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Cluster analysis --- Mathematical statistics --- Statistics --- R (Computer program language)

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"Wireless networking covers a variety of topics involving many challenges. The main concern of clustering approaches for mobile wireless sensor networks (WSNs) is to prolong the battery life of the individual sensors and the network lifetime. For a successful clustering approach, the need of a powerful mechanism to safely elect a cluster head remains a challenging task in many research works that take into account the mobility of the network. In Mobile, Wireless and Sensor Networks: A Clustering Algorithm for Energy Efficiency and Safety, the authors use an approach based on computing of the weight of each node in the network as the proposed technique to deal with this problem. They present a virtual laboratory platform (VLP) of baptized mercury, allowing students and researchers to make practical work (PW) on different aspects of mobile wireless sensor networks. The authors' choice of WSNs is motivated mainly by the use of real experiments needed in most college courses on WSNs. These usual experiments, however, require an expensive investment and many nodes in the classroom. The platform presented here aims to show the feasibility, the flexibility, and the reduced cost using the authors' approach. The authors demonstrate the performance of the proposed algorithms that contribute to the familiarization of the learners in the field of WSNs₍"--

Wireless communication systems. --- Mobile computing. --- Cluster analysis. --- Computer algorithms. --- Cooperating objects (Computer systems)

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This book puts forward a new method for solving the text document (TD) clustering problem, which is established in two main stages: (i) A new feature selection method based on a particle swarm optimization algorithm with a novel weighting scheme is proposed, as well as a detailed dimension reduction technique, in order to obtain a new subset of more informative features with low-dimensional space. This new subset is subsequently used to improve the performance of the text clustering (TC) algorithm and reduce its computation time. The k-mean clustering algorithm is used to evaluate the effectiveness of the obtained subsets. (ii) Four krill herd algorithms (KHAs), namely, the (a) basic KHA, (b) modified KHA, (c) hybrid KHA, and (d) multi-objective hybrid KHA, are proposed to solve the TC problem; each algorithm represents an incremental improvement on its predecessor. For the evaluation process, seven benchmark text datasets are used with different characterizations and complexities. Text document (TD) clustering is a new trend in text mining in which the TDs are separated into several coherent clusters, where all documents in the same cluster are similar. The findings presented here confirm that the proposed methods and algorithms delivered the best results in comparison with other, similar methods to be found in the literature.

Engineering. --- Artificial intelligence. --- Computational Intelligence. --- Artificial Intelligence. --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Construction --- Industrial arts --- Technology --- Document clustering. --- Clustering, Document --- Cluster analysis --- File organization (Computer science) --- Computational intelligence. --- Intelligence, Computational --- Artificial intelligence --- Soft computing

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The present Special Issue, “Innovative Extraction Techniques and Hyphenated Instrument Configuration for Complex Matrices Analysis”, aims to collect and to disseminate some of the most significant and recent contributions in the interdisciplinary area of innovative extraction procedures from complex matrices followed by validated analytical methods using hyphenated instrument configurations to support the optimization of the whole process and the scale-up possibility

alginate --- n/a --- heavy metals --- high-speed counter-current chromatography (HSCCC) --- microwave processing --- phytochemicals --- microNIR --- antioxidant activity --- in-line monitoring --- Wuyi Rock tea --- metabolomics --- seawater --- optimization --- walnut septum --- color analysis --- metabolite profiling --- rosuvastatin --- dispersive liquid-liquid microextraction --- antioxidant --- mouse melanoma B16 cells --- nails --- extraction --- sample preparation --- quality --- MAE --- Panax notoginseng --- physicochemical properties --- flow injection --- ionic liquids --- branched-chain keto acids --- Semen Cuscutae --- near-infrared spectroscopy --- volatile organic compounds --- odor --- SFE --- single-drop microextraction --- experimental design --- cluster analysis --- therapeutic drug monitoring --- Thymus algeriensis --- metformin --- tyrosinase --- gas chromatography-olfactometry --- Ajuga genevensis --- phytosterols --- serum --- diabetes --- GHB --- polyphenols --- ultrasound assisted extraction --- microextraction --- oolong tea --- alkaloid --- minor ginsenosides --- inductively coupled plasma-mass spectrometry --- wood --- stir bar sorptive extraction --- HPLC-Q-TOF/MS --- GHB glucuronide --- Hericium erinaceuns mycelium --- endogenous values --- cultivars --- Tieguanyin tea cultivar --- SIRT1 --- modification --- HPLC-MS/MS --- fluid bed process --- steamed Panax notoginseng --- dry extract --- UPLC-QTOF MS --- flavonoids --- blood-enriching activity --- UPLC-QqQ MS --- HPLC-PDA --- neurodegenerative disease --- biological activity --- rare earth elements --- response surface methodology --- solid-phase microextraction --- Ultra-Turrax extraction --- bovine hide --- ultra-high-performance liquid chromatography tandem mass spectrometry --- gel strength --- hematopoiesis --- genistein --- muscle --- Lycium ruthenicun --- hemostatic activity --- flavonoid --- ultra-high-performance liquid chromatography coupled to electrospray ionization mass spectrometry --- HILIC --- surfactant --- saponins --- pigments --- chlorogenic acids --- daidzein --- Fe3O4 --- LC-MS --- Asphodeline lutea --- actinidin --- total polyphenolic content --- stir cake sorptive extraction --- gelatin --- ruthenicunoid A

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Photovoltaic solar energy technology (PV) has been developing rapidly in the past decades, leading to a multi-billion-dollar global market. It is of paramount importance that PV systems function properly, which requires the generation of expected energy both for small-scale systems that consist of a few solar modules and for very large-scale systems containing millions of modules. This book increases the understanding of the issues relevant to PV system design and correlated performance; moreover, it contains research from scholars across the globe in the fields of data analysis and data mapping for the optimal performance of PV systems, faults analysis, various causes for energy loss, and design and integration issues. The chapters in this book demonstrate the importance of designing and properly monitoring photovoltaic systems in the field in order to ensure continued good performance.

fault diagnosis --- modeling --- simulation --- fault tree analysis --- photovoltaic system --- Bartlett’s test --- metaheuristic --- population density --- spatial analyses --- AC parameters --- parameter estimation --- fiber reinforced polymeric plastic (FRP) --- Hartigan’s dip test --- energy --- image processing --- real data --- photovoltaic (PV) systems monitoring --- forecast --- photovoltaic plants --- system --- graphical malfunction detection --- defects --- STATCOM --- photo-generated current --- performance analysis --- photovoltaic module performance --- solar energy --- urban context --- thermal interaction --- underdamped oscillation --- reliability --- membership algorithm --- photovoltaic systems --- availability --- fuzzy logic controller --- ANOVA --- solar farm --- energy yield --- cluster analysis --- photovoltaics --- annual yield --- residential buildings --- PV array --- PV system --- dc-dc converter --- quasi-opposition based learning --- grid-connected --- performance ratio --- organic soiling --- vegetated/green roof --- conventional roof membrane --- UV-fluorescence imaging --- PV thermal performance --- PV systems --- failure mode and effect analysis --- ageing and degradation of PV-modules --- sheet molding compound FRP --- Jarque-Bera’s test --- Tukey’s test --- technical costs --- Kruskal-Wallis’ test --- improved cuckoo search algorithm --- PV energy performance --- pultruded FRP --- cracks --- maximum power point tracking (MPPT) --- structural design --- software development --- floating PV generation structure --- malfunction detection --- modules --- photovoltaic performance --- maximum power point --- GIS --- impedance spectroscopy --- floating PV systems (FPV) --- solar cells --- Renewable Energy --- loss analysis --- shade resilience --- Scanning Electron Microscopy (SEM) --- failure detection --- optimization problem --- failure rates --- FCM algorithm --- stability analysis --- reactive power support --- mooring system --- buck converter --- Mood’s Median test --- photovoltaic modeling --- module architecture --- PV module --- data analysis --- partial shading --- opposition-based learning --- silicon --- floating PV module (FPVM) --- electroluminescence --- urban compactness