Spatiotemporal Characteristics of Public Attention Level on the 2022 Extreme Drought in Yangtze River Basin Based on Weibo Text Analysis by LI Zhe, CHEN Zhe, XIANG Da-xiang, CUI Chang-lu

“…Utilizing texts from Weibo, a mainstream social media platform in China, as data sources, this study used machine learning and artificial intelligence algorithms to collect Weibo text data throughout the drought progression process. …”
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Smart Electric Vehicle Charging Management Using Reinforcement Learning on FPGA Platforms by Udhaya Mugil Damodarin, Gian Carlo Cardarilli, Luca Di Nunzio, Marco Re, Sergio Spanò

“…The FPGA implementation leverages hardware design strategies to ensure efficient operation and real-time response within a limited amount of required energy, allowing for its implementation in embedded applications and possibly enabling the use of an energy harvesting power source, like a small solar panel. The proposed design effectively manages multiple EV chargers by dynamically allocating current and prioritizing charging tasks to maintain service quality. …”
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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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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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Role,application and challenges of IoT in smart EV charging management:a review by Tripti Kunj, Kirti Pal

“…Additionally, the paper emphasizes the importance of adaptive algorithms and machine learning models for predictive maintenance and efficient resource allocation. …”
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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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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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Deep reinforcement learning based resource provisioning for federated edge learning by Xingyun Chen, Junjie Pang, Tonghui Sun

“…The MFLD algorithm leverages Deep Reinforcement Learning (DRL) techniques to automatically select UEs and allocate the computation resources according to the task requirement. …”
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Grouping control of electric vehicles based on improved golden eagle optimization for peaking by Yang Yu, Yuhang Huo, Shixuan Gao, Qian Wu, Mai Liu, Xiao Chen, Xiaoming Zheng, Xinlei Cai

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Development and validation of an interpretable multi-task model to predict outcomes in patients with rhabdomyolysis: a multicenter retrospective cohort studyResearch in context by Chunli Liu, Jie Shi, Fengjuan Wang, Duo Li, Yu Luo, Bofan Yang, Yunlong Zhao, Li Zhang, Dingwei Yang, Heng Jin, Jie Song, Xiaoqin Guo, Haojun Fan, Qi Lv

“…Ten machine learning (ML) algorithms were applied to construct multi-task prediction models. …”
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Machine learning in predicting firm performance: a systematic review by Yaseen Hezam, Hoa Luong, Lilian Anthonysamy

“…It reveals a predominance of classification methods in ML, with neural networks, logistic regression, and decision trees being the most frequently employed algorithms. These findings underscore the potential of ML techniques to provide a more nuanced and accurate prediction of firm performance by integrating diverse data sources and attributes. …”
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Crop yield prediction using machine learning: An extensive and systematic literature review by Sarowar Morshed Shawon, Falguny Barua Ema, Asura Khanom Mahi, Fahima Lokman Niha, H.T. Zubair

“…Also, the most applied machine learning algorithms are Linear Regression (LR), Random Forest (RF), and Gradient Boosting Trees (GBT) whereas the most applied deep learning algorithms are Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM). …”
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Optimizing integration techniques for UAS and satellite image data in precision agriculture — a review by Aliasghar Bazrafkan, C. Igathinathane, Nonoy Bandillo, Paulo Flores

“…The combined spectral information from UAS and satellite sources confirms instrumental in crop monitoring and biomass estimation. …”
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Two-sided Energy Storage Cooperative Scheduling Method for Transmission and Distribution Network Based on Multi-agent Attention-deep Reinforcement Learning by CHEN Shi, ZHU Yujie, LIU Yihong, XU Liuchao, TANG Guodeng

“…An improved Shapley value is used to allocate additional income, providing a cooperative incentive. …”
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Hydropneumatic storage methodology towards a new era of hybrid energy system's efficiency and flexibility by JoaoS.T. Coelho, Modesto Pérez-Sánchez, Oscar E. Coronado-Hernández, Mohsen Besharat, Rui-Lin Feng, Elias Tasca, Ling Zhou, Helena M. Ramos

“…The optimization of hybrid systems through Solver and Python algorithms with various objective functions enables optimal design choices tailored to specific needs such as drinking water supply, irrigation, or industrial processes. …”
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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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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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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

“…AI technologies, including predictive modeling and ML algorithms such as random forests and convolutional neural networks (CNNs), can analyze diverse data sources—such as meteorological, environmental, and health records—to detect patterns and predict outbreaks. …”
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Provenance-Finding of Dust Storms Using AVHRR Sensor Images of NOAA Satellite (Case Study: Southwest of Iran) by Mohammad Hossein Rezaei Moghaddam, Mojtaba Mahdian Boruojeni

“…The first area is located in the southwest of Ilam province and bordering of this province with Iraq, which has the highest number of points allocated in terms of density. The dust formed in this area, often does not enter the country affecting the neighboring country. …”
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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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