PULSE: A modular framework for predictive energy efficiency in heterogeneous data centers by Daniel Flores-Martin, Felipe Lemus-Prieto, Juan A. Rico-Gallego

“…This work introduces PULSE (PUE Unified Learning and Simulation Engine), a novel software platform that integrates deep learning-based prediction models with a natural language assistant to support PUE optimization in real-world settings. …”
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Leveraging explainable artificial intelligence for early detection and mitigation of cyber threat in large-scale network environments by G. Nalinipriya, S. Rama Sree, K. Radhika, E. Laxmi Lydia, Faten Khalid Karim, Mohamad Khairi Ishak, Samih M. Mostafa

“…A Sparse Denoising Autoencoder (SDAE) model recognizes and classifies cyber threats. Additionally, the Hiking Optimization Algorithm (HOA) is employed to fine-tune the hyperparameters of the SDAE model. …”
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Failure Management Overview in Optical Networks by Sergio Cruzes

“…The potential of large language models (LLMs) and digital twins (DTs) for further advancements in automating failure management, optimizing performance, and network optimization in optical networks is also examined. …”
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Automatic Diagnosis of Traumatic Brain Injury Using Deep Learning with CT scan Images by Behrang Rezvani Kakhki, Hossein Zakeri, Sayyed Majid Sadrzadeh, Seyed Mohammad Mousavi, elnaz vafadar moradi, golnoush shahraki

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Yield Diagnosis and Tuning for Emerging Semiconductors During Research Stage by Chunshan Wang, Zizhao Ma, Yuxuan Zhu, Chensheng Jin, Dongyu Chen, Chuxin Zhang, Yining Chen, Wenzhong Bao, Yufeng Xie

“…In this paper, we propose a yield diagnosis and tuning scheme based on ensemble learning and Bayesian optimization, which demonstrate outstanding performance even with a limited data volume. …”
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An XGBoost-SHAP framework for identifying key drivers of urban flooding and developing targeted mitigation strategies by Xiaoping Fu, Mo Wang, Dongqing Zhang, Furong Chen, Xiaotao Peng, Lie Wang, Soon Keat Tan

“…This research proposes an innovative framework to recognize the driving factors and evaluate the impact of land cover changes on urban flooding, using a machine learning simulation model in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). …”
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Artificial Neural Network Framework for Hybrid Control and Monitoring in Turning Operations by Bogdan Felician Abaza, Vlad Gheorghita

“…This paper proposes a hybrid control and monitoring framework designed to enhance turning operations by integrating artificial neural networks (ANNs) for predictive modeling and adaptive recalibration. The system leverages machine learning (ML) to improve machining efficiency, tool longevity, and energy consumption optimization. …”
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Research on the Photovoltaic MPPT Method Based on Improved BP-SVM-ELM Combination Prediction by DAI Bowang, ZHAO Xianggui, ZHU Qiliang

“…The algorithm uses genetic algorithm to optimize BP neural network, least squares support vector machine and extreme learning machine (ELM) to predict the voltage of maximum power point respectively, and then adopts variance-covariance(VC) weight dynamic allocation method to combine the predictions. …”
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Predicting 14-day readmission in middle-aged and elderly patients with pneumonia using emergency department data: a multicentre retrospective cohort study with a survival machine l... by Ta-Chien Chan, Jiunn-Horng Kang, Tian-Shin Yeh, Nguyen Thanh Nhu, Jer-Hwa Chang, Yu-Tien Tzeng, Chia-Chieh Wu, Carlos Lam

“…Given that the 14-day readmission rate is considered a healthcare quality indicator, this study is the first to develop survival machine learning (ML) models using emergency department (ED) data to predict 14-day readmission risk following pneumonia-related admissions.Design A retrospective multicentre cohort study.Setting This study used the Taipei Medical University Clinical Research Database, including data from patients at three affiliated hospitals.Participants 11 989 hospital admissions for pneumonia among patients aged ≥45 years admitted from 2014 to 2021.Primary and secondary outcome measures The dataset was randomly split into training (80%), validation (10%) and independent test (10%) sets. …”
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Accelerated development of high-strength and high-conductivity Cu-Cr-Ti alloys based on data-driven design and experimental validation by Li Feng, Jiangnan Li, Qiong Lu, Yuanqi You, Zunyan Xu, Liyuan Liu, Li Fu, Peng Gao, Jianhong Yi, Caiju Li

“…To address this challenge, this study applied a machine learning approach: a Support Vector Regression (SVR) based “composition-conductivity” model was constructed to predict the impact of individual elements on the alloy’s electrical conductivity. …”
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Metaheuristic Algorithms to Determine PID Controller Parameters for Mobile Robots by DINH Quy Long, NGUYEN Tuan Minh, NGUYEN The Dung

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EEG microstate analysis in children with prolonged disorders of consciousness by Yi Zhang, Zhichong Hui, Yuwei Su, Weihang Qi, Guangyu Zhang, Liang Zhou, Jiamei Zhang, Kaili Shi, Yonghui Yang, Lei Yang, Gongxun Chen, Sansong Li, Mingmei Wang, Dengna Zhu

“…Correlation analysis examined relationships between microstate parameters and Coma Recovery Scale-Revised (CRS-R) scores in children with pDoC. Support vector machine (SVM) models were trained using combined temporal and spatial microstate features, optimized via grid search and random search algorithms. …”
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Stacking modeling with genetic algorithm-based hyperparameter tuning for uniaxial compressive strength prediction by Tanveer Alam Munshi, Khanum Popi, Labiba Nusrat Jahan, M. Farhad Howladar, Mahamudul Hashan

“…A notable contribution of this study lies in the application of both grid search and genetic algorithm (GA) for hyperparameter optimization, implemented across both individual base learners and the stacking ensemble model. …”
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Mapping Complex Landslide Scars Using Deep Learning and High-Resolution Topographic Derivatives from LiDAR Data in Quebec, Canada by Hejar Shahabi, Saeid Homayouni, Didier Perret, Bernard Giroux

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Intratumoral and peritumoral radiomics for forecasting microsatellite status in gastric cancer: a multicenter study by Yunzhou Xiao, Jianping Zhu, Huanhuan Xie, Zhongchu Wang, Zhaohai Huang, Miaoguang Su

“…After standardizing and reducing the dimensionality of these features, six radiomic models were constructed utilizing three machine learning techniques: Support Vector Machine (SVM), Linear Support Vector Classification (LinearSVC), and Logistic Regression (LR). …”
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Associations between exposure to heavy metal and sarcopenia prevalence: a cross-sectional study using NHANES data by Yingying Zhang, Qianbing Li, Xiangfei Wang

“…After identifying the core variables, optimal machine learning models were constructed, and SHAP analyses were performed.ResultsWe found that the LGBM model exhibited the best predictive performance. …”
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Methods for state of health estimation for lithium-ion batteries: An essential review by Rhdifa Houda, Ammar Abderazzak, Bouattane Omar

“…Thus, two examples are presented for each method: neural networks (NN) and support vector machines (SVM) for data-driven, the combination of variable forgetting factor recursive least squares (VFF-RLS) with adaptive unscented Kalman filter (AUKF) and particle swarm optimization (PSO), genetic algorithm (GA), particle filter (PF), recursive least squares (RLS) for model-based method to show how each method is applied. …”
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Forecasting dengue across Brazil with LSTM neural networks and SHAP-driven lagged climate and spatial effects by Xiang Chen, Paula Moraga

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Epigenetic profiling for prognostic stratification and personalized therapy in breast cancer by Xiao Guo, Chuanbo Feng, Jiaying Xing, Yuyan Cao, Tengda Liu, Wenchuang Yang, Runhong Mu, Tao Wang

“…By integrating epigenetic insights with machine learning, this model has the potential to improve clinical decision-making and optimize therapeutic strategies for breast cancer patients.…”
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ROBOT NAVIGATION IN INDOOR ENVIRONMENT THROUGH SELF LEARNING by Chandan Kalita, Kishore Kashyap, Mirzanur Rahman, Satyajit Sarma, Parvez Aziz Boruah

“…This data is then utilized to train a Machine Learning model, specifically based on Deep Reinforcement Learning techniques. …”
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