Analysis of Techno–Economic and Social Impacts of Electric Vehicle Charging Ecosystem in the Distribution Network Integrated with Solar DG and DSTATCOM by Ramesh Bonela, Sriparna Roy Ghatak, Sarat Chandra Swain, Fernando Lopes, Sharmistha Nandi, Surajit Sannigrahi, Parimal Acharjee

“…In this work, a comprehensive planning framework for an electric vehicle charging ecosystem (EVCE) is developed, incorporating solar distributed generation (DG) and a distribution static compensator (DSTATCOM), to assess their long-term techno–economic and environmental impacts. The optimal locations and capacities of the EVCE, solar DG, and DSTATCOM are determined using an improved particle swarm optimization algorithm based on the success rate technique. …”
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Meteorological data implications modeling on evapotranspiration variability in arid and semi-arid zones in Saudi Arabia using hybrid metaheuristic by Oulad Naoui Noureddine, Sekkoum Mohamed, Cherif El Amine, Ali Alzaed, Meseret Abeje Gedfew, Sherif S. M. Ghoneim, Enas E. Hussein

“…In this paper, the Bat algorithm (BAT) with the Newton Method (NM), Bird Swarm Algorithm (BSA), Genetic Algorithm (GA), and Chicken Swarm Optimization Algorithm (CSO) are used as a hybrid model in arid and semi-arid zones in Saudi Arabia as well as for modeling rainfall, temperature, and solar radiation implications on evapotranspiration variability. …”
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SHERA: SHAP-Enhanced Resource Allocation for VM Scheduling and Efficient Cloud Computing by Ashwin Singh Slathia, Abhiram Sharma, P. B. Krishna, Saksham Anand, Ayush Rathi, Linda Joseph, Xiao-Zhi Gao

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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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Exploiting full-duplex opportunities in WLANs via a reinforcement learning-based medium access control protocol by Song Liu, Peng Wei

“…Thus, we develop a Window-Constraint Bayesian (WCB) algorithm to generate optimized scheduling policies online. …”
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Let’s get in sync: current standing and future of AI-based detection of patient-ventilator asynchrony by Thijs P. Rietveld, Björn J. P. van der Ster, Abraham Schoe, Henrik Endeman, Anton Balakirev, Daria Kozlova, Diederik A. M. P. J. Gommers, Annemijn H. Jonkman

“…Results of algorithms are generally promising (average reported sensitivity, specificity and accuracy of 0.80, 0.93 and 0.92, respectively), but most algorithms are only available offline, can detect a small subset of PVAs (focusing mostly on ineffective effort and double trigger asynchronies), or remain in the development or validation stage (84% (16/19 of the reviewed studies)). …”
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A Developed Mathematical Model for Designing a Multilevel Sustainable Supply Chain Network Taking into Account Environmental Decisions by Mehrab Paydarfard, Roya Pirzadeh, Ali Ahmadi, Masoud Zohrabi, Farkhondeh Mortaz Hejri, Malek Hasan

“…In addition, the proposed model was optimized by the whale optimization algorithm (WOA) to find the best solution in large-scale instances in a short and reasonable time. …”
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Robust model predictive control for polytopic uncertain systems via a high-rate network with the FlexRay protocol by Jianhua Wang, Fuqiang Fan, Yanye Yu, Shuxin Du, Xiaorui Guo

“…Subsequently, taking both high-rate networks and FRP into account, sufficient conditions are obtained by solving a time-varying terminal constraint set of an auxiliary optimization problem. In addition, an algorithm including both off-line and on-line parts is provided to find a sub-optimal solution. …”
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Classification of Fritillaria thunbergii appearance quality based on machine vision and machine learning technology by DONG Chengye, LI Dongfang, FENG Huaiqu, LONG Sifang, XI Te, ZHOU Qin’an, WANG Jun

“…In addition, to optimize YOLO-X, according to the unique features of F. thunbergii dataset, a dilated convolution structure was embedded into the end of the backbone feature extraction network of YOLO-X as it could improve the model sensitivity to the dimension feature. …”
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MRI-based brain tumor ensemble classification using two stage score level fusion and CNN models by Oussama Bouguerra, Bilal Attallah, Youcef Brik

“…Nine deep learning models are then trained and tested on the enhanced dataset, experimenting with five optimizers. …”
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An artificial intelligence model integrating culprit lesion diagnosis and risk assessment for acute coronary syndromeResearch in context by Peng Peng Xu, Bin Hu, Fan Zhou, Zhi Han Xu, Qian Chen, Tong Yuan Liu, Bang Jun Guo, Chang Sheng Zhou, Xin Wei Tao, Hong Yan Qiao, Jia Ni Zou, Xiang Ming Fang, Wen Cai Huang, Long Jiang Zhang

“…Additionally, the RF model showed a significant improvement in performance compared to the stenosis severity model in both Cohorts 3 and 4 (all net reclassification improvement [NRI] values > 0). …”
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Development of several machine learning based models for determination of small molecule pharmaceutical solubility in binary solvents at different temperatures by Mohammed Alqarni, Ali Alqarni

“…This study shows that advanced machine learning models, particularly BNN and NODE, can predict pharmaceutical solubility and improve crystallization process design and optimization.…”
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Deep convolutional neural network (DCNN)-based model for pneumonia detection using chest x-ray images by S. I. Ele, U. R. Alo, H. F. Nweke, A. H. Okemiri, E. O. Uche-Nwachi

“…This study focuses on developing and implementing a machine learning model tailored specifically for medical diagnosis, leveraging advancements in computer vision and deep learning algorithms. …”
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Development and validation of machine learning-based diagnostic models using blood transcriptomics for early childhood diabetes prediction by Xin Huang, Xin Huang, Di Ouyang, Weiming Xie, Huawei Zhuang, Siyu Gao, Pan Liu, Lizhong Guo

“…Five feature selection methods (Lasso, Elastic Net, Random Forest, Support Vector Machine, and Gradient Boosting Machine) were employed to optimize gene sets. Nine machine learning algorithms (Decision Tree, Gradient Boosting Machine, K-Nearest Neighbors, Linear Discriminant Analysis, Logistic Regression, Multilayer Perceptron, Naive Bayes, Random Forest, and Support Vector Machine) were combined with selected features, generating 45 unique model combinations. …”
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Real-Time Anomaly Detection in IoMT Networks Using Stacking Model and a Healthcare- Specific Dataset by Hadjer Goumidi, Samuel Pierre

“…This model integrates XGBoost as the meta-learner with Random Forest and ANN as base models, leveraging their strengths to optimize anomaly detection. …”
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Comparison of time-to-event machine learning models in predicting biliary complication and mortality rate in liver transplant patients by Aref Andishgar, Sina Bazmi, Kamran B. Lankarani, Seyed Alireza Taghavi, Mohammad Hadi Imanieh, Gholamreza Sivandzadeh, Samira Saeian, Nazanin Dadashpour, Alireza Shamsaeefar, Mahdi Ravankhah, Hamed Nikoupour Deylami, Reza Tabrizi, Mohammad Hossein Imanieh

“…Seven survival machine learning algorithms were used: LASSO, Ridge, RSF, E-NET, GBS, C-GBS, and FS-SVM. …”
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Balancing line hardening, distributed generation and de-energization for wildfire risk mitigation with microgrid formation by Mengqi Yao, Shunbo Lei, Weimin Wu, Duncan S. Callaway

“…An adopted column-and-constraint generation algorithm is developed to solve the model and obtain the optimal decisions. …”
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Explainable predictive models of short stature and exploration of related environmental growth factors: a case-control study by Jiani Liu, Xin Zhang, Wei Li, Francis Manyori Bigambo, Dandan Wang, Xu Wang, Beibei Teng

“…Additionally, we evaluated the performance of the nine machine learning algorithms to determine the optimal model. The Shapley additive explanation (SHAP) method was subsequently employed to prioritize factor importance and refine the final model. …”
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Method and experimental verification of spatial attitude prediction for an advanced hydraulic support system under mining influence by Zhuang Yin, Kun Zhang, ZengBao Zhang, Hongyue Chen, Lingyu Meng, Zhen Wang, Mingchao Du, Xiangpeng Hu, Defu Zhao, Dan Tian

“…This improvement enhances the accuracy and parameter optimization efficiency of the advanced support attitude prediction model, thereby providing robust theoretical and technical support for the intelligent, safe, and efficient mining operations of the advanced coupling support system.…”
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Techno-economic modeling and analysis of a PV EV charged with battery energy storage system (BESS) on Kalimantan Island by Aripriharta, Satria Adiguna, Arif N. Afandi, Muhammad Cahyo Bagaskoro

“…Results show Tarakan as the most optimal location, generating 215,804.88 kWh for IDR 916.9/kWh and lowering emissions by 435,884.29 kgCO2e, while Samarinda is the least optimal location. …”
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