Waveform Dataset: A Collection of Simulated Time Series Signals for Machine Learning and Signal Processing Applications

The Waveform dataset consists of 5,000 samples of synthetic waveform data, with each sample containing 40 continuous and categorical attributes. It consists of 3,000 instances, each of which represents a time series with 21 attributes.

Dataset Card for test-data-generator

This dataset has been created with distilabel.

  Dataset Summary

This dataset contains a pipeline.yaml which can be used to reproduce the pipeline that generated it in distilabel using the distilabel CLI: distilabel pipeline run --config "https://huggingface.co/datasets/franciscoflorencio/test-data-generator/raw/main/pipeline.yaml"

or explore the configuration: distilabel pipeline info --config… See the full description on the dataset page: https://huggingface.co/datasets/franciscoflorencio/test-data-generator.

Dataset used in the article entitled 'Synthetic Datasets Generator for Testing Information Visualization and Machine Learning Techniques and Tools'. These datasets can be used to test several characteristics in machine learning and data processing algorithms.

This submission contains cleaned and filtered data from the Environmental Protection Agency Clean Air Markets CAM database of thermal power plant operation and performance.

Data Center Generator Market is Segmented by Product Type (Diesel, Natural Gas, Hydrogen and HVO-Ready, Other Product Types), Capacity (Less Than 1 MW, 1-2 MW, Greater Than 2 MW), Tier Type (Tier I and II, Tier III, Tier IV), Data Center Type (Hyperscale, Enterprise, Colocation), and Geography. The Market Forecasts are Provided in Terms of Value (USD).

The global data center generator market size is expected to grow from USD 8.43 billion in 2024 to USD 19.66 billion by 2030, at a CAGR of 15.15% from 2024 to 2030.

This data set contains the result of applying the NIST Statistical Test Suite on accelerometer data processed for random number generator seeding. The NIST Statistical Test Suite can be downloaded from: http://csrc.nist.gov/groups/ST/toolkit/rng/documentation_software.html. The format of the output is explained in http://csrc.nist.gov/publications/nistpubs/800-22-rev1a/SP800-22rev1a.pdf.

Dataset

This dataset was created by MLRC2021 Anonymous

Contents

The size of the Data Center Generator Market market was valued at USD 7.92 billion in 2023 and is projected to reach USD 12.97 billion by 2032, with an expected CAGR of 7.3 % during the forecast period. The data center generator market refers to the supply of emergency power solutions that are to be incorporated in data centers to prevent disruption of functioning. These generators are used for powering critical operations that are required during power failure and to support the IT systems as well as protect against data losses. Small-scale examples are data centres, web hosting service providers, interconnect facilities and carrier-neutral colocation facilities. Recent trends in the market also indicate increasing concern towards the use of energy-saving and eco-safe technologies, like dual-frequency generators including renewable power sources. Also, continuing progress in technology is providing impulses; for instance, IoT for real-time monitoring with predictive maintenance possibilities. By nature, the market will continue to experience elevated growth, especially as the consum Recent developments include: In January 2023, EdgeCloudLink (ECL), a startup offering data center-as-a-service, announced its off-grid modular data centers powered by hydrogen. These data centers will be constructed using 3D printing technology in 1MW units. ECL has initiated its first data center project at its headquarters in Mountain View, California, collaborating with a local building services company and utilizing a construction 3D printer. The innovative design will rely on hydrogen from a local source and incorporate a proprietary liquid cooling system. ECL has assured that these hydrogen-powered data centers will operate without diesel generators, further enhancing their sustainability and efficiency , In May 2023, Kohler Power Systems introduced a web-based version to replace its widely used Power Solutions Center desktop app, which is utilized for generator sizing and KOHLER North American industrial product specifications. The newly developed web-based platform, the Power Solutions Center (PSC), offers users convenient access to technical data directly through KohlerPower.com. Users can retrieve product guide specifications, building information modeling (BIM) files, product drawings, and genset performance information through the free PSC software, enhancing their experience and streamlining the process of accessing essential information , In October 2022, LCL, a Belgian data center company, used hydrotreated vegetable oil (HVO) to replace diesel in its backup generators. The company announced that LCL Brussels-West in Aalst, which invested in six new 2.25 MVA generators, would be the first site to adopt this biodiesel. The facility comprises eight backup generators, including two older 1MW units and six new HVO-powered generators. This transition from diesel to renewable fuel sources demonstrates LCL's commitment to sustainability. It paves the way for DC generator manufacturers to innovate and develop advanced products in line with renewable energy requirements , In November 2022, Kohler Power Systems inaugurated the production expansion at its existing generator manufacturing facility in Wisconsin, U.S. This expansion aims to enhance Kohler's manufacturing capabilities in North America, specifically to cater to critical strategic industries such as data centers. By increasing its production capacity, Kohler Power Systems is well-positioned to meet the growing demands of these industries .

Snapshot img

Generator Market In Data Centers Size 2025-2029

The generator market in data centers size is valued to increase USD 4.63 billion, at a CAGR of 8.6% from 2024 to 2029. Increasing investments in data centers will drive the generator market in data centers.

Major Market Trends & Insights

Europe dominated the market and accounted for a 33% growth during the forecast period.
By Type - Diesel segment was valued at USD 4.88 billion in 2023
By Capacity - Less than 1MW segment accounted for the largest market revenue share in 2023

Market Size & Forecast

Market Opportunities: USD 143.59 million
Market Future Opportunities: USD 4634.70 million
CAGR : 8.6%
Europe: Largest market in 2023

Market Summary

The market is a dynamic and evolving sector, driven by the increasing demand for uninterrupted power supply and the growing reliance on data centers for digital transformation. Core technologies, such as fuel cells and lithium-ion batteries, are gaining traction due to their efficiency and environmental benefits. Meanwhile, applications like backup power and prime power continue to dominate the market. Service types, including generator rental and maintenance, are essential for ensuring the reliability and longevity of these systems. Regulations, such as emissions standards, are shaping the market landscape, with an increasing focus on reducing carbon emissions. Looking forward, the next five years are expected to bring significant growth, as investments in data centers continue to surge. For instance, according to recent reports, the data center market is projected to reach a compound annual growth rate of 12% by 2026. Furthermore, the adoption of next-generation power monitoring and management software is on the rise, enabling more efficient energy management and reducing the overall carbon footprint of data centers. Related markets such as the renewable energy sector and energy storage systems are also experiencing significant growth, offering opportunities for collaboration and innovation in the market.

What will be the Size of the Generator Market In Data Centers during the forecast period?

Get Key Insights on Market Forecast (PDF) Request Free Sample

How is the Generator In Data Centers Market Segmented and what are the key trends of market segmentation?

The generator in data centers industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. TypeDieselGasCapacityLess than 1MW1MW-2MWMore than 2MWVariantTier IIITier IVTier I and IIGeographyNorth AmericaUSCanadaEuropeFranceGermanyItalyThe NetherlandsUKAPACChinaIndiaJapanRest of World (ROW)

By Type Insights

The diesel segment is estimated to witness significant growth during the forecast period.

In the dynamic and evolving data center market, diesel generators play a pivotal role in ensuring high-performance and reliability during power fluctuations or transient scenarios. With a wide range of capacity offerings, these generators are the preferred choice for large-scale data center infrastructure due to their cost-effectiveness and safety features. The diesel generator system encompasses various components, such as the diesel engine, generating unit, fuel storage supply, and electrical switchgear. According to recent studies, approximately 65% of data centers rely on diesel generators for backup power. Furthermore, the market for diesel generators in data centers is projected to expand by 25% in the next five years, as more businesses invest in critical power systems to maintain high availability and minimize downtime. Power quality monitoring, generator commissioning, and load balancing are essential aspects of generator maintenance schedules. Fuel cell technology and energy storage solutions are increasingly integrated into these systems to enhance efficiency and reduce noise levels. Power factor correction and generator control systems ensure optimal performance and minimize environmental impact. Environmental impact assessment, power usage effectiveness, and diesel generator efficiency are crucial metrics for data center infrastructure. Predictive maintenance models and fault-tolerant systems enable proactive maintenance and reduce downtime. Generator automation, backup power redundancy, and critical power systems are integral components of high availability systems. The generator installation standards mandate strict adherence to safety regulations and emissions guidelines. Generator exhaust emissions are continuously monitored and reduced through advanced technologies. Remote generator monitoring and paralleling systems enable seamless integration into the power distribution units. In summary, diesel generators are a vital component of data center infrastructure, pr

The global data center generator market by investment was valued at USD 6 billion in 2023 and is expected to reach USD 10.83 billion by 2029, growing at a CAGR of 10.36%.

The Weather Generator Gridded Data consists of two products:

[1] statistically perturbed gridded 100-year historic daily weather data including precipitation [in mm], and detrended maximum and minimum temperature in degrees Celsius, and

[2] stochastically generated and statistically perturbed gridded 1000-year daily weather data including precipitation [in mm], maximum temperature [in degrees Celsius], and minimum temperature in degrees Celsius.

The base climate of this dataset is a combination of historically observed gridded data including Livneh Unsplit 1915-2018 (Pierce et. al. 2021), Livneh 1915-2015 (Livneh et. al. 2013) and PRISM 2016-2018 (PRISM Climate Group, 2014). Daily precipitation is from Livneh Unsplit 1915-2018, daily temperature is from Livneh 2013 spanning 1915-2015 and was extended to 2018 with daily 4km PRISM that was rescaled to the Livneh grid resolution (1/16 deg). The Livneh temperature was bias corrected by month to the corresponding monthly PRISM climate over the same period. Baseline temperature was then detrended by month over the entire time series based on the average monthly temperature from 1991-2020. Statistical perturbations and stochastic generation of the time series were performed by the Weather Generator (Najibi et al. 2024a and Najibi et al. 2024b).

The repository consists of 30 climate perturbation scenarios that range from -25 to +25 % change in mean precipitation, and from 0 to +5 degrees Celsius change in mean temperature. Changes in thermodynamics represent scaling of precipitation during extreme events by a scaling factor per degree Celsius increase in mean temperature and consists primarily of 7%/degree-Celsius with 14%/degree-Celsius as sensitivity perturbations. Further insight for thermodynamic scaling can be found in full report linked below or in Najibi et al. 2024a and Najibi et al. 2024b.

The data presented here was created by the Weather Generator which was developed by Dr. Scott Steinschneider and Dr. Nasser Najibi (Cornell University). If a separate weather generator product is desired apart from this gridded climate dataset, the weather generator code can be adopted to suit the specific needs of the user. The weather generator code and supporting information can be found here: https://github.com/nassernajibi/WGEN-v2.0/tree/main. The full report for the model and performance can be found here: https://water.ca.gov/-/media/DWR-Website/Web-Pages/Programs/All-Programs/Climate-Change-Program/Resources-for-Water-Managers/Files/WGENCalifornia_Final_Report_final_20230808.pdf

This software tool generates simulated radar signals and creates RF datasets. The datasets can be used to develop and test detection algorithms by utilizing machine learning/deep learning techniques for the 3.5 GHz Citizens Broadband Radio Service (CBRS) or similar bands. In these bands, the primary users of the band are federal incumbent radar systems. The software tool generates radar waveforms and randomizes the radar waveform parameters. The pulse modulation types for the radar signals and their parameters are selected based on NTIA testing procedures for ESC certification, available at http://www.its.bldrdoc.gov/publications/3184.aspx. Furthermore, the tool mixes the waveforms with interference and packages them into one RF dataset file. The tool utilizes a graphical user interface (GUI) to simplify the selection of parameters and the mixing process. A reference RF dataset was generated using this software. The RF dataset is published at https://doi.org/10.18434/M32116.

Sandbox Data Generator Market Outlook

According to our latest research, the global Sandbox Data Generator market size reached USD 1.41 billion in 2024 and is projected to grow at a robust CAGR of 11.2% from 2025 to 2033. By the end of the forecast period, the market is expected to attain a value of USD 3.71 billion by 2033. This remarkable growth is primarily driven by the increasing demand for secure, reliable, and scalable test data generation solutions across industries such as BFSI, healthcare, and IT and telecommunications, as organizations strive to enhance their data privacy and compliance capabilities in an era of heightened regulatory scrutiny and digital transformation.

A major growth factor propelling the Sandbox Data Generator market is the intensifying focus on data privacy and regulatory compliance across global enterprises. With stringent regulations such as GDPR, CCPA, and HIPAA becoming the norm, organizations are under immense pressure to ensure that non-production environments do not expose sensitive information. Sandbox data generators, which enable the creation of realistic yet anonymized or masked data sets for testing and development, are increasingly being adopted to address these compliance challenges. Furthermore, the rise of DevOps and agile methodologies has led to a surge in demand for efficient test data management, as businesses seek to accelerate software development cycles without compromising on data security. The integration of advanced data masking, subsetting, and anonymization features within sandbox data generation platforms is therefore a critical enabler for organizations aiming to achieve both rapid innovation and regulatory adherence.

Another significant driver for the Sandbox Data Generator market is the exponential growth of digital transformation initiatives across various industry verticals. As enterprises migrate to cloud-based infrastructures and adopt advanced technologies such as AI, machine learning, and big data analytics, the need for high-quality, production-like test data has never been more acute. Sandbox data generators play a pivotal role in supporting these digital initiatives by supplying synthetic yet realistic datasets that facilitate robust testing, model training, and system validation. This, in turn, helps organizations minimize the risks associated with deploying new applications or features, while reducing the time and costs associated with traditional data provisioning methods. The rise of microservices architecture and API-driven development further amplifies the necessity for dynamic, scalable, and automated test data generation solutions.

Additionally, the proliferation of data breaches and cyber threats has underscored the importance of robust data protection strategies, further fueling the adoption of sandbox data generators. Enterprises are increasingly recognizing that using real production data in test environments can expose them to significant security vulnerabilities and compliance risks. By leveraging sandbox data generators, organizations can create safe, de-identified datasets that maintain the statistical properties of real data, enabling comprehensive testing without jeopardizing sensitive information. This trend is particularly pronounced in sectors such as BFSI and healthcare, where data sensitivity and compliance requirements are paramount. As a result, vendors are investing heavily in enhancing the security, scalability, and automation capabilities of their sandbox data generation solutions to cater to the evolving needs of these high-stakes industries.

From a regional perspective, North America is anticipated to maintain its dominance in the global Sandbox Data Generator market, driven by the presence of leading technology providers, a mature regulatory landscape, and high digital adoption rates among enterprises. However, the Asia Pacific region is poised for the fastest growth, fueled by rapid digitalization, increasing investments in IT infrastructure, and growing awareness of data privacy and compliance issues. Europe also represents a significant market, supported by stringent data protection regulations and a strong focus on innovation across key industries. As organizations worldwide continue to prioritize data security and agile development, the demand for advanced sandbox data generation solutions is expected to witness sustained growth across all major regions.

Component Analysis

The Sandbox Data Genera

1666 Global export shipment records of Waveform Generator with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

• Repository author: Tommaso Zanotti* email: tommaso.zanotti@unimore.it or francescomaria.puglisi@unimore.it * Version v1.0

This repository includes MATLAB files and datasets related to the IEEE IIRW 2023 conference proceeding:T. Zanotti et al., "Reliability Analysis of Random Telegraph Noisebased True Random Number Generators," 2023 IEEE International Integrated Reliability Workshop (IIRW), South Lake Tahoe, CA, USA, 2023, pp. 1-6, doi: 10.1109/IIRW59383.2023.10477697

The repository includes:

The data of the bitmaps reported in Fig. 4, i.e., the results of the simulation of the ideal RTN-based TRNG circuit for different reseeding strategies. To load and plot the data use the "plot_bitmaps.mat" file.

The result of the circuit simulations considering the EvolvingRTN from the HfO2 device shown in Fig. 7, for two Rgain values. Specifically, the data is contained in the following csv files:

"Sim_TRNG_Circuit_HfO2_3_20s_Vth_210m_no_Noise_Ibias_11n.csv" (lower Rgain)

"Sim_TRNG_Circuit_HfO2_3_20s_Vth_210m_no_Noise_Ibias_4_8n.csv" (higher Rgain)

The result of the circuit simulations considering the temporary RTN from the SiO2 device shown in Fig. 8. Specifically, the data is contained in the following csv files:

"Sim_TRNG_Circuit_SiO2_1c_300s_Vth_180m_Noise_Ibias_1.5n.csv" (ref. Rgain)

"Sim_TRNG_Circuit_SiO2_1c_100s_200s_Vth_180m_Noise_Ibias_1.575n.csv" (lower Rgain)

"Sim_TRNG_Circuit_SiO2_1c_100s_200s_Vth_180m_Noise_Ibias_1.425n.csv" (higher Rgain)

PFam Domains and biological process GO categories for the four rhizobia strains. Predicted proteins related to multiple GO biological process categories are joined together with the pipe character. (XLSX 639Â kb)

133326 Global import shipment records of Diesel Generator with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

When run, the GFCM creates tabular and graphical data of the hourly operating status and market outcomes for the generators that make up the electric generating fleet.

Dataset Generator

## Overview

Dataset Generator is a dataset for object detection tasks - it contains FTC Element annotations for 1,512 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).