Modernizing Transactional Systems: Deep Dive from Monolithic to Micro services Architectures by Krishna Kumaar Ragothaman

“…It investigates the role of these architectures in the sectors such as e-commerce, banking, and online transactions, addressing research questions about the most effective architectures for transactional applications and the influence of intelligent algorithms on real-time analytics and decision-making. …”
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Smart Thermostat Development and Validation on an Environmental Chamber Using Surrogate Modelling by Leonidas Zouloumis, Nikolaos Ploskas, Nikolaos Taousanidis, Giorgos Panaras

“…Although dynamic simulation tools and decision-making algorithms are core components of energy management methodologies, they are often accompanied by excessive computational cost. …”
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Decentralized Coordination of Temperature Control in Multiarea Premises by Maria Yukhymchuk, Volodymyr Dubovoi, Viacheslav Kovtun

“…As a basic task for research on decentralized coordination control of objects that mutually influence each other, stabilizing the comfort temperatures was set in multizone rooms using movable heaters. …”
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Probabilistic Topology Optimization Framework for Geometrically Nonlinear Structures Considering Load Position Uncertainty and Imperfections by Muayad Habashneh, Oveys Ghodousian, Hamed Fathnejat, Majid Movahedi Rad

“…Extending the conventional framework to encompass imperfect geometrically nonlinear analyses, this research discovers the intricate interplay between nonlinearity and uncertainty, shedding light on their combined effects on probabilistic analysis. …”
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The role of explainable AI in enhancing breast cancer diagnosis using machine learning and deep learning models by Zulfikar Ali Ansari, Manish Madhava Tripathi, Rafeeq Ahmed

“…Although artificial intelligence (AI) has showed amazing promise in breast cancer prediction mainly machine learning (ML) algorithms as well as deep learning (DL), practical use of these models is greatly hampered by their lack of interpretability and transparency. …”
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IMMUNOPATHOGENESIS OF MYASTHENIA GRAVIS (REVIEW) by E. D. Gasymly

“…Thanks to the development of biotechnological methods, the researchers were able to identify the subtype of lymphocytes involved in the development of myasthenia gravis. …”
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The role of artificial intelligence in enhancing disaster preparedness and trauma care by Mohamad Sorani

“…This article underscores the urgent need for interdisciplinary research, investment, and international cooperation to fully realize AI's transformative potential in these critical fields.…”
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Ten-year cardiovascular risk estimation in type 2 diabetes in Europe using the novel SCORE2-Diabetes model by G. G. Arabidze, M. N. Mamedov, H. R. Akhundova

“…The article presents a validated prognostic score (SCORE2-Diabetes) developed by a group of European researchers in collaboration with the European Society of Cardiology (ESC) for 10-year cardiovascular risk in type 2 diabetes (T2D) in Europe. …”
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Implementation status of European guidelines on trauma management of prehospital bleeding control: a national survey in Austria by Julia Doescher, Sibylle Langenecker

“…Further studies are needed to explore the reasons for this non-adherence, and additional qualitative research in this field is essential.…”
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SHARPNESS IMPROVEMENT OF MAGNETIC RESONANCE IMAGES USING A GUIDED-SUBSUMED UNSHARP MASK FILTER by Manar AL-ABAJI, Zohair AL-AMEEN

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Method for Selecting Pulsed Signals by Their Duration in Fading Channels by M. V. Buhaiov, S. V. Zakirov

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Highway Rest Area Truck Parking Occupancy Prediction Using Machine Learning: A Case Study from Poland by Artur Budzyński, Maria Cieśla

“…This study addresses this gap by applying supervised machine learning algorithms to predict hourly occupancy levels of truck parking lots at highway rest areas using a dataset collected from digital monitoring systems in Poland. …”
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Deep learning-based strategies for evaluating and enhancing university teaching quality by Ying Gao

“…The research process involves multiple complex stages, including data collection, preprocessing, feature extraction, model construction, training, validation, and results analysis. …”
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Design of Intrusion Detection and Response Mechanism for Power Grid SCADA Based on Improved LSTM and FNN by Yu Huang, Liangyuan Su

“…To improve the accuracy of such systems, the study first uses sequence feature construction algorithms to explicitly represent sequence feature information. …”
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Radiomics-based machine learning for automated detection of Pneumothorax in CT scans. by Hanieh Alimiri Dehbaghi, Karim Khoshgard, Hamid Sharini, Samira Jafari Khairabadi, Farhad Naleini

“…The used machine learning algorithms are Gradient Tree Boosting (GBM), eXtreme Gradient Boosting (XGBoost), and Light GBM. …”
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A novel method for asynchronous source localisation based on time of arrival measurements by Huijie Zhu, Sheng Liu, Zhiqiang Yao, Moses Chukwuka Okonkwo, Zheng Peng

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Handwriting Difficulties: A Review of Recent Advances in the Identification and Intervention by Suatmi Murnani, Kazuharu Hashitsume, Tomohiko Igasaki

“…Rather than proposing a new method or computational framework, it highlights trends, challenges, and opportunities in current research. We systematically reviewed 107 primary studies published between 2019 and 2024, sourced from IEEE Xplore and SpringerLink. …”
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Artificial neural networks-based multi-objective optimization of immersion cooling battery thermal management system using Hammersley sampling method by Muhammed Donmez, Mehmet Ihsan Karamangil

“…This research optimizes lithium-ion battery module cooling through immersion cooling, addressing pressure drop and after discharge average cell temperature. …”
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Predicting cancer risk using machine learning on lifestyle and genetic data by Mohamed Abdelmoaty Ahmed, Ahmed AbdelMoety, Asmaa Mohamed Ahmed Soliman

“…Nine supervised learning algorithms were evaluated and compared, including Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), Support Vector Machines (SVMs), and several ensemble methods. …”
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Crash severity prediction using a virtual geometry-group-based deep learning approach with images-based feature representation by Nanon Sonnatthanon, Kasem Choocharukul

“…Accurate prediction of accident severity is essential for developing effective road safety interventions. While previous research has explored various statistical and machine learning models, their predictive performance has been limited due to a primary focus on accurate metrics and the challenges posed by discrete accident data. …”
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