Joint planning of energy storage site selection and line capacity expansion in distribution networks considering the volatility of new energy by Xu Feifei, Pan Xia, Chen Bowei, Li Xiaoshuang, Nie Zhi, Feng Miaoyong, Feng Miaoyong

“…Compared to optimization models that do not consider the integration of new energy sources, the output solution of this model can reduce the abandonment of new energy by at least 50%. It also avoids the numerical problems that may arise from iterative algorithms and logical transformation, demonstrating engineering application value.…”
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A novel deep learning model for predicting marine pollution for sustainable ocean management by Michael Onyema Edeh, Surjeet Dalal, Musaed Alhussein, Khursheed Aurangzeb, Bijeta Seth, Kuldeep Kumar

“…The classification was done using two types of machine learning algorithms: two-step clustering and a fully convolutional network (FCN). …”
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Enhanced Detection of Intrusion Detection System in Cloud Networks Using Time-Aware and Deep Learning Techniques by Nima Terawi, Huthaifa I. Ashqar, Omar Darwish, Anas Alsobeh, Plamen Zahariev, Yahya Tashtoush

“…We generate real DoS traffic, including normal, Internet Control Message Protocol (ICMP), Smurf attack, and Transmission Control Protocol (TCP) classes, and develop nine predictive algorithms, combining traditional machine learning and advanced deep learning techniques with optimization methods, including the synthetic minority sampling technique (SMOTE) and grid search (GS). …”
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A Two-Stage Corrosion Defect Detection Method for Substation Equipment Based on Object Detection and Semantic Segmentation by Zhigao Wang, Xinsheng Lan, Yong Zhou, Fangqiang Wang, Mei Wang, Yang Chen, Guoliang Zhou, Qing Hu

“…To enhance the performance of both YOLOv8 and DDRNet, a multi-head attention block is integrated into their algorithms. Additionally, to address the challenge posed by the scarcity of corrosion defect samples, this study augmented the dataset using the cut-copy-paste method. …”
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Performance Evaluation of Uplink Cell-Free Massive MIMO Network Under Weichselberger Rician Fading Channel by Birhanu Dessie, Javed Shaikh, Georgi Iliev, Maria Nenova, Umar Syed, K. Kiran Kumar

“…However, estimating the channel with high-performance, low-cost computational methods is still a problem. Different algorithms have been developed to address these challenges in channel estimation. …”
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Improving Efficiency of Rolling Mill Stand Electric Drives Through Load Alignment by Stanislav S. Voronin, Andrey A. Radionov, Alexander S. Karandaev, Roman A. Lisovsky, Boris M. Loginov, Mark A. Zinchenko, Vadim R. Khramshin, Ivan N. Erdakov

“…The prospects of this research include the optimization of high-speed and high-load electric drive modes to reduce the energy costs of rolling and the development of an LDC based on fuzzy logic algorithms.…”
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Remote Sensing Change Detection by Pyramid Sequential Processing With Mamba by Jiancong Ma, Bo Li, Hanxi Li, Siying Meng, Ruitao Lu, Shaohui Mei

“…Recent advancements have introduced numerous effective algorithms, significantly enhancing the performance of CD tasks. …”
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Implementation of carrier-grade quantum communication networks over 10000 km by Hao-Ze Chen, Ming-Han Li, Yu Zhou Wang, Zhen-Geng Zhao, Cheng Ye, Fei Long Li, Zhu Chen, Sheng-Long Han, Bao Tang, Ya Jun Miao, Wei Qi

“…Abstract Quantum computing poses a serious threat to classical cryptographic algorithms based on computational complexity. Quantum key distribution (QKD), utilizing the principles of quantum mechanics, enables secure key exchange and has been proven to be an essential technology to resist the threat of quantum computing. …”
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Interactive cardiovascular disease prediction system using learning techniques: Insights from extensive experiments by Purnima Pal, Harsh Vikram Singh, Veena Grover, R. Manikandan, Rasoul Karimi, Mohammad Khishe

“…Additionally, ensemble learning models also show promise, with the Random Forest model delivering competitive accuracy, effectively capturing attributes and temporal dependencies within cardiovascular disease data. …”
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Artificial Intelligence-Based Segmentation and Classification of Plant Images with Missing Parts and Fractal Dimension Estimation by Ganbayar Batchuluun, Seung Gu Kim, Jung Soo Kim, Tahir Mahmood, Kang Ryoung Park

“…Existing research on image-based plant classification has demonstrated high performance using artificial intelligence algorithms. However, limited camera viewing angles can cause parts of the plant to be invisible in the acquired images, leading to an inaccurate classification. …”
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Steganography in IoT: A Comprehensive Survey on Approaches, Challenges, and Future Directions by Maha Driss, Lamia Berriche, Safa Ben Atitallah, Siwar Rekik

“…We evaluated and validated the techniques employed using key metrics such as imperceptibility, robustness, and embedding capacity while emphasizing the computational restrictions, real-time processing requirements of IoT devices, and the vital requirement for energy-efficient algorithms. This survey also investigates the integration of steganography and cryptographic approaches, as well as advances in Machine Learning (ML), Deep Learning (DL), and quantum techniques that could revolutionize the field. …”
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Electromyography Signal Acquisition, Filtering, and Data Analysis for Exoskeleton Development by Jung-Hoon Sul, Lasitha Piyathilaka, Diluka Moratuwage, Sanura Dunu Arachchige, Amal Jayawardena, Gayan Kahandawa, D. M. G. Preethichandra

“…This article emphasizes muscle synergy analysis and adaptive control algorithms to enhance personalization and fatigue compensation, followed by the benefits of multimodal sensing and edge computing in addressing the limitations of EMG-only systems. …”
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Unveiling the ageing-related genes in diagnosing osteoarthritis with metabolic syndrome by integrated bioinformatics analysis and machine learning by Jian Huang, Lu Wang, Jiangfei Zhou, Tianming Dai, Weicong Zhu, Tianrui Wang, Hongde Wang, Yingze Zhang

“…These hub ARGs not only demonstrated strong diagnostic values based on nomogram data but also exhibited a significant correlation with immune cell infiltration. …”
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MulLeak: Exploiting Multiply Instruction Leakage to Attack the Stack-optimized Kyber Implementation on Cortex-M4 by Fan Huang, Xiaolin Duan, Chengcong Hu, Mengce Zheng, Honggang Hu

“…This research underscores the potential vulnerabilities in PQC implementations against side-channel attacks and contributes to the ongoing discourse on the physical security of cryptographic algorithms. …”
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Main trends in the improvement of software of mobile laser remote chemical reconnaissance complexes by V. A. Inozemcev, A. A. Grigor’ev, I. N. Efimov, A. A. Pozvonkov, A. S. Soloshin

“…The contemporary level of the development of the theory of laser location and technical possibilities of lidar systems allows not only to solve certain problems of remote control of the optical properties of aerosol formations, but also to measure their concentrational characteristics and the parameters of the distribution function of the aerosol particles, using multi-frequency laser sensing. …”
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A Review on Millimeter-Wave Hybrid Beamforming for Wireless Intelligent Transport Systems by Waleed Shahjehan, Rajkumar Singh Rathore, Syed Waqar Shah, Mohammad Aljaidi, Ali Safaa Sadiq, Omprakash Kaiwartya

“…In this systematic review, a detailed literature review of algorithms/techniques used in hybrid beamforming along with performance metrics, characteristics, limitations, as well as performance evaluations are provided to enable communication compatible with modern Wireless Intelligent Transport Systems (WITSs). …”
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Advances in impact force identification: A comprehensive review of techniques and mathematical innovations by Hamed Kalhori, Shabnam Tashakori, Ben Halkon, Mehrisadat Makki Alamdari, Bing Li, Morteza Saberi

“…Unresolved challenges are also identified, particularly in scenarios involving multiple concurrent impacts, sparse sensor networks, and online operation under dynamic environmental conditions. …”
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NMR-based metabolomic approach to estimate chemical and sensorial profiles of olive oil by Gaia Meoni, Leonardo Tenori, Francesca Di Cesare, Stefano Brizzolara, Pietro Tonutti, Chiara Cherubini, Laura Mazzanti, Claudio Luchinat

“…By integrating NMR data with traditional chemical analyses and sensory evaluation, we developed multivariate models to evaluate the predictive power of NMR spectra coupled with machine learning algorithms for 50 distinct olive oil quality parameters, including physicochemical properties, fatty acid composition, total polyphenols, tocopherols, and sensory attributes. …”
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Predictive analysis of root canal morphology in relation to root canal treatment failures: a retrospective study by Mohmed Isaqali Karobari, Vishnu Priya Veeraraghavan, P. J. Nagarathna, Sudhir Rama Varma, Jayaraj Kodangattil Narayanan, Santosh R. Patil

“…Demographic data, tooth type, and root canal morphology were also recorded. Univariate and multivariate logistic regression analyses were performed to identify predictors of RCT failure. …”
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Elevated Temperature Effects on FRP–Concrete Bond Behavior: A Comprehensive Review and Machine Learning-Based Bond Strength Prediction by Aseel Salameh, Rami Hawileh, Hussam Safieh, Maha Assad, Jamal Abdalla

“…Therefore, cement mortar-bonded CFRP textiles display better performance in fire endurance. This present paper also utilizes machine learning algorithms for the prediction of bond strength under elevated temperatures based on an experimental database of 37 beams. …”
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