Dynamic Adaptation for Independent Task Scheduling Using Dynamic Programming in Multiprocessor Systems by Lotfi BENDIAF, Ahmed HARBOUCHE, Mohammed Amin TAHRAOUI

“…Efficient scheduling requires optimizing competing objectives, such as minimizing makespan and maximizing processor utilization, to ensure that resources are used effectively. In this work, we propose DYnamic Task Allocation using dynamic programminG (DyTAg), a task scheduling algorithm based on dynamic programming, designed to support dynamic adaptation in HCS. …”
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Leveraging AI for early cholera detection and response: transforming public health surveillance in Nigeria by Adamu Muhammad Ibrahim, Mohamed Mustaf Ahmed, Shuaibu Saidu Musa, Usman Abubakar Haruna, Mohammed Raihanatu Hamid, Olalekan John Okesanya, Aishat Muhammad Saleh, Don Eliso Lucero-Prisno III

“…By integrating AI into Nigeria’s public health infrastructure, early detection and response can be improved, resource allocation optimized, and disease transmission minimized. …”
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Distributed robust scheduling of distribution-microgrid based on deep learning method integration by WANG Yihong, LIU Jichun, QIU Gao, ZHOU Hao, HE Peixin

“…Considering the uncertainty of the real-time output of new energy in the microgrid, the proposed two-stage robust economic dispatching model adopts column-and-constraint generation (C&CG) and alternating direction multiplier method (ADMM) combines the column and constraint generation algorithm and joint target cascade analysis algorithm for distributed solution. …”
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A maChine and deep Learning Approach to predict pulmoNary hyperteNsIon in newbornS with congenital diaphragmatic Hernia (CLANNISH): Protocol for a retrospective study. by Ilaria Amodeo, Giorgio De Nunzio, Genny Raffaeli, Irene Borzani, Alice Griggio, Luana Conte, Francesco Macchini, Valentina Condò, Nicola Persico, Isabella Fabietti, Stefano Ghirardello, Maria Pierro, Benedetta Tafuri, Giuseppe Como, Donato Cascio, Mariarosa Colnaghi, Fabio Mosca, Giacomo Cavallaro

“…The native sequences from fetal magnetic resonance imaging (MRI) will be collected. Data from different sources will be integrated and analyzed using ML and DL, and forecasting algorithms will be developed for each outcome. …”
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Identification of patients at risk of new onset heart failure: Utilizing a large statewide health information exchange to train and validate a risk prediction model. by Son Q Duong, Le Zheng, Minjie Xia, Bo Jin, Modi Liu, Zhen Li, Shiying Hao, Shaun T Alfreds, Karl G Sylvester, Eric Widen, Jeffery J Teuteberg, Doff B McElhinney, Xuefeng B Ling

“…<h4>Conclusions</h4>Utilizing machine learning modeling techniques on passively collected clinical HIE data, we developed and validated an incident-HF prediction tool that performs on par with other models that require proactively collected clinical data. Our algorithm could be integrated into other HIEs to leverage the EMR resources to provide individuals, systems, and payors with a risk stratification tool to allow for targeted resource allocation to reduce incident-HF disease burden on individuals and health care systems.…”
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Optimization strategies in NOMA-based vehicle edge computing network by Jianbo DU, Nana XUE, Yan SUN, Jing JIANG, Shulei LI, Guangyue LU

“…Nowadays, vehicular network is confronting the challenges to support ubiquitous connections and vast computation-intensive and delay-sensitive smart service for numerous vehicles.To address these issues, non-orthogonal multiple access (NOMA) and mobile edge computing (MEC) are considered as two promising technologies by letting multiple vehicles to share the same wireless resources, and the powerful edge computing resources were adopted at the edge of vehicular wireless access network respectively.A NOMA-based vehicular edge computing network was studied.Under the condition of guaranteeing task processing delay, the joint optimization problem of task offloading, user clustering, computing resource allocation and transmission power control was proposed to minimize the task processing cost.Since the proposed problem was difficult to solve, it was divided into sub-problems, and a low-complexity and easy-to-implement method was proposed to solve it.The simulation results show that compared with other benchmark algorithms, the proposed algorithm performs well in minimizing costs.…”
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Optimization strategies in NOMA-based vehicle edge computing network by Jianbo DU, Nana XUE, Yan SUN, Jing JIANG, Shulei LI, Guangyue LU

“…Nowadays, vehicular network is confronting the challenges to support ubiquitous connections and vast computation-intensive and delay-sensitive smart service for numerous vehicles.To address these issues, non-orthogonal multiple access (NOMA) and mobile edge computing (MEC) are considered as two promising technologies by letting multiple vehicles to share the same wireless resources, and the powerful edge computing resources were adopted at the edge of vehicular wireless access network respectively.A NOMA-based vehicular edge computing network was studied.Under the condition of guaranteeing task processing delay, the joint optimization problem of task offloading, user clustering, computing resource allocation and transmission power control was proposed to minimize the task processing cost.Since the proposed problem was difficult to solve, it was divided into sub-problems, and a low-complexity and easy-to-implement method was proposed to solve it.The simulation results show that compared with other benchmark algorithms, the proposed algorithm performs well in minimizing costs.…”
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Task Scheduling in Cloud Environment&#x2013;Techniques, Applications, and Tools: A Systematic Literature Review by Olanrewaju L. Abraham, Md Asri Bin Ngadi, Johan Bin Mohamad Sharif, Mohd Kufaisal Mohd Sidik

“…Cloud computing has become a revolutionary model for providing computational resources and services via the internet. As the volume of tasks and the dynamic nature of cloud resources increase, several critical challenges emerge, including load balancing, resource utilization, task allocation, and system performance. …”
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Scheduling Jobs with Variable Job Processing Times on Unrelated Parallel Machines by Guang-Qian Zhang, Jian-Jun Wang, Ya-Jing Liu

“…m unrelated parallel machines scheduling problems with variable job processing times are considered, where the processing time of a job is a function of its position in a sequence, its starting time, and its resource allocation. The objective is to determine the optimal resource allocation and the optimal schedule to minimize a total cost function that dependents on the total completion (waiting) time, the total machine load, the total absolute differences in completion (waiting) times on all machines, and total resource cost. …”
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Study on multi-satellite cooperative spectrum cognitive method integrating Stackelberg game and federated learning by Xiaojin DING, Yehui XU, Wen BAO, Gengxin ZHANG

“…To solve the problem of the weak spectrum-cognitive ability caused by monitoring angle, direction resolution, limited processing ability and peak power for a low-earth-orbit (LEO) satellite, a multi-satellite cooperative spectrum cognitive method integrating Stackelberg game and federated learning was proposed.Firstly, considering the available computing resource, cognitive performance, processing and transmission delay of each spectrum cognitive satellite, a cooperative-satellite selection and computing-resource allocation algorithm was built for multiple spectrum-cognitive tasks.Secondly, based on the selected satellites and the allocated computing resources, a low-complexity multi-satellite cooperative spectrum cognitive strategy was further designed, which could automatically sense the spectrum holes, and detect interference as well as identify the modulation mode.Simulation results demonstrate that compared to the single-node cognitive method, the designed multi-satellite cooperative spectrum cognitive strategy can obtain a better cognitive performance.Moreover, comparing with the existing model, the model utilized in the designed strategy can effectively achieve 96.69% and 93.32% lower number of parameters and required floating point operations per second, whilst maintaining the performance.…”
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Gemini: A Cascaded Dual-Agent DRL Framework for Task Chain Planning in UAV-UGV Collaborative Disaster Rescue by Mengxuan Wen, Yunxiao Guo, Changhao Qiu, Bangbang Ren, Mengmeng Zhang, Xueshan Luo

“…Specifically, this framework comprises a chain selection agent and a resource allocation agent: The chain selection agent plans paths for task chains, and the resource allocation agent distributes platform loads along generated paths. …”
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Interference Mitigation in mmWave Heterogeneous Cloud-Radio Access Network: For Better Performance and User Connectivity by Najwan M. Swadi, Firas A. Sabir, Hamed S. Al-Raweshidy

“…It integrates User-RRH associations to mitigate interference, enhance network throughput (via Heuristic Algorithm) and RRH-BBU clustering (via k-means) to manage resources in the network. …”
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IntelliGrid AI: A Blockchain and Deep-Learning Framework for Optimized Home Energy Management with V2H and H2V Integration by Sami Binyamin, Sami Ben Slama

“…The core of IntelliGrid AI is an advanced Q-learning algorithm that intelligently allocates energy resources. …”
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The methodology for calculating the number of teaching staff using economically feasible norms by L. A. Krokhmal, Yu. A. Kovshun

“…It has been established that the planned number of teaching staff is lower than the planned staffing level, calculated based on the volume of contact work hours, which makes it possible to encourage universities to restructure their curricula without going beyond funding limits.Conclusons and Relevance:the proposed approach allowed to conduct the calculation of teaching staff in accordance with the curriculum with a standardized volume of financial resources allocated to finance the remuneration of teaching staff of a specific educational program. …”
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Genomic selection optimization in blueberry: Data‐driven methods for marker and training population design by Paul Adunola, Luis Felipe V. Ferrão, Juliana Benevenuto, Camila F. Azevedo, Patricio R. Munoz

“…Our contribution in this study is threefold: (i) for the genotyping resource allocation, the use of genetic data‐driven methods to select an optimal set of markers slightly improved prediction results for all the traits; (ii) for the long‐term implication, we carried out a simulation study and emphasized that data‐driven method results in a slight improvement in genetic gain over 30 cycles than random marker sampling; and (iii) for the phenotyping resource allocation, we compared different optimization algorithms to select training population, showing that it can be leveraged to increase predictive performances. …”
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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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Microgrid Resilience Enhancement with Sensor Network-Based Monitoring and Risk Assessment Involving Uncertain Data by Tangxiao Yuan, Kossigan Roland Assilevi, Kondo Hloindo Adjallah, Ayité Sénah A. Ajavon, Huifen Wang

“…This paper focuses on enhancing the resilience of microgrids—localized power systems that integrate multiple energy sources—against challenges such as natural disasters, technological obstacles, and human errors. …”
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Intelligent scheduling mechanism of time-sensitive network modal in polymorphic network by Sijin YANG, Lei ZHUANG, Yu SONG, Jiaxing WANG, Xinyu YANG

“…For the problems of uncertain forwarding scheduling and long solving time of time-sensitive network modal in polymorphic network, a joint routing and scheduling mechanism of time-sensitive network modal based on CSQF was proposed.Considering the requirement of bounded delay, network state and different routing mechanisms, a hybrid resource scheduling problem of joint cache queue and routing was formulated to optimize the resource usage of the entire network.Then, the traffic characteristics and cache queue utilization was used to predict the cache utilization of the next cycle, which was based on deep reinforcement learning.In addition, by using multi-queue CSQF forwarding scheduling mechanism and explicit routing algorithm based on cache utilization, an iterative scheduling algorithm was proposed to achieve deterministic forwarding and resource allocation.Simulation results show that the mechanism can effectively adjust the transmission scheduling of deterministic applications according to the resource usage of the network, and has better schedulability compared with other off-line scheduling mechanisms.…”
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Intelligent scheduling mechanism of time-sensitive network modal in polymorphic network by Sijin YANG, Lei ZHUANG, Yu SONG, Jiaxing WANG, Xinyu YANG

“…For the problems of uncertain forwarding scheduling and long solving time of time-sensitive network modal in polymorphic network, a joint routing and scheduling mechanism of time-sensitive network modal based on CSQF was proposed.Considering the requirement of bounded delay, network state and different routing mechanisms, a hybrid resource scheduling problem of joint cache queue and routing was formulated to optimize the resource usage of the entire network.Then, the traffic characteristics and cache queue utilization was used to predict the cache utilization of the next cycle, which was based on deep reinforcement learning.In addition, by using multi-queue CSQF forwarding scheduling mechanism and explicit routing algorithm based on cache utilization, an iterative scheduling algorithm was proposed to achieve deterministic forwarding and resource allocation.Simulation results show that the mechanism can effectively adjust the transmission scheduling of deterministic applications according to the resource usage of the network, and has better schedulability compared with other off-line scheduling mechanisms.…”
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Rescheduling of Multi-Scenario and Multi-Objective Dynamic Changes of Ship Group Construction by ZHANG Aoyuan, HU Xiaofeng, ZHANG Yahui

“…First, the objective function is selected based on different production stage and abnormal disturbance, and a mathematical model is then developed, incorporating site constraints, task precedence constraints, and human resource constraints. Next, a site allocation algorithm is introduced, and an improved non-dominated sorting algorithm based on reference points is adopted to solve the problem. …”
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