\r\n\t
",isbn:"978-1-83962-718-7",printIsbn:"978-1-83962-717-0",pdfIsbn:"978-1-83962-754-5",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,hash:"4df95c7f295de7f6003e635d9a309fe9",bookSignature:"Dr. Yajuan Zhu, Dr. Qinghong Luo and Dr. Yuguo Liu",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/8969.jpg",keywords:"Water Cycle, Water Use Strategy, Vegetation Dynamics, Plant Community, Precipitation, Carbon Emission, Soil Respiration, Autotrophic Respiration, Algae Crust, Wind, Temperature, Vegetation Stability",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"January 26th 2021",dateEndSecondStepPublish:"February 23rd 2021",dateEndThirdStepPublish:"April 24th 2021",dateEndFourthStepPublish:"July 13th 2021",dateEndFifthStepPublish:"September 11th 2021",remainingDaysToSecondStep:"a month",secondStepPassed:!1,currentStepOfPublishingProcess:2,editedByType:null,kuFlag:!1,biosketch:"Dr. Zhu holds a Ph.D. in Ecology and is currently an Associate Research Professor at the Chinese Academy of Forestry at the Institute of Desertification Studies, she has led a number of national projects while working there.",coeditorOneBiosketch:"Dr. Luo holds a Ph.D. in Physical Geography and is currently a Research Professor at the Institute of Afforestation and Sand Control, Xinjiang Academy of Forestry. She is a holder of several technological patents in her area of research.",coeditorTwoBiosketch:"Dr. Liu holds a Ph.D. in Ecology and is currently an Assistant Professor at the Institute of Desertification Studies, Chinese Academy of Forestry. He has published several international works that have been recognized.",coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"180427",title:"Dr.",name:"Yajuan",middleName:null,surname:"Zhu",slug:"yajuan-zhu",fullName:"Yajuan Zhu",profilePictureURL:"https://mts.intechopen.com/storage/users/180427/images/system/180427.jpg",biography:"Dr. Yajuan Zhu obtained her Bachelor's degree in Agriculture from Northwest Agriculture and Forestry University in 2002 and PhD in Ecology from Chinese Academy of Sciences in 2007. She was a postdoctoral fellow working on the topic of land desertification control in the Research Institute of Forestry, Chinese Academy of Forestry, followed by her appointment as an Assistant Professor at the Institute of Desertification Studies, Chinese Academy of Forestry and currently she is an Associate Research Professor at the same institute. She is a Master's supervisor with interests in plant ecology in deserts, biodiversity, stable isotope ecology, isohydrology and desertification control.",institutionString:"Chinese Academy of Forestry",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Chinese Academy of Forestry",institutionURL:null,country:{name:"China"}}}],coeditorOne:{id:"340564",title:"Dr.",name:"Qinghong",middleName:null,surname:"Luo",slug:"qinghong-luo",fullName:"Qinghong Luo",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000032N5e7QAC/Profile_Picture_1605773886590",biography:"Dr. Qinghong Luo holds a Master's degree from Life Science College, Shihezi University (2006) and PhD in Physical geography from Xinjiang Ecology and Geography Institute, Chinese Academy of Sciences (2018). She was initially an Assistant Research Professor at Institute of Afforestation and Sand Control, Xinjiang Academy of Forestry, after an Associate Research Professor and currently she is a Research Professor at the same institute. Her research interests include desert vegetation dynamics, plant-soil interaction and desertification control among others. She has participated in a number of funded and non funded projects and is a holder of several patents.",institutionString:"Chinese Academy of Forestry",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Chinese Academy of Forestry",institutionURL:null,country:{name:"China"}}},coeditorTwo:{id:"340567",title:"Dr.",name:"Yuguo",middleName:null,surname:"Liu",slug:"yuguo-liu",fullName:"Yuguo Liu",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000032N5hEQAS/Profile_Picture_1605774524148",biography:"Dr. Yuguo Liu obtained his bachelor's degree, majoring in Environmental Sciences from Inner Mongolia University in 2007 and doctoral degree, majoring in Ecology from Institute of Botany, the Chinese Academy of Sciences in 2013. He has been working as an Assistant Professor at the Institute of Desertification Studies, Chinese Academy of Forestry ever since. His research interests include ecological protection and restoration of fragile areas, and karst vegetation and rocky desertification control.",institutionString:"Chinese Academy of Forestry",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Chinese Academy of Forestry",institutionURL:null,country:{name:"China"}}},coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"10",title:"Earth and Planetary Sciences",slug:"earth-and-planetary-sciences"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"194667",firstName:"Marijana",lastName:"Francetic",middleName:null,title:"Ms.",imageUrl:"https://mts.intechopen.com/storage/users/194667/images/4752_n.jpg",email:"marijana@intechopen.com",biography:"As an Author Service Manager my responsibilities include monitoring and facilitating all publishing activities for authors and editors. From chapter submission and review, to approval and revision, copyediting and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. Whether that be identifying an exceptional author and proposing an editorship collaboration, or contacting researchers who would like the opportunity to work with IntechOpen, I establish and help manage author and editor acquisition and contact."}},relatedBooks:[{type:"book",id:"5962",title:"Estuary",subtitle:null,isOpenForSubmission:!1,hash:"43058846a64b270e9167d478e966161a",slug:"estuary",bookSignature:"William Froneman",coverURL:"https://cdn.intechopen.com/books/images_new/5962.jpg",editedByType:"Edited by",editors:[{id:"109336",title:"Prof.",name:"William",surname:"Froneman",slug:"william-froneman",fullName:"William Froneman"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"1591",title:"Infrared Spectroscopy",subtitle:"Materials Science, Engineering and Technology",isOpenForSubmission:!1,hash:"99b4b7b71a8caeb693ed762b40b017f4",slug:"infrared-spectroscopy-materials-science-engineering-and-technology",bookSignature:"Theophile Theophanides",coverURL:"https://cdn.intechopen.com/books/images_new/1591.jpg",editedByType:"Edited by",editors:[{id:"37194",title:"Dr.",name:"Theophanides",surname:"Theophile",slug:"theophanides-theophile",fullName:"Theophanides Theophile"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3092",title:"Anopheles mosquitoes",subtitle:"New insights into malaria vectors",isOpenForSubmission:!1,hash:"c9e622485316d5e296288bf24d2b0d64",slug:"anopheles-mosquitoes-new-insights-into-malaria-vectors",bookSignature:"Sylvie Manguin",coverURL:"https://cdn.intechopen.com/books/images_new/3092.jpg",editedByType:"Edited by",editors:[{id:"50017",title:"Prof.",name:"Sylvie",surname:"Manguin",slug:"sylvie-manguin",fullName:"Sylvie Manguin"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3161",title:"Frontiers in Guided Wave Optics and Optoelectronics",subtitle:null,isOpenForSubmission:!1,hash:"deb44e9c99f82bbce1083abea743146c",slug:"frontiers-in-guided-wave-optics-and-optoelectronics",bookSignature:"Bishnu Pal",coverURL:"https://cdn.intechopen.com/books/images_new/3161.jpg",editedByType:"Edited by",editors:[{id:"4782",title:"Prof.",name:"Bishnu",surname:"Pal",slug:"bishnu-pal",fullName:"Bishnu Pal"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"72",title:"Ionic Liquids",subtitle:"Theory, Properties, New Approaches",isOpenForSubmission:!1,hash:"d94ffa3cfa10505e3b1d676d46fcd3f5",slug:"ionic-liquids-theory-properties-new-approaches",bookSignature:"Alexander Kokorin",coverURL:"https://cdn.intechopen.com/books/images_new/72.jpg",editedByType:"Edited by",editors:[{id:"19816",title:"Prof.",name:"Alexander",surname:"Kokorin",slug:"alexander-kokorin",fullName:"Alexander Kokorin"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"1373",title:"Ionic Liquids",subtitle:"Applications and Perspectives",isOpenForSubmission:!1,hash:"5e9ae5ae9167cde4b344e499a792c41c",slug:"ionic-liquids-applications-and-perspectives",bookSignature:"Alexander Kokorin",coverURL:"https://cdn.intechopen.com/books/images_new/1373.jpg",editedByType:"Edited by",editors:[{id:"19816",title:"Prof.",name:"Alexander",surname:"Kokorin",slug:"alexander-kokorin",fullName:"Alexander Kokorin"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"57",title:"Physics and Applications of Graphene",subtitle:"Experiments",isOpenForSubmission:!1,hash:"0e6622a71cf4f02f45bfdd5691e1189a",slug:"physics-and-applications-of-graphene-experiments",bookSignature:"Sergey Mikhailov",coverURL:"https://cdn.intechopen.com/books/images_new/57.jpg",editedByType:"Edited by",editors:[{id:"16042",title:"Dr.",name:"Sergey",surname:"Mikhailov",slug:"sergey-mikhailov",fullName:"Sergey Mikhailov"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"371",title:"Abiotic Stress in Plants",subtitle:"Mechanisms and Adaptations",isOpenForSubmission:!1,hash:"588466f487e307619849d72389178a74",slug:"abiotic-stress-in-plants-mechanisms-and-adaptations",bookSignature:"Arun Shanker and B. 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"}},{type:"book",id:"878",title:"Phytochemicals",subtitle:"A Global Perspective of Their Role in Nutrition and Health",isOpenForSubmission:!1,hash:"ec77671f63975ef2d16192897deb6835",slug:"phytochemicals-a-global-perspective-of-their-role-in-nutrition-and-health",bookSignature:"Venketeshwer Rao",coverURL:"https://cdn.intechopen.com/books/images_new/878.jpg",editedByType:"Edited by",editors:[{id:"82663",title:"Dr.",name:"Venketeshwer",surname:"Rao",slug:"venketeshwer-rao",fullName:"Venketeshwer Rao"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"4816",title:"Face Recognition",subtitle:null,isOpenForSubmission:!1,hash:"146063b5359146b7718ea86bad47c8eb",slug:"face_recognition",bookSignature:"Kresimir Delac and Mislav Grgic",coverURL:"https://cdn.intechopen.com/books/images_new/4816.jpg",editedByType:"Edited by",editors:[{id:"528",title:"Dr.",name:"Kresimir",surname:"Delac",slug:"kresimir-delac",fullName:"Kresimir Delac"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"66545",title:"Dictionary Learning-Based Speech Enhancement",doi:"10.5772/intechopen.85308",slug:"dictionary-learning-based-speech-enhancement",body:'\nSpeech is the most important tool of expression and it is crucial information carrier of language communication. Speech signals in real-world scenarios are corrupted due to some disturbing noise such as background noise, reverberation, babble noise, etc. The purpose of speech enhancement (SE) is to extract the clean speech signal from the interferer components mixture as much as possible, so as the clarity and intelligibility of the speech signal. The research of speech enhancement technology is particularly important and difficult. Speech denoising is an importance problem with increasing various applications as hearing aids, speech/speaker recognition, mobile communications over telephone, and Internet [1]. The difficulties arise from the nature of real-world noise that is often unknown, nonstationary, potentially speech-like, overlapping between [1, 2, 3].
\nAssume that the noisy speech x is a linear additive mixture of the clean speech s and the interfere n as defined in the following equation:
\nwhere x(t) is the time-domain mixture signal at sample t, and s(t) and n(t) are the time-domain speech and interferer signals, respectively. The speech enhancement algorithm attempts to suppress noise without distorting speech and obtain the enhanced speech components \n
The speech enhancement techniques mainly focus on removal of noise from speech signal. The various types of noise and techniques for removal of those noises are presented [5, 6, 7, 8, 9, 10, 11, 12, 13]. The famous spectral subtraction technique [5] extracted the clean speech spectrum based on the principle that the noise contamination process is additive. The major advantage of the spectral subtraction method is their simplicity by subtracting an estimation of the interfere spectrum from the observed mixture spectrum [5, 6]. The main problem with the magnitude spectral subtraction is that it does not attenuate noise sufficiently negative magnitude by error in the subtraction.
\nFiltering techniques [7, 8] or short-time spectral amplitude (STSA) estimators [9] or estimators based on super-Gaussian prior distributions for speech DFT coefficients are [10, 11, 12, 13] the statistical models assumed for each of the speech and noise signals that estimate the clean speech from the noisy observation without any prior information on the noisy type or speaker identity. However, in the case of nonstation of background noise, these methods face much difficulty in estimating the noise power spectral density (PSD) [14, 15, 16].
\nRecently, dictionary learning (DL) techniques, which build dictionary consisting of atoms and represent a class of signals in terms of the atoms, have been shown to be effective in machine learning, neuroscience, and audio processing [17, 18, 19, 20]. In speech enhancement, the dictionary models utilize specific types of the a priori information considered for both the speech and noise signals [21, 22, 23, 24, 25]. This class of methods assumes that a target spectrogram can be generated from a set of basis target spectra (a dictionary) through weighted linear combinations. Generally, this approach decomposes the time-frequency representations (the power or magnitude spectrogram) of noisy speech in terms of elementary atoms of a dictionary. One of the key issues in dictionary-based speech enhancement is how to precisely learn a dictionary. Dictionary learning methods are commonly based on an alternating optimization strategy, in which the signal representation is fixed, and the dictionary elements are learned; then the sparse signal representation is found, while the dictionary is fixed. Two popular methods have appeared to determine a dictionary within a matrix decomposition including sparse coding [26] and nonnegative matrix factorization (NMF) [27].
\nThe observation that speech and other structured signals can be well approximated by few atoms of a suitably trained dictionary [28], which lies at the core of sparse representation (SR). In SR, sparse signals can be reconstructed with a few atoms of an overcomplete dictionary. Recently, developed SR has been shown to be effective in data representation, which factorizes given matrix with regularization methods or regularization term to constrain the sparsity of desire representation. Since speech signals are generally sparse in the time-frequency domain and many types of noise are nonsparse, the target speech signal was decomposed and reconstructed from the noisy speech-driven sparse dictionary [21, 22, 23].
\nIn many reality applications, the nonnegativities of the signals and the dictionary are required such as multispectral data analysis [29, 30], image representation [31, 32], and some other important problems [33, 34], the so-called nonnegative dictionary learning becomes necessary. Nonnegative matrix factorization is a popular dictionary method, which projects the given nonnegative matrix onto the subspace spanned by nonnegative dictionary vectors. Treating speech enhancement as a source separation problem between speech and noise, NMF-based techniques can be used to factorize spectrograms into nonnegative speech and noise dictionaries and their nonnegative activations. On the one hand, a clean speech signal can be estimated from the product of speech dictionaries and their activation.
\nIn this chapter, we review the dictionary learning approaches for speech enhancement. After a brief introduction to the problem and its characterization as a sound source separation task, we present a survey on both theoretically and applicable of dictionary-based techniques, the main subject of this chapter. We finally provide an overview of the evaluation methods and suggest some future lines of works.
\nDictionary learning performs approximate matrix factorization of a data matrix into the product of a dictionary matrix and a coding matrix, under some sparsity constraints on the coding matrix. Dictionary learning is the generalization of gain-shape codebook learning. Signal vectors are represented as linear combinations of multiple dictionary atoms, allowing for lower approximation error while maintaining equal dictionary size. Two relatively different methods are described for how to form the dictionary from the given data including sparse representation (SR) and nonnegative matrix factorization (NMF).
\nLet X be a matrix of M training signals \n
where \n
Eq. (2) shows that a signal x can be expressed as the linear combination of only a few column vectors in D. Matrix factorization problem (2) is a difficult problem, since the joint optimization of D and C is nonconvex. Many dictionary algorithms follow an iterative scheme that alternates between updates of dictionary D and sparse coding C to minimize the cost function (2). K-SVD, one of the methods, goes under the category of sparse representation (SR), which came from the theory of sparse and redundant representation of signals. It was first introduced by Aharon et al. [34]. The K-SVD algorithm defines an initial overcomplete dictionary matrix \n
The sparse coding approximation step derives the column cm, m = 1. M by using the orthogonal matching pursuit (OMP) algorithm with given X and D to solve the following equation:
\nThe updating dictionary step is taken by minimizing the approximation error (2) with the current coding C. Atom-by-atom is updated in an iterative process.
\nwhere c[i] is the ith row of C. The residual norm is minimized by seeking for a rank-one approximation [35]. The approximation is based on computing the singular value decomposition (SVD) [23].
\nNonnegative matrix factorization (NMF) can be viewed as an approach for dictionary learning. NMF, first introduced by Paatero and Tapper [36] and later popularized by Lee and Seung [23, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37], has been known as a part-based representation model. Different to other matrix factorization approaches, NMF takes into account the fact that most types of real-world data, particularly sound and videos, are nonnegative and maintain such nonnegativity constraints in factorization. Moreover, the nonnegativity constraints in NMF are compatible with the intuitive notion of combining parts to form a whole, that is, they provide a parts-based local representation of the data. A parts based model not only provides an efficient representation of the data but can potentially aid in the discovery of causal structure within it and in learning relationships between the parts.
\nGiven a nonnegative matrix \n
where f is denoted a distance metric.
\nDifferent the similarity measures between X and the product DC lead to different variants of NMF. The common choices include Euclidean distance [38], generalized Kullback-Leibler divergence [39], Itakura-Saito divergence [40]… For instance, the NMF based on Kullback–Leibler (KL) divergence is formulated as follows:
\nThere exist different optimization models for the approximation factorization (5) [36, 39, 40]. The most popular solution is alternative multiplicative update rules (MURs) [36], which do not have required user-specified optimization parameters. For a KL cost function (6), the iteratively updating rules are given by:
\nHowever, it is found that the monotonicity guaranteed by the proof of multiplicative updates may not imply the full Karush-Kuhn-Tucker conditions [39, 40]. MUR is relatively simple and easy to implement, but it converges slower in comparison with gradient approaches [41]. More efficient algorithms equipped with stronger theoretical convergence property have been introduced. One popular method is to apply gradient descent algorithms with additive update rules, which are represented by the projective gradient descent method (PGD) [42]. In PGD framework, to select the learning step size, a line search method with the Armijo rule is applied [42] and the new estimate is obtained by first calculating the unconstrained steepest-descent update and then zeroing its negative elements. In addition, considering the separate convexity, the two-variable optimization problem is converted into the nonnegative least squares (NLS) optimization subproblems, which alternate the minimization over either D or C, with the other matrix fixed.
\nBecause of the initial condition K < < min{N, M}, the obtained basis vectors are incomplete over the original vector space. In other words, this NMF approach tries to represent the high-dimensional stochastic pattern with far fewer bases, so the perfect approximation can be achieved successfully only if the intrinsic features are identified in D.
\nNMF will not get the unique solution under the sole nonnegativity constraint. Hence, to remedy the ill-posedness, it is imperative to introduce additional auxiliary constraints on D and/or C as regularization terms, which will also incorporate prior knowledge and reflect the characteristics of the issues more comprehensively. The constrained NMF models can be unified under the similar extended objective function
\nwhere the regularization parameters αand χ are used to balance the trade-off between the fitting goodness and the constraints g(D) and h(C).
\nThe performance of NMF can be improved by imposing extra constraints and regularizations. For the sparseness learning, the sparse term h(C) expects to constraint the mount of nonzero elements in each column of the projection matrix. The L0 norm could be selected to count nonzero elements in C [43]. One limitation of using L0 norm is that the solution is not unique because of many local minima of the cost function. In this situation, the L1 norm of the projection matrix is usually replaced as a relaxation of the L0 penalty [44, 45].
\nA major outcome of speech enhancement techniques is the improved quality and reduced listening effort in the presence of an interfering noise signal. The decomposition of time-frequency representations, such as the power or magnitude spectrogram in terms of elementary atoms, has become a popular tool in speech enhancement since their success in finding high-“quality” dictionary atoms that best describe latent features of the underprocessed data. The dictionary-based techniques utilize specific types of the a priori information of speech or noise [21, 23, 46, 47, 48, 49, 50]. A priori information can be typical patterns or statistics obtained from a speech or noise database. Dictionary-based speech enhancement consists of two separate stages: a training stage, in which the model parameters are learned, and a denoising stage, in which the noise reduction task is carried out. In the first step, dictionary D is learned while fixing coefficient matrix C, and in second step, C is computed with the fixed dictionary matrix D. This process of alternate minimization is repeated iteratively until a stopping criterion is reached. In order to learn dictionary atoms capable of revealing the hidden structure in speech, long temporal context of speech signals must be considered. Two major classes of dictionary-based speech enhancement techniques may be the offline learning and online learning. Offline algorithms for dictionary learning are second-order iterative batch procedures, accessing the whole training set at each iteration in order to minimize a cost function under some constraints [21, 22, 23]. In speech enhancement, learning spectrotemporal atoms spanning several consecutive frames is done through training large volumes of datasets, which places unrealistic demand on computing power and memory. In large-scale tasks, online dictionary learning tends to gain lower empirical cost than conventional batch learning [46, 47, 48, 49, 50].
\nSpeech enhancement herein is implemented in the short-time Fourier transform (STFT) magnitude domain, assuming that the phase of the interferer can be approximated with the phase of the mixture. The number of frequency bins per frame is determined by the length of the time-domain analysis window, where a Hamming window was chosen for the STFT. The temporal smoothness frames are determined by the time-domain analysis window overlap, where a minimum amount of overlap is necessary to avoid aliasing.
\nSparse representation has been described as an overcomplete models wherein the number of bases is greater than the dimensionality of spectral representations. In sparse representation, sparse signals can be expressed as the linear combination of only a few atoms in an overcomplete dictionary. While speech signals are generally sparse in the time-frequency domain and many types of noise are nonsparse, the target speech signal reconstructed from the noisy speech is considered as clean speech. A possibly overcomplete dictionary of atoms is trained for both speech and interferer magnitudes, which are then concatenated into a composite dictionary. The training process of updated dictionary is drawn in Figure 1.
\nThe training process of updated dictionary.
When applying the sparse coding technique to speech enhancement, it is desirable to have the trained offline clean speech dictionary Dspeech to be coherent to the speech signal and incoherent to the background noise signal as well as a coherent noise dictionary Dnoise. In the enhancement step, the noisy speech is sparsely coded in the composite dictionary [Dspeech, Dnoise]. As a result, this mixture of speech and interferer x is explained by a sum of a linear combination of atoms from the speech dictionary Dspeech and a linear combination of atoms from the interferer dictionary Dnoise. The noisy x is coded using the least angle regression (LASSO) [51] with a preset threshold θ as follows:
\nThe clean speech magnitude is estimated by disregarding the contribution from the interferer dictionary, preserving only the linear combination of speech dictionary atoms (analogously for the interferer) and
\nIt is known that NMF represents data as a linear combination of a set of basis vectors, in which both the combination coefficients and the basis vectors are nonnegative. Although the basis learned by NMF is sparse, it is different from sparse coding [26]. This is because NMF learns a low rank representation of the data, while sparse coding usually learns the full rank representation. Treating speech enhancement as a source separation problem (speech and noise), NMF-based techniques can be used to factorize spectrograms into nonnegative speech and noise dictionaries and their nonnegative activations. Assume that a clean speech spectrogram as Xspeech and a clean noise spectrogram as Xnoise. Consider a supervised denoising approach where the clean speech basis matrix Dspeech and the clean noise basis matrix Dnoise are learned separately by performing NMF on the speech and the noise. During training process, minimized \n
To reduce the noise in the noisy speech, the concatenated dictionary D = [Dspeech, Dnoise] is fixed and utilized in decomposing the noisy speech Xnoisy by
\nwhere the time-varying activation matrix is formulated \n
Discarding the noise coding matrix, the target speech is estimated from the product of speech dictionaries and their activations as
\nThe clean speech waveform is estimated using the noisy phase and inverse DFT and the general framework of NMF-based speech enhancement is drawn in Figure 2.
\nBlock diagram of NMF-based speech enhancement.
The aforementioned dictionary learning approaches access the whole training set to determine the bases, which are referred as offline training process. These methods were reported to have good performance on modeling nonstationary noise types, which had been seen during training. For the time-frequency analysis of audio signals, however, the obtained basis may not be adequate to capture the temporal dependency of repeating patterns within the signal, and the success of these methods strongly relies on the prior knowledge of noise or speech or both, which limits implementations of the models. Recently, the online dictionary learning methods have been proposed in two aspects of implementing scheme [46, 47, 48, 49, 50] and circumventing the mismatch problem between the training and testing stages [24, 52].
\nOne drawback of the multiplicative update procedure on offline dictionary learning is the requirement of all the training signals to be read into memory and processed in each iteration. This high demand on both computing resources and memory is prohibitive in large-scale tasks. To address this problem, the online optimization algorithms were developed in an incremental fashion, which processes one sample of the training set at a time based on stochastic approximations or only a part of the training data at a time and updates patterns gradually until completely processed whole training corpus [46, 47, 48, 51]. More specifically, given M samples \n
where \n
The coefficient matrix is computed by
\nFor the online NMF framework, at step t, on the arrival of sample x(t), the corresponding coefficient c(t) is formulated by
\nwhere D(t−1) is the previous basis matrix. The matrix D(t) is updated by
\nwhere \n
In [50], an online noise basis learning scheme is proposed that uses the temporal dependencies of speech and noise signal to construct informative prior distribution. In this model, the noise basis matrix is learned from the noisy observation. To update the noise basis, the past noisy DFT magnitude frames are stored into a buffer and the buffer will be then updated with fixed speech basis when a new noisy frame arrives.
\nKwon et al. [52] present a speech enhancement technique combining statistical models and NMF with online update of speech and noise bases. A cascaded structure of combining a statistical model-based enhancement (SE) (the first state) [53] and NMF approach (second stage) with simultaneous update of speech and noise bases is proposed. In this model, the output clean speech at current frame is fed as an input to update the speech and noise bases in the following frame. In other words, at each frame, the clean speech estimation is obtained; the speech and noise bases for the NMF analysis in the following frame are updated. This online bases update makes it possible to deal with the speech and noise variations that cannot be covered by the training noise database and is considered a promising way to cope with the nonstationary nature of the signal. The noisy data X′(t) used for the online bases update herein is constructed by concatenating preenhanced output XSE(t) of performing statistical model-based enhancement (SE) with the current frame input X(t). The updating dictionary process will be learned by adding a regular term to the original objective function as follows:
\nwhere D′(t) = [D′speech, (t)D′noise(t)] denotes the basis matrix in NMF decomposing of the concatenated noisy data X′(t) and D(t) = [Dspeech, (t)Dnoise(t)] is the basis matrix used to analyze the t-frame X(t) in the second state.
\nIn the experimental simulations, speech and noise materials were selected from TIMIT [53] (192 sentences), NOISEX-92 DBs (15 types of noise: birds, casino, cicadas, computer keyboard, eating chips, f16, factory1, factory2, frogs, jungle, machineguns, motorcycles, ocean, pink, and volvo) [54], the GRID audiovisual corpus (34 speakers of both genders) [55], the NOIZEUS speech corpus (30 utterances with clean samples) [1]. The noisy speech examples were synthesized by adding clean speech to different types of noises at various input SNRs.
\nSpeech enhancement algorithms aim to improve both the speech quality and the speech intelligibility. A high-quality speech signal is perceived as being natural and pleasant to listen to, and free of distracting artifacts. An effective technique should suppress noises without bringing too much distortion to the enhanced speech. Measuring speech quality is challenging, as it is subjective and can be classified into subjective and objective measures. The speech enhancement performance was commonly evaluated in terms of three criteria including the signal to noise ratio (SNR) of enhanced speech [56], the segmental SNR (segSNR) [56], or the perceptual estimation of speech quality score (PESQ) [57, 58, 59]. Given the true and estimated speech magnitude spectra, the frequency-weighted segmental SNR is defined as:
\nsegSNR is a conceptually simple objective measure, computed on individual signal frames, and the per-frame scores are averaged over time.
\nwhere Xb,speech (t) is the frequency-domain representation of the clean speech signal, for frequency b and time frame t, \n
Contrary to spectral subtraction, dictionary approach does not assume a stationary interferer, optimizes the trade-off between source distortion and source confusion, and thus shows superiority over objective quality measures like cepstral distance, in the speaker-dependent and -independent case, in real-world environments and under low SNR condition. One possible reason could be due to lack of plenty of data to estimate a noise dictionary. At low SNR levels, the total volume of noise is much higher than that at high SNR levels, which offers a higher chance to obtain a good dictionary or noise modeling. However, under high SNR conditions, a lot of noise spectrum is buried in speech spectrum, which could make the learning of a noise dictionary difficult. The pretrained speech dictionary models outperform state-of-the-art methods like multiband spectral subtraction and approaches based on vector quantization [21, 22, 23]. Offline speech dictionary learning in a joint decomposition framework of the noisy speech spectrogram and a primary estimate of the clean speech spectrogram. Online learning approach processes input signals piece-by-piece by breaking the training data into small pieces and updates learned patterns gradually using accumulated statistics. With this approach, only a limited segment of the input signal is processed at a time. The online estimated dictionary is sufficient enough in basis subspace to avoid speech distortion. The online approaches tend to give better performance than batch learning [53].
\nThe computing demand for both offline learning and online learning consists of updating the coefficient matrix C and the pattern matrix D. The learning task is defined as an optimization problem, which aims to minimize an objective cost function f(D) with respect to the pattern matrix D. It is observed that the reconstruction error for both the online and offline methods converges to a similar value after several iterations and not monotonically decreasing at the beginning. Both batch and online learning converge to a stationary point of the expected cost function f(D) with unlimited data and unlimited computing resources. This situation is only valid in theory. For small-scale tasks where data are limited, but computing resources are unlimited, batch learning converges to a stationary point of the cost function ft(D), while online learning fails to converge, resulting in suboptimal patterns. For large-scale tasks, the more common situation is where training data are abundant but computing resources are limited. In this situation, due to its early learning property, online learning tends to obtain lower empirical cost than batch learning [49]. For sparse coding where the pattern matrix is overcomplete, for example, (K > M), then online learning is slower than batch learning. The online learning is significantly faster than the batch alternating learning by a factor of the large number of spectrograms reconstructed at each iteration [60].
\nIn short, dictionary learning plays an important role in machine learning, where data vectors are modeled as sparse linear combinations of basis factors (i.e., dictionary). However, how to conduct dictionary learning in noisy environment has not been well studied. In this chapter, we have reviewed speech enhancement techniques based on dictionary learning. The dictionary learning-based algorithms have gained a lot of attention due to their success in finding high-“quality” dictionary atoms (basis vectors) that best describe latent features of the underprocessed data. As a multivariate data analysis and dimensionality reduction technique, two relatively novel paradigms for dimensionality reduction and sparse representation, NMF and SR, have been in the ascendant since its inception. They enhance learning and data representation due to their parts-based and sparse representation from the nonnegativity or purely additive constraint. NMF and SR produce high-quality enhancement results when the dictionaries for different sources are sufficiently distinct. This survey chapter mainly focuses on the theoretical research into dictionary learning-based speech enhancement where the principles, basic models, properties, algorithms, and employing on SR and NMF are summarized systematically.
\nThis research is partially supported by the Ministry of Science and Technology under Grant Number 108-2634-F-008 -004 through Pervasive Artificial Intelligence Research (PAIR) Labs, Taiwan.
\nChemical communications in insects are exploited for many features as food seeking and preference, orientation, recruitment, defense, reproductive habitats, predator recognition, and mate attraction [1]. Chemical communication is distinguished by its effectiveness over long distances than others as mechanical and visual communications. Various active compounds were isolated and identified from different plant species that explore several activities toward other organisms [2, 3, 4, 5]. The wide range of these compounds affects different insect pests in different ways. Herbivorous insects may use host plant volatiles for determination of food, mates, and/or oviposition and hibernation sites by stimulation of insect chemoreceptor cells in taste sensilla present on antennae, tarsi, and mouthparts [6]. The manipulation of insect behavior occurs by detection of the chemical stimuli known as semiochemicals [7] or infochemicals [8]. Semiochemicals are defined as informative molecules released from one organism that evokes either a behavioral or physiological response between members of the same or different species. They are mainly used in plant-insect or insect-insect interactions as alternative or complementary components to insecticide approaches in different integrated pest management (IPM) strategies. Such compounds are mainly affecting the behavior of various insect pests via chemical signals which occur between insect and insect or plant and insect. Semiochemicals considered a promising component in IPM programs for controlling insect pests. They are involved in different control strategies such as monitoring, mass trapping, mating disruption, and attract-and-kill and push-pull strategies [1].
\nIn insects, the interaction of chemical signals can either stimulate or inhibit the behavior of the pest and so change its response. The response of insects to plant volatiles differs and is either attractive (adapted herbivore) or repellent (non-adapted herbivore). The classification of plant volatiles as attractants and repellents is not standardized due to fluctuation of insect behavior responses to such volatiles depending on their concentration. Herbivorous insects develop host plant compounds and use them as sex pheromone precursors or sex pheromones [9]. For example, male orchid bees assemble terpenoid mixtures from orchids and transfer them as an aggregation pheromone to stimulate leakage in mating [10]. Furthermore, moths, butterflies, grasshoppers, beetles, and aphids utilize pyrrolizidine alkaloids as feeding deterrents against their parasites and/or predators [11]. The interactions which occur between different organisms are divided into two main categories, intraspecific and interspecific, depending on how the interactions occur. An intraspecific communication passes between individuals of the same species, while an interspecific communication involves an interaction between members of different species. Based on the communication signal and subsequently the relation between the receiver and the emitter, semiochemicals are classified into two main functional groups: pheromones and allelochemicals [1].
\nPheromones are defined as species-specific chemical signals which enable communication between life-forms of the same species. Pheromones are secreted by insects which caused a specific reaction, for example, either a definite behavior (immediate effect on the behavior of the receiver) which is called a releaser pheromone or a developmental process (physiological effects on the receiver) which is called a primer pheromone [12]. Pheromones have been classified into eight various types: aggregation pheromones, alarm pheromones, oviposition-deterrent pheromones, home recognition pheromones, sex pheromones, trail pheromones, recruitment pheromones, and royal pheromones. Primer pheromones stimulate the olfactory sensory neurons that emit signals to the insect’s brain which stimulate hormones released by the endocrine system [13]. Caste determination in social insects (bees, wasps, ants, termites, locusts) resembles the most famous example for primer pheromone in Figure 1 [14]. Releaser pheromones are divided by function into sex pheromones, trail pheromones, alarm pheromones, etc. Sex pheromone is the most commonly known which species specific that attract opposite sexes for mating is highly. Concerning trail pheromones, these are commonly known in social insects for orientation and also for recruit nest mates toward a suitable food source. For example, ants and termites deposit these pheromones as they navigate their territory, thus promoting extensive nets of chemical routes [15]. On the other hand, bees release airborne orientation pheromones including forage marking, nest entrance finding, and swarming from the Nasonov gland. These pheromones are composed of mixtures of geraniol, farnesol, citral, and other minor compounds [16]. Alarm pheromones are well-developed pheromones in social insects for defensive function and are composed of multicomponent volatiles as mono- and sesquiterpenes and acetates [16, 17, 18]. The aggregation pheromones attract conspecifics of both sexes, e.g., bark beetles. The beetles start digging up into the bark of the host tree, thus releasing a mixture of terpenoids which are long-range aggregation pheromones that synthesized de novo, and others produced terpenoids via gut symbiotic bacteria or sequestered from the host tree. Depending on evoke aggregation pheromones, a great number of beetles attack, leading to killing of the host tree [14, 19].
\nSchematic profile drawings for exocrine glands of some social insects with a pheromonal function (capital lettering) [14].
The second subclass of semiochemicals is allelochemicals which includes substances that transmit chemical messages between different species. Fundamentally, these substances resemble an interspecific communication which are emitted by individuals of one species and are understood by individuals of a different species. Allelochemicals are divided depending on the benefits and costs to the signaler and receiver. They have been divided into five categories according to [1, 20] as follows.
\nAllomones (from Greek “allos + hormone” = excite others): released from one organism that stimulate a response in an individual of another species. The response is beneficial to the emitter, e.g., poisonous allelochemicals. They can also be seen as a deterrent emitted by insects against their predators as a defense mechanism. Granular trichomes which cover plant leaves and stems release herbivore-deterring allomones under stress conditions as a defense process. These allomones are toxic for the herbivorous insect pests, e.g., nicotine from a tobacco plant. Moreover, bolas spiders can deceit, lure, and capture male moths by synthesizing and mimicking moth pheromones [14].
\nKairomones (from a Greek word “kairos” = opportunistic or exploitative): emitted by one organism that stimulate a response in an individual of another species. The response is beneficial to the recipient, e.g., orientation of predaceous checkered beetles (Coleoptera, Cleridae) toward the aggregation pheromone of their prey and bark beetle (Coleoptera, Curculionidae, Scolytinae) [14, 21]. Kairomones may be allomones or pheromones depending on the circumstances. For example, American bolas spiders attract their prey (male moths) by releasing attractant allomones which serve as sex pheromones emitted by female moths. Also, exudates of warm-blooded animals that pull blood-sucking insects toward their hosts serve as kairomones.
\nSynomones: beneficial to both the releaser and receiver. Examples include scents used by flowers to attract pollinating insects. Moreover, herbivore-induced plant volatiles are considered to be active synomones which recruit natural enemies of insect pests toward the affected plants [22]. Also, synomones play an essential role in mate-finding communication. This role relies on the reduction of competition in the olfaction communication channel between closely related species with overlapping pheromone components. This advisable action is important in preventing exhaustion from the time and energy required for orientation toward heterospecifics [23]. In termites, hydroquinone is a phagostimulant compound secreted by labial glands distinguished as pheromones and synomones when different species are partaking the same foraging territory. It acts as a pheromone when recognized by nest mates of the same species and as a synomone when perceived by another termite species [24].
\nAntimones: maladaptive for both the releaser and receiver. These substances are produced or acquired by an organism that, when encountered by another individual of a different species in the natural environment, activate in the receiving individual a repellent response to the emitting and receiving individuals [1].
\nApneumones (from a Greek word “a-pneum” = breathless or lifeless): emitted by a non-living source, causing a favorable behavioral or physiological reaction to a receiving organism, but harmful to other species that may be found either in or on the non-living material. Apneumones were suggested by [7]. Rare cases of these allelochemicals have been found later in the literature, e.g., hexanal and 2-methyl-2-butanol released from rabbit stools attract sandfly females for oviposition [25].
\nChemical communication is an essential item for insects’ survivals that qualify them to adapt their behavior depending on the surrounding environment [1]. In insects, chemical communication is based on a mixture of one or several semiochemical substances which stimulate various receptor organs. The efficiency of semiochemicals in chemical communication is mainly based on various physical properties such as chemical nature, solubility volatility, and its lifetime in the environment. Also, the stability of such volatiles affects their efficiency in IPM programs [1]. Dispersal is a natural activity of insect where the movement is directed (taxes) or random (kineses) which is motivated by chemical or visual stimuli. There are three mechanisms of insect behavioral responses for finding an odor source. In the first mechanism called true chemotaxis, the insects align their body directly toward the odor source due to sensing the gradient of odor molecules. For the second mechanism, the insect does not discover the odor direction but becomes stimulated either for moving at different rates which is called orthokinesis or turning at various frequencies depending on changes in odor concentration (klinokinesis). The third mechanism depends on the odor of molecules impulse insect toward some other stimulus. Anemotaxis is the most common example for this mechanism where the molecules of an attractive chemical stimulate the receptive insects to fly upwind [26].
\nIn insects, chemosensory stimulation occurs in various receptor organs via constant bombardment of chemical signals which improved the insect’s ability to detect, discriminate, and distinguish innumerable different molecules as different odors. The insect receptor organs include antennae, mouthparts, and ovipositors. These receptors are very sensitive even for a few molecules of specific semiochemicals. Attraction (directed movement toward stimuli) and repulsion (directed movement away from stimuli) are the main insect responses to various odors. For field traps, insect catches not only occur via taxes but also via kineses (random movement). The insect can detect any odor by olfactory receptors located in the sensory organs including antennae, mouthparts, and ovipositors [27]. Various types of sensilla are recorded including trichodea, basiconica, styloconica, chaetica, etc. Knowledge of the types of sensilla on the antennae and mouthparts provides a foundation for understanding the olfaction and feeding preferences of herbivorous insect pests and subsequently can be useful for improving new control strategies for the target pests [28, 29]. The basic structure of sensillum is explored by [30] in Figure 2. The sensillum formed from the sensory neuron attached to branched cuticular pores (P) which allows odor passage. Sensillum pores act to filter molecules received from the airstream and concentrated it in the lumen of the sensillum and passed to branched neurons which convey impulses from and to the central nervous system.
\nBasic structure of sensillum [30].
In insects, the ability to discriminate different odors depends only on the evolutionary pressures of the molecules which stimulate the development of specific binding proteins (BPs) and specific receptor sites present on individual chemosensory neurons. This selectivity bestowed upon chemosensory neurons by the receptor types expressed represents one level of signal filtering in the insect’s olfactory system. The olfaction mechanism in insects is summarized by [14] in Figure 3. In brief, a chemical signal crosses the sensillum lymph (SL) through a pore and then binds to highly specific binding proteins: pheromone binding proteins/odorant binding proteins (PBPs/OBPs). The signal-PBP/OBP-complex passes or is transported to the chemosensory neuron, where it binds to a specific olfactory receptor protein (OR or R) in the neuron membrane. These receptor proteins were identified in 1999 by [31, 32]. They all belong to the same “seven-transmembrane-domain” protein family; however, they differ between taxa a great deal [33]. From a molecular perspective, binding to the OR activates so-called G-proteins, which are also located in the neuron membrane and part of a phosphorylation-dependent energy exchange, triggering a cascade of signaling reactions. These eventually lead to electrical impulses being sent down from the axon of the neuron to the antennal lobe (AL) (Figure 4). The AL is structured into a number of neuron groups (glomeruli) that are innervated separately and only in response to specific individual odors or classes of chemically similar ones [34]. Filtering of these signals is accomplished after reaching the AL glomeruli depending on their quality, quantity, and temporal and spatial characteristics. From the AL, specific patterns of neural activity are processed to higher integrative centers of the brain, such as the mushroom bodies (MBs; Figure 4), which are believed to be involved in the control of complex behaviors.
\nSimplified schematic concept of perireceptor events in the insect’s chemosensory sensilla. Absorbed stimulus molecules diffuse from the sensillum surface through pores in the cuticle (C) into the sensillum lymph. There, they are taken up by odorant- or pheromone-binding proteins and are transported through the aqueous lymph until they reach a specific receptor molecule (R) on the outer dendritic membrane (DM). This activates dendritic ion channels via membrane-bound proteins (*) and intracellular second messenger cascades such as cyclic guanosine monophosphate (cGMP), inositol trisphosphate (IP3), and Ca ions. Also, the stimulus molecule could degrade in the sensory lymphatic room by specific enzymes (E) into inactive metabolites so that it can no longer activate the receptor [35].
Schematic view of the central brain area of the honeybee showing the antennal lobes with their specific glomeruli (small circles). From the AL projection neurons (PN) send olfactory information into the mushroom bodies. The MBs are higher-order integration centers of olfactory, visual, and mechanosensory information and are believed to play a role in the control of complex behaviors as well as learning and memory. SOG: Sub-esophageal ganglion [36].
Olfactory/chemical signals represent essential components in different insect management strategies including monitoring, mass trapping, luring and killing, mating disruption, and push-pull strategy (stimulo-deterrent diversion). Also, host plant volatiles play an important role in IPM strategies as the main olfactory response of insect pests for determination of food, mates, and/or oviposition and hibernation sites [1]. Host plant volatiles are often induced by different environmental factors. For instance, the feeding process of herbivore may increase emission of volatiles in plants; these volatiles are referred to as herbivore-induced plant volatiles that stimulate natural enemies to find their prey as illustrated in Figure 5 [37]. Moreover, isolation and identification of such molecules are essential for consideration as new substances involved in IPM programs.
\nHerbivore-induced volatile effects on herbivores and their natural enemies [37].
Recently, the application of different semiochemicals has become an important category of integrated pest management. Various semiochemical compounds are widely applied not only for controlling insect pests [38, 39, 40, 41] but also for conservation of rare and threatened insects [42]. Semiochemical substances provide prospective interest in IPM programs depending on the outcome advantages of using such substances. For instance, these substances are distinguished by high volatility that allows diffusion for long distances, application in low concentrations, and rapid dissipation that reduces health and environmental risks compared with chemical pesticides. The efficacy of such molecules mainly depends on their physical properties, i.e., molecular structure, volatility, solubility, and lifetime in the environment. Also, the environmental factors are an important parameter that affect the activity of semiochemical compounds. For example, temperature affects the stability of such compounds by increasing the diffusion of volatile compounds, leading to decreased molecule lifetime in the environment [1].
\nControl strategies of herbivorous insects are mainly based on semiochemicals which include monitoring, mass trapping, lure-and-kill (attract-annihilate), mating disruption, and push-pull strategy (stimulo-deterrent diversion) tactics. Pheromones are considered as a promising and important component in IPM programs. It can be applied singly or in integration with other control strategies in the agricultural system management for monitoring and controlling various insect pests [1]. The pheromone application is performed in two ways: indirect control and direct control strategies. The direct control involved mass trapping and area-wide dissemination which includes disruption, attractant, and attract-and-kill (lure-and-kill). However, the indirect control involves monitoring for quarantine and spray timing strategy. Pheromone traps are widely used commercially for different purposes in IPM strategies. For example, pheromone-baited traps are used as attract-and-kill or mating disruption techniques to prevent males from reproducing. Furthermore, pheromone can play an important role for detection of information about insect populations. It represents an overview for sex ratio and the mating status which are serious data for the detection of the population phase which is subject to cyclical changes in population density [43, 44]. Interestingly, strategies depending on pheromone application are useful for measuring the genetic diversity of insect pests. For example, the genetic diversity of the Asian long-horned beetle in Asia, North America, and Europe is reported to be based on pheromone traps [45].
\nCombinations of different communication signals are extremely more efficient in attracting insects than a single stimulus for controlling insect pests. The most successful strategies for insect management were recorded for a combination between different communication signals as visual (color, shape, or size) and olfactory stimuli [1]. Lure-and-kill strategy is an important and widespread tactic which used sticky materials to prevent captured insect from escaping and/or baited with insecticide. Also, combining an insecticide and/or a food stimulant can further enhance the efficacy of visual-depending traps for field applications. The chemical and visual stimuli that attract insects to their host plants have been incorporated into a wide range of insect traps that work better than using a single stimulus [46, 47, 48, 49, 50]. Many examples exist where visual stimuli enhance insect responses to semiochemical-based traps [51, 52, 53]. Using spheres with red color attractant coated with a non-drying adhesive combined with attractants with odors resembling ripening apples results in an excellent control of the apple maggot fly, Rhagoletis pomonella (Walsh) [47]. Also, the choice for suitable places for female mosquitoes to lay eggs is a key factor for the survival of immature stages (eggs and larvae). This knowledge stands out in importance concerning the control of disease vectors. The selection of a place for oviposition requires a set of chemical, visual, olfactory, and tactile cues that interact with the female before laying eggs, helping the localization of adequate sites for oviposition [54].
\nAuthors are listed below with their open access chapters linked via author name:
",metaTitle:"IntechOpen authors on the Global Highly Cited Researchers 2018 list",metaDescription:null,metaKeywords:null,canonicalURL:null,contentRaw:'[{"type":"htmlEditorComponent","content":"New for 2018 (alphabetically by surname).
\\n\\n\\n\\n\\n\\n\\n\\n\\n\\nJocelyn Chanussot (chapter to be published soon...)
\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\nYuekun Lai
\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\nPrevious years (alphabetically by surname)
\\n\\nAbdul Latif Ahmad 2016-18
\\n\\nKhalil Amine 2017, 2018
\\n\\nEwan Birney 2015-18
\\n\\nFrede Blaabjerg 2015-18
\\n\\nGang Chen 2016-18
\\n\\nJunhong Chen 2017, 2018
\\n\\nZhigang Chen 2016, 2018
\\n\\nMyung-Haing Cho 2016, 2018
\\n\\nMark Connors 2015-18
\\n\\nCyrus Cooper 2017, 2018
\\n\\nLiming Dai 2015-18
\\n\\nWeihua Deng 2017, 2018
\\n\\nVincenzo Fogliano 2017, 2018
\\n\\nRon de Graaf 2014-18
\\n\\nHarald Haas 2017, 2018
\\n\\nFrancisco Herrera 2017, 2018
\\n\\nJaakko Kangasjärvi 2015-18
\\n\\nHamid Reza Karimi 2016-18
\\n\\nJunji Kido 2014-18
\\n\\nJose Luiszamorano 2015-18
\\n\\nYiqi Luo 2016-18
\\n\\nJoachim Maier 2014-18
\\n\\nAndrea Natale 2017, 2018
\\n\\nAlberto Mantovani 2014-18
\\n\\nMarjan Mernik 2017, 2018
\\n\\nSandra Orchard 2014, 2016-18
\\n\\nMohamed Oukka 2016-18
\\n\\nBiswajeet Pradhan 2016-18
\\n\\nDirk Raes 2017, 2018
\\n\\nUlrike Ravens-Sieberer 2016-18
\\n\\nYexiang Tong 2017, 2018
\\n\\nJim Van Os 2015-18
\\n\\nLong Wang 2017, 2018
\\n\\nFei Wei 2016-18
\\n\\nIoannis Xenarios 2017, 2018
\\n\\nQi Xie 2016-18
\\n\\nXin-She Yang 2017, 2018
\\n\\nYulong Yin 2015, 2017, 2018
\\n"}]'},components:[{type:"htmlEditorComponent",content:'New for 2018 (alphabetically by surname).
\n\n\n\n\n\n\n\n\n\nJocelyn Chanussot (chapter to be published soon...)
\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nYuekun Lai
\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPrevious years (alphabetically by surname)
\n\nAbdul Latif Ahmad 2016-18
\n\nKhalil Amine 2017, 2018
\n\nEwan Birney 2015-18
\n\nFrede Blaabjerg 2015-18
\n\nGang Chen 2016-18
\n\nJunhong Chen 2017, 2018
\n\nZhigang Chen 2016, 2018
\n\nMyung-Haing Cho 2016, 2018
\n\nMark Connors 2015-18
\n\nCyrus Cooper 2017, 2018
\n\nLiming Dai 2015-18
\n\nWeihua Deng 2017, 2018
\n\nVincenzo Fogliano 2017, 2018
\n\nRon de Graaf 2014-18
\n\nHarald Haas 2017, 2018
\n\nFrancisco Herrera 2017, 2018
\n\nJaakko Kangasjärvi 2015-18
\n\nHamid Reza Karimi 2016-18
\n\nJunji Kido 2014-18
\n\nJose Luiszamorano 2015-18
\n\nYiqi Luo 2016-18
\n\nJoachim Maier 2014-18
\n\nAndrea Natale 2017, 2018
\n\nAlberto Mantovani 2014-18
\n\nMarjan Mernik 2017, 2018
\n\nSandra Orchard 2014, 2016-18
\n\nMohamed Oukka 2016-18
\n\nBiswajeet Pradhan 2016-18
\n\nDirk Raes 2017, 2018
\n\nUlrike Ravens-Sieberer 2016-18
\n\nYexiang Tong 2017, 2018
\n\nJim Van Os 2015-18
\n\nLong Wang 2017, 2018
\n\nFei Wei 2016-18
\n\nIoannis Xenarios 2017, 2018
\n\nQi Xie 2016-18
\n\nXin-She Yang 2017, 2018
\n\nYulong Yin 2015, 2017, 2018
\n'}]},successStories:{items:[]},authorsAndEditors:{filterParams:{sort:"featured,name"},profiles:[{id:"6700",title:"Dr.",name:"Abbass A.",middleName:null,surname:"Hashim",slug:"abbass-a.-hashim",fullName:"Abbass A. Hashim",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/6700/images/1864_n.jpg",biography:"Currently I am carrying out research in several areas of interest, mainly covering work on chemical and bio-sensors, semiconductor thin film device fabrication and characterisation.\nAt the moment I have very strong interest in radiation environmental pollution and bacteriology treatment. The teams of researchers are working very hard to bring novel results in this field. I am also a member of the team in charge for the supervision of Ph.D. students in the fields of development of silicon based planar waveguide sensor devices, study of inelastic electron tunnelling in planar tunnelling nanostructures for sensing applications and development of organotellurium(IV) compounds for semiconductor applications. I am a specialist in data analysis techniques and nanosurface structure. I have served as the editor for many books, been a member of the editorial board in science journals, have published many papers and hold many patents.",institutionString:null,institution:{name:"Sheffield Hallam University",country:{name:"United Kingdom"}}},{id:"54525",title:"Prof.",name:"Abdul Latif",middleName:null,surname:"Ahmad",slug:"abdul-latif-ahmad",fullName:"Abdul Latif Ahmad",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"20567",title:"Prof.",name:"Ado",middleName:null,surname:"Jorio",slug:"ado-jorio",fullName:"Ado Jorio",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Universidade Federal de Minas Gerais",country:{name:"Brazil"}}},{id:"47940",title:"Dr.",name:"Alberto",middleName:null,surname:"Mantovani",slug:"alberto-mantovani",fullName:"Alberto Mantovani",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"12392",title:"Mr.",name:"Alex",middleName:null,surname:"Lazinica",slug:"alex-lazinica",fullName:"Alex Lazinica",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/12392/images/7282_n.png",biography:"Alex Lazinica is the founder and CEO of IntechOpen. After obtaining a Master's degree in Mechanical Engineering, he continued his PhD studies in Robotics at the Vienna University of Technology. Here he worked as a robotic researcher with the university's Intelligent Manufacturing Systems Group as well as a guest researcher at various European universities, including the Swiss Federal Institute of Technology Lausanne (EPFL). During this time he published more than 20 scientific papers, gave presentations, served as a reviewer for major robotic journals and conferences and most importantly he co-founded and built the International Journal of Advanced Robotic Systems- world's first Open Access journal in the field of robotics. Starting this journal was a pivotal point in his career, since it was a pathway to founding IntechOpen - Open Access publisher focused on addressing academic researchers needs. Alex is a personification of IntechOpen key values being trusted, open and entrepreneurial. Today his focus is on defining the growth and development strategy for the company.",institutionString:null,institution:{name:"TU Wien",country:{name:"Austria"}}},{id:"19816",title:"Prof.",name:"Alexander",middleName:null,surname:"Kokorin",slug:"alexander-kokorin",fullName:"Alexander Kokorin",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/19816/images/1607_n.jpg",biography:"Alexander I. Kokorin: born: 1947, Moscow; DSc., PhD; Principal Research Fellow (Research Professor) of Department of Kinetics and Catalysis, N. Semenov Institute of Chemical Physics, Russian Academy of Sciences, Moscow.\r\nArea of research interests: physical chemistry of complex-organized molecular and nanosized systems, including polymer-metal complexes; the surface of doped oxide semiconductors. He is an expert in structural, absorptive, catalytic and photocatalytic properties, in structural organization and dynamic features of ionic liquids, in magnetic interactions between paramagnetic centers. The author or co-author of 3 books, over 200 articles and reviews in scientific journals and books. He is an actual member of the International EPR/ESR Society, European Society on Quantum Solar Energy Conversion, Moscow House of Scientists, of the Board of Moscow Physical Society.",institutionString:null,institution:{name:"Semenov Institute of Chemical Physics",country:{name:"Russia"}}},{id:"62389",title:"PhD.",name:"Ali Demir",middleName:null,surname:"Sezer",slug:"ali-demir-sezer",fullName:"Ali Demir Sezer",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/62389/images/3413_n.jpg",biography:"Dr. Ali Demir Sezer has a Ph.D. from Pharmaceutical Biotechnology at the Faculty of Pharmacy, University of Marmara (Turkey). He is the member of many Pharmaceutical Associations and acts as a reviewer of scientific journals and European projects under different research areas such as: drug delivery systems, nanotechnology and pharmaceutical biotechnology. Dr. Sezer is the author of many scientific publications in peer-reviewed journals and poster communications. Focus of his research activity is drug delivery, physico-chemical characterization and biological evaluation of biopolymers micro and nanoparticles as modified drug delivery system, and colloidal drug carriers (liposomes, nanoparticles etc.).",institutionString:null,institution:{name:"Marmara University",country:{name:"Turkey"}}},{id:"61051",title:"Prof.",name:"Andrea",middleName:null,surname:"Natale",slug:"andrea-natale",fullName:"Andrea Natale",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"100762",title:"Prof.",name:"Andrea",middleName:null,surname:"Natale",slug:"andrea-natale",fullName:"Andrea Natale",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"St David's Medical Center",country:{name:"United States of America"}}},{id:"107416",title:"Dr.",name:"Andrea",middleName:null,surname:"Natale",slug:"andrea-natale",fullName:"Andrea Natale",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Texas Cardiac Arrhythmia",country:{name:"United States of America"}}},{id:"64434",title:"Dr.",name:"Angkoon",middleName:null,surname:"Phinyomark",slug:"angkoon-phinyomark",fullName:"Angkoon Phinyomark",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/64434/images/2619_n.jpg",biography:"My name is Angkoon Phinyomark. I received a B.Eng. degree in Computer Engineering with First Class Honors in 2008 from Prince of Songkla University, Songkhla, Thailand, where I received a Ph.D. degree in Electrical Engineering. My research interests are primarily in the area of biomedical signal processing and classification notably EMG (electromyography signal), EOG (electrooculography signal), and EEG (electroencephalography signal), image analysis notably breast cancer analysis and optical coherence tomography, and rehabilitation engineering. I became a student member of IEEE in 2008. During October 2011-March 2012, I had worked at School of Computer Science and Electronic Engineering, University of Essex, Colchester, Essex, United Kingdom. In addition, during a B.Eng. I had been a visiting research student at Faculty of Computer Science, University of Murcia, Murcia, Spain for three months.\n\nI have published over 40 papers during 5 years in refereed journals, books, and conference proceedings in the areas of electro-physiological signals processing and classification, notably EMG and EOG signals, fractal analysis, wavelet analysis, texture analysis, feature extraction and machine learning algorithms, and assistive and rehabilitative devices. I have several computer programming language certificates, i.e. Sun Certified Programmer for the Java 2 Platform 1.4 (SCJP), Microsoft Certified Professional Developer, Web Developer (MCPD), Microsoft Certified Technology Specialist, .NET Framework 2.0 Web (MCTS). I am a Reviewer for several refereed journals and international conferences, such as IEEE Transactions on Biomedical Engineering, IEEE Transactions on Industrial Electronics, Optic Letters, Measurement Science Review, and also a member of the International Advisory Committee for 2012 IEEE Business Engineering and Industrial Applications and 2012 IEEE Symposium on Business, Engineering and Industrial Applications.",institutionString:null,institution:{name:"Joseph Fourier University",country:{name:"France"}}},{id:"55578",title:"Dr.",name:"Antonio",middleName:null,surname:"Jurado-Navas",slug:"antonio-jurado-navas",fullName:"Antonio Jurado-Navas",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/55578/images/4574_n.png",biography:"Antonio Jurado-Navas received the M.S. degree (2002) and the Ph.D. degree (2009) in Telecommunication Engineering, both from the University of Málaga (Spain). He first worked as a consultant at Vodafone-Spain. From 2004 to 2011, he was a Research Assistant with the Communications Engineering Department at the University of Málaga. In 2011, he became an Assistant Professor in the same department. From 2012 to 2015, he was with Ericsson Spain, where he was working on geo-location\ntools for third generation mobile networks. Since 2015, he is a Marie-Curie fellow at the Denmark Technical University. His current research interests include the areas of mobile communication systems and channel modeling in addition to atmospheric optical communications, adaptive optics and statistics",institutionString:null,institution:{name:"University of Malaga",country:{name:"Spain"}}}],filtersByRegion:[{group:"region",caption:"North America",value:1,count:5703},{group:"region",caption:"Middle and South America",value:2,count:5174},{group:"region",caption:"Africa",value:3,count:1690},{group:"region",caption:"Asia",value:4,count:10246},{group:"region",caption:"Australia and Oceania",value:5,count:889},{group:"region",caption:"Europe",value:6,count:15653}],offset:12,limit:12,total:117316},chapterEmbeded:{data:{}},editorApplication:{success:null,errors:{}},ofsBooks:{filterParams:{hasNoEditors:"0",sort:"dateEndThirdStepPublish",topicId:"8,11,12,14"},books:[{type:"book",id:"10581",title:"Alkaline Chemistry and Applications",subtitle:null,isOpenForSubmission:!0,hash:"4ed90bdab4a7211c13cd432aa079cd20",slug:null,bookSignature:"Dr. Riadh Marzouki",coverURL:"https://cdn.intechopen.com/books/images_new/10581.jpg",editedByType:null,editors:[{id:"300527",title:"Dr.",name:"Riadh",surname:"Marzouki",slug:"riadh-marzouki",fullName:"Riadh Marzouki"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10374",title:"Advances in Micro- and Nanofluidics",subtitle:null,isOpenForSubmission:!0,hash:"b7ba9cab862a9bca2fc9f9ee72ba5eec",slug:null,bookSignature:"Prof. S. M. Sohel Murshed",coverURL:"https://cdn.intechopen.com/books/images_new/10374.jpg",editedByType:null,editors:[{id:"24904",title:"Prof.",name:"S. M. Sohel",surname:"Murshed",slug:"s.-m.-sohel-murshed",fullName:"S. M. Sohel Murshed"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10597",title:"Electric Grid Modernization",subtitle:null,isOpenForSubmission:!0,hash:"62f0e391662f7e8ae35a6bea2e77accf",slug:null,bookSignature:"Dr. Mahmoud Ghofrani",coverURL:"https://cdn.intechopen.com/books/images_new/10597.jpg",editedByType:null,editors:[{id:"183482",title:"Dr.",name:"Mahmoud",surname:"Ghofrani",slug:"mahmoud-ghofrani",fullName:"Mahmoud Ghofrani"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10412",title:"Transition Metals",subtitle:null,isOpenForSubmission:!0,hash:"bd7287b801dc0ac77e01f66842dc1d99",slug:null,bookSignature:"Dr. Sajjad Haider and Dr. Adnan Haider",coverURL:"https://cdn.intechopen.com/books/images_new/10412.jpg",editedByType:null,editors:[{id:"110708",title:"Dr.",name:"Sajjad",surname:"Haider",slug:"sajjad-haider",fullName:"Sajjad Haider"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10216",title:"Paraffin - Thermal Energy Storage Applications",subtitle:null,isOpenForSubmission:!0,hash:"456090b63f5ba2290e24e655abd119bf",slug:null,bookSignature:"Dr. Elsayed Zaki and Dr. Abdelghaffar S. Dhmees",coverURL:"https://cdn.intechopen.com/books/images_new/10216.jpg",editedByType:null,editors:[{id:"220156",title:"Dr.",name:"Elsayed",surname:"Zaki",slug:"elsayed-zaki",fullName:"Elsayed Zaki"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10506",title:"Liquid Metals",subtitle:null,isOpenForSubmission:!0,hash:"a1c30d83631953e1c8905554d937bb10",slug:null,bookSignature:"Dr. Samson Jerold Samuel Chelladurai, Dr. S. Gnanasekaran and Dr. Suresh Mayilswamy",coverURL:"https://cdn.intechopen.com/books/images_new/10506.jpg",editedByType:null,editors:[{id:"247421",title:"Dr.",name:"Samson Jerold Samuel",surname:"Chelladurai",slug:"samson-jerold-samuel-chelladurai",fullName:"Samson Jerold Samuel Chelladurai"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10491",title:"Anaerobic Digestion in Natural and Built Environments",subtitle:null,isOpenForSubmission:!0,hash:"082ec753a05d6c7ed8cc5559e7dac432",slug:null,bookSignature:"Dr. Anna Sikora and Dr. Anna Detman",coverURL:"https://cdn.intechopen.com/books/images_new/10491.jpg",editedByType:null,editors:[{id:"146985",title:"Dr.",name:"Anna",surname:"Sikora",slug:"anna-sikora",fullName:"Anna Sikora"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10573",title:"Fluid-Structure Interaction",subtitle:null,isOpenForSubmission:!0,hash:"3950d1f9c82160d23bc594d00ec2ffbb",slug:null,bookSignature:"Dr. Khaled Ghaedi",coverURL:"https://cdn.intechopen.com/books/images_new/10573.jpg",editedByType:null,editors:[{id:"190572",title:"Dr.",name:"Khaled",surname:"Ghaedi",slug:"khaled-ghaedi",fullName:"Khaled Ghaedi"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10590",title:"Humic Substance",subtitle:null,isOpenForSubmission:!0,hash:"85786eb36b3e13979aae664a4e046625",slug:null,bookSignature:"Prof. Abdelhadi Makan",coverURL:"https://cdn.intechopen.com/books/images_new/10590.jpg",editedByType:null,editors:[{id:"247727",title:"Prof.",name:"Abdelhadi",surname:"Makan",slug:"abdelhadi-makan",fullName:"Abdelhadi Makan"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10609",title:"Zeolites",subtitle:null,isOpenForSubmission:!0,hash:"90681a8fef45a03f68f4b9276acba2d3",slug:null,bookSignature:"Dr. Pavel Krivenko",coverURL:"https://cdn.intechopen.com/books/images_new/10609.jpg",editedByType:null,editors:[{id:"180922",title:"Dr.",name:"Pavel",surname:"Krivenko",slug:"pavel-krivenko",fullName:"Pavel Krivenko"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10495",title:"Insights Into Global Engineering Education After the Birth of Industry 5.0",subtitle:null,isOpenForSubmission:!0,hash:"e83ddb1aa8017926d0635bbe8a90feca",slug:null,bookSignature:"Dr.Ing. Montaha Bouezzeddine",coverURL:"https://cdn.intechopen.com/books/images_new/10495.jpg",editedByType:null,editors:[{id:"313464",title:"Dr.Ing.",name:"Montaha",surname:"Bouezzeddine",slug:"montaha-bouezzeddine",fullName:"Montaha Bouezzeddine"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10502",title:"Aflatoxins",subtitle:null,isOpenForSubmission:!0,hash:"34fe61c309f2405130ede7a267cf8bd5",slug:null,bookSignature:"Dr. Lukman Bola Abdulra'uf",coverURL:"https://cdn.intechopen.com/books/images_new/10502.jpg",editedByType:null,editors:[{id:"149347",title:"Dr.",name:"Lukman",surname:"Abdulra'uf",slug:"lukman-abdulra'uf",fullName:"Lukman Abdulra'uf"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}],filtersByTopic:[{group:"topic",caption:"Agricultural and Biological Sciences",value:5,count:10},{group:"topic",caption:"Biochemistry, Genetics and Molecular Biology",value:6,count:14},{group:"topic",caption:"Business, Management and Economics",value:7,count:2},{group:"topic",caption:"Chemistry",value:8,count:6},{group:"topic",caption:"Computer and Information Science",value:9,count:10},{group:"topic",caption:"Earth and Planetary Sciences",value:10,count:4},{group:"topic",caption:"Engineering",value:11,count:15},{group:"topic",caption:"Environmental Sciences",value:12,count:2},{group:"topic",caption:"Immunology and Microbiology",value:13,count:4},{group:"topic",caption:"Materials Science",value:14,count:5},{group:"topic",caption:"Mathematics",value:15,count:1},{group:"topic",caption:"Medicine",value:16,count:55},{group:"topic",caption:"Neuroscience",value:18,count:1},{group:"topic",caption:"Pharmacology, Toxicology and Pharmaceutical Science",value:19,count:5},{group:"topic",caption:"Physics",value:20,count:2},{group:"topic",caption:"Psychology",value:21,count:3},{group:"topic",caption:"Robotics",value:22,count:1},{group:"topic",caption:"Social Sciences",value:23,count:3},{group:"topic",caption:"Technology",value:24,count:1},{group:"topic",caption:"Veterinary Medicine and Science",value:25,count:2}],offset:12,limit:12,total:28},popularBooks:{featuredBooks:[{type:"book",id:"7802",title:"Modern Slavery and Human Trafficking",subtitle:null,isOpenForSubmission:!1,hash:"587a0b7fb765f31cc98de33c6c07c2e0",slug:"modern-slavery-and-human-trafficking",bookSignature:"Jane Reeves",coverURL:"https://cdn.intechopen.com/books/images_new/7802.jpg",editors:[{id:"211328",title:"Prof.",name:"Jane",middleName:null,surname:"Reeves",slug:"jane-reeves",fullName:"Jane Reeves"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"9961",title:"Data Mining",subtitle:"Methods, Applications and Systems",isOpenForSubmission:!1,hash:"ed79fb6364f2caf464079f94a0387146",slug:"data-mining-methods-applications-and-systems",bookSignature:"Derya Birant",coverURL:"https://cdn.intechopen.com/books/images_new/9961.jpg",editors:[{id:"15609",title:"Dr.",name:"Derya",middleName:null,surname:"Birant",slug:"derya-birant",fullName:"Derya Birant"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"8545",title:"Animal Reproduction in Veterinary Medicine",subtitle:null,isOpenForSubmission:!1,hash:"13aaddf5fdbbc78387e77a7da2388bf6",slug:"animal-reproduction-in-veterinary-medicine",bookSignature:"Faruk Aral, Rita Payan-Carreira and Miguel Quaresma",coverURL:"https://cdn.intechopen.com/books/images_new/8545.jpg",editors:[{id:"25600",title:"Prof.",name:"Faruk",middleName:null,surname:"Aral",slug:"faruk-aral",fullName:"Faruk Aral"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"9157",title:"Neurodegenerative Diseases",subtitle:"Molecular Mechanisms and Current Therapeutic Approaches",isOpenForSubmission:!1,hash:"bc8be577966ef88735677d7e1e92ed28",slug:"neurodegenerative-diseases-molecular-mechanisms-and-current-therapeutic-approaches",bookSignature:"Nagehan Ersoy Tunalı",coverURL:"https://cdn.intechopen.com/books/images_new/9157.jpg",editors:[{id:"82778",title:"Ph.D.",name:"Nagehan",middleName:null,surname:"Ersoy Tunalı",slug:"nagehan-ersoy-tunali",fullName:"Nagehan Ersoy Tunalı"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"8686",title:"Direct Torque Control Strategies of Electrical Machines",subtitle:null,isOpenForSubmission:!1,hash:"b6ad22b14db2b8450228545d3d4f6b1a",slug:"direct-torque-control-strategies-of-electrical-machines",bookSignature:"Fatma Ben Salem",coverURL:"https://cdn.intechopen.com/books/images_new/8686.jpg",editors:[{id:"295623",title:"Associate Prof.",name:"Fatma",middleName:null,surname:"Ben Salem",slug:"fatma-ben-salem",fullName:"Fatma Ben Salem"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"7434",title:"Molecular Biotechnology",subtitle:null,isOpenForSubmission:!1,hash:"eceede809920e1ec7ecadd4691ede2ec",slug:"molecular-biotechnology",bookSignature:"Sergey Sedykh",coverURL:"https://cdn.intechopen.com/books/images_new/7434.jpg",editors:[{id:"178316",title:"Ph.D.",name:"Sergey",middleName:null,surname:"Sedykh",slug:"sergey-sedykh",fullName:"Sergey Sedykh"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"9208",title:"Welding",subtitle:"Modern Topics",isOpenForSubmission:!1,hash:"7d6be076ccf3a3f8bd2ca52d86d4506b",slug:"welding-modern-topics",bookSignature:"Sadek Crisóstomo Absi Alfaro, Wojciech Borek and Błażej Tomiczek",coverURL:"https://cdn.intechopen.com/books/images_new/9208.jpg",editors:[{id:"65292",title:"Prof.",name:"Sadek Crisostomo Absi",middleName:"C. Absi",surname:"Alfaro",slug:"sadek-crisostomo-absi-alfaro",fullName:"Sadek Crisostomo Absi Alfaro"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"7831",title:"Sustainability in Urban Planning and Design",subtitle:null,isOpenForSubmission:!1,hash:"c924420492c8c2c9751e178d025f4066",slug:"sustainability-in-urban-planning-and-design",bookSignature:"Amjad Almusaed, Asaad Almssad and Linh Truong - Hong",coverURL:"https://cdn.intechopen.com/books/images_new/7831.jpg",editors:[{id:"110471",title:"Dr.",name:"Amjad",middleName:"Zaki",surname:"Almusaed",slug:"amjad-almusaed",fullName:"Amjad Almusaed"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"9343",title:"Trace Metals in the Environment",subtitle:"New Approaches and Recent Advances",isOpenForSubmission:!1,hash:"ae07e345bc2ce1ebbda9f70c5cd12141",slug:"trace-metals-in-the-environment-new-approaches-and-recent-advances",bookSignature:"Mario Alfonso Murillo-Tovar, Hugo Saldarriaga-Noreña and Agnieszka Saeid",coverURL:"https://cdn.intechopen.com/books/images_new/9343.jpg",editors:[{id:"255959",title:"Dr.",name:"Mario Alfonso",middleName:null,surname:"Murillo-Tovar",slug:"mario-alfonso-murillo-tovar",fullName:"Mario Alfonso Murillo-Tovar"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"9139",title:"Topics in Primary Care Medicine",subtitle:null,isOpenForSubmission:!1,hash:"ea774a4d4c1179da92a782e0ae9cde92",slug:"topics-in-primary-care-medicine",bookSignature:"Thomas F. Heston",coverURL:"https://cdn.intechopen.com/books/images_new/9139.jpg",editors:[{id:"217926",title:"Dr.",name:"Thomas F.",middleName:null,surname:"Heston",slug:"thomas-f.-heston",fullName:"Thomas F. Heston"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"9839",title:"Outdoor Recreation",subtitle:"Physiological and Psychological Effects on Health",isOpenForSubmission:!1,hash:"5f5a0d64267e32567daffa5b0c6a6972",slug:"outdoor-recreation-physiological-and-psychological-effects-on-health",bookSignature:"Hilde G. Nielsen",coverURL:"https://cdn.intechopen.com/books/images_new/9839.jpg",editors:[{id:"158692",title:"Ph.D.",name:"Hilde G.",middleName:null,surname:"Nielsen",slug:"hilde-g.-nielsen",fullName:"Hilde G. Nielsen"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"8697",title:"Virtual Reality and Its Application in Education",subtitle:null,isOpenForSubmission:!1,hash:"ee01b5e387ba0062c6b0d1e9227bda05",slug:"virtual-reality-and-its-application-in-education",bookSignature:"Dragan Cvetković",coverURL:"https://cdn.intechopen.com/books/images_new/8697.jpg",editors:[{id:"101330",title:"Dr.",name:"Dragan",middleName:"Mladen",surname:"Cvetković",slug:"dragan-cvetkovic",fullName:"Dragan Cvetković"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}}],offset:12,limit:12,total:5150},hotBookTopics:{hotBooks:[],offset:0,limit:12,total:null},publish:{},publishingProposal:{success:null,errors:{}},books:{featuredBooks:[{type:"book",id:"7802",title:"Modern Slavery and Human Trafficking",subtitle:null,isOpenForSubmission:!1,hash:"587a0b7fb765f31cc98de33c6c07c2e0",slug:"modern-slavery-and-human-trafficking",bookSignature:"Jane Reeves",coverURL:"https://cdn.intechopen.com/books/images_new/7802.jpg",editors:[{id:"211328",title:"Prof.",name:"Jane",middleName:null,surname:"Reeves",slug:"jane-reeves",fullName:"Jane Reeves"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"9961",title:"Data Mining",subtitle:"Methods, Applications and Systems",isOpenForSubmission:!1,hash:"ed79fb6364f2caf464079f94a0387146",slug:"data-mining-methods-applications-and-systems",bookSignature:"Derya Birant",coverURL:"https://cdn.intechopen.com/books/images_new/9961.jpg",editors:[{id:"15609",title:"Dr.",name:"Derya",middleName:null,surname:"Birant",slug:"derya-birant",fullName:"Derya Birant"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"8545",title:"Animal Reproduction in Veterinary Medicine",subtitle:null,isOpenForSubmission:!1,hash:"13aaddf5fdbbc78387e77a7da2388bf6",slug:"animal-reproduction-in-veterinary-medicine",bookSignature:"Faruk Aral, Rita Payan-Carreira and Miguel Quaresma",coverURL:"https://cdn.intechopen.com/books/images_new/8545.jpg",editors:[{id:"25600",title:"Prof.",name:"Faruk",middleName:null,surname:"Aral",slug:"faruk-aral",fullName:"Faruk Aral"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"9157",title:"Neurodegenerative Diseases",subtitle:"Molecular Mechanisms and Current Therapeutic Approaches",isOpenForSubmission:!1,hash:"bc8be577966ef88735677d7e1e92ed28",slug:"neurodegenerative-diseases-molecular-mechanisms-and-current-therapeutic-approaches",bookSignature:"Nagehan Ersoy Tunalı",coverURL:"https://cdn.intechopen.com/books/images_new/9157.jpg",editors:[{id:"82778",title:"Ph.D.",name:"Nagehan",middleName:null,surname:"Ersoy Tunalı",slug:"nagehan-ersoy-tunali",fullName:"Nagehan Ersoy Tunalı"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"8686",title:"Direct Torque Control Strategies of Electrical Machines",subtitle:null,isOpenForSubmission:!1,hash:"b6ad22b14db2b8450228545d3d4f6b1a",slug:"direct-torque-control-strategies-of-electrical-machines",bookSignature:"Fatma Ben Salem",coverURL:"https://cdn.intechopen.com/books/images_new/8686.jpg",editors:[{id:"295623",title:"Associate Prof.",name:"Fatma",middleName:null,surname:"Ben Salem",slug:"fatma-ben-salem",fullName:"Fatma Ben Salem"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"7434",title:"Molecular Biotechnology",subtitle:null,isOpenForSubmission:!1,hash:"eceede809920e1ec7ecadd4691ede2ec",slug:"molecular-biotechnology",bookSignature:"Sergey Sedykh",coverURL:"https://cdn.intechopen.com/books/images_new/7434.jpg",editors:[{id:"178316",title:"Ph.D.",name:"Sergey",middleName:null,surname:"Sedykh",slug:"sergey-sedykh",fullName:"Sergey Sedykh"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"9208",title:"Welding",subtitle:"Modern Topics",isOpenForSubmission:!1,hash:"7d6be076ccf3a3f8bd2ca52d86d4506b",slug:"welding-modern-topics",bookSignature:"Sadek Crisóstomo Absi Alfaro, Wojciech Borek and Błażej Tomiczek",coverURL:"https://cdn.intechopen.com/books/images_new/9208.jpg",editors:[{id:"65292",title:"Prof.",name:"Sadek Crisostomo Absi",middleName:"C. Absi",surname:"Alfaro",slug:"sadek-crisostomo-absi-alfaro",fullName:"Sadek Crisostomo Absi Alfaro"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"7831",title:"Sustainability in Urban Planning and Design",subtitle:null,isOpenForSubmission:!1,hash:"c924420492c8c2c9751e178d025f4066",slug:"sustainability-in-urban-planning-and-design",bookSignature:"Amjad Almusaed, Asaad Almssad and Linh Truong - Hong",coverURL:"https://cdn.intechopen.com/books/images_new/7831.jpg",editors:[{id:"110471",title:"Dr.",name:"Amjad",middleName:"Zaki",surname:"Almusaed",slug:"amjad-almusaed",fullName:"Amjad Almusaed"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"9343",title:"Trace Metals in the Environment",subtitle:"New Approaches and Recent Advances",isOpenForSubmission:!1,hash:"ae07e345bc2ce1ebbda9f70c5cd12141",slug:"trace-metals-in-the-environment-new-approaches-and-recent-advances",bookSignature:"Mario Alfonso Murillo-Tovar, Hugo Saldarriaga-Noreña and Agnieszka Saeid",coverURL:"https://cdn.intechopen.com/books/images_new/9343.jpg",editors:[{id:"255959",title:"Dr.",name:"Mario Alfonso",middleName:null,surname:"Murillo-Tovar",slug:"mario-alfonso-murillo-tovar",fullName:"Mario Alfonso Murillo-Tovar"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"9139",title:"Topics in Primary Care Medicine",subtitle:null,isOpenForSubmission:!1,hash:"ea774a4d4c1179da92a782e0ae9cde92",slug:"topics-in-primary-care-medicine",bookSignature:"Thomas F. Heston",coverURL:"https://cdn.intechopen.com/books/images_new/9139.jpg",editors:[{id:"217926",title:"Dr.",name:"Thomas F.",middleName:null,surname:"Heston",slug:"thomas-f.-heston",fullName:"Thomas F. Heston"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}}],latestBooks:[{type:"book",id:"7434",title:"Molecular Biotechnology",subtitle:null,isOpenForSubmission:!1,hash:"eceede809920e1ec7ecadd4691ede2ec",slug:"molecular-biotechnology",bookSignature:"Sergey Sedykh",coverURL:"https://cdn.intechopen.com/books/images_new/7434.jpg",editedByType:"Edited by",editors:[{id:"178316",title:"Ph.D.",name:"Sergey",middleName:null,surname:"Sedykh",slug:"sergey-sedykh",fullName:"Sergey Sedykh"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"8545",title:"Animal Reproduction in Veterinary Medicine",subtitle:null,isOpenForSubmission:!1,hash:"13aaddf5fdbbc78387e77a7da2388bf6",slug:"animal-reproduction-in-veterinary-medicine",bookSignature:"Faruk Aral, Rita Payan-Carreira and Miguel Quaresma",coverURL:"https://cdn.intechopen.com/books/images_new/8545.jpg",editedByType:"Edited by",editors:[{id:"25600",title:"Prof.",name:"Faruk",middleName:null,surname:"Aral",slug:"faruk-aral",fullName:"Faruk Aral"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"9569",title:"Methods in Molecular Medicine",subtitle:null,isOpenForSubmission:!1,hash:"691d3f3c4ac25a8093414e9b270d2843",slug:"methods-in-molecular-medicine",bookSignature:"Yusuf Tutar",coverURL:"https://cdn.intechopen.com/books/images_new/9569.jpg",editedByType:"Edited by",editors:[{id:"158492",title:"Prof.",name:"Yusuf",middleName:null,surname:"Tutar",slug:"yusuf-tutar",fullName:"Yusuf Tutar"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"9839",title:"Outdoor Recreation",subtitle:"Physiological and Psychological Effects on Health",isOpenForSubmission:!1,hash:"5f5a0d64267e32567daffa5b0c6a6972",slug:"outdoor-recreation-physiological-and-psychological-effects-on-health",bookSignature:"Hilde G. Nielsen",coverURL:"https://cdn.intechopen.com/books/images_new/9839.jpg",editedByType:"Edited by",editors:[{id:"158692",title:"Ph.D.",name:"Hilde G.",middleName:null,surname:"Nielsen",slug:"hilde-g.-nielsen",fullName:"Hilde G. Nielsen"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"7802",title:"Modern Slavery and Human Trafficking",subtitle:null,isOpenForSubmission:!1,hash:"587a0b7fb765f31cc98de33c6c07c2e0",slug:"modern-slavery-and-human-trafficking",bookSignature:"Jane Reeves",coverURL:"https://cdn.intechopen.com/books/images_new/7802.jpg",editedByType:"Edited by",editors:[{id:"211328",title:"Prof.",name:"Jane",middleName:null,surname:"Reeves",slug:"jane-reeves",fullName:"Jane Reeves"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"8063",title:"Food Security in Africa",subtitle:null,isOpenForSubmission:!1,hash:"8cbf3d662b104d19db2efc9d59249efc",slug:"food-security-in-africa",bookSignature:"Barakat Mahmoud",coverURL:"https://cdn.intechopen.com/books/images_new/8063.jpg",editedByType:"Edited by",editors:[{id:"92016",title:"Dr.",name:"Barakat",middleName:null,surname:"Mahmoud",slug:"barakat-mahmoud",fullName:"Barakat Mahmoud"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10118",title:"Plant Stress Physiology",subtitle:null,isOpenForSubmission:!1,hash:"c68b09d2d2634fc719ae3b9a64a27839",slug:"plant-stress-physiology",bookSignature:"Akbar Hossain",coverURL:"https://cdn.intechopen.com/books/images_new/10118.jpg",editedByType:"Edited by",editors:[{id:"280755",title:"Dr.",name:"Akbar",middleName:null,surname:"Hossain",slug:"akbar-hossain",fullName:"Akbar Hossain"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"9157",title:"Neurodegenerative Diseases",subtitle:"Molecular Mechanisms and Current Therapeutic Approaches",isOpenForSubmission:!1,hash:"bc8be577966ef88735677d7e1e92ed28",slug:"neurodegenerative-diseases-molecular-mechanisms-and-current-therapeutic-approaches",bookSignature:"Nagehan Ersoy Tunalı",coverURL:"https://cdn.intechopen.com/books/images_new/9157.jpg",editedByType:"Edited by",editors:[{id:"82778",title:"Ph.D.",name:"Nagehan",middleName:null,surname:"Ersoy Tunalı",slug:"nagehan-ersoy-tunali",fullName:"Nagehan Ersoy Tunalı"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"9961",title:"Data Mining",subtitle:"Methods, Applications and Systems",isOpenForSubmission:!1,hash:"ed79fb6364f2caf464079f94a0387146",slug:"data-mining-methods-applications-and-systems",bookSignature:"Derya Birant",coverURL:"https://cdn.intechopen.com/books/images_new/9961.jpg",editedByType:"Edited by",editors:[{id:"15609",title:"Dr.",name:"Derya",middleName:null,surname:"Birant",slug:"derya-birant",fullName:"Derya Birant"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"8686",title:"Direct Torque Control Strategies of Electrical Machines",subtitle:null,isOpenForSubmission:!1,hash:"b6ad22b14db2b8450228545d3d4f6b1a",slug:"direct-torque-control-strategies-of-electrical-machines",bookSignature:"Fatma Ben Salem",coverURL:"https://cdn.intechopen.com/books/images_new/8686.jpg",editedByType:"Edited by",editors:[{id:"295623",title:"Associate Prof.",name:"Fatma",middleName:null,surname:"Ben Salem",slug:"fatma-ben-salem",fullName:"Fatma Ben Salem"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},subject:{topic:{id:"1338",title:"Family Studies",slug:"social-psychology-family-studies",parent:{title:"Social Psychology",slug:"social-psychology"},numberOfBooks:1,numberOfAuthorsAndEditors:31,numberOfWosCitations:3,numberOfCrossrefCitations:7,numberOfDimensionsCitations:18,videoUrl:null,fallbackUrl:null,description:null},booksByTopicFilter:{topicSlug:"social-psychology-family-studies",sort:"-publishedDate",limit:12,offset:0},booksByTopicCollection:[{type:"book",id:"5761",title:"Quality of Life and Quality of Working Life",subtitle:null,isOpenForSubmission:!1,hash:"f6000bc0eeed7fcf0277a2f8d75907d9",slug:"quality-of-life-and-quality-of-working-life",bookSignature:"Ana Alice Vilas Boas",coverURL:"https://cdn.intechopen.com/books/images_new/5761.jpg",editedByType:"Edited by",editors:[{id:"175373",title:"Dr.",name:"Ana Alice",middleName:null,surname:"Vilas Boas",slug:"ana-alice-vilas-boas",fullName:"Ana Alice Vilas Boas"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}],booksByTopicTotal:1,mostCitedChapters:[{id:"55323",doi:"10.5772/intechopen.68873",title:"Positive Psychology: The Use of the Framework of Achievement Bests to Facilitate Personal Flourishing",slug:"positive-psychology-the-use-of-the-framework-of-achievement-bests-to-facilitate-personal-flourishing",totalDownloads:1003,totalCrossrefCites:2,totalDimensionsCites:5,book:{slug:"quality-of-life-and-quality-of-working-life",title:"Quality of Life and Quality of Working Life",fullTitle:"Quality of Life and Quality of Working Life"},signatures:"Huy P. Phan and Bing H. Ngu",authors:[{id:"196435",title:"Prof.",name:"Huy",middleName:"P",surname:"Phan",slug:"huy-phan",fullName:"Huy Phan"}]},{id:"55349",doi:"10.5772/intechopen.68596",title:"The Development of a Human Well-Being Index for the United States",slug:"the-development-of-a-human-well-being-index-for-the-united-states",totalDownloads:1434,totalCrossrefCites:3,totalDimensionsCites:4,book:{slug:"quality-of-life-and-quality-of-working-life",title:"Quality of Life and Quality of Working Life",fullTitle:"Quality of Life and Quality of Working Life"},signatures:"J. Kevin Summers, Lisa M. Smith, Linda C. Harwell and Kyle D. Buck",authors:[{id:"197485",title:"Dr.",name:"J. Kevin",middleName:null,surname:"Summers",slug:"j.-kevin-summers",fullName:"J. Kevin Summers"},{id:"197486",title:"Ms.",name:"Lisa",middleName:null,surname:"Smith",slug:"lisa-smith",fullName:"Lisa Smith"},{id:"197487",title:"Ms.",name:"Linda",middleName:null,surname:"Harwell",slug:"linda-harwell",fullName:"Linda Harwell"},{id:"197488",title:"Dr.",name:"Kyle",middleName:null,surname:"Buck",slug:"kyle-buck",fullName:"Kyle Buck"}]},{id:"56529",doi:"10.5772/intechopen.70237",title:"Well-being and Quality of Working Life of University Professors in Brazil",slug:"well-being-and-quality-of-working-life-of-university-professors-in-brazil",totalDownloads:1147,totalCrossrefCites:0,totalDimensionsCites:3,book:{slug:"quality-of-life-and-quality-of-working-life",title:"Quality of Life and Quality of Working Life",fullTitle:"Quality of Life and Quality of Working Life"},signatures:"Alessandro Vinicius de Paula and Ana Alice Vilas Boas",authors:[{id:"175373",title:"Dr.",name:"Ana Alice",middleName:null,surname:"Vilas Boas",slug:"ana-alice-vilas-boas",fullName:"Ana Alice Vilas Boas"},{id:"196534",title:"Dr.",name:"Alessandro Vinicius",middleName:null,surname:"De Paula",slug:"alessandro-vinicius-de-paula",fullName:"Alessandro Vinicius De Paula"}]}],mostDownloadedChaptersLast30Days:[{id:"55530",title:"Quality of Life and Physical Activity: Their Relationship with Physical and Psychological Well-Being",slug:"quality-of-life-and-physical-activity-their-relationship-with-physical-and-psychological-well-being",totalDownloads:1269,totalCrossrefCites:2,totalDimensionsCites:2,book:{slug:"quality-of-life-and-quality-of-working-life",title:"Quality of Life and Quality of Working Life",fullTitle:"Quality of Life and Quality of Working Life"},signatures:"Arantzazu Rodríguez-Fernández, Ana Zuazagoitia-Rey-Baltar and\nEstibaliz Ramos-Díaz",authors:[{id:"90485",title:"Dr.",name:"Arantzazu",middleName:null,surname:"Rodriguez-Fernández",slug:"arantzazu-rodriguez-fernandez",fullName:"Arantzazu Rodriguez-Fernández"},{id:"205182",title:"Dr.",name:"Ana",middleName:null,surname:"Zuazagoitia-Rey-Baltar",slug:"ana-zuazagoitia-rey-baltar",fullName:"Ana Zuazagoitia-Rey-Baltar"},{id:"205183",title:"Dr.",name:"Estibaliz",middleName:null,surname:"Ramos-Díaz",slug:"estibaliz-ramos-diaz",fullName:"Estibaliz Ramos-Díaz"}]},{id:"55349",title:"The Development of a Human Well-Being Index for the United States",slug:"the-development-of-a-human-well-being-index-for-the-united-states",totalDownloads:1434,totalCrossrefCites:3,totalDimensionsCites:4,book:{slug:"quality-of-life-and-quality-of-working-life",title:"Quality of Life and Quality of Working Life",fullTitle:"Quality of Life and Quality of Working Life"},signatures:"J. Kevin Summers, Lisa M. Smith, Linda C. Harwell and Kyle D. Buck",authors:[{id:"197485",title:"Dr.",name:"J. Kevin",middleName:null,surname:"Summers",slug:"j.-kevin-summers",fullName:"J. Kevin Summers"},{id:"197486",title:"Ms.",name:"Lisa",middleName:null,surname:"Smith",slug:"lisa-smith",fullName:"Lisa Smith"},{id:"197487",title:"Ms.",name:"Linda",middleName:null,surname:"Harwell",slug:"linda-harwell",fullName:"Linda Harwell"},{id:"197488",title:"Dr.",name:"Kyle",middleName:null,surname:"Buck",slug:"kyle-buck",fullName:"Kyle Buck"}]},{id:"55004",title:"Psychological Well-Being of Individuals as Employees and a Paradigm in the Future Economy and Society",slug:"psychological-well-being-of-individuals-as-employees-and-a-paradigm-in-the-future-economy-and-societ",totalDownloads:921,totalCrossrefCites:0,totalDimensionsCites:0,book:{slug:"quality-of-life-and-quality-of-working-life",title:"Quality of Life and Quality of Working Life",fullTitle:"Quality of Life and Quality of Working Life"},signatures:"Simona Šarotar Žižek and Matjaž Mulej",authors:[{id:"192730",title:"Associate Prof.",name:"Simona",middleName:null,surname:"Šarotar Žižek",slug:"simona-sarotar-zizek",fullName:"Simona Šarotar Žižek"},{id:"197979",title:"Dr.",name:"Matjaž",middleName:null,surname:"Mulej",slug:"matjaz-mulej",fullName:"Matjaž Mulej"}]},{id:"54653",title:"Quality of Life, Well-Being and Social Policies in European Countries1",slug:"quality-of-life-well-being-and-social-policies-in-european-countries1",totalDownloads:816,totalCrossrefCites:0,totalDimensionsCites:0,book:{slug:"quality-of-life-and-quality-of-working-life",title:"Quality of Life and Quality of Working Life",fullTitle:"Quality of Life and Quality of Working Life"},signatures:"Ángel Carrasco‐Campos, Almudena Moreno and Luis‐Carlos\nMartínez",authors:[{id:"196212",title:"Prof.",name:"Almudena",middleName:null,surname:"Moreno Minguez",slug:"almudena-moreno-minguez",fullName:"Almudena Moreno Minguez"},{id:"196411",title:"Dr.",name:"Angel",middleName:null,surname:"Carrasco Campos",slug:"angel-carrasco-campos",fullName:"Angel Carrasco Campos"},{id:"196412",title:"Dr.",name:"Luis Carlos",middleName:null,surname:"Martínez Fernández",slug:"luis-carlos-martinez-fernandez",fullName:"Luis Carlos Martínez Fernández"}]},{id:"54570",title:"Exploring the Antecedents of Happiness: Reconceptualization of Human Needs with Glasser's Choice Theory",slug:"exploring-the-antecedents-of-happiness-reconceptualization-of-human-needs-with-glasser-s-choice-theo",totalDownloads:1106,totalCrossrefCites:0,totalDimensionsCites:1,book:{slug:"quality-of-life-and-quality-of-working-life",title:"Quality of Life and Quality of Working Life",fullTitle:"Quality of Life and Quality of Working Life"},signatures:"Turgut Turkdogan",authors:[{id:"197018",title:"Ph.D.",name:"Turgut",middleName:null,surname:"Turkdogan",slug:"turgut-turkdogan",fullName:"Turgut Turkdogan"}]},{id:"54807",title:"Understanding the Concept of Life Quality within the Framework of Social Service Provision: Theoretical Analysis and a Case Study",slug:"understanding-the-concept-of-life-quality-within-the-framework-of-social-service-provision-theoretic",totalDownloads:808,totalCrossrefCites:0,totalDimensionsCites:0,book:{slug:"quality-of-life-and-quality-of-working-life",title:"Quality of Life and Quality of Working Life",fullTitle:"Quality of Life and Quality of Working Life"},signatures:"Zuzana Palovičová",authors:[{id:"196861",title:"Associate Prof.",name:"Zuzana",middleName:null,surname:"Palovicova",slug:"zuzana-palovicova",fullName:"Zuzana Palovicova"}]},{id:"56529",title:"Well-being and Quality of Working Life of University Professors in Brazil",slug:"well-being-and-quality-of-working-life-of-university-professors-in-brazil",totalDownloads:1147,totalCrossrefCites:0,totalDimensionsCites:3,book:{slug:"quality-of-life-and-quality-of-working-life",title:"Quality of Life and Quality of Working Life",fullTitle:"Quality of Life and Quality of Working Life"},signatures:"Alessandro Vinicius de Paula and Ana Alice Vilas Boas",authors:[{id:"175373",title:"Dr.",name:"Ana Alice",middleName:null,surname:"Vilas Boas",slug:"ana-alice-vilas-boas",fullName:"Ana Alice Vilas Boas"},{id:"196534",title:"Dr.",name:"Alessandro Vinicius",middleName:null,surname:"De Paula",slug:"alessandro-vinicius-de-paula",fullName:"Alessandro Vinicius De Paula"}]},{id:"54549",title:"Physical and Psychical Well-Being and Stress: The Perspectives of Leaders and Employees",slug:"physical-and-psychical-well-being-and-stress-the-perspectives-of-leaders-and-employees",totalDownloads:853,totalCrossrefCites:0,totalDimensionsCites:0,book:{slug:"quality-of-life-and-quality-of-working-life",title:"Quality of Life and Quality of Working Life",fullTitle:"Quality of Life and Quality of Working Life"},signatures:"Simona Šarotar Žižek and Vesna Čančer",authors:[{id:"192730",title:"Associate Prof.",name:"Simona",middleName:null,surname:"Šarotar Žižek",slug:"simona-sarotar-zizek",fullName:"Simona Šarotar Žižek"},{id:"197783",title:"Dr.",name:"Vesna",middleName:null,surname:"Čančer",slug:"vesna-cancer",fullName:"Vesna Čančer"}]},{id:"54223",title:"Work-Related Well-Being: From Qualitative Job Insecurity to Cognitive Reappraisal",slug:"work-related-well-being-from-qualitative-job-insecurity-to-cognitive-reappraisal",totalDownloads:702,totalCrossrefCites:0,totalDimensionsCites:0,book:{slug:"quality-of-life-and-quality-of-working-life",title:"Quality of Life and Quality of Working Life",fullTitle:"Quality of Life and Quality of Working Life"},signatures:"Delia Vîrgă",authors:[{id:"196953",title:"Ph.D.",name:"Delia",middleName:null,surname:"Virga",slug:"delia-virga",fullName:"Delia Virga"}]},{id:"54577",title:"Building a Quality of Life Index",slug:"building-a-quality-of-life-index",totalDownloads:1093,totalCrossrefCites:0,totalDimensionsCites:2,book:{slug:"quality-of-life-and-quality-of-working-life",title:"Quality of Life and Quality of Working Life",fullTitle:"Quality of Life and Quality of Working Life"},signatures:"Ryan M. Yonk, Josh T. Smith and Arthur R. Wardle",authors:[{id:"196259",title:"Dr.",name:"Ryan Merlin",middleName:null,surname:"Yonk",slug:"ryan-merlin-yonk",fullName:"Ryan Merlin Yonk"},{id:"197814",title:"Mr.",name:"Joshua",middleName:null,surname:"Smith",slug:"joshua-smith",fullName:"Joshua Smith"}]}],onlineFirstChaptersFilter:{topicSlug:"social-psychology-family-studies",limit:3,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[{type:"book",id:"10176",title:"Microgrids and Local Energy Systems",subtitle:null,isOpenForSubmission:!0,hash:"c32b4a5351a88f263074b0d0ca813a9c",slug:null,bookSignature:"Prof. Nick Jenkins",coverURL:"https://cdn.intechopen.com/books/images_new/10176.jpg",editedByType:null,editors:[{id:"55219",title:"Prof.",name:"Nick",middleName:null,surname:"Jenkins",slug:"nick-jenkins",fullName:"Nick Jenkins"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}}],offset:8,limit:8,total:1},route:{name:"profile.detail",path:"/profiles/134882/florin-constantinescu",hash:"",query:{},params:{id:"134882",slug:"florin-constantinescu"},fullPath:"/profiles/134882/florin-constantinescu",meta:{},from:{name:null,path:"/",hash:"",query:{},params:{},fullPath:"/",meta:{}}}},function(){var e;(e=document.currentScript||document.scripts[document.scripts.length-1]).parentNode.removeChild(e)}()