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Change Bit-dept. Procedure for Data Measured Preprocessing before Compression

Change Bit-Depth Procedure for Data Measured Preprocessing b...

IEEE Region 8 International Conference on Computational Technologies in Electrical and Electronics Engineering, SIBIRCON

作者： Alexey V. Levenets Vladislav V. Bondarenko Ruslan I. Bahenov Oleg I. Belozerov Svetlana I. Belozerova Sergey A. Bogatenkov Dept. Automation and System Engineering Pacific National University Khabarovsk Russia Dept. Information Systems and Mathematics Sholom-Aleichem Priamursky State University Birobidzhan Russia Dept. Computer Technology and Computer Graphics Far Eastern State Transport University Khabarovsk Russia Dept. Information Technology in Economics South Ural State University Chelyabinsk Russia

ISBN: (纸本)9781665464819

The paper proposes to change the bit-dept. of the original data sequence as a preprocessing of the measuring data, which is carried out before the compression procedure. In this case the digit capacity conversion is performed without accounting for the primary data sample boundaries. The simulation was carried out in the Matlab software environment. The findings of the authors’ research are presented. They prove to be a promising approach for some types of the studied data at least and several digit capacity values. The analysis of autocorrelation function values showing the data correlation revealed by the conversion is used as an assessment of perspective of the active conversion. In this article the authors review the values of secondary maximums of autocorrelation function. Their occurrence shows the demonstration of the implied correlative correspondence. Such correlations can potentially allow the converted data to be compressed more effectively than the original data using the known compression methods.

关键词： Current measurement Software Encoding Autocorrelation Matlab

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Machine Learning Segmentation and Classification Algorithm to Support Simulated Point Cloud As-Built Model Applications

Machine Learning Segmentation and Classification Algorithm t...

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2021 International Conference on Computing in Civil Engineering, I3CE 2021

作者： Shen, Junzhe Ren, Ran Nicholas Dib, H. McGraw, Tim Habib, Ayman Dept. of Computer Graphics Technology West LafayetteIN United States School of Construction Management Technology West LafayetteIN United States School of Construction Management Technology Knoy Hall of Technology West LafayetteIN United States Lyles School of Civil Engineering West LafayetteIN United States

ISBN: (纸本)9780784483893

Management and maintenance of existing buildings remains a major problem due to the lack of existing three-dimensional (3D) models and accurate as-built representation. In this paper the authors propose to use 3D scanner technology to capture the as-built and existing conditions of the buildings combined with building information modeling (BIM) as the underlying technology, which is a 3D semantic representation of all the life cycle phases of a building. This paper presents the results from creating as-built BIM models of existing buildings, using point cloud (a set of points in 3D space) and machine learning as an intermediate medium. Machine learning methodologies are used to speed up the computation of segmentation and classification of point clouds from a 3D virtual indoor environment using procedural modeling, which focused on two attributes, point density and the level of random errors. In this paper we will present findings on the evaluation of the performance of machine learning segmentation and classification algorithm based on the comparison of ten different point cloud data sets. Different sets of segmentation and classification models with comparison between models and within themselves were provided, which included the mean loss and accuracy between models with different point density. © 2021 Computing in Civil Engineering 2021 - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2021. All rights reserved.

关键词： Life cycle

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Suitable Embedding to Find Similarity Between Left and Right Retinas of a Person 12

Suitable Embedding to Find Similarity Between Left and Right...

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12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019

作者： Biswas, Sangeeta Rohdin, Johan Drahansky, Martin Brno University of Technology Dept. of Intelligent Systems Brno Czech Republic Dept. of Computer Graphics and Multimedia Brno University of Technology Brno Czech Republic

ISBN: (纸本)9781728148526

It is often argued among biometric researchers that the left and right retinas of the same person are as different as the retinas of two different persons. However, in our previous work we showed that by looking at retinal images human volunteers can find some similarity and tell whether a pair of the left and right retinal images belongs to a single person or to two different persons. We also showed that using cosine similarity between the embedded vectors of two retinal images it is possible to find the correct right retinal image for a left retinal image more than what could be expected by chance. In this paper we investigate which type of embedding can give us better cosine similarity measurement between the left and right retinal images of a person. © 2019 IEEE.

关键词： Embeddings

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A database framework for the characterization and classification of parametric models based on complexity metrics to support data analytics 14

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ASME 2019 14th International Manufacturing Science and Engineering Conference, MSEC 2019

作者： Camba, Jorge D. Contero, Manuel Pérez-López, David Dept. of Computer Graphics Technology Purdue University West LafayetteIN United States I3B Universitat Politècnica de València Valencia Spain Institute of New Imaging Technology Universitat Jaume i Castellón de la Plana Spain

ISBN: (纸本)9780791858745

We present a database architecture for exploring,classifying, and visualizing feature-based parametric CADmodels based on quantitative complexity metrics. The systemconsists of (1) an external relational database structure wheremodels are stored along with their graph representation and thenumerical values of each complexity metric, (2) a client modulethat is integrated in the user's CAD system and facilitatesnavigation within the repository, and (3) a report generationmodule that allows exporting CAD complexity data from theexternal repository to other applications for validation andanalysis. In this paper, we justify the need for our system in thecontext of data analytics and discuss the rationale of its designas well as its architecture and implementations details. Finally,we describe a use case that illustrates the application of ourframework in the characterization and evaluation of CADmodels. © ASME 2019 14th International Manufacturing Science and Engineering Conference. All rights reserved.

关键词： computer aided design

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In-dept. assessment of an interactive graph-based approach for the segmentation for pancreatic metastasis in ultrasound acquisitions of the liver with two specialists in internal medicine

arXiv

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arXiv 2018年

作者： Egger, Jan Schmalstieg, Dieter Bettac, Lucas Hänle, Mark Hann, Alexander Chen, Xiaojun Gräter, Tilmann Egger, Jan Zoller, Wolfram G. Hann, Alexander Institute for Computer Graphics Vision Graz University of Technology Graz Austria Dept. of Internal Medicine I Ulm University Ulm Germany School of Mechanical Engineering Shanghai Jiao Tong University Shanghai China Dept. of Diagnostic and Interventional Radiology Ulm University Ulm Germany BioTechMed-Graz Graz Austria Dept. of Internal Medicine and Gastroenterology Katharinenhospital Stuttgart Germany

The manual outlining of hepatic metastasis in (US) ultrasound acquisitions from patients suffering from pancreatic cancer is common practice. However, such pure manual measurements are often very time consuming, and the results repeatedly differ between the raters. In this contribution, we study the in-dept. assessment of an interactive graph-based approach for the segmentation for pancreatic metastasis in US images of the liver with two specialists in Internal Medicine. Thereby, evaluating the approach with over one hundred different acquisitions of metastases. The two physicians or the algorithm had never assessed the acquisitions before the evaluation. In summary, the physicians first performed a pure manual outlining followed by an algorithmic segmentation over one month later. As a result, the experts satisfied in up to ninety percent of algorithmic segmentation results. Furthermore, the algorithmic segmentation was much faster than manual outlining and achieved a median Dice Similarity Coefficient (DSC) of over eighty percent. Ultimately, the algorithm enables a fast and accurate segmentation of liver metastasis in clinical US images, which can support the manual outlining in daily practice. Copyright © 2018, The Authors. All rights reserved.

关键词： Graphic methods

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A secure contact protocol for delay tolerant networks

A secure contact protocol for delay tolerant networks

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International Conference on computer and Information Science (ACIS)

作者： Manghui Tu Kyle W. Riordan Geyang Xie Shuhui Yang Dept. Computer Information Technology & Graphics Purdue University Northwest Hammond IN USA

ISBN: (纸本)9781509055081

Current DTN systems are vulnerable to malicious attacks by compromised nodes taking advantage of the DTN protocols that control how nodes join and leave the backbone. Without addressing such security issues, DTN systems could result in performance degrade, the compromise of message confidentiality and integrity, and denial of service. Thus, effective mechanisms to identify and fix this vulnerability are urgently needed. The objective of this research is to address these issues by identifying DTN system vulnerabilities and potential threats, and providing potential countermeasures. We first illustrate vulnerabilities of the epidemic based contact history propagation protocol and then identify the potential threats to system performance, availability, and integrity as well as countermeasures to prevent such threats existing in DTN networks. A secure contact protocol is developed for DTN network with epidemic based contact history propagation protocol and simulations are conducted to assess its effectiveness on attack detection.

关键词： Peer-to-peer computing History Routing protocols Delays Security System performance

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Automatic viewpoint selection for exploration of time-dependent cerebral aneurysm data

Automatic viewpoint selection for exploration of time-depend...

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Workshops on Image processing for the medicine, 2017

作者： Meuschke, Monique Engelke, Wito Beuing, Oliver Preim, Bernhard Lawonn, Kai Dept. of Computer Graphics and Simulation OvG-University Magdeburg Research Campus STIMULATE Germany Simulation and Software Technology German Aerospace Center Braunschweig Germany Institute of Neuroradiology University Hospital of Magdeburg Research Campus STIMULATE Germany Institute of Computational Visualistics University of Koblenz – Landau Germany

ISBN: (纸本)9783662543443

This paper presents an automatic selection of viewpoints, forming a camera path, to support the exploration of cerebral aneurysms. Aneurysms bear the risk of rupture with fatal consequences for the patient. For the rupture risk evaluation, a combined investigation of morphological and hemodynamic data is necessary. However, the extensive nature of the time-dependent data complicates the analysis. During exploration, domain experts have to manually determine appropriate views, which can be a tedious and time-consuming process. Our method determines optimal viewpoints automatically based on input data such as wall thickness or pressure. The viewpoint selection is modeled as an optimization problem. Our technique is applied to five data sets and we evaluate the results with two domain experts by conducting informal interviews. © Springer-Verlag GmbH Deutschland 2017.

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Evaluation of algorithms for multi-modality whole heart segmentation: An open-access grand challenge

arXiv

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arXiv 2019年

作者： Zhuang, Xiahai Li, Lei Payer, Christian Štern, Darko Urschler, Martin Heinrich, Mattias P. Oster, Julien Wang, Chunliang Smedby, Örjan Bian, Cheng Yang, Xin Heng, Pheng-Ann Mortazi, Aliasghar Bagci, Ulas Yang, Guanyu Sun, Chenchen Galisot, Gaetan Ramel, Jean-Yves Brouard, Thierry Tong, Qianqian Si, Weixin Liao, Xiangyun Zeng, Guodong Shi, Zenglin Zheng, Guoyan Wang, Chengjia MacGillivray, Tom Newby, David Rhode, Kawal Ourselin, Sebastien Mohiaddin, Raad Keegan, Jennifer Firmin, David Yang, Guang School of Data Science Fudan University Shanghai200433 China Fudan-Xinzailing Joint Research Center for Big Data Fudan University Shanghai200433 China School of Biomedical Engineering Shanghai Jiao Tong University Shanghai200240 China Institute of Computer Graphics and Vision Graz University of Technology Graz8010 Austria Ludwig Boltzmann Institute for Clinical Forensic Imaging Graz8010 Austria Institute of Medical Informatics University of Lubeck Lubeck23562 Germany Inserm Université de Lorraine U1254 IADI Nancy France School for Technology and Health KTH Royal Institute of Technology StockholmSE-10044 Sweden School of Biomed. Eng. Health Science Centre Shenzhen University Shenzhen518060 China Dept. of Comp. Sci. and Eng. Chinese University of Hong Kong Hong Kong China University of Central Florida Orlando32816 United States School of Computer Science and Engineering Southeast University Nanjing210096 China Université de Tours 64 avenue Jean Portalis Tours37200 France School of Computer Science Wuhan University Wuhan430072 China Guangdong Provincial Key Laboratory of Computer Vision and Virtual Reality Technology SIAT Shenzhen China Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Institute for Surgical Technology & Biomechanics University of Bern Bern3014 Switzerland BHF Centre for Cardiovascular Science University of Edinburgh Edinburgh United Kingdom Edinburgh Imaging Facility QMRI University of Edinburgh Edinburgh United Kingdom Department of Imaging Sciences & Biomedical Engineering Kings College London London United Kingdom Cardiovascular Research Centre Royal Brompton Hospital LondonSW3 6NP United Kingdom National Heart and Lung Institute Imperial College London London LondonSW7 2AZ United Kingdom

Knowledge of whole heart anatomy is a prerequisite for many clinical applications. Whole heart segmentation (WHS), which delineates substructures of the heart, can be very valuable for modeling and analysis of the anatomy and functions of the heart. However, automating this segmentation can be arduous due to the large variation of the heart shape, and different image qualities of the clinical data. To achieve this goal, a set of training data is generally needed for constructing priors or for training. In addition, it is difficult to perform comparisons between different methods, largely due to differences in the datasets and evaluation metrics used. This manuscript presents the methodologies and evaluation results for the WHS algorithms selected from the submissions to the Multi-Modality Whole Heart Segmentation (MM-WHS) challenge, in conjunction with MICCAI 2017. The challenge provides 120 three-dimensional cardiac images covering the whole heart, including 60 CT and 60 MRI volumes, all acquired in clinical environments with manual delineation. Ten algorithms for CT data and eleven algorithms for MRI data, submitted from twelve groups, have been evaluated. The results show that many of the deep learning (DL) based methods achieved high accuracy, even though the number of training datasets were limited. A number of them also reported poor results in the blinded evaluation, probably due to overfitting in their training. The conventional algorithms, mainly based on multi-atlas segmentation, demonstrated robust and stable performance, even though the accuracy is not as good as the best DL method in CT segmentation. The challenge, including provision of the annotated training data and the blinded evaluation for submitted algorithms on the test data, continues as an ongoing benchmarking resource via its homepage (***/zhuangxiahai/0/mmwhs/). Copyright © 2019, The Authors. All rights reserved.

关键词： Heart

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Analysis of a Payload-based Network Intrusion Detection System Using Pattern Recognition Processors

Analysis of a Payload-based Network Intrusion Detection Syst...

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International Symposium on Collaborative Technologies and Systems

作者： Irshad M. Iqbal Ricardo A. Calix Dept. of Computer Information Technology and Graphics Purdue University Calumet Hammond Indiana

Intrusion detection systems are a necessary tool to protect computer networks from cyber-attacks. Analyzing the payload of a packet can help in identifying strings that can help to detect attacks. Machine learning can be used to train models based on feature extraction of packet payloads. One important issue is that payload based intrusion detection systems may be too slow for standard processing approaches. Analyzing payloads has advantages over analyzing the standard headers of a packet. However, this approach is more resource intensive. The purpose of this study is to analyze the speed and accuracy performance of a payload based network intrusion detection system using pattern recognition processor with a unigram feature extraction approach. Results of the study are presented and discussed.

关键词： Payloads Feature extraction Program processors Pattern recognition Intrusion detection Machine learning algorithms Training

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System resilience enhancement through modularization for large scale cyber systems

System resilience enhancement through modularization for lar...

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IEEE International Conference on Communications in China Workshops (ICCC)

作者： Manghui Tu Liangliang Xiao Dept. of Computer Information Technology & Graphics Purdue University Northwest Hammond IN USA Dept. of Computer Science and Information Technology Frostburg State University Frostburg MD USA

ISBN: (纸本)9781509021376

It has become increasingly evident that large scale cyber systems can be brittle and may exhibit unpredictable behavior when faced with unexpected disturbances. Even weak and innocuous disturbances can bring down the system inoperative and may introduce catastrophic disasters to the society. The goal of this research is to provide effective mechanisms to enhance the resilience of large scale cyber systems. Process interactions will be modeled and the relationship between interaction and system resilience will be analyzed. The effectiveness of modularization on resilience enhancement will be illustrated. A dynamic programming algorithm based solution will be developed to provide a solution to enhance system resilience through system modularization.

关键词： dynamic programming computer networks Modularity computer network dynamic programming dynamic programming algorithm Fault tolerance Unpredictable behavior Resilience Scale formation Solutions

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