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rabindra.tharu.np@gmail.com
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Enhanced Hand Gesture Recognition with Surface Electromyogram and Machine Learning
This study delves into decoding hand gestures using surface electromyography (EMG) signals collected via a precision Myo-armband sensor, leveraging machine learning algorithms. The research entails rigorous data preprocessing to extract features and labels from raw EMG data. Following partitioning into training and testing sets, four traditional machine learning models are scrutinized for their efficacy in…
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rabindra.tharu.np@gmail.com
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Improving Fire Detection Accuracy through Enhanced Convolutional Neural Networks and Contour Techniques
In this study, a novel method combining contour analysis with deep CNN is applied for fire detection. The method was made for fire detection using two main algorithms: one which detects the color properties of the fires, and another which analyzes the shape through contour detection. To overcome the disadvantages of previous methods, we generate…
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rabindra.tharu.np@gmail.com
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Quantitative Prediction and Analysis of Rattle Index Using DNN on Sound Quality of Synthetic Sources with Gaussian Noise
This study researched the prediction of the BSR noise evaluation quantitative index, Loudness N10, for sound sources with noise using statistics and machine learning. A total of 1170 data points was obtained from 130 automotive seats measured at 9-point positions, with Gaussian noise integrated to construct synthetic sound data. Ten physical quantities related to sound…
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rabindra.tharu.np@gmail.com
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Large-Area Film Thickness Identification of Transparent Glass by Hyperspectral Imaging
This study introduces a novel method for detecting and measuring transparent glass sheets using hyperspectral imaging (HSI). The main goal of this study is to create a conversion technique that can accurately display spectral information from collected images, particularly in the visible light spectrum (VIS) and near-infrared (NIR) areas. This technique enables the capture of…
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rabindra.tharu.np@gmail.com
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A Novel Real-Time Detection and Classification Method for ECG Signal Images Based on Deep Learning
In this paper, a novel deep learning method Mamba-RAYOLO is presented, which can improve detection and classification in the processing and analysis of ECG images in real time by integrating three advanced modules. The feature extraction module in our work with a multi-branch structure during training can capture a wide range of features to ensure…
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rabindra.tharu.np@gmail.com
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A Reflected-Light-Mode Multiwavelength Interferometer for Measurement of Step Height Standards
The article is dedicated to measuring the thickness of step height standards using the author’s version of the variable wavelength interferometer (VAWI) in the reflected-light mode, where the interference pattern is created by the combination of two Wollaston prisms. The element of novelty consists in replacing the traditional search for the coincidence of fringes in…
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rabindra.tharu.np@gmail.com
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Deciphering Optimal Radar Ensemble for Advancing Sleep Posture Prediction through Multiview Convolutional Neural Network (MVCNN) Approach Using Spatial Radio Echo Map (SREM)
Assessing sleep posture, a critical component in sleep tests, is crucial for understanding an individual’s sleep quality and identifying potential sleep disorders. However, monitoring sleep posture has traditionally posed significant challenges due to factors such as low light conditions and obstructions like blankets. The use of radar technolsogy could be a potential solution. The objective…
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rabindra.tharu.np@gmail.com
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Magnetic Stirring Device for Limiting the Sedimentation of Cells inside Microfluidic Devices
In experiments considering cell handling in microchannels, cell sedimentation in the storage container is a key problem because it affects the reproducibility of the experiments. Here, a simple and low-cost cell mixing device (CMD) is presented; the device is designed to prevent the sedimentation of cells in a syringe during their injection into a microfluidic…
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rabindra.tharu.np@gmail.com
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Graph Attention Informer for Long-Term Traffic Flow Prediction under the Impact of Sports Events
Traffic flow prediction is one of the challenges in the development of an Intelligent Transportation System (ITS). Accurate traffic flow prediction helps to alleviate urban traffic congestion and improve urban traffic efficiency, which is crucial for promoting the synergistic development of smart transportation and smart cities. With the development of deep learning, many deep neural…
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rabindra.tharu.np@gmail.com
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Integrating High-Performance Flexible Wires with Strain Sensors for Wearable Human Motion Detection
Flexible electronics have revolutionized the field by overcoming the rigid limitations of traditional devices, offering superior flexibility and adaptability. Conductive ink performance is crucial, directly impacting the stability of flexible electronics. While metal filler-based inks exhibit excellent conductivity, they often lack mechanical stability. To address this challenge, we present a novel conductive ink utilizing a…
