Pub Date : 2015-08-01DOI: 10.1109/DSP-SPE.2015.7369555
Ahmad B. Zoubi, K. S. Alguri, Ganghun Kim, V. J. Mathews, R. Menon, J. Harley
Fluorescent miscroscopy is a state-of-the-art method for creating high contrast and high resolution images of microscopic structures and has found wide application in microendoscopy (i.e., imaging cellular information from an optical probe within an animal). Cannula based microscopy methods have recently shown great promise for efficient microendoscopy imaging. Yet, performing real-time imaging with cannula methods have yet to be achieved due to the high computational complexity of the algorithms used for image reconstruction. We present an approach based on compressive sensing to improve computational speed and image reconstruction quality. We compare our approach with the state-of-the-art implementation based on direct binary search, a non-linear optimization technique. Results demonstrating up to 70 times improvement in the computation time and visual quality of the image over the direct binary search method are included in the paper.
{"title":"Fast imaging in cannula microscope using orthogonal matching pursuit","authors":"Ahmad B. Zoubi, K. S. Alguri, Ganghun Kim, V. J. Mathews, R. Menon, J. Harley","doi":"10.1109/DSP-SPE.2015.7369555","DOIUrl":"https://doi.org/10.1109/DSP-SPE.2015.7369555","url":null,"abstract":"Fluorescent miscroscopy is a state-of-the-art method for creating high contrast and high resolution images of microscopic structures and has found wide application in microendoscopy (i.e., imaging cellular information from an optical probe within an animal). Cannula based microscopy methods have recently shown great promise for efficient microendoscopy imaging. Yet, performing real-time imaging with cannula methods have yet to be achieved due to the high computational complexity of the algorithms used for image reconstruction. We present an approach based on compressive sensing to improve computational speed and image reconstruction quality. We compare our approach with the state-of-the-art implementation based on direct binary search, a non-linear optimization technique. Results demonstrating up to 70 times improvement in the computation time and visual quality of the image over the direct binary search method are included in the paper.","PeriodicalId":91992,"journal":{"name":"2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE)","volume":"5 1","pages":"214-219"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85284012","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 : 2015-08-01DOI: 10.1109/DSP-SPE.2015.7369589
Y. Alotaibi, Y. Seddiq
A mapping system based on an artificial neural network was designed, trained, and tested to map Arabic acoustic parameters to their corresponding articulatory features. The main objective of the study was to find the correlation between these two different types of features. To train and test the system, an in-house database was created for all 29 Arabic alphabets as carrier words for our intended Arabic phonemes. Fifty Arabic native speakers were asked to utter all alphabets 10 times. Hence, the database consisted of 10 repetitions of each alphabet produced by each speaker, resulting in 14,500 tokens. The system was tested to extract Arabic articulatory features using another disjoint speech data subset. The overall accuracy of the system was 64.06% for all articulatory feature elements and all Arabic phonemes.
{"title":"Mapping Arabic acoustic parameters to their articulatory features using neural networks","authors":"Y. Alotaibi, Y. Seddiq","doi":"10.1109/DSP-SPE.2015.7369589","DOIUrl":"https://doi.org/10.1109/DSP-SPE.2015.7369589","url":null,"abstract":"A mapping system based on an artificial neural network was designed, trained, and tested to map Arabic acoustic parameters to their corresponding articulatory features. The main objective of the study was to find the correlation between these two different types of features. To train and test the system, an in-house database was created for all 29 Arabic alphabets as carrier words for our intended Arabic phonemes. Fifty Arabic native speakers were asked to utter all alphabets 10 times. Hence, the database consisted of 10 repetitions of each alphabet produced by each speaker, resulting in 14,500 tokens. The system was tested to extract Arabic articulatory features using another disjoint speech data subset. The overall accuracy of the system was 64.06% for all articulatory feature elements and all Arabic phonemes.","PeriodicalId":91992,"journal":{"name":"2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE)","volume":"9 1","pages":"409-414"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82483228","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 : 2015-08-01DOI: 10.1109/DSP-SPE.2015.7369569
J. E. Cadena, A. Beex
Analysis and design of a digital filter, implemented with fixed-point arithmetic, provides students with opportunities to apply and integrate a large variety of concepts. They also learn about various applications and trade-offs. Evaluating the performance of the resulting nonlinear system against the desired response presents interesting choices regarding the utility of various discrete-time measurement approaches. As digital filters are often subsystems in an analog processing chain, it makes sense to measure digital filter performance using analog domain measurements. Measuring performance in real time brings out timing issues not encountered in the discrete-time performance measurements. The re-development of a useful framework for the implementation of such a design experience, using a modern USB-interfaced processor, has provided the additional learning experience that assembly language programming still has its place.
{"title":"DSP education by fixed-point implementation & measurement","authors":"J. E. Cadena, A. Beex","doi":"10.1109/DSP-SPE.2015.7369569","DOIUrl":"https://doi.org/10.1109/DSP-SPE.2015.7369569","url":null,"abstract":"Analysis and design of a digital filter, implemented with fixed-point arithmetic, provides students with opportunities to apply and integrate a large variety of concepts. They also learn about various applications and trade-offs. Evaluating the performance of the resulting nonlinear system against the desired response presents interesting choices regarding the utility of various discrete-time measurement approaches. As digital filters are often subsystems in an analog processing chain, it makes sense to measure digital filter performance using analog domain measurements. Measuring performance in real time brings out timing issues not encountered in the discrete-time performance measurements. The re-development of a useful framework for the implementation of such a design experience, using a modern USB-interfaced processor, has provided the additional learning experience that assembly language programming still has its place.","PeriodicalId":91992,"journal":{"name":"2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE)","volume":"25 1","pages":"295-300"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82425701","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 : 2015-08-01DOI: 10.1109/DSP-SPE.2015.7369559
Ziqiang Meng, Yachao Li, M. Xing, Z. Bao
Synthetic aperture radar (SAR) raw data simulator is an important tool for parameter-optimizing and algorithm-testing, particularly for those complicated configurations in which real raw data is difficult to obtain. As a new and special imaging mode, bistatic forward-looking SAR with constant acceleration (BFCA-SAR) can perform two-dimensional imaging for targets in the straight-ahead position over mono-static SAR. But there exist more complicated square roots and high-order terms in range history owing to high velocities and accelerations from both platforms. In addition, space variances in phase terms of two-dimensional frequency spectrum (2-D FS) make it difficult to gain echo data accurately. In this paper, a fast scene raw data simulator for BFCA-SAR based on quantitative analysis and effective correction of phase space variance is proposed. With high precision, our method can generate raw data more efficiently than traditional algorithms.
{"title":"Fast raw data simulator of extended scenes for bistatic forward-looking synthetic aperture radar with constant acceleration","authors":"Ziqiang Meng, Yachao Li, M. Xing, Z. Bao","doi":"10.1109/DSP-SPE.2015.7369559","DOIUrl":"https://doi.org/10.1109/DSP-SPE.2015.7369559","url":null,"abstract":"Synthetic aperture radar (SAR) raw data simulator is an important tool for parameter-optimizing and algorithm-testing, particularly for those complicated configurations in which real raw data is difficult to obtain. As a new and special imaging mode, bistatic forward-looking SAR with constant acceleration (BFCA-SAR) can perform two-dimensional imaging for targets in the straight-ahead position over mono-static SAR. But there exist more complicated square roots and high-order terms in range history owing to high velocities and accelerations from both platforms. In addition, space variances in phase terms of two-dimensional frequency spectrum (2-D FS) make it difficult to gain echo data accurately. In this paper, a fast scene raw data simulator for BFCA-SAR based on quantitative analysis and effective correction of phase space variance is proposed. With high precision, our method can generate raw data more efficiently than traditional algorithms.","PeriodicalId":91992,"journal":{"name":"2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE)","volume":"39 1","pages":"237-242"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81007179","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 : 2015-08-01DOI: 10.1109/DSP-SPE.2015.7369533
J. Gunther, T. Moon
This paper describes a series of C programming lab assignments that accompany a junior-level course on discrete-time signals and systems. These assignments were designed to develop student into experts in two core competencies: filtering and frequency analysis of signals. As students develop knowledge and practice these two skills, they learn about a variety of related techniques including sample rate conversion, edge detection in images, the Hilbert transform, noise cancellation, AM and FM modulation and demodulation, and global positioning. The labs reinforce concepts taught in class. Students get extensive practice in designing filters to meet given specifications. Students report enthusiasm for learning about real systems and processing real signals. By focusing on two key capabilities, students are able to advance to a high level of maturity in these areas over a single semester.
{"title":"Nine C programming labs to turn students into filtering and signal analysis experts","authors":"J. Gunther, T. Moon","doi":"10.1109/DSP-SPE.2015.7369533","DOIUrl":"https://doi.org/10.1109/DSP-SPE.2015.7369533","url":null,"abstract":"This paper describes a series of C programming lab assignments that accompany a junior-level course on discrete-time signals and systems. These assignments were designed to develop student into experts in two core competencies: filtering and frequency analysis of signals. As students develop knowledge and practice these two skills, they learn about a variety of related techniques including sample rate conversion, edge detection in images, the Hilbert transform, noise cancellation, AM and FM modulation and demodulation, and global positioning. The labs reinforce concepts taught in class. Students get extensive practice in designing filters to meet given specifications. Students report enthusiasm for learning about real systems and processing real signals. By focusing on two key capabilities, students are able to advance to a high level of maturity in these areas over a single semester.","PeriodicalId":91992,"journal":{"name":"2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE)","volume":"12 1","pages":"89-94"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89321736","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 : 2015-08-01DOI: 10.1109/DSP-SPE.2015.7369585
M. Murguia, Carlos Avalos-Gonzalez, O. Arias-Enriquez
This paper describes preliminary results of an auxiliary system designed to obtain a standard of gait kinematic of children in the age of 6 to 12 years of a specific population. It is expected that the use of the system may help children from vulnerable social groups with disabilities due to accidents or illness. The system is based on the Microsoft Kinect 3D sensor. Corporal segments and markers are determined by extracting the body silhouette using a background subtraction technique and morphologic operations on the depth plane. Results obtained with the proposed system proved that the system is able to estimate the main corporal markers needed in gait analysis. The estimations showed good correlation compared with a manual ground truth. The maximum relative angle average deviation found was 1.63° indicating acceptable mark tracking.
{"title":"Body markers detection based on 3D video processing oriented to children gait analysis","authors":"M. Murguia, Carlos Avalos-Gonzalez, O. Arias-Enriquez","doi":"10.1109/DSP-SPE.2015.7369585","DOIUrl":"https://doi.org/10.1109/DSP-SPE.2015.7369585","url":null,"abstract":"This paper describes preliminary results of an auxiliary system designed to obtain a standard of gait kinematic of children in the age of 6 to 12 years of a specific population. It is expected that the use of the system may help children from vulnerable social groups with disabilities due to accidents or illness. The system is based on the Microsoft Kinect 3D sensor. Corporal segments and markers are determined by extracting the body silhouette using a background subtraction technique and morphologic operations on the depth plane. Results obtained with the proposed system proved that the system is able to estimate the main corporal markers needed in gait analysis. The estimations showed good correlation compared with a manual ground truth. The maximum relative angle average deviation found was 1.63° indicating acceptable mark tracking.","PeriodicalId":91992,"journal":{"name":"2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE)","volume":"40 1","pages":"385-390"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89892714","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 : 2015-08-01DOI: 10.1109/DSP-SPE.2015.7369564
G. Hampson, J. Tuthill, A. Brown, J. Bunton, T. Bateman
For many decades Digital Signal Processing (DSP) nodes have been designed for processing digital data received from arrays of radio telescopes. Common threads in all these nodes are: digital communications, processing and memory. Fundamentally the aim of each system was to provide the greatest operational capability for the technology available at that time. As the systems grew in size it became apparent that a key performance indicator was how processing nodes communicated. Poor communication could result in delayed schedules, reduced operational performance and higher system costs. The Square Kilometre Array (SKA) project represents a quantum leap in system size relative to current radio astronomy telescopes. This paper explores current work in this area and introduces the possibility of a fully optically connected processing and memory node. Such a node could be utilized for multi-stage polyphase filterbanks, beamforming and correlation. The application presented here is radio astronomy, but it could also be applied to defence and telecommunication systems.
{"title":"A reconfigurable optically connected beamformer and correlator processing node for SKA","authors":"G. Hampson, J. Tuthill, A. Brown, J. Bunton, T. Bateman","doi":"10.1109/DSP-SPE.2015.7369564","DOIUrl":"https://doi.org/10.1109/DSP-SPE.2015.7369564","url":null,"abstract":"For many decades Digital Signal Processing (DSP) nodes have been designed for processing digital data received from arrays of radio telescopes. Common threads in all these nodes are: digital communications, processing and memory. Fundamentally the aim of each system was to provide the greatest operational capability for the technology available at that time. As the systems grew in size it became apparent that a key performance indicator was how processing nodes communicated. Poor communication could result in delayed schedules, reduced operational performance and higher system costs. The Square Kilometre Array (SKA) project represents a quantum leap in system size relative to current radio astronomy telescopes. This paper explores current work in this area and introduces the possibility of a fully optically connected processing and memory node. Such a node could be utilized for multi-stage polyphase filterbanks, beamforming and correlation. The application presented here is radio astronomy, but it could also be applied to defence and telecommunication systems.","PeriodicalId":91992,"journal":{"name":"2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE)","volume":"50 1","pages":"267-271"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89157032","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 : 2015-08-01DOI: 10.1109/DSP-SPE.2015.7369591
Ayush Sharma, David V. Anderson
Despite the existence of a robust model to identify basic emotions, the ability to classify a large group of emotions with reliability is yet to be developed. Hence, objective of this paper is to develop an efficient technique to identify emotions with an accuracy comparable to humans. The array of emotions addressed in this paper go far beyond what are present on the circumflex diagram. Due to the nature of correlation and ambiguity present in emotions, both prosodic and spectral features of speech are considered during the feature extraction. Feature selection algorithms are applied to work on a subset of relevant features. Owing to the low dimensionality of the feature space, several cross validation methods are employed in combination with different classifiers and their performances are compared. In addition to cross validation, the bootstrap error estimate is also calculated and a combination of both is used as an overall estimate of the classification accuracy of the model.
{"title":"Deep emotion recognition using prosodic and spectral feature extraction and classification based on cross validation and bootstrap","authors":"Ayush Sharma, David V. Anderson","doi":"10.1109/DSP-SPE.2015.7369591","DOIUrl":"https://doi.org/10.1109/DSP-SPE.2015.7369591","url":null,"abstract":"Despite the existence of a robust model to identify basic emotions, the ability to classify a large group of emotions with reliability is yet to be developed. Hence, objective of this paper is to develop an efficient technique to identify emotions with an accuracy comparable to humans. The array of emotions addressed in this paper go far beyond what are present on the circumflex diagram. Due to the nature of correlation and ambiguity present in emotions, both prosodic and spectral features of speech are considered during the feature extraction. Feature selection algorithms are applied to work on a subset of relevant features. Owing to the low dimensionality of the feature space, several cross validation methods are employed in combination with different classifiers and their performances are compared. In addition to cross validation, the bootstrap error estimate is also calculated and a combination of both is used as an overall estimate of the classification accuracy of the model.","PeriodicalId":91992,"journal":{"name":"2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE)","volume":"32 1","pages":"421-425"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87016580","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 : 2015-08-01DOI: 10.1109/DSP-SPE.2015.7369573
C. Wright, T. Welch, M. Morrow
Students who are learning fundamental principles of optical engineering can take advantage of existing knowledge of digital signal processing to greatly facilitate mastery of the new topics. This paper describes how professors can take advantage of this opportunity.
{"title":"Leveraging student knowledge of DSP for optical engineering","authors":"C. Wright, T. Welch, M. Morrow","doi":"10.1109/DSP-SPE.2015.7369573","DOIUrl":"https://doi.org/10.1109/DSP-SPE.2015.7369573","url":null,"abstract":"Students who are learning fundamental principles of optical engineering can take advantage of existing knowledge of digital signal processing to greatly facilitate mastery of the new topics. This paper describes how professors can take advantage of this opportunity.","PeriodicalId":91992,"journal":{"name":"2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE)","volume":"49 1","pages":"319-324"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90413844","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 : 2015-08-01DOI: 10.1109/DSP-SPE.2015.7369570
William J. Esposito, Fernando A. Mujica, Domingo G. Garcia, G. Kovacs
The Stanford “Lab-In-A-Box” project comprises an open source hardware and software tool chain for teaching signal processing and analog electronics. It is intended to improve the teaching of these concepts by providing a platform that is more open and understandable and by lowering the economic barriers to students interested in the field. To do this, the Lab-In-A-Box brings a full powered Digital Signal Processor (DSP) core to the popular Arduino microcontroller environment and marries it with a simple to use analog front end (AFE). The software platform provided with the Lab-In-A-Box includes an Arduino-like development environment that facilitates learning and quick development of signal processing applications without abstracting away the intricacies of a practical implementation. This system has been used to create several teaching examples and has been tested in courses at Stanford University.
{"title":"The Lab-In-A-Box project: An Arduino compatible signals and electronics teaching system","authors":"William J. Esposito, Fernando A. Mujica, Domingo G. Garcia, G. Kovacs","doi":"10.1109/DSP-SPE.2015.7369570","DOIUrl":"https://doi.org/10.1109/DSP-SPE.2015.7369570","url":null,"abstract":"The Stanford “Lab-In-A-Box” project comprises an open source hardware and software tool chain for teaching signal processing and analog electronics. It is intended to improve the teaching of these concepts by providing a platform that is more open and understandable and by lowering the economic barriers to students interested in the field. To do this, the Lab-In-A-Box brings a full powered Digital Signal Processor (DSP) core to the popular Arduino microcontroller environment and marries it with a simple to use analog front end (AFE). The software platform provided with the Lab-In-A-Box includes an Arduino-like development environment that facilitates learning and quick development of signal processing applications without abstracting away the intricacies of a practical implementation. This system has been used to create several teaching examples and has been tested in courses at Stanford University.","PeriodicalId":91992,"journal":{"name":"2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE)","volume":"61 1","pages":"301-306"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83004241","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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