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Saleh and Martin Koller",coverURL:"https://cdn.intechopen.com/books/images_new/6847.jpg",editedByType:"Edited by",editors:[{id:"144691",title:"Prof.",name:"Hosam",surname:"Saleh",slug:"hosam-saleh",fullName:"Hosam Saleh"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}],publishedBooksByAuthor:[]},onlineFirst:{chapter:{type:"chapter",id:"66135",title:"Multimodal Biometrics for Person Authentication",doi:"10.5772/intechopen.85003",slug:"multimodal-biometrics-for-person-authentication",body:'\nBiometrics is a technology that uses physical and/or behavioral characteristics of people to identify them. Systems of this type implement two processes (Figure 1) [1]:
Enrollment
Authentication
Biometric recognition system.
The physical features are fingerprints, hand geometry, handprint, facial image, iris, retina, and ear. Behavioral features are signature, lip motion, speech, dynamics of typing, hand movements, and gait.
\nThe characteristics of effective biometrics are:
Unique features for each individual
Invariant traits over time (e.g., due to the effect of aging)
Features that are relatively easy to obtain (computational complexity small)
Precise algorithms enabling classification
Resistance to various types of attacks
Low cost
Ease of implementation
The security of the biometric system is usually assessed on the basis of some indicators. These are:
False match rate (FMR). It belongs to the group of matching errors. This indicator is defined as the expected probability that the downloaded sample will be falsely matched to the template in the database, but it will not be the test user pattern. If the indicator is high, it means that there is a risk that an unauthorized person will be recognized as a system user.
False rejection (FRR) is equivalent to the FMR. The difference between these indicators is that FMR refers to a single match, and the FRR refers to a situation where one or more attempts to match a sample to a template from the database may occur. The FRR error is referred to in the literature as type I error.
False discrepancy (FNMR). This is the coefficient determining the probability that the sample taken will not be matched to the pattern in the database belonging to the user from whom the sample was taken. In biometric verification (1:1) systems, the indicator means that the sample has not been identified by a specific pattern, while in biometric identification systems (1:N), this indicator determines the probability that a given pattern will not be found in the database.
The false acceptance factor (FAR) is equivalent to the FNMR indicator. The difference between him and FNMR is the same as between FRR and FMR.
Equal error rate (EER). It is defined as the intersection of the FAR and FRR characteristics in the graph of the dependence of these errors on the threshold of sensitivity (t). This factor indicates the optimal sensitivity threshold at which the same number of people is incorrectly rejected and incorrectly accepted. The lower the EER error value, the better the biometric system is.
The FMR (FRR) and FNMR (FAR) parameters can also be represented by graphs (Figure 2):
Receiver operating characteristic (ROC) curve showing the dependence of FNMR on FMR. You can use it to show the accuracy of the system.
Detection error trade-off (DET) showing error rates on both axes, most often on a logarithmic scale. This curve is plotted for both matching errors and decisions (Figure 2).
The graph of FAR, FRR, and EER in receiver operating characteristic (ROC) curve.
If we use only one biometric authentication system, the results obtained are not always good enough. Unimodal biometric systems using a single sensor have many limitations, such as lack of uniqueness, universality, and lack of interference level associated with the acquired data, as a result of which they are unable to provide the required level of identification/verification efficiency (Table 1). This is due to the fact that the reliability of the biometric modality applied is affected by the precision of a single biometric system (Table 2).
\nName | \nDescription | \n
---|---|
Distortion of the input biometric data | \nDistorted biometric data may prevent the correct alignment process with database templates, as a result of which users are incorrectly rejected or identified | \n
Intra class variations | \nBiometric data obtained from the person during authentication may differ from the data used to generate the template during registration, thus affecting the matching process. The biometric template should have a small intra-class variance | \n
Interclass similarities | \nBiometric features should be significantly different for different people and should ensure small similarities between classes in the feature space. There is an upper limit to the users who can be effectively distinguished by any biometric system. The capacity of the identification system cannot be arbitrarily increased for fixed sets of feature vectors and the matching algorithm. The biometric template should have large interclass variations | \n
Non-universality | \nObtaining accurate (useful) biometric data from the users is not always possible | \n
Intruder attacks | \nAttacks of this type involve the manipulation of biometric features to avoid recognition. It is also possible to create artificial biometric patterns in order to accept the identity of another person | \n
Limitations of unimodal biometrics.
Name | \nDescription | \n
---|---|
Recognition accuracy | \nThe multi-biometric system ensures greater accuracy and reliability thanks to many independent biometric features that are difficult to attack | \n
Continuous monitoring | \nIn case when one biometric modality is obstructed, other modalities of the multi-biometric system ensure correct user identification | \n
Privacy | \nMulti-biometric systems provide greater resistance to certain types of loopholes and attacks. It is difficult and/or impossible to steal many biometric patterns (templates) stored in the biometric database | \n
Biometric data enrollment | \nWhen biometric input data is unavailable or unacceptable by a biometric system, another biometric system modality may be used | \n
Resistance on spoof attacks | \nUsually the attacker is not able to use many relevant (accurate) spoofed biometrics | \n
Advantages of multi-biometric systems.
The multi-biometric system can be (Figure 3) (a) a multi-sensor system that allows obtaining data from various sensors using one biometric feature, (b) a system with multiple algorithms processing a single biometric feature, (c) a system consolidating multiple occurrences of the same body trait, (d) a system using multiple templates of the same biometric method obtained with the help of a single sensor, and (e) a multimodal system combining information about the biometric features of the individual to establish his identity [2, 3, 4].
\nTypes of multi-biometric systems.
In multimodal biometric systems, there are a number of strategies (scenarios) for the fusion of biometric information:
Data fusion from sensors. Data from various sensors form one vector. Fusion of information obtained from many different sensors for a single biometric feature.
The fusion of feature vectors extracted from various biometric modalities for further processing. A merger of information obtained from several unimodal biometric systems that process different body characteristics of the same person (Figure 4a).
Fusion at the decision level. The merger of decisions developed on the basis of information from different biometric modalities, and the resultant feature vector defines two main classes, i.e., rejection or acceptance (Figure 4b).
Rank level fusion. The classifier determines the rank of each registered biometric identity. A high position is a good indicator of a good fit (Figure 4b).
Levels of fusion. (a) Feature level fusion and (b) score/rank level fusion.
The fusion of biometrics modalities on different levels of multi-biometrics system is extensively studied in the literature (Table 3). For all that the merger at the level of feature vectors is relatively poorly discussed. The merger at this level includes the integration of feature vectors corresponding to many sources of information. Because the feature vectors contain more elements than the input biometric data, it is obvious that the merger at the feature vectors level will provide better authentication results. However, mergers at this level are difficult to implement in practice because (i) sets of features of many modalities may be incompatible, (ii) the combination of two feature vectors may result in a vector of features with very large dimensionality, and (iii) a complex comparing system is required.
\nBiometrics traits | \nFusion methods | \nDescription of the implementation method | \nReferences | \n
---|---|---|---|
Fingerprint and face | \nIn [5], it was proposed to extract face and fingerprint characteristics invariant to the rotation and scaling of Zernike moments (ZM). On the basis of ZM, the fusion of facial features and fingerprints is realized. The RBF network implements the decision-making process. The accuracy rate is 96.55%. Testing result of authentication rate are FAR, 4.95%, and FRR, 1.12% | \n[5] | \n|
Score | \nIn [6], authors presented score level fusion technique using the SIFT features for the face and the minutiae features for fingerprint. Results are: FAR = 1.98%, FRR = 3.18%, and accuracy = 97.41 | \n[6] | \n|
Fingerprint, finger knuckle print, finger vein Finger shape | \nThe multi-set canonical correlation analysis is used to fuse multiple feature sets. The feature based on MCCA achieves the recognition performance, with EER = 2.3900e-04 | \n[1] | \n|
With the help of the unified Gabor filter, fingerprint codes and finger vein codes are generated. The extraction of features is carried out by using a supervised local canonical correlation analysis (SLPCCA), and finally the NN-classifier is used | \n[7] | \n||
Fingerprint and iris | \nScore | \nIn [8], authors propose a frequency approach to generate a unified homogeneous template for fingerprint and iris features. Scores generated from these templates are fused using the sum rule | \n[8] | \n
Palm print and hand shape | \nInformation from the face image and gait image are combined at the function level. Using the principal component analysis (PCA) method, facial features were obtained The result of multiple discrimination analysis (MDA) is gait energy image (GEI) Recognition rate results are 91.3% | \n[9] | \n|
Palm print and iris | \nIn system described in [10], texture parameters are extracted based on Gabor filters. | \n[10] | \n|
Fusion of the palm print features and iris features is based on the wavelets. Decision is obtained using kNN classifier. Recognition accuracy is 99.2% and FRR = 1.6% | \n|||
\n | In [11], fusion method for the information of phases about the iris and palm utilizes a Baud limited image product (BLIP) | \n[11] | \n|
Finger knuckle and palm print | \nIn this paper, feature extraction method for palm print is monogenic binary coding; for inner knuckle print recognition, two algorithms named ridgelet transform and SIFT are proposed. The extracted feature vectors are classified using SVM | \n[12] | \n|
Palm print and face | \nThe PCA is used to extract features of palm and face images. Fusion technique concatenated the feature vectors of the face and palm modalities into one fused vector, and feature selection is performed. | \n[13] | \n|
Face and gait | \nMethod is based on learning face and gait features in image transform spaces. Two methods are considered—PCA and LDA | \n[14] | \n|
Face and iris | \nScore | \nMulti-biometrics system using dual iris, visible and thermal face traits is considered. 1D Log-Gabor and Complex Gabor Jet Descriptor (CGJD) were used to extract feature vectors. Authors proposed a score level fusion algorithm | \n[15] | \n
The ordinal measures and local binary pattern (LBP) methods are proposed to extract features from iris and face regions, respectively | \n[16] | \n||
Paper [17] presents the extractions of iris features based on 2D Gabor and facial features using the PCA method | \n[17] | \n||
Face and hand geometry | \nThe 2D DCT is used to extract discriminant face features which are concatenated with hand geometric features. The resultant feature vector is classified using SVM | \n[18] | \n|
Face and ear | \nScores | \nTo match score level, fusion is proposed in [19]. Authors use Dempster-Shafer decision theory for each modality. Recognition rate is 95.53% with 4.47% EER | \n[19] | \n
Ocular—iris and conjunctival vascular | \nScore | \nIn [4], authors presented fusion of both iris and conjunctival vascular information. A weighted fusion method is proposed for each modality. The fusion resulted in an EER of 2.83% | \n[4] | \n
Face, ear, and signature | \nRank | \nIn [20], the PCA and Fisher’s linear discriminant (FLD) methods in the face, ear, and signature, multimodal biometrics system is proposed. Local features are extracted from face, ear, and signature data. Features are matched using Euclidean distance. This system is using rank level fusion | \n[20] | \n
Summary of works on multimodal biometric systems.
The multi-biometric system (dorsal vein + periocular + palm print) is presented in Figure 5.
\nConsidered multi-biometric system architecture.
In our proposed method, the first is preprocessing block including noise elimination, ROI detection and normalization, and contrast normalization. For all three modalities, noise elimination for an image \n
where \n
Next step in preprocessing phase is ROI detection and normalization (Figure 6). This operation is quite different for dorsal vein images, palm print images, and periocular images. For dorsal vein images, we use distance transform to detect the dorsal image center and build square ROI based on this center coordinates [22, 23]. The ROI design for palm print images is based on hand-specific points (finger valleys) and two angles [24]. The periocular region is detected based on the center of the iris. Using the conventional algorithm for detecting the iris, we determine the center of the iris and its diameter. The periocular area is a rectangle centered in the iris center [25, 26].
\nROI area for dorsal vein images (a), palm print images (b), and periocular images (c).
After the ROI detection, we perform image size normalization and apply the contrast normalization by using CLAHE algorithm. The image is divided into non-overlapping areas of equal size, and the histograms of each region are calculated. Next, the cutoff threshold for histograms is obtained, and each histogram is processed in such a way that its height does not exceed the cutoff threshold [21].
\nThe sample input images after normalization operations and operations using the CLAHE algorithm are shown in Figure 7. Next processing blocks include feature extraction, feature selection, fusion, and classification.
\nImages after normalization (size 150 × 150 pixels) and after applying the CLAHE algorithm.
In biologically inspired vision models, receptor fields exist that are the primary aspect of early visual processing in mammalian vision systems. Gabor functions are widely used in image feature analysis because they are similar to receptive field profiles in mammalian cortical simple cells. These fields are modeled using Gabor filters [27].
\nImitation of mammalian vision systems (or some of them) in object recognition systems leads to their increased efficiency and plausibility. Object recognition systems that are inspired by the biological approach use filter banks, in particular Gabor filters (Figure 8) [28, 29, 30, 31, 32].
\n2D functions and 2D Gabor filter.
The 2D Gabor filter family can be represented as expressed in Eq. (2):
\nwhere \n
The \n
\n\n
Gabor response images are obtained by convolution operation of multiscale and multi-orientation Gabor filters \n
where and\n
The Gabor filter responses for palm print image and dorsal vein image are shown in Figures 9 and 10, respectively.
\nImaginary part of the Gabor filter responses of a palm print image.
Imaginary part of the Gabor filter responses of a dorsal vein image.
The periocular area contains the iris, eyes, eyelids, eyelashes, and partially eyebrows. The
\n
\n
The
where\n
The idea of this operator is presented in Figure 11.
\nThe basic idea of LBP approach.
For an image size \n
where
Using the
Typically image is divided into
In the case \n
The original image (a) and image as a result of the LBP operator (b).
The
The multi-biometric system has been tested using certain parts of the following databases: PolyU palmprint [24], IIITD periocular database [25], and Bosphorus hand vein database [35]. We choose 20 subjects with 10 images per subject at random. From 10 images, 5 images are used for training and 5 for the testing.
\nThe combination of feature vectors at this level is difficult to achieve in practice due to the combination of certain fundamentally different feature vectors that can result in a resulting vector of features with very large dimensionality. In a merger at the level of feature vectors, each individual modality process generates a feature vector. The fusion process combines these feature vectors into one vector.
\nFor dorsal vein images and for palm print images, we perform the same image processing operations that the feature vectors have the same sizes. As a result of convolution operation of multiscale and multi-orientation Gabor filters with the input image, we get the Gabor response images. The feature vector has a very large size of
For periocular images, the feature vector has a size of 36 × 59 = 2124.
\nNext we reduce dimensionality of these vectors used in PCA method (Figure 14 and Table 4) [5]. Separated features are normalized using zero mean and unit variance as
\nSteps to image processing using PCA.
PCA algorithm | \n
Organizing the training set of images \n\n where | \n
Calculating the average of the set T \n\n | \n
Calculating \n\n | \n
Calculating the covariance matrix C \n\n | \n
The eigenvectors and corresponding eigenvalues are computed \n\n | \n
The eigenvectors and their corresponding eigenvalues are paired and ordered from high to low. Approximated image is calculated as \n\n for \n | \n
PCA algorithm.
where \n
\nTable 5 shows the recognition performance depending on the number of selected eigenvectors.
\nModality | \nNumber of the eigenvectors | \n|||
---|---|---|---|---|
k = 40 | \nk = 60 | \nk = 80 | \nk = 100 | \n|
Dorsal vein | \n88 | \n89.3 | \n91.4 | \n92.6 | \n
Palm print | \n88.7 | \n89.3 | \n90.6 | \n92.8 | \n
Periocular | \n86 | \n86.8 | \n89 | \n89.2 | \n
Dorsal vein + palm print | \n90.3 | \n91.1 | \n92.3 | \n93.1 | \n
Dorsal vein + periocular | \n91.1 | \n92 | \n92.4 | \n92.8 | \n
Palm print + periocular | \n90.7 | \n91.4 | \n91.8 | \n92.1 | \n
Recognition rates [%] for different modality.
In this chapter, Gabor’s functions and LBP features are proposed for recognition in a multi-biometric system that uses three modalities: dorsal vein, periocular, and palm print. Using PCA method dimensionality feature vectors from these modality are reduced. Feature vectors are normalized and fused using concatenation operation. Based on the results, we suggest that multi-biometric system using the fusion of dorsal vein, periocular, and palm print images can offer recognition rate which the unimodal biometric system cannot.
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\\n\\nBez prethodne privole i izričite pisane dozvole, ne možete stvarati okvire oko naših stranica ili koristiti druge tehnike koje na bilo koji način mogu promijeniti prezentaciju ili izgled naše stranice.
\\n\\nIntechOpen može ove Odredbe izmijeniti u bilo koje vrijeme i bez prethodne obavijesti. Koristeći ovu stranicu vi se slažete s trenutnim Odredbama i uvjetima koje su na snazi.
\\n\\nOve Odredbe i uvjeti su sastavljeni u skladu s odredbama prava Ujedinjenog Kraljevstva, a za sve sporove nadležan je sud u Londonu, Ujedinjeno Kraljevstvo.
\\n"}]'},components:[{type:"htmlEditorComponent",content:"Pristupom na stranicu www.intechopen.com slažete se s ovim odredbama, sa svim primjenjivim zakonskim odredbama, te se slažete s poštovanjem svih lokalnih zakona. Korištenje i/ili pristup ovoj stranici temelji se na potpunom prihvaćanju ovih odredbi. Svi materijali na ovoj stranici zaštićeni su primjenjivim zakonima o autorskim pravima i žigu.
\n\nSljedeća terminologija odnosi se na Odredbe i uvjete, te na sve naše ugovore:
\n\nKlijent, stranka, vi, vaš odnosi se na vas, osobu koja pristupa ovoj stranici i prihvaća IntechOpenove Odredbe i uvjete;
\n\nKompanija, tvrtka, mi, naše odnosi se na tvrtku IntechOpen;
\n\nStranke, strane odnosi se na klijenta i na nas, ili samo na klijenta ili nas.
\n\nSve odredbe koje se odnose na ponudu, prihvat ili razmatranje plaćanja, a za koja mi pružamo asistenciju klijentu, bilo na ugovoreni ili fiksni način, a s ciljem da se ostvare potrebe i želje klijenta u svezi s našim uslugama, su podložne zakonskim odredbama Ujedinjenog Kraljevstva.
\n\nOsim ako nije suprotno navedeno, IntechOpen i/ili svi davatelji licence vlasnici su intelektualnog vlasništva nad svim materijalima na www.intechopen.com. Sva prava intelektualnog vlasništva su pridržana. Stranice sa www.intechopen.com možete gledati, preuzimati, dijeliti, dijeliti poveznice i printati za osobnu uporabu, a temeljem pravila sadržanih u ovim Odredbama i uvjetima.
\n\nMi koristimo kolačiće. Korištenjem IntechOpenove stranice slažete se s korištenjem kolačića u skladu s IntechOpenovom Politikom privatnosti. Većina modernih, interaktivnih stranica koristi kolačiće kako bi omogućila ponovno pronalaženje korisničkih detalja kod svakog posjeta. Na našoj stranici kolačići se uglavnom koriste kako bi omogućili funkcionalnost i olakšali posjetiteljima korištenje stranice.
\n\nIntechOpen ili njegovi suradnici niti u jednom slučaju neće biti odgovorni za štete (štete uključuju gubitak podataka ili profita, druge poslovne prekide, te sve ostale štete) koje nastanu zbog korištenja materijala na IntechOpenovoj stranici ili nemogućnosti da se iste koriste, čak i ako je IntechOpen ili njegov predstavnik o takvoj šteti obaviješten pismenim ili usmenim putem. Neke jurisdikcije ne dozvoljavaju ograničenja garancija ili ograničenja obveza za posljedične ili slučajne štete pa se u tom slučaju ova ograničenja možda ne odnose na vas.
\n\nMaterijali koji se pojavljuju na IntechOpenovoj stranici mogu sadržavati manje greške, tipfelere ili fotografske greške. IntechOpen može napraviti promjene na bilo kojem materijalu koji se nalazi na stranici u bilo koje vrijeme.
\n\nIntechOpen nije formalno povezan niti s jednom vanjskom stranicom čije poveznice vode na www.intechopen.com, osim ako to nije izravno navedeno. Iz tog razloga IntechOpen nije odgovoran za sadržaj koji se pojavljuje na takvim stranicama. Poveznica na IntechOpenovu stranicu ne implicira povezanost sa IntechOpenom. Korištenje takvih poveznica isključiva je odgovornost korisnika.
\n\nZadržavamo pravo vlasništva nad cjelokupnom stranicom www.intechopen.com i nad svim materijalom na toj stranici. Koristeći se našim uslugama, slažete se da maknete sve poveznice na našu stranicu odmah nakon što to od vas zatražimo. Također, zadržavamo pravo da ove Odredbe i uvjete, i politiku o poveznicama izmjenimo u bilo koje vrijeme. Koristeći se poveznicama na naše stranice slažete se s ovim Odredbama i uvjetima.
\n\nAko smatrate da je bilo koja poveznica na našoj stranici sumnjiva iz bilo kojeg razloga, molimo vas da nas kontaktirate. U tom slučaju razmotrit ćemo micanje poveznice s naše stranice, iako nismo obvezni to napraviti.
\n\nBez prethodne privole i izričite pisane dozvole, ne možete stvarati okvire oko naših stranica ili koristiti druge tehnike koje na bilo koji način mogu promijeniti prezentaciju ili izgled naše stranice.
\n\nIntechOpen može ove Odredbe izmijeniti u bilo koje vrijeme i bez prethodne obavijesti. Koristeći ovu stranicu vi se slažete s trenutnim Odredbama i uvjetima koje su na snazi.
\n\nOve Odredbe i uvjeti su sastavljeni u skladu s odredbama prava Ujedinjenog Kraljevstva, a za sve sporove nadležan je sud u Londonu, Ujedinjeno Kraljevstvo.
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Heat stress decreases the secretion of luteinizing hormone and estradiol resulting in reduced length and intensity of estrus expression, increased incidence of anoestrus and silent heat in farm animals. Oocytes exposed to thermal stress lose its competence for fertilization and development into the blastocyst stage, which results in decreased fertility because of the production of poor quality oocytes and embryos. Furthermore, low progesterone secretion limits the endometrial functions, and subsequently embryo development. In addition, the increased secretion of endometrial prostaglandin F2 alpha during heat stress threatens the maintenance of pregnancy. In general, the percentage of conception rate was found to be reduced by 4.6% for each unit increase in temperature humidity index (THI) above 70, and heat stress during pregnancy further slows down the growth of the foetus and results in lower birth weight. In tropical and subtropical regions, during hot days, the testicular temperature may increase and impair both the spermatogenic cycle and semen quality, which culminates in decreased bull fertility. The effects of heat stress on livestock can be minimized via adapting suitable scientific strategies comprising physical modifications of the environment, nutritional management and genetic development of breeds that are less sensitive to heat stress. In addition, the summer infertility may be countered through advanced reproductive technologies involving hormonal treatments, timed artificial insemination and embryo transfer, which may enhance the chances for establishing pregnancy in farm animals.",book:{id:"5861",slug:"theriogenology",title:"Theriogenology",fullTitle:"Theriogenology"},signatures:"Govindan Krishnan, Madiajagan Bagath, Prathap Pragna,\nMallenahally Kusha Vidya, Joy Aleena, Payyanakkal Ravindranathan\nArchana, Veerasamy Sejian and Raghavendra Bhatta",authors:[{id:"89780",title:"Dr.",name:"Veerasamy",middleName:null,surname:"Sejian",slug:"veerasamy-sejian",fullName:"Veerasamy Sejian"},{id:"177210",title:"Dr.",name:"Raghavendra",middleName:null,surname:"Bhatta",slug:"raghavendra-bhatta",fullName:"Raghavendra Bhatta"},{id:"177220",title:"Dr.",name:"M",middleName:null,surname:"Bagath",slug:"m-bagath",fullName:"M Bagath"},{id:"201967",title:"Dr.",name:"Govindan",middleName:null,surname:"Krishnan",slug:"govindan-krishnan",fullName:"Govindan Krishnan"},{id:"201968",title:"Ms.",name:"Archana",middleName:null,surname:"Pr",slug:"archana-pr",fullName:"Archana Pr"},{id:"201969",title:"Ms.",name:"Pragna",middleName:null,surname:"Prathap",slug:"pragna-prathap",fullName:"Pragna Prathap"},{id:"201970",title:"Ms.",name:"Aleena",middleName:null,surname:"Joy",slug:"aleena-joy",fullName:"Aleena Joy"},{id:"201971",title:"Dr.",name:"Vidya",middleName:null,surname:"Mk",slug:"vidya-mk",fullName:"Vidya Mk"}]},{id:"55006",doi:"10.5772/intechopen.68650",title:"Immunocastration as Alternative to Surgical Castration in Pigs",slug:"immunocastration-as-alternative-to-surgical-castration-in-pigs",totalDownloads:1876,totalCrossrefCites:9,totalDimensionsCites:19,abstract:"Surgical castration of piglets is a routine practice in pig production used to prevent the incidence of boar taint of pig meat, which may develop in entire male pigs as they reach puberty. This practice is being presently questioned in the European Union, and there is a strong initiative to end it. The initiative is presently voluntary; however, key stakeholders of European pig production sector have signed a declaration, and the actions undertaken by them already affect the business. Before such new concepts in pig production can be implemented, alternative solutions are needed, one of them being immunocastration. The present chapter will thus focus on the presentation of immunocastration as one of the promising alternatives to surgical castration. Theoretical and practical aspects of immunocastration in pig production will be described, and the advantages and disadvantages of this alternative will be summarised. Physiological principles of immunocastration and impacts on metabolism, growth performance, body composition and meat quality will be described and aspects of public acceptability reviewed.",book:{id:"5861",slug:"theriogenology",title:"Theriogenology",fullTitle:"Theriogenology"},signatures:"Marjeta Čandek-Potokar, Martin Škrlep and Galia Zamaratskaia",authors:[{id:"23161",title:"Dr.",name:"Marjeta",middleName:null,surname:"Čandek-Potokar",slug:"marjeta-candek-potokar",fullName:"Marjeta Čandek-Potokar"},{id:"198220",title:"Dr.",name:"Martin",middleName:null,surname:"Škrlep",slug:"martin-skrlep",fullName:"Martin Škrlep"},{id:"198221",title:"Prof.",name:"Galia",middleName:null,surname:"Zamaratskaia",slug:"galia-zamaratskaia",fullName:"Galia Zamaratskaia"}]},{id:"55696",doi:"10.5772/intechopen.69444",title:"Estrus Cycle Monitoring in Wild Mammals: Challenges and Perspectives",slug:"estrus-cycle-monitoring-in-wild-mammals-challenges-and-perspectives",totalDownloads:1852,totalCrossrefCites:0,totalDimensionsCites:6,abstract:"The knowledge of reproductive physiology is of paramount importance to guide reproductive management and to make possible future application of assisted reproduction techniques (ARTs) aiming ex situ conservation of wild mammals. Nevertheless, information on the basic reproductive aspects of wild mammals remain scarce, and appropriate management practices have not yet been developed for all the species. This chapter discusses the methods most currently used for reproductive monitoring in wild females. Additionally, the difficulties regarding their use in different species and the possibilities of these procedures in captivity or in free-living mammals are addressed.",book:{id:"5861",slug:"theriogenology",title:"Theriogenology",fullTitle:"Theriogenology"},signatures:"Alexandre R. Silva, Nei Moreira, Alexsandra F. Pereira, Gislayne C.X.\nPeixoto, Keilla M. Maia, Lívia B. Campos and Alana A. Borges",authors:[{id:"90066",title:"Dr.",name:"Alexandre",middleName:"Rodrigues",surname:"Silva",slug:"alexandre-silva",fullName:"Alexandre Silva"},{id:"177090",title:"Dr.",name:"Alexsandra Fernandes",middleName:null,surname:"Pereira",slug:"alexsandra-fernandes-pereira",fullName:"Alexsandra Fernandes Pereira"},{id:"177093",title:"MSc.",name:"Gislayne Christianne Xavier",middleName:null,surname:"Peixoto",slug:"gislayne-christianne-xavier-peixoto",fullName:"Gislayne Christianne Xavier Peixoto"},{id:"198314",title:"Prof.",name:"Nei",middleName:null,surname:"Moreira",slug:"nei-moreira",fullName:"Nei Moreira"},{id:"198315",title:"MSc.",name:"Keilla Moreira",middleName:null,surname:"Maia",slug:"keilla-moreira-maia",fullName:"Keilla Moreira Maia"},{id:"198316",title:"MSc.",name:"Lívia Batista",middleName:null,surname:"Campos",slug:"livia-batista-campos",fullName:"Lívia Batista Campos"},{id:"198317",title:"MSc.",name:"Alana Azevedo",middleName:null,surname:"Borges",slug:"alana-azevedo-borges",fullName:"Alana Azevedo Borges"}]},{id:"56522",doi:"10.5772/intechopen.69549",title:"Role of Melatonin in Reproductive Seasonality in Buffaloes",slug:"role-of-melatonin-in-reproductive-seasonality-in-buffaloes",totalDownloads:1725,totalCrossrefCites:2,totalDimensionsCites:5,abstract:"Buffaloes are characterized by seasonal reproductive activity. Anestrus buffalo heifers and lactating buffaloes were used to study the effect of melatonin treatment on the resumption of ovarian activity during out-of-breeding season. Buffaloes of treated group were injected or implanted with melatonin (18 mg melatonin/50 kg body weight). Using CIDR-eCG protocol preceded with melatonin successfully achieved estrus behavior and induced conception rate during out-of-breeding season. Furthermore, the reproductive performance of buffaloes during out-of-breeding season was clearly improved by melatonin implantation in conjunction with CIDR-eCG protocol due to the luteotrophic effect of melatonin expressed as increasing diameter of CL (corpus luteum) and progesterone concentration. This improvement resulted in greater values of conception rate, in melatonin implanted compared to not implanted buffaloes. Melatonin implantation in anestrus buffalo heifers increased the diameter of largest follicles and melatonin concentration but progesterone and luteinizing hormone (LH) concentrations were decreased. In addition, melatonin implantation in anestrus lactating buffaloes increased the SOD (superoxide dismutase) enzyme activity. Sustained release of exogenous melatonin significantly protects against oxidative stress while increasing beneficial total antioxidant capacity (TAC) concentration in summer-stressed anestrus buffaloes. Melatonin implantation in conjunction with CIDR-eCG protocol successfully improved some blood metabolites, in anestrus buffalo heifers during out-of-breeding season under tropical conditions.",book:{id:"5861",slug:"theriogenology",title:"Theriogenology",fullTitle:"Theriogenology"},signatures:"Tamer Awad Ramadan",authors:[{id:"197651",title:"Dr.",name:"Tamer",middleName:"Awad",surname:"Ramadan",slug:"tamer-ramadan",fullName:"Tamer Ramadan"}]},{id:"54974",doi:"10.5772/intechopen.68651",title:"Markers for Sperm Freezability and Relevance of Transcriptome Studies in Semen Cryopreservation: A Review",slug:"markers-for-sperm-freezability-and-relevance-of-transcriptome-studies-in-semen-cryopreservation-a-re",totalDownloads:1586,totalCrossrefCites:0,totalDimensionsCites:4,abstract:"Advances in sperm assessment techniques have offered new perspectives to improve the technology of semen cryopreservation. This review addresses some recent achievements in the proteomics of seminal plasma and spermatozoa and exemplifies its importance as markers for sperm fertility following cryopreservation. Recent advances in transcriptome studies on sperm RNA-Seq data have generated new information aimed to unravel the physiological roles of RNAs in the sperm-egg fertilization processes and their associations with male fertility. The relevance of the sperm freezability markers and the potential associations of RNA-profiling sequences with the sperm biological functions have been discussed.",book:{id:"5861",slug:"theriogenology",title:"Theriogenology",fullTitle:"Theriogenology"},signatures:"Leyland Fraser",authors:[{id:"199650",title:"Dr.",name:"Leyland",middleName:null,surname:"Fraser",slug:"leyland-fraser",fullName:"Leyland Fraser"}]}],mostDownloadedChaptersLast30Days:[{id:"55696",title:"Estrus Cycle Monitoring in Wild Mammals: Challenges and Perspectives",slug:"estrus-cycle-monitoring-in-wild-mammals-challenges-and-perspectives",totalDownloads:1852,totalCrossrefCites:0,totalDimensionsCites:6,abstract:"The knowledge of reproductive physiology is of paramount importance to guide reproductive management and to make possible future application of assisted reproduction techniques (ARTs) aiming ex situ conservation of wild mammals. Nevertheless, information on the basic reproductive aspects of wild mammals remain scarce, and appropriate management practices have not yet been developed for all the species. This chapter discusses the methods most currently used for reproductive monitoring in wild females. Additionally, the difficulties regarding their use in different species and the possibilities of these procedures in captivity or in free-living mammals are addressed.",book:{id:"5861",slug:"theriogenology",title:"Theriogenology",fullTitle:"Theriogenology"},signatures:"Alexandre R. Silva, Nei Moreira, Alexsandra F. Pereira, Gislayne C.X.\nPeixoto, Keilla M. Maia, Lívia B. Campos and Alana A. Borges",authors:[{id:"90066",title:"Dr.",name:"Alexandre",middleName:"Rodrigues",surname:"Silva",slug:"alexandre-silva",fullName:"Alexandre Silva"},{id:"177090",title:"Dr.",name:"Alexsandra Fernandes",middleName:null,surname:"Pereira",slug:"alexsandra-fernandes-pereira",fullName:"Alexsandra Fernandes Pereira"},{id:"177093",title:"MSc.",name:"Gislayne Christianne Xavier",middleName:null,surname:"Peixoto",slug:"gislayne-christianne-xavier-peixoto",fullName:"Gislayne Christianne Xavier Peixoto"},{id:"198314",title:"Prof.",name:"Nei",middleName:null,surname:"Moreira",slug:"nei-moreira",fullName:"Nei Moreira"},{id:"198315",title:"MSc.",name:"Keilla Moreira",middleName:null,surname:"Maia",slug:"keilla-moreira-maia",fullName:"Keilla Moreira Maia"},{id:"198316",title:"MSc.",name:"Lívia Batista",middleName:null,surname:"Campos",slug:"livia-batista-campos",fullName:"Lívia Batista Campos"},{id:"198317",title:"MSc.",name:"Alana Azevedo",middleName:null,surname:"Borges",slug:"alana-azevedo-borges",fullName:"Alana Azevedo Borges"}]},{id:"55491",title:"Mitigation of the Heat Stress Impact in Livestock Reproduction",slug:"mitigation-of-the-heat-stress-impact-in-livestock-reproduction",totalDownloads:4243,totalCrossrefCites:9,totalDimensionsCites:23,abstract:"Heat stress affects the fertility and reproductive livestock performance by compromising the physiology reproductive tract, through hormonal imbalance, decreased oocyte quality and poor semen quality, and decreased embryo development and survival. Heat stress decreases the secretion of luteinizing hormone and estradiol resulting in reduced length and intensity of estrus expression, increased incidence of anoestrus and silent heat in farm animals. Oocytes exposed to thermal stress lose its competence for fertilization and development into the blastocyst stage, which results in decreased fertility because of the production of poor quality oocytes and embryos. Furthermore, low progesterone secretion limits the endometrial functions, and subsequently embryo development. In addition, the increased secretion of endometrial prostaglandin F2 alpha during heat stress threatens the maintenance of pregnancy. In general, the percentage of conception rate was found to be reduced by 4.6% for each unit increase in temperature humidity index (THI) above 70, and heat stress during pregnancy further slows down the growth of the foetus and results in lower birth weight. In tropical and subtropical regions, during hot days, the testicular temperature may increase and impair both the spermatogenic cycle and semen quality, which culminates in decreased bull fertility. The effects of heat stress on livestock can be minimized via adapting suitable scientific strategies comprising physical modifications of the environment, nutritional management and genetic development of breeds that are less sensitive to heat stress. In addition, the summer infertility may be countered through advanced reproductive technologies involving hormonal treatments, timed artificial insemination and embryo transfer, which may enhance the chances for establishing pregnancy in farm animals.",book:{id:"5861",slug:"theriogenology",title:"Theriogenology",fullTitle:"Theriogenology"},signatures:"Govindan Krishnan, Madiajagan Bagath, Prathap Pragna,\nMallenahally Kusha Vidya, Joy Aleena, Payyanakkal Ravindranathan\nArchana, Veerasamy Sejian and Raghavendra Bhatta",authors:[{id:"89780",title:"Dr.",name:"Veerasamy",middleName:null,surname:"Sejian",slug:"veerasamy-sejian",fullName:"Veerasamy Sejian"},{id:"177210",title:"Dr.",name:"Raghavendra",middleName:null,surname:"Bhatta",slug:"raghavendra-bhatta",fullName:"Raghavendra Bhatta"},{id:"177220",title:"Dr.",name:"M",middleName:null,surname:"Bagath",slug:"m-bagath",fullName:"M Bagath"},{id:"201967",title:"Dr.",name:"Govindan",middleName:null,surname:"Krishnan",slug:"govindan-krishnan",fullName:"Govindan Krishnan"},{id:"201968",title:"Ms.",name:"Archana",middleName:null,surname:"Pr",slug:"archana-pr",fullName:"Archana Pr"},{id:"201969",title:"Ms.",name:"Pragna",middleName:null,surname:"Prathap",slug:"pragna-prathap",fullName:"Pragna Prathap"},{id:"201970",title:"Ms.",name:"Aleena",middleName:null,surname:"Joy",slug:"aleena-joy",fullName:"Aleena Joy"},{id:"201971",title:"Dr.",name:"Vidya",middleName:null,surname:"Mk",slug:"vidya-mk",fullName:"Vidya Mk"}]},{id:"55324",title:"The Role of Androgens in Ovarian Follicular Development: From Fertility to Ovarian Cancer",slug:"the-role-of-androgens-in-ovarian-follicular-development-from-fertility-to-ovarian-cancer",totalDownloads:1755,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Androgens, steroid hormones produced by follicular cells, play a crucial role in the regulation of ovarian function. They affect folliculogenesis directly through androgen receptors (ARs) or indirectly through aromatization to estrogens. Androgens are thought to be primarily involved in preantral follicle growth and prevention of follicular atresia. It also seems possible that they are involved in the activation of primordial follicles. According to the World Health Organization, endocrine-disrupting chemicals (EDCs) are substances that alter hormonal signaling. EDCs comprise a wide variety of synthetic or natural chemicals arising from anthropogenic, industrial, agricultural, and domestic sources. EDCs interfere with natural regulation of the endocrine system by either mimicking or blocking the function of endogenous hormones as well as acting directly on gene expression or through epigenetic modifications. Disruptions in ovarian processes caused by EDCs may originate adverse outcomes such as anovulation, infertility, or premature ovarian failure. In this chapter, we aim to point out a possible involvement of androgen excess or deficiency in the regulation of ovarian function. We will summarize the effects of EDCs expressing antiandrogenic or androgenic activity on female physiology. Continuous exposition to even small concentration of such compounds can initiate oncogenesis within the ovary.",book:{id:"5861",slug:"theriogenology",title:"Theriogenology",fullTitle:"Theriogenology"},signatures:"Malgorzata Duda, Kamil Wartalski, Zbigniew Tabarowski and\nGabriela Gorczyca",authors:[{id:"177042",title:"Ph.D.",name:"Malgorzata",middleName:null,surname:"Duda",slug:"malgorzata-duda",fullName:"Malgorzata Duda"},{id:"177918",title:"Dr.",name:"Zbigniew",middleName:null,surname:"Tabarowski",slug:"zbigniew-tabarowski",fullName:"Zbigniew Tabarowski"},{id:"205391",title:"MSc.",name:"Kamil",middleName:null,surname:"Wartalski",slug:"kamil-wartalski",fullName:"Kamil Wartalski"},{id:"205392",title:"MSc.",name:"Gabriela",middleName:null,surname:"Gorczyca",slug:"gabriela-gorczyca",fullName:"Gabriela Gorczyca"}]},{id:"56522",title:"Role of Melatonin in Reproductive Seasonality in Buffaloes",slug:"role-of-melatonin-in-reproductive-seasonality-in-buffaloes",totalDownloads:1726,totalCrossrefCites:2,totalDimensionsCites:5,abstract:"Buffaloes are characterized by seasonal reproductive activity. Anestrus buffalo heifers and lactating buffaloes were used to study the effect of melatonin treatment on the resumption of ovarian activity during out-of-breeding season. Buffaloes of treated group were injected or implanted with melatonin (18 mg melatonin/50 kg body weight). Using CIDR-eCG protocol preceded with melatonin successfully achieved estrus behavior and induced conception rate during out-of-breeding season. Furthermore, the reproductive performance of buffaloes during out-of-breeding season was clearly improved by melatonin implantation in conjunction with CIDR-eCG protocol due to the luteotrophic effect of melatonin expressed as increasing diameter of CL (corpus luteum) and progesterone concentration. This improvement resulted in greater values of conception rate, in melatonin implanted compared to not implanted buffaloes. Melatonin implantation in anestrus buffalo heifers increased the diameter of largest follicles and melatonin concentration but progesterone and luteinizing hormone (LH) concentrations were decreased. In addition, melatonin implantation in anestrus lactating buffaloes increased the SOD (superoxide dismutase) enzyme activity. Sustained release of exogenous melatonin significantly protects against oxidative stress while increasing beneficial total antioxidant capacity (TAC) concentration in summer-stressed anestrus buffaloes. Melatonin implantation in conjunction with CIDR-eCG protocol successfully improved some blood metabolites, in anestrus buffalo heifers during out-of-breeding season under tropical conditions.",book:{id:"5861",slug:"theriogenology",title:"Theriogenology",fullTitle:"Theriogenology"},signatures:"Tamer Awad Ramadan",authors:[{id:"197651",title:"Dr.",name:"Tamer",middleName:"Awad",surname:"Ramadan",slug:"tamer-ramadan",fullName:"Tamer Ramadan"}]},{id:"54974",title:"Markers for Sperm Freezability and Relevance of Transcriptome Studies in Semen Cryopreservation: A Review",slug:"markers-for-sperm-freezability-and-relevance-of-transcriptome-studies-in-semen-cryopreservation-a-re",totalDownloads:1586,totalCrossrefCites:0,totalDimensionsCites:4,abstract:"Advances in sperm assessment techniques have offered new perspectives to improve the technology of semen cryopreservation. This review addresses some recent achievements in the proteomics of seminal plasma and spermatozoa and exemplifies its importance as markers for sperm fertility following cryopreservation. Recent advances in transcriptome studies on sperm RNA-Seq data have generated new information aimed to unravel the physiological roles of RNAs in the sperm-egg fertilization processes and their associations with male fertility. The relevance of the sperm freezability markers and the potential associations of RNA-profiling sequences with the sperm biological functions have been discussed.",book:{id:"5861",slug:"theriogenology",title:"Theriogenology",fullTitle:"Theriogenology"},signatures:"Leyland Fraser",authors:[{id:"199650",title:"Dr.",name:"Leyland",middleName:null,surname:"Fraser",slug:"leyland-fraser",fullName:"Leyland Fraser"}]}],onlineFirstChaptersFilter:{topicId:"1384",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:8,numberOfPublishedChapters:87,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:98,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:27,numberOfPublishedChapters:286,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:9,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:139,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:129,numberOfOpenTopics:0,numberOfUpcomingTopics:2,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!1},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:105,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:9,numberOfPublishedChapters:101,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:11,numberOfOpenTopics:2,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:0,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!1},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:9,numberOfOpenTopics:4,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. 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Topics will include asset liability management, financial consequences of the financial crisis and covid-19, financial accounting, mergers and acquisitions, management accounting, SMEs, financial markets, corporate finance and governance, managerial technology and innovation, resource management and sustainable development, social entrepreneurship, corporate responsibility, ethics and accountability, microeconomics, labour economics, macroeconomics, public economics, financial economics, econometrics, direct marketing, creative marketing, internet marketing, market planning and forecasting, brand management, market segmentation and targeting and other topics under business and management. This book series will focus on various aspects of business and management whose in-depth understanding is critical for business and company management to function effectively during this uncertain time of financial crisis, Covid-19 pandemic, and military activity in Europe.
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Moreover, in the field of machine learning, evolutionary computation has carved out a significant niche both in the generation of learning models and in the automatic design and optimization of hyperparameters in deep learning models. This collection aims to include quality volumes on various topics related to evolutionary algorithms and, alternatively, other metaheuristics of interest inspired by nature. For example, some of the issues of interest could be the following: Advances in evolutionary computation (Genetic algorithms, Genetic programming, Bio-inspired metaheuristics, Hybrid metaheuristics, Parallel ECs); Applications of evolutionary algorithms (Machine learning and Data Mining with EAs, Search-Based Software Engineering, Scheduling, and Planning Applications, Smart Transport Applications, Applications to Games, Image Analysis, Signal Processing and Pattern Recognition, Applications to Sustainability).",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",keywords:"Genetic Algorithms, Genetic Programming, Evolutionary Programming, Evolution Strategies, Hybrid Algorithms, Bioinspired Metaheuristics, Ant Colony Optimization, Evolutionary Learning, Hyperparameter Optimization"},{id:"26",title:"Machine Learning and Data Mining",scope:"The scope of machine learning and data mining is immense and is growing every day. It has become a massive part of our daily lives, making predictions based on experience, making this a fascinating area that solves problems that otherwise would not be possible or easy to solve. This topic aims to encompass algorithms that learn from experience (supervised and unsupervised), improve their performance over time and enable machines to make data-driven decisions. It is not limited to any particular applications, but contributions are encouraged from all disciplines.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/26.jpg",keywords:"Intelligent Systems, Machine Learning, Data Science, Data Mining, Artificial Intelligence"},{id:"27",title:"Multi-Agent Systems",scope:"Multi-agent systems are recognised as a state of the art field in Artificial Intelligence studies, which is popular due to the usefulness in facilitation capabilities to handle real-world problem-solving in a distributed fashion. 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We welcome chapters presenting research on the many applications of multi-agent studies including, but not limited to, the following key areas: machine learning for multi-agent systems; modeling swarms robots and flocks of UAVs with multi-agent systems; decision science and multi-agent systems; software engineering for and with multi-agent systems; tools and technologies of multi-agent systems.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/27.jpg",keywords:"Collaborative Intelligence, Learning, Distributed Control System, Swarm Robotics, Decision Science, Software Engineering"}],annualVolumeBook:{},thematicCollection:[],selectedSeries:{title:"Artificial Intelligence",id:"14"},selectedSubseries:null},seriesLanding:{item:{id:"7",title:"Biomedical Engineering",doi:"10.5772/intechopen.71985",issn:"2631-5343",scope:"Biomedical Engineering is one of the fastest-growing interdisciplinary branches of science and industry. 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Dr. Koprowski has authored more than a hundred research papers with dozens in impact factor (IF) journals and has authored or co-authored six books. Additionally, he is the author of several national and international patents in the field of biomedical devices and imaging. Since 2011, he has been a reviewer of grants and projects (including EU projects) in biomedical engineering.",institutionString:null,institution:{name:"University of Silesia",institutionURL:null,country:{name:"Poland"}}},subseries:[{id:"7",title:"Bioinformatics and Medical Informatics",keywords:"Biomedical Data, Drug Discovery, Clinical Diagnostics, Decoding Human Genome, AI in Personalized Medicine, Disease-prevention Strategies, Big Data Analysis in Medicine",scope:"Bioinformatics aims to help understand the functioning of the mechanisms of living organisms through the construction and use of quantitative tools. The applications of this research cover many related fields, such as biotechnology and medicine, where, for example, Bioinformatics contributes to faster drug design, DNA analysis in forensics, and DNA sequence analysis in the field of personalized medicine. Personalized medicine is a type of medical care in which treatment is customized individually for each patient. Personalized medicine enables more effective therapy, reduces the costs of therapy and clinical trials, and also minimizes the risk of side effects. Nevertheless, advances in personalized medicine would not have been possible without bioinformatics, which can analyze the human genome and other vast amounts of biomedical data, especially in genetics. The rapid growth of information technology enabled the development of new tools to decode human genomes, large-scale studies of genetic variations and medical informatics. The considerable development of technology, including the computing power of computers, is also conducive to the development of bioinformatics, including personalized medicine. In an era of rapidly growing data volumes and ever lower costs of generating, storing and computing data, personalized medicine holds great promises. Modern computational methods used as bioinformatics tools can integrate multi-scale, multi-modal and longitudinal patient data to create even more effective and safer therapy and disease prevention methods. 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Recently, bioinspired systems have been successfully employing biomechanics to develop and improve assistive technology and rehabilitation devices. The research topic "Bioinspired Technology and Biomechanics" welcomes studies reporting recent advances in bioinspired technologies that contribute to individuals\' health, inclusion, and rehabilitation. Possible contributions can address (but are not limited to) the following research topics: Bioinspired design and control of exoskeletons, orthoses, and prostheses; Experimental evaluation of the effect of assistive devices (e.g., influence on gait, balance, and neuromuscular system); Bioinspired technologies for rehabilitation, including clinical studies reporting evaluations; Application of neuromuscular and biomechanical models to the development of bioinspired technology.',annualVolume:11404,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/8.jpg",editor:{id:"144937",title:"Prof.",name:"Adriano",middleName:"De Oliveira",surname:"Andrade",fullName:"Adriano Andrade",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRC8QQAW/Profile_Picture_1625219101815",institutionString:null,institution:{name:"Federal University of Uberlândia",institutionURL:null,country:{name:"Brazil"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"49517",title:"Prof.",name:"Hitoshi",middleName:null,surname:"Tsunashima",fullName:"Hitoshi Tsunashima",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYTP4QAO/Profile_Picture_1625819726528",institutionString:null,institution:{name:"Nihon University",institutionURL:null,country:{name:"Japan"}}},{id:"425354",title:"Dr.",name:"Marcus",middleName:"Fraga",surname:"Vieira",fullName:"Marcus Vieira",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003BJSgIQAX/Profile_Picture_1627904687309",institutionString:null,institution:{name:"Universidade Federal de Goiás",institutionURL:null,country:{name:"Brazil"}}},{id:"196746",title:"Dr.",name:"Ramana",middleName:null,surname:"Vinjamuri",fullName:"Ramana Vinjamuri",profilePictureURL:"https://mts.intechopen.com/storage/users/196746/images/system/196746.jpeg",institutionString:"University of Maryland, Baltimore County",institution:{name:"University of Maryland, Baltimore County",institutionURL:null,country:{name:"United States of America"}}}]},{id:"9",title:"Biotechnology - Biosensors, Biomaterials and Tissue Engineering",keywords:"Biotechnology, Biosensors, Biomaterials, Tissue Engineering",scope:"The Biotechnology - Biosensors, Biomaterials and Tissue Engineering topic within the Biomedical Engineering Series aims to rapidly publish contributions on all aspects of biotechnology, biosensors, biomaterial and tissue engineering. We encourage the submission of manuscripts that provide novel and mechanistic insights that report significant advances in the fields. Topics can include but are not limited to: Biotechnology such as biotechnological products and process engineering; Biotechnologically relevant enzymes and proteins; Bioenergy and biofuels; Applied genetics and molecular biotechnology; Genomics, transcriptomics, proteomics; Applied microbial and cell physiology; Environmental biotechnology; Methods and protocols. Moreover, topics in biosensor technology, like sensors that incorporate enzymes, antibodies, nucleic acids, whole cells, tissues and organelles, and other biological or biologically inspired components will be considered, and topics exploring transducers, including those based on electrochemical and optical piezoelectric, thermal, magnetic, and micromechanical elements. Chapters exploring biomaterial approaches such as polymer synthesis and characterization, drug and gene vector design, biocompatibility, immunology and toxicology, and self-assembly at the nanoscale, are welcome. 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