A Multi-Agent Approach to Modeling Task-Oriented Dialog Policy Learning by Songfeng Liang, Kai Xu, Zhurong Dong

“…Furthermore, we conduct a theoretical analysis of the convergence properties of the proposed model. Experiments were conducted on two distinct task-oriented dialogue datasets, revealing that the proposed multi-agent model exhibits a significantly faster learning speed and a higher dialogue success rate compared to baseline approaches.…”
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Cyber-Physical System Security for Manufacturing Industry 4.0 Using LSTM-CNN Parallel Orchestration by Salman Saeidlou, Nikdokht Ghadiminia, Kwadwo Oti-Sarpong

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Supervised Convolutional Encoder-Decoder With Gated Linear Units for Detecting Fetal R-Peaks by Yao Chen, Jian Wang, Jing Zhang, Junkun Zhang, Zhentao Qin, Xinran Liu

“…To address the issue of unbalanced sequence labels, we adopt and fine-tune the focal loss function, promoting superior prediction and faster convergence. …”
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Data Driven Second Integral Sliding Mode Control for the Digital Phase-Locked Loop by Haiqin Liu, Mingdong Hou, Guangye Li, Renming Yang, Yun Zhang

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Nonlinear Robust Controller Applied to an Antilock Braking System With Estimation of Parametric Uncertainties and External Perturbations by Cuauhtemoc Acosta Lua, Stefano Di Gennaro

“…The proposed controller’s performance has been validated through numerical simulations using CarSim and real–time experiments on an ABS laboratory setup, representing a quarter–car model. …”
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Accelerated Convergence Method for Flow Field Based on DMD-POD Combined Reduced-Order Optimization Model by Jianhui Li, Jun Huang, Yahui Sun, Guoqiang Li

“…The results show that for linear equations, the proposed method achieves a significant acceleration, with a convergence speed five times faster than traditional numerical methods. …”
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A Survey of Deep Learning Approaches for Pedestrian Detection in Autonomous Systems by Majdi Sukkar, Rajendrasinh Jadeja, Madhu Shukla, Rajesh Mahadeva

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Robot Simulation on Agri-Field Point Cloud With Centimeter Resolution by Shintaro Noda, Masayuki Kogoshi, Wataru Iijima

“…The need for robotic agricultural automation has been driven by global population growth and climate change.To efficiently evaluate and develop agricultural robots not limited to the growing season, we developed a dynamics simulator that works fast on 3D point-cloud models of agricultural fields.The point-cloud models have been widely used in recent agricultural research thanks to advances in aerial photography technology. …”
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Accelerating Multilingual Cryptocurrency Forensics: An NLP-Driven Approach for Efficient Mnemonic Identification by Hsin-Hsiung Kao

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Vehicle-to-Vehicle Communication Channel Estimator Based on Gate Recurrent Unit by Jun-Han Wang, He He, Kosuke Tamura, Shun Kojima, Jaesang Cha, Chang-Jun Ahn

“…On the other hand, the frame structure of the IEEE 802.11p standard contains a few number of pilots and a large pilot interval, which is not sufficient to track the rapidly changing channel environment accurately. …”
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Fast and High-Precision Human Fall Detection Using Improved YOLOv8 Model by Ahlam R. Khekan, Hadi S. Aghdasi, Pedram Salehpour

“…The You Only Look Once (YOLO) models have been widely used previously for designing and implementing human fall detection systems. …”
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Real-Time Interference Mitigation for Reliable Target Detection with FMCW Radar in Interference Environments by Youlong Weng, Ziang Zhang, Guangzhi Chen, Yaru Zhang, Jiabao Chen, Hongzhan Song

“…Frequency-modulated continuous-wave (FMCW) millimeter-wave (mmWave) radar systems are increasingly utilized in environmental sensing due to their high range resolution and robust sensing ability in severe weather environments. …”
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Memory State Dynamics in BEOL FeFETs: Impact of Area Ratio on Analog Write Mechanisms and Charging by Hannes Dahlberg, Oscar Kaatranen, Karl-Magnus Persson, Arto Rantala, Jacek Flak, Lars-Erik Wernersson

“…FE capacitors are non-destructively integrated in the Back-End-of-Line (BEOL) with Si MOSFETs to create FE-Metal-FETs (FeMFETs). …”
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Interference Mitigation and Collision Avoidance of Dynamic UAVBSs Network via Mobility Control: A Game Theoretic Approach by Omar Ali Thabet, Didem Kivanc Tureli, Ufuk Tureli

“…The Utility-Driven Partial Synchronous Learning (UDPSL) algorithm speeds up convergence by using a learning algorithm. This algorithm is seen to increase the incidence of collision when UAVBSs are located close together and require an additional collision avoidance mechanism. …”
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Differential Evolution-Based End-Fire Realized Gain Optimization of Active and Parasitic Arrays by Rozita Konstantinou, Ihsan Kanbaz, Okan Yurduseven, Michail Matthaiou

“…The optimization process first maximizes the end-fire gain in the active array by selecting the optimal current excitation vector. …”
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Optimizing Security in IoT Ecosystems Using Hybrid Artificial Intelligence and Blockchain Models: A Scalable and Efficient Approach for Threat Detection by William Villegas-Ch, Jaime Govea, Rommel Gutierrez, Aracely Mera-Navarrete

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Optimized Prediction of Weapon Effectiveness in BVR Air Combat Scenarios Using Enhanced Regression Models by Andre R. Kuroswiski, Annie S. Wu, Angelo Passaro

“…This study investigates high-performance models for predicting the Weapon Engagement Zone (WEZ) in beyond-visual-range (BVR) air combat scenarios. …”
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Swarm-Based Trajectory Generation and Optimization for Stress-Aligned 3D Printing by Xavier Guidetti, Efe C. Balta, and John Lygeros

“…Our results demonstrate a remarkable improvement in computational efficiency, achieving a <inline-formula> <tex-math notation="LaTeX">$115\times $ </tex-math></inline-formula> faster computation speed than existing methods. This efficiency, combined with the possibility to tune the trajectory spacing to match the deposition process constraints, makes the potential integration of our approach into existing 3D printing processes seamless. …”
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A Deep Q-Learning Algorithm With Guaranteed Convergence for Distributed and Uncoordinated Operation of Cognitive Radios by Ankita Tondwalkar, Andres Kwasinski

“…Importantly, further simulations show that the presented UDMA-DQL approach achieves a much faster learning performance compared to an equivalent table-based Q-learning implementation.…”
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High-Throughput Variable-to-Fixed Entropy Codec Using Selective, Stochastic Code Forests by Manuel Martinez Torres, Miguel Hernandez-Cabronero, Ian Blanes, Joan Serra-Sagrista

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