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This video demonstrates the real-time data acquisition and noise reduction capabilities of a CMOS capacitive sensor array (CSA) implemented on an FPGA. The system captures the evaporation process of a deionized water droplet placed on the sensor array, using multiple sampling (MS) and pixel-wise accumulation (PWA) techniques to enhance signal quality and reduce random noise. The system efficiently processes and transmits the data, showcasing the gradual reduction in the droplet's size as it evaporates.
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101 Views
The pulse parameter-editable nanosecond pulse power supply (NPPS) based on all-solid-state Marx power topology is one of the critical excitation sources for studying the characteristics of atmospheric pressure low-temperature plasma (APLTP), its efficient applications, and the regulation of discharge characteristic. We have developed a 20kV/400W nanosecond pulse power supply with editable pulse edge parameters to validate the effectiveness of the diode-capacitor network (DCN) method.
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59 Views
Supplementary video for the article "A Programmable CMOS DEP Chip for Cell Manipulation"
This video demonstrates the use of a CMOS DEP chip for particle manipulation, including particle patterning, concentration control, and single particle manipulation, all performed on the same chip and sample.
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402 Views
This dataset is supplementary materials for "Study and Implementation of VLC with Angular Diversity Receiver for IoT Systems".
1. ADR Demonstraion.mp4
This describes the prototype of the ADR for IoT systems. It starts from the introduction of the prototype to the demonstration.
Real-time sensor data transmission is demonstrated. The monitor shows the light sensor value at the access point and the user node.
2. Mobile suitability Demonstration.mp4
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601 Views
This dataset encapsulates a comprehensive collection of eye movement recordings captured during sleep, exceeding 100 distinct episodes. The recordings are primarily categorized into Rapid Eye Movement (REM), Slow Eye Movement (SEM), and non-movement phases, providing a rich resource for sleep research. Each video is meticulously recorded in high-definition .mp4 format, ensuring clarity and precision in capturing subtle ocular dynamics.
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7 Views
Automated and autonomous industrial inspection is a longstanding research field, driven by the necessity to enhance safety and efficiency within industrial settings. In addressing this need, we introduce an autonomously navigating robotic system designed for comprehensive plant inspection. This innovative system comprises a robotic platform equipped with a diverse array of sensors integrated to facilitate the detection of various process and infrastructure parameters.
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291 Views
Egocentric video and Inertial sensor data Kitchen activity dataset is the first V-S-S interaction-focused dataset for the ego-HAR task.
It consists of sequences of everyday kitchen activities involving rich interactions among the subject's body, object, and environment.
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38 Views
Our video action dataset is generated using a 3D simulation program developed in Unity. Each data sample consists of a video capturing a human performing various actions. Our initial set of actions comprises a total of 10 different yoga poses: camel, chair, child's pose, lord of the dance, lotus, thunderbolt, triangle, upward dog, warrior II, and warrior III. Within each of these 10 yoga poses, there are four variations, some exhibiting more pronounced differences than others. This results in a total of 40 action types within our dataset.
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113 Views
This dataset features a wide range of synthetic American Sign Language (ASL) digits, spanning numbers 0 through 9. These ASL sign representations were meticulously crafted using Unity software, resulting in dynamic 3-D scenes set against diverse backgrounds. To enhance the dataset's comprehensiveness, it includes contributions from three distinct subjects, adding a rich variety of ASL digit gestures. This diversity makes it a valuable resource for researchers interested in ASL digit recognition and gesture analysis.
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393 Views
Gowers' Sign is a visual symptom exhibited by many neuromuscular dystrophies, including Becker muscular dystrophy, congenital muscular dystrophy, congenital myopathy, and Duchenne muscular dystrophy, which is the most aggressive, with a life expectancy of 20 to 30 years. Additionally, there is a 2.5-year gap between the onset of initial symptoms and a confirmed diagnosis. Early detection allows for the treatment of the disease, leading to a better quality of life. To the best of our knowledge, a non-invasive computer vision system for detecting Gowers' Sign has not yet been proposed.
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20 Views