IEEE DataPort’s Spring 2020 Dataset Upload Competition Entries
All contest entries will be evaluated and must meet all contest rules in order to be eligible for prizes.
The data collection includes posts from social media networks popular among Russian-speaking people. The information was gathered using pre-defined keywords ("war," "special military operation," and so on) and is mainly relevant to Ukraine's continuing conflict with Russia. Following a thorough assessment and analysis of the data, propaganda and false news were detected. The information gathered has been anonymized. Feature engineering and text preparation can extract new insights and information from this data source.
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Light wfeight Function create stem3 model with an complex route as in link figure data set
Link:
https://www.mathworks.com/matlabcentral/communitycontests/contests/5/ent...
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Ground reaction forces (GRFs) and center of pressure trajectories (CoPs) are required for a comprehensive biomechanical analysis. They are also important outcome measures in sports sciences or clinical areas. GRFs and CoPs are usually measured by force plate, which is rarely equipped on staircases in laboratories. We present a one-dimensional convolutional neural network for estimating GRFs and CoPs during stair ascent and descent using multi-level of kinematics as input.
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Models of the electrical machines are used in the process of development control system and verification of them. Nowadays multiphase machines are attracting attention due to their reliability; however, standard MATLAB libraries are limited by 5-phase and 3-phase models. This paper considers a universal model of 3-, 5-, 6-, 7-, 9-phase permanent magnet synchronous motor. The model was developed using standard blocks of MATALB Simulink and can be used as a component of SimPowerSystem. Simulation results are provided as well as a link to the library for use free of charge.
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The dataset includes processed sequences of optical time domain reflectometry (OTDR) traces incorporating different types of fiber faults namely fiber cut, fiber eavesdropping (fiber tapping), dirty connector and bad splice. The dataset can be used for developping ML-based approaches for optical fiber fault detection, localization, idenification, and characterization.
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A synthetic data for low power (P ≤10 mW) InGaAsP MQW-DFB lasers operating at a wavelength (λ) ranging from 1.53 to 1.57 µm at a case temperature laying between -40 ℃ to 85 ℃ with side mode suppression ratio of more than 35 dB is generated and can be used for laser lifetime prediction using machine learning based approaches.
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The concentration of sea ice is essential for determining crucial climate factors. Together with sea ice thickness, it is possible to determine significant air-sea fluxes and atmospheric heat transfer. In this study, the SARAL/AltiKa Sea Ice Algorithm is used to determine the monthly sea ice concentration (SIC) in the Arctic (SSIA). For the period from April 2013 to December 2020, data from the dual-frequency microwave radiometer (23.8 GHz and 37 GHz) on the SARAL/AltiKa satellite are used to compute SIC.
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<p>This multilingual Twitter dataset spans over 2 years from October 2019 to the end of 2021, including 3 months before the outbreak of the COVID-19 pandemic.</p>
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There are three videos demonstrating the steady operation, dynamics, and low voltage ridge through of the IEEE papers: A New Low Switching Frequency Control of Regenerative CHB Drive With Low-Voltage Ride-Through Capability AND Control of Regenerative CHB Motor Drives at Fundamental Switching Frequency
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This data set includes raw data from the RFID reader and the processed attributes.
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This dataset analyzes a survey delivered in 2019 to 259 experts in engineering education that asked them to forecast which information and communication technologies were most likely to impact the practice of engineering education based on the expert's discipline (electrical, electronics, mechanical, telecommunications engineering, computer science, etc.) and region.
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<p>cnki dataset</p>
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Fast traslate Icon translate Fast traslate Icon translate Because this instructional material will be used for teaching in some way, Youtube will be used because it offers authentic and can allow learners to review and rebuild concepts for national sustainable education with a humanistic national standard. Students will be able to understand further educational programs, essential thinking systems, and standards aspects by watching the video transcriptions in the table below.
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Nowadays road accident in Bangladesh is a buzzword due to its lack of carefulness of the driver of the vehicle where some parameter exists. The traffic safety of the roadway is an essential concern not only for transportation governing agencies but also for citizens of our country. For safe driving suggestions, the important thing is to find the variables that are tensed to relate to the fatal accidents that are occurring often. In this dataset, we provides a detailed account of the road accidents that covers the year of 2016 to 2019.
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Nowadays road accident in Bangladesh is a buzzword due to its lack of carefulness of the driver of the vehicle where some parameter exists. The traffic safety of the roadway is an essential concern not only for transportation governing agencies but also for citizens of our country. For safe driving suggestions, the important thing is to find the variables that are tensed to relate to the fatal accidents that are occurring often. In this dataset, we provides a detailed account of the road accidents that covers the year of 2016 to 2019.
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Here we provide the dataset containing the power measurements obtained with our RIS prototype, which were carried out in the anechoic chamber of TU Darmstadt.
The use of data here contained is intended only for research purposes.
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Rainfall Runoff _ Mahaweli River
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Synaptic vesicle glycoprotein 2A (SV2A) is the most widely distributed transmembrane glycoprotein present on secretory vesicles in the pre-synaptic terminal of neurons throughout the central nervous system (Bajjalieh et al., 1994). SV2A can be used as a marker to visualize pre-synaptic density distribution in vivo using positron emission tomography (PET) imaging thanks to the SV2A radioligands available, including [11C]UCB-J (Nabulsi et al., 2016). Given the brain-wide distribution of SV2A, regional analysis of SV2A PET data may be limiting the amount of information that can be obtained.
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The integration of communication and artificial intelligence has become a development trend, one of the applications is semantic communication, but the current research lacks the support of comprehensive datasets. To solve this problem, we built a new image and video dataset, named SCO dataset, for the researches on semantic communication and computing. First, we introduce the peculiarities of the dataset, which contains 5100 images and 138 video clips. Secondly, we we give the data generation and processing methods of the dataset, including images and videos.
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Wireless Intelligence Channel (WIC) is a realistic channel data set, which is designed for deep learning research work in MIMO as well as other applications. The WIC data set is obtained directly through commercial BSs and a device capable of data acquisition that is similar to a commercial terminal. The scene selection and parameter configuration involved in the experiment are based on the characteristics of realistic scenarios and the existing configurations in commercial BSs, without assumptions and restrictions on the ideal experimental conditions.
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This dataset contains solar radiation data at the high resolution of 1 second for consecutive 72 hours under dynamic weather conditions (sunny and cloudy days). This data can be useful in various fields and researchers can use it in their research for algorithms validation and performance evaluation.
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Opening up of the CBRS band for the secondary users' transmissions poses challenges in the protection of incumbent radar users from co-channel interference. The use of Machine Learning algorithms for addressing these challenges requires representative real-world datasets.This dataset contains overlapping radar and LTE signals captures over-the-air in the shared CBRS band using an experimental testbed composed of software defined radios in RF anechoic chamber.
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This dataset is related to a method for molecular communication in fluids described on "Fluorescent nanoparticles for reliable communication among implantable medical devices," Carbon, vol. 190, pp. 262-275, Apr. 2022, by Federico Calì, Luca Fichera, Giuseppe Trusso Sfrazzetto, Giuseppe Nicotra, Gianfranco Sfuncia, Elena Bruno, Luca Lanzanò, Ignazio Barbagallo, Giovanni Li-Destri, Nunzio Tuccitto; doi: 10.1016/J.CARBON.2022.01.016.
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Synthetic Digitally Modulated Signal Datasets for Automatic Modulation Classification contain CSPB.ML.2018 and CSPB.ML.2022, two high-quality communication signal datasets with eight modulation types: BPSK, QPSK, 8-PSK, pi/4-DQPSK, MSK, 16-QAM, 64-QAM, and 256-QAM. There are 14,000 signals of each modulation type in each dataset for a total of 112,000 signals per dataset. The two datasets are useful for signal processing testing, neural network (NN) training, initial NN testing, and out-of-distribution NN testing as signal generation parameters differ between the two datasets.
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The complete description of the dataset can be found at: https://arxiv.org/abs/2305.03170
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Multipath Wireless Network
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Future wireless networks must incorporate awareness, adaptability, and intelligence as fundamental building elements in order to meet the wide range of requirements of the next-generation communication systems. Wireless sensing techniques can be used to gather awareness from the radio signals present in the surroundings. However, threats from hostile attackers, such as jamming, eavesdropping, and manipulation, are also present along with this. This paper describes in detail an RF-jamming detection test-bed and provides experimentally measured data.
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Beam management is a challenging task for millimeter wave (mmWave) and sub-terahertz communication systems, especially in scenarios with highly-mobile users. Leveraging external sensing modalities such as vision, LiDAR, radar, position, or a combination of them, to address this beam management challenge has recently attracted increasing interest from both academia and industry. This is mainly motivated by the dependency of the beam direction decision on the user location and the geometry of the surrounding environment---information that can be acquired from the sensory data.
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This data set provides complex-baseband samples of vehicle-to-vehicle communication (V2V) radios in the presence of primitive jamming signals. Up to 600 vehicles are simulated in this dataset using commerical IEEE 802.11p radios. Supporting example code found on CodeOcean can be used for developing novel physical layer based jamming detection and mitigation strategies using machine learning for ad hoc vehicular networks.
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Evolving from the well-known ray-tracing dataset DeepMIMO, the DeepVerse 6G dataset additionally provides multi-modal sensing data generated from various emulators. These emulators provide the wireless, radar, LiDAR, vision and position data. With a parametric generator, the DeepVerse dataset can be customized by the user for various communication and sensing applications.
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Biometric management and that to which uses face, is indeed a very challenging work and requires a dedicated dataset which imbibes in it variations in pose, emotion and even occlusions. The Current work aims at delivering a dataset for training and testing purposes.SJB Face dataset is one such Indian face image dataset, which can be used to recognize faces. SJB Face dataset contains face images which were collected from digital camera. The face dataset collected has certain conditions such as different pose, Expressions, face partially occluded and with a uniform attire.
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This synthetic dataset is generated using Matlab automotive driving toolbox to simulate a 77GHz FMCW millimeter-wave radar sensing in the road scenario. Especially for the Doppler ambiguity case, when the object vehicles move within or out of the unambiguous detecable velocity range. The dataset contains in total 20 recordings with the duration of 1 second each. Both time-division modulation (TDM) and binary phase modulation (BPM) data are provided. Each recording consists of complex ADC raw data and complex range-Doppler map, together with the ground-truth range and velocity.
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the data of Gaussian Process Regression Based Traffic Prediction and Rate Coordination for Service Chain Congestion Optimization
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PROTEIN STRUCTURE AND SYNTHETIC MULTI-VIEW CLUSTERING DATASETS
Multi-View Clustering (MVC) datasets used in the following paper:
Evolutionary Multi-objective Clustering Over Multiple Conflicting Data Views. Authors: Mario Garza-Fabre, Julia Handl, and Adán José-García. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION. Accepted for publication, November 2022.
This entry contains all 420 datasets used in the paper, including:
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This dataset contains support data for the manuscript "Parallel 3D Frequency Domain Electromagnetic Modeling based on Mesh Partitioning technique" submitted to TGRS.
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Blockchain technology is widely used in data asset transactions. Especially for the private data of the public, such data cannot be circulated to unauthorized receivers, it is necessary to ensure that the transaction records and data contents can be audited and traced. In this paper, based on bilinear mapping, we construct a triple receiver public key encryption scheme as a regulatable data asset transaction mechanism, and construct a blockchain data asset transaction platform, namely Digital Asset Exchange Protocol.
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Blockchain technology is widely used in data asset transactions. Especially for the private data of the public, such data cannot be circulated to unauthorized receivers, it is necessary to ensure that the transaction records and data contents can be audited and traced. In this paper, based on bilinear mapping, we construct a triple receiver public key encryption scheme as a regulatable data asset transaction mechanism, and construct a blockchain data asset transaction platform, namely Digital Asset Exchange Protocol.
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Blockchain technology is widely used in data asset transactions. Especially for the private data of the public, such data cannot be circulated to unauthorized receivers, it is necessary to ensure that the transaction records and data contents can be audited and traced. In this paper, based on bilinear mapping, we construct a triple receiver public key encryption scheme as a regulatable data asset transaction mechanism, and construct a blockchain data asset transaction platform, namely Digital Asset Exchange Protocol.
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Blockchain technology is widely used in data asset transactions. Especially for the private data of the public, such data cannot be circulated to unauthorized receivers, it is necessary to ensure that the transaction records and data contents can be audited and traced. In this paper, based on bilinear mapping, we construct a triple receiver public key encryption scheme as a regulatable data asset transaction mechanism, and construct a blockchain data asset transaction platform, namely Digital Asset Exchange Protocol.
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Blockchain technology is widely used in data asset transactions. Especially for the private data of the public, such data cannot be circulated to unauthorized receivers, it is necessary to ensure that the transaction records and data contents can be audited and traced. In this paper, based on bilinear mapping, we construct a triple receiver public key encryption scheme as a regulatable data asset transaction mechanism, and construct a blockchain data asset transaction platform, namely Digital Asset Exchange Protocol.
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Blockchain technology is widely used in data asset transactions. Especially for the private data of the public, such data cannot be circulated to unauthorized receivers, it is necessary to ensure that the transaction records and data contents can be audited and traced. In this paper, based on bilinear mapping, we construct a triple receiver public key encryption scheme as a regulatable data asset transaction mechanism, and construct a blockchain data asset transaction platform, namely Digital Asset Exchange Protocol.
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Blockchain technology is widely used in data asset transactions. Especially for the private data of the public, such data cannot be circulated to unauthorized receivers, it is necessary to ensure that the transaction records and data contents can be audited and traced. In this paper, based on bilinear mapping, we construct a triple receiver public key encryption scheme as a regulatable data asset transaction mechanism, and construct a blockchain data asset transaction platform, namely Digital Asset Exchange Protocol.
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The monitored data is obtained using the optical time domain reflectometry (OTDR) principle, which is commonly used for troubleshooting fiber optic cables or links. The data set contains raw OTDR traces that include one or two reflective events caused by the placement of one or two reflectors and/or an open physical contact (PC) at the end of the monitored optical fiber link.
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This data is the Federal Communication Commission (FCC) F(50,50) signal strength variation curves for the Very High Frequency (VHF) Channel 7-13 and the Ultra High Frequency (UHF) Channel 14-69. The signal strength for both curves is in dBuV/m for an Effective Radiated Power (ERP) per dipole of 1 kW. All data are based on a 9 m mobile antenna height measurement for 30 m to 600 m antenna heights within a transmitter-receiver separation ranging from 1.5 km to 100 km.
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