An efficient method for network security situation assessment by Xiaoling Tao, Kaichuan Kong, Feng Zhao, Siyan Cheng, Sufang Wang

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Efficient Conical Area Differential Evolution with Biased Decomposition and Dual Populations for Constrained Optimization by Weiqin Ying, Bin Wu, Yu Wu, Yali Deng, Hainan Huang, Zhenyu Wang

“…The constraint-handling methods using multiobjective techniques in evolutionary algorithms have drawn increasing attention from researchers. …”
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Com-BIS: A Community-Based Barter Incentive Scheme in Socially Aware Networking by Li Liu, Qiuyuan Yang, Xiangjie Kong, Hannan Bin Liaqat, Ahmedin Mohammed Ahmed, Nakema Deonauth, Feng Xia

“…In this method, network nodes are grouped into communities and they allocate their forwarding services for different communities optimally using 0-1 knapsack algorithm. The simulation results show that Com-BIS stimulates selfish nodes to cooperate in data delivery for other nodes effectively which improves the forwarding performance considerably.…”
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Exploring the Limitations of Peripheral Blood Transcriptional Biomarkers in Predicting Influenza Vaccine Responsiveness by Luca Marchetti, Emilio Siena, Mario Lauria, Denise Maffione, Nicola Pacchiani, Corrado Priami, Duccio Medini

“…This analysis revealed that composite measures provide a more accurate assessment of the seroresponse to multicomponent influenza vaccines.…”
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System Layout and Grasp Efficiency Optimization for a Multirobot Waste Sorting System by Bart Engelen, Sander Teck, Jef R. Peeters, Karel Kellens

“…The findings demonstrate substantial improvements in picking efficiency of up to 3.6% and pick rates up to 37.5%, underscoring the potential of advanced heuristic algorithms in robotic waste sorting systems. Future work will focus on refining gripper designs and exploring predictive algorithms to further enhance grasp success rates.…”
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Optimizing Boride Coating Thickness on Steel Surfaces Through Machine Learning: Development, Validation, and Experimental Insights by Selim Demirci, Durmuş Özkan Şahin, Sercan Demirci, Armağan Gümüş, Mehmet Masum Tünçay

“…Among the ML algorithms tested, XGBoost exhibited the highest accuracy. …”
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Detection of breast cancer using machine learning and explainable artificial intelligence by Tharunya Arravalli, Krishnaraj Chadaga, H Muralikrishna, Niranjana Sampathila, D. Cenitta, Rajagopala Chadaga, K. S. Swathi

“…An intricate mix of environmental factors and individual genetic composition can lead to the formation of this deadly carcinoma. …”
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Ensemble Machine Learning for the Prediction and Understanding of the Refractive Index in Chalcogenide Glasses by Miruna-Ioana Belciu, Alin Velea

“…This study employs various machine learning models to reliably predict the refractive index at 20 °C using a small dataset of 541 samples extracted from the SciGlass database. The input for the algorithms consists of a selected set of physico-chemical features computed for the chemical composition of each entry. …”
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On the Security of Data Collection and Transmission from Wireless Sensor Networks in the Context of Internet of Things by Hong Yu, Jingsha He, Ruohong Liu, Dajie Ji

“…In the context of Internet of Things (IoT), multiple cooperative nodes in wireless sensor networks (WSNs) can be used to monitor an event, jointly generate a report and then send it to one or more Internet nodes for further processing. …”
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An anti‐jamming method in multistatic radar system based on convolutional neural network by Jieyi Liu, Maoguo Gong, Mingyang Zhang, Hao Li, Shanshan Zhao

“…Abstract For the existing jamming discrimination methods on the multistatic radar system, the single feature of target echo space correlation is utilised as the metric, which leads to the lack of comprehensive feature extraction and universal discrimination algorithm. In this study, a discrimination method in a multistatic radar system based on the convolutional neural network is proposed. …”
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Deep Reinforcement Learning-Based Motion Control Optimization for Defect Detection System by Yuhuan Cai, Liye Zhao, Xingyu Chen, Zhenjun Li

“…A composite reward mechanism is introduced to mitigate potential motor instability, while CP-MPA is utilized to optimize the performance of the proposed m-TD3 composite controller. …”
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UAV Spiral Maneuvering Trajectory Intelligent Generation Method Based on Virtual Trajectory by Tao Chen, Shaopeng Li, Yong Xian, Leliang Ren, Zhenyu Liu

“…A deep reinforcement learning (DRL) approach, employing the proximal policy optimization (PPO) algorithm, is implemented to train a policy network capable of end-to-end virtual trajectory generation. …”
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Quantitative Evaluation Method for the Severity of Surface Fuzz Defects in Carbon Fiber Prepreg by Yutong Liu, Mei Sang, Yusheng Liu, Haojun Lin, Xueming Wang, Tiegen Liu

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The Gut Microbiota and Colorectal Cancer: Understanding the Link and Exploring Therapeutic Interventions by Imen Zalila-Kolsi, Dhoha Dhieb, Hussam A. Osman, Hadjer Mekideche

“…The study of intratumoral microbiota offers new diagnostic and prognostic tools that, combined with artificial intelligence algorithms, could predict treatment responses and assess the risk of adverse effects. …”
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CrySPAI: A New Crystal Structure Prediction Software Based on Artificial Intelligence by Zongguo Wang, Ziyi Chen, Yang Yuan, Yangang Wang

“…In this paper, we present a crystal structure prediction software based on artificial intelligence, named as CrySPAI, to predict energetically stable crystal structures of inorganic materials given their chemical compositions. The software consists of three key modules, an evolutionary optimization algorithm (EOA) that searches for all possible crystal structure configurations, density functional theory (DFT) that provides the accurate energy values for these structures, and a deep neural network (DNN) that learns the relationship between crystal structures and their corresponding energies. …”
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A joint data and knowledge‐driven method for power system disturbance localisation by Zikang Li, Jiyang Tian, Hao Liu

“…By integrating the physical constraints of disturbance type‐topology information and localisation cost characteristics, a composite constraint loss function is proposed that embed physical knowledge into the data‐driven method. …”
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PREDICTION OF THE USE OF REFRIGERANTS IN LOW-TEMPERATURE EQUIPMENT by J. V. Tatarenko, V. M. Mizin, N. O. Rachkovskiy

“…The highest values of the heat transfer coefficient are obtained when working on refrigerants R410A and R717.Conclusion The implemented algorithms can be helpful for obtaining the characteristics of the steam-compressor refrigerator elements across a wide range of boiling and condensing temperatures taking various factors and the percentage composition of the mixed working substance into account. …”
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Uninterrupted Connectivity Using Conditional Time Split Energy Extraction With Beamforming System for Disaster Affected Wireless Networks by K. Ashok, T. Sudha

“…A distributed BF system using Minimum Mean Square Error algorithm is jointly implemented at all cooperating nodes. …”
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Compliance Control of a Cable-Driven Space Manipulator Based on Force–Position Hybrid Drive Mode by Runhui Xiang, Hejie Xu, Xinliang Li, Xiaojun Zhu, Deshan Meng, Wenfu Xu

“…Finally, the feasibility of the proposed algorithm is demonstrated through simulations and compared with the PID control method. …”
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Systems Biology of Human Microbiome for the Prediction of Personal Glycaemic Response by Nikhil Kirtipal, Youngchang Seo, Jangwon Son, Sunjae Lee

“…Machine learning algorithms and genome-scale modeling are now being applied to find microbiological biomarkers associated with diabetes risk, predicted disease progression, and guide customized therapy. …”
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