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45 results found

Dataset for paper Y. Ma, S. Mosleh and J. Coder, "Analyzing 5G NR-U and WiGig Coexistence with Multiple-Beam Directional LBT," 2022 IEEE 19th Annual Consumer Communications & Networking Conference (CCNC), 2022, pp. 272-275, doi: 10.1109/CCNC49033.2022.9700690

Data provided by  National Institute of Standards and Technology

This project produces synthetic datasets of spectrum sharing simulation results (I/Q data, metadata, and KPIs).

Tags: wireless coexistence,Spectrum sharing,machine learning,wireless communications and networks,4G,5G,6G,Wi-Fi,

Modified: 2024-02-22

Views: 0

QFlow 2.0: Quantum dot data for machine learning

Data provided by  National Institute of Standards and Technology

Using a modified Thomas-Fermi approximation, we model a reference semiconductor system comprising a quasi-1D nanowire with a series of five depletion gates whose voltages determine the number of quantum dots (QDs), the charges on each of the QDs, as well as the conductance through the wire. The original dataset, QFlow lite, consists of 1 001 idealized simulated measurements with gate configurations sampling over different realizations of the same type of device.

Tags: machine learning,quantum dots,simulated data,

Modified: 2024-02-22

Views: 0

Trojan Detection Software Challenge - nlp-summary-jan2022-train

Data provided by  National Institute of Standards and Technology

Round 9 Train DatasetThis is the training data used to construct and evaluate trojan detection software solutions. This data, generated at NIST, consists of natural language processing (NLP) AIs trained to perform one of three tasks, sentiment classification, named entity recognition, or extractive question answering on English text. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers.

Tags: Trojan Detection,Artificial Intelligence,ai,machine learning,Adversarial Machine Learning,

Modified: 2024-02-22

Views: 0

Data for Modeling OFDM Communication Signals with Generative Adversarial Networks

Data provided by  National Institute of Standards and Technology

This repository contains results for experiments on generative modeling of synthetic Orthogonal-Frequency Division Multiplexing (OFDM) communication signals. (This record supersedes Software and Data for Modeling OFDM Communication Signals with Generative Adversarial Networks, formerly at https://doi.org/10.18434/mds2-2428)

Tags: generative adversarial network,machine learning,wireless communications,

Modified: 2024-02-22

Views: 0

Bulk Data Storage System (BDSS) API (Version 1.1.0)

Data provided by  United States Patent and Trademark Office

The Bulk Data Storage System (BDSS) API allows the public to discover, search by date, and download patent and trademark data within BDSS in bulk form.

Tags: patent,trademark,uspto,bulk,bdss,api,

Modified: 2024-02-22

Views: 0

Bulk Search and Download (BSD) API (Version 1.0.0)

Data provided by  United States Patent and Trademark Office

The Bulk Search and Download API allows searching published patent applications (pre-grant publications, pgpubs) and issued patents (patent grants) across various fields from 2001 to present, and to request a custom zip package for the given patent application or patent ids. Download up to 100 document numbers at a time. Wait time can vary based on the number of requests being processed.

Tags: uspto,patent,patent grant,published patent application,pre-grant,pgpub,api,

Modified: 2024-02-22

Views: 0

Cancer Moonshot Patent Data Set API (Version 1.0.1)

Data provided by  United States Patent and Trademark Office

The Cancer Moonshot Patent Data Set API allows the public to discover and search USPTO Cancer Moonshot Patent Data.

Tags: api,uspto,cancer,moonshot,patent,application,

Modified: 2024-02-22

Views: 0

Enriched Citation API (Version 1)

Data provided by  United States Patent and Trademark Office

The Enriched Citation API provides the Intellectual Property 5 (IP5 - EPO, JPO, KIPO, CNIPA, and USPTO) and the Public with greater insight into the patent evaluation process. It allows users to quickly view information about which references, or prior art, were cited in specific patent application Office Actions, including: bibliographic information of the reference, the claims that the prior art was cited against, and the relevant sections that the examiner relied upon.

Tags: uspto,ip5,enriched,citation,prior art,office action,claims,machine learning,ai,api,statutes,references,

Modified: 2024-02-22

Views: 0

Enriched Citation API (Version 2)

Data provided by  United States Patent and Trademark Office

The Enriched Citation API provides the Intellectual Property 5 (IP5 - EPO, JPO, KIPO, CNIPA, and USPTO) and the Public with greater insight into the patent evaluation process. It allows users to quickly view information about which references, or prior art, were cited in specific patent application Office Actions, including: bibliographic information of the reference, the claims that the prior art was cited against, and the relevant sections that the examiner relied upon.

Tags: uspto,ip5,enriched,citation,prior art,office action,claims,machine learning,ai,api,statutes,references,

Modified: 2024-02-22

Views: 0

Office Action Citations API (beta)

Data provided by  United States Patent and Trademark Office

Contains detailed information derived from the Office actions issued by patent examiners to applicants during the patent examination process. The Office Action is a written notification to the applicant of the examiners decision on patentability. It generally discloses the reasons for any rejections, objections, or requirements and includes relevant information or references that the applicant may find useful for responding to the examiner and deciding whether to continue prosecuting the application.

Tags: uspto,patent,patent application,office actions,api,citations,

Modified: 2024-02-22

Views: 0