Integrating IoT sensors and machine learning for sustainable precision agroecology: enhancing crop resilience and resource efficiency through data-driven strategies, challenges, an... by Val Hyginus Udoka Eze, Esther Chidinma Eze, George Uwadiegwu Alaneme, Pius Erheyovwe BUBU, Ezekiel Oluwaseun Ejiofor Nnadi, Michael Ben Okon

“…Coupled with advanced ML algorithms, this data facilitates predictive analytics and real-time decision-making, optimizing resource utilization for irrigation, pest control, and yield prediction. …”
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Hybrid Automata-Based Control Framework for Real-Time Optimization in Space-Based Solar Power Transmission by Patil Ankita, Ranjan Mritunjay, Deore Kalyani, Sonje Pranjal, Patil Kiran, Patil Rutuja

“…While usual machine learning algorithms may predict the production of energy, they cannot respond sufficiently in real time to alter according to dynamic environmental conditions. …”
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USE OF ARTIFICIAL INTELLIGENCE TO IDENTIFY AND CORRECT MISCONCEPTIONS ABOUT RADIATION by Oleksandr Tymoshchuk

“…AI tools, including natural language processing models for text analysis and machine learning algorithms for misconceptions classification, were used to provide personalised feedback and targeted corrective information. …”
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DEVELOPMENT OF METHODOLOGY FOR DESIGNING TESTABLE COMPONENT STRUCTURE OF DISCIPLINARY COMPETENCE by Vladimir I. Freyman

“…The research findings can help promoting learning efficiency increase, a choice of adequate control devices, accuracy of assessment, and also efficient use of personnel, temporal and material resources of higher education institutions. Proposed algorithms, methods and approaches to procedure of control results organization and realization of developed competences and its components can be used as methodical base while designing the computerassisted system for educational process management and quality supervision of graduates’ competences. …”
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The Effect of Producing with IT Project Pilot Scheme on 5th-Grade Students' Problem-Solving Skills and Attitudes towards Coding by Taliye Cehdioğlu, Kerem Kılıçer

“…This study aimed to examine the effect of coding and 3D design education given within the scope of Producing with IT Project Pilot Scheme on 5th-grade students' problem-solving skills and attitudes towards coding. …”
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Method of terminal control in ascent segment of unmanned aerial vehicle with ballistic phase by N. Y. Polovinchuk, S. V. Ivanov, M. Y. Zhukova, D. G. Belonozhko

“…Such algorithms have good convergence and injection accuracy due to the prediction of parameters during the flight at a shorter time interval.Discussion and Conclusions. …”
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Current Topics on the Integration of Artificial Intelligence in the Histopathological and Molecular Diagnosis of Uveal Melanoma by Serena Salzano, Giuseppe Broggi, Andrea Russo, Teresio Avitabile, Antonio Longo, Rosario Caltabiano, Manuel Mazzucchelli

“…Particular focus is placed on its role in histopathological assessments of UM, where algorithms facilitate the analysis of whole-slide images (WSIs). …”
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Advanced machine learning artificial neural network classifier for lithology identification using Bayesian optimization by Saâd Soulaimani, Saâd Soulaimani, Ayoub Soulaimani, Kamal Abdelrahman, Abdelhalim Miftah, Mohammed S. Fnais, Biraj Kanti Mondal

“…A key feature of this strategy is leveraging population search algorithms to fine-tune hyperparameters, thus boosting prediction accuracy. …”
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Cascade Machine Learning Approach Applied to Short-Term Medium Horizon Demand Forecasting by Bruno Brentan, Ariele Zanfei, Martin Oberascher, Robert Sitzenfrei, Joaquin Izquierdo, Andrea Menapace

“…The LSTM model estimates, utilizing a univariate approach, the hourly forecasting of water demand for the entire available dataset and the minimum night flow. The algorithm considers various time series sizes for each DMA and predicts the water demand values for each hour throughout the week. …”
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DESIGN AND FIELD TEST OF FUZZY PID CONTROL SYSTEM OF ACTIVE SUSPENSION FOR BLUEBERRY HARVESTER by Cun Chu, Haibin Wang, Ruiqing Zhang, Zhiyong Chu

“…In field tests, these reductions were 36.51%, 33.84%, and 30.21%, respectively. …”
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A continuous multi-night sleep database for exploring sleep structure similarity by Shaofei Ying, Junze Fu, Lin Wang, Haokai Zhang, Yue Yu, Hongqiong Wang, Jiaxin Xie, Tiejun Liu

“…It provides valuable opportunities to investigate the physiological mechanisms of sleep structure continuity, advancing sleep features recognition and prediction algorithms, and designing individualised templates for closed-loop sleep stimulation. …”
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Role of Artificial Intelligence and Machine Learning to Create Predictors, Enhance Molecular Understanding, and Implement Purposeful Programs for Myocardial Recovery by Frederick M. Lang, Benjamin C. Lee, Dor Lotan, Mert. R. Sabuncu, Veli K. Topkara

“…By identifying novel patterns in high-dimensional data, artificial intelligence (AI) and machine learning (ML) algorithms can enhance the identification of key predictors and molecular drivers of myocardial recovery. …”
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FBiLSTM-Attention short-term load forecasting based on fuzzy logic by Yan ZHANG, Zepeng KANG, Xiaozhi GAO, Nan YANG, Zhaolei WANG

“…Aiming at the problem of high uncertainty in power load data due to various factors, a fuzzy logic based FBiLSTM Attention short-term load forecasting model was proposed by combining the uncertainty of load data with deep learning algorithms to improve the accuracy of load forecasting. …”
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WEST GCN-LSTM: Weighted stacked spatio-temporal graph neural networks for regional traffic forecasting by Theodoros Theodoropoulos, Angelos-Christos Maroudis, Uwe Zdun, Antonios Makris, Konstantinos Tserpes

“…Furthermore, the aforementioned information is included via two novel dedicated algorithms, the Shared Borders Policy and the Adjustable Hops Policy. …”
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Anomaly Detection in IoMT Environment Based on Machine Learning: An Overview by Peyman Vafadoost Sabzevar, Hamidreza Rokhsati, Alireza Chamansara, Ahmad Hajipour

“…The purpose of anomaly detection is to develop methods that can detect attackers' attacks and prevent them from happening again. Algorithms and methods based on statistics play an important role in predicting and diagnosing anomalies. …”
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Safe and Robust Binary Classification and Fault Detection Using Reinforcement Learning by Josh Netter, Kyriakos G. Vamvoudakis, Timothy F. Walsh, Jaideep Ray

“…In this paper, we propose a learning-based method utilizing the Soft Actor-Critic (SAC) algorithm to train a binary Support Vector Machine (SVM) classifier. …”
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sedInterFoam 1.0: a three-phase numerical model for sediment transport applications with free surfaces by A. Mathieu, Y. Kim, T.-J. Hsu, C. Bonamy, J. Chauchat

“…Using sedInterFoam, four test cases are successfully reproduced to validate the free-surface evolution algorithm's implementation, mass conservation of sediment and fluid phases, and predictive capabilities and to demonstrate its potential in modeling a broader range of coastal applications with sediment transport dominated by surface waves.…”
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Velocity-Constraint Kalman Filtering for Enhanced Bubble Tracking in Motion-Compensated Ultrasound Localization Microscopy by Yifei Zhu, Lingyin Jiang, Qi Zhang, Jun Yin, Bingze Du, Guofeng Zhang, Haijun Zhang, Bo Ding, Han Lin, Honghui Xue, Xiasheng Guo, Xiao-Yang Zhang, Jing-Ning Zhu, Dong Zhang, Juan Tu, Ning Gu

“…Unlike traditional methods relying on observed bubble positions, the proposed algorithm combined statistical information derived from historical data with Kalman-filter-predicted positions to enable more accurate bubble localization. …”
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Exploring the comprehensive integration of artificial intelligence in optimizing HVAC system operations: A review and future outlook by Shengze Lu, Shiyu Zhou, Yan Ding, Moon Keun Kim, Bin Yang, Zhe Tian, Jiying Liu

“…The main features of the AI technology are first introduced. The main algorithms of supervised learning, reinforcement learning, and deep learning are then analyzed in the fields of air conditioning operation optimization, energy consumption prediction and control, indoor environmental protection, and fault detection and diagnosis. …”
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Advances in Federated Learning: Applications and Challenges in Smart Building Environments and Beyond by Mohamed Rafik Aymene Berkani, Ammar Chouchane, Yassine Himeur, Abdelmalik Ouamane, Sami Miniaoui, Shadi Atalla, Wathiq Mansoor, Hussain Al-Ahmad

“…This review paper explores the foundational concepts, and architectural variations of FL, prominent aggregation algorithms like FedAvg, FedProx, and FedMA, and diverse innovative applications in thermal comfort optimization, energy prediction, healthcare, and anomaly detection within smart buildings. …”
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