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The aim of this book was to collect the most recent methods developed for NSO and its practical applications. The book contains seven papers: The first is the foreword by the Guest Editors giving a brief review of NSO and its real-life applications and acknowledging the outstanding contributions of Professor Adil Bagirov to both the theoretical and practical aspects of NSO. The second paper introduces a new and very efficient algorithm for solving uncertain unit-commitment (UC) problems. The third paper proposes a new nonsmooth version of the generalized damped Gauss–Newton method for solving nonlinear complementarity problems. In the fourth paper, the abs-linear representation of piecewise linear functions is extended to yield simultaneously their DC decomposition as well as the pair of generalized gradients. The fifth paper presents the use of biased-randomized algorithms as an effective methodology to cope with NP-hard and nonsmooth optimization problems in many practical applications. In the sixth paper, a problem concerning the scheduling of nuclear waste disposal is modeled as a nonsmooth multiobjective mixed-integer nonlinear optimization problem, and a novel method using the two-slope parameterized achievement scalarizing functions is introduced. Finally, the last paper considers binary classification of a multiple instance learning problem and formulates the learning problem as a nonconvex nonsmooth unconstrained optimization problem with a DC objective function.

Information technology industries --- multiple instance learning --- support vector machine --- DC optimization --- nonsmooth optimization --- achievement scalarizing functions --- interactive method --- multiobjective optimization --- spent nuclear fuel disposal --- non-smooth optimization --- biased-randomized algorithms --- heuristics --- soft constraints --- DC function --- abs-linearization --- DCA --- Gauss-Newton method --- nonsmooth equations --- nonlinear complementarity problem --- B-differential --- superlinear convergence --- global convergence --- stochastic programming --- stochastic hydrothermal UC problem --- parallel computing --- asynchronous computing --- level decomposition

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The aim of this book was to collect the most recent methods developed for NSO and its practical applications. The book contains seven papers: The first is the foreword by the Guest Editors giving a brief review of NSO and its real-life applications and acknowledging the outstanding contributions of Professor Adil Bagirov to both the theoretical and practical aspects of NSO. The second paper introduces a new and very efficient algorithm for solving uncertain unit-commitment (UC) problems. The third paper proposes a new nonsmooth version of the generalized damped Gauss–Newton method for solving nonlinear complementarity problems. In the fourth paper, the abs-linear representation of piecewise linear functions is extended to yield simultaneously their DC decomposition as well as the pair of generalized gradients. The fifth paper presents the use of biased-randomized algorithms as an effective methodology to cope with NP-hard and nonsmooth optimization problems in many practical applications. In the sixth paper, a problem concerning the scheduling of nuclear waste disposal is modeled as a nonsmooth multiobjective mixed-integer nonlinear optimization problem, and a novel method using the two-slope parameterized achievement scalarizing functions is introduced. Finally, the last paper considers binary classification of a multiple instance learning problem and formulates the learning problem as a nonconvex nonsmooth unconstrained optimization problem with a DC objective function.

multiple instance learning --- support vector machine --- DC optimization --- nonsmooth optimization --- achievement scalarizing functions --- interactive method --- multiobjective optimization --- spent nuclear fuel disposal --- non-smooth optimization --- biased-randomized algorithms --- heuristics --- soft constraints --- DC function --- abs-linearization --- DCA --- Gauss–Newton method --- nonsmooth equations --- nonlinear complementarity problem --- B-differential --- superlinear convergence --- global convergence --- stochastic programming --- stochastic hydrothermal UC problem --- parallel computing --- asynchronous computing --- level decomposition --- n/a --- Gauss-Newton method

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The accelerating power of deep learning in diagnosing diseases will empower physicians and speed up decision making in clinical environments. Applications of modern medical instruments and digitalization of medical care have generated enormous amounts of medical images in recent years. In this big data arena, new deep learning methods and computational models for efficient data processing, analysis, and modeling of the generated data are crucially important for clinical applications and understanding the underlying biological process. This book presents and highlights novel algorithms, architectures, techniques, and applications of deep learning for medical image analysis.

interpretable/explainable machine learning --- image classification --- image processing --- machine learning models --- white box --- black box --- cancer prediction --- deep learning --- multimodal learning --- convolutional neural networks --- autism --- fMRI --- texture analysis --- melanoma --- glcm matrix --- machine learning --- classifiers --- explainability --- explainable AI --- XAI --- medical imaging --- diagnosis --- ARMD --- change detection --- unsupervised learning --- microwave breast imaging --- image reconstruction --- tumor detection --- digital pathology --- whole slide image processing --- multiple instance learning --- deep learning classification --- HER2 --- medical images --- transfer learning --- optimizers --- neo-adjuvant treatment --- tumour cellularity --- cancer --- breast cancer --- diagnostics --- imaging --- computation --- artificial intelligence --- 3D segmentation --- active surface --- discriminant analysis --- PET imaging --- medical image analysis --- brain tumor --- cervical cancer --- colon cancer --- lung cancer --- computer vision --- musculoskeletal images --- lung disease detection --- taxonomy --- convolutional neural network --- CycleGAN --- data augmentation --- dermoscopic images --- domain transfer --- macroscopic images --- skin lesion segmentation --- infection detection --- COVID-19 --- X-ray images --- bayesian inference --- shifted-scaled dirichlet distribution --- MCMC --- gibbs sampling --- object detection --- surgical tools --- open surgery --- egocentric camera --- computers in medicine --- segmentation --- MRI --- ECG signal detection --- portable monitoring devices --- 1D-convolutional neural network --- medical image segmentation --- domain adaptation --- meta-learning --- U-Net --- computed tomography (CT) --- magnetic resonance imaging (MRI) --- low-dose --- sparse-angle --- quantitative comparison --- n/a

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This book contains 37 papers by 73 renowned experts from 13 countries around the world, on following topics: neutrosophic set; neutrosophic rings; neutrosophic quadruple rings; idempotents; neutrosophic extended triplet group; hypergroup; semihypergroup; neutrosophic extended triplet group; neutrosophic extended triplet semihypergroup and hypergroup; neutrosophic offset; uninorm; neutrosophic offuninorm and offnorm; neutrosophic offconorm; implicator; prospector; n-person cooperative game; ordinary single-valued neutrosophic (co)topology; ordinary single-valued neutrosophic subspace; ?-level; ordinary single-valued neutrosophic neighborhood system; ordinary single-valued neutrosophic base and subbase; fuzzy numbers; neutrosophic numbers; neutrosophic symmetric scenarios; performance indicators; financial assets; neutrosophic extended triplet group; neutrosophic quadruple numbers; refined neutrosophic numbers; refined neutrosophic quadruple numbers; multigranulation neutrosophic rough set; nondual; two universes; multiattribute group decision making; nonstandard analysis; extended nonstandard analysis; monad; binad; left monad closed to the right; right monad closed to the left; pierced binad; unpierced binad; nonstandard neutrosophic mobinad set; neutrosophic topology; nonstandard neutrosophic topology; visual tracking; neutrosophic weight; objectness; weighted multiple instance learning; neutrosophic triangular norms; residuated lattices; representable neutrosophic t-norms; De Morgan neutrosophic triples; neutrosophic residual implications; infinitely ?-distributive; probabilistic neutrosophic hesitant fuzzy set; decision-making; Choquet integral; e-marketing; Internet of Things; neutrosophic set; multicriteria decision making techniques; uncertainty modeling; neutrosophic goal programming approach; shale gas water management system.

nonstandard neutrosophic supremum --- classical statistics --- complex neutrosophic set --- neutrosophic offnorm --- neutrosophic extended triplet group --- multi-attribute decision-making (MADM) --- neutrosophic time series --- refined neutrosophic quadruple numbers --- BNHHA aggregation operator --- neutrosophic offconorm --- monad --- matrix representation --- left monad closed to the right --- implicator --- neutrsophic set --- neutrosophic correlation --- neutrosophic cubic sets --- decision-making --- MoBiNad set --- open and closed monads to the left/right --- distance measure --- De Morgan neutrosophic triples --- group decision making --- financial assets --- soft expert set --- uninorm --- multi-attribute group decision making --- sampling plan --- cubic sets --- neutrosophic cubic ordered weighted geometric operator (NCOWG) --- shale gas water management system --- weighted average operator --- aggregation operations --- quality function deployment --- Einstein t-norm --- neutrosophic rings --- non-standard neutrosophic topology --- BNHWA aggregation operator --- hypergroup --- triangular neutrosophic cubic fuzzy number --- pierced and unpierced binads --- numerical application --- neutrosophic cubic weighted geometric operator (NCWG) --- relations --- extended nonstandard analysis --- arithmetic averaging operator --- nonstandard reals --- Choquet integral --- Function approximation --- neutrosophic triangular norms --- weighted geometric operator --- neutrosophic regression --- optimization solution --- ordinary single valued neutrosophic neighborhood system --- smart port --- neutrosophic topology --- multi-criteria decision making techniques --- low-carbon supplier selection --- producer’s risk --- quasi-completely regular semigroup --- score function --- MAGDM --- multicriteria decision-making --- neutrosophic soft rough --- NET-hypergroup --- refined neutrosophic numbers --- neutrosophic logical relationship groups --- combined weighted average --- TOPSIS --- neutrosophic logical relationship --- logarithmic aggregation operators --- non-standard analysis --- multi-attribute decision-making --- neutrosophic extended triplet semihypergroup (NET-semihypergroup) --- aggregation --- nonstandard neutrosophic logic --- symmetric relation --- uncertainty modeling --- single valued neutrosophic sets --- BNHOWA aggregation operator --- ordinary single valued neutrosophic subspace --- generalized neutrosophic extended triplet group --- multi-attribute decision making --- ordinary single valued neutrosophic base --- nonstandard arithmetic operations --- pierced binad --- MCGDM problems --- simplified neutrosophic set --- residuated lattices --- Neutrosophic compound orthogonal neural network --- rough set approximation --- single-valued neutrosophic linguistic set --- binad --- multi-granulation neutrosophic rough set --- single valued neutrosophic set --- infinitesimals --- standard reals --- soft set --- non-standard neutrosophic mobinad set --- certainty function --- neutrosophic weight --- two universes --- sample size --- n-person cooperative game --- paper defect diagnosis --- performance indicators --- semihypergroup --- logarithmic operational laws --- right monad closed to the left --- idempotents --- unpierced binad --- neutrosophic cubic hybrid weighted arithmetic and geometric aggregation operator (NCHWAGA) --- neutrosophic symmetric scenarios --- extended nonstandard neutrosophic logic --- neutrosophic statistics --- neutrosophic goal programming approach --- neutrosophic offset --- neutrosophic statistical interval method --- weighted multiple instance learning --- neutrosophic cubic Einstein ordered weighted geometric operator (NCEOWG) --- fuzzy parameterized single valued neutrosophic soft expert set --- single-valued neutrosophic soft number and its operations --- Internet of Things --- extended non-standard analysis --- dietary fat level --- soft sets --- visual tracking --- neutrosophic offuninorm --- neutrosophic cubic Einstein weighted geometric operator (NCEWG) --- ordinary single valued neutrosophic subbase --- membership function --- non-dual --- SVN soft weighted arithmetic averaging operator --- Q-neutrosophic set --- neutrosophic sets --- fuzzy numbers --- intuitionistic fuzzy parameters --- producer’s risk’ --- graph representation --- exponential similarity measure --- infinities --- maximizing deviation --- Multi-attribute decision making --- SVN soft weighted geometric averaging operator --- objectness --- Q-neutrosophic soft set --- accuracy function --- consumer’s risk --- decision making --- Neutrosophic number --- clifford semigroup --- neutrosophic numbers --- neutrosophic residual implications --- nonstandard neutrosophic lattices of first type (as poset) and second type (as algebraic structure) --- covering --- e-marketing --- nonstandard analysis --- neutrosophic quadruple rings --- complex neutrosophic soft expert set --- single-valued neutrosophic set --- neutrosophic cubic soft expert system --- neutrosophic cubic soft sets --- triangular neutrosophic number --- supply chain sustainability metrics --- neutrosophic quadruple numbers --- ?-level --- nonstandard neutrosophic infimum --- infinitely ?-distributive --- plithogeny --- neutrosophic set --- fuzzy logic --- prospector --- Neutrosophic function --- representable neutrosophic t-norms --- probabilistic neutrosophic hesitant fuzzy set (PNHFS) --- prostate cancer --- nonstandard unit interval --- port evaluation --- simplified neutrosophic hesitant fuzzy set --- ordinary single valued neutrosophic (co)topology