The Analysis of the Possibility to Conduct Orbital Manoeuvres of Nanosatellites in the Context of the Maximisation of a Specific Operational Task by Magdalena Lewinska, Michal Kedzierski

“…The conclusions from the conducted analyses confirmed that an appropriate strategy of orbital manoeuvres may greatly improve the operational efficiency of the nanosatellite, while, at the same time, continuing to save fuel and energy. …”
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Integrating artificial intelligence in nanomembrane systems for advanced water desalination by Anbarasu Krishnan, Thanigaivel Sundaram, Beemkumar Nagappan, Yuvarajan Devarajan, Bhumika

“…The increasing global demand for clean drinking water calls for innovative approaches to optimize desalination processes, making them more sustainable and efficient. …”
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Forecasting motion trajectories of elbow and knee joints during infant crawling based on long–short-term memory (LSTM) networks by Jieyi Mo, Qiliang Xiong, Ying Chen, Yuan Liu, Xiaoying Wu, Nong Xiao, Wensheng Hou

“…It experimentally explores how different input and output time-frames affect prediction accuracy and sets the stage for future research focused on optimizing models and developing effective control strategies to improve assistive crawling devices.…”
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Prediction of porosity, hardness and surface roughness in additive manufactured AlSi10Mg samples. by Fatma Alamri, Imad Barsoum, Shrinivas Bojanampati, Maher Maalouf

“…Advanced machine learning techniques to predict part quality can improve repeatability and open additive manufacturing to various industries. …”
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Hybrid machine learning and physics-based model for estimating lettuce (Lactuca sativa) growth and resource consumption in aeroponic systems by Benedetta Fasciolo, Nicolò Grasso, Giulia Bruno, Paolo Chiabert

“…Despite these challenges, the hybrid model offers a promising solution for optimizing controlled environment agriculture, addressing critical challenges in modern agriculture by improving efficiency and sustainability.…”
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Deep Q-Networks for Minimizing Total Tardiness on a Single Machine by Kuan Wei Huang, Bertrand M. T. Lin

“…Due to its computational intractability, exact approaches such as dynamic programming algorithms and branch-and-bound algorithms struggle to produce optimal solutions for large-scale instances in a reasonable time. …”
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A new temporal locality-based workload prediction approach for SaaS services in a cloud environment by Wiem Matoussi, Tarek Hamrouni

“…The method will be implemented in order to simultaneously achieve a twofold benefit: obtain precise forecast results while optimizing response time. In this regard, we have chosen to control the computation time by dynamizing the size of the sliding window associated to the recent history to be analyzed, since the larger the size of the entry in the prediction model, the more the algorithmic complexity increases. …”
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Data-Driven Pavement Performance: Machine Learning-Based Predictive Models by Mohammad Fahad, Nurullah Bektas

“…This study concludes that integrating machine learning with finite element analysis provides further improvements in pavement performance predictions.…”
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A Novel Active RFID and TinyML based system for livestock Localization in Pakistan by Syed Atir Raza Shirazi, Maham Fatima, Abdul Wahab, Sadaf Ali

“…To realize the full potential of this unique Active RFID and TinyML-based livestock localization system in Pakistan, further research should focus on optimizing localization algorithms, enhancing TinyML models, and exploring interaction with upcoming technologies …”
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Leveraging Agent-Based Modeling and IoT for Enhanced E-Commerce Strategies by Mohamed Shili, Sajid Anwar

“…The key objective is to create a multi-agent system that optimizes interactions between IoT devices and e-commerce systems, thereby improving operational efficiency, adaptability, and user experience in online transactions. …”
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Sentiment Analysis Using Stacking Ensemble After the 2024 Indonesian Election Results by Andy Victor Pakpahan, Fahmi Reza Ferdiansyah, Robby Gustian, Muhammad Nur Faiz, Sukma Aji

“…In contrast, the stacking ensemble model achieved a significantly higher accuracy of 81.53%. This improvement highlights the effectiveness of ensemble learning in integrating different algorithmic perspectives to enhance predictive performance. …”
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Enhancing Autonomous Driving Perception: A Practical Approach to Event-Based Object Detection in CARLA and ROS by Jingxiang Feng, Peiran Zhao, Haoran Zheng, Jessada Konpang, Adisorn Sirikham, Phuri Kalnaowakul

“…In contrast, event-based cameras, which operate asynchronously and capture rapid changes with high temporal resolution and expansive dynamic range, offer a promising augmentation. While the previous research on event-based object detection has predominantly focused on algorithmic enhancements via advanced preprocessing and network optimizations to improve detection accuracy, the practical engineering and integration challenges of deploying these sensors in real-world systems remain underexplored. …”
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Increasing the noise immunity of radio receiving paths with automatic sensitivity control by Р. V. Zayats, I. Y. Malevich

“…Studies of various possible ASC structures have shown that with a proportional exchange of the transmission coefficient for the DR, an improvement in the noise immunity of the RRP is provided while maintaining a high sensitivity of the system. …”
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Enhancing healthcare AI stability with edge computing and machine learning for extubation prediction by Kuo-Yang Huang, Ying-Lin Hsu, Che-Liang Chung, Huang-Chi Chen, Ming-Hwarng Horng, Ching-Hsiung Lin, Ching-Sen Liu, Jia-Lang Xu

“…Notably, the edge-based architecture reduced server data transmissions by 83.33%, while improving system stability, resilience, and sustainability. …”
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Advanced Brain Tumor Segmentation With a Multiscale CNN and Conditional Random Fields by Ala Guennich, Mohamed Othmani, Hela Ltifi

“…The use of high-precision automatic algorithms for segmenting brain tumors has the potential to improve disease diagnosis, treatment monitoring, and large-scale pathological studies. …”
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Long Short-Term Memory-Based Computerized Numerical Control Machining Center Failure Prediction Model by Jintak Choi, Zuobin Xiong, Kyungtae Kang

“…When rolling pins are machining with CNC equipment, a sensor system is installed to collect acoustic data, analyze failure patterns, and apply RUL prediction algorithms. The AI-based predictive maintenance system developed ensures the reliability and operational efficiency of CNC equipment, while also laying the foundation for a smart factory monitoring platform, thus enhancing competitiveness in intelligent manufacturing environments.…”
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Challenges and Applications of Artificial Intelligence in Education: A Systematic Review by Saeid Arifnejad, Asadolah khadivi, Farhad Alipour

“…Additionally, it facilitates efficient teaching methodologies, automates grading and assessment, and optimizes resource allocation. The integration of AI can significantly improve the quality of education.Value: This research contributes to bridging the knowledge gap regarding AI applications in education while identifying key challenges for educators and policymakers.…”
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Understanding visitor flow and behaviour in developing tourism-service-oriented villages by space syntax methodologies: a case study of Tabian Rural Section of Qingshan Village, Ha... by Shuqin Wang, Yan Huang, Tianjie Li

“…This study innovatively combines space syntax models for extended application in the research of rural BEs, providing guidance for optimizing strategies to improve spatial configuration in homogeneous villages.…”
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A human pose estimation network based on YOLOv8 framework with efficient multi-scale receptive field and expanded feature pyramid network by Shaobin Cai, Han Xu, Wanchen Cai, Yuchang Mo, Liansuo Wei

“…Therefore, EE-YOLOv8 achieves the highest accuracy while maintaining the lowest parameter count and computational complexity among all analyzed algorithms. …”
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Energy-Efficient model for integrated berth allocation and quay crane management by Saeedeh Khalilpoor, Mehdi A. Kamran, Reza Babazadeh, Reza Kia

“…Several numerical experiments in different dimensions are defined and implemented with both algorithms. The results analysis gives an overall perspective, while both algorithms show their value and strong points and weaknesses in meeting demanding requirements of modern container terminal logistics. …”
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