An Intelligent LoRaWAN-Based IoT Device for Monitoring and Control Solutions in Smart Farming Through Anomaly Detection Integrated With Unsupervised Machine Learning by Maram Fahaad Almufareh, Mamoona Humayun, Zulfiqar Ahmad, Asfandyar Khan

“…Predominantly, the study also indicates precision in the temperature variation prediction model through the use of the predictive model based on the linear regression and random forest algorithms. …”
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An Efficient Evolutionary Task Scheduling/Binding Framework for Reconfigurable Systems by A. Al-Wattar, S. Areibi, G. Grewal

“…The framework utilizes an Island Based Genetic Algorithm flow that optimizes several objectives including performance, area, and power consumption. …”
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Enhancing Ophthalmic Diagnosis and Treatment with Artificial Intelligence by David B. Olawade, Kusal Weerasinghe, Mathugamage Don Dasun Eranga Mathugamage, Aderonke Odetayo, Nicholas Aderinto, Jennifer Teke, Stergios Boussios

“…Furthermore, AI is being utilized to develop personalized treatment plans by analyzing large datasets to predict individual responses to therapies, thus optimizing patient outcomes and reducing healthcare costs. …”
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Application of business analysis tools in company management by A. Yu. Orlova, A. A. Sorokin, D. G. Lovyannikov

“…We have developed an algorithm for the implementation of a business intelligence system and for this purpose built models in the EPC AS-IS and TO-BE notation. …”
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Free-form型机床的切齿优化（一）——优化模型的建立 by 张艳红, 郭九生, 王小椿

“…In this paper, Free-form style machine tool setting parameters is analyzed, and a mathematical model of optimal synthesis is established. Keeping the predetermined second-order contact parameters unchanged and optimizing third-order contact, this model can meanwhjle optimize the forth-order contact parameters, improving quality of the meshing. …”
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Integrating Positron Emission Tomography Combined with Computed Tomography Imaging into Advanced Radiation Therapy Planning: Clinical Applications, Innovations, and Challenges by Subhash Chand Kheruka, Anjali Jain, M. Sharjeel Usmani, Naema Al-Maymani, Noura Al-Makhmari, Huda Al-Saidi, Sana Al-Rashdi, Anas Al-Balushi, Vipin Jayakrishnan, Khulood Al-Riyami, Rashid Al-Sukaiti, Raza Sayani

“…The review also addresses persistent barriers, including limited tracer specificity, spatial resolution constraints, integration complexity, and high implementation costs. Beyond technical discussions, we reflect on emerging ethical considerations, such as transparency in AI-driven planning, patient consent in algorithm-assisted treatment decisions, and the need for equitable access to PET/CT technologies. …”
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Predicting child mortality determinants in Uttar Pradesh using Machine Learning: Insights from the National Family and Health Survey (2019–21) by Pinky Pandey, Sacheendra Shukla, Niraj Kumar Singh, Mukesh Kumar

“…Four machine learning algorithms—Random Forests, Logistic Regression, K-Nearest Neighbors (KNN), and Naive Bayes—were applied alongside a traditional logistic regression model. …”
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Learning Deceptive Tactics for Defense and Attack in Bayesian–Markov Stackelberg Security Games by Julio B. Clempner

“…By leveraging Bayesian techniques, we aim to minimize the expected total discounted costs, thus optimizing decision-making in the security domain. …”
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Tire Pressure Monitoring System Using Feature Fusion and Family of Lazy Classifiers by Arpit Pandey, Sridharan Naveen Venkatesh, Prabhakaranpillai Sreelatha Anoop, B. R. Manju, Vaithiyanathan Sugumaran

“…The study examines autoregressive moving average (ARMA), histogram, and statistical features individually and in combinations (statistical‐histogram, histogram‐ARMA, statistical‐ARMA, and statistical‐histogram‐ARMA) to improve predictive accuracy. By integrating these features, the study aims to optimize predictive modeling of TPMS. …”
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Prediction of risk for acute kidney injury and its progression to mortality in obese patients admitted to ICU postoperatively by LI Qiang, LI Qiang, MU Guo, MU Guo, WANG Wenzhang

“…Conclusion‍　‍Risk predictive models for postoperative AKI and mortality in obese ICU patients are successfully constructed, and are valuable tools for clinicians to optimize early intervention and improve clinical outcomes for the patients. …”
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Deep Mining on the Formation Cycle Features for Concurrent SOH Estimation and RUL Prognostication in Lithium-Ion Batteries by Dongchen Yang, Weilin He, Xin He

“…By integrating diverse datasets with advanced algorithms and models, we perform correlation analyses of parameters such as capacity, voltage, temperature, pressure, and strain, enabling precise SOH estimation and RUL prediction. …”
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Deep learning radiomics nomogram predicts lymph node metastasis in laryngeal squamous cell carcinoma by Yun Liang, Yun Liang, Min He, Wenqing Chen, Wenqing Chen, Lizhen Li, Lizhen Li, Yumeng Dong, Yumeng Dong, Gang Liang, Hui Huangfu, Zengyu Jiang, Zengyu Jiang, Sheng He, Sheng He, Sheng He

“…Radiomics features were extracted from CT images, and 7 machine learning algorithms were used to develop 7 radiomics models, which were combined with deep learning features extracted from the ResNet50 deep learning network to form deep learning radiomics (DLR) models. …”
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Research on the Virtual Coupling Technology for Urban Rail Transit Trains by YANG Weifeng, LEI Chengjian, HAN Chen, LI Qihe, XIE Xing

“…The paper additionally highlights the technical challenges faced in engineering applications, including the need for improved cooperative control algorithms, enhanced vehicle-to-vehicle communication mechanisms, and optimized safety braking models.…”
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Software and methodological support for additional professional courses: ideas, problems, monitoring by O. D. Prokhorenko, S. V. Morin, O. A. Kozyreva

“…By building prospects for theorizing and implementing ideas for improving the quality of modeling and using software and methodological support for further education courses, we can distinguish in the integrative representation of the direction and prospects of an individual’s achievements three types of solving professional and pedagogical problems theorized in the work (algorithmic, creative-stimulative and innovative-promising).…”
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Elastic regularization networks for enhanced UAV visual tracking by Qingjiao Meng, Ji Li, Yan Jin, Zhaotian Deng

“…On the DTB70 dataset, the proposed method achieves a precision of 0.747 and a success rate of 0.789, representing improvements of 1% and 2.9%, respectively, over the STRCF algorithm. …”
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Research on Hybrid Wind Speed Prediction System Based on Artificial Intelligence and Double Prediction Scheme by Ying Nie, He Bo, Weiqun Zhang, Haipeng Zhang

“…Regarding point prediction in the developed double prediction system, a novel nonlinear integration method based on a backpropagation network optimized using the multiobjective evolutionary algorithm based on decomposition was successfully implemented to derive the final prediction results, which enable further improvement of the accuracy of point prediction. …”
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Multiobjective Synchronous Control of Heavy-Duty Vehicles Based on Longitudinal and Lateral Coupling Dynamics by Yongjie Lu, Tongtong Wang, Hangxing Zhang

“…But the vertical and lateral dynamics equations and controls system of the vehicle are always independent of each other, and the multiobjective control is generally achieved through the coordination of control algorithms. In this paper, taking the dynamic load of the tire as a link, the vertical dynamic model and the lateral dynamic model of heavy-duty vehicle are coupled. …”
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CTAB modified SnO₂ PEDOT PSS heterojunction humidity sensor with enhanced sensitivity stability and machine learning evaluation by Poundoss Chellamuthu, Kirubaveni Savarimuthu, M Gulam Nabi Alsath, R. Krishnamoorthy, Yuvaraj T, Feras Alnaimat, Mohammad Shabaz

“…Furthermore, to validate real-time application feasibility, machine learning (ML) algorithms were implemented to model and predict sensor behavior. …”
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Artificial Intelligence in Glioblastoma—Transforming Diagnosis and Treatment by Alen Rončević, Nenad Koruga, Anamarija Soldo Koruga, Robert Rončević

“…In treatment planning, AI could improve approaches by optimizing surgical resection, radiotherapy regimen, and chemotherapy protocols. …”
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Ensemble Transformer–Based Detection of Fake and AI–Generated News by Md. Ishraquzzaman, Mohammed Ashraful Islam Chowdhury, Shahreen Rahman, Riasat Khan

“…The proposed ensemble model is optimized by applying model pruning (reducing parameters from 265M to 210M, improving training time by 25%) and dynamic quantization (reducing model size by 50%, maintaining 95.68% accuracy), enhancing scalability and efficiency while minimizing computational overhead. …”
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