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Ahmed Latif Yaser, Hamdy M. Mousa and Mahmoud Hussein
Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network?s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solut...
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Yen-Cheng Chu, Yun-Jie Jhang, Tsung-Ming Tai and Wen-Jyi Hwang
The objective of this study is to present novel neural network (NN) algorithms and systems for sensor-based hand gesture recognition. The algorithms are able to classify accurately a sequence of hand gestures from the sensory data produced by acceleromet...
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Mohammad Asad Tariq, Vasanthi Sethu, Senthilkumar Arumugasamy, Anurita Selvarajoo
Pág. 1 - 14
In the present research, local rambutan seed extract was used as a bio-coagulant for the treatment of palm oil mill effluent (POME). Jar test experiments were conducted to find the optimal operating conditions for the removal of turbidity and total suspe...
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Dragos Paul Mihai, Cosmin Trif, Gheorghe Stancov, Denise Radulescu and George Mihai Nitulescu
Transient receptor potential ankyrin 1 (TRPA1) is a ligand-gated calcium channel activated by cold temperatures and by a plethora of electrophilic environmental irritants (allicin, acrolein, mustard-oil) and endogenously oxidized lipids (15-deoxy-?12, 14...
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Salaheddin Hosseinzadeh, Mahmood Almoathen, Hadi Larijani and Krystyna Curtis
Among the many technologies competing for the Internet of Things (IoT), one of the most promising and fast-growing technologies in this landscape is the Low-Power Wide-Area Network (LPWAN). Coverage of LoRa, one of the main IoT LPWAN technologies, has pr...
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Salaheddin Hosseinzadeh, Mahmood Almoathen, Hadi Larijani and Krystyna Curtis
Among the many technologies competing for the Internet of Things (IoT), one of the most promising and fast-growing technologies in this landscape is the Low-Power Wide-Area Network (LPWAN). Coverage of LoRa, one of the main IoT LPWAN technologies, has pr...
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Angel E. Muñoz-Zavala, Jorge E. Macías-Díaz, Daniel Alba-Cuéllar and José A. Guerrero-Díaz-de-León
This paper reviews the application of artificial neural network (ANN) models to time series prediction tasks. We begin by briefly introducing some basic concepts and terms related to time series analysis, and by outlining some of the most popular ANN arc...
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Tameem Adel and Mark Levene
We investigate the utility of side information in the context of machine learning and, in particular, in supervised neural networks. Side information can be viewed as expert knowledge, additional to the input, that may come from a knowledge base. Unlike ...
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Zahra Alizadeh, Jafar Yazdi, Joong Hoon Kim and Abobakr Khalil Al-Shamiri
Monthly flow predictions provide an essential basis for efficient decision-making regarding water resource allocation. In this paper, the performance of different popular data-driven models for monthly flow prediction is assessed to detect the appropriat...
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Alessandra Caggiano, Giulio Mattera and Luigi Nele
The drilling of carbon fiber-reinforced plastic (CFRP) materials is a key process in the aerospace industry, where ensuring high product quality is a critical issue. Low-quality of final products may be caused by the occurrence of drilling-induced defect...
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Anna Bakurova, Olesia Yuskiv, Dima Shyrokorad, Anton Riabenko, Elina Tereschenko
Pág. 14 - 22
The subject of the research is the methods of constructing and training neural networks as a nonlinear modeling apparatus for solving the problem of predicting the energy consumption of metallurgical enterprises. The purpose of this work is to develop a ...
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Marco A. Martínez Ramírez, Emmanouil Benetos and Joshua D. Reiss
Virtual analog modeling of audio effects consists of emulating the sound of an audio processor reference device. This digital simulation is normally done by designing mathematical models of these systems. It is often difficult because it seeks to accurat...
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Waqas Saleem, Muhammad Zain-ul-abdein, Hassan Ijaz, Abdullah Salmeen Bin Mahfouz, Anas Ahmed, Muhammad Asad and Tarek Mabrouki
In dry turning operation, various parameters influence the cutting force and contribute in machining precision. Generally, the numerical cutting models are adopted to establish the optimum cutting parameters and results are substantiated with the experim...
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Tushar Ganguli and Edwin K. P. Chong
We present a novel technique for pruning called activation-based pruning to effectively prune fully connected feedforward neural networks for multi-object classification. Our technique is based on the number of times each neuron is activated during model...
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Soha Abd El-Moamen Mohamed, Marghany Hassan Mohamed and Mohammed F. Farghally
In this paper, a proposed algorithm that dynamically changes the neural network structure is presented. The structure is changed based on some features in the cascade correlation algorithm. Cascade correlation is an important algorithm that is used to so...
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Yu-Hung Chang, Chien-Hung Liu and Shingchern D. You
The dynamic flexible job-shop problem (DFJSP) is a realistic and challenging problem that many production plants face. As the product line becomes more complex, the machines may suddenly break down or resume service, so we need a dynamic scheduling frame...
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Juan M. Lujano-Rojas, Rodolfo Dufo-López, Jesús Sergio Artal-Sevil and Eduardo García-Paricio
Assessing the training process of artificial neural networks (ANNs) is vital for enhancing their performance and broadening their applicability. This paper employs the Monte Carlo simulation (MCS) technique, integrated with a stopping criterion, to const...
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Quan Sun, Xuhui Pan, Xiao Ling, Bo Wang, Qinghong Sheng, Jun Li, Zhijun Yan, Ke Yu and Jiasong Wang
In the realm of non-cooperative space security and on-orbit service, a significant challenge is accurately determining the pose of abandoned satellites using imaging sensors. Traditional methods for estimating the position of the target encounter problem...
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Yaju Rajbhandari, Anup Marahatta, Bishal Ghimire, Ashish Shrestha, Anand Gachhadar, Anup Thapa, Kamal Chapagain and Petr Korba
Short-term electricity demand forecasting is one of the best ways to understand the changing characteristics of demand that helps to make important decisions regarding load flow analysis, preventing imbalance in generation planning, demand management, an...
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Jeng-Fung Chen, Ho-Nien Hsieh and Quang Hung Do
The accuracy of reservoir flow forecasting has the most significant influence on the assurance of stability and annual operations of hydro-constructions. For instance, accurate forecasting on the ebb and flow of Vietnam?s Hoabinh Reservoir can aid in the...
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