Titlebook: Artificial Intelligence and Industrial Applications; Algorithms, Techniqu Tawfik Masrour,Hassan Ramchoun,Mohamed Hosni Conference proceedin

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The Impact of Systolic Blood Pressure Level and Comparative Study for Predicting Cardiovascular Dis-field where Data Mining has contributed to automate the diagnosis and sometimes may be applied in the treatment stage of the disease. This paper aims to define the efficient classifier medical decision support system compared to four classification algorithms (K-Nearest Neighbors, Support Vector Ma

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A Multi-Agent System for the Optimization of Medical Waste Management,sis, as Medical Waste (MW) can be a vector of virus transmission if the process is not properly controlled. This fact calls into question the current models of MWM, especially in developing countries where in the majority of cases the MWM is operated in a hazardous manner, representing a real danger

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,A Relaxed Variant of Distributed Q-Learning Algorithm for Cooperative Matrix Games, the presence of the stochasticity problem due to the over-estimation of action values. In this article, we present a new relaxation of the Distributed Q-learning by introducing a new update rule for the Q-function of each agent. We discuss the existing literature, then compare our algorithm with di

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Remote Sensing Image Super-Resolution Using Deep Convolutional Neural Networks and Autoencoder,lationship between low-resolution images and high-resolution ones. This paper explores deep convolutional auto-encoder-based super-resolution, which includes one auto-encoder unit with several convolutional blocks in both the encoding and the decoding sub-units. In this study, we used RGB slices com

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Part of Speech Tagging of Amazigh Language as a Very Low-Resourced Language: Particularities and ChOS tagging is a crucial step before every natural language processing application (syn tactic analysis, machine translation, autocorrection….) because the performance of each application depends, inter alia, on the performance of the used POS tagging. Thus, in order to realize an efficient POS tagge

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,Learning Sparse Fully Connected Layers in Convolutional Neural Networks,rameters, which restricts their utilization in platform-limited devices. Searching for an appropriate and simple convolutional neural network architecture with an optimal number of parameters is still a challenging problem. In fact, in many well-known convolutional neural networks like LeNet, AlexNe