Improving Integrated Energy Systems With Improved Particle Swarm Optimization: Co-Optimizing Renewables, Electric Vehicles, Gas Systems, and Demand Management by Vahid Khademi, Soodabeh Soleymani, Reza Sharifi, Babak Mozafari

“…This research focuses on optimizing integrated energy systems to enhance both energy efficiency and profitability. Due to the uncertainty in renewable energy output and fluctuating electricity prices, a scenario-based model is utilized. …”
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A scoping review of artificial intelligence applications in clinical trial risk assessment by Douglas Teodoro, Nona Naderi, Anthony Yazdani, Boya Zhang, Alban Bornet

“…AI techniques, including traditional machine learning, deep learning (e.g., graph neural networks, transformers), and causal machine learning, are used for tasks like adverse drug event prediction, treatment effect estimation, and phase transition prediction. These methods utilize diverse data sources, from molecular structures and clinical trial protocols to patient data and scientific publications. …”
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Smart Tool-Related Faults Monitoring System Using Process Simulation-Based Machine Learning Algorithms by Arash Ebrahimi Araghizad, Faraz Tehranizadeh, Kemal Kilic, Erhan Budak

“…In this paper a novel approach for monitoring tool-related faults in milling processes by utilizing process simulation-based machine learning algorithms, specifically Random Forest algorithms, for fault detection is presented. …”
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Cloud-Based Internet-of-Things System for Long-Term Bridge Bearing Monitoring Using Computer Vision by Gunhee Kim, Junsik Shin, Jongbin Won, Jongwoong Park

“…The system features an event-driven power mechanism to minimize energy consumption and utilizes vision-based displacement measurement techniques, providing both portability and efficiency. …”
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GC-MT: A Novel Vessel Trajectory Sequence Prediction Method for Marine Regions by Haixiong Ye, Wei Wang, Xiliang Zhang

“…This study introduces a Graph Convolutional Mamba Network (GC-MT) utilizing AIS data for predicting vessel trajectories. …”
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Load frequency control in isolated island city microgrids using deep graph reinforcement learning considering extensive scenarios by Ping He, Xiongwei Huang, Ruobing He, Linkun Yuan

“…In addition, transfer learning is utilized to bolster the agents’ learning efficacy and adaptability to new conditions. …”
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Enhanced Occupational Safety in Agricultural Machinery Factories: Artificial Intelligence-Driven Helmet Detection Using Transfer Learning and Majority Voting by Simge Özüağ, Ömer Ertuğrul

“…A transfer learning approach was employed, utilizing nine pre-trained neural networks for the extraction of deep features. …”
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Deep Water Subsea Energy Storage, Lessons Learned from the Offshore Oil and Gas Industry by Rasmus Juhlin, Alexander H. Slocum, Mohsen Assadi

“…In a future where a large portion of power will be supplied by highly intermittent sources such as solar- and wind-power, energy storage will form a crucial part of the power mix ensuring that there is enough flexibility in the system to cope with the intermittency. …”
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Classification of Complex Power Quality Disturbances Based on Lissajous Trajectory and Lightweight DenseNet by Xi Zhang, Jianyong Zheng, Fei Mei, Huiyu Miao

“…To achieve a rapid response and highly accurate classification of power quality disturbances (PQDs), this paper proposes an efficient classification algorithm for PQDs based on Lissajous trajectory (LT) and a lightweight DenseNet, which utilizes the concept of Lissajous curves to construct an ideal reference signal and combines it with the original PQD signal to synthesize a feature trajectory with a distinctive shape. …”
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Stochastic carbon footprint tracing for power systems with uncertainty by Jiashuo Hu, Mengge Shi, Xiao‐ping Zhang, Youwei Jia

“…Abstract The increasing penetration of distributed energy resources (DERs) and renewable energy sources (RESs) requires more granular analysis for accurate carbon footprint tracing. …”
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Forecasting Electricity Demand in Renewable-Integrated Systems: A Case Study from Italy Using Recurrent Neural Networks by Alessandro Franco, Cecilia Pagliantini

“…Utilizing real consumption data from Terna—Rete Elettrica Nazionale S.p.A.…”
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Financing health system elements in Africa: A scoping review. by Humphrey Cyprian Karamagi, David Njuguna, Solyana Ngusbrhan Kidane, Herve Djossou, Hillary Kipchumba Kipruto, Aminata Binetou-Wahebine Seydi, Juliet Nabyonga-Orem, Diane Karenzi Muhongerwa, Kingsley Addai Frimpong, Benjamin Musembi Nganda

“…Thus, we aimed to generate evidence on how to utilize resources from different sources of funds in Africa. …”
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Aboveground biomass estimation using multimodal remote sensing observations and machine learning in mixed temperate forest by Shashika Himandi Gardeye Lamahewage, Chandi Witharana, Rachel Riemann, Robert Fahey, Thomas Worthley

“…We utilized 67 explanatory variables, which were extracted from three RS sources resulting in nine RF models. …”
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Carbon footprint assessment of livestock farms under tropical conditions: first approximation by S. A. Guamán-Rivera, F. M. Carrillo Riofrío, M. E. Jativa-Brito, L. E. Chuqui-Puma, G. M. Soldado Soldado, L. D. Cabezas Andrade, H. R. Sanchez Quispe, A. A. Casierra Cardenas, J. M. Mira Naranjo, J. P. Santillán Aguirre, C. D. Congo-Yépez

“…Abstract This study evaluates the carbon footprint (CF) of livestock farms in the Orellana Province of the Ecuadorian Amazon, focusing on emissions from enteric fermentation, manure management, and energy use. Utilizing Tier I and Tier II methodologies outlined by the IPCC (2006), the research quantifies greenhouse gas (GHG) emissions across three distinct typologies of Agricultural Productive Units (APUs): Conventional Systems (Type 1), Efficient Resource Use (Type 2), and Subsistence and Dependency Systems (Type 3). …”
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DBA-ViNet: an effective deep learning framework for fruit disease detection and classification using explainable AI by Saravanan Srinivasan, Lalitha Somasundharam, Sukumar Rajendran, Virendra Pal Singh, Sandeep Kumar Mathivanan, Usha Moorthy

“…Abstract Objective The primary aim of this research is to develop an effective and robust model for identifying and classifying diseases in general fruits, particularly apples, guavas, mangoes, pomegranates, and oranges, utilizing computer vision techniques. Material An open-source collection of fruit disease images, comprising both diseased and healthy samples from the first five fruit types, was used in this study. …”
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Power control of an autonomous wind energy conversion system based on a permanent magnet synchronous generator with integrated pumping storage by Farid Merahi, Hamza Mernache, Djamal Aouzelag, Abd Essalam Badoud, Mohit Bajaj, Ievgen Zaitsev

“…Abstract Wind energy plays a crucial role as a renewable source for electricity generation, especially in remote or isolated regions without access to the main power grid. …”
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AI-powered literature search: some observations and concerns by Farooq Azam Rathore, Fareeha Farooq

“…This raises questions about the data sources utilized by these AI tools and the overall reliability of their outputs. …”
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Optimizing E-Commerce Selection Under Uncertainty: A New Framework for Decision-Making With Extended Fuzzy TOPSIS by Jency Leona Edward, Palanivel Kaliyaperumal

“…Data pertinent to e-commerce websites during the pandemic was sourced from various channels, including web analytics, marketing reports, and customer feedback surveys. …”
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Enhancing Security Operations Center: Wazuh Security Event Response with Retrieval-Augmented-Generation-Driven Copilot by Ismail, Rahmat Kurnia, Farid Widyatama, Ilham Mirwansyah Wibawa, Zilmas Arjuna Brata, Ukasyah, Ghitha Afina Nelistiani, Howon Kim

“…This paper specifically utilizes Wazuh, an open-source Security Information and Event Management (SIEM) platform, as the foundation for capturing, analyzing, and correlating security events from endpoints. …”
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Online Prediction and Correction of Static Voltage Stability Index Based on Extreme Gradient Boosting Algorithm by Huiling Qin, Shuang Li, Juncheng Zhang, Zhi Rao, Chengyu He, Zhijun Chen, Bo Li

“…With the increasing integration of renewable energy sources into the power grid and the continuous expansion of grid infrastructure, real-time preventive control becomes crucial. …”
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