Secure energy efficiency maximization for joint ITS and IRS assisted satellite downlink communications by Shaochuan Yang, Kaizhi Huang, Hehao Niu, Yi Wang, Ya Liu, Zheng Chu

“…The aim is to maximize the secure energy efficiency by jointly designing ITS beamforming, IRS phase shift, jammer precoding vector, and transmit power allocation. To develop a low‐complexity solution,first, an approximated concave lower bound of the non‐concave objective function is derived by utilizing Dinkelbach's method and a novel successive convex approximation technique. …”
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Knowledge Graph Representation of Felder-Silverman Learning Style Model for Computing Education by Mubasher Yousuf, Syed Imran Jami, Shaukat Wasi, Muhammad Shoaib Siddiqui

“…Moreover, LSKGs enable effective resource allocation by aligning teaching methods with learning styles.…”
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Enhancing Visitor Forecasting with Target-Concatenated Autoencoder and Ensemble Learning by Ray-I Chang, Chih-Yung Tsai, Yu-Wei Chang

“…Accurate forecasting of inbound visitor numbers is crucial for effective planning and resource allocation in the tourism industry. Preceding forecasting algorithms primarily focused on time series analysis, often overlooking influential factors such as economic conditions. …”
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MetaStackD A robust meta learning based deep ensemble model for prediction of sensors battery life in IoE environment by D. Gayathri, S. P. Shantharajah

“…Leveraging regression algorithms such as Random Forest, Gradient Boosting, Light Gradient Boosting, Categorical Boosting and Extreme Gradient Boosting, we have modeled the non-linear and temporal dynamics of sensor battery degradation, thereby enabling proactive maintenance strategies, dynamic energy management, and resource allocation. …”
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Hierarchical Cluster Control Method for Flexible Load in Distribution Network Based on Improved Alternating Direction Multiplier Method by Juncheng ZHANG, Min LI, Zhiwen LIU, Jing TAN, Yigang TAO, Tianlu LUO

“…Firstly, the flexible loads are clustered hierarchically using the BIRCH clustering algorithm. Secondly, based on Nash negotiation theory, the original problem is decomposed into two sub problems: cost minimization and revenue allocation, and a flexible load cluster regulation model for distribution networks is established. …”
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A dynamic network traffic classifier using supervised ML for a Docker-based SDN network by Pritom Kumar Mondal, Lizeth P. Aguirre Sanchez, Emmanuele Benedetto, Yao Shen, Minyi Guo

“…Software-defined networking (SDN) with machine learning (ML) has become an emerging solution for network scheduling, quality of service (QoS), resource allocations, and security. This paper focuses on the implementation of a network traffic classifier using a novel Docker-based SDN network. …”
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METHODOLOGICAL APPROACHES TO THE DEVELOPMENT OF MECHANISMS FOR THE SYSTEM INTEGRATION OF AGRICULTURAL, PROCESSING AND MARKETING ENTERPRISES by Anna Aleksandrovna LEKSINA

“…This is a three-stage structured algorithm for constructing elements of functional, informational, organizational and resource subsystems and the relationships between them. …”
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STF-LPPVA: Local Privacy-Preserving Method for Vehicle Assignment Based on Spatial–Temporal Fusion by Lei Tang, Zhengxin Cao, Xin Zhou, Junzhe Zhang, Junchi Ma

“…Based on the similarity of the vectors, the cloud platform can allocate vehicles using the Kuhn–Monkreth (KM) algorithm. …”
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Path Algebra-Driven Classification Solution to Realize User-Centric Performance-Oriented Virtual Network Embeddings by Stelios Prekas, Panagiotis A. Karkazis, Panagiotis Trakadas

“…The intense diversity of the Next-Generation Networking environments like 6G and the forthcoming deployment of immersive applications with varied user-specific requirements transform the efficient allocation of resources into a real challenge. Traditional solutions like the shortest path algorithm and mono-constraint methodologies are inadequate to handle customized user-defined performance parameters and effectively classify physical resources according to these intricate demands. …”
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Machine Learning in Public Governance: A Systematic Review of Applications, Trends and Challenges by Y. Nuruly, G. N. Sansyzbayeva, L. Z. Ashirbekova, S. K. Tazhiyeva

“…The analysis results allowed us to identify four functional areas of ML application in public administration: transparency and ethics, resource allocation and service provision, institutional design, and technical integration. …”
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Spectrum Sharing Design for Integrated Aeronautical Communication and Radar System by Lanchenhui Yu, Jingjing Zhao, Quan Zhou, Yanbo Zhu, Kaiquan Cai

“…An alternative optimization (AO) algorithm is proposed to solve the non-convex problem with highly coupled variables. …”
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Optimizing Deep Learning Models for Fire Detection, Classification, and Segmentation Using Satellite Images by Abdallah Waleed Ali, Sefer Kurnaz

“…Achieving 82% detection accuracy in real-world applications could drastically reduce response times, minimize the damage caused by wildfires, and enhance resource allocation for firefighting efforts, emphasizing the importance of continued research in this domain.…”
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SLAM: Sales Lead AMplification Through GenAI and ML for e-Learning Platforms by Ganesan Ramachandran, Tanmay Narang, Vallidevi Krishnamurthy

“…In the domain of sales, the accurate prediction of leads is deemed essential for optimizing resource allocation and maximizing conversion rates. …”
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Enhancing revenue generation in Bangladesh’s FinTech sector: a comprehensive analysis of real-time predictive customer behavior modeling in AWS using a hybrid OptiBoost-EnsembleX m... by Avijit Chowdhury

“…The anticipation of future customer conduct is a cornerstone for resource allocation in sales and marketing, enabling strategic decision-making in manufacturing operations, inventory planning, and point-of-sale scenarios. …”
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Workload Forecasting Methods in Cloud Environments: An Overview by Samah Aziz, Manar Kashmoola

“…Cloud computing is becoming increasingly popular due to its on-demand resource allocation and scalability. It is essential to precisely anticipate workload as applications and users on cloud-based services increase to distribute resources effectively and avoid service interruptions. …”
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Explainable machine learning models for mortality prediction in patients with sepsis in tertiary care hospital ICU in low- to middle-income countries by Saumya Diwan, Vinay Gandhi, Esha Baidya Kayal, Puneet Khanna, Amit Mehndiratta

“…Conclusions The proposed approach could provide preemptive estimations into prognostication and outcome prediction of patients with sepsis in low-resource settings. This will aid in clinical decision-making, resource allocation and research for new treatment modalities.…”
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Optimizing Energy Efficiency in Cloud Data Centers: A Reinforcement Learning-Based Virtual Machine Placement Strategy by Abdelhadi Amahrouch, Youssef Saadi, Said El Kafhali

“…The proposed method, RLVMP, classifies VMs as sensitive or insensitive and dynamically allocates resources to minimize energy consumption while ensuring compliance with service level agreements (SLAs). …”
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Energy Simulation and Optimal Scheduling of Integrated Energy System Considering Hybrid Energy Storage by Yongwei LUO, Chengren LI, Ling ZHANG, Jianmin ZHANG, Xinhong WU, Jinbu LIAN, Jin FAN

“…The complementary multi-energy based integrated energy system (IES) is an important way to improve regional energy efficiency and optimize energy resources allocation. An energy flow matrix model is established for the IES equipment with the minimal operating cost of the IES as the objective function, and a hybrid algorithm combining dynamic programming and the improved PSO is proposed. …”
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Literature review for the topic of automation of scheduling classes and exams in higher education institutions by Wadhah M Al-Gabri

“…The analytical study results of a number of the Russian and foreign sources on methods and algorithms of the classes and exams timetabling automation are described. …”
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Use of machine learning to predict creativity among nurses: a multidisciplinary approach by Rola H. Mudallal, Majd T. Mrayyan, Mohammad Kharabsheh

“…The developed decision support system may be valuable for helping nurse managers evaluate creativity among nurses; this allows for more informed decisions about staff allocation, development, and resource optimization. …”
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