Enhancing Smart Microgrid Resilience and Virtual Power Plant Profitability Through Hybrid IGWO-PSO Optimization With a Three-Phase Bidding Strategy by T. Yuvaraj, T. Sengolrajan, Natarajan Prabaharan, K. R. Devabalaji, Akie Uehara, Tomonobu Senjyu

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P4CN-YOLOv5s: a passion fruit pests detection method based on lightweight-improved YOLOv5s by Zhiping Tan, Zhiping Tan, Dapeng Ye, Jiancong Wang, Wenxiang Wang

“…In P4CN-YOLOv5s, the Mosaic-9 and Mixup algorithms are initially used for data augmentation to augment the training dataset and enhance data complexity. …”
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Optimizing Heart-Kidney Interaction for Cancer Detection Through Physiological Process Simulation as a Decision Support System by Najmeh Sadat Jaddi, Salwani Abdullah, Zalinda Othman, Yazrina Yahya, Mohd Zakree Ahmad Nazri, Say Leng Goh, Fatemeh Alvankarian, Jafar Alvankarian

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Hybrid Efficient Fast Charging Strategy for WPT Systems: Memetic-Optimized Control with Pulsed/Multi-Stage Current Modes and Neural Network SOC Estimation by Marouane El Ancary, Abdellah Lassioui, Hassan El Fadil, Yassine El Asri, Anwar Hasni, Abdelhafid Yahya, Mohammed Chiheb

“…The proposed approach employs a memetic algorithm (MA) to dynamically optimize the charging parameters, achieving an optimal balance between speed and battery longevity while maintaining 90.78% system efficiency at the SAE J2954-standard 85 kHz operating frequency. …”
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Prediction of lithium-ion battery SOC based on IGA-GRU and the fusion of multi-head attention mechanism by Pei Tang, Minnan Jiang, Weikai Xu, Zhengyu Ding, Mao Lv

“…Compared with the traditional parameter optimization approach, this paper uses the immune genetic algorithm to find the optimal hyperparameters of the model, which on the one hand has a wider choice of parameters, and on the other hand has been improved for the genetic algorithm is easy to fall into the local optimal solution, so as to improve the SOC estimation accuracy of the GRU model. …”
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Experimental determination and theoretical calculation for CO2 liquid-solid phase equilibrium in PLNG by Zihe LI, Jianlu ZHU, Qing MIAO, Feng YAN, Xin OUYANG, Chaofei NIE, Hui HAN, Yuxing LI

“…Objective Compared with traditional submarine pipelines, Floating Liquefied Natural Gas (FLNG) facilities are deemed more suitable for the exploitation of offshore natural gas. …”
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Learning-based early detection of post-hepatectomy liver failure using temporal perioperative data: a nationwide multicenter retrospective study in ChinaResearch in context by Kai Wang, Qian Yang, Kang Li, Shanhua Tang, Baoluhe Zhang, Xiangyun Liao, Shunda Du, Wenguang Fu, Zhiwei Li, Huanwei Chen, Haorong Xie, Pengxiang Huang, Jieyuan Li, Qiuting Wang, Haiqing Liu, Zhiwei Huang, Pheng Ann Heng, Xueshuai Wan, Chuanjiang Li, Weixin Si

“…Our approach was compared with state-of-the-art machine learning and deep learning methods. …”
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Suppression and control of unbalanced and misalignment coupler vibration of a double-rotor permanent magnet drive by Yongcun GUO, Xin MA, Shuang WANG, Deyong LI, Tun YANG

“…By comparing the MNN−ILC algorithm with the traditional ILC algorithm and the existing improved ILC algorithm. …”
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SYSTEMIZATION AND DEVELOPMENT OF TECHNIQUES FOR LEADERS PERSONAL QUALITIES IDENTIFICATION AT VARIOUS LEVELS AND SCOPES OF ACTIVITY by Maxim Vladimirovich Kolesnikov

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Phytoplanktonic Photoacclimation Under Clouds by Charlotte Begouen Demeaux, Emmanuel Boss, Jason R. Graff, Michael J. Behrenfeld, Toby K. Westberry

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A configuration and scheduling optimization method for integrated energy systems considering massive flexible load resources by Zihao Wang, Shenhua Wang, Hanwen Ni, Junyin Wang, Jun Zhang

“…Future research will further incorporate hydrogen demand response mechanisms and optimize the output of integrated energy systems from the perspective of spot markets. …”
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Missing values imputation using Fuzzy K-Top Matching Value by Azza Ali, Mervat Abu-Elkheir, Ahmed Atwan, Mohammed Elmogy

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SCUC Considering Loads and Wind Power Forecasting Uncertainties using Binary Gray Wolf Optimization Method by Majid Moazzami, Sayed Jamal Al-Din Hosseini, Hossein Shahinzadeh, Gevork B. Gharehpetian, Jalal Moradi

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Development and validation of an explainable machine learning model for predicting postoperative pulmonary complications after lung cancer surgery: a machine learning studyResearch... by Shaolin Chen, Ting Deng, Qing Yang, Jin Li, Juanyan Shen, Xu Luo, Juan Tang, Xulian Zhang, Jordan Tovera Salvador, Junliang Ma

“…Feature selection involved univariate analysis, collinearity analysis, nine ML algorithms, and expert consensus. Twelve independent ML models and 26 stacking ensemble models were developed. …”
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Balancing public safety and civil rights: Successes and challenges of AI-based video surveillance systems by S.S. Vaddiparti, F. Babaiev

“…It revealed that although modern AI video analytics systems are highly effective in enhancing security (e.g., threat detection and behavioural analysis), they also generate significant ethical and legal risks – particularly with respect to privacy violations and algorithmic discrimination. A comparative legal analysis highlighted marked differences in regulatory models across jurisdictions: European systems emphasise privacy protection, while the Chinese approach prioritises threat prevention. …”
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Comparing the Performance of Machine Learning Models and Conventional Risk Scores for Predicting Major Adverse Cardiovascular Cerebrovascular Events After Percutaneous Coronary Int... by Min-Young Yu, Hae Young Yoo, Ga In Han, Eun-Jung Kim, Youn-Jung Son

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Optimization of anti-MRSA compound production by Streptomyces sp. AR05 using an integrated RSM-ANN-GA approach by Fateh Merouane, Amani Kifadji, Racha Mansouri, Meroua Safa Mechouche, Chemes El-Houda Messaad, Anfal Bellebcir

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Categorizing Mental Stress: A Consistency-Focused Benchmarking of ML and DL Models for Multi-Label, Multi-Class Classification via Taxonomy-Driven NLP Techniques by Juswin Sajan John, Boppuru Rudra Prathap, Gyanesh Gupta, Jaivanth Melanaturu

“…Building on existing literature, discussions with psychologists and other mental health practitioners, we developed a taxonomy of 27 distinctive markers spread across 4 label categories; aiming to create a preliminary screening tool leveraging textual data.The core objective is to identify the most suitable model for this complex task, encompassing comprehensive evaluation of various machine learning and deep learning algorithms. we experimented with support vector machines (SVM), random forest (RF) and long short-term memory (LSTM) algorithms incorporating various feature combinations involving Term Frequency-Inverse Document Frequency (TF-IDF) and Latent Dirichlet Allocation (LDA). …”
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Evaluating Machine Learning Models for Predicting Hardness of AlCoCrCuFeNi High-Entropy Alloys by Uma Maheshwera Reddy Paturi, Muhammad Ishtiaq, Pasupuleti Lakshmi Narayana, Anoop Kumar Maurya, Seong-Woo Choi, Nagireddy Gari Subba Reddy

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Fine-tuning text-to-SQL models with reinforcement-learning training objectives by Xuan-Bang Nguyen, Xuan-Hieu Phan, Massimo Piccardi

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