Lossless Hyperspectral Image Compression in Comet Interceptor and Hera Missions with Restricted Bandwith by Kasper Skog, Tomáš Kohout, Tomáš Kašpárek, Antti Penttilä, Monika Wolfmayr, Jaan Praks

“…These results contribute valuable knowledge to the behavioral characteristics of both algorithms and provide insight for entities planning on using either algorithm on board planetary missions.…”
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THE USE OF QALY AS AN INTEGRAL MEASURE OF EFFECTIVENESS IN THE EVALUATION OF MEDICAL TECHNOLOGIES by N. Z. Musina, V. K. Fedyaeva

“…Its versatility enables better decision-making on financing the medical treatment within a limited budget. With this algorithm, the financial resources are allocated in such a way as to maximize the levels of QALY. …”
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Energy-Efficient Target Area Imaging for UAV-SAR-Based ISAC: Beamforming Design and Trajectory Optimization by Jiayi Zhou, Xiangyin Zhang, Kaiyu Qin, Feng Yang, Libo Wang, Deyu Song

“…To achieve maximum energy efficiency, we jointly optimized the UAV’s trajectory, velocity, communication beamforming, sensing beamforming, and power allocation. Numerical results demonstrate that compared to existing benchmarks and PSO algorithms, the proposed method significantly improves the energy efficiency of UAV-SAR-based ISAC systems through optimized trajectory design.…”
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A Multi-Objective Hybrid Game Pricing Strategy for Integrated Energy Operator-Load Aggregator Alliances Considering Integrated Demand Response by Yunlong Wang, Shan He

“…Secondly, to achieve cooperation between load aggregators, we use Nash bargaining theory to decompose the cooperative game model into two subproblems: maximizing alliance benefits and allocating cooperation benefits. Finally, we use the Alternative Direction Method of Multipliers (ADMM) algorithm combined with dichotomy and compromise programming theory to solve the model, to maximize the interests of all parties in the continuous interaction process. …”
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A Dynamic Just-in-Time Component Delivery Framework for Off-Site Construction by Tongguang Si, Hong Xian Li, Zhen Lei, Hexu Liu, SangHyeok Han

“…Traditionally, both parties tend to rely on internal resources or third-party resources to manage schedule changes, paying little attention to the optimisation of the component delivery process. …”
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Predicting Hospitalization Length in Geriatric Patients Using Artificial Intelligence and Radiomics by Lorenzo Fantechi, Federico Barbarossa, Sara Cecchini, Lorenzo Zoppi, Giulio Amabili, Mirko Di Rosa, Enrico Paci, Daniela Fornarelli, Anna Rita Bonfigli, Fabrizia Lattanzio, Elvira Maranesi, Roberta Bevilacqua

“…(1) Background: Predicting hospitalization length for COVID-19 patients is crucial for optimizing resource allocation and patient management. Radiomics, combined with machine learning (ML), offers a promising approach by extracting quantitative imaging features from CT scans. …”
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Excavation Safety Modeling Approach Using BIM and VPL by Numan Khan, Ahmad K. Ali, Miroslaw J. Skibniewski, Do Yeop Lee, Chansik Park

“…A set of rules-based algorithms was developed in commercially available software using visual programming language (VPL) that automatically generates geometric conditions in BIM and visualizes the potential risks and safety resources installation along with their quantity take-off and optimized locations. …”
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Next-Gen UAV-Satellite Communications: AI Innovations and Future Prospects by Sherief Hashima, Ahmad Gendia, Kohei Hatano, Osamu Muta, Mostafa S. Nada, Ehab Mahmoud Mohamed

“…Furthermore, it includes a case study demonstrating the effectiveness of multi-armed bandit (MAB) algorithms in optimizing resource allocation and decision-making processes for UAV-low Earth orbit (LEO) satellite communication scenarios, showcasing significant improvements in network performance. …”
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Trajectory Optimization for High-Speed and Long-Range Interceptor Based on Improved Adaptive hp Pseudospectral Method by Changxin Luo, Chijun Zhou, Jiong Li, Humin Lei

“…On the other hand, the curvature of the system state curve is used as the criterion to segment the original mesh nonuniformly so that more mesh points can be allocated where the curvature is large. These two points together ensure that the collocation point resources can be used more efficiently in the mesh refinement process. …”
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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

“…Abstract Background Prediction of postoperative patient-reported outcomes and risk for revision surgery after total hip arthroplasty (THA) or total knee arthroplasty (TKA) can inform clinical decision-making, health resource allocation, and care planning. 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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On the Modelling of the Mobile WiMAX (IEEE 802.16e) Uplink Scheduler by Darmawaty Mohd Ali, Kaharudin Dimyati

“…Packet scheduling has drawn a great deal of attention in the field of wireless networks as it plays an important role in distributing shared resources in a network. The process involves allocating the bandwidth among users and determining their transmission order. …”
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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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Comprehensive Load Regulation Strategy Considering Outage Risk in Power Tight Balance Scenarios by Shunjiang Wang, Zhongwei Li, Rongmao Wang, Huan Ma

“…Then, orderly consumption power (OCP) is determined by power balance analyzing and flexible resource accessing, reasonably allocated over the subsystems by considering the load types and energy efficiencies, and further specified by components of peak shifting, peak averting and power rationing. …”
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Preventing Health Risks Through Intelligent Medical Appointment Management Using Disease and Attendance Propensity by Fredy Troncoso-Espinosa, Guillermo Latorre-Nunez, Catalina Valenzuela-Nunez, Juan San Martin-Duran

“…Patients scheduled by the intelligent model show higher mean propensities to attend appointments and to develop diseases, ensuring that medical resources are allocated efficiently to those in greatest need. …”
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Dynamic energy consumption monitoring and scheduling for green buildings: A comprehensive approach by Hua Zheng, Pengming Wang

“…The scheduling strategy adopts a dynamic approach based on priority to flexibly allocate energy resources to ensure the coordinated operation of various energy systems in the building. …”
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Modeling Energy Access Challenges in Europe: A Neural Network Approach to Predicting Household Heating Inadequacy Using Macro-Energy Indicators by Monika Kulisz, Justyna Kujawska, Michał Cioch, Wojciech Cel

“…The findings highlight the potential of machine learning to predict the percentage of the population unable to keep their houses adequately warm, enabling policymakers to allocate resources more efficiently and target vulnerable populations. …”
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Cooperative control method for multi-agent ground fracturing truck group based on offline reinforcement learning by RuYi Wang, HuiShen Jiao, YingCheng Tian, Yi Zhao, SiQi Wang, Ke Zhang, Bo Huang, QinRui Sun, DanDan Zhu

“…Abstract The increasing scale of unconventional oil and gas resource development has driven the demand for complex fracturing technologies. …”
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Forecasting dengue in Bangladesh using meteorological variables with a novel feature selection approach by Mahadee Al Mobin

“…The necessity for advanced forecasting mechanisms has never been more critical to enhance the effectiveness of vector control strategies and resource allocations. This study formulates a dynamic data pipeline to forecast dengue incidence based on 13 meteorological variables using a suite of state-of-the-art machine learning models and custom features engineering, achieving an accuracy of 84.02%, marking a substantial improvement over existing studies. …”
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Large Language Model-Assisted Reinforcement Learning for Hybrid Disassembly Line Problem by Xiwang Guo, Chi Jiao, Peng Ji, Jiacun Wang, Shujin Qin, Bin Hu, Liang Qi, Xianming Lang

“…Recycling end-of-life products is essential for reducing environmental impact and promoting resource reuse. In the realm of remanufacturing, researchers are increasingly concentrating on the challenge of the disassembly line balancing problem (DLBP), particularly on how to allocate work tasks effectively to enhance productivity. …”
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Bayesian optimization of hybrid quantum LSTM in a mixed model for precipitation forecasting by Yumin Dong, Huanxin Ding

“…Accurate forecasting is of great significance for reducing the impact of floods, optimizing crop planting plans, rationally allocating water resources, and ensuring traffic safety. …”
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