Enhancing Secure Energy Efficiency of SWIPT IoT Network Considering IRS and Artificial-Noise: A Deep Learning Approach by Kimchheang Chhea, Jung-Ryun Lee

“…Our goal is to maximize secure EE, where the secure EE is defined as the secrecy rate over the power consumption of the user. We aim to jointly optimize phase-shift of IRS, transmit power of jammer and user, to maximize the objective function while ensuring that the secrecy rate is greater than the predefined threshold while allowing the eavesdroppers to harvest energy using SWIPT. …”
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Deep Reinforcement Learning-Based Multi-Agent System with Advanced Actor–Critic Framework for Complex Environment by Zihao Cui, Kailian Deng, Hongtao Zhang, Zhongyi Zha, Sayed Jobaer

“…We introduce an advanced multi-agent deep reinforcement learning (DRL) framework, specifically a Multi-Agent Proximal Policy Optimization (MA-PPO), designed to optimize target acquisition while operating within defined ammunition and time constraints. …”
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Research on RF Intensity Temperature Sensing based on 1D-CNN by DING Meiqi, GUI Lin, WANG Ziyi, SHANG Disen, QIAN Min, LI Qiankun

“…【Results】The experimental results show that the RMSE of the prediction model based on 1D-CNN reaches the order of 10^-3, while the RMSE of the traditional algorithms is usually in the order of 10^-1. …”
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FedACT: An adaptive chained training approach for federated learning in computing power networks by Min Wei, Qianying Zhao, Bo Lei, Yizhuo Cai, Yushun Zhang, Xing Zhang, Wenbo Wang

“…Second, we propose a Genetic-Algorithm-based Sorting (GAS) method to optimize the order of clients participating in training. …”
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Introducing an oncoplastic approach for centrally located breast cancer patients by Mohammadreza Karoobi, Seyed Mostafa Meshkati Yazd, Fatemeh Aminolroaya, Hadiseh Mahram, Samineh Saghafinia, Stefano Pompei, Nahid Nafissi, Pantea Khalili

“…This study aims to present a comprehensive algorithm designed to optimize surgical planning and enhance aesthetic outcomes for patients undergoing surgery for central breast cancers. …”
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Conceptual Framework of Energy-and-Ecology of Indoor Plant Lighting by Sergei A. Rakut’ko

“…(Conclusions) For the first time, the author raises a question about the development of structural elements of the BAT formation algorithm in lighting horticulture in terms of energy-ecological indicators as an integrative optimality criterion of the system. …”
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Quantifying ruminal health: A statistical review and application of area and time under the curve in animal science by Luis O. Tedeschi

“…These insights allow researchers and practitioners to evaluate feeding strategies, diagnose metabolic disorders, and optimize animal management practices. AUC-based metrics, supported by the ATAUC algorithm, enable scalable and pragmatic solutions for real-time monitoring and decision-making. …”
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YOLOv8-OCHD: A Lightweight Wood Surface Defect Detection Method Based on Improved YOLOv8 by Zuxing Chen, Junjie Feng, Xueyan Zhu, Bin Wang

“…This effectively reduces the difficulty and cost of deployment on mobile terminals while significantly improving algorithm accuracy, meeting real-time requirements, and providing a more efficient and feasible technical solution for relevant applications. …”
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An Efficient and Cost-Effective Vehicle Detection and Tracking System for Collision Avoidance in Foggy Weather by Naeem Raza, Muhammad Asif Habib, H. M. Sajid Imran, Abdul Qayum, Sajida Perveen, Sohail Jabbar, Shahzad Sarwar, Mudassar Ahmad

“…The proposed ECE-VDT system encompasses an optimized SimYOLO-V5s algorithm and its five variants for vehicle detection, while the optimized deep-SORT algorithm is proposed for vehicle tracking. …”
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Improving cancer detection through computer-aided diagnosis: A comprehensive analysis of nonlinear and texture features in breast thermograms. by Hamed Khodadadi, Shima Nazem

“…The effectiveness of the proposed approach is enhanced by integrating texture and complexity features. Besides, to optimize feature selection and reduce redundancy, a metaheuristic optimization technique called Non-Dominated Sorting Genetic Algorithm (NSGA III) is applied. …”
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UAV Small Target Detection Model Based on Dual Branches and Adaptive Feature Fusion by Guogang Wang, Mingxing Gao, Yunpeng Liu

“…The model first constructs a small target detection framework with dual branches to improve the detection accuracy while reducing the number of parameters. Secondly, the model introduces semantic and detail injection (SDI) in the neck network and embeds bidirectional adaptive feature fusion in the detection head to innovate and optimize the feature fusion mechanism, achieve the full interaction of deep and shallow information, enhance the feature representation of small targets, and overcome the problem of scale inconsistency. …”
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Cost-benefit analysis in demand response with penalty and grid management using blockchain by Manikandan Ramasamy, Thenmalar Kaliannan, Saravanakumar Ramasamy

“…Two distinct optimization methods such as the gray wolf optimization algorithm and particle swarm optimization are employed to solve the optimization model. …”
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Energy efficiency maximization in MIMO links aided by metasurfaces with global reflection constraints by Ayşegül Ilay Tunalı, Robert Kuku Fotock, Alessio Zappone, Giorgio Taricco, Giuseppa Alfano, Hakan Ali Çırpan

“…Abstract This work develops two radio resource allocation algorithms to optimize the energy efficiency of a multiple-input multiple-output (MIMO) communication system where a metasurface is deployed near the transmit antenna array to create a reconfigurable holographic beamforming structure. …”
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Financial Management of Innovative Activity by V. P. Shestak, E. I. Moreva, I. G. Tyutyunnik

“…A form of control functional was obtained on the sets of observable characteristics of the controlling and controlled subsystems while optimizing the results of innovative activity due to the feedback channel. …”
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Modelling and Solving Rescheduling Problems in Dynamic Permutation Flow Shop Environments by Pablo Valledor, Alberto Gomez, Paolo Priore, Javier Puente

“…The aim of this paper is to analyse, model, and solve the rescheduling problem in dynamic permutation flow shop environments while considering several criteria to optimize. Searching optimal solutions in multiobjective optimization problems may be difficult as these objectives are expressing different concepts and are not directly comparable. …”
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Bayesian Regularization Backpropagation Neural Network for Glass Beams in Lateral–Torsional Buckling by Saddam Hussain, Chiara Bedon, Gaurav Kumar, Zaheer Ahmed

“…Additionally, the Bayesian regularization backpropagation (trainbr) algorithm is used to optimize the input–output relationship accuracy. …”
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Deep knowledge tracing and cognitive load estimation for personalized learning path generation using neural network architecture by Chunyan Tong, Changhong Ren

“…A dual-objective optimization algorithm balances knowledge acquisition with cognitive load management to generate paths that maintain optimal challenge levels. …”
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Acute severe ulcerative colitis: using JAK-STAT inhibitors for improved clinical outcomes by Shruthi Karthikeyan, Chetan Ambastha, Kian Keyashian

“…Here we discuss methods to optimize the dosing of IFX to maximize its efficacy, while exploring recent work done on the safety and efficacy of JAK-STAT inhibitors as a salvage therapy, therefore suggesting a novel treatment algorithm to improve clinical outcomes in medically managed ASUC patients.…”
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Masks-to-Skeleton: Multi-View Mask-Based Tree Skeleton Extraction with 3D Gaussian Splatting by Xinpeng Liu, Kanyu Xu, Risa Shinoda, Hiroaki Santo, Fumio Okura

“…Furthermore, we use a minimum spanning tree (MST) algorithm during the optimization loop to regularize the graph to a tree structure. …”
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Efficient vision transformers with edge enhancement for robust small target detection in drone-based remote sensing by Xuguang Zhu, Zhizhao Zhang

“…Combined with an Inner Generalized Intersection-over-Union (Inner-GIoU) loss function to optimize bounding box geometric consistency, MLD-DETR achieves 36.7% AP50% and 14.5% APs on the VisDrone2019 dataset, outperforming the baseline RT-DETR by 3.2% and 1.8% in accuracy while achieving 20% parameter reduction and maintaining computational efficiency suitable for UAV platforms equipped with modern edge computing hardware. …”
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