Scalable FPGA Implementation of a Reliability-Based Direct Turbo Decoder for Short Block Codes by Senthil Murugan, Ramesh Bhakthavatchalu, Karthi Balasubramanian, B. Yamuna, Deepak Mishra, Sree Ranjani Rajendran

“…This paper presents the first hardware implementation of the RCODD algorithm on an FPGA, featuring a serial architecture optimized for minimal memory usage and logic complexity. …”
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Heterogeneous Multi-Agent Deep Reinforcement Learning for Cluster-Based Spectrum Sharing in UAV Swarms by Xiaomin Liao, Yulai Wang, Yang Han, You Li, Chushan Lin, Xuan Zhu

“…Each UAV is equipped with an intelligent agent to execute the deep reinforcement learning (DRL) algorithm. Correspondingly, the HMDRL-UC consists of two parts: multi-agent proximal policy optimization for cluster head (MAPPO-H) and independent proximal policy optimization for cluster member (IPPO-M). …”
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Photovoltaic Power Forecasting with Weather Conditioned Attention Mechanism by Xuetao Jiang, Yuchun Gou, Meiyu Jiang, Lihui Luo, Qingguo Zhou

“…We propose a Multi-Stream Attention Fusion Network (MSAFN) which utilizes an algorithm to derive the optimal decomposition algorithm for different weather conditions. …”
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Robust Beamforming for Superdirective Antenna Arrays and Experimental Validations by Mengying Gao, Haifan Yin, Liangcheng Han, Jingcheng Xie

“…To solve this optimization problem, we propose an efficient orthogonal complement-aided quadratic constraint least squares (OC-QCLS) algorithm, which achieves the maximum possible directivity under the sensitivity constraint. …”
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A smarter approach to liquefaction risk: harnessing dynamic cone penetration test data and machine learning for safer infrastructure by Shubhendu Vikram Singh, Sufyan Ghani

“…ML models, including Support Vector Machine (SVM) optimized with Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), Genetic Algorithm (GA), and Firefly Algorithm (FA), were employed to predict the e/qd ratio using key geotechnical parameters, such as fine content, peak ground acceleration, reduction factor, and penetration rate. …”
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AI enhancing prefabricated aesthetics and low carbon coupled with 3D printing in chain hotel buildings from multidimensional neural networks by Gangwei Cai, Yin Lou, Feidong Lu

“…The results indicate that AI can not only optimize energy consumption and structural efficiency in the renovation process but also achieve low-carbon goals while maintaining high-quality aesthetic designs. …”
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Sagittal Plane Kinematic Deviations and Spatio-Temporal Gait Characteristics in Children with Idiopathic Toe Walking: A Comparative Analysis Using Statistical Parametric Mapping by Rocio Pozuelo-Calvo, Almudena Serrano-Garcia, Yolanda Archilla-Bonilla, Angel Ruiz-Zafra, Manuel Noguera-Garcia, Kawtar Benghazi-Akhlaki, Miguel Membrilla-Mesa, Carla DiCaudo, Jose Heredia-Jimenez

“…<b>Background/Objectives</b>: Idiopathic Toe Walking (ITW) is a pediatric gait disorder characterized by persistent toe-to-heel ambulation in the absence of neurological, orthopedic, or developmental abnormalities. While spatio-temporal parameters often remain within normal ranges, subtle but clinically significant kinematic deviations may underlie compensatory mechanisms that sustain gait functionality. …”
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Investigation on Circadian Action and Color Quality in Laser-Based Illuminant for General Lighting and Display by Shuo-Di Lei, Bi-Jing Liu, Yang Gao, Xiao-Ya Dong, Yu-Jia Gong, Jian Xu, Yun-Xin Xu, Dong Wang, Zi-Quan Guo, Ting-Zhu Wu, Chen-Liang Zhou, Zong-Jian Cai, Yi-Jun Lu, Zhong Chen

“…In this work, the genetic algorithm is employed to optimize both circadian action factor (CAF) and color quality of laser-based illuminants (LBIs) with three, four, and five spectral bands to disclose its possible use in two common white lighting applications, i.e. bedroom lighting and office lighting. …”
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Development and validation of a quick screening tool for predicting neck pain patients benefiting from spinal manipulation: a machine learning study by Changxiao Han, Guangyi Yang, Haibao Wen, Minrui Fu, Bochen Peng, Bo Xu, Xunlu Yin, Ping Wang, Liguo Zhu, Minshan Feng

“…Results The combined LASSO and Boruta algorithms identified nine optimal predictors, with the union feature set achieving superior performance. …”
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rhBNN+ Comprehensive Detections and Analyses of the Human Body Temperatures and Sounds by the Same Smart Mask by Bingcan Liao, Pin Sun, Shuyi Chen, Rihong Huang, Junyu Yang, Guofeng Li, Chengzhi Lv, Nan Zhu, Shui Guan, Hailong Liu, Rong Liu, Ali Mansouri, Changkai Sun

“…The SVM achieved 84.3% accuracy for sound data classification, while the Lion algorithm−optimized SVM achieved an even higher accuracy of 93.6%. …”
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Artificial intelligence-augmented smart grid architecture for cyber intrusion detection and mitigation in electric vehicle charging infrastructure by Ankita Sharma, Shalli Rani, Mohammad Shabaz

“…It incorporates AI-driven security models and anomaly detection algorithms to enhance grid resilience and optimize energy utilization. …”
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Spatial–degree of freedom improvement of interference alignment in multi-input, multi-output interference channels by Yi-bing Li, Xue-ying Diao, Qian-hui Dong

“…To improve the achievable degree of freedom in the K -user interference network, we propose a rank minimization interference minimization algorithm. Unlike the existing methods concentrating on the promotion of degree of freedom, our rank optimization method works directly with the interference matrix rather than its projection using the receive beamformers. …”
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PHEV Routing with Hybrid Energy and Partial Charging: Solved via Dantzig–Wolfe Decomposition by Zhenhua Chen, Qiong Chen, Cheng Xue, Yiying Chao

“…While the full model fails to solve instances with more than 30 customers, the DW algorithm achieves high-quality solutions with optimality gaps typically below 3%. …”
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Text Detection Method With Emphasis on Text Component Importance and Lightweight Design by Lanlan Yin, Qiming Wu

“…Therefore, this study proposes an image scene text detection method based on a lightweight deep relation inference scene text detection algorithm. This algorithm simplifies the network of detection algorithms that consider the importance of text components, aiming to reduce computational complexity while addressing issues such as excessive smoothing. …”
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Improved Combinatorial Benders Decomposition for a Scheduling Problem with Unrelated Parallel Machines by Francisco Regis Abreu Gomes, Geraldo Robson Mateus

“…For the first set the proposed method performs 21.85% on average faster than the standard implementation of the Benders algorithm. For the second set the proposed method failed to find an optimal solution in only 31 in 600 instances, obtained an average gap of 0.07%, and took an average computational time of 377.86 s, while the best results of the other methods were 57, 0.17%, and 573.89 s, respectively.…”
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ASSESSMENT OF THE EFFICACY OF DOSE RADIATION THERAPY REGIMENS FOR TREATING CANCER ACCORDING TO CRITERIA FOR EARLY TOXICITY OF RADIOTHERAPY by V. A. Lisin

“…Optimization of dose fractionation regimens is an important way to increase the effectiveness of radiotherapy for malignant tumors. …”
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Deep reinforcement learning for integrated vessel path planning with safe anchorage allocation by Gil-Ho Shin, Hyun Yang

“…Additionally, the system ensured practicality through path simplification using the Douglas-Peucker algorithm while maintaining safety standards. The visualized optimal paths enhance navigational guidance, thereby improving both maritime traffic safety and port operational efficiency.…”
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UAV spatiotemporal crowdsourcing resource allocation based on deep reinforcement learning by Yaxi LIU, Xulong LI, Jiahao HUO, Wei HUANGFU

“…This approach aims to minimize the average AoI across the network while also reducing the energy consumption of IoT devices. …”
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High-robustness integrated adversarial training method for fingerprint-based indoor localization systems by ZHANG Xuejun, LI Mei, CHEN Hui, WANG Guohua

“…These findings verify that EDEAD optimizes computational efficiency while maintaining high robustness.…”
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Toward Energy Efficiency and Fairness in UAV-Based Task Offloading by Mohamed El-Emary, Ali Ranjha, Diala Naboulsi, Razvan Stanica

“…This results in a joint optimization framework combining 1) a Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm for UAV trajectory control to enhance service coverage and energy efficiency, with 2) a low-complexity task offloading algorithm for UEs. …”
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