecific capacitance (F/g) | \nEnergy density (Wh/kg) | \n
---|---|---|
PVA-sulfuric acid (1 V) | \n11.54 | \n3.2 | \n
PVDF-ionic liquid (3 V) | \n61.66 | \n19.53 | \n
Ionic liquid soak | \n137.6 | \n48.62 | \n
Specific capacitance and energy density values of the fabric device achieved with different polymer electrolytes and preparation techniques.
The device can be steadily cycled between 0 and 3 V window range without fade in capacitance values. This is not the only major advantage of such a device. Since the fabric is being used as a separator and not as the electrode itself, it essentially reduces the weight of the device in half, as compared to other wearable energy storage devices that rely on a fabric skeleton backing for each electrode. The fabric can then be further sown in as a patch thus making the only additional weight contribution to the device that of the gel electrolyte. Another key advantage of the described system is the ability to be easily modified for various applications. Depending on the energy need, the area of the electrode used can be increased or decreased to give highly tunable capacitance values (Figure 7a and b). Since the application and fabrication of the gel fabric is easily controlled, the device can also be made into sections. Various electrodes can be applied next to each other as isolated devices on the same fabric. One patch of fabric could contain many isolated devices. This gives high tunability to the device. Three isolated devices were made in one patch and when connected in series it achieved a working voltage of 9 V. In a parallel wiring the device achieved 3 times the current output and energy density of an individual one (Figure 7c–e). The fabricated device is highly versatile in terms of how it can fit to different applications. Electrical contacts can be made by simply applying copper tapes with silver paint to the ends of the electrodes. These connections need not be pre-made, giving a further degree of freedom.
\n(a) Pictures of different size with increasing areas of electrode materials used for the fabric device; (b) corresponding cyclic voltammetry profiles at 200 mV/s scan rate; (c) picture of isolated devices in a single patch of fabric; (d) corresponding cyclic voltammetry profiles at 200 mV/s scan rate in parallel connections and (e) corresponding cyclic voltammetry profiles at 200 mV/s scan rate in series connections.
Textile fabrics are exposed to stress in the form of flexing, bending or wrinkling. This is unavoidable in clothing when the wearer executes any form of motion. Such an environment must be taken into consideration when making fabric integrated devices. Here we tested our fabric device by exposing them to 10,000 cycles, where in each cycle it was bent to an angle of 120° and brought back to normal shape (Figure 8a). This is a higher degree of bending than fabrics would have to usually sustain on a daily basis. The device showed no depreciation in terms of capacitance after the cycling (Figure 8b). Another consideration to be taken into account is the exposure to moisture in the form of sweat from the wearer. Our device was soaked in a bath of water and cycled. In this test no observable depreciation in energy density was noticed (Figure 8c). Finally, the device was cycled 8000 times at a current density of 2 A/g that resulted in a final capacitance of 102% (Figure 8d). This increased capacitance is due to the forcible opening of the pores of the BP electrode with constant cycling. The high retention rate is very promising and ensures that the electrolyte is not being degraded at such high voltage ranges.
\n(a) Picture of the degree of bending during each cycle of the stress test; (b) cyclic voltammetry curve of the device before and after bending; (c) picture of the water bath immersion tests; and (d) cycling curve of the device at 2 A/g current density.
There still exists room for improvement for the described architecture of the fabric devices. Altering the electrodes by creating more energy dense materials is a quick way to further improve the properties of the device. Using pseudocapacitive materials like transition metal oxides or conductive polymers in an asymmetrical electrode arrangement has the potential to further enhance the properties. This will be explored in our following works.
\nThe wearable energy storage devices have seen much development over the last decade. This evolution included starting from cotton coated electrodes that were not highly reproducible and moving to more reliable techniques such as screen printing using a polymer resist. Further, full active material loaded yarns have been realized. There are however drawbacks with each of the approaches which include either a limit to the active material content and subsequently the energy density, or a lack of strong materials that can sustain the wear and tear of fabrics that will potentially go into articles of clothing. The most promise is shown when using yarn-based devices that, if coupled with high strength, may provide the best properties.
\nIn our work we designed an approach to making a tunable device that can accommodate a various range of practical applications including those requiring voltages as high as 9 V or high current ratings. The gel fabric separator fabricated and reported here utilizes just the essential amounts of fabric, which can be easily patched onto articles of clothing thus adding no extra weight. The final device we created exhibits an energy density of 48 Wh/kg at 1 A/g current density and can sustain high cycling without any noticeable losses in capacitance. The described fabrication approach is versatile and can be adopted for making various electrodes that can further improve the properties of the fabric energy storage devices.
\nThis work was partly funded by the following grants: DURIP-ONR N00014-15-1-2473, AFOSR LRIR 16COR322, ARMY W911NF-16-2-0026, NASA NNX13AF46A, and NNC16CA17C. The financial support from the above-mentioned Government institutions is highly appreciated.
\nThe authors declare that there was no conflict of interest during this work.
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On September, 29th 2006 he has won a post PhD fellowship from the university of Bologna (from October 2006 to October 2008), at the competitive examination he was ranked first in the industrial engineering area. He extensively served as referee for several international journals. He is author/coauthor of more than 100 research papers. He has been involved in some projects supported by MURST and European Community. 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Because of this aspect, the framework of modern forensic medicine includes a new field, that of forensic genetics, that mostly involves working with investigations that have human genotype identification as a goal.",book:{id:"5259",slug:"forensic-analysis-from-death-to-justice",title:"Forensic Analysis",fullTitle:"Forensic Analysis - From Death to Justice"},signatures:"Raluca Dumache, Veronica Ciocan, Camelia Muresan and Alexandra Enache",authors:[{id:"179199",title:"Dr.",name:"Raluca",middleName:null,surname:"Dumache",slug:"raluca-dumache",fullName:"Raluca Dumache"},{id:"181860",title:"Prof.",name:"Alexandra",middleName:null,surname:"Enache",slug:"alexandra-enache",fullName:"Alexandra Enache"},{id:"190151",title:"Dr.",name:"Camelia",middleName:null,surname:"Muresan",slug:"camelia-muresan",fullName:"Camelia Muresan"},{id:"190153",title:"Dr.",name:"Veronica",middleName:null,surname:"Ciocan",slug:"veronica-ciocan",fullName:"Veronica Ciocan"}]},{id:"19164",doi:"10.5772/19434",title:"Epidemiology and Diagnostic Problems of Electrical Injury in Forensic Medicine",slug:"epidemiology-and-diagnostic-problems-of-electrical-injury-in-forensic-medicine",totalDownloads:6433,totalCrossrefCites:5,totalDimensionsCites:6,abstract:null,book:{id:"243",slug:"forensic-medicine-from-old-problems-to-new-challenges",title:"Forensic Medicine",fullTitle:"Forensic Medicine - From Old Problems to New Challenges"},signatures:"William Dokov and Klara Dokova",authors:[{id:"34961",title:"Dr.",name:"Klara",middleName:null,surname:"Dokova",slug:"klara-dokova",fullName:"Klara Dokova"},{id:"34976",title:"Dr.",name:"Klara",middleName:null,surname:"Dokova",slug:"klara-dokova",fullName:"Klara Dokova"}]}],mostDownloadedChaptersLast30Days:[{id:"50789",title:"Molecular Genetics and its Applications in Forensic Sciences",slug:"molecular-genetics-and-its-applications-in-forensic-sciences",totalDownloads:4655,totalCrossrefCites:4,totalDimensionsCites:7,abstract:"The way to medico legal identification was open at the end of the twenty‐first century by the “digital fingerprinting” represented by the multifactorial phenotypical trait, determined by both polygenic and environmental factors, followed by group‐specific antigens, or with specificity for blood and tissue, and ending with the DNA molecule in use today. Because of this aspect, the framework of modern forensic medicine includes a new field, that of forensic genetics, that mostly involves working with investigations that have human genotype identification as a goal.",book:{id:"5259",slug:"forensic-analysis-from-death-to-justice",title:"Forensic Analysis",fullTitle:"Forensic Analysis - From Death to Justice"},signatures:"Raluca Dumache, Veronica Ciocan, Camelia Muresan and Alexandra Enache",authors:[{id:"179199",title:"Dr.",name:"Raluca",middleName:null,surname:"Dumache",slug:"raluca-dumache",fullName:"Raluca Dumache"},{id:"181860",title:"Prof.",name:"Alexandra",middleName:null,surname:"Enache",slug:"alexandra-enache",fullName:"Alexandra Enache"},{id:"190151",title:"Dr.",name:"Camelia",middleName:null,surname:"Muresan",slug:"camelia-muresan",fullName:"Camelia Muresan"},{id:"190153",title:"Dr.",name:"Veronica",middleName:null,surname:"Ciocan",slug:"veronica-ciocan",fullName:"Veronica Ciocan"}]},{id:"19160",title:"Death Scene Investigation from the Viewpoint of Forensic Medicine Expert",slug:"death-scene-investigation-from-the-viewpoint-of-forensic-medicine-expert",totalDownloads:27471,totalCrossrefCites:2,totalDimensionsCites:7,abstract:null,book:{id:"243",slug:"forensic-medicine-from-old-problems-to-new-challenges",title:"Forensic Medicine",fullTitle:"Forensic Medicine - From Old Problems to New Challenges"},signatures:"Serafettin Demirci and Kamil Hakan Dogan",authors:[{id:"30612",title:"Prof.",name:"Kamil Hakan",middleName:null,surname:"Dogan",slug:"kamil-hakan-dogan",fullName:"Kamil Hakan Dogan"},{id:"32211",title:"Dr.",name:"Serafettin",middleName:null,surname:"Demirci",slug:"serafettin-demirci",fullName:"Serafettin Demirci"}]},{id:"57199",title:"Negative Autopsy in Infant and Juvenile Population: Role of Cardiac Arrhythmias",slug:"negative-autopsy-in-infant-and-juvenile-population-role-of-cardiac-arrhythmias",totalDownloads:1417,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Negative autopsy is a post-mortem examination in which a comprehensive analysis does not provide a cause of death. These include situation of death, anatomical and histological analysis, toxicology and microbiological study. A low part of autopsies remain without a conclusive cause of death, but all these cases are usually seen in young population, apparently healthy who died suddenly and unexpectedly. In these situations a cardiac arrhythmia is suspected as cause of death and genetic testing is recommended despite not regularly performed. Sudden death is a natural and unexpected decease that occurs in apparently healthy people, or whose disease was not severe enough to expect a fatal outcome. It can be due to several pathologies, usually of cardiac cause and called sudden cardiac death. In infants and young people, both long QT syndrome and catecholaminergic polymorphic ventricular tachycardia are main causes in negative autopsies. These genetic diseases lead to ventricular fibrillation, syncope and sudden cardiac death in a normal heart. Unfortunately, sudden cardiac death could be the first manifestation of the diseases, being early identification and prevention a crucial point in current medical practice. This chapter focuses on sudden death and negative autopsy in young population, mainly due to cardiac arrhythmias.",book:{id:"6262",slug:"post-mortem-examination-and-autopsy-current-issues-from-death-to-laboratory-analysis",title:"Post Mortem Examination and Autopsy",fullTitle:"Post Mortem Examination and Autopsy - Current Issues From Death to Laboratory Analysis"},signatures:"Georgia Sarquella-Brugada, Sergi Cesar, Anna Fernandez-Falgueras,\nMaria Dolores Zambrano, Anna Iglesias, Josep Brugada, Ramon\nBrugada and Oscar Campuzano",authors:[{id:"54165",title:"Prof.",name:"Ramon",middleName:null,surname:"Brugada",slug:"ramon-brugada",fullName:"Ramon Brugada"},{id:"54168",title:"Dr.",name:"Oscar",middleName:null,surname:"Campuzano",slug:"oscar-campuzano",fullName:"Oscar Campuzano"},{id:"218478",title:"Dr.",name:"Georgia",middleName:null,surname:"Sarquella-Brugada",slug:"georgia-sarquella-brugada",fullName:"Georgia Sarquella-Brugada"},{id:"218479",title:"Dr.",name:"Sergi",middleName:null,surname:"Cesar",slug:"sergi-cesar",fullName:"Sergi Cesar"},{id:"218480",title:"MSc.",name:"Anna",middleName:null,surname:"Fernandez-Falgueras",slug:"anna-fernandez-falgueras",fullName:"Anna Fernandez-Falgueras"},{id:"218482",title:"Dr.",name:"Maria Dolores",middleName:null,surname:"Zambrano",slug:"maria-dolores-zambrano",fullName:"Maria Dolores Zambrano"},{id:"218483",title:"MSc.",name:"Anna",middleName:null,surname:"Iglesias",slug:"anna-iglesias",fullName:"Anna Iglesias"},{id:"218484",title:"Prof.",name:"Josep",middleName:null,surname:"Brugada",slug:"josep-brugada",fullName:"Josep Brugada"}]},{id:"57778",title:"Defining Dental Age for Chronological Age Determination",slug:"defining-dental-age-for-chronological-age-determination",totalDownloads:2606,totalCrossrefCites:1,totalDimensionsCites:3,abstract:"Dental age assessment is one of the most reliable methods of chronological age estimation used for criminal, forensic and anthropologic purposes. Visual, radiographic, chemical and histological techniques can be used for dental age estimation. Visual method is based on the sequence of eruption of the teeth and morphological changes that are caused due to function such as attrition, changes in color that are indicators of aging. Radiographs of the dentition can be used to determine the stage of dental development of the teeth from initial mineralization of a tooth, crown formation to root apex maturation. Histological methods require the preparation of the tissues for detailed microscopic examination. The chemical analysis of dental hard tissues determines alterations in ion levels with age, whereas the histological and chemical methods are invasive methods requiring extraction/sectioning of the tooth. In this chapter, the different techniques and considered studies were overviewed in conjunction with their advantages and disadvantages. It needs to be taken into consideration that rather than restricting on one age estimation technique, using the other available techniques additionally and performing repetitive measurements may be beneficial for accurate age estimation.",book:{id:"6262",slug:"post-mortem-examination-and-autopsy-current-issues-from-death-to-laboratory-analysis",title:"Post Mortem Examination and Autopsy",fullTitle:"Post Mortem Examination and Autopsy - Current Issues From Death to Laboratory Analysis"},signatures:"Fatma Deniz Uzuner, Emine Kaygısız and Nilüfer Darendeliler",authors:[{id:"172009",title:"Dr.",name:"Fatma Deniz",middleName:null,surname:"Uzuner",slug:"fatma-deniz-uzuner",fullName:"Fatma Deniz Uzuner"},{id:"200985",title:"Dr.",name:"Emine",middleName:null,surname:"Kaygisiz",slug:"emine-kaygisiz",fullName:"Emine Kaygisiz"},{id:"222232",title:"Prof.",name:"Nilufer",middleName:null,surname:"Darendeliler",slug:"nilufer-darendeliler",fullName:"Nilufer Darendeliler"}]},{id:"50757",title:"Forensic Analysis of the Wakayama Arsenic Murder Case",slug:"forensic-analysis-of-the-wakayama-arsenic-murder-case",totalDownloads:2582,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"This is a review paper of forensic analysis of a murder case of Wakayama arsenic poisoning incident. The influence of this case on scientific research was not small in such a way that papers related to PTSD, disaster medical, copycats, chemical analysis, unwanted chemicals in food, terrorism, and so on were published. The forensic analyses on Wakayama arsenic poisoning incidence have characteristic that SPring-8, a largest synchrotron radiation facility, was used, as well as many other analytical techniques, but now most of the forensic analyses submitted from the prosecutor have been revealed to be fabrication, hiding the truth by logarithmic calculations, and therefore not scientific. Most of the testimonies at the court by the analysts were also lies. Examples of such false analyses are explained.",book:{id:"5259",slug:"forensic-analysis-from-death-to-justice",title:"Forensic Analysis",fullTitle:"Forensic Analysis - From Death to Justice"},signatures:"Jun Kawai",authors:[{id:"180878",title:"Prof.",name:"Jun",middleName:null,surname:"Kawai",slug:"jun-kawai",fullName:"Jun Kawai"}]}],onlineFirstChaptersFilter:{topicId:"180",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:8,limit:8,total:0},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:90,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:108,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:140,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:123,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:22,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:11,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:"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"}}}},{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"}}}}]},series:{item:{id:"6",title:"Infectious Diseases",doi:"10.5772/intechopen.71852",issn:"2631-6188",scope:"This series will provide a comprehensive overview of recent research trends in various Infectious Diseases (as per the most recent Baltimore classification). Topics will include general overviews of infections, immunopathology, diagnosis, treatment, epidemiology, etiology, and current clinical recommendations for managing infectious diseases. Ongoing issues, recent advances, and future diagnostic approaches and therapeutic strategies will also be discussed. This book series will focus on various aspects and properties of infectious diseases whose deep understanding is essential for safeguarding the human race from losing resources and economies due to pathogens.",coverUrl:"https://cdn.intechopen.com/series/covers/6.jpg",latestPublicationDate:"August 12th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:13,editor:{id:"131400",title:"Prof.",name:"Alfonso J.",middleName:null,surname:"Rodriguez-Morales",slug:"alfonso-j.-rodriguez-morales",fullName:"Alfonso J. 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He is an External Professor, Master in Research on Tropical Medicine and International Health, Universitat de Barcelona, Spain. He is also a professor at the Master in Clinical Epidemiology and Biostatistics, Universidad Científica del Sur, Lima, Peru. In 2021 he has been awarded the “Raul Isturiz Award” Medal of the API. Also, in 2021, he was awarded with the “Jose Felix Patiño” Asclepius Staff Medal of the Colombian Medical College, due to his scientific contributions to COVID-19 during the pandemic. He is currently the Editor in Chief of the journal Travel Medicine and Infectious Diseases. His Scopus H index is 47 (Google Scholar H index, 68).",institutionString:"Institución Universitaria Visión de las Américas, Colombia",institution:null},editorTwo:null,editorThree:null},subseries:{paginationCount:6,paginationItems:[{id:"22",title:"Applied Intelligence",coverUrl:"https://cdn.intechopen.com/series_topics/covers/22.jpg",isOpenForSubmission:!0,annualVolume:11418,editor:{id:"27170",title:"Prof.",name:"Carlos",middleName:"M.",surname:"Travieso-Gonzalez",slug:"carlos-travieso-gonzalez",fullName:"Carlos Travieso-Gonzalez",profilePictureURL:"https://mts.intechopen.com/storage/users/27170/images/system/27170.jpeg",biography:"Carlos M. Travieso-González received his MSc degree in Telecommunication Engineering at Polytechnic University of Catalonia (UPC), Spain in 1997, and his Ph.D. degree in 2002 at the University of Las Palmas de Gran Canaria (ULPGC-Spain). He is a full professor of signal processing and pattern recognition and is head of the Signals and Communications Department at ULPGC, teaching from 2001 on subjects on signal processing and learning theory. His research lines are biometrics, biomedical signals and images, data mining, classification system, signal and image processing, machine learning, and environmental intelligence. He has researched in 52 international and Spanish research projects, some of them as head researcher. He is co-author of 4 books, co-editor of 27 proceedings books, guest editor for 8 JCR-ISI international journals, and up to 24 book chapters. He has over 450 papers published in international journals and conferences (81 of them indexed on JCR – ISI - Web of Science). He has published seven patents in the Spanish Patent and Trademark Office. He has been a supervisor on 8 Ph.D. theses (11 more are under supervision), and 130 master theses. He is the founder of The IEEE IWOBI conference series and the president of its Steering Committee, as well as the founder of both the InnoEducaTIC and APPIS conference series. He is an evaluator of project proposals for the European Union (H2020), Medical Research Council (MRC, UK), Spanish Government (ANECA, Spain), Research National Agency (ANR, France), DAAD (Germany), Argentinian Government, and the Colombian Institutions. He has been a reviewer in different indexed international journals (<70) and conferences (<250) since 2001. He has been a member of the IASTED Technical Committee on Image Processing from 2007 and a member of the IASTED Technical Committee on Artificial Intelligence and Expert Systems from 2011. \n\nHe has held the general chair position for the following: ACM-APPIS (2020, 2021), IEEE-IWOBI (2019, 2020 and 2020), A PPIS (2018, 2019), IEEE-IWOBI (2014, 2015, 2017, 2018), InnoEducaTIC (2014, 2017), IEEE-INES (2013), NoLISP (2011), JRBP (2012), and IEEE-ICCST (2005)\n\nHe is an associate editor of the Computational Intelligence and Neuroscience Journal (Hindawi – Q2 JCR-ISI). He was vice dean from 2004 to 2010 in the Higher Technical School of Telecommunication Engineers at ULPGC and the vice dean of Graduate and Postgraduate Studies from March 2013 to November 2017. He won the “Catedra Telefonica” Awards in Modality of Knowledge Transfer, 2017, 2018, and 2019 editions, and awards in Modality of COVID Research in 2020.\n\nPublic References:\nResearcher ID http://www.researcherid.com/rid/N-5967-2014\nORCID https://orcid.org/0000-0002-4621-2768 \nScopus Author ID https://www.scopus.com/authid/detail.uri?authorId=6602376272\nScholar Google https://scholar.google.es/citations?user=G1ks9nIAAAAJ&hl=en \nResearchGate https://www.researchgate.net/profile/Carlos_Travieso",institutionString:null,institution:{name:"University of Las Palmas de Gran Canaria",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"23",title:"Computational Neuroscience",coverUrl:"https://cdn.intechopen.com/series_topics/covers/23.jpg",isOpenForSubmission:!0,annualVolume:11419,editor:{id:"14004",title:"Dr.",name:"Magnus",middleName:null,surname:"Johnsson",slug:"magnus-johnsson",fullName:"Magnus Johnsson",profilePictureURL:"https://mts.intechopen.com/storage/users/14004/images/system/14004.png",biography:"Dr Magnus Johnsson is a cross-disciplinary scientist, lecturer, scientific editor and AI/machine learning consultant from Sweden. \n\nHe is currently at Malmö University in Sweden, but also held positions at Lund University in Sweden and at Moscow Engineering Physics Institute. \nHe holds editorial positions at several international scientific journals and has served as a scientific editor for books and special journal issues. \nHis research interests are wide and include, but are not limited to, autonomous systems, computer modeling, artificial neural networks, artificial intelligence, cognitive neuroscience, cognitive robotics, cognitive architectures, cognitive aids and the philosophy of mind. \n\nDr. Johnsson has experience from working in the industry and he has a keen interest in the application of neural networks and artificial intelligence to fields like industry, finance, and medicine. \n\nWeb page: www.magnusjohnsson.se",institutionString:null,institution:{name:"Malmö University",institutionURL:null,country:{name:"Sweden"}}},editorTwo:null,editorThree:null},{id:"24",title:"Computer Vision",coverUrl:"https://cdn.intechopen.com/series_topics/covers/24.jpg",isOpenForSubmission:!0,annualVolume:11420,editor:{id:"294154",title:"Prof.",name:"George",middleName:null,surname:"Papakostas",slug:"george-papakostas",fullName:"George Papakostas",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002hYaGbQAK/Profile_Picture_1624519712088",biography:"George A. 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He has (co)authored more than 150 publications in indexed journals, international conferences and book chapters, 1 book (in Greek), 3 edited books, and 5 journal special issues. His publications have more than 2100 citations with h-index 27 (GoogleScholar). His research interests include computer/machine vision, machine learning, pattern recognition, computational intelligence. \nDr. Papakostas served as a reviewer in numerous journals, as a program\ncommittee member in international conferences and he is a member of the IAENG, MIR Labs, EUCogIII, INSTICC and the Technical Chamber of Greece (TEE).",institutionString:null,institution:{name:"International Hellenic University",institutionURL:null,country:{name:"Greece"}}},editorTwo:null,editorThree:null},{id:"25",title:"Evolutionary Computation",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",isOpenForSubmission:!0,annualVolume:11421,editor:{id:"136112",title:"Dr.",name:"Sebastian",middleName:null,surname:"Ventura Soto",slug:"sebastian-ventura-soto",fullName:"Sebastian Ventura Soto",profilePictureURL:"https://mts.intechopen.com/storage/users/136112/images/system/136112.png",biography:"Sebastian Ventura is a Spanish researcher, a full professor with the Department of Computer Science and Numerical Analysis, University of Córdoba. Dr Ventura also holds the positions of Affiliated Professor at Virginia Commonwealth University (Richmond, USA) and Distinguished Adjunct Professor at King Abdulaziz University (Jeddah, Saudi Arabia). Additionally, he is deputy director of the Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) and heads the Knowledge Discovery and Intelligent Systems Research Laboratory. He has published more than ten books and over 300 articles in journals and scientific conferences. Currently, his work has received over 18,000 citations according to Google Scholar, including more than 2200 citations in 2020. In the last five years, he has published more than 60 papers in international journals indexed in the JCR (around 70% of them belonging to first quartile journals) and he has edited some Springer books “Supervised Descriptive Pattern Mining” (2018), “Multiple Instance Learning - Foundations and Algorithms” (2016), and “Pattern Mining with Evolutionary Algorithms” (2016). He has also been involved in more than 20 research projects supported by the Spanish and Andalusian governments and the European Union. He currently belongs to the editorial board of PeerJ Computer Science, Information Fusion and Engineering Applications of Artificial Intelligence journals, being also associate editor of Applied Computational Intelligence and Soft Computing and IEEE Transactions on Cybernetics. Finally, he is editor-in-chief of Progress in Artificial Intelligence. He is a Senior Member of the IEEE Computer, the IEEE Computational Intelligence, and the IEEE Systems, Man, and Cybernetics Societies, and the Association of Computing Machinery (ACM). Finally, his main research interests include data science, computational intelligence, and their applications.",institutionString:null,institution:{name:"University of Córdoba",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"26",title:"Machine Learning and Data Mining",coverUrl:"https://cdn.intechopen.com/series_topics/covers/26.jpg",isOpenForSubmission:!0,annualVolume:11422,editor:{id:"24555",title:"Dr.",name:"Marco Antonio",middleName:null,surname:"Aceves Fernandez",slug:"marco-antonio-aceves-fernandez",fullName:"Marco Antonio Aceves Fernandez",profilePictureURL:"https://mts.intechopen.com/storage/users/24555/images/system/24555.jpg",biography:"Dr. Marco Antonio Aceves Fernandez obtained his B.Sc. (Eng.) in Telematics from the Universidad de Colima, Mexico. 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He has received many awards and honors in India and abroad including various Young Scientist Awards, BBSRC India Partnering Award, and Dr. JC Bose National Award of Department of Biotechnology, Min. of Science and Technology, Govt. of India. Dr. Saxena is a fellow of various international societies/academies including the Royal College of Pathologists, United Kingdom; Royal Society of Medicine, London; Royal Society of Biology, United Kingdom; Royal Society of Chemistry, London; and Academy of Translational Medicine Professionals, Austria. He was named a Global Leader in Science by The Scientist. 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Saxena is a vice dean and professor at King George's Medical University, Lucknow, India. His research interests involve understanding the molecular mechanisms of host defense during human viral infections and developing new predictive, preventive, and therapeutic strategies for them using Japanese encephalitis virus (JEV), HIV, and emerging viruses as a model via stem cell and cell culture technologies. His research work has been published in various high-impact factor journals (Science, PNAS, Nature Medicine) with a high number of citations. He has received many awards and honors in India and abroad including various Young Scientist Awards, BBSRC India Partnering Award, and Dr. JC Bose National Award of Department of Biotechnology, Min. of Science and Technology, Govt. of India. 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He is the president of the Travel Medicine Committee of the Pan-American Infectious Diseases Association (API), as well as the president of the Colombian Association of Infectious Diseases (ACIN). He is a member of the Committee on Tropical Medicine, Zoonoses, and Travel Medicine of ACIN. He is a vice-president of the Latin American Society for Travel Medicine (SLAMVI) and a Member of the Council of the International Society for Infectious Diseases (ISID). Since 2014, he has been recognized as a Senior Researcher, at the Ministry of Science of Colombia. He is a professor at the Faculty of Medicine of the Fundacion Universitaria Autonoma de las Americas, in Pereira, Risaralda, Colombia. He is an External Professor, Master in Research on Tropical Medicine and International Health, Universitat de Barcelona, Spain. He is also a professor at the Master in Clinical Epidemiology and Biostatistics, Universidad Científica del Sur, Lima, Peru. In 2021 he has been awarded the “Raul Isturiz Award” Medal of the API. Also, in 2021, he was awarded with the “Jose Felix Patiño” Asclepius Staff Medal of the Colombian Medical College, due to his scientific contributions to COVID-19 during the pandemic. He is currently the Editor in Chief of the journal Travel Medicine and Infectious Diseases. His Scopus H index is 47 (Google Scholar H index, 68).",institutionString:"Institución Universitaria Visión de las Américas, Colombia",institution:null},{id:"332819",title:"Dr.",name:"Chukwudi Michael",middleName:"Michael",surname:"Egbuche",slug:"chukwudi-michael-egbuche",fullName:"Chukwudi Michael Egbuche",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/332819/images/14624_n.jpg",biography:"I an Dr. Chukwudi Michael Egbuche. I am a Senior Lecturer in the Department of Parasitology and Entomology, Nnamdi Azikiwe University, Awka.",institutionString:null,institution:{name:"Nnamdi Azikiwe University",country:{name:"Nigeria"}}},{id:"284232",title:"Mr.",name:"Nikunj",middleName:"U",surname:"Tandel",slug:"nikunj-tandel",fullName:"Nikunj Tandel",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/284232/images/8275_n.jpg",biography:'Mr. Nikunj Tandel has completed his Master\'s degree in Biotechnology from VIT University, India in the year of 2012. He is having 8 years of research experience especially in the field of malaria epidemiology, immunology, and nanoparticle-based drug delivery system against the infectious diseases, autoimmune disorders and cancer. He has worked for the NIH funded-International Center of Excellence in Malaria Research project "Center for the study of complex malaria in India (CSCMi)" in collaboration with New York University. The preliminary objectives of the study are to understand and develop the evidence-based tools and interventions for the control and prevention of malaria in different sites of the INDIA. Alongside, with the help of next-generation genomics study, the team has studied the antimalarial drug resistance in India. Further, he has extended his research in the development of Humanized mice for the study of liver-stage malaria and identification of molecular marker(s) for the Artemisinin resistance. At present, his research focuses on understanding the role of B cells in the activation of CD8+ T cells in malaria. Received the CSIR-SRF (Senior Research Fellow) award-2018, FIMSA (Federation of Immunological Societies of Asia-Oceania) Travel Bursary award to attend the IUIS-IIS-FIMSA Immunology course-2019',institutionString:"Nirma University",institution:{name:"Nirma University",country:{name:"India"}}},{id:"334383",title:"Ph.D.",name:"Simone",middleName:"Ulrich",surname:"Ulrich Picoli",slug:"simone-ulrich-picoli",fullName:"Simone Ulrich Picoli",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/334383/images/15919_n.jpg",biography:"Graduated in Pharmacy from Universidade Luterana do Brasil (1999), Master in Agricultural and Environmental Microbiology from Federal University of Rio Grande do Sul (2002), Specialization in Clinical Microbiology from Universidade de São Paulo, USP (2007) and PhD in Sciences in Gastroenterology and Hepatology (2012). She is currently an Adjunct Professor at Feevale University in Medicine and Biomedicine courses and a permanent professor of the Academic Master\\'s Degree in Virology. She has experience in the field of Microbiology, with an emphasis on Bacteriology, working mainly on the following topics: bacteriophages, bacterial resistance, clinical microbiology and food microbiology.",institutionString:null,institution:{name:"Universidade Feevale",country:{name:"Brazil"}}},{id:"229220",title:"Dr.",name:"Amjad",middleName:"Islam",surname:"Aqib",slug:"amjad-aqib",fullName:"Amjad Aqib",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/229220/images/system/229220.png",biography:"Dr. Amjad Islam Aqib obtained a DVM and MSc (Hons) from University of Agriculture Faisalabad (UAF), Pakistan, and a PhD from the University of Veterinary and Animal Sciences Lahore, Pakistan. Dr. Aqib joined the Department of Clinical Medicine and Surgery at UAF for one year as an assistant professor where he developed a research laboratory designated for pathogenic bacteria. Since 2018, he has been Assistant Professor/Officer in-charge, Department of Medicine, Manager Research Operations and Development-ORIC, and President One Health Club at Cholistan University of Veterinary and Animal Sciences, Bahawalpur, Pakistan. He has nearly 100 publications to his credit. His research interests include epidemiological patterns and molecular analysis of antimicrobial resistance and modulation and vaccine development against animal pathogens of public health concern.",institutionString:"Cholistan University of Veterinary and Animal Sciences",institution:{name:"University of Agriculture Faisalabad",country:{name:"Pakistan"}}},{id:"333753",title:"Dr.",name:"Rais",middleName:null,surname:"Ahmed",slug:"rais-ahmed",fullName:"Rais Ahmed",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/333753/images/20168_n.jpg",biography:null,institutionString:null,institution:{name:"University of Agriculture Faisalabad",country:{name:"Pakistan"}}},{id:"62900",title:"Prof.",name:"Fethi",middleName:null,surname:"Derbel",slug:"fethi-derbel",fullName:"Fethi Derbel",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/62900/images/system/62900.jpeg",biography:"Professor Fethi Derbel was born in 1960 in Tunisia. He received his medical degree from the Sousse Faculty of Medicine at Sousse, University of Sousse, Tunisia. He completed his surgical residency in General Surgery at the University Hospital Farhat Hached of Sousse and was a member of the Unit of Liver Transplantation in the University of Rennes, France. He then worked in the Department of Surgery at the Sahloul University Hospital in Sousse. Professor Derbel is presently working at the Clinique les Oliviers, Sousse, Tunisia. His hospital activities are mostly concerned with laparoscopic, colorectal, pancreatic, hepatobiliary, and gastric surgery. He is also very interested in hernia surgery and performs ventral hernia repairs and inguinal hernia repairs. He has been a member of the GREPA and Tunisian Hernia Society (THS). During his residency, he managed patients suffering from diabetic foot, and he was very interested in this pathology. For this reason, he decided to coordinate a book project dealing with the diabetic foot. Professor Derbel has published many articles in journals and collaborates intensively with IntechOpen Access Publisher as an editor.",institutionString:"Clinique les Oliviers",institution:null},{id:"300144",title:"Dr.",name:"Meriem",middleName:null,surname:"Braiki",slug:"meriem-braiki",fullName:"Meriem Braiki",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/300144/images/system/300144.jpg",biography:"Dr. Meriem Braiki is a specialist in pediatric surgeon from Tunisia. She was born in 1985. She received her medical degree from the University of Medicine at Sousse, Tunisia. She achieved her surgical residency training periods in Pediatric Surgery departments at University Hospitals in Monastir, Tunis and France.\r\nShe is currently working at the Pediatric surgery department, Sidi Bouzid Hospital, Tunisia. Her hospital activities are mostly concerned with laparoscopic, parietal, urological and digestive surgery. She has published several articles in diffrent journals.",institutionString:"Sidi Bouzid Regional Hospital",institution:null},{id:"229481",title:"Dr.",name:"Erika M.",middleName:"Martins",surname:"de Carvalho",slug:"erika-m.-de-carvalho",fullName:"Erika M. de Carvalho",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/229481/images/6397_n.jpg",biography:null,institutionString:null,institution:{name:"Oswaldo Cruz Foundation",country:{name:"Brazil"}}},{id:"186537",title:"Prof.",name:"Tonay",middleName:null,surname:"Inceboz",slug:"tonay-inceboz",fullName:"Tonay Inceboz",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/186537/images/system/186537.jfif",biography:"I was graduated from Ege University of Medical Faculty (Turkey) in 1988 and completed his Med. PhD degree in Medical Parasitology at the same university. I became an Associate Professor in 2008 and Professor in 2014. I am currently working as a Professor at the Department of Medical Parasitology at Dokuz Eylul University, Izmir, Turkey.\n\nI have given many lectures, presentations in different academic meetings. I have more than 60 articles in peer-reviewed journals, 18 book chapters, 1 book editorship.\n\nMy research interests are Echinococcus granulosus, Echinococcus multilocularis (diagnosis, life cycle, in vitro and in vivo cultivation), and Trichomonas vaginalis (diagnosis, PCR, and in vitro cultivation).",institutionString:"Dokuz Eylül University",institution:{name:"Dokuz Eylül University",country:{name:"Turkey"}}},{id:"71812",title:"Prof.",name:"Hanem Fathy",middleName:"Fathy",surname:"Khater",slug:"hanem-fathy-khater",fullName:"Hanem Fathy Khater",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/71812/images/1167_n.jpg",biography:"Prof. Khater is a Professor of Parasitology at Benha University, Egypt. She studied for her doctoral degree, at the Department of Entomology, College of Agriculture, Food and Natural Resources, University of Missouri, Columbia, USA. She has completed her Ph.D. degrees in Parasitology in Egypt, from where she got the award for “the best scientific Ph.D. dissertation”. She worked at the School of Biological Sciences, Bristol, England, the UK in controlling insects of medical and veterinary importance as a grant from Newton Mosharafa, the British Council. Her research is focused on searching of pesticides against mosquitoes, house flies, lice, green bottle fly, camel nasal botfly, soft and hard ticks, mites, and the diamondback moth as well as control of several parasites using safe and natural materials to avoid drug resistances and environmental contamination.",institutionString:null,institution:{name:"Banha University",country:{name:"Egypt"}}},{id:"99780",title:"Prof.",name:"Omolade",middleName:"Olayinka",surname:"Okwa",slug:"omolade-okwa",fullName:"Omolade Okwa",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/99780/images/system/99780.jpg",biography:"Omolade Olayinka Okwa is presently a Professor of Parasitology at Lagos State University, Nigeria. She has a PhD in Parasitology (1997), an MSc in Cellular Parasitology (1992), and a BSc (Hons) Zoology (1990) all from the University of Ibadan, Nigeria. She teaches parasitology at the undergraduate and postgraduate levels. She was a recipient of a Commonwealth fellowship supported by British Council tenable at the Centre for Entomology and Parasitology (CAEP), Keele University, United Kingdom between 2004 and 2005. She was awarded an Honorary Visiting Research Fellow at the same university from 2005 to 2007. \nShe has been an external examiner to the Department of Veterinary Microbiology and Parasitology, University of Ibadan, MSc programme between 2010 and 2012. She is a member of the Nigerian Society of Experimental Biology (NISEB), Parasitology and Public Health Society of Nigeria (PPSN), Science Association of Nigeria (SAN), Zoological Society of Nigeria (ZSN), and is Vice Chairperson of the Organisation of Women in Science (OWSG), LASU chapter. She served as Head of Department of Zoology and Environmental Biology, Lagos State University from 2007 to 2010 and 2014 to 2016. She is a reviewer for several local and international journals such as Unilag Journal of Science, Libyan Journal of Medicine, Journal of Medicine and Medical Sciences, and Annual Research and Review in Science. \nShe has authored 45 scientific research publications in local and international journals, 8 scientific reviews, 4 books, and 3 book chapters, which includes the books “Malaria Parasites” and “Malaria” which are IntechOpen access publications.",institutionString:"Lagos State University",institution:{name:"Lagos State University",country:{name:"Nigeria"}}},{id:"273100",title:"Dr.",name:"Vijay",middleName:null,surname:"Gayam",slug:"vijay-gayam",fullName:"Vijay Gayam",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/273100/images/system/273100.jpeg",biography:"Dr. Vijay Bhaskar Reddy Gayam is currently practicing as an internist at Interfaith Medical Center in Brooklyn, New York, USA. He is also a Clinical Assistant Professor at the SUNY Downstate University Hospital and Adjunct Professor of Medicine at the American University of Antigua. He is a holder of an M.B.B.S. degree bestowed to him by Osmania Medical College and received his M.D. at Interfaith Medical Center. His career goals thus far have heavily focused on direct patient care, medical education, and clinical research. He currently serves in two leadership capacities; Assistant Program Director of Medicine at Interfaith Medical Center and as a Councilor for the American\r\nFederation for Medical Research. As a true academician and researcher, he has more than 50 papers indexed in international peer-reviewed journals. He has also presented numerous papers in multiple national and international scientific conferences. His areas of research interest include general internal medicine, gastroenterology and hepatology. He serves as an editor, editorial board member and reviewer for multiple international journals. His research on Hepatitis C has been very successful and has led to multiple research awards, including the 'Equity in Prevention and Treatment Award” from the New York Department of Health Viral Hepatitis Symposium (2018) and the 'Presidential Poster Award” awarded to him by the American College of Gastroenterology (2018). He was also awarded 'Outstanding Clinician in General Medicine” by Venus International Foundation for his extensive research expertise and services, perform over and above the standard expected in the advancement of healthcare, patient safety and quality of care.",institutionString:"Interfaith Medical Center",institution:{name:"Interfaith Medical Center",country:{name:"United States of America"}}},{id:"93517",title:"Dr.",name:"Clement",middleName:"Adebajo",surname:"Meseko",slug:"clement-meseko",fullName:"Clement Meseko",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/93517/images/system/93517.jpg",biography:"Dr. Clement Meseko obtained DVM and PhD degree in Veterinary Medicine and Virology respectively. He has worked for over 20 years in both private and public sectors including the academia, contributing to knowledge and control of infectious disease. Through the application of epidemiological skill, classical and molecular virological skills, he investigates viruses of economic and public health importance for the mitigation of the negative impact on people, animal and the environment in the context of Onehealth. \r\nDr. Meseko’s field experience on animal and zoonotic diseases and pathogen dynamics at the human-animal interface over the years shaped his carrier in research and scientific inquiries. He has been part of the investigation of Highly Pathogenic Avian Influenza incursions in sub Saharan Africa and monitors swine Influenza (Pandemic influenza Virus) agro-ecology and potential for interspecies transmission. He has authored and reviewed a number of journal articles and book chapters.",institutionString:"National Veterinary Research Institute",institution:{name:"National Veterinary Research Institute",country:{name:"Nigeria"}}},{id:"158026",title:"Prof.",name:"Shailendra K.",middleName:null,surname:"Saxena",slug:"shailendra-k.-saxena",fullName:"Shailendra K. Saxena",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRET3QAO/Profile_Picture_2022-05-10T10:10:26.jpeg",biography:"Professor Dr. Shailendra K. Saxena is a vice dean and professor at King George's Medical University, Lucknow, India. His research interests involve understanding the molecular mechanisms of host defense during human viral infections and developing new predictive, preventive, and therapeutic strategies for them using Japanese encephalitis virus (JEV), HIV, and emerging viruses as a model via stem cell and cell culture technologies. His research work has been published in various high-impact factor journals (Science, PNAS, Nature Medicine) with a high number of citations. He has received many awards and honors in India and abroad including various Young Scientist Awards, BBSRC India Partnering Award, and Dr. JC Bose National Award of Department of Biotechnology, Min. of Science and Technology, Govt. of India. Dr. Saxena is a fellow of various international societies/academies including the Royal College of Pathologists, United Kingdom; Royal Society of Medicine, London; Royal Society of Biology, United Kingdom; Royal Society of Chemistry, London; and Academy of Translational Medicine Professionals, Austria. He was named a Global Leader in Science by The Scientist. He is also an international opinion leader/expert in vaccination for Japanese encephalitis by IPIC (UK).",institutionString:"King George's Medical University",institution:{name:"King George's Medical University",country:{name:"India"}}},{id:"94928",title:"Dr.",name:"Takuo",middleName:null,surname:"Mizukami",slug:"takuo-mizukami",fullName:"Takuo Mizukami",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/94928/images/6402_n.jpg",biography:null,institutionString:null,institution:{name:"National Institute of Infectious Diseases",country:{name:"Japan"}}},{id:"233433",title:"Dr.",name:"Yulia",middleName:null,surname:"Desheva",slug:"yulia-desheva",fullName:"Yulia Desheva",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/233433/images/system/233433.png",biography:"Dr. Yulia Desheva is a leading researcher at the Institute of Experimental Medicine, St. Petersburg, Russia. She is a professor in the Stomatology Faculty, St. Petersburg State University. She has expertise in the development and evaluation of a wide range of live mucosal vaccines against influenza and bacterial complications. Her research interests include immunity against influenza and COVID-19 and the development of immunization schemes for high-risk individuals.",institutionString:'Federal State Budgetary Scientific Institution "Institute of Experimental Medicine"',institution:null},{id:"238958",title:"Mr.",name:"Atamjit",middleName:null,surname:"Singh",slug:"atamjit-singh",fullName:"Atamjit Singh",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/238958/images/6575_n.jpg",biography:null,institutionString:null,institution:null},{id:"252058",title:"M.Sc.",name:"Juan",middleName:null,surname:"Sulca",slug:"juan-sulca",fullName:"Juan Sulca",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/252058/images/12834_n.jpg",biography:null,institutionString:null,institution:null},{id:"191392",title:"Dr.",name:"Marimuthu",middleName:null,surname:"Govindarajan",slug:"marimuthu-govindarajan",fullName:"Marimuthu Govindarajan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/191392/images/5828_n.jpg",biography:"Dr. M. Govindarajan completed his BSc degree in Zoology at Government Arts College (Autonomous), Kumbakonam, and MSc, MPhil, and PhD degrees at Annamalai University, Annamalai Nagar, Tamil Nadu, India. He is serving as an assistant professor at the Department of Zoology, Annamalai University. His research interests include isolation, identification, and characterization of biologically active molecules from plants and microbes. He has identified more than 20 pure compounds with high mosquitocidal activity and also conducted high-quality research on photochemistry and nanosynthesis. He has published more than 150 studies in journals with impact factor and 2 books in Lambert Academic Publishing, Germany. He serves as an editorial board member in various national and international scientific journals.",institutionString:null,institution:null},{id:"274660",title:"Dr.",name:"Damodar",middleName:null,surname:"Paudel",slug:"damodar-paudel",fullName:"Damodar Paudel",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/274660/images/8176_n.jpg",biography:"I am DrDamodar Paudel,currently working as consultant Physician in Nepal police Hospital.",institutionString:null,institution:null},{id:"241562",title:"Dr.",name:"Melvin",middleName:null,surname:"Sanicas",slug:"melvin-sanicas",fullName:"Melvin Sanicas",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241562/images/6699_n.jpg",biography:null,institutionString:null,institution:null},{id:"117248",title:"Dr.",name:"Andrew",middleName:null,surname:"Macnab",slug:"andrew-macnab",fullName:"Andrew Macnab",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of British Columbia",country:{name:"Canada"}}},{id:"322007",title:"Dr.",name:"Maria Elizbeth",middleName:null,surname:"Alvarez-Sánchez",slug:"maria-elizbeth-alvarez-sanchez",fullName:"Maria Elizbeth Alvarez-Sánchez",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Universidad Autónoma de la Ciudad de México",country:{name:"Mexico"}}},{id:"337443",title:"Dr.",name:"Juan",middleName:null,surname:"A. 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The emergence of any viral disease is hard to anticipate, which often contributes to death. A viral disease can be defined as an infectious disease that has recently appeared within a population or exists in nature with the rapid expansion of incident or geographic range. This series will focus on various crucial factors related to emerging viral infectious diseases, including epidemiology, pathogenesis, host immune response, clinical manifestations, diagnosis, treatment, and clinical recommendations for managing viral infectious diseases, highlighting the recent issues with future directions for effective therapeutic strategies.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/6.jpg",hasOnlineFirst:!0,hasPublishedBooks:!0,annualVolume:11402,editor:{id:"158026",title:"Prof.",name:"Shailendra K.",middleName:null,surname:"Saxena",slug:"shailendra-k.-saxena",fullName:"Shailendra K. Saxena",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRET3QAO/Profile_Picture_2022-05-10T10:10:26.jpeg",biography:"Professor Dr. Shailendra K. Saxena is a vice dean and professor at King George's Medical University, Lucknow, India. His research interests involve understanding the molecular mechanisms of host defense during human viral infections and developing new predictive, preventive, and therapeutic strategies for them using Japanese encephalitis virus (JEV), HIV, and emerging viruses as a model via stem cell and cell culture technologies. His research work has been published in various high-impact factor journals (Science, PNAS, Nature Medicine) with a high number of citations. He has received many awards and honors in India and abroad including various Young Scientist Awards, BBSRC India Partnering Award, and Dr. JC Bose National Award of Department of Biotechnology, Min. of Science and Technology, Govt. of India. 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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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