Signal Processing
This paper presents a dataset of brain Electroencephalogram (EEG) signals created when Malayalam vowels and consonants are spoken. The dataset was created by capturing EEG signals utilizing the OpenBCI Cyton device while a volunteer spoke Malayalam vowels and consonants. It includes recordings obtained from both sub-vocal and vocal. The creation of this dataset aims to support individuals who speak Malayalam and suffer from neurodegenerative diseases.
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2556 Views
This is the dataset of received signal strength indicator (RSSI) from Wi-Fi routers in different environments.
RSSI was collected by a person holding an Android tablet within one hour
in S301, Graduate School of Informatic Science (Main Building), Kobe University, Japan.
We collected the RSSI between the terminal and Wi-Fi routers
per second 30 times at 20 reference points with doors open.
Then, we collected RSSI data again with doors closed.
The distance between reference points is greater than or equal to 2 m.
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156 Views
This study presents a method for detecting arc faults by combining load identification and MLP-SVM. The method addresses the issue of interfering loads on arc fault detection and the lack of significant arc fault features in some loads. Initially, the eigenvalues of the line currents for single and mixed loads are extracted in the time domain, both during arc fault and normal operation. Subsequently, load identification is performed using a complex matrix calculation method. After identification, an eigenmatrix and history matrix are created for each load.
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283 Views
We introduce an online-offline Iraquian hand-drawing dataset for early Parkinson’s disease detection, exclusively collected using smartphones, thus eliminating the need for specialized equipment like digitizing tablets and pens. Our dataset comprises data from 30 healthy individuals (17 men, 13 women) with an average age of 56 years (SD = 6.12) and 30 PD patients (23 men, 7 women) with an average age of 60 years (SD = 4.91), gathered at Marjan Hospital in Hilla, Babil Governorate, Iraq.
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452 Views
The timely and accurate diagnosis of severe faults in the high-speed train air compressor is crucial due to the potential for significant safety issues. In response to this problem, this paper proposes a high-speed train air compressor fault diagnosis method based on an improved complete ensemble empirical mode decomposition adaptive noise (ICEEMDAN) and t-Distributed Stochastic Neighbor Embedding (t-SNE) algorithm.
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129 Views
This dataset utilizes Asus RT-AC86U routers and nexmon tools to collect Channel State Information (CSI) data in a 7 by 5 meters meeting room furnished with typical furniture including a conference table, several chairs, and a locker. The data, stored in .pcap format, is accompanied by processing code on GitHub, enabling parsing into CSI matrix data stored in .npy format. Each CSI matrix contains amplitude and processed phase values for four channels, encompassing data from both external and internal antennas within the room.
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361 Views
ABSTRACT Analysis of stock prices has been widely studied because of the strong demand among private investors and financial institutions. However, it is difficult to accurately capture the factors that cause fluctuations in stock prices, as they are affected by a variety of factors. Therefore, we used non-harmonic analysis, a frequency technique with at least to more accurately than conventional analysis methods, to visualize the periodicity of the Nasdaq Composite Index stock price from January 4, 2010 to September 8, 2023.
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79 Views
Visual saliency prediction has been extensively studied in the context of standard dynamic range (SDR) display. Recently, high dynamic range (HDR) display has become popular, since HDR videos can provide the viewers more realistic visual experience than SDR ones. However, current studies on visual saliency of HDR videos, also called HDR saliency, are very few. Therefore, we establish an SDR-HDR Video pair Saliency Dataset (SDR-HDR-VSD) for saliency prediction on both SDR and HDR videos.
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331 Views
This dataset contains results of the 60 GHz indoor sensing measurement campaign using a bistatic OFDM radar based on 5G-specified positioning reference signals (PRSs). The data can be used for testing end-to-end indoor millimeter-wave radio positioning as well as simultaneous localization and mapping (SLAM) algorithms, including channel parameter estimation. Beamformed PRS with dense angular sampling in transmission and reception allows efficient capture of line-of-sight (LoS) as well as multipath components.
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1727 Views
QiandaoEar22 is a high-quality noise dataset designed for identifying specific ships among multiple underwater acoustic targets using ship-radiated noise. This dataset includes 9 hours and 28 minutes of real-world ship-radiated noise data and 21 hours and 58 minutes of background noise data.
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625 Views