Role,application and challenges of IoT in smart EV charging management:a review by Tripti Kunj, Kirti Pal

“…Additionally, the paper emphasizes the importance of adaptive algorithms and machine learning models for predictive maintenance and efficient resource allocation. …”
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Fault-Tolerance Distributed Control Plane for Software Defined Networks by Vasily N. Pashkov

“…The proactive backup controller allocation algorithm which allows to minimize the time to repair in the case of a single controller instance failure is discussed. …”
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Identification of patients at risk of new onset heart failure: Utilizing a large statewide health information exchange to train and validate a risk prediction model. by Son Q Duong, Le Zheng, Minjie Xia, Bo Jin, Modi Liu, Zhen Li, Shiying Hao, Shaun T Alfreds, Karl G Sylvester, Eric Widen, Jeffery J Teuteberg, Doff B McElhinney, Xuefeng B Ling

“…<h4>Conclusions</h4>Utilizing machine learning modeling techniques on passively collected clinical HIE data, we developed and validated an incident-HF prediction tool that performs on par with other models that require proactively collected clinical data. Our algorithm could be integrated into other HIEs to leverage the EMR resources to provide individuals, systems, and payors with a risk stratification tool to allow for targeted resource allocation to reduce incident-HF disease burden on individuals and health care systems.…”
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Modified Lagrangian Methods for Separable Optimization Problems by Abdelouahed Hamdi, Aiman A. Mukheimer

“…The proposed scheme is based on a class of modified Lagrangians combined with the allocation of resources decomposition algorithm. Under mild assumptions, we show that the method generates convergent primal-dual sequences.…”
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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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Development and validation of an interpretable multi-task model to predict outcomes in patients with rhabdomyolysis: a multicenter retrospective cohort studyResearch in context by Chunli Liu, Jie Shi, Fengjuan Wang, Duo Li, Yu Luo, Bofan Yang, Yunlong Zhao, Li Zhang, Dingwei Yang, Heng Jin, Jie Song, Xiaoqin Guo, Haojun Fan, Qi Lv

“…Early and accurate prediction of acute kidney injury (AKI), disease severity, renal replacement therapy (RRT) requirements, and mortality risk is essential for timely identification of high-risk individuals, personalized treatment planning, and optimal allocation of healthcare resources. We aimed to develop and externally validate an interpretable multi-task machine learning (ML) model to predict four clinical outcomes in patients with rhabdomyolysis: AKI, disease severity, the need for RRT, and in-hospital mortality. …”
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Distributed congestion control strategy using network utility maximization theory in VANET by Guozhen TAN, Guodong HAN, Fuxin ZHANG, Nan DING, Mingjian LIU

“…Cooperative vehicle safety system (CVSS) rely on periodical beacons to track neighboring vehicles.High traffic density often causes channel congestion,seriously damaging the performance of CVSS.Existing congestion control strategies aim to ensure the performance in network layer,without considering the service requirements of vehicles in different driving contexts.To solve the problem,a distributed congestion control strategy using network utility maximization (NUM) theory was proposed.First of all,the NUM model for channel resource allocation was introduced.A utility function reflecting vehicle’s safety requirements was proposed in the model.Then under the condition of fixed transmit powers,a optimization problem of channel resource allocation was proposed.Lastly,to solve the optimization problem,a distributed congestion control algorithm named utility-based rate congestion control (UBRCC) algorithm was designed,the algorithm worked out the optimal beaconing rate by updating vehicle’s congestion price,realizing the resource allocation according to vehicle’s safety requirements.Simulation results validate that UBRCC algorithm can efficiently control channel congestion,reduce transmission delay,ensure reliable data transmission and satisfies the requirements of safety applications.…”
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Does managing a retirement portfolio via rate of return, Sharpe ratio and social interaction generate good returns? An analysis for the years 2017 to 2020 by Nicollas Mateus Gomes, Helberte João França Almeida, Rafael Jasper Feltrin, Guilherme de Oliveira

“…Innovatively, the machine learning algorithm optimizes the portfolio allocation using reinforcement learning, which rewards good decisions and punishes bad decisions based on individual and social criteria. …”
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Group Stable Matching Problem in Freight Pooling Service of Vehicle–Cargo Matching Platform by Linlin Kong, Min Huang

“…As a result, they significantly improve the intelligence and precision of logistics resource allocation. However, at the current stage, vehicle–cargo matching platforms rarely promote freight pooling services, leading to resource underutilization. …”
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Two-layer energy optimization of HVAC system in a cement factory building by Xiaoquan Lu, Kaijie Fang, Yuqi Zhou, Ju Sheng, Hanmiao Chen

“…Finally, a typical case of a double-story model of a cement factory office building using the GA algorithm was compared and verified, showing the effectiveness of the proposed model.…”
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Joint Caching and Computation in UAV-Assisted Vehicle Networks via Multi-Agent Deep Reinforcement Learning by Yuhua Wu, Yuchao Huang, Ziyou Wang, Changming Xu

“…This requires balancing system energy consumption and resource allocation fairness while maximizing cache hit rate and minimizing task latency. …”
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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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Microgrid Resilience Enhancement with Sensor Network-Based Monitoring and Risk Assessment Involving Uncertain Data by Tangxiao Yuan, Kossigan Roland Assilevi, Kondo Hloindo Adjallah, Ayité Sénah A. Ajavon, Huifen Wang

“…This paper focuses on enhancing the resilience of microgrids—localized power systems that integrate multiple energy sources—against challenges such as natural disasters, technological obstacles, and human errors. …”
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IntelliGrid AI: A Blockchain and Deep-Learning Framework for Optimized Home Energy Management with V2H and H2V Integration by Sami Binyamin, Sami Ben Slama

“…The core of IntelliGrid AI is an advanced Q-learning algorithm that intelligently allocates energy resources. …”
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The methodology for calculating the number of teaching staff using economically feasible norms by L. A. Krokhmal, Yu. A. Kovshun

“…It has been established that the planned number of teaching staff is lower than the planned staffing level, calculated based on the volume of contact work hours, which makes it possible to encourage universities to restructure their curricula without going beyond funding limits.Conclusons and Relevance:the proposed approach allowed to conduct the calculation of teaching staff in accordance with the curriculum with a standardized volume of financial resources allocated to finance the remuneration of teaching staff of a specific educational program. …”
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Integrating Machine Learning for Enhanced Agricultural Productivity: A Focus on Bananas and Arecanut in the Context of India’s Economic Growth by B. S. Saruk, G. Mokesh Rayalu

“…Assist yield projections may provide governments and policymakers with valuable information to make well-informed choices about food security, import–export policies, and resource allocation. It facilitates national- and regional-level food supply planning. …”
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Efficient Priority Access to the Shared Commercial Radio with Offloading for Public Safety in LTE Heterogeneous Networks by Chafika Tata, Michel Kadoch

“…The results of the simulation showed that the allocation of radio resources via the courteous mechanism with offloading of new bearers to small cells reduces the rate of blocking bearers and delays the preemption of active bearers present in the LTE HetNets. …”
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Deep Learning-Driven Geospatial Modeling of Elderly Care Accessibility: Disparities Across the Urban-Rural Continuum in Central China by Yi Yu, Tian Dong

“…Taking Changsha as a case study, this research constructs an accessibility evaluation system based on the 15-min life circle theory, utilizing multi-source data. Spatial weighting characteristics of elderly care facility locations were analyzed through machine learning algorithms, and service coverage disparities between urban districts and suburban towns were assessed under 5-, 10-, and 15-min walking thresholds. …”
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Research on Stacking Distribution of Steel Plates Input Based on Improved Multi-objective Particle Swarm Optimization by ZHONG Chuanjie, CHENG Wenming, DU Run, GAO Xuchao, ZHANG Lin

“…The inventory balance index was established based on the standard deviation of the number of steel plates allocated to each reservoir to fully mobilize and balance material storage resources during operation. …”
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OPTIMASI PENJADWALAN PROYEK DENGAN PENYEIMBANGAN BIAYA MENGGUNAKAN KOMBINASI CPM DAN ALGORITMA GENETIKA by Riza Arifudin

“…The allocation of activities is determined based on the earliest start time and latest start time by taking into account the cost of resources in each period of the project. …”
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