Joint Beamforming Design and Power Minimization for Friendly Jamming Relaying Hybrid RF/VLC Systems by Jaber Al-Khori, Galymzhan Nauryzbayev, Mohamed M. Abdallah, Mounir Hamdi

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Solution Methods for the Multiple-Choice Knapsack Problem and Their Applications by Tibor Szkaliczki

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Design and Assessment of an Austenitic Stainless Alloy for Laser Powder Bed Additive Manufacturing by Mariam Assi, Julien Favre, Marcin Brykala, Franck Tancret, Anna Fraczkiewicz

“…A computational approach is proposed to design novel and optimized austenitic alloy compositions. …”
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Deep learning-based semantic segmentation with novel navigation line extraction for autonomous agricultural robots by Chijioke Leonard Nkwocha, Ning Wang

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Implementation of Visual Odometry on Jetson Nano by Jakub Krško, Dušan Nemec, Vojtech Šimák, Mário Michálik

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An Innovative Smart Irrigation Using Embedded and Regression-Based Machine Learning Technologies for Improving Water Security and Sustainability by Abdennabi Morchid, Abdennacer Elbasri, Zahra Oughannou, Hassan Qjidaa, Rachid El Alami, Badre Bossoufi, Saleh Mobayen, Pawel Skruch

“…This study proposes an irrigation system based on embedded systems, using sensors and algorithms to collect and analyze data in order to optimize water management. …”
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CMDMamba: dual-layer Mamba architecture with dual convolutional feed-forward networks for efficient financial time series forecasting by Zhenkai Qin, Zhenkai Qin, Zhenkai Qin, Baozhong Wei, Baozhong Wei, Yujia Zhai, Ziqian Lin, Xiaochuan Yu, Xiaochuan Yu, Jingxuan Jiang

“…By doing so, it provides more accurate time series modeling, optimizes algorithmic trading strategies, and facilitates investment portfolio risk warnings.ResultsExperiments conducted on four real-world financial datasets demonstrate that CMDMamba achieves a 10.4% improvement in prediction accuracy for multivariate forecasting tasks compared to state-of-the-art models.DiscussionMoreover, CMDMamba excels in both predictive accuracy and computational efficiency, setting a new benchmark in the field of financial time series forecasting.…”
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Comparison metrics and power trade-offs for BCI motor decoding circuit design by Joe Saad, Adrian Evans, Ilan Jaoui, Victor Roux-Sibillon, Emmanuel Hardy, Lorena Anghel

“…To better understand how to minimize this power consumption, we review the optimizations used in state-of-the-art decoding circuits.…”
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Bayesian network structure learning by opposition-based learning by Baodan Sun, Xinyi Zhang, Junhui Jiang, Jianguang Gong, Dan Lin

“…In this paper, we propose a new Bayesian network structure learning algorithm, OP-PSO-DE, which combines Particle Swarm Optimization(PSO) and Differential Evolution to search for the optimal structure. …”
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Updating parameters of an information model for road construction flow in work development project by T. V. Bobrova

“…A modelling algorithm has been developed for creating an updated structure of a specialized linear flow in an integrated computer environment, which provides visualization of a construction site, control and operational management of work in a shared data environment. …”
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YOLO-RDM: Innovative Detection Methods for Eggplants and Stems in Complex Natural Environment by Qin Liu, Zhibin Zhou, Lu Xiong, Meilian Lu, Jingwen Ouyang

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Intelligent System for Student Performance Prediction Using Machine Learning by Mustafa S. Ibrahim Alsumaidaie, Ahmed Adil Nafea, Abdulrahman Abbas Mukhlif, Ruqaiya D. Jalal, Mohammed M AL-Ani

“…All algorithms demonstrated high precision and recall. Notably, K-Nearest Neighbors exhibited exceptional computational efficiency with a training time of 0.00 seconds. …”
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Protecting digital assets using an ontology based cyber situational awareness system by Tariq Ammar Almoabady, Yasser Mohammad Alblawi, Ahmad Emad Albalawi, Majed M. Aborokbah, S. Manimurugan, Ahmed Aljuhani, Hussain Aldawood, P. Karthikeyan

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Automatic Synthesis of Recurrent Neurons for Imitation Learning From CNC Machine Operators by Hoa Thi Nguyen, Roland Olsson, Oystein Haugen

“…Analyzing time series data in industrial settings demands domain knowledge and computer science expertise to develop effective algorithms. …”
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Importance Sampling and Feature Fusion Paradigm-Boosted Multi-Modal Convolutional Neural Networks: Deployment in Composite Curing Process Monitored by Electro-Mechanical Impedance by Xin Zhao, Zeyuan Gao, Meng Li, Zhibin Han, Jianjian Zhu

“…However, training CNNs on multi-modal EMI signals requires addressing data heterogeneity, class imbalance, and computational complexity at present. This study develops the Importance Sampling Algorithm-optimized Multi-Modal CNNs (ISA-MM-CNNs) paradigm for EMI-based evaluation of composite curing processes. …”
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An efficient and resilient energy management strategy for hybrid microgrids inspired by the honey badger's behavior by Ahmed A. Shaier, Mahmoud M. Elymany, Mohamed A. Enany, Nadia A. Elsonbaty, Marwa M. Tharwat, Marwa M. Ahmed

“…This system employs a multi-objective optimization algorithm to dynamically identify the best energy management system (EMS). …”
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Lightweight encoding for medical additive manufacturing files by Xin Zhao, Jinjie Huang, Mingcong Xu

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Energy-efficient artificial fish swarm-based clustering protocol for enhancing network lifetime in underwater wireless sensor networks by Puneet Kaur, Kiranbir Kaur, Kuldeep Singh, Kiran Saleem, Ateeq Ur Rehman, Rupesh Gupta, Seada Hussen Adem

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Clearing Model for Flexibility Dispatching of Virtual Power Plants and Energy Spot Market Considering Transmission-Distribution Coordination by HUANG Fuquan, HE Yujun, GUO Hongye, LI Yun, CHEN Tunan

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Path Planning of Underground Robots via Improved A* and Dynamic Window Approach by Jianlong Dai, Yinghao Chai, Peiyin Xiong

“…To overcome these challenges, we propose an improved path planning algorithm integrating an enhanced A* method with an improved Dynamic Window Approach (DWA). …”
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