Signal Processing
The data was collected by outfitting one of the players with the experimental balloon, which incorporated the embedded circuit and sensors. The sensors positioned at the top-right to the player within the bubble balloon, where a player stand inside. The sensors' data were collected at specific sampling frequencies (Accelerometer: 1000Hz, Gyroscope: 1000Hz, and Pressure: 40Hz). The experiment was conducted involving five different players. This approach allowed for the inclusion of diverse data samples, taking into account variations in player metrics, movements, and gameplay dynamics.
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187 Views
Developing mind-controlled prosthetics that seamlessly integrate with the human nervous system is a significant challenge in the field of bioengineering. This project investigates the use of labelled brainwave patterns to control a bionic arm equipped with a sense of touch. The core objective is to establish a communication channel between the brain and the artificial limb, enabling intuitive and natural control while incorporating sensory feedback.
The project involves:
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601 Views
One of the Dravidian language spoken majorly by 60 million people in and around Karnataka state of India is known as Kannada. It is one among 22 scheduled languages of India. Kannada langauge is written in Kannada scriptwhich has its traces back from kadamba script (325-550 AD). There are many languages which were used centuries back and aren’t being used currently whereas Kannada is one such language which is used even today for writing official documents and are being taught at schools which means it is going to be for many years.
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179 Views
Data over voice channel. The carrier is chirp. The dataset has been dealed. Except for the last column number, all other contents are the characteristic values of the signal. you can use Deep learning model to classify the dataset. There are 8 labels in dataset, and this dataset is suit for data classification.
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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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2560 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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159 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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338 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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484 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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131 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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391 Views