A control system to regulate the temperature of the micro hotplate in a MEMS gas sensor is presented. The controlelement, called micro hotplate, is comprised of a micro heater and a temperature sensor, both made with ...
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A control system to regulate the temperature of the micro hotplate in a MEMS gas sensor is presented. The controlelement, called micro hotplate, is comprised of a micro heater and a temperature sensor, both made with polysilicon, located near each other. This material has a Temperature Coefficient of Resistance (TCR) that is the basis for the design of the temperature controller of the gas sensor system. A high temperature between 250 and 400°C is needed to produce a chemical reaction between the gas and the sensing film, hence a reliable temperature control for the micro hotplate is desired. Thermal insulation of the circuitry from the heating element, having a monolithic sensor system, and low power consumption, are the main specifications for the system. This is obtained by means of a micro pit realized with MEMS micromachining processes. The analysis of the circuit proposed to fulfill these characteristics is presented, for its future integration with a standard CMOS technology. A trade off is established between the sensor structure parameters and the circuit design.
A novel CMAC hybrid control strategy with fast convergence and high precision is proposed for the electric loading system of UAVs in order to solve disturbance of the surplus torque. This CMAC control strategy employs...
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Single sample face recognition (SSFR) is an active and challenging research subject in the biometric and artificial intelligence communities with the ultimate objective of recognizing individuals using only one facial...
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In this paper, we consider the robust output feedback problem for constrained linear systems. A novel interpolation based control scheme is introduced, which guarantees feasibility and robust asymptotically stable clo...
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The industrial automation with multi processing controller is a technology that has revolutionized the way that industrial processes are managed. It has enabled the automation of complex and varied processes, allowing...
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Without traditional mechanical differentials, electric vehicles need electric differentials to avoid slipping. This paper proposed a novel electric differential control strategy to solve the problem. According to the ...
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The global outbreak of the novel Coronavirus disease (COVID-19) has impacted millions of individuals, leading to widespread health, economic, and social consequences. Additionally, the overwhelming number of COVID-19 ...
The global outbreak of the novel Coronavirus disease (COVID-19) has impacted millions of individuals, leading to widespread health, economic, and social consequences. Additionally, the overwhelming number of COVID-19 cases has strained healthcare facilities, underscoring the crucial need for timely and accurate detection of infected individuals to mitigate the pandemic’s impact. Inspired by the fact that existing deep learning models often rely on millions of parameters, rendering them unsuitable for resource-constrained devices, we developed a lightweight Parallel Convolutional Neural Network (PCNN) in this research. The model addresses the necessity for efficient COVID-19 pneumonia diagnostics from chest X-ray images by significantly reducing the number of parameters, resulting in a notable accuracy of 99.25% with 313k parameters. To further reduce parameters, separable convolution blocks were introduced, yielding an accuracy of 99.21% with 224k parameters. Despite their lightweight nature, our model demonstrates competitive performance compared to heavyweight models, emphasizing an accuracy rate of 99.21%. By minimizing computational costs and memory requirements, our model offers a cost-effective solution that can be effortlessly deployed on devices with limited resources.
The transport mechanisms in both silicon porous layers (PSL) and ZnO/PSL/c-Si heterostructures were identified by Current-Voltage (I-V) measurements. The PSL were made by anodic etching of p-type (100) Silicon (Si) wa...
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The transport mechanisms in both silicon porous layers (PSL) and ZnO/PSL/c-Si heterostructures were identified by Current-Voltage (I-V) measurements. The PSL were made by anodic etching of p-type (100) Silicon (Si) wafers with resistivity of 1-5 ¿-cm. The heterostructures were manufactured by depositing a zinc oxide (ZnO) film by DC-sputtering on the previously obtained PSL. The measured electrical resistivity of the ZnO films and the PSL were of 5.3 × 10 5 and 5.7 × 10 7 ¿-cm, respectively. The current flow in the PSL is limited by the space-charge regions (SCL), due to the charge trapped in the distinct energy localized states. For the heterostructures similar results were found, where the dominant transport mechanisms are associated to the physical characteristics of the PSL and the ZnO films. Accordingly a bandgap diagram for ZnO/PSL heterostructure is proposed, where the participation of the variety of the defect levels are considered.
Power flow optimization is paramount in ensuring reliable and efficient operation of electrical grid networks, especially as grids become more intricate with the integration of renewable energy sources. Classical comp...
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Grid congestion forms an obstacle for the adoption of electric vehicles (EVs) by companies for their sustainability goals. This paper presents a robust approach to smart charging of large fleets of EVs that only utili...
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