<b>Supporting dataset for the construction of a digital twin aquaculture farm based on underwater visual perception and water quality time-series prediction</b>
This dataset contains 8,888 real-world images of cooking oils collected to support Artificial Intelligence (AI) and computer vision research in cooking oil quality assessment. The dataset consists of two cooking oil categories: Soyabean Oil and Mustard Oil. Images were collected…
Traditional power distribution networks within developing energy sectors frequently rely on legacy monitor-<br>ing systems or completely lack digitized telemetry, which severely limits situational awareness and delays<br>fault detection. To address these operational challenges, t…
This study investigated the effectiveness of Generative AI-Supported Competency-Based Instruction on undergraduate students' technical skills, problem-solving ability, self-regulated learning, and employability skills in Electrical/Electronic Technology Education. The findings re…
This study proposes a systematic method to investigate the impact of climate change on water quality using multivariate analysis and machine learning. This approach is applied in the Upper Guadiana Basin (UGB), a semi-arid region in central Spain, by analyzing historical temperat…
This article presents a machine learning-based predictive framework for assessing organizational Decision-Making Quality (DMQ) using Big Data Analytics Capabilities (BDAC) in healthcare organizations. The proposed framework integrates five BDAC dimensions—organizational, technica…
Leaf Area Index (LAI) serves as a key biophysical parameter for characterizing vegetation canopy structure and ecosystem functions. To address the absence of LAI products for the Fengyun-3B (FY-3B) satellite and the limitations of current satellite LAI products, this study propos…