Sensors

This dataset presents a comprehensive collection of measurements from a Thermoelectric Generator (TEG) energy harvesting prototype, equipped with nine PT100 temperature sensors and detailed recordings of voltage and current outputs. Collected over a 12-month period starting in October 2022, the data provide insights into the performance of the TEG under varying environmental conditions.

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<p>Abstract – This paper shows an overview of the recent developments in the field of Electric Vehicles (EVs), the integration of EVs and Smart Cars, the battery technology and the power electronics in EVs.&nbsp;Over the past decades, the automotive industry has faced growing challenges, including environmental concerns and the finite amount of fuel resources that mainly includes petrol and diesel. In response to these challenges, Electric Vehicles (EVs) have emerged as sustainable alternative, promising reduced emissions and increased energy efficiency.

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1124 Views

Self-powered photodetectors which can operate without external power sources hold immense promise in future photodetection systems owing to their zero-power features. To achieve high-performance self-powered optoelectronic devices, efficient separation of electron-hole pairs to generate sufficiently high photocurrents is critical, especially in the case of 2D and 3D hybrid devices.

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31 Views

Due to the rapid mobility and superior obstacle surmounting capabilities, quadruped robots are increasingly employed in industrial inspections. Quadruped robots usually utilize laser simultaneous localization and mapping (SLAM) for autonomous navigation. However, SLAM is susceptible to inaccuracies under the rapid movement and rotation of quadruped robots.

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41 Views

Response data for ammonia and ethanol gases was collected using the electronic nose system.To meet the need for accurate, real-time, and stable monitoring of ammonia concentration in the breeding environment in livestock and poultry breeding areas, the electronic nose detection system solved the problems of poor real-time performance and low detection accuracy. An active pumping ammonia detection artificial olfactory system based on a bionic chamber is proposed. The sensing unit of the system consists of a bionic chamber and eight sensors.

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100 Views

Recently, a novel method was proposed to estimate the distance between a couple of wireless transceivers and a reflecting obstacle by analyzing the frequency dependence of the RSS. Although the resolution of this method is rather coarse for typical 2.4 GHz systems, a traffic monitoring system based on that novel approach has been successfully evaluated

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117 Views

We demonstrate the fabrication and optimization of waveguide Bragg gratings on single-crystal sapphire substrates using femtosecond laser direct writing. The gratings are fabricated using modulated bursts and are embedded inside single-mode depressed cladding waveguides. Through design optimization, and fabrication parameter tuning, a depressed cladding waveguide with a loss of ~0.8 dB/cm and a Bragg grating with a reflectivity of higher than 90% in the telecommunications wavelength band are demonstrated.

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This project is used to examine the actual resolution of a cross talk based TDC. In which, the ZYNQ core is used to provide a reference clock after device start-up. In the meantime, the IDELAY instance inside the LOOP MUX can be adjusted at different tap counts to find out the TDC's resolution. Where, the IDELAY tap delay is determined by comparing it with the reference clock. To be more specific, a crystal clock pulse is brought into the TDC loop by the MMCM. 

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435 Views

The data is uploaded according to the requirements of IEEE DataPort. The file is named 'data of robot control experiments.zip', and it contains two folders. The folder named 'Data of Section IV-B' is the experimental data in Section IV-B, and the folder named 'Data of Appendix A' is the experimental data in Appendix A.

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57 Views

The accurate classification of landfill waste diversion plays a critical role in efficient waste management practices. Traditional approaches, such as visual inspection, weighing and volume measurement, and manual sorting, have been widely used but suffer from subjectivity, scalability, and labour requirements. In contrast, machine learning approaches, particularly Convolutional Neural Networks (CNN), have emerged as powerful deep learning models for waste detection and classification.

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662 Views

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