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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Modified Lagrangian Methods for Separable Optimization Problems by Abdelouahed Hamdi, Aiman A. Mukheimer

“…The proposed scheme is based on a class of modified Lagrangians combined with the allocation of resources decomposition algorithm. Under mild assumptions, we show that the method generates convergent primal-dual sequences.…”
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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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An integrated vehicle routing model to optimize agricultural products distribution in retail chains by W. Madushan Fernando, Amila Thibbotuwawa, H. Niles Perera, Peter Nielsen, Deniz Kenan Kilic

“…It introduces an integrated bi-objective VRP model that concurrently optimizes resource allocation, order scheduling, and route planning. …”
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Machine learning based risk analysis and predictive modeling of structure fire related casualties by Andres Schmidt, Eric Gemmil, Russ Hoskins

“…As the first statewide analysis of its kind, our spatial assessment provides a useful tool for resource allocation, risk factor reduction, and safety education efforts targeted to reduce the number of serious injuries or fatalities from structure fires.…”
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Augmented robustness in home demand prediction: Integrating statistical loss function with enhanced cross-validation in machine learning hyperparameter optimisation by Banafshe Parizad, Ali Jamali, Hamid Khayyam

“…Sustainable forecasting of home energy demand (SFHED) is crucial for promoting energy efficiency, minimizing environmental impact, and optimizing resource allocation. Machine learning (ML) supports SFHED by identifying patterns and forecasting demand. …”
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The impacts of specific place visitations on theft patterns: a case study in Greater London, UK by Tongxin Chen, Kate Bowers, Tao Cheng

“…Abstract Exploring the impacts of population place visitation on crime patterns is crucial for understanding crime mechanisms and optimising resource allocation in crime prevention. While recent studies have broadly examined dynamic population activities at specific places from geo big data, limited crime-related studies have utilised this measurement to disentangle the impact of specific place visitation on urban crime patterns. …”
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Bilevel Programming Model of Urban Public Transport Network under Fairness Constraints by Jingjing Hao, Xinquan Liu, Xiaojing Shen, Nana Feng

“…The results showed that (1) the travel cost deprivation coefficient of the three groups declined from 33.42 to 26.51, with a decrease of 20.68%; the Gini coefficient of the road area declined from 0.248 to 0.030, with a decrease of 87.76%; it could be seen that the transportation equity feeling of low-income groups and objective resource allocation improved significantly; (2) before the optimization of public transport network, the sharing rate of cars, buses, and bicycles was 42%, 47%, and 11%, respectively; after the optimization, the sharing rate of each mode was 7%, 82%, and 11%, respectively. …”
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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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Binary Chaotic White Shark Optimizer for the Unicost Set Covering Problem by Pablo Zúñiga-Valenzuela, Broderick Crawford, Felipe Cisternas-Caneo, Eduardo Rodriguez-Tello, Ricardo Soto, José Barrera-Garcia, Fernando Lepe-Silva

“…This work establishes WSO as a robust metaheuristic for USCP, with applications in resource allocation and network design.…”
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GSF-YOLOv8: A Novel Approach for Fire Detection Using Gather-Distribute Mechanism and SimAM Attention by Caixiong Li, Dali Wu, Xing Zhang, Peng Wu

“…To address the current challenges in fire detection algorithms, including insufficient feature extraction, high computational complexity, limited deployment on resource-constrained devices, missed detections, false detections, and low accuracy, we developed a high-precision algorithm named GSF-YOLOv8. …”
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Dynamic UAV Inspection Boosted by Vehicle Collaboration Under Harsh Conditions in the IoT Realm by Dai Hou, Zhiheng Yao, Bo Jin, Xingwei Cai, Huan Xu, Jiaxiang Xu, Tianping Deng

“…Empowered by the IoT, these systems optimize resource allocation and boost the efficiency of IoT-based applications. …”
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A Green Cloud-Based Framework for Energy-Efficient Task Scheduling Using Carbon Intensity Data for Heterogeneous Cloud Servers by B. M. Beena, Prashanth Cheluvasai Ranga, Thotapalli Sri Surya Manideep, Sneha Saragadam, Garikipati Karthik

“…For data centres aiming to enhance efficiency and reduce their carbon footprint, intelligent automation provides tangible benefits, including optimized resource allocation, dynamic workload balancing, and lower operational costs. …”
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Machine learning-driven prediction of medical expenses in triple-vessel PCI patients using feature selection by Kuan-Yu Chen, Yen-Chun Huang, Chih-Kuang Liu, Shao-Jung Li, Mingchih Chen

“…Developing efficient strategies for resource allocation has become a paramount concern due to tightening healthcare budgets and the escalating costs of treating heart conditions. …”
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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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Dynamic Water Scheduling in the Northwest River Delta Basin Based on Minimum Discharge Flow Control in Cross-section by WU Di, FANG Chunyan, SHANG Yunfei

“…The whale optimization algorithm was used to find the optimal water allocation plan. …”
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NCREASING ECONOMIC PERFORMANCES USING OPTIMIZATION by Daniela-Elena ȘURCĂ

“…The optimization led to the improvement of the overall economic performance by the rational allocation of resources and the establishment of the crop structure in order to obtain large yields. …”
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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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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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