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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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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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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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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Robust Planning for Hydrogen-Based Multienergy System Considering P2HH and Seasonal Hydrogen Storage by Shufan Wang, Dong Yang, Linglu Zhang, Lingzhi Chenmei

“…Meanwhile, we also consider the N-1 contingency constraints to make the technology selection, capacity allocation, and economic operation more reliable. The complex constraints resulting from producing two independent binary variables are converted into mixed integer linear constraints, which can be solved effectively using the nested column-and-constraint generation algorithm. …”
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Mixed fleet-based two-echelon vehicle routing optimization for cold chain logistics with diverse recharging strategies. by Yaling Li, Wenzhu Liao, Yuqi Huang

“…The presented model optimizes economic and environmental considerations to mitigate air pollution and reduce dependence on non-renewable energy sources while providing feasible routes. This study proposes an allocation algorithm and an enhanced ant colony algorithm to address a single-objective two-echelon vehicle routing problem with the mixed fleet (2EVRPMF). …”
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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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Predicting determinants of unimproved water supply in Ethiopia using machine learning analysis of EDHS-2019 data by Jember Azanaw, Mihret Melese, Eshetu Abera Worede

“…This study aimed to provide more accurate predictions and data-driven insights that can inform policy-making, resource allocation, and interventions to address Ethiopia’s water crisis. …”
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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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Optimization strategies in NOMA-based vehicle edge computing network by Jianbo DU, Nana XUE, Yan SUN, Jing JIANG, Shulei LI, Guangyue LU

“…Nowadays, vehicular network is confronting the challenges to support ubiquitous connections and vast computation-intensive and delay-sensitive smart service for numerous vehicles.To address these issues, non-orthogonal multiple access (NOMA) and mobile edge computing (MEC) are considered as two promising technologies by letting multiple vehicles to share the same wireless resources, and the powerful edge computing resources were adopted at the edge of vehicular wireless access network respectively.A NOMA-based vehicular edge computing network was studied.Under the condition of guaranteeing task processing delay, the joint optimization problem of task offloading, user clustering, computing resource allocation and transmission power control was proposed to minimize the task processing cost.Since the proposed problem was difficult to solve, it was divided into sub-problems, and a low-complexity and easy-to-implement method was proposed to solve it.The simulation results show that compared with other benchmark algorithms, the proposed algorithm performs well in minimizing costs.…”
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Optimization strategies in NOMA-based vehicle edge computing network by Jianbo DU, Nana XUE, Yan SUN, Jing JIANG, Shulei LI, Guangyue LU

“…Nowadays, vehicular network is confronting the challenges to support ubiquitous connections and vast computation-intensive and delay-sensitive smart service for numerous vehicles.To address these issues, non-orthogonal multiple access (NOMA) and mobile edge computing (MEC) are considered as two promising technologies by letting multiple vehicles to share the same wireless resources, and the powerful edge computing resources were adopted at the edge of vehicular wireless access network respectively.A NOMA-based vehicular edge computing network was studied.Under the condition of guaranteeing task processing delay, the joint optimization problem of task offloading, user clustering, computing resource allocation and transmission power control was proposed to minimize the task processing cost.Since the proposed problem was difficult to solve, it was divided into sub-problems, and a low-complexity and easy-to-implement method was proposed to solve it.The simulation results show that compared with other benchmark algorithms, the proposed algorithm performs well in minimizing costs.…”
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An Effective QoS-Aware Hybrid Optimization Approach for Workflow Scheduling in Cloud Computing by Min Cui, Yipeng Wang

“…However, developing effective workflow scheduling algorithms to find optimal or near-optimal task-to-VM allocation solutions that meet users’ specific QoS requirements still remains an open area of research. …”
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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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Certificateless Batch Authentication Scheme and Intrusion Detection Model Based on the Mobile Edge Computing Technology NDN-IoT Environment by Jianzhao Sun

“…Compared with the linear search algorithm, the algorithm proposed in this paper can significantly reduce the computation time.…”
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Hybrid Optimization Machine Learning Framework for Enhancing Trust and Security in Cloud Network by Himani Saini, Gopal Singh, Amrinder Kaur, Sunil Saini, Niyaz Ahmad Wani, Vikram Chopra, Zahid Akhtar, Shahid Ahmad Bhat

“…For resource allocation, the framework employs the Time-aware modified best fit decreasing (T-MBFD) algorithm, which adapts to fluctuating workloads. …”
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Temporal dependent rate-distortion optimization based on distortion backward propagation by Hongwei GUO, Ce ZHU, Xu YANG, Lei LUO

“…Rate-distortion optimization (RDO) is a crucial technique in block based hybrid video encoders.However, the widely used independent RDO is far from obtaining optimal coding performance.To improve the rate-distortion (R-D) performance of high efficiency video coding (HEVC), a temporal dependent RDO algorithm was proposed.Firstly, the formula to calculate temporal distortion propagation factor was derived by using an exponential R-D function.Then, the coding distortion and motion compensation predicted error were obtained by pre-encoding, and the temporal distortion propagation factor was estimated by using distortion backward propagation.Finally, the Lagrange multiplier and quantization parameter of coding tree unit were adaptively adjusted to optimize bit resources allocation.Experimental results show that compared with the original RDO method in HEVC under the low-delay configuration, the proposed algorithm achieves an average 4.4% bit rate reduction for all test sequences, and up to 13.0% bit rate reduction for test sequence BasketballDrill, at the same reconstructed video quality.…”
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