Embedded implementation of phase imbalance faults in three-phase inverters: The impact of MOSFET conduction resistance variations by Oussama Idbouhouch, Mourad Zegrari, Nabila Rabbah, Ibtihal Ait Abdelmoula, Hicham Oufettoul, Saad Motahhir

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Achieving Distributed Consensus in UWB Sensor Networks: A Low Sampling Rate Scheme with Quantized Measurements by Lorenzo Taponecco, Luca Sanguinetti

“…Distributed consensus in sensor networks has received great attention in the last few years. Most of the research activity has been devoted to study the sensor interactions that allow the convergence of distributed consensus algorithms toward a globally optimal decision. …”
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GeoAI Dataset for Training a Deep Learning-based GEMS Snow Detection Model by Jin-Woo Yu, Jun-Hyeok Jung, Kyoung-Hee Kang, Yong-Mi Lee, Hyung-Sup Jung

“…Despite this, GEMS relies solely on the ultraviolet and partial visible bands, lacking the infrared bands crucial for snow detection, and it has no proprietary snow detection algorithm, instead utilizing near-real-time ice and snow extent data from the U.S. …”
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An efficient dual-branch framework via implicit self-texture enhancement for arbitrary-scale histopathology image super-resolution by Minghong Duan, Linhao Qu, Zhiwei Yang, Manning Wang, Chenxi Zhang, Zhijian Song

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Practicality of training a quantum-classical machine in the noisy intermediate-scale quantum era by Tarun Dutta, Alex Jin, Clarence Liu Huihong, José Ignacio Latorre, Manas Mukherjee

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An optimized approach for predicting water quality features and a performance evaluation for mapping surface water potential zones based on Discriminant Analysis (DA), Geographical... by Abhijeet Das

“…To achieve this goal, this investigation relies on Drinking (Dr)-Water Quality Index (WQI) and multivariate statistical techniques including discriminant analysis (DA), to assess the variations of surface water quality in the selected region. Again, this research used a strong methodology by incorporating Machine learning (ML) algorithms, such as: Artificial Neural Network (ANN), Gaussian Process Regression (GPR), Support Vector Machine (SVM), and Linear Regression Model (LRM), were applied to forecast and confirm the quality of the water. …”
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Use artificial neural network to recommend the lumbar spinal endoscopic surgical corridor by Chien-Min Chen, Pei-Chen Chen, Ying-Chieh Chen, Guan-Chyuan Wang

“…The SHapley Additive exPlanations algorithm was utilized to explain the relative importance of each factor. …”
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On-Site Safety Inspections Through Marker-Less Augmented Reality and Blockchain Notarization of BIM-Based Processes by Alessandra Corneli, Alessandro Carbonari, Francesco Spegni, Tommaso Pieroni, Berardo Naticchia

“…Then, the interoperable-format IFC is used to upload the model in a BIM platform. On-site outdoor localization is ensured by a GPS-RTK system, while for indoor spaces, an artificial intelligence algorithm that recognizes features is used. …”
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Application of a Hybrid Model for Data Analysis in Hydroponic Systems by Kuanysh Bakirov, Jamalbek Tussupov, Akhmet Tussupov, Ibraheem Shayea, Aruzhan Shoman

“…Experimental evaluation demonstrated superior predictive performance by using XGBoost, achieving an accuracy and F1-score of 97.88%, ROC-AUC of 99.99%, and computational efficiency (training completed in 2.3 s), outperforming RandomForest and GradientBoosting algorithms. Real-time data collection was facilitated through IoT sensors transmitting readings via Wi-Fi every 5 s to a local server, accumulating approximately 17,280 records per day. …”
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Yield Response of Different Rice Ecotypes to Meteorological, Agro-Chemical, and Soil Physiographic Factors for Interpretable Precision Agriculture Using Extreme Gradient Boosting a... by Md. Sabbir Ahmed, Md. Tasin Tazwar, Haseen Khan, Swadhin Roy, Junaed Iqbal, Md. Golam Rabiul Alam, Md. Rafiul Hassan, Mohammad Mehedi Hassan

“…The result shows that the root mean squared error (RMSE) of three different ecotypes are in between 9.38% and 24.37% and that of R-squared values are between 89.74% and 99.13% on two different machine learning algorithms. Moreover, the explainability of the models is also shown in this study with the help of the explainable artificial intelligence (XAI) model called Local Interpretable Model-Agnostic Explanations (LIME).…”
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Digital Empowerment in Social Work: Leveraging AI to Enhance Educational Access in Developing Nations by Zvinodashe Revesai, Benjamin Tungwa, Telson Anesu Chisosa, Vanessa Runyararo Meki

“…The findings show that, with careful implementation and consideration of the context, artificial intelligence can reduce inequalities in education and enhance students' abilities through personalized learning paths, virtual environments for practice, and automated feedback systems. However, this research points out the need for addressing the digital divide and ethical issues associated with artificial intelligence, including problems of privacy and algorithmic bias. …”
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DLLabelsCT: Annotation tool using deep transfer learning to assist in creating new datasets from abdominal computed tomography scans, case study: Pancreas. by Henrik Mustonen, Antti Isosalo, Minna Nortunen, Mika Nevalainen, Miika T Nieminen, Heikki Huhta

“…The utilization of artificial intelligence (AI) is expanding significantly within medical research and, to some extent, in clinical practice. …”
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Detecting Obfuscated Malware Infections on Windows Using Ensemble Learning Techniques by Yadigar Imamverdiyev, Elshan Baghirov, John Chukwu Ikechukwu

“…The findings contribute to cybersecurity efforts by comprehensively assessing machine learning algorithms for obfuscated malware detection through memory analysis. …”
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A Summary of Recent Advances in the Literature on Machine Learning Techniques for Remote Sensing of Groundwater Dependent Ecosystems (GDEs) from Space by Chantel Nthabiseng Chiloane, Timothy Dube, Mbulisi Sibanda, Tatenda Dalu, Cletah Shoko

“…This study provides a comprehensive overview of the progress made in applying advanced ML algorithms to assess and monitor GDEs. It begins with a systematic literature review following the PRISMA framework, followed by an analysis of temporal and geographic trends in ML applications for GDE research. …”
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Diagnosis of gastrointestinal fistulas in pancreatic necrosis by X-ray and computed tomography by T. G. Barmina, L. T. Khamidova, O. A. Zabavskaya, I. E. Selina, P. A. Yartsev, F. A.-K. Sharifullin, I. E. Popova, E. A. Eletskaia, А. M. Kuzmin

“…The purpose of the study: to clarify the possibilities of using X-ray research methods in the framework of a comprehensive diagnosis of gastrointestinal fistulas in pancreatic necrosis.Materials and methods. …”
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Ultra-Short Baseline Synthetic Aperture Passive Positioning Based on Interferometer Assistance by Gaogao Liu, Qidong Zhang, Jian Xu, Jiangbo Zhu, Ziyu Huang, Beibei Mu, Hongfu Guo

“…The synthetic aperture passive positioning (SAPP) method has attracted the attention of researchers due to its high positioning resolution. …”
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SA-MARL: Novel Self-Attention-Based Multi-Agent Reinforcement Learning With Stochastic Gradient Descent by Rabbiya Younas, Hafiz Muhammad Raza Ur Rehman, Ingyu Lee, Byung-Won On, Sungwon Yi, Gyu Sang Choi

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Virtual Communicative Review of Children’s Art Schools of Irkutsk Region by Dvorovenko Olga

“…The accounts with high engagement rates became involved in social media recommendation algorithms.…”
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Speech Emotion Recognition Based on Voice Fundamental Frequency by Teodora DIMITROVA-GREKOW, Aneta KLIS, Magdalena IGRAS-CYBULSKA

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Predictive diagnostics of computer systems logs using natural language processing techniques by Vladislav A. Kiriachek, Soltan I. Salpagarov

“…A comparative assessment of various anomaly detection algorithms was performed, including k-nearest neighbors, autoencoders, One Class SVM, Isolation Forest, Local Outlier Factor, and Elliptic Envelope. …”
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