IDEA Section 618 Data Products: Data Displays - Part C IDEA Part C & Part B 619 Data Displays present annual data related to infants, toddlers, and children with disabilities based on data from various sources including IDEA Section 618 data, IDEA Annual Performance Report data, and Census data. The data displays are used to provide a clear, quick and accurate snapshot of each State’s/ entity’s education data regarding children served under the IDEA. 2024 Part C Data Displays 2024 2023 Part C Data Displays 2023 2022 Part C Data Displays 2022 2021 Part C Data Displays 2021

This article discusses how to make statistical graphics a more prominent element of the undergraduate statistics curricula. The focus is on several different types of assignments that exemplify how to incorporate graphics into a course in a pedagogically meaningful way. These assignments include having students deconstruct and reconstruct plots, copy masterful graphs, create one-minute visual revelations, convert tables into “pictures,” and develop interactive visualizations, for example, with the virtual earth as a plotting canvas. In addition to describing the goals and details of each assignment, we also discuss the broader topic of graphics and key concepts that we think warrant inclusion in the statistics curricula. We advocate that more attention needs to be paid to this fundamental field of statistics at all levels, from introductory undergraduate through graduate level courses. With the rapid rise of tools to visualize data, for example, Google trends, GapMinder, ManyEyes, and Tableau, and the increased use of graphics in the media, understanding the principles of good statistical graphics, and having the ability to create informative visualizations is an ever more important aspect of statistics education. Supplementary materials containing code and data for the assignments are available online.

International Data & Economic Analysis (IDEA) is USAID's comprehensive source of economic and social data and analysis. IDEA brings together over 12,000 data series from over 125 sources into one location for easy access by USAID and its partners through the USAID public website. The data are broken down by countries, years and the following sectors: Economy, Country Ratings and Rankings, Trade, Development Assistance, Education, Health, Population, and Natural Resources. IDEA regularly updates the database as new data become available. Examples of IDEA sources include the Demographic and Health Surveys, STATcompiler; UN Food and Agriculture Organization, Food Price Index; IMF, Direction of Trade Statistics; Millennium Challenge Corporation; and World Bank, World Development Indicators. The database can be queried by navigating to the site displayed in the Home Page field below.

The texts of the loan conditions used as raw data for this article was supplied to us by the World Bank on a confidential basis. The replication data therefore only provides our aggregated data that reproduces all the results in the publication itself. To promote replicability and to promote future research on the World Bank and its lending practices, we have reproduced the confidential raw data to the fullest extent possible by relying only on publicly available information. The data set contains the project-specific conditions attached to 1242 World Bank loan and borrowing agreements. For each of these, the data set lists the project number, project year, borrower country ISO3C code, the date of the document, the abbreviated World Bank project name, the URL to the text or PDF document, and the texts of the loan-specific conditions. The latter were extracted through a combination of quantitative text analysis and reading of the actual loan agreement documents. This data covers all the observations used in the article, with the exception of 205 projects with their conditions that the World Bank has chosen to keep confidential. Nearly all of these are from the 1980s. We encourage future research using this data. If you undertake such work, please cite the article as source.

Historical price and volatility data for US Dollar in IDEAS across different time periods.

This project sought to address the changing role of ideas and intellectuals in the public discourses of contemporary 'knowledge societies'. To this end, the ethos and development of two ideas institutions were investigated - the think tank Demos and the LSE. The project sought to reconceptualise the general dynamics of societal ideas and the role of contemporary intellectuals by suggesting that ideas are increasingly 'vehicular' in character, that is, flexible, mobile, pragmatic, inclusive, and geared towards producing an image of their intellectual 'mediators' as agenda-setting agents in an increasingly media-orientated public sphere. Together with the project's analysis of two prominent 'vehicular ideas' - 'Third Way' and 'knowledge society' - the case studies suggest that this perspective is at least fruitful and challenging in understanding contemporary forms of 'ideas work'. Another research task was to assess whether think tanks and universities are converging in style and practice, and some evidence for this was found. However, the influence runs in both directions, with think tanks like Demos incorporating several typically academic norms. The study produced 33 interview transcripts, 18 research diaries, 14 working papers, 13 possible publications, and a journal special issue. Two successful public meetings were held with the hosts at the LSE and Demos.

In support of the 2014 DSITIA Open Data competition, this dataset was developed by departmental workshop participants, and others, to provide ideas for potential uses of science data.

Ideas and activities for inspiring drama is a book. It was written by Phil Parker and published by Folens in 2007.

The Imaging Database for Epilepsy And Surgery (IDEAS)

Peter N. Taylor, Yujiang Wang, Callum Simpson, Vytene Janiukstyte, Jonathan Horsley, Karoline Leiberg, Beth Little, Harry Clifford, Sophie Adler, Sjoerd B. Vos, Gavin P Winston, Andrew W McEvoy, Anna Miserocchi, Jane de Tisi, John S Duncan

Magnetic resonance imaging (MRI) is a crucial tool to identify brain abnormalities in a wide range of neurological disorders. In focal epilepsy MRI is used to identify structural cerebral abnormalities. For covert lesions, machine learning and artificial intelligence algorithms may improve lesion detection if abnormalities are not evident on visual inspection. The success of this approach depends on the volume and quality of training data. Herein, we release an open-source dataset of preprocessed MRI scans from 442 individuals with drug-refractory focal epilepsy who had neurosurgical resections, and detailed demographic information. The MRI scan data includes the preoperative 3D T1 and where available 3D FLAIR, as well as a manually inspected complete surface reconstruction and volumetric parcellations. Demographic information includes age, sex, age of onset of epilepsy, location of surgery, histopathology of resected specimen, occurrence and frequency of focal seizures with and without impairment of awareness, focal to bilateral tonic-clonic seizures, number of anti-seizure medications (ASMs) at time of surgery, and a total of 1764 patient years of post-surgical follow up. Crucially, we also include resection masks delineated from post-surgical imaging. To demonstrate the veracity of our data, we successfully replicated previous studies showing long-term outcomes of seizure freedom in the range of around 50%. Our imaging data replicates findings of group level atrophy in patients compared to controls. Resection locations in the cohort were predominantly in the temporal and frontal lobes. We envisage our dataset, shared openly with the community, will catalyse the development and application of computational methods in clinical neurology.

https://arxiv.org/abs/2406.06731

This release on OpenNeuro includes only raw T1w and FLAR scans. Fully processed data, including resection masks and other demographic information can be found at the following locations: https://www.cnnp-lab.com/ideas-data

• Bids https://figshare.com/s/07fca72410094bc49506 Raw T1w and FLAIR scans organised in BIDS format. Nifti and json descriptors included

• Masks https://figshare.com/s/31ab43d1829b12ac13e8 Resection masks for IDEAS cohort in native, and freesurfer orig.mgz space

• Freesurfer_brain https://figshare.com/s/39b61a1df5fa8443e3c4 skullstripped brain from freesurfer in nifti format

• Freesurfer_orig https://figshare.com/s/f13391a4161b807ce6b0 freesurfer orig.mgz converted to nifti format

• Freesurfer_zip https://figshare.com/s/b13b8bb41390d3f7a088 freesurfer surface and volumetric reconstructions

• Tables_stats_freesurfer https://figshare.com/s/010142dd51e37ba4e4e2 Freesurfer thickness, volume, and surface areas for the Desikan-Kiliany parcellation.

• Tables_metadata https://figshare.com/s/bab70268afeb1071202b clinical and demographic metadata

• Table_resected https://figshare.com/s/097ba0e254e36f0eee52 table indicating the percentage of each brain region in the Desikan-Kiliany atlas subsequently resected by surgery.

• Tables_zscores https://figshare.com/s/8c086fc295a75f85e628 Freesurfer thickness, volume, and surface areas for the Desikan-Kiliany parcellation, z-scored against normative controls post-combat.

• Tables_group_effect https://figshare.com/s/323db205354788c4d1f0 Group effect size differences to controls

Key ideas in economics is a book. It was written by Robert Dransfield and published by Nelson Thornes in 2003.

The Multiview Extended Video with Activities (MEVA) dataset consists video data of human activity, both scripted and unscripted, collected with roughly 100 actors over several weeks. The data was collected with 29 cameras with overlapping and non-overlapping fields of view. The current release consists of about 328 hours (516GB, 4259 clips) of video data, as well as 4.6 hours (26GB) of UAV data. Other data includes GPS tracks of actors, camera models, and a site map. We have also released annotations for roughly 184 hours of data. Further updates are planned.

This repository contains replication data for "Whose ideas are worth spreading? The representation of women and ethnic groups in TED talks".

IDEA Section 618 Data Products: Static Tables Part C Child Count and Settings Table 1 Number of infants and toddlers ages birth through 2 and 3 and older, and percentage of population, receiving early intervention services under IDEA, Part C, by age and state.

Historical price and volatility data for IDEAS in Euro across different time periods.

This statistic shows the revenue of the industry “data processing, hosting and related activities“ in Luxembourg from 2012 to 2017, with a forecast to 2025. It is projected that the revenue of data processing, hosting and related activities in Luxembourg will amount to approximately 394.53 million U.S. Dollars by 2025.

Data DescriptionThe CADDI dataset is designed to support research in in-class activity recognition using IMU data from low-cost sensors. It provides multimodal data capturing 19 different activities performed by 12 participants in a classroom environment, utilizing both IMU sensors from a Samsung Galaxy Watch 5 and synchronized stereo camera images. This dataset enables the development and validation of activity recognition models using sensor fusion techniques.Data Generation ProceduresThe data collection process involved recording both continuous and instantaneous activities that typically occur in a classroom setting. The activities were captured using a custom setup, which included:A Samsung Galaxy Watch 5 to collect accelerometer, gyroscope, and rotation vector data at 100Hz.A ZED stereo camera capturing 1080p images at 25-30 fps.A synchronized computer acting as a data hub, receiving IMU data and storing images in real-time.A D-Link DSR-1000AC router for wireless communication between the smartwatch and the computer.Participants were instructed to arrange their workspace as they would in a real classroom, including a laptop, notebook, pens, and a backpack. Data collection was performed under realistic conditions, ensuring that activities were captured naturally.Temporal and Spatial ScopeThe dataset contains a total of 472.03 minutes of recorded data.The IMU sensors operate at 100Hz, while the stereo camera captures images at 25-30Hz.Data was collected from 12 participants, each performing all 19 activities multiple times.The geographical scope of data collection was Alicante, Spain, under controlled indoor conditions.Dataset ComponentsThe dataset is organized into JSON and PNG files, structured hierarchically:IMU Data: Stored in JSON files, containing:Samsung Linear Acceleration Sensor (X, Y, Z values, 100Hz)LSM6DSO Gyroscope (X, Y, Z values, 100Hz)Samsung Rotation Vector (X, Y, Z, W quaternion values, 100Hz)Samsung HR Sensor (heart rate, 1Hz)OPT3007 Light Sensor (ambient light levels, 5Hz)Stereo Camera Images: High-resolution 1920×1080 PNG files from left and right cameras.Synchronization: Each IMU data record and image is timestamped for precise alignment.Data StructureThe dataset is divided into continuous and instantaneous activities:Continuous Activities (e.g., typing, writing, drawing) were recorded for 210 seconds, with the central 200 seconds retained.Instantaneous Activities (e.g., raising a hand, drinking) were repeated 20 times per participant, with data captured only during execution.The dataset is structured as:/continuous/subject_id/activity_name/ /camera_a/ → Left camera images /camera_b/ → Right camera images /sensors/ → JSON files with IMU data

/instantaneous/subject_id/activity_name/repetition_id/ /camera_a/ /camera_b/ /sensors/ Data Quality & Missing DataThe smartwatch buffers 100 readings per second before sending them, ensuring minimal data loss.Synchronization latency between the smartwatch and the computer is negligible.Not all IMU samples have corresponding images due to different recording rates.Outliers and anomalies were handled by discarding incomplete sequences at the start and end of continuous activities.Error Ranges & LimitationsSensor data may contain noise due to minor hand movements.The heart rate sensor operates at 1Hz, limiting its temporal resolution.Camera exposure settings were automatically adjusted, which may introduce slight variations in lighting.File Formats & Software CompatibilityIMU data is stored in JSON format, readable with Python’s json library.Images are in PNG format, compatible with all standard image processing tools.Recommended libraries for data analysis:Python: numpy, pandas, scikit-learn, tensorflow, pytorchVisualization: matplotlib, seabornDeep Learning: Keras, PyTorchPotential ApplicationsDevelopment of activity recognition models in educational settings.Study of student engagement based on movement patterns.Investigation of sensor fusion techniques combining visual and IMU data.This dataset represents a unique contribution to activity recognition research, providing rich multimodal data for developing robust models in real-world educational environments.CitationIf you find this project helpful for your research, please cite our work using the following bibtex entry:@misc{marquezcarpintero2025caddiinclassactivitydetection, title={CADDI: An in-Class Activity Detection Dataset using IMU data from low-cost sensors}, author={Luis Marquez-Carpintero and Sergio Suescun-Ferrandiz and Monica Pina-Navarro and Miguel Cazorla and Francisco Gomez-Donoso}, year={2025}, eprint={2503.02853}, archivePrefix={arXiv}, primaryClass={cs.CV}, url={https://arxiv.org/abs/2503.02853}, }

This statistic shows the revenue of the industry “data processing, hosting and related activities“ in Germany from 2012 to 2019, with a forecast to 2025. It is projected that the revenue of data processing, hosting and related activities in Germany will amount to approximately 3,757.12 million U.S. Dollars by 2025.

100 ideas for secondary teachers. Teaching philosophy and ethics is a book. It was written by John Taylor and published by Bloomsbury in 2014.

Data from three separate small-scale experiments (N = 55; 30; 58) conducted with students from the University of Cambridge (Engineering Department) and from Delft University of Technology (Industrial Design Engineering). The data consists of participants ideas (scans) and the assessment done by judges (spreadsheets).

As organizations strive to fortify their data security posture in 2024, monitoring unauthorized access attempts emerges as the top priority for 58 percent of companies worldwide. This focus on detecting potential breaches underscores the growing awareness of cyber threats and the critical need for robust cybersecurity measures. Data exfiltration attempts and overprivileged access for humans also rank high on the list of key activities to monitor, highlighting the multifaceted approach required for comprehensive data protection. Evolving security technologies To address these security concerns, companies are implementing various application and data-centric security technologies. Database firewalls lead the pack as the most widely adopted solution, with web application firewalls (WAF) close behind, utilized by over 60 percent of organizations. Looking ahead, many firms plan to acquire bot management tools in the next 12 months, signaling a shift towards more advanced threat detection and prevention mechanisms. Investing in cybersecurity following data breaches The importance of data security is further emphasized by organizations' responses to breaches. A significant 63 percent of companies plan to increase their cybersecurity investment following a data breach, marking a 12 percent rise from the previous year. This proactive approach extends to specific areas such as Incident Response (IR) planning and testing, with 55 percent of firms intending to boost investment in this crucial aspect of cybersecurity. Additionally, over half of the surveyed companies aim to enhance their threat detection and response capabilities in the wake of a breach, demonstrating a commitment to learning from security incidents and strengthening defenses.