This dataset is Bill Proposal History of the Republic of Korea 20th National Assembly(2016-2020) Lawmakers. This dataset consists of 21,594 rows with 37 columns. Contents are mainly written in korean, so translation will be needed for foreign researchers. If any further instruction or information is needed, contact by minhan.nick.cho@gmail.com.
5G-NR is beginning to be widely deployed in the mmWave frequencies in urban areas in the US and around the world. Due to the directional nature of mmWave signal propagation, improving performance of such deployments heavily relies on beam management and deployment configurations.
The dataset has been developed in Smart Connected Vehicles Innovation Centre (SCVIC) of the University of Ottawa in Kanata North Technology Park.
In order to define a benchmark for Machine Learning (ML)-based Advanced Persistent Threat (APT) detection in the network traffic, we create a dataset named SCVIC-APT-2021, that can realistically represent the contemporary network architecture and APT characteristics. Please cite the following original article where this work was initially presented:
Research in Natural Language Processing (NLP) and computational linguistics highly depends on a good quality representative corpus of any specific language. Bangla is one of the most spoken languages in the world but Bangla NLP research is in its early stage of development due to the lack of quality public corpus. This article describes the detailed compilation methodology of a comprehensive monolingual Bangla corpus, KUMono (Khulna University Monolingual corpus).
Healthcare systems are capable of collecting a significant number of patient health-related parameters. Analyzing them to find the reasons that cause a given disease is challenging. Feature Selection techniques have been used to address this issue---reducing these parameters to a smaller set with the most "determinant" information. However, existing proposals usually focus on classification problems---aimed to detect whether a person is or is not suffering from an illness or from a finite set of illnesses.
Bitcoin (BTC), ether (ETH), gridcoin (GRC), curecoin (CURE), and foldingcoin (FLDC) market capitalizations in USD.
We constructed datasets by extracting different features from Android Apk files, including permissions (official definition and customization), APIs and vulnerabilities. The datasets can be used for malware detection.
This data set contains data collected from an overhead crane (https://doi.org/10.1109/WF-IoT.2018.8355217) OPC UA server when driving an L-shaped path with different loads (0kg, 120kg, 500kg, and 1000kg). Each driving cycle was driven with an anti-sway system activated and deactivated. Each driving cycle consisted of repeating five times the process of lifting the weight, driving from point A to point B along with the path, lowering the weight, lifting the weight, driving back to point A, and lowering the weight.
The data we are providing this time is a part of the dataset which was used in our previous work, titled “Integrating Activity Recognition and Nursing Care Records: The System, Deployment, and a Verification Study”. The authors of this work proposed a theory that extending of start and end times of the activities can increase the prediction rate. The reason behind the theory is that many of the nurses provided the labels before or after completing an activity. In the paper, they verified and proved this theory.
