Abstract: This dataset is sourced from anonymous health check-up records from a hospital, containing a variety of health indicators from different participants. The dataset includes basic information about the participants (such as gender, age, etc.) as well as a series of health metrics, such as blood pressure, weight, and diabetes-related indicators (e.g., urea nitrogen, blood glucose, insulin levels), along with diagnostic recommendations for each participant.
This dataset comprises a collection of CSV files containing paired time-series measurements essential for nonlinear compensation research in electrochemical seismometers (MET). Each CSV file, named according to specific magnitude-frequency combinations (magX_freqY.csv), contains two columns: 'origin' representing the original system response and 'target' representing the desired compensated output.
This dataset contains heartbeat and electromyography (EMG) signals recorded from the brachioradialis muscle under different conditions: rest and induced fatigue. It is intended for research in biomechanics, fatigue detection, and physiological signal processing. The data provide insights into muscle activity and heart rate variations, making it valuable for applications in biomedical engineering and human performance analysis.
At-sea testing of underwater acoustic communication systems requires resources unavailable to the wider research community, and researchers often resort to simplified channel models to test new protocols. The present dataset comprises in-situ hydrophone recordings of communications and channel probing waveforms, featuring an assortment of popular modulation formats. The waveforms were transmitted in three frequency bands (4-8 kHz, 9-14 kHz, and 24-32 kHz) during an overnight experiment in an enclosed fjord environment, and were recorded on two hydrophone receivers.
Photoplethysmography (PPG) is a low cost non-invasive
optical technique that can be used to assess changes in tissue
blood volume [6]. This method provides valuable information
related to the cardiovascular system. The tissue's region is
illuminated using a light source and a photodetector records
the reflected light, which varies depending on the presence
and concentration of RBCs and their oxygenation levels.
Depending on the oxygenation level of hemoglobin, RBCs
absorb light in different ways. When blood volume in the
Semantic code search, retrieving code that matches a given natural language query, is an important task to improve productivity in software engineering. Existing code search datasets face limitations: they rely on human annotators who assess code primarily through semantic understanding rather than functional verification, leading to potential inaccuracies and scalability issues. Additionally, current evaluation metrics often overlook the multi-choice nature of code search. This paper introduces CoSQA+, pairing high-quality queries from CoSQA with multiple suitable codes.
This study presents a deep learning-based framework for detecting vehicle deceleration patterns using Ultra-Wideband (UWB) Channel Impulse Response (CIR) analysis. Unlike traditional GPS or IMU-based systems, which struggle in GPS-denied environments such as tunnels, the proposed method leverages UWB CIR signal variations to classify two key driving behaviors: rapid deceleration and gradual deceleration. All data were collected from real-world experiments using UWB devices installed on actual vehicles at a professional highway testing site.
three-level network topology experimental environment was constructed based on a typical home network. An optical network terminal (Bell XE-140W-TD) was used as the starting point for Internet access, and a Gigabit wired connection was established with the core router (Huawei TC30) via a shielded Cat 6 cable. This router is a Huawei beta version that can obtain specific device information and corresponding traffic after NAT. The experimental evaluation of traffic attribution association in subsequent chapters will use this as ground truth label data for comparison.
This dataset provides detailed information and customer reviews for restaurants listed on Zomato in Bangalore, with a focus on The Nest - The Den Bengaluru, located on ITPL Main Road, Whitefield. It includes key attributes such as location, contact details, rating, cuisines offered, average cost, and detailed user-generated reviews. The dataset is ideal for sentiment analysis, customer feedback mining, restaurant recommendation systems, and hospitality service quality studies.
This dataset provides detailed information and customer reviews for restaurants listed on Zomato in Bangalore, with a focus on The Nest - The Den Bengaluru, located on ITPL Main Road, Whitefield. It includes key attributes such as location, contact details, rating, cuisines offered, average cost, and detailed user-generated reviews. The dataset is ideal for sentiment analysis, customer feedback mining, restaurant recommendation systems, and hospitality service quality studies.
This dataset provides detailed information and customer reviews for restaurants listed on Zomato in Bangalore, with a focus on The Nest - The Den Bengaluru, located on ITPL Main Road, Whitefield. It includes key attributes such as location, contact details, rating, cuisines offered, average cost, and detailed user-generated reviews. The dataset is ideal for sentiment analysis, customer feedback mining, restaurant recommendation systems, and hospitality service quality studies.
This dataset provides packet traces captured in a realistic 5G Vehicle-to-Everything (5G-V2X) environment, encompassing both legitimate vehicular communications and Distributed Denial of Service (DDoS) attacks. By deploying four user equipments (UEs) under multiple attacker configurations, the collected captures reflect various DDoS types (TCP SYN, UDP, and mixed) and reveal their impact on 5G-V2X networks. The dataset is further enriched with Argus files and CSV feature tables, facilitating data-driven approaches such as Machine Learning (ML)-based detection agents.
This dataset contains Challenge-Response Pairs (CRPs) from Ring Oscillator-based Physical Unclonable Functions (RO-PUFs) operating under constant and variable voltage conditions. Collected from three chips fabricated in a 22nm FDSOI process and powered by a Switched-Capacitor DC-DC converter, it includes two sections: responses at a fixed voltage and across nine voltage levels (nominal and ±10% variations). Organized into ten folders, the dataset includes 1K CRPs per chip for each voltage and a combined folder with 20K CRPs.
PassengerEEG is a brain-signal dataset designed to study how human passengers perceive and cognitively respond to potential traffic hazards in highly automated vehicles (AVs). As AVs increasingly replace human drivers, understanding passenger cognition becomes essential for improving vehicle safety and adaptive decision-making.
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Electroplating chemicals are the silent architects behind the shiny, corrosion-resistant surfaces we often take for granted. From the gleaming chrome on car parts to the delicate gold plating on jewelry, these chemicals are the backbone of a process that blends chemistry with craftsmanship. At its core, electroplating is the method of depositing a thin layer of metal onto the surface of another material using electric current, and the chemicals involved make all the difference. But this isn’t just science—it’s also art.
Electroplating chemicals are the silent architects behind the shiny, corrosion-resistant surfaces we often take for granted. From the gleaming chrome on car parts to the delicate gold plating on jewelry, these chemicals are the backbone of a process that blends chemistry with craftsmanship. At its core, electroplating is the method of depositing a thin layer of metal onto the surface of another material using electric current, and the chemicals involved make all the difference. But this isn’t just science—it’s also art.
This dataset presents the distribution networks developed in our unpublished paper, "US Representative Feeder Sets for Distribution Grid Economics and Policy Applications." In the paper, we generate feeder sets that reproduce the economic characteristics of local distribution grids by starting from prototypical feeders that represent the electric installations in a specific location.
In order to accelerate the CU partitioning in VVC-SCC, we have established a specialized dataset for screen content. Firstly, we collect a wide variety of screen content videos and images in YUV format. Secondly, we encode these sequences under four different Quantization Parameters (QPs) to obtain comprehensive information about CU partitioning in VVC-SCC. This includes the length, width, position, mode labels, and RDcost values corresponding to each mode. This dataset will provide valuable data support for optimizing the CU partitioning process in screen content coding.
This is the dataset for paper VI-BEVSEG training and testing. For more details about the dataset structure, please refer to Nuscense or V2X-Sim. We only use the number 1 vehicle in the V2X-Sim dataset. Replace the folder in this dataset, and only keep the vehicle 1 six onboard cameras information, infrastructure camera information and their semantic camera information in 'sweeps' and 'samples' folder. Then replace the 'v1.0-trainval' folder with ours and put the h5 maps under V2X-Sim folder.
This is the dataset for paper VI-BEVSEG training and testing. This dataset mostly inherits from V2X-Sim dataset. Follow the same dataset structure as the V2X-Sim dataset. Follow the V2X-Sim instruction to use. The only change we made is adding some 'h5' ground truth semantic maps. And we only keep the vehicle 1 camera information and infrastructure camera information.
This dataset presents longitudinal measurements of plant growth characteristics under varying lighting conditions. Collected for 30 individual plants, the data spans multiple time points and includes key variables such as plant fresh weight (g), plant height (mm), plant width (mm), and number of leaves. Each measurement is associated with a specific plant, date (DD/MM/YYYY), experimental group, and a lighting recipe defined by the percentage composition of Red, Green, and Blue light.
Introduction
Welcome to the new challenging event-based multi-object tracking dataset (DSEC-MOT) repository. Our goal is to provide a challenging and diverse event-based MOT dataset with various real-world scenarios to facilitate the objective and comphrehensive evaluation of event-based multi-object tracking algorithms. This dataset, built upon DSEC, contains a variety of traffic entities and complex scenarios, aiming to address the current lack of event-based MOT datasets.
