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Context

ViC dataset is a collection for implementing a Dynamic Spectrum Access(DSA) system testbed in the CBRS band in the USA. This data is a DSA system which consists of a 2-tier user : Incident user: generating a chirp signal with a Radar system, Primary user: LTE-TDD signal with a CBSD base station system, and corresponds to signal waveforms in the band 3.55-3.56 GHz (Ch1), 3.56-3.57 GHz (Ch2) respectively. There are a total of 12 classes, excluding the assumption that two of the 16 cases are used by CBSD base stations, depending on the presence or absence of two users in two channels. The labels of each data have the following meanings :

0000 (0) : All off 0001 (1) : Ch2 - Radar on 0010 (2) : Ch2 - LTE on 0011 (3) : Ch2 – LTE, Radar on 0100 (4) : Ch1 – Radar on 0101 (5) : Ch1 – Radar on / Ch2 – Radar on 0110 (6) : Ch1 – Radar on /Ch2 – LTE on 0111 (7) : Ch1 – Radar on / Ch2 – LTE, Radar on 1000 (8) : Ch1 – LTE on 1001 (9) : Ch1 – LTE on / Ch2 – Radar on (X) 1010 (10) : Ch1 – LTE on / Ch2 – LTE on (X) 1011 (11) : Ch1 – LTE on / Ch2 – LTE, Radar on 1100 (12) : Ch1 – LTE, Radar on 1101 (13) : Ch1 – LTE, Radar on / Ch2 – Radar on (X) 1110 (14) : Ch1 – LTE, Radar on / Ch2 – LTE on (X) 1111 (15) : Ch1 – LTE, Radar on / Ch2 – LTE, Radar on

Content

This dataset has a total of 7 types consisting of one raw dataset expressed in two extensions, 4 processed datasets processed in different ways, and a label. Except for one of the datasets, all are Python version of numpy files, and the other is a csv file.

(Raw) The raw data is a IQ data generated from testbeds created by imitating the SAS system of CBRS in the United States. In the testbeds, the primary user was made using the LabView communication tool and the USRP antenna (Radar), and the secondary user was made by manufacturing the CBSD base station. This has both csv format and numpy format exist.

(Processed) All of these data except one are normalized to values between 0 and 255 and consist of spectrogram, scalogram, and IQ data. The other one is a spectrogram dataset which is not normalized. They are measured between 250us. In the case of spectrograms and scalograms, the figure formed at 3.56 GHz to 3.57 GHz corresponds to channel 1, and at 3.55 GHz to 3.56 GHz corresponds to channel 2. Among them, signals transmitted from the CBSD base station are output in the form of LTE-TDD signals, and signals transmitted from the Radar system are output in the form of Chirp signals.

(Label) All of the above five data share one label. This label has a numpy format.

Total-Long-Term-Liabilities Time Series for Believe SAS. Believe S.A. provides digital music services for independent labels and local artists in France, Germany, rest of Europe, the Americas, Asia, Oceania, and Pacific. It operates through two segments, Premium Solutions and Automated Solutions. The company engages in the sale, promotion, and delivery of digital content provided by artists and labels by developing their catalog on digital platforms and social media; administration of copyrights; provision of synchronization services comprising the use of recorded music in advertising, films and series, video games and television; and organization of musical events. It also offers TuneCore digital platform for artists to distribute their audio content in an automated manner to streaming and social media platforms. Believe S.A. was incorporated in 2005 and is headquartered in Paris, France.

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🪔 South Asian Sounds - KIIT 🎧

A curated dataset of 9,450 labeled audio segments capturing the rich and diverse soundscapes of South Asia. This dataset is designed for audio classification tasks and includes sounds ranging from traditional music and religious rituals to environmental noises and animal calls.

📁 Dataset Details

• Total Audio Files: 9,450
• Format: WAV
• Segment Duration: 4 seconds each
• Number of Classes: 21
• File Naming Convention: Class-ID_Class-Name_Segment-Number.wav
• Organization: Randomly distributed across 10 folders
• Metadata File: Included (metadata.csv)

🏷️ Classes and Labels

📄 Metadata Columns

• slice_file_name: Name of the audio segment
• slicing_start_time: Start time of the segment
• slicing_end_time: End time of the segment
• ClassID: Numeric class label (0 to 20)
• Class_name: Descriptive class name
• folder: Folder containing the segment

🌐 Official Website

🔗 sas-kiit.netlify.app

📚 Citation

Paper Link : https://ieeexplore.ieee.org/document/10829485 If you use this dataset, please cite: @inproceedings{chatterjee2024south, title={South Asian Sounds: Audio Classification}, author={Chatterjee, Rajdeep and Bishwas, Pappu and Chakrabarty, Sudip and Bandyopadhyay, Tathagata}, booktitle={2024 4th International Conference on Computer, Communication, Control & Information Technology (C3IT)}, pages={1--6}, year={2024}, organization={IEEE} }

👥 Contributors

• Sudip Chakrabarty
• Pappu Bishwas
• Rajdeep Chatterjee
• Tathagata Bandyopadhyay

📌 License & Usage

This dataset is intended for research and academic use only.
Please provide proper citation when using it in your work.

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The global Top Coated Label Films market is experiencing robust growth, driven by increasing demand across diverse sectors including food & beverages, pharmaceuticals, and personal care. The market's expansion is fueled by several key factors: the rising preference for aesthetically appealing and durable labels, technological advancements in film coating techniques leading to enhanced product protection and shelf life, and the burgeoning e-commerce sector necessitating high-quality labels for efficient product identification and tracking. The projected Compound Annual Growth Rate (CAGR) suggests a substantial market expansion over the forecast period (2025-2033). Polypropylene and Polyethylene segments dominate the market due to their cost-effectiveness and versatility, while applications in the food and beverage industry are expected to witness significant growth owing to stringent regulations and increasing consumer awareness regarding product authenticity and safety. However, fluctuations in raw material prices and environmental concerns related to plastic waste pose potential challenges to market growth. Competitive landscape analysis reveals the presence of both established multinational corporations and regional players, indicating a dynamic market with opportunities for both large-scale production and specialized niche applications. Geographic segmentation shows strong growth in the Asia-Pacific region, driven primarily by the expanding economies of China and India, with significant growth also anticipated in North America and Europe due to established markets and increased consumer demand for branded products. The market is segmented by application and type, with a further breakdown by region providing detailed insights for strategic planning and investment decisions. The historical period (2019-2024) indicates steady growth, establishing a firm foundation for the robust expansion predicted for the forecast period. Future growth is likely to be influenced by innovations in sustainable film technologies and increasing adoption of eco-friendly packaging solutions. Companies are likely focusing on expanding their product portfolios to cater to specific industry needs and enhance their market share within this growing sector.

The Longitudinal Study of Ocular Complications of AIDS was a 15-year multi-center observational study which collected demographic, medical history, treatment, and vision-related data at quarterly visits from 2,392 patients with AIDS. Each SAS dataset in this collection relates to the cumulative patient-visits from a particular LSOCA form. For example, va.sas7bdat is the SAS dataset for the visual acuity data. Use the appropriate LSOCA form and SAS labels from the SAS PROC CONTENTS to decode each data item.

Net-Income Time Series for Believe SAS. Believe S.A. provides digital music services for independent labels and local artists in France, Germany, rest of Europe, the Americas, Asia, Oceania, and Pacific. It operates through two segments, Premium Solutions and Automated Solutions. The company engages in the sale, promotion, and delivery of digital content provided by artists and labels by developing their catalog on digital platforms and social media; administration of copyrights; provision of synchronization services comprising the use of recorded music in advertising, films and series, video games and television; and organization of musical events. It also offers TuneCore digital platform for artists to distribute their audio content in an automated manner to streaming and social media platforms. Believe S.A. was incorporated in 2005 and is headquartered in Paris, France.

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This is the limited access database for the Study to Understand Fall Reduction and Vitamin D in You (STURDY) randomized response-adaptive clinical trial. The database includes baseline, treatment and post randomization data. This Database includes a set of files pertaining to the full study population (688 randomized participants plus screenees who were not randomized) and a set of files pertaining to the burn-in cohort (the 406 participants randomized prior to the first adjustment of the randomization probabilities). The Database also includes files that support the analyses included in the primary outcome paper published by the Annals of Internal Medicine (2021;174:(2):145-156). Each data file in the Database corresponds to a specific data collection form or type of data. This documentation notebook includes a SAS PROC CONTENTS listing for each SAS file and a copy of the relevant form if applicable. Each variable on each SAS data file has an associated SAS label. Several STURDY documents, including the final versions of the screening and trial consent statements, the Protocol, and the Manual of Procedures, are included with this documentation notebook to assist with understanding and navigation of STURDY data. Notes on analysis questions and issues are also included, as is a list of STURDY publications.

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These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed. Teenage adolescent females residing in Baltimore, Maryland who were involved in a relationship with a history of violence were sought after to participate in this research study. Respondents were interviewed and then followed through daily diary entries for several months. The aim of the research was to understand the context regarding teen dating violence (TDV). Prior research on relationship context has not focused on minority populations; therefore, the focus of this project was urban, predominantly African American females. The available data in this collection includes three SAS (.sas7bdat) files and a single SAS formats file that contains variable and value label information for all three data files. The three data files are: final_baseline.sas7bdat (157 cases / 252 variables) final_partnergrid.sas7bdat (156 cases / 76 variables) hart_final_sas7bdata (7004 cases / 23 variables)

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Goodwill Time Series for Believe SAS. Believe S.A. provides digital music services for independent labels and local artists in France, Germany, rest of Europe, the Americas, Asia, Oceania, and Pacific. It operates through two segments, Premium Solutions and Automated Solutions. The company engages in the sale, promotion, and delivery of digital content provided by artists and labels by developing their catalog on digital platforms and social media; administration of copyrights; provision of synchronization services comprising the use of recorded music in advertising, films and series, video games and television; and organization of musical events. It also offers TuneCore digital platform for artists to distribute their audio content in an automated manner to streaming and social media platforms. Believe S.A. was incorporated in 2005 and is headquartered in Paris, France.

Unweighted and weighted percentages for demographic and smoking-related variables.