Energy Efficient Design for Two-Way AF Relay Networks by Yong Li, Zhengguang Zheng, Mingyue Zhao, Yunli Chen, Chuanyong Liu

“…We propose an optimal energy-efficient power allocation algorithm based on iterative search technique. …”
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Predicting determinants of unimproved water supply in Ethiopia using machine learning analysis of EDHS-2019 data by Jember Azanaw, Mihret Melese, Eshetu Abera Worede

“…The problem is most acute in low-income nations, where many people still use unimproved water sources such as exposed wells and surface water. Public health systems are heavily burdened by these sources since they are closely associated with the spread of waterborne illnesses. …”
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A Distributed Low-Degree-of-Freedom Aerial Target Localization Method Based on Hybrid Measurements by Xiaoshuang Jiao, Jinming Chen, Lifeng Jiang, Weiping Li, Xiaochao Yang, Weiwei Wang, Jun Zhang

“…Simulation results validate the significant advantages of the proposed algorithm in enhancing localization accuracy, reducing system costs, and optimizing resource allocation. …”
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Deep learning-based time series prediction for precision field crop protection by Tao He, Meijin Li, Dong Jin

“…We introduce the Resource-Aware Adaptive Decision Algorithm (RAADA), which leverages reinforcement learning to translate SADF-Net’s predictions into optimized strategies for resource allocation, such as irrigation scheduling and pest control. …”
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Energy Harvesting for Throughput Enhancement of Cooperative Wireless Sensor Networks by Van-Dinh Nguyen, Chuyen T. Nguyen, Oh-Soon Shin

“…We then propose an iterative power allocation algorithm which converges to a locally optimal solution at a Karush-Kuhn-Tucker point. …”
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Optimizing multi-objective hybrid energy systems with pumped hydro storage for enhanced stability and efficiency in renewable energy integration by Junxian Li, Jiaxin Yuan, Xuxin Yue

“…Renewable energy sources include the intermittent nature, which is a vital challenge that causes considerable wind and solar energy losses. …”
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Domain-weighted transfer learning and discriminative embeddings for low-resource speaker verification by Han Wang, Mingrui He, Mingjun Zhang, Changzhi Luo, Longting Xu

“…In this paper, we propose a domain-weighted allocation fine-tuning strategy that employs the Kernel Mean Matching (KMM) algorithm to adjust the distribution differences between the in-domain and out-of-domain datasets. …”
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Designing a work program for the discipline based on the elements of competencies by A. M. Polyanskiy, E. A. Smirnova

“…According to the authors, the use of the elements of competences allocated from the texts of standards, scientific and methodological developments and other sources of the subject field of activity of the university graduate, allows to determine the set and content of knowledge, skills and knowledge necessary for training in the field of preparation more fully, rationally distribute them among educational disciplines and practices, to form the main didactic units of the work program of the academic discipline, to ensure the traceability of the requirements to the results of mastering the disciplines to a specific source of requirements.In the process of research, a methodology for the collection, processing and systematization of information necessary for the preparation of documents for the organization of the educational process at the department of the university was developed and approved; the analysis of professional and branch standards of software engineering is carried out; an array of elements of competencies required by the graduate training directions 09.03.04 is formed; software tools for processing and structuring information, managing changes in the elements of competences, taking into account the interrelations between them are proposed.The article describes the structure of the data array of competencies required by the graduate of the bachelor’s degree in the direction of training 09.03.04 “Software Engineering”; the results of the analysis of the main types of competence sources are presented: the educational standard in the specified direction of bachelor’s degree, professional standards and branch standards of software engineering, ontological and architectural models of entities of the subject domain; an algorithm for the collection, processing and systematization of information necessary for the formation of competency elements; examples of forming various types elements of competences are given.The study has showed that the competence approach, expanded in the proposed methodology, to the formation of working programs of educational disciplines and practices of the basic professional educational program of higher education allows to ensure the completeness, relevance and consistency of the requirements for the preparation of students, the rational distribution of the subject matter of the teaching material between disciplines and their mutual coherence in the educational process.…”
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SUSTAINABLE BACKUP POWER WITH V2G INTEGRATION IN HYBRID MICROGRID by B. Karthikeyan, K. S. Yamuna, K. Padmapriya, S. Priyadharsini, K. Sabareeshwari, P. Sree Mathi

“…The gadget ensures uninterrupted energy for critical systems which includes the Intensive Care Unit and emergency gadget whilst deprioritizing non-vital loads to optimize aid allocation. Advanced manage algorithms dynamically manage power flows ensuring effective operation even in the face of renewable power variability. …”
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Multi-Stage Data-Driven Framework for Customer Journey Optimization and Operational Resilience by Tzu-Chien Wang, Ruey-Shan Guo, Chialin Chen, Chia-Kai Li

“…To address these limitations, this study proposes a multi-stage data-driven framework integrating latent Dirichlet allocation (LDA) for behavioral insights, deep learning for predictive modeling, and heuristic algorithms for adaptive decision-making. …”
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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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Perspective of Chinese GF-1 high-resolution satellite data in agricultural remote sensing monitoring by Qing-bo ZHOU, Qiang-yi YU, Jia LIU, Wen-bin WU, Hua-jun TANG

“…In addition, the thematic product series in terms of land cover, crop allocation, crop growth and production are required to be developed in association with other data sources at multiple spatial scales. …”
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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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Conversion relationships and three-dimensional storage and utilization modes of four water resources in an open-pit mining area by Tianci CHEN, Zhimin XU, Yajun SUN, Jie FANG, Qiangmin WANG, Xiaofeng XIONG, Yuhao ZHU, Zihan LU, Fei WAN

“…By constructing an allocation model for the four water resources using an improved genetic algorithm, this study established a three-dimensional storage and comprehensive allocation and utilization system characterized by four water resources, five storage modes, and five utilization pathways for the open-pit mining area. …”
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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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Deep Reinforcement Learning-Based Energy Management Strategy for Green Ships Considering Photovoltaic Uncertainty by Yunxiang Zhao, Shuli Wen, Qiang Zhao, Bing Zhang, Yuqing Huang

“…The numerical results demonstrate that, compared to those obtained with the Double DQN algorithm, the PPO algorithm, and the DDPG algorithm without considering the PV system, the proposed DDPG algorithm reduces the total economic cost by 1.36%, 0.96%, and 4.42%, while effectively allocating power between the hydrogen fuel cell and the lithium battery and considering the uncertainty of on-board PV generation. …”
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Scientific planning of dynamic crops in complex agricultural landscapes based on adaptive optimization hybrid SA-GA method by Changlong Li, Zengye Su, Yudan Nie, Zhiyi Ye, Jinyi Li, Jing Wang, Zicong Yang, Xuxin Li, Weijian Zeng, Yanjian Chen

“…This research establishes an integrated “monitoring-modelling-decision” paradigm, driven by multi-source data and machine learning, offering a practical and robust tool that provides valuable guidance for enhancing resource allocation efficiency and promoting sustainable precision agriculture in complex topographical regions, thereby holding significant reference value for optimising agricultural production nationwide.…”
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Digital Low-Altitude Airspace Unmanned Aerial Vehicle Path Planning and Operational Capacity Assessment in Urban Risk Environments by Ouge Feng, Honghai Zhang, Weibin Tang, Fei Wang, Dikun Feng, Gang Zhong

“…In the implementation of path planning, compared with the A* and Weight-A* algorithms, the Parallel-A* algorithm demonstrates clear advantages in terms of lower average comprehensive risk and fewer turning points. …”
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Reinforcement Learning and Multi-Access Edge Computing for 6G-Based Underwater Wireless Networks by Juan Carlos Cepeda-Pacheco, Mari Carmen Domingo

“…The results show that our proposed algorithm outperforms the Total Offloading (Offloading), Local Execution (Locally), and Actor-Critic (AC) algorithms.…”
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Efficient Task Scheduling and Load Balancing in Fog Computing for Crucial Healthcare Through Deep Reinforcement Learning by Prashanth Choppara, Bommareddy Lokesh

“…This architecture reduces transmission latency by placing processing nodes close to the source of data generation, namely IoT-enabled healthcare devices. …”
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