Intersections of Big Data and IoT in Academic Publications: A Topic Modeling Approach by Diana-Andreea Căuniac, Andreea-Alexandra Cîrnaru, Simona-Vasilica Oprea, Adela Bâra

“…As vast amounts of data are generated from various sources such as social media, sensors and online transactions, the analysis of Big Data offers organizations the ability to derive insights and make informed decisions. …”
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Ecological and Statistical Evaluation of Genetic Algorithm (GARP), Maximum Entropy Method, and Logistic Regression in Predicting Spatial Distribution of Astragalus sp. by Amir Ghahremanian, Abbas Ahmadi, Hamid Toranjzar, Javad Varvani, Nourollah Abdi

“…The ability to predict species distribution can help optimize resource allocation for habitat restoration and enhance biodiversity conservation efforts.…”
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Solving the Privacy-Equity Trade-off in Data Sharing By Using Homophily, Diversity, and <italic>t</italic>-Closeness Based Anonymity Algorithm by Abdul Majeed, Seong Oun Hwang

“…In the modern era, personal data published by data owners play a vital role in decision-making, resource allocation, disease mitigation, and/or epidemiological analysis. …”
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Scalability and Cost Optimization in Load-Balanced Microservice Scheduling System by Shamsuddeen Rabiu, Chan Huah Yong, Sharifah Mashita Syed Mohamad

“…Additionally, a specialized algorithm is introduced to evaluate the cost, execution time, and availability aspects of microservice applications, enabling optimized resource allocation in a distributed manner. …”
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Harnessing Data-mining Algorithms to Model and Evaluate Factors Influencing Distortion Product Otoacoustic Emission Variations in a Mining Industry by Sajad Zare, Reza Esmaeili, Mojtaba Nakhaei pour

“…Conclusions: As a result of determining the weight of factors causing variations in OAEs, the allocation of resources for control measures and effective reduction will be accomplished more efficiently and accurately.…”
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GAPO: A Graph Attention-Based Reinforcement Learning Algorithm for Congestion-Aware Task Offloading in Multi-Hop Vehicular Edge Computing by Hongwei Zhao, Xuyan Li, Chengrui Li, Lu Yao

“…Building on this foundation, an attention-based Actor–Critic framework makes joint offloading decisions by intelligently selecting the optimal destination and collaboratively determining the ratios for offloading and resource allocation. A multi-objective reward function, designed to minimize task latency and to alleviate link congestion, guides the entire learning process. …”
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Task offloading optimization in mobile edge computing based on a deep reinforcement learning algorithm using density clustering and ensemble learning by Yi Qin, Junyan Chen, Lei Jin, Rui Yao, Zidan Gong

“…Opportunistic computing offloading is effective to enhance computing performance in dynamic edge network environments; however, careless offloading of tasks to ESs can lead to WDs preempting network computing resources with limited bandwidth, thereby resulting in inefficient allocation of computing resources. …”
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Exploring the Role of Artificial Intelligence in Wastewater Treatment: A Dynamic Analysis of Emerging Research Trends by Javier De la Hoz-M, Edwan Anderson Ariza-Echeverri, Diego Vergara

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The application of machine learning algorithms for predicting length of stay before and during the COVID-19 pandemic: evidence from Wuhan-area hospitals by Yang Liu, Yang Liu, Renzhao Liang, Chengzhi Zhang

“…This study offers valuable guidance to hospital administrators for planning resource allocation strategies that can effectively meet the demand. …”
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Simulation study on the urban-rural integration circulatory mechanism system in China: Based on system dynamics model and multi-objective genetic algorithm by Gaoyang Liang, Mingqiang Xing, Jianqiang Zhao

“…Additionally, multi-objective optimization solutions are proposed using a Multi-Objective Genetic Algorithm (MOP-GA), which suggest that a comprehensive development strategy that balances urban-rural resource allocation achieves the highest level of integration. …”
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Redefining Trauma Triage for Elderly Adults: Development of Age-Specific Guidelines for Improved Patient Outcomes Based on a Machine-Learning Algorithm by Ji Yeon Lim, Yongho Jee, Seong Gyu Choi, Yoon Hee Choi, Sam S. Torbati, Carl T. Berdahl, Sun Hwa Lee

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Fairness-Aware Utility Maximization for Multi-UAV-Aided Terrestrial Networks by Nishant Gupta, Satyam Agarwal, Aymen Fakhreddine

“…In the second stage, we utilize the solution obtained in the first part and develop an interference-aware iterative scheme to jointly optimize user scheduling, resource allocation, and ABS placement. Given the non-convex nature of this problem, we employ the successive convex approximation technique to approximate the non-convex objectives and constraints. …”
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Optimizing Pharmaceutical Inventory and Investment Strategies During Pandemics: A Dynamic Approach Integrating Environmental Emission Rates and Advanced Optimization Algorithms by Vinita Dwivedi, Mamta Keswani, Uttam Kumar Khedlekar, Lalji Kumar

“…Optimal control theory is applied for dynamic investment adjustments, enhancing resource allocations and decision-making. The study addresses a complex replenishment problem involving joint pricing, environmental costs, order costs, preservation technology, and replenishment schedules for non-instantaneous deteriorating items, aiming to maximize retailer's profit. …”
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Optimal Economic Dispatch Strategy for Cascade Hydropower Stations Considering Electric Energy and Peak Regulation Markets by Fan Liu, Wentao Huang, Jingjing Ma, Jun He, Can Lv, Yukun Yang

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Compatible matching and synergy operation optimization of hydrogen-electric hybrid energy storage system in DC microgrid by Banghua Du, Yanyu Peng, Yang Li, Changjun Xie, Shihao Zhu, Wenchao Zhu, Yang Yang, Li You, Leiqi Zhang, Bo Zhao

“…Hydrogen energy storage (HES) systems could balanced source-load mismatches in DC microgrids. By combining HES with electrical energy storage (EES), the start-up delay and rapid degradation of HES under fluctuating inputs can be mitigated, enhancing system adaptability. …”
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A TRIZ-based algorithm for business model innovation in manufacturing SMEs: a systematic framework for strategic innovation integrated with the business model canvas by Juan G. Mejia-Duque, Andres Guerrero-Alvarado

“…A single-case study in a Colombian manufacturing SME demonstrated measurable improvements in resource allocation, cost efficiency, quality, customer engagement, and market opportunity identification, strengthening competitiveness and value creation. …”
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Methods for Cognitive Diagnosis of Students’ Abilities Based on Keystroke Features by Xu Chi, Xinyu Guo, Yu Sheng

“…This provides strong support for the formulation of teaching strategies and the allocation of resources, and the method possesses important application value and practical significance.…”
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Secondary Frequency Control of Islanded Microgrid Based on Deep Reinforcement Learning by Li WANG, Yuxiang JIANG, Xiangjun ZENG, Bin ZHAO, Junhao LI

“…The frequency deviation is used as the state input variable, and the design of the state space, action space, reward function, neural network, and hyperparameters in the deep Q-Networks algorithm is carried out. The reward function balances the goals of frequency recovery and power allocation among distributed energy resources , ensuring consistency in action selection among the intelligent agents. …”
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Load balancing method of service cluster based on mean-variance by Xiaoan BAO, Xue WEI, Lei CHEN, Guoheng HU, Na ZHANG

“…When a large number of concurrent requests are allocated,the load scheduling mechanism is to achieve the load balancing of nodes in the network by minimizing the response time and maximizing the utilization ratio of nodes.In the load balancing algorithm based on genetic algorithm,the fitness function is designed to have an important influence on the load balancing efficiency.A service cluster load balancing method based on mean-variance was proposed to optimize the fitness function.The investment portfolio selection model mean-variance was used to minimize the response time,which was used to get the weight of each server's resource utilization,so as to obtain the optimal allocation combination.This method improves the accuracy and efficiency of the fitness function.Compared with other models in different service environment,the simulation results show that the load balancing algorithm makes the service cluster get a better balance performance in terms of node utilization and response time.…”
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Internet of Things Based Application Placement Technique in Fog Environment by N Malathy, M Ruba, S Vinothini

“…Leveraging an Improved Memetic Algorithm (IMA), this strategy enables effective scheduling of parallel IoT workflows across fog and cloud servers, ensuring balanced resource utilization and enhanced scalability. …”
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