Machine Learning
Reference Evapotranspiration (ETo) is the basic element of smart irrigation water management for sustainable developments in agriculture. Penman-Monteith (FAO-56 PM) is the standard method of ETo. The FAO-56 PM is complex in nature due to the requirements of many climatic conditions. Many existing machine learning-based solutions for simplification of ETo are limited to a specific area and not in accordance with the standard method FAO-56 PM.
- Categories:
The dataset used in this study was derived from data collected from two courses offered on the University of Jordan's E-learning Portal during the second semester of 2020, namely "Computer Skills for Humanities Students" (CSHS) and "Computer Skills for Medical Students" (CSMS). Over the sixteen-week duration of each course, students participated in various activities such as reading materials, video lectures, assignments, and quizzes. To preserve student privacy, the log activity of each student was anonymized.
- Categories:
BIMCV-COVID19+ dataset is a large dataset with chest X-ray images CXR (CR, DX) and computed tomography (CT) imaging of COVID-19 patients along with their radiographic findings, pathologies, polymerase chain reaction (PCR), immunoglobulin G (IgG) and immunoglobulin M (IgM) diagnostic antibody tests and radiographic reports from Medical Imaging Databank in Valencian Region Medical Image Bank (BIMCV).
- Categories:
<p>Anonymized data used in the study of "<span style="font-family: Calibri, sans-serif; font-size: 11pt;">Administrative data processing, Clustering, classification, and association rules, Human factors and ergonomics, Machine learning"</span></p>
- Categories:
Data preprocessing is a fundamental stage in deep learning modeling and serves as the cornerstone of reliable data analytics. These deep learning models require significant amounts of training data to be effective, with small datasets often resulting in overfitting and poor performance on large datasets. One solution to this problem is parallelization in data modeling, which allows the model to fit the training data more effectively, leading to higher accuracy on large data sets and higher performance overall.
- Categories:
This dataset containg 1900+ images divided into fresh oranges and rotten oranges. In an orange packing factory, a video was recorded, by placing the camera parallel and above the oranges conveyor. The video was captured for 10 minutes with a quality of Ultra High Definition (4K) with 60 frames per second and a High Dynamic Range feature. The video was changed from High Dynamic Range to Standard Dynamic Range by the use of Splice - Video Editor & Maker software. The video is inserted to developed algorithm operating video processing on it and creating the frames.
- Categories:
Driving practices while HR physiology and pre- and post-EDA were acquired. Stress levels are also rated on a 1-5 scale. The gamer's steering wheel angle, pedals, and steering wheel buttons associated with the driving activity are tracked every 10 msec. The normalized data were stored in Figure 1 in the .xlsx file. Using the Balanced Latin Square method, participants develop each level to avoid level learning when designing experiments with multiple conditions.
- Categories:
The Advanced Metering Infrastructure is established in Electrical Drives Laboratory, School of Electrical and Electronics Engineering, SASTRA Deemed to be University, Thanjavur, Tamil Nadu,India. Further, the ARP spoofing attack emulation is deliberated between Smart Meter and Data Concentrator through the Ettercap tool in two different test beds by incorporating Modbus TCP/IP and MQTT.Then, the benign and malicious traffic patterns of two protocols are captured using Wireshark to form the dataset.
- Categories: