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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Abiotic drivers of activity in a large, free-ranging, freshwater teleost, Murray cod (Maccullochella peelii). by Jason D Thiem, Ian J Wooden, Lee J Baumgartner, Gavin L Butler, Jamin Forbes, Matthew D Taylor, Robyn J Watts

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Predicting clinical outcomes at hospital admission of patients with COVID-19 pneumonia using artificial intelligence: a secondary analysis of a randomized clinical trial by Caio César Souza Conceição, Camila Marinelli Martins, Mayck Medeiros Silva, Hugo Caire de Castro Faria Neto, Davide Chiumello, Davide Chiumello, Davide Chiumello, Patricia Rieken Macedo Rocco, Fernanda Ferreira Cruz, Pedro Leme Silva

“…BackgroundPredicting clinical improvement after hospital admission in patients with COVID-19 is crucial for effective resource allocation. Machine-learning tools can help identify patients likely to show clinical improvement based on real-world data. …”
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Performance Assessment of a Rehabilitation Transportation Reservation Matching Service with Market Design Mechanisms by Chen Yu Lan, Chih Peng Chu, Cheng Chieh (Frank) Chen

“…This study applies the market design theory to match the rehabilitation buses with the requests of patients, so as to improve resource utilization efficiency in rural areas. The developed market design mechanisms aim to allocate resources to those who need them most in a matching manner, by using the deferred acceptance algorithm and the top trading cycle approach. …”
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Research on spectrum sensing technologies based on goodness of fit by Guangyue LU, Cai XU, Yinghui YE, Yin MI

“…Cognitive radio technology has achieved the dynamic allocation of spectrum resources,and improves the utilization rate of spectrum resources.Accurate and efficient spectrum sensing is the key step in cognitive radio.Developing a fast and high-performance spectrum sensing method has become an urgent problem to be solved.In recent years,goodness of fit（GOF）theory has been applied widely in the field of spectrum sensing and the effective spectrum sensing technology under small sample point has been implemented.Therefore,the research on spectrum sensing technology based on GOF has very significant value.The development process of GOF in areas of cognitive radio spectrum sensing was summarized,its basic principle common fitting criterion and fitting object were introduced.The simulation comparison of the algorithm was carried under the Gaussian channel and its prospects of further research was forecasted finally.…”
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Token Money or Cryptocurrency: technological Content and Economic Essence by A. V.  Varnavskiy

“…The paradox of the algorithmic guarantor, reflecting the absence of the need for formalization of algorithmic informal institutions, is formulated. …”
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Joint Encryption and Optimization for 6G MEC-Enabled IoT Networks by Manzoor Ahmed, Wali Ullah Khan, Fatma S. Alrayes, Yahia Said, Ali M. Al-Sharafi, Mi-Hye Kim, Khongorzul Dashdondov, Inam Ullah

“…An optimization algorithm is introduced to address these challenges by jointly allocating resources, thereby optimizing throughput, conserving energy, and meeting latency benchmarks through dynamic system adaptation. …”
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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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Advances in Deep Learning Applications for Plant Disease and Pest Detection: A Review by Shaohua Wang, Dachuan Xu, Haojian Liang, Yongqing Bai, Xiao Li, Junyuan Zhou, Cheng Su, Wenyu Wei

“…To address these challenges, deep learning technologies have emerged as a promising solution for the accurate and timely identification of plant diseases and pests, thereby reducing crop losses and optimizing agricultural resource allocation. By leveraging its advantages in image processing, deep learning technology has significantly enhanced the accuracy of plant disease and pest detection and identification. …”
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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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Energy Harvesting for Throughput Enhancement of Cooperative Wireless Sensor Networks by Van-Dinh Nguyen, Chuyen T. Nguyen, Oh-Soon Shin

“…We then propose an iterative power allocation algorithm which converges to a locally optimal solution at a Karush-Kuhn-Tucker point. …”
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A Deep Learning Model for ERP Enterprise Financial Management System by Hui Zhang

“…The proposed model can help enterprises organize their limited resources, realize the scientific allocation of enterprise resources, and create more benefits for enterprises.…”
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Grouping control of electric vehicles based on improved golden eagle optimization for peaking by Yang Yu, Yuhang Huo, Shixuan Gao, Qian Wu, Mai Liu, Xiao Chen, Xiaoming Zheng, Xinlei Cai

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Fast fault diagnosis of smart grid equipment based on deep neural network model based on knowledge graph. by Lin Jun, Zhou Chenliang

“…It can not only meet the demand of users and realize the optimal allocation of resources, but also improve the safety, economy and reliability of power supply, it has become a major trend in the future development of electric power industry. …”
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Artificial intelligence in project management: A bibliometric analysis by Nurkhat Ibadildin, Zhaxat Kenzhin, Gaukhar Yeshenkulova, Rymkul Ismailova, Assel Nurguzhina, Samalgul Nassanbekova, Aiman Kadyrova

“…The analysis maps the evolution of AI-driven project management practices, focusing on resource allocation, risk management, and scheduling optimization. …”
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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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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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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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ISCCO: a deep learning feature extraction-based strategy framework for dynamic minimization of supply chain transportation cost losses by Yangyan Li, Tingting Chen

“…Additionally, ISCCO optimized goods allocation using a genetic algorithm enhanced integer linear programming model. …”
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Analyzing Method of the Absorption Capability of New Energy in Distribution Network with Consideration of Regional Self-discipline and Absorption Quality by Yan CHEN, Wei JIN, Wenbin WANG, Huibin LI, Shengfeng HAN, Kai JIA

“…Firstly, the strategy for implementing the self-discipline operation of the distribution network was unveiled, and the performance indices of self-discipline operation capability were created. Then, the optimal allocation model for the new energy absorption capability of the distribution network was constructed, and the operation behavior model of the distribution network satisfying self-discipline constraints was built based on energy storage, flexible load, and network reconstruction, and solved by the genetic algorithm. …”
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