Machine Learning

This paper introduces a dataset capturing brain signals generated by the recognition of 100 Malayalam words, accompanied by their English translations. The dataset encompasses recordings acquired from both vocal and sub-vocal modalities for the Malayalam vocabulary. For the English equivalents, solely vocal signals were collected. This dataset is created to help Malayalam speaking patients with neuro-degenerative diseases.


A real world radio frequency fingerprinting (RFF) dataset for enhancement strategy by exploiting the physical unclonable function (PUF) to tune the RF hardware impairments in a unique and secure manner, which is exemplified by taking power amplifiers (PAs) in RF chains as an example. This is achieved by intentionally and slightly tuning the PA non-linearity characteristics using the active load-pulling technique. The dataset is collected from the cable-connected measurement and over-the-air measurement.


 Publicly available dataset weibo_senti_100k, which consists of Weibo comments, verify the validity of the model. We have assigned the label of 0 to negative semantics, 1 to neutral statements, and 2 to positive semantics in the dataset,comments data is divided into a training set, a test set and a validation set, distributed in a ratio of 3:1:1 to facilitate the training and evaluation of our machine learning model.


As an artificial structure, tailings ponds exhibit regular geometric shapes and relatively straight dams in HRRSIs. Because the typical tailings dam is composed of an initial dam and successive accumulation dams, the tailings dam structure presents obvious linear stripe characteristics. The initial dam, constructed using sand, gravel, or concrete, has a bright color, while the color of the accumulation dam varies based on factors such as particle size, soil coverage, and vegetation restoration.


Public safety is seriously threatened by road accidents, which are a major global concern in urban settings. The capital of Bangladesh, Dhaka City, stands out among these locations as a perfect illustration of the complicated difficulties confronted by highly populated cities in ensuring road safety. In this paper, we have used time-series analysis to model the temporal patterns and trends in accident occurrence and machine learning algorithms to identify accident hotspots and comprehend the causes of traffic accidents.


The uploaded project is the code and dataset for Charging Efficiency Optimization Based on Swarm Reinforcement Learning under Dynamic Energy Consumption for WRSN. The details of each document in the uploaded project are as follows. Document data: The data file contains network data and simulation data. Document iostream: The iostream file contains the program for reading data and writing data. Document main: The main file contains the main program that executes the simulation. Document network: The network file


The Colour-Rendered Bosphorus Projections (CRBP) Face Dataset represents an innovative advancement in facial recognition and computer vision technologies. This dataset uniquely combines the precision of 3D face modelling with the detailed visual cues of 2D imagery, creating a multifaceted resource for various research activities. Derived from the acclaimed Bosphorus 3D Face Database, the CRBP dataset introduces colour-rendered projections to enrich the original dataset.


This work presents a new labeled dataset of videos with native and professional interpreters articulating words and expressions in Libras (Brazilian Sign Language). We used a methodology based on related studies, the support of the team of articulators, and the existing datasets in the literature.


This dataset is designed for the purpose of curve fitting, a key process in the reconstruction of implicit curves. It encompasses a collection of point cloud data that has been sampled directly from curves, as well as the code necessary to generate point cloud data from these curves.


X-CANIDS Dataset (In-Vehicle Signal Dataset)

In March 2024, one of our recent research "X-CANIDS: Signal-Aware Explainable Intrusion Detection System for Controller Area Network-Based In-Vehicle Network" was published in IEEE Transactions on Vehicular Technology. Here we publish the dataset used in the article. We hope our dataset facilitates further research using deserialized signals as well as raw CAN messages.

Real-world data collection. Our benign driving dataset is unique in that it has been collected from real-world environments.