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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An interpretable machine learning model to predict hospitalizations by Hagar Elbatanouny, Hissam Tawfik, Tarek Khater, Anatoliy Gorbenko

“…Leveraging a comprehensive dataset sourced from the Mexican government, various supervised learning algorithms including Random Forest, Gradient Boosting, Support Vector Machine, K-Nearest Neighbors, and Multilayer Perceptron are trained and evaluated to discern factors contributing to hospitalizations. …”
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AnimalMotionViz: An interactive software tool for tracking and visualizing animal motion patterns using computer vision by Angelo L. De Castro, Jin Wang, Jessica G. Bonney-King, Gota Morota, Emily K. Miller-Cushon, Haipeng Yu

“…Although several precision livestock technologies have been developed to record dairy cattle movements, there is a lack of open-source tools to track and visualize group-level cattle movement patterns. …”
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Division of Multi-harmonic Responsibilities Based on DBSCAN Clustering and Interval Regression by Shilong CHEN, Tao WU, Cheng GUO, Zirui ZHANG, Jinghao SUN

“…The harmonic monitoring data of an actual power grid is used to verify the proposed method, and it is proved that the proposed method can use the existing statistical harmonic monitoring data to allocate the harmonic responsibility of each harmonic source in a reasonable time scale under background harmonic changes, which can provide new ideas for the division of responsibility for multiple harmonics during the operation of the actual power system.…”
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Deep Learning-Driven Geospatial Modeling of Elderly Care Accessibility: Disparities Across the Urban-Rural Continuum in Central China by Yi Yu, Tian Dong

“…Taking Changsha as a case study, this research constructs an accessibility evaluation system based on the 15-min life circle theory, utilizing multi-source data. Spatial weighting characteristics of elderly care facility locations were analyzed through machine learning algorithms, and service coverage disparities between urban districts and suburban towns were assessed under 5-, 10-, and 15-min walking thresholds. …”
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Opinion Mining on Viet Thanh Nguyen’s The Sympathizer Using Topic Modelling and Sentiment Analysis by Sea Yun Ying, Pantea Keikhosrokiani, Moussa Pourya Asl

“…This study aims to propose a computerized method to examine how matters of space and spatiality are addressed in literary writings. As the primary source of data, the study will focus on Viet Thanh Nguyen’s The Sympathizer (2015), which explores the lives of Vietnamese diaspora in two geographical locations, Vietnam, and America. …”
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Incorporating Contextual Factors into a Comprehensive Analysis of Operational Efficiency and Service Quality in Healthcare Sector by Utsav Pandey, Sanjeet Singh

“…The results show that the efficiency scores in operational productivity and quality of service are 67% and 64%, respectively. The major source of inefficiency is the number of cases in observation rooms (almost 47%) followed by health examination (22%). …”
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Integrating Machine Learning for Enhanced Agricultural Productivity: A Focus on Bananas and Arecanut in the Context of India’s Economic Growth by B. S. Saruk, G. Mokesh Rayalu

“…Agriculture is the main source of income for most developing nations. The purpose of the study is to investigate the significant role that agriculture plays in boosting India's economic growth. …”
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Wireless-powered cooperative energy aware anycast routing in wireless sensor networks by Fazle Hadi, Sheeraz Ahmed, Abid Ali Minhas, Abdulaziz Al Mazyad, Najam ul Islam, Imran Ahmed, Nadeem Javaid

“…In contrary to conventional cooperative networks, it is considered here that all the relays did not have embedded energy supply, rather equipped with rechargeable batteries and energy harvesting units. Hence, from source signals, they accumulate sufficient harvested energy before the information is forwarded to its destination. …”
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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

“…This extensive search yielded 184 eligible papers from eight electronic sources. A total of 97 papers have been chosen for further analysis based on inclusion and exclusion criteria. …”
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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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Lossless Hyperspectral Image Compression in Comet Interceptor and Hera Missions with Restricted Bandwith by Kasper Skog, Tomáš Kohout, Tomáš Kašpárek, Antti Penttilä, Monika Wolfmayr, Jaan Praks

“…The JPEG 2000 implementation is sourced from the JasPer library, whereas a custom implementation was written for CCSDS 122.0. …”
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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

“…When integrated with renewable sources, such as solar (PV) and wind energy, they offer a flexible, long-lasting energy management system, applicable across different water-energy sectors to support Sustainable Development Goals. …”
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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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Content-based dynamic superframe adaptation for Internet of Medical Things by Yousaf Zia, Arshad Farhad, Faisal Bashir, Kashif Naseer Qureshi, Ghufran Ahmed

“…It uses five Quality of Service metrics simultaneously: the application defined data traffic, receive ratio, Personal Area Network source nodes in numbers, number of collisions, and observed delay to achieve the optimal solution. …”
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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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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

“…In addition, following methods were used: scientific sources review, document analysis and observation method based on the university materials, in whose activities the methodology for calculating the number of teaching staff has been implemented through economically justified standards.Results: the focus of the presented research was aimed at increasing the efficiency of financial support for the salaries of teaching staff. …”
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