Pub Date : 2017-06-01DOI: 10.1109/NAECON.2017.8268719
Gayatri M. Behara, V. Chodavarapu
We present a portable system that is capable of providing autonomous surveillance in real-world environments. We aim to expand the functionality of surveillance systems by combining autonomous object recognition along with depth perception to identify the object and its distance from the camera. Such capability would prove invaluable to autonomous surveillance applications, where persons carrying any forbidden and/or dangerous objects are detected in real-time and appropriate warnings are signaled. We have selected Microsoft Kinect V2 system which includes built-in hardware implementation of algorithms to identify humzans in a complex real-world setting. In addition, the system can simultaneously track 6 people at any time and provide their skeletal joint diagrams for motion tracking. The current work deals with using the skeletal joint diagrams and depth maps to create a focus around the hand area of the people. Our developed algorithm deals with object detection after the segmentation of hands. We use machine learning techniques with establishment of training datasets that include the library of objects that we aim to detect. Finally, the complete signal processing software is implemented within a single board computer.
{"title":"Towards autonomous surveillance in real world environments","authors":"Gayatri M. Behara, V. Chodavarapu","doi":"10.1109/NAECON.2017.8268719","DOIUrl":"https://doi.org/10.1109/NAECON.2017.8268719","url":null,"abstract":"We present a portable system that is capable of providing autonomous surveillance in real-world environments. We aim to expand the functionality of surveillance systems by combining autonomous object recognition along with depth perception to identify the object and its distance from the camera. Such capability would prove invaluable to autonomous surveillance applications, where persons carrying any forbidden and/or dangerous objects are detected in real-time and appropriate warnings are signaled. We have selected Microsoft Kinect V2 system which includes built-in hardware implementation of algorithms to identify humzans in a complex real-world setting. In addition, the system can simultaneously track 6 people at any time and provide their skeletal joint diagrams for motion tracking. The current work deals with using the skeletal joint diagrams and depth maps to create a focus around the hand area of the people. Our developed algorithm deals with object detection after the segmentation of hands. We use machine learning techniques with establishment of training datasets that include the library of objects that we aim to detect. Finally, the complete signal processing software is implemented within a single board computer.","PeriodicalId":306091,"journal":{"name":"2017 IEEE National Aerospace and Electronics Conference (NAECON)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132872138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-06-01DOI: 10.1109/NAECON.2017.8268799
S. Harper, Jonathan Graf, Michael A. Capone, Justin Eng, Michael Farrell, L. Lerner
Cyber-Physical Systems improve efficiency, accuracy, and access in systems ranging from household appliances to power stations to airplanes. They also bring new risks at the intersection of physical, information, and mission assurance. This paper presents CP-SMARTS, a framework providing a means for propagating CPS assurances from planning to deployment.
{"title":"Formal enforcement of mission assurance properties in cyber-physical systems","authors":"S. Harper, Jonathan Graf, Michael A. Capone, Justin Eng, Michael Farrell, L. Lerner","doi":"10.1109/NAECON.2017.8268799","DOIUrl":"https://doi.org/10.1109/NAECON.2017.8268799","url":null,"abstract":"Cyber-Physical Systems improve efficiency, accuracy, and access in systems ranging from household appliances to power stations to airplanes. They also bring new risks at the intersection of physical, information, and mission assurance. This paper presents CP-SMARTS, a framework providing a means for propagating CPS assurances from planning to deployment.","PeriodicalId":306091,"journal":{"name":"2017 IEEE National Aerospace and Electronics Conference (NAECON)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127750649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-06-01DOI: 10.1109/NAECON.2017.8268758
A. Gillette, Christopher M. Wilson, A. George
Small satellites and CubeSats are becoming an indispensable platform in space-industry development, however, these systems are severely resource-limited. Depending upon mission requirements and available communication bandwidth, it can take hours to days to downlink an image from a spacecraft to the ground. Improvements in sensors tend to generate increasingly larger data products. Since small spacecraft have limited storage space, it is crucial to filter and delete images that do not meet minimum science criteria. Depending on the mission, criteria may vary. Images can be prioritized based on having features such as high land percentage or a specific land color. Certain images are rarely useful, such as pitch-black images and cloud-filled images, and can be readily deleted. This research describes an autonomous image-classification framework to efficiently use downlink bandwidth by prioritizing image products with high science value for download while deleting others, as well as a training framework for classifier calibration.
{"title":"Efficient and autonomous processing and classification of images on small spacecraft","authors":"A. Gillette, Christopher M. Wilson, A. George","doi":"10.1109/NAECON.2017.8268758","DOIUrl":"https://doi.org/10.1109/NAECON.2017.8268758","url":null,"abstract":"Small satellites and CubeSats are becoming an indispensable platform in space-industry development, however, these systems are severely resource-limited. Depending upon mission requirements and available communication bandwidth, it can take hours to days to downlink an image from a spacecraft to the ground. Improvements in sensors tend to generate increasingly larger data products. Since small spacecraft have limited storage space, it is crucial to filter and delete images that do not meet minimum science criteria. Depending on the mission, criteria may vary. Images can be prioritized based on having features such as high land percentage or a specific land color. Certain images are rarely useful, such as pitch-black images and cloud-filled images, and can be readily deleted. This research describes an autonomous image-classification framework to efficiently use downlink bandwidth by prioritizing image products with high science value for download while deleting others, as well as a training framework for classifier calibration.","PeriodicalId":306091,"journal":{"name":"2017 IEEE National Aerospace and Electronics Conference (NAECON)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128439959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-06-01DOI: 10.1109/NAECON.2017.8268777
Almabrok E. Essa, I. Sudakov, Tharanga Kariyawasam, Mingxue Gong, V. Asari
Greenhouse gas emissions from tundra lakes are a significant positive feedback of the atmosphere. Therefore, detailed knowledge of size distribution of tundra lakes in the Arctic region and their geometrical properties is potentially valuable in order to understand and accurately model the sources of methane emissions from boreal permafrost. In this paper we develop a new approach for computational image analysis of tundra lake patterns on historical maps, which accurately measures the perimeter and area of tundra lakes and calculates their fractal dimension and normal size distribution. We use this approach in order to test whether the size distributions of tundra lakes in the Arctic landscape follow the Pareto distribution or not. For the assessment, we utilize the historical maps of permafrost and detect the features of patterns geometry.
{"title":"Detection of tundra lake patterns on permafrost historical maps","authors":"Almabrok E. Essa, I. Sudakov, Tharanga Kariyawasam, Mingxue Gong, V. Asari","doi":"10.1109/NAECON.2017.8268777","DOIUrl":"https://doi.org/10.1109/NAECON.2017.8268777","url":null,"abstract":"Greenhouse gas emissions from tundra lakes are a significant positive feedback of the atmosphere. Therefore, detailed knowledge of size distribution of tundra lakes in the Arctic region and their geometrical properties is potentially valuable in order to understand and accurately model the sources of methane emissions from boreal permafrost. In this paper we develop a new approach for computational image analysis of tundra lake patterns on historical maps, which accurately measures the perimeter and area of tundra lakes and calculates their fractal dimension and normal size distribution. We use this approach in order to test whether the size distributions of tundra lakes in the Arctic landscape follow the Pareto distribution or not. For the assessment, we utilize the historical maps of permafrost and detect the features of patterns geometry.","PeriodicalId":306091,"journal":{"name":"2017 IEEE National Aerospace and Electronics Conference (NAECON)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114498218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-06-01DOI: 10.1109/NAECON.2017.8268752
S. Majerus, Xinyao Tang, Jifu Liang, S. Mandal
We develop data-driven predictive models for reliability and failure mechanisms of integrated circuits (ICs) at high temperature (HT) by characterizing their aging performance using integrated monitoring circuits (“silicon odometers”). Ring oscillators subjected to multiple stress profiles are promising as digital odometers. In initial experiments, the frequencies of six oscillators fabricated in a 0.5 μm CMOS process were measured for more than six months at 195° C. The results were fitted to generate a data-driven aging model. This model provides information on cumulative changes in device parameters that can be utilized by designers to ensure that the system will meet specified HT reliability targets. Preliminary test results from an automated experimental setup that includes a bandgap voltage reference circuit as an additional silicon odometer are also presented.
{"title":"Embedded silicon odometers for monitoring the aging of high-temperature integrated circuits","authors":"S. Majerus, Xinyao Tang, Jifu Liang, S. Mandal","doi":"10.1109/NAECON.2017.8268752","DOIUrl":"https://doi.org/10.1109/NAECON.2017.8268752","url":null,"abstract":"We develop data-driven predictive models for reliability and failure mechanisms of integrated circuits (ICs) at high temperature (HT) by characterizing their aging performance using integrated monitoring circuits (“silicon odometers”). Ring oscillators subjected to multiple stress profiles are promising as digital odometers. In initial experiments, the frequencies of six oscillators fabricated in a 0.5 μm CMOS process were measured for more than six months at 195° C. The results were fitted to generate a data-driven aging model. This model provides information on cumulative changes in device parameters that can be utilized by designers to ensure that the system will meet specified HT reliability targets. Preliminary test results from an automated experimental setup that includes a bandgap voltage reference circuit as an additional silicon odometer are also presented.","PeriodicalId":306091,"journal":{"name":"2017 IEEE National Aerospace and Electronics Conference (NAECON)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134094684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-06-01DOI: 10.1109/NAECON.2017.8268716
Almabrok E. Essa, V. Asari
How to describe an image accurately with the most useful information is the key of any face recognition task. In this paper, we argue that robust recognition requires several different kinds of information to be taken into account. Therefore, a new technique that combines the facial shape with the local structure of a face image is proposed, namely fusing shape and appearance features (FSAF). It is based on Gabor wavelets and local edge/corner feature integration (LFI) technique. Given an input image, the Gabor features histogram and LFI histogram are built separately. Then a final feature descriptor is formed by concatenating these two histograms, which feeds to the support vector machine (svm) classifier to recognize the face image. FSAF is evaluated on several challenging face datasets and provided promising results.
{"title":"Fusing facial shape and appearance based features for robust face recognition","authors":"Almabrok E. Essa, V. Asari","doi":"10.1109/NAECON.2017.8268716","DOIUrl":"https://doi.org/10.1109/NAECON.2017.8268716","url":null,"abstract":"How to describe an image accurately with the most useful information is the key of any face recognition task. In this paper, we argue that robust recognition requires several different kinds of information to be taken into account. Therefore, a new technique that combines the facial shape with the local structure of a face image is proposed, namely fusing shape and appearance features (FSAF). It is based on Gabor wavelets and local edge/corner feature integration (LFI) technique. Given an input image, the Gabor features histogram and LFI histogram are built separately. Then a final feature descriptor is formed by concatenating these two histograms, which feeds to the support vector machine (svm) classifier to recognize the face image. FSAF is evaluated on several challenging face datasets and provided promising results.","PeriodicalId":306091,"journal":{"name":"2017 IEEE National Aerospace and Electronics Conference (NAECON)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134320973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-06-01DOI: 10.1109/NAECON.2017.8268743
Mohammad Sarim, R. Jha, Manish Kumar
We recently developed a novel learning solution for unsupervised learning in robots based on resistive memory devices arranged in a crossbar fashion and validated it by navigating a robot in an unknown environment with randomly placed obstacles [1]. In this work, we study the effects of variations in device doping concentrations and the resistive states on the performance of the robot during navigation tasks. Such variabilities arise from the variation in process parameters during device fabrication. We have modeled the variabilities in the initial device doping concentration and in the update of the device resistive states. We have also considered the possibility of a device getting stuck in a low resistance state. This study will help us evaluate the performance of our learning scheme and develop specifications on acceptable range of variability in these devices for application-specific tasks.
{"title":"Neuromorphic device specifications for unsupervised learning in robots","authors":"Mohammad Sarim, R. Jha, Manish Kumar","doi":"10.1109/NAECON.2017.8268743","DOIUrl":"https://doi.org/10.1109/NAECON.2017.8268743","url":null,"abstract":"We recently developed a novel learning solution for unsupervised learning in robots based on resistive memory devices arranged in a crossbar fashion and validated it by navigating a robot in an unknown environment with randomly placed obstacles [1]. In this work, we study the effects of variations in device doping concentrations and the resistive states on the performance of the robot during navigation tasks. Such variabilities arise from the variation in process parameters during device fabrication. We have modeled the variabilities in the initial device doping concentration and in the update of the device resistive states. We have also considered the possibility of a device getting stuck in a low resistance state. This study will help us evaluate the performance of our learning scheme and develop specifications on acceptable range of variability in these devices for application-specific tasks.","PeriodicalId":306091,"journal":{"name":"2017 IEEE National Aerospace and Electronics Conference (NAECON)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133333407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-06-01DOI: 10.1109/NAECON.2017.8268787
Mansour Aljohani, Nihad Alfaysale, Ethan Lin, L. Monte, H. Abdelbagi, Abdulmajid Mrebit, M. Wicks
Non-coherent marine radar technology has matured over the past several decades. Researchers have investigated coherening one or more magnetron oscillator based marine radars by sampling the radar signals on transmit and receive [1]. We leverage this research to contribute to the science and technology of RF Tomography based upon exploitation of marine radar technology and these sampling techniques. This requires many steps. First, selecting and suitably modifying an affordable yet suitable marine radar. In this case, we employ a Furuno DRS25A. Second, by embedding an RF sampling circuit, we capture samples of the various radar waveforms. Third, we digitize these transmit and receive signals using a Signatec ADC model PX1500. Next, we design an experimental geometry to support image formation via RF Tomography. We apply Filtered Back projection (FBP) based upon the Fourier Slice Theorem (FST) in order to the match filtered the data and image targets. We provide both simulation analysis and experimental results in this paper.
{"title":"Applying filtered back projection algorithm for pseudo-coherent radar","authors":"Mansour Aljohani, Nihad Alfaysale, Ethan Lin, L. Monte, H. Abdelbagi, Abdulmajid Mrebit, M. Wicks","doi":"10.1109/NAECON.2017.8268787","DOIUrl":"https://doi.org/10.1109/NAECON.2017.8268787","url":null,"abstract":"Non-coherent marine radar technology has matured over the past several decades. Researchers have investigated coherening one or more magnetron oscillator based marine radars by sampling the radar signals on transmit and receive [1]. We leverage this research to contribute to the science and technology of RF Tomography based upon exploitation of marine radar technology and these sampling techniques. This requires many steps. First, selecting and suitably modifying an affordable yet suitable marine radar. In this case, we employ a Furuno DRS25A. Second, by embedding an RF sampling circuit, we capture samples of the various radar waveforms. Third, we digitize these transmit and receive signals using a Signatec ADC model PX1500. Next, we design an experimental geometry to support image formation via RF Tomography. We apply Filtered Back projection (FBP) based upon the Fourier Slice Theorem (FST) in order to the match filtered the data and image targets. We provide both simulation analysis and experimental results in this paper.","PeriodicalId":306091,"journal":{"name":"2017 IEEE National Aerospace and Electronics Conference (NAECON)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114333952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-06-01DOI: 10.1109/NAECON.2017.8268772
D. Dykes, Katherine M. Bowland, K. Allen
A millimeter-wave fragmented aperture antenna is investigated in this work. The antenna operates across Ka-and V-bands, from 30 to 60 GHz. The development process of the antenna is provided, including initial considerations based on prior work, modeling and simulation, fabrication, and measured data. Comparison of modeled and measured data is shown, along with a discussion of these results.
{"title":"Wideband millimeter-wave fragmented aperture antenna","authors":"D. Dykes, Katherine M. Bowland, K. Allen","doi":"10.1109/NAECON.2017.8268772","DOIUrl":"https://doi.org/10.1109/NAECON.2017.8268772","url":null,"abstract":"A millimeter-wave fragmented aperture antenna is investigated in this work. The antenna operates across Ka-and V-bands, from 30 to 60 GHz. The development process of the antenna is provided, including initial considerations based on prior work, modeling and simulation, fabrication, and measured data. Comparison of modeled and measured data is shown, along with a discussion of these results.","PeriodicalId":306091,"journal":{"name":"2017 IEEE National Aerospace and Electronics Conference (NAECON)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114761695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-06-01DOI: 10.1109/NAECON.2017.8268790
Muftah Akroush, M. Wicks, H. Abdelbagi, Turki M. Alanazi, Abdunaser Abdusamad, Abdulhakim Daluom
Reconstructing high quality images of underground objects using ground penetrating radar (GPR) depends on method for 3D GPR data collection and processing. In this paper, we propose an accurate, fast method to reconstruct the image of underground targets using an optimal linear filter, such as matched filter processing. The match filter is the most common approach to simplify the solution of the inversion problem in GPR model. The proposed method is an optimal technical that increases the signal to noise ratio (SNR) to sharpen the quality of the image. Using this technique leads to decreased of reconstruction time. Also, it reduces the data acquisition time which is critical in most GPR applications. Compared with other algorithms, such as truncated singular value decomposition (TSVD) or algebraic reconstruction technique (ART), matched filter algorithms yield a high quality 2D image of shallowly buried objects faster and with minimal computational load or noise effect. Simulation results were carried out using the computational electromagnetic software FEKO and MATLAB, which demonstrate the effectiveness and feasibility of the proposed reconstruction method.
{"title":"RF tomography based optimal linear filter","authors":"Muftah Akroush, M. Wicks, H. Abdelbagi, Turki M. Alanazi, Abdunaser Abdusamad, Abdulhakim Daluom","doi":"10.1109/NAECON.2017.8268790","DOIUrl":"https://doi.org/10.1109/NAECON.2017.8268790","url":null,"abstract":"Reconstructing high quality images of underground objects using ground penetrating radar (GPR) depends on method for 3D GPR data collection and processing. In this paper, we propose an accurate, fast method to reconstruct the image of underground targets using an optimal linear filter, such as matched filter processing. The match filter is the most common approach to simplify the solution of the inversion problem in GPR model. The proposed method is an optimal technical that increases the signal to noise ratio (SNR) to sharpen the quality of the image. Using this technique leads to decreased of reconstruction time. Also, it reduces the data acquisition time which is critical in most GPR applications. Compared with other algorithms, such as truncated singular value decomposition (TSVD) or algebraic reconstruction technique (ART), matched filter algorithms yield a high quality 2D image of shallowly buried objects faster and with minimal computational load or noise effect. Simulation results were carried out using the computational electromagnetic software FEKO and MATLAB, which demonstrate the effectiveness and feasibility of the proposed reconstruction method.","PeriodicalId":306091,"journal":{"name":"2017 IEEE National Aerospace and Electronics Conference (NAECON)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128400251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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