Empowering Sustainability: The Crucial Role of IoT-Enabled Distributed Learning Systems in Reducing Carbon Footprints by Anjana M S, Aryadevi Remanidevi Devidas, Maneesha Vinodini Ramesh

“…Transitioning to cleaner energy sources and improving energy efficiency are essential steps to reduce the environmental impact of electricity generation. …”
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Enhancing Typhoid Fever Diagnosis Based on Clinical Data Using a Lightweight Machine Learning Metamodel by Fariha Ahmed Nishat, M. F. Mridha, Istiak Mahmud, Meshal Alfarhood, Mejdl Safran, Dunren Che

“…Its reliance on accessible clinical parameters ensures practical applicability and scalability, potentially improving patient outcomes and aiding in disease control. …”
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Prediction of microbe-drug associations using a CNN-Bernoulli random forest model by Zihao Song, Qingnuo Li, Jincheng Zhao, Qinggang Bu, Zekang Bian, Jia Qu

“…This approach enhances computational efficiency and improves the model’s ability to capture complex patterns, thereby increasing the precision and interpretability of drug response predictions. …”
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Using machine learning to predict the rupture risk of multiple intracranial aneurysms by Junqiang Feng, Chunyi Wang, Yu Wang, He Liu, He Liu

“…By analyzing detailed morphological and anatomical parameters, our model provides a tailored approach to rupture risk assessment in MIAs, offering potential improvements over existing methods.MethodsTo address dataset imbalance, we conducted five-fold cross-validation. …”
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Structural-methodical model of computer program for control of theoretical knowledge of cadets by V. V. Bulgakov

“…Basically, readymade computer programs are used, which are universal and are intended for wide application, without taking into account the specifics of Universities.Research and development of structural and methodological model was carried out with the use of theoretical analysis of the provisions of pedagogy on the problems of control, evaluation and analysis of the level of theoretical knowledge, methods of theory of algorithms and decision-making, methods of synthesis and analysis of information processes. …”
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Green Video Transcoding in Cloud Environments Using Kubernetes: A Framework With Dynamic Renewable Energy Allocation and Priority Scheduling by B. M. Beena, Prashanth Cheluvasai Ranga, A. Vinitha Chowdary, Rohan Gamidi, M. Hemasri, Tejaswi Muppala

“…Conserving energy and improving energy efficiency in cloud servers is a major challenge. …”
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The Use of Artificial Intelligence in Medical Diagnostics: Opportunities, Prospects and Risks by Nataliia Sheliemina

“…The AI integration in healthcare can revolutionise the industry by improving patient outcomes, optimising resource allocation, and reducing operational costs. …”
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Fine-Tuning Retrieval-Augmented Generation with an Auto-Regressive Language Model for Sentiment Analysis in Financial Reviews by Miehleketo Mathebula, Abiodun Modupe, Vukosi Marivate

“…Future initiatives will focus on incorporating a wider range of data sources and improving the system’s ability to express nuanced sentiments effectively, enhancing its usefulness in diverse real-world scenarios.…”
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A High Resolution Melting Analysis (HRM) PCR assay for the detection and identification of Old World Leishmania species. by Yusr Saadi-Ben Aoun, Hejer Souguir, Hamed Chouaieb, Mongia Kraiem, Insaf Bel Hadj Ali, Ahmed S Chakroun, Florian Noguier, Akila Fathallah-Mili, David Piquemal, Ikram Guizani

“…Its integration into molecular diagnostic algorithms for CL or in eco-epidemiological studies holds promise for improving disease management and control.…”
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Predicting Quality of Life in People Living with HIV: A Machine Learning Model Integrating Multidimensional Determinants by Meilian Xie, Zhiyun Zhang, Yanping Yu, Li Zhang, Jieli Zhang, Dongxia Wu

“…Abstract Objective With survival steadily improving among people living with HIV(PLWH), quality of life (QoL) has emerged as the ultimate benchmark of therapeutic success. …”
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Intelligent Wireless Power Scheduling for Lunar Multienergy Systems: Deep Reinforcement Learning for Real-Time Adaptive Beam Steering and Vehicle-to-Grid Energy Optimization by Thomas Tongxin Li, Shuangqi Li, Cynthia Xin Ding, Zhaoyao Bao, Mohannad Alhazmi

“…A case study simulating a 30-day mission near Shackleton Crater evaluates the effectiveness of the AI–driven WPT system, demonstrating a 54.6% reduction in energy downtime and a 41.3% improvement in beam alignment efficiency compared to static power scheduling methods. …”
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Inferring Mechanical Properties of Wire Rods via Transfer Learning Using Pre-Trained Neural Networks by Adriany A. F. Eduardo, Gustavo A. S. Martinez, Ted W. Grant, Lucas B. S. Da Silva, Wei-Liang Qian

“…The primary objective of this study is to explore how machine learning techniques can be incorporated into the analysis of material deformation. Neural network algorithms are applied to the study of mechanical properties of wire rods subjected to cold plastic deformations. …”
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Bioconvergence: advancing biosensors with nanotechnology for real-time health monitoring by Rosaline Mishra, Sakshi Minocha, Radha Goel, Praveen Kumar Gaur, Kanak Lata, Rashmi Singh

“…This technology could lead to a more efficient and individualised healthcare system by improving disease diagnosis, treatment, and overall patient outcomes.…”
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Optimizing photocatalytic dye degradation: A machine learning and metaheuristic approach for predicting methylene blue in contaminated water by Yunus Ahmed, Keya Rani Dutta, Sharmin Nahar Chowdhury Nepu, Meherunnesa Prima, Hamad AlMohamadi, Parul Akhtar

“…This work points out the possibility of taking complete advantage of advanced machine learning algorithms along with metaheuristics optimization in improving photocatalytic processes, hence opening a bright avenue for real applications in water treatment.…”
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Current Status of Application of Spaceborne GNSS-R Raw Intermediate-Frequency Signal Measurements: Comprehensive Review by Qiulan Wang, Jinwei Bu, Yutong Wang, Donglan Huang, Hui Yang, Xiaoqing Zuo

“…Finally, the existing research results are summarized, and suggestions for future prospects are put forward, including improving the accuracy of signal processing and reflection signal analysis, developing more advanced algorithms and technologies, and so on, to achieve more accurate and reliable Earth observation and remote sensing applications. …”
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Machine Learning–Based Analysis of Lifestyle Risk Factors for Atherosclerotic Cardiovascular Disease: Retrospective Case-Control Study by Hye-Jin Kim, Heeji Choi, Hyo-Jung Ahn, Seung-Ho Shin, Chulho Kim, Sang-Hwa Lee, Jong-Hee Sohn, Jae-Jun Lee

“…However, the light gradient boosting model demonstrated better performance in accuracy, recall, and F1 ConclusionsAnalyzing lifestyle behavioral factors in ASCVD risk with an ML model improves the predictive performance compared to traditional models. …”
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A machine learning model for predicting acute respiratory distress syndrome risk in patients with sepsis using circulating immune cell parameters: a retrospective study by Kaihuan Zhou, Lian Qin, Yin Chen, Hanming Gao, Yicong Ling, Qianqian Qin, Chenglin Mou, Tao Qin, Junyu Lu

“…Early identification of patients with sepsis at high risk of developing ARDS is crucial for timely intervention, optimization of treatment strategies, and improvement of clinical outcomes. However, traditional risk prediction methods are often insufficient. …”
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Tell me y: anticipation of sex discrepancies in cell-free DNA testing due to maternal genetic abnormalities: a case report by Nuria Balaguer, Emilia Mateu-Brull, Jose Antonio Martínez-Conejero, Ana Cervero, Roser Navarro, Jorge Jiménez-Almazán, Miguel Milán

“…These findings suggest the need for improvements to current bioinformatics pipelines to identify and exclude possible maternal perturbations from the classification algorithms used for aneuploidy and sex calls.…”
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Predicting patient outcomes and risk for revision surgery after hip and knee replacement surgery: study protocol for a comparison of modelling approaches using the Swiss National J... by Léonie Hofstetter, Nathalie Schweyckart, Christof Seiler, Christian Brand, Laura C. Rosella, Mazda Farshad, Milo A. Puhan, Cesar A. Hincapié

“…Machine learning (ML) algorithms are increasingly used as an alternative to traditional logistic regression (LR) prediction, but there is uncertainty about their superiority in overall model performance. …”
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Optimized Identification of Sentence-Level Multiclass Events on Urdu-Language-Text Using Machine Learning Techniques by Somia Ali, Uzma Jamil, Muhammad Younas, Bushra Zafar, Muhammad Kashif Hanif

“…Our results were compared to previously reported techniques that used traditional models, highlighting the significant improvements offered by our approaches. The novelty of this research lies in the inclusion of 16 event categories to broaden coverage and the implementation of the SMFCNN and transformer-based algorithms. …”
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