The clinical performance of an office-based risk scoring system for fatal cardiovascular diseases in North-East of Iran. by Sadaf G Sepanlou, Reza Malekzadeh, Hossein Poustchi, Maryam Sharafkhah, Saeed Ghodsi, Fatemeh Malekzadeh, Arash Etemadi, Akram Pourshams, Paul D Pharoah, Christian C Abnet, Paul Brennan, Paolo Boffetta, Sanford M Dawsey, Farin Kamangar

“…Risk scoring systems for CVD are needed to prioritize allocation of limited resources. Most of these risk score algorithms have been based on a long array of risk factors including blood markers of lipids. …”
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Genetics of kidney stones and the role of genetic testing in prevention: a guide for urologists by Francesco Pintus, Noemi Giordano, Daniela Francesca Giachino, Giorgia Mandrile

“…This paper reviews the updated evidences in KSD genetics and suggest a diagnostic algorithm aimed to increase the diagnostic rate of genetic stones, allowing a personalized treatment and, in turn, a higher disease-free survival for the patients and a more efficient allocation of resources, analyzing the cost-effectiveness of genetic testing in urolithiasis. …”
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Prediction of dengue disease severity among pediatric Thai patients using early clinical laboratory indicators. by James A Potts, Robert V Gibbons, Alan L Rothman, Anon Srikiatkhachorn, Stephen J Thomas, Pra-On Supradish, Stephenie C Lemon, Daniel H Libraty, Sharone Green, Siripen Kalayanarooj

“…Earlier diagnosis of severe dengue illnesses would have a substantial impact on the allocation of health resources in endemic countries.…”
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Energy-Efficient Aerial STAR-RIS-Aided Computing Offloading and Content Caching for Wireless Sensor Networks by Xiaoping Yang, Quanzeng Wang, Bin Yang, Xiaofang Cao

“…Given the non-convex nature of this problem, we decompose it into a content caching decision subproblem, a computing offloading decision subproblem, a hovering position subproblem, and a STAR-RIS resource allocation subproblem. We propose a deep reinforcement learning (DRL)–successive convex approximation (SCA) combined algorithm to iteratively achieve near-optimal solutions with low complexity. …”
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Solving 0-1 Knapsack and Bin Packing Problem Using Logical Social Group Optimization by Rhiddhi Prasad Das, Junali Jasmine Jena, Suresh Chandra Satapathy, Naeem M. S. Hannoon

“…Both problems have prominent utilization in the real world such as in resource allocation, logistics, decision-making, etc. …”
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Simulating the root-to-shoot ratio of natural grassland biomass in China by the AutoGluon framework by Rui Guo, Xiaodong Huang, Yangjing Xiu, Minglu Che, Jinlong Gao, Shuai Fu, Qisheng Feng, Tiangang Liang

“…This study has achieved spatial mapping of natural grassland R/S, offering valuable insights into carbon allocation, ecosystem functioning, and the sustainable management of grassland resources.…”
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Machine Learning Approaches to Predict Patient’s Length of Stay in Emergency Department by Mohammad A. Shbool, Omar S. Arabeyyat, Ammar Al-Bazi, Abeer Al-Hyari, Arwa Salem, Thana’ Abu-Hmaid, Malak Ali

“…However, managing the health systems efficiently and achieving the best planning and allocation of their EDs’ resources becomes crucial to improve their capabilities to accommodate the crisis’s impact. …”
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Premier Dynamic Bandwidth Management and Tensile Wavelength Selection Ensuring QoS for NG-EPONs by Purushottam Singh, Pushpendra Kumar, Harshita Patel, Kanojia Sindhuben Babulal, Gayathri Ananthakrishnan

“…Comparative analysis reveals that TW-DBA outperforms existing algorithms like Flexible Wavelength (FW), First-Fit, and Water Filled, both in computational efficiency and resource allocation. …”
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Joint Encryption and Optimization for 6G MEC-Enabled IoT Networks by Manzoor Ahmed, Wali Ullah Khan, Fatma S. Alrayes, Yahia Said, Ali M. Al-Sharafi, Mi-Hye Kim, Khongorzul Dashdondov, Inam Ullah

“…An optimization algorithm is introduced to address these challenges by jointly allocating resources, thereby optimizing throughput, conserving energy, and meeting latency benchmarks through dynamic system adaptation. …”
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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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Artificial intelligence analysis in cyber domain: A review by Liguo Zhao, Derong Zhu, Wasswa Shafik, S Mojtaba Matinkhah, Zubair Ahmad, Lule Sharif, Alisa Craig

“…This method permits for the allocation of multiple log source types through a sliding time window and provides a scalable solution, which is a much-needed function.…”
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Superimposed Training-Based Channel Estimation for MIMO Relay Networks by Xiaoyan Xu, Jianjun Wu, Shubo Ren, Lingyang Song, Haige Xiang

“…Through the superposition of a group of additional training vectors at the relay subject to power allocation, the separated estimates of the source-relay and relay-destination channels can be obtained directly at the destination, and the accordance with the two-hop AF strategy can be guaranteed at the same time. …”
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Application of predator-prey optimization for task scheduling in cloud computing by Zahra Jalali Khalil Abadi, Behnam Mohammad Hasani zade, Najme Mansouri, Mohammad Masoud Javidi

“…Cloud computing environments require scheduling to allocate resources efficiently and ensure optimal performance. …”
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Interference Mitigation in Coexisting Satellites and Cloud-Assisted Ground Networks in the mmWave Band by Sirine Ben Ati, Hayssam Dahrouj, Mohamed-Slim Alouini

“…Such coexistence of space and ground communications becomes prone to wireless interference, and so the cross-development of intelligent resource allocation techniques becomes indispensable for assessing the benefit of such hybrid space-ground networks. …”
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Information-guided adaptive learning approach for active surveillance of infectious diseases by Qi Tan, Chenyang Zhang, Jiwen Xia, Ruiqi Wang, Lian Zhou, Zhanwei Du, Benyun Shi

“…Based on a probabilistic model, we evaluate the information gain of monitoring a spatio-temporal target and design a greedy selection algorithm for monitoring targets selection. Moreover, we integrate two major surveillance objectives, i.e., informativeness and coverage, in the monitoring target selection. …”
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Enhancing Campus Mobility: Simulated Multi-Objective Optimization of Electric Vehicle Sharing Systems Within an Intelligent Transportation System Frameworks by Omar S. Aba Hussen, Shaiful J. Hashim, Nasri Sulaiman Member, S.A.R. Alhaddad, Bassam Y. Ribbfors, Masanobu Umeda, Keiichi Katamine

“…This research offers valuable insights into the implementation of EV sharing systems in educational institutions, emphasizing the advantages of focused resource allocation and the integration of dynamic decision variables.…”
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Machine learning-based academic performance prediction with explainability for enhanced decision-making in educational institutions by Wesam Ahmed, Mudasir Ahmad Wani, Pawel Plawiak, Souham Meshoul, Amena Mahmoud, Mohamed Hammad

“…Abstract Education is crucial for the growth of effective life skills and the allocation of needed resources. Higher education institutions are adopting advanced technologies, such as artificial intelligence (AI), to enhance traditional teaching methods. …”
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Dynamic Subchannel Assignment-Based Cross-Layer MAC and Network Protocol for Multihop Ad Hoc Networks by Khanh Nguyen Quang, Van Duc Nguyen, Hyunseung Choo

“…The proposed dynamic sub-channel assignment algorithm provides a new interference avoidance mechanism which solves several drawbacks of existing radio resource allocation techniques in wireless networks using OFDMA/TDD, such as the hidden node and exposed node problems, mobility, and cochannels interference in frequency (CCI). …”
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Secure communication approach for Internet of things based on C-RAN fronthaul compression by Yong WANG, Mu ZHOU, Zengshan TIAN, Jinjun WU

“…A resource allocation algorithm was proposed for downlink C-RAN secure communication system.This algorithm jointly optimized the parameters of base station (BS) mode,quantized noise and beamforming under the constraints of SINR requirements of Internet of things information receiver,eavesdropped receiver and fronthaul link capacity.Such a design was a non-convex optimization problem,and a step-by step optimization algorithm was proposed to decompose the original optimization problem efficiently.Semi-definite technique and function smoothing approach were adopted,and the local optimization solution of the original problem was obtained by the iterative different of convex method.Bi-section approach was further proposed to determine BS mode,and the transmitting power of the BSs were finally optimized.Simulation results indicate that the proposed joint optimization algorithm achieves better performance than group sparse optimization algorithm and baseline algorithm,and it has approximate optimal performance as the exhaustive search algorithm.…”
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EcoTaskSched: a hybrid machine learning approach for energy-efficient task scheduling in IoT-based fog-cloud environments by Asfandyar Khan, Faizan Ullah, Dilawar Shah, Muhammad Haris Khan, Shujaat Ali, Muhammad Tahir

“…Abstract The widespread adoption of cloud services has posed several challenges, primarily revolving around energy and resource efficiency. Integrating cloud and fog resources can help address these challenges by improving fog-cloud computing environments. …”
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