A volatile organic compound (VOCs) classification system is developed for non-invasive biomarker screening tests. The developed system utilizes a preconcentrator, which contains an absorbent material for trapping VOCs...
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ISBN:
(纸本)9798350381566;9798350381559
A volatile organic compound (VOCs) classification system is developed for non-invasive biomarker screening tests. The developed system utilizes a preconcentrator, which contains an absorbent material for trapping VOCs at low temperatures and thermally desorbingat specific elevated temperatures. This system is especially useful for detection of odor mixture at low concentration and target VOCs biomarkers in the odor sample can also be measured with enhanced selectivity. All sensing processes, including a PID temperature controller for heating preconcentrator, odor sensor interface, and solenoid valve control, are performed using only a single embedded microcontroller. An odor mixture with low concentration is measured and classified in order to investigate the developed system. The result of the experiment and the principal component analysis (PCA) shows that the system with the preconcentrator can measure the VOCs mixture of odor sample in terms of sensitivity and selectivity. This system prototype is useful for screening tests of exhaled breath biomarker.
In response to the constant threat of forceful invasions targeting residences, businesses, and institutions, the researchers developed a Suspicious-Activity Detection system that integrates real-time human pose detect...
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Birds are nice-looking from their aesthetic looks and life styles, around 50 billion of birds are living on the earth where some birds are in threat of extinction. For people, distinguishing and classification of bird...
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This paper presents a vibration testing program designed to evaluate the reliability of PCB boards in complex underwater environments. The study thoroughly examines the structural components of the PCB and the vibrati...
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Automation and robotics are known as one of the key technological enablers of industry 4.0. In the world of production, automation and robotics are leaders in digital transformation. While there is abundant research d...
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In this paper, an automatic cigarette appearance defect detection system based on deep learning algorithm is proposed, aiming to improve the defect detection efficiency and accuracy in the cigarette production process...
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ISBN:
(纸本)9798350377040;9798350377033
In this paper, an automatic cigarette appearance defect detection system based on deep learning algorithm is proposed, aiming to improve the defect detection efficiency and accuracy in the cigarette production process. By using a pre-trained ResNet18 network model, the system automatically identifies defective products in the cigarette production line. We trained and validated the model on the dataset, and showed the trends of the loss function and accuracy during the training process. The experimental results show that the model can effectively recognize multiple cigarette defects, especially in handling broken and deformed defects, and exhibits high accuracy and robustness. The study shows that the application of deep learning-based defect detection technology in cigarette production has significant potential and can provide intelligent solutions for quality control.
This paper considers a system composed of multiple Unmanned Aerial Vehicles (UAVs), in this case quadrotors, carrying a payload by flexible cables. A set of dynamic equations is proposed to describe the behavior of th...
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ISBN:
(纸本)9798350358513;9798350358520
This paper considers a system composed of multiple Unmanned Aerial Vehicles (UAVs), in this case quadrotors, carrying a payload by flexible cables. A set of dynamic equations is proposed to describe the behavior of the system during flight. In a scenario describing one of the UAVs to have a failure and automatically detaching from the system, a distributed recovery strategy is proposed to restore stability to the remaining team, using a combination of Proportional, Integrative and Derivative control, Integrative Sliding Mode Control, and Consensus-Based control. A considered software architecture is provided, and software-in-the-loop tests are performed as a validation step for the proposed algorithms. Results are compared with the more classical Sliding Mode Control technique and subsequently integrated with a formation change strategy.
To enhance the detection capability of satellite systems for airborne targets, this paper proposes a dual-satellite passive positioning method that incorporates the weights of direction-finding errors. The method cons...
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This study aims to develop a 3D diagnostic system for electric vehicle surface damage, leveraging fiber optic sensors and the CenterNet algorithm, specifically designed to address the current issues of low efficiency ...
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This study constructs an intelligent investment advisor system based on a knowledge graph to address the complex decision-making needs in financial markets. By integrating natural language processing (NLP) technology ...
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