The dataset contains fundamental approaches regarding modeling individual photovoltaic (PV) solar cells, panels and combines into array and how to use experimental test data as typical curves to generate a mathematical model for a PV solar panel or array.

The work starts with a short overview of grid requirements for photovoltaic (PV) systems and control structures of grid-connected PV power systems. Advanced control strategies for PV power systems are presented next, to enhance the integration of this technology. The aim of this work is to investigate the response of the three-phase PV systems during symmetrical and asymmetrical grid faults.

Driving behavior plays a vital role in maintaining safe and sustainable transport, and specifically, in the area of traffic management and control, driving behavior is of great importance since specific driving behaviors are significantly related with traffic congestion levels. Beyond that, it affects fuel consumption, air pollution, public health as well as personal mental health and psychology. Use of Smartphone sensors for data acquisition has emerged as a means to understand and model driving behavior. Our aim is to analyze driving behavior using on Smartphone sensors’ data streams.

Real-time gesture recognition with bio-impedance measurement. Two videos , one for hand gesture, another for pinch gesture

This data resource is an outcome of the NSF RAPID project titled "Democratizing Genome Sequence Analysis for COVID-19 Using CloudLab" awarded to University of Missouri-Columbia.

The resource contains the output of variant analysis (along with CADD scores) on human genome sequences obtained from the COVID-19 Data Portal. The variants include single nucleotide polymorphisms (SNPs) and short insert and deletes (indels).

This dataset is released with our research paper titled “Scene-graph Augmented Data-driven Risk Assessment of Autonomous Vehicle Decisions” (https://arxiv.org/abs/2009.06435). In this paper, we propose a novel data-driven approach that uses scene-graphs as intermediate representations for modeling the subjective risk of driving maneuvers. Our approach includes a Multi-Relation Graph Convolution Network, a Long-Short Term Memory Network, and attention layers.

The datasets consist of operational data and detailed information of three inverter transformers in a 3.275 MW PV plant in the outskirt of Brisbane, Australia. The data includes load current, top-oil temperature, moisture in top oil, ambient temperature, solar irradiance and individual current harmonics (up to 31st order). The time interval of the data is either 1 minute or 3 seconds (dependent on the data type). The data can be used to study the ageing of inverter transformers in this PV plant. 

A team of researchers from Qatar University, Doha, Qatar, and the University of Dhaka, Bangladesh along with their collaborators from Malaysia in collaboration with medical doctors from Hamad Medical Corporation and Bangladesh have created a database of chest X-ray images for Tuberculosis (TB) positive cases along with Normal images. In our current release, there are 3500 TB images, and 3500 normal images.

This is a repository of 102 smart home conflict scenarios, which were designated as conflict by actual human users. In other words, humans consider the scenarios below to be conflicts in a smart home environment. To see how to use this repository, and how the repository was collected, please read the following paper:

Giemsa-stained thin blood smear slides from 150 P. falciparum-infected and 50 healthy patients were collected and photographed at Chittagong Medical College Hospital, Bangladesh. The smartphone’s built-in camera acquired images of slides for each microscopic field of view.