Enabling Power Systems With SQKD in Presence of Remote Nodes by Mariam Gado, Muhammad Ismail

“…Due to the complexity of the allocation problem, this paper develops algorithms based on Density-Based Spatial Clustering of Applications with Noise algorithm (DBSCAN), Dijksra’s algorithm and genetic algorithms. …”
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LEO computing satellite constellation design for heterogeneous QoS requirements by PENG Yuming, SUN Yijing, DI Boya

“…A two-stage constellation design algorithm was proposed, which firstly optimized the resource allocation strategy of computational satellites and then determined the constellation parameters under optimal QoS conditions. …”
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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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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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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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Research on Machine Learning-Based Extraction and Classification of Crop Planting Information in Arid Irrigated Areas Using Sentinel-1 and Sentinel-2 Time-Series Data by Lixiran Yu, Hongfei Tao, Qiao Li, Hong Xie, Yan Xu, Aihemaiti Mahemujiang, Youwei Jiang

“…The newly developed framework exhibits exceptional precision in categorization while maintaining impressive adaptability, offering crucial insights for optimizing agricultural operations and sustainable resource allocation in irrigation-dependent arid zones.…”
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Buffer-aided cooperative NOMA with power transfer by Long YANG, Li ZHAO, Yuchen ZHOU, Bingtao HE, Jian CHEN

“…To improve the throughput of multiuser simultaneous wireless information and power transfer systems, a buffer-aided cooperative non-orthogonal multiple access scheme with power transfer was designed to maximize the average throughput under the constraints of average/peak power, user’s rate, and the buffer stability.To reduce the optimization complexity, the Lyapunov’s method was introduced to convert the long-term average optimization problem into a series of time-discrete subproblems, and an adaptive transmission and resource allocation optimization algorithm was proposed, where the working mode, the user scheduling and the power allocation were dynamically optimized according to the time-varying channel/buffer state.Simulation results demonstrate that compared with the existing schemes, the proposed scheme can significantly enhance the average throughput whilst achieving the tradeoff between the delay and throughput.…”
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Research on deep reinforcement learning in Internet of vehicles edge computing based on Quasi-Newton method by ZHANG Jianwu, LU Zetao, ZHANG Qianhua, ZHAN Ming

“…To address the issues of ineffective task offloading decisions caused by multitasking and resource constraints in vehicular networks, the Quasi-Newton method deep reinforcement learning dual-phase online offloading (QNRLO) algorithm was proposed. …”
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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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Underwater Acoustic MAC Protocol for Multi-Objective Optimization Based on Multi-Agent Reinforcement Learning by Jinfang Jiang, Yiling Dong, Guangjie Han, Gang Su

“…MOMA-MAC utilizes a delay reward mechanism combined with the Multi-agent Proximal Policy Optimization Algorithm (MAPPO) to design a dual reward mechanism, which enables agents to adaptively collaborate and compete to optimize the use of network resources. …”
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Predicting Intensive Care Unit Admissions in COVID-19 Patients: An AI-Powered Machine Learning Model by A. M. Mutawa

“…Intensive Care Units (ICUs) have been in great demand worldwide since the COVID-19 pandemic, necessitating organized allocation. The spike in critical care patients has overloaded ICUs, which along with prolonged hospitalizations, has increased workload for medical personnel and lead to a significant shortage of resources. …”
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Optimizing sum rates in IoT networks: A novel IRS-NOMA cooperative system by Mukkara Prasanna Kumar, Ammar Summaq, Sunil Chinnadurai, Poongundran Selvaprabhu, Vinoth Babu Kumaravelu, Md. Abdul Latif Sarker, Dong Seog Han

“…By leveraging our optimization algorithm, the proposed system ensures efficient resource allocation, achieving superior spectral efficiency and fairness among users compared to traditional models. …”
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A Machine Learning Approach for Quantifying Academic Misconduct by Almasi S. Maguya

“…To deal with this problem effec tively, a clear understanding of its magnitude is necessary for planning and resource allocation. This paper proposes a machine learning algorithm to quantify the mag nitude of academic misconduct among undergraduate students. …”
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Task Scheduling in Cloud Environment–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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A Dynamic Interval Auto-Scaling Optimization Method Based on Informer Time Series Prediction by Yu Ding, Chenhao Li, Zhengong Cai, Xinghao Wang, Bowei Yang

“…As an essential feature of container cloud platforms and cloud-native architecture, auto-scaling aims to automatically and quickly adjust the allocation of cloud resources according to the resource requirements of applications. …”
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Low-altitude Secure Communication Driven by Deep Reinforcement Learning: An Integrated Sensing and Communication Design by Zhiqiang WEI, Jiashuo ZHANG, Fan LIU, Zai YANG, Zesong FEI

“…Using the Deep Deterministic Policy Gradient (DDPG) algorithm, the optimal framework is learned over time, dynamically optimizing the communication UAV’s trajectory and resource allocation to maximize long-term sensing and secure communication performance. …”
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Semantic aware intelligent optimization for IRS/UAV-enabled MEC in wideband cognitive radio networks by Wei Zheng, Pengshan Ren, Qing Li

“…The proposed semantic-aware optimization framework incorporates semantic information to achieve more efficient task scheduling and resource allocation. Particularly, the proposed optimization framework jointly optimizes UAV trajectories, subcarrier allocation, IRS reflection coefficients, task offloading ratios, task priorities and contextual relevance to maximize semantic utility and system energy efficiency while dynamically ensuring task demands. …”
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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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Cluster channel equalization using adaptive sensing and reinforcement learning for UAV communication by Xin Liu, Shanghong Zhao, Yanxia Liang, Shahid Karim

“…Simulation results demonstrate that the U-FRQL-EA algorithm effectively reduces the system’s bit error rate, enhances communication quality, and optimizes network resource utilization, offering a novel solution for improving the performance of uncrewed aerial vehicle communication systems.…”
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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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