Machine Learning

Accurate and consistent monitoring of lake water levels is essential for understanding hydrological dynamics and climate-driven variability in remote and data-scarce regions. Satellite altimetry provides high-precision lake level observations, but its limited spatial and temporal coverage constrain large-scale monitoring. Combining Digital Elevation Model (DEM) and remote sensing imagery offers an alternative, but the accuracy of resultant water level is affected by the uncertainties of inherent elevation and image processing.

We developed IIST BCI Dataset-9, a novel EEG-based Brain-Computer Interface (BCI)
dataset to improve wheelchair control systems using Malayalam dialect variations. BCI
systems help people with motor disabilities by allowing them to control devices using brain
signals. The limited number of BCI datasets in Indian languages makes it harder for native
speakers to use these systems. To address this, we created a dataset with 15 Malayalam
words related to basic wheelchair commands like Forward, Backward, Go, Stop, Reverse,

This dataset aims to collect and collate information about activity on the Bitcoin blockchain, with a focus directed at on-chain data which describes the state of the network at any given time. Some examples of these metrics include:

• Datetime
• Mempool Size
• Transaction rate
• market cap usd
• Average block size
• Market price usd
• Exchange volume usd
• Average confirmation time
• Hash rate
• Difficulty
• Miners revenue
• Total transaction fees

This dataset was curated mainly to cater to mitigation strategies for the Human-Peafowl Conflict that exists in these regions. The absence of natural predators has contributed to a significant increase in the peafowl population, exacerbating challenges for farmers. Peafowls are sometimes considered agricultural pests due to their tendency to feed on and damage crops. The vocalizations are from the Indian Peafowl (Pavo cristatus), a species native to the Indian subcontinent and especially abundant in India and Sri Lanka.

The increasing congestion of the radio frequency spectrum presents challenges for efficient spectrum utilization. Cognitive radio systems enable dynamic spectrum access with the aid of recent innovations in neural networks. However, traditional real-valued neural networks (RVNNs) face difficulties in low signal-to-noise ratio (SNR) environments, as they were not specifically developed to capture essential wireless signal

Abstract

Hamstring Injuries (HSIs) are common among athletes and necessitate extended rehabilitation before Return to Sport (RTS). Post-injury, athletes undergo physical examinations, which often fall short in assessing injury severity or guiding rehabilitation. Therefore, imaging techniques such as Magnetic Resonance Imaging (MRI) are used to evaluate the injury more comprehensively, aiding in the assessment of optimal rehabilitation and RTS timelines. Given the significant impact of HSIs on athletic careers, early prediction is essential.

The dataset is constructed using SUMO. It contains two road network datasets of different scales: a small-scale network (SR) and a larger regional network in Shenyang (SY). The dataset was constructed using the SUMO simulation platform, containing two road network datasets at different scales: a small-scale test network (SR) and a regional-level Shenyang network (SY). The SR network comprises 110 road segments, while the SY network contains 514 segments.

This dataset comprises high-resolution 3-axis accelerometer recordings collected from human participants performing distinct hand gestures, intended for training gesture-based assistive interfaces. Each participant’s raw motion signals are individually organized, enabling both user-specific and generalizable model development. The dataset includes time-series accelerometer data, along with a feature-augmented version containing extracted statistical and temporal descriptors such as RMS, Jerk, Entropy, and SMA. 

This data provides a comprehensive collection of air quality and meteorological data from several large cities in India. With 1,410 records, it includes key characteristics like the Air Quality Index (AQI) according to both U.S. and China standards, temperature, atmospheric pressure, humidity, wind speed, wind direction, and timestamps.