In this paper, we introduce a surveillance system utilizing mmWave-FMCW radar designed for restricted control areas. The experiment, conducted in our laboratory, defines the restricted control area parameters. Employi...
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ISBN:
(数字)9798350381559
ISBN:
(纸本)9798350381566
In this paper, we introduce a surveillance system utilizing mmWave-FMCW radar designed for restricted control areas. The experiment, conducted in our laboratory, defines the restricted control area parameters. Employing the TI-IWR6843AOPEVM model, operating at 60–64 GHz, and providing point cloud and Doppler information, we assumed walking paths for testing, partitioning scenarios into four distinct cases to simulate real-world scenarios. System performance evaluation, assessed through confusion matrices, demonstrates an achieved accuracy of up to 76.9%. Notably, errors are mainly caused by multipath effects due to static objects within the testing environment.
作者:
Mishne, GalCharles, AdamHalıcıoğlu Data Science Institute
Department of Electrical and Computer Engineering the Neurosciences Graduate Program UC San Diego 9500 Gilman Drive La Jolla CA92093 United States Department of Biomedical Engineering
Kavli Neuroscience Discovery Institute Center for Imaging Science Department of Neuroscience Mathematical Institute for Data Science Johns Hopkins University BaltimoreMD21287 United States
Optical imaging of the brain has expanded dramatically in the past two decades. New optics, indicators, and experimental paradigms are now enabling in-vivo imaging from the synaptic to the cortex-wide scales. To match...
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In this paper, we propose a methodology aimed to enhancing the accuracy of moving target positioning using FMCW radar within spectrogram mapping. Utilizing a 10 GHz operating frequency, the FMCW radar effectively dete...
详细信息
ISBN:
(数字)9798350381559
ISBN:
(纸本)9798350381566
In this paper, we propose a methodology aimed to enhancing the accuracy of moving target positioning using FMCW radar within spectrogram mapping. Utilizing a 10 GHz operating frequency, the FMCW radar effectively detects moving targets. However, the interpretation of intermediate frequency (IF) signals posed challenges due to multiple reflections and resulting ambiguous distances between objects. For solving this problem, we propose two steps of solution: employing an enveloping method and normalization of the IF signal. This process can extract maximum amplitude peaks specific to the target. Experimental validation involved detecting a drone moving away from the radar. Comparative analysis pre and post signal processing in spectrogram terms demonstrate the efficacy of our technique. Furthermore, verification of the detection range of radar was conducted using the GSM-015 GNSS speed meter. Results confirm the accuracy of the positioning capabilities of radar, emphasizing the effectiveness of the proposed approach.
Industrial conveyor belt systems are an efficient means of transport due to their adaptability and extension. Nonetheless, such systems are prone to various failures, including but not limited to: idler anomalies; bel...
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ISBN:
(数字)9798350380903
ISBN:
(纸本)9798350380910
Industrial conveyor belt systems are an efficient means of transport due to their adaptability and extension. Nonetheless, such systems are prone to various failures, including but not limited to: idler anomalies; belt tears; and pin misalignment which can cause significant disruptions in the production process. Preemptive maintenance and health monitoring of these conveyor belts is a common practice for avoiding these failures, but a challenging task due to the rarity of comprehensive anomaly detection datasets in the area, with current works aimed at evaluating the belt's immediate condition at fixed points. This study addresses this research gap by comparing multiple machine learning techniques, such as a proposed Hybrid Neural Network (HNN) tailored for classification of multiple anomaly classes, as well as machine learning approaches for time series based on feature extraction, Catch22, Minirocket Arsenal, and Time Series Forest. Our proposed HNN architecture performed better in classifying and distinguishing between different types of anomalies, with an accuracy of 95.55%. The obtained results suggest a promising approach for the area of predictive maintenance for industrial conveyor systems, as well as gives insights on possible improvements on the model and future research.
This research proposes the dandelion optimizer (DO), a bioinspired stochastic optimization technique, as a solution for achieving maximum power point tracking (MPPT) in photovoltaic (PV) arrays under partial shading (...
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The Flying Robot Trial League (FRTL), from RoboCup Brazil, is a competition that stimulates the development of autonomous and intelligent flying robots for inspection and operation in pipeline lanes and oil installati...
The Flying Robot Trial League (FRTL), from RoboCup Brazil, is a competition that stimulates the development of autonomous and intelligent flying robots for inspection and operation in pipeline lanes and oil installations. In this context, this work presents the system developed by the BDP-UaiFly Team for the 2022 competition, using the off-the-shelf Parrot Bebop 2 to execute the Equipment Transport phase. This paper presents in detail the system platform and the navigation and sensing strategies implemented for autonomous navigation and image processing. In particular, the strategy adopted for cargo transportation based on servo-visual control is presented. Practical experiments validate the proposed solutions for the phases of the challenge.
Future wireless communication systems will evolve toward multi-functional integrated systems to improve spectrum utilization and reduce equipment sizes. A joint radar and communication (JRC) system, which can support ...
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Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitati...
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Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze continued...challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative
In this research study, we compare the predictive performance of two advanced deep learning-based models in order to provide a solution to TACE (Transarterial Chemoembolization) response prediction in HCC (Hepatocellu...
In this research study, we compare the predictive performance of two advanced deep learning-based models in order to provide a solution to TACE (Transarterial Chemoembolization) response prediction in HCC (Hepatocellular Carcinoma) patients. Using entire abdominal CT scans enabled a broader perspective available for the model, eliminating the need for segmentation during the preprocessing. Making use of both single-phase and multi-phase CT imaging, we have used DenseNet121 and have obtained an accuracy of 80% for the multi-phase *** Relevance: The ability to predict the effectiveness of TACE treatment prior to its administration makes it possible to provide a better decision-making aid for physicians and patients.
In this paper, the overall health index of underground cable system is determined using Fuzzy Logic and Scoring and Weighting Average methods. The relevant data of 73 feeders has been collected in the prepared evaluat...
In this paper, the overall health index of underground cable system is determined using Fuzzy Logic and Scoring and Weighting Average methods. The relevant data of 73 feeders has been collected in the prepared evaluation forms, divided into five major component groups: cable, joint, termination, manhole, and ductbank. In each component, various testing methods and diagnostic techniques are applied, and then the numerical score is determined according to the technical criteria for condition assessment. Subsequently, the obtained overall health index is multiplied with the conditional factor to incorporate the differences in installation type and configuration as well as the operating and environmental conditions. Finally, the overall health index based on these two methods is compared to verify the accuracy of the obtained results to properly plan the preventive and condition-based maintenance and to improve the reliability of the underground cable system.
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