Titlebook: Repetitive and Restricted Behaviors and Interests in Autism Spectrum Disorders; From Neurobiology to Eynat Gal,Nurit Yirmiya Book 2021 Spri

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Esther Dromi,Alona Oren,Aviva Mimouni-Blocht future movement. Machine learning techniques can detect paradigms and insights that can be used to construct surprisingly correct predictions. We propose the long short-term memory (LSTM) model to examine the future price of a stock. This paper is to predict stock market prices to make more acquai

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Parisa Ghanouni,Tal Jarusas filler in conjunction with randomly dispersed short coir fibre reinforced HDPE composites along with 5 wt% MAPE as compatibilizer. It is observed the properties such as flexural strength and mechanical rigidity (tensile and flexural) of the lime sludge infused composites improved with filler addi

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Ayelet Ben-Sasson,Kevin Stephensong in nature; there is no single condition of machining parameters, which gives the best machining quality. Multi-objective particle swarm optimization technique was used to find the best optimal condition of MWCNT mixed-EDM parameters to minimize the SR and maximize the MRR. The best global solution

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Roni Enten-Vissokerstrated. The microstructure–mechanical properties are correlated to understand the operative densification and strengthening mechanism. Heterogeneous composition and bimodal grain size distribution of the alloy offers appreciable strength–ductility for structural applications. The chapter will provi

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Eynat Gal,Ayelet Ben-Sassonure and activation functions on the prediction. The predicted ANN data were further used to develop revised RSM model. The later prediction model and the respective optimization resulted the best cutting parameters for achieving the minimum .. The predicted surface roughness from GA is . for the opt

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