Optimizing Medical IoT Disaster Management with Data Compression by Nunudzai Mrewa, Athirah Mohd Ramly, Angela Amphawan, Tse Kian Neo

“…They promise improved data handling, more effective decision-making, and optimized resource allocation across a range of IoT applications. …”
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Optimal Operation Method for Microgrid with Wind/PV/Diesel Generator/Battery and Desalination by Qingfeng Tang, Nian Liu, Jianhua Zhang

“…The power supply mode of island microgrid with a variety of complementary energy resources is one of the most effective ways to solve the problem of future island power supply. …”
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Visual analytics of urban epidemic situation development and dynamic regulation by Song WANG, Shijie CHEN, Hanglin LI, Xiaohui LI, Qiongfang FENG, Huijie WANG

“…In order to solve the reasonable allocation of limited medical resources for patients, a visual platform for dynamic control of cabin hospital was built based on the dataset of the COVID-19 epidemic in Wuhan cabin hospital, which integrates multi-source data such as public opinion, space-time trajectory and science popularization.The droppingwater diagram was introduced to dynamically monitor the overall situation of the cabin hospital.The theme model and sentiment dictionary were used to extract the emotional features of the masses, the WordStream were used to visually present the trend of urban public opinion.The path planning algorithm based on hospital load capacity were built for treatment route, the population-oriented science information of access to cabin hospital and the urban recovery model can enhance anti-epidemic confidence.The system is helpful to realize the reasonable allocation of human and material resources, timely guide the emotional trend of the masses, pay attention to the change of public opinion after the release of new polices/decisions, and slow down the phenomenon of patients gathering.The function and effectiveness of the system was verified by the analysis of several cases.…”
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A Distributed Low-Degree-of-Freedom Aerial Target Localization Method Based on Hybrid Measurements by Xiaoshuang Jiao, Jinming Chen, Lifeng Jiang, Weiping Li, Xiaochao Yang, Weiwei Wang, Jun Zhang

“…Simulation results validate the significant advantages of the proposed algorithm in enhancing localization accuracy, reducing system costs, and optimizing resource allocation. …”
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Reinforcement Learning and Multi-Access Edge Computing for 6G-Based Underwater Wireless Networks by Juan Carlos Cepeda-Pacheco, Mari Carmen Domingo

“…These AUVs are strategically positioned to execute tasks either fully locally, partially, or by offloading them entirely to a more resource-equipped AUV (AUV MEC). We achieve this by jointly optimizing the task offloading strategy, resource allocation, and the trajectories of the AUVs. …”
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Fuzzy logic-based particle swarm optimization for integrated energy management system considering battery storage degradation by Oladimeji Ibrahim, Mohd Junaidi Abdul Aziz, Razman Ayop, Ahmed Tijjani Dahiru, Wen Yao Low, Mohd Herwan Sulaiman, Temitope Ibrahim Amosa

“…By leveraging the adaptability of fuzzy logic to adjust PSO parameters dynamically, the method optimizes the allocation and utilization of diverse energy resources within a grid-connected microgrid. …”
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Digital Low-Altitude Airspace Unmanned Aerial Vehicle Path Planning and Operational Capacity Assessment in Urban Risk Environments by Ouge Feng, Honghai Zhang, Weibin Tang, Fei Wang, Dikun Feng, Gang Zhong

“…This research provides a theoretical foundation for the scientific management and optimal resource allocation of urban low-altitude airspace, facilitating the safe application and sustainable development of UAVs in urban environments.…”
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Efficient Task Scheduling and Load Balancing in Fog Computing for Crucial Healthcare Through Deep Reinforcement Learning by Prashanth Choppara, Bommareddy Lokesh

“…In such simulations, diverse healthcare scenarios, ranging from continuous patient monitoring systems to crucial emergency response applications, are recreated, providing a rich framework for testing the real-time processing capabilities of the model. This algorithm, DRL, has been fine-tuned and extensively implemented in these scenarios to show how the algorithm controls and optimizes tasks and their urgency in accordance with resource demand. …”
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Natural gas bi-level demand response strategies considering incentives and complexities under dynamic pricing by Huibin Zeng, Jie Zhou, Hongbin Dai

“…The upper-level model uses dynamic gas pricing to guide users in adjusting consumption, thereby reducing peaks, filling valleys, and optimizing resource allocation. The lower-level model considers factors like weather and heating, creating incentives to boost user participation and flexibility. …”
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Multi-Stage Data-Driven Framework for Customer Journey Optimization and Operational Resilience by Tzu-Chien Wang, Ruey-Shan Guo, Chialin Chen, Chia-Kai Li

“…To address these limitations, this study proposes a multi-stage data-driven framework integrating latent Dirichlet allocation (LDA) for behavioral insights, deep learning for predictive modeling, and heuristic algorithms for adaptive decision-making. …”
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An interpretable machine learning model to predict hospitalizations by Hagar Elbatanouny, Hissam Tawfik, Tarek Khater, Anatoliy Gorbenko

“…This study underscores the potential of interpretable machine learning in aiding hospital managers to optimize resource allocation, hospitalization cases, and make data-driven decisions during pandemics.…”
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Tasmanian devil whale optimization (TDWO) is introduced for secure video transmission in 5G networks. by Fengren Lin, Minrong Lu

“…The experimental results prove that the TDWO resource allocation algorithm yields significant experimental outcomes, with throughput, bit error rate (BER), QoE and fitness values of 25.557 Mbps, 0.021, 18.332 and 0.013, respectively.…”
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Kneeliverse: A universal knee-detection library for performance curves by Mário Antunes, Tyler Estro, Pranav Bhandari, Anshul Gandhi, Geoff Kuenning, Yifei Liu, Carl Waldspurger, Avani Wildani, Erez Zadok

“…These points represent optimal trade-offs between cost and performance, facilitating efficient decision-making and resource allocation. However, accurately determining the knees and elbows in curves poses a significant challenge. …”
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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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A Hierarchical Reinforcement Learning Framework for Multi-Agent Cooperative Maneuver Interception in Dynamic Environments by Qinlong Huang, Yasong Luo, Zhong Liu, Jiawei Xia, Ming Chang, Jiaqi Li

“…To address the challenges of real-time decision-making and resource optimization in multi-agent cooperative interception tasks within dynamic environments, this paper proposes a hierarchical framework for reinforcement learning-based interception algorithm (HFRL-IA). …”
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Fault aware task scheduling in cloud using min-min and DBSCAN by S.M.F D Syed Mustapha, Punit Gupta

“…The proposed algorithm considers high execution enabled powerful data centers with least fault probability during resource allocation which reduces the probability of fault and increases the tolerance. …”
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A Wind Power Density Forecasting Model Based on RF-DBO-VMD Feature Selection and BiGRU Optimized by the Attention Mechanism by Bixiong Luo, Peng Zuo, Lijun Zhu, Wei Hua

“…Accurate prediction of wind power density (WPD) holds significant practical importance for wind farms, grid operators, and the entire wind power industry, as it facilitates informed decision-making, optimized resource allocation, and enhanced system performance. …”
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Pulse Sequence Division in Mixed Signal Flow by V. F. Korotkov, R. S. Zyryanov

“…Based on the classification improved algorithm for the allocation sequence is developed. …”
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An Optimal Transmission Strategy for Joint Wireless Information and Energy Transfer in MIMO Relay Channels by Dingcheng Yang, Xiaoxiao Zhou, Lin Xiao

“…It is focused on the precoder design and resource allocation strategies for the system to allocate the resources among the nodes in decode-and-forward (DF) mode. …”
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Time-Triggered Task Offloading Scheduling in TSN-Based Edge Computing Power Networks by Hongrui Nie, Yang Wu, Weifeng Zhu, Jinzuo Zhong, Hang Yang, Yu Zhou

“…Computing power networks (CPN), connecting distributed computing resources over networks, have been proposed as potential next-generation novel network systems to enable optimal resource allocation among multiple computing nodes. …”
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