The Former Prisoner of War (POW) Statistical Tracking System database is a registry designed to comply with Public Law 97-37, the Former Prisoner of War Benefits Act of 1981. This database contains information about the Medical Evaluation Program for ex-POWs at VA facilities. The program provides a complete medical and psychiatric evaluation of ex-POWs. Only ex-POWs who volunteer to participate in the program are included in this registry. Health examinations are given to ex-POWs at VA facilities. The findings are then recorded on a special coding sheet, VA Form 10-0048a. Quarterly, these code sheets are sent to the Austin Information Technology Center, where they are manually keyed into the database. The main users of this registry are: * The Advisory Committee on Former Prisoners of War * Congress * National Academy of Sciences * Researchers * The National Center for Veteran Analysis and Statistics.

An April 2023 survey of Americans found that around 57 percent of the respondents were concerned about the government tracking their online behavior daily. A further 46 percent were concerned about companies tracking their online data. Approximately 34 percent of respondents were afraid of being tracked online.

An October 2024 survey among adults in the United States found that around ** percent of respondents assume that companies are always collecting and tracking their personal data, compared to only ** percent of those who did not think so.

Cognitive workload is an important component in performance psychology, ergonomics, and human factors. Unfortunately, benchmarks and publicly available datasets are scarce, making it difficult to establish new approaches and comparative studies. In this work, COLET-COgnitive workLoad state estimation based on Eye-Tracking dataset is presented. Forty-seven (47) individuals' eye movements were monitored as they solved puzzles involving visual search tasks of varying complexity and duration. The authors give an in-depth study of the participants' performance during the experiments while eye and gaze features were derived from low-level eye recorded metrics, and their relationships with the experiment tasks were investigated. Finally, the results from the classification of cognitive workload levels solely based on eye and gaze data, by employing and testing a set of machine learning algorithms are provided. The dataset is made available to the public.

Please cite the following work:

Ktistakis, E., Skaramagkas, V., Manousos, D., Tachos, N. S., Tripoliti, E., Fotiadis, D. I., & Tsiknakis, M. (2022). Colet: A dataset for cognitive workload estimation based on eye-tracking. Computer Methods and Programs in Biomedicine, 106989. https://doi.org/10.1016/j.cmpb.2022.106989

Data files for analysis reported in M&C manuscript

County/city, township, date (subgroup indicators such as confirmed cases, gender, age, bacteriology positivity), usage instructions: If interfacing with the machine daily, it is recommended to select the single-day dataset. If selecting the annual cumulative dataset, there are approximately 100,000 to 300,000 records, the data volume is relatively large, and it is recommended to confirm the demand before downloading. Tuberculosis is a chronic infectious disease, and the treatment for individual cases may last 6-8 months or longer. Therefore, the "under management" cases in this dataset refer to cases still under tracking and treatment, regardless of the year of illness. Updated every morning, the previous day's township indicators are summarized. The daily dataset contains up to 369 records, while the annual cumulative dataset contains approximately 100,000 to 300,000 records.

This statistic shows the leading application tracking systems (ATS) used by enterprise and mid-market companies who have their headquarters in the United States in 2020. At that time, Workday was the most widely used ATS among these companies, being the primary ATS for nearly 22 percent of the reviewed 1,063 companies.

This dataset supports our study "Statistical Analysis of Fluorescence Intensity Transients with Bayesian Methods," which introduces Fluorescence Intensity Trace Statistical Analysis (FITSA), a Bayesian approach for direct analysis of fluorescence intensity traces. From these traces, FITSA estimates diffusion coefficient and molecular brightness. The repository contains all fluorescence intensity traces used in our comparative analysis of FITSA and fluorescence correlation spectroscopy (FCS). A README file describes the data structure. We provide both synthetic and experimental datasets that demonstrate various applications of FITSA. When combined with our separately published code, these datasets enable reproduction of our analysis and support further methodological development in the field. Based on our analysis of these traces, we demonstrate that FITSA achieves precision comparable to FCS while requiring substantially fewer photons and shorter measurement times., , , # Experimental and synthetic datasets supporting FITSA: Statistical analysis of fluorescence intensity transients with Bayesian methods

This repository contains the complete set of traces used in the study:

"Statistical Analysis of Fluorescence Intensity Transients with Bayesian Methods"

Authors: Hamed Karimi, Martin Laasmaa, Margus Pihlak, Marko Vendelin

Repository Structure

The datasets are organized in subfolders corresponding to the figures in the study. Since some datasets were used across multiple figures, all relevant figure numbers are included in the subfolder names.

Synthetic Datasets

Multiple synthetic datasets were generated with varying molecular brightness levels, as shown in Figure 5 and associated Supporting Materials figures. These datasets are stored in dedicated subfolders, with the molecular brightness indicated in the subfolder name. For example:

• mu_mol-50k represents data with a molecular brightness of 50,000 1/s

Additional Experimental Dat...,

Examples of descriptive statistics that can be gleaned from Tracker data that could not be determined from standard beam cross data (Track CASK-β N = 30, Track Control N = 29).

This dataset contain information about Statistics of trips, passengers, drivers and vehicles by year and month and activity in tracking vehicles for qualified drivers

a register of waste-tracking in Nauru;

The dataset contains all data used during the evaluation of statistical characteristics preservation. Archives are protected by password "trace-share" to avoid false detection by antivirus software.

For more information, see the project repository at https://github.com/Trace-Share.

Selected Attack Traces

We selected 72 different traces of network attacks obtained from various internet databases. File names refer to common names of contained vulnerabilities, malware, or attack tools.

Background Traffic Data

Publicly available dataset CSE-CIC-IDS-2018 was used as a background traffic data. The evaluation uses data from the day Thursday-01-03-2018 containing a sufficient proportion of regular traffic without any statistically significant attacks. Only traffic aimed at victim machines (range 172.31.69.0/24) is used to reduce less significant traffic.

Evaluation Results and Dataset Structure

Traces variants (traces-normalized.zip, traces-adjusted.zip)

./traces-normalized/ — normalized PCAP files and details in YAML format;

./traces-adjusted/ — configuration files for traces combination in YAML format.

Computed statistics (statistics.zip)

./statistics-background/ — background traffic statistics computed by ID2T;

./statistics-combination/ — combined traces statistics computed by ID2T for all adjust options (selected only combinations where ID2T provided all statistics files);

./statistics-difference/ — computed mean and median differences of background and combined traffic traces.

Evaluation results

statistics-difference.ipynb — file containing visualization of statistics differences.

One data set was used to run the t-tests; the other contains all the data necessary to run the LMMs reported in the paper

The Online Attendance Tracking System market is experiencing significant growth as organizations increasingly transition to digital solutions for managing attendance records and employee time management. These systems provide a streamlined approach to tracking attendance, reducing manual errors, and ensuring accurat

The Ultra Long-Life GPS Tracker market has emerged as a vital sector within the broader GPS tracking industry, catering to an increasing need for reliable location tracking solutions across various applications. These advanced tracking devices boast extended battery life, allowing them to operate for months or even

The Package Tracking Systems market has witnessed a significant transformation over the past decade, driven by the rapid evolution of e-commerce and logistic operations. As businesses and consumers increasingly demand real-time visibility into the status of their shipments, package tracking systems have emerged as e

Between 2020 and 2025, the global GPS tracking device market size is forecast to grow steadily. In 2022, the size of this market amounted to roughly **** billion U.S. dollars, with this number expected to peak to over *** billion dollars at the end of the given period.

The Eye Tracking System market has witnessed significant growth and innovation over recent years, driven by advancements in technology and the increasing demand for user experience enhancements across various industries. Eye tracking technology, which captures and analyzes eye movements, has found applications in fi