Relevant bibliographies by topics / Computer software Classification

Academic literature on the topic 'Computer software Classification'

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Published: 10 December 2022
Last updated: 29 January 2023

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Journal articles on the topic "Computer software Classification"

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Pi, Chenchen. "Development and Classification of Computer Software Testing Technology." Journal of Physics: Conference Series 1650 (October 2020): 032111. http://dx.doi.org/10.1088/1742-6596/1650/3/032111.

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Lavrischeva, E. M. "Classification of software engineering disciplines." Cybernetics and Systems Analysis 44, no. 6 (November 2008): 791–96. http://dx.doi.org/10.1007/s10559-008-9053-5.

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Berdonosov, Victor D., and Elena V. Redkolis. "ON CLASSIFICATION OF COMPUTER-AIDED SOFTWARE ENGINEERING SYSTEMS (CASE)." Scholarly Notes of Komsomolsk-na-Amure State Technical University 1, no. 4 (December 30, 2010): 12–25. http://dx.doi.org/10.17084/2010.iv-1(4).2.

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Prieto-Díaz, Rubén. "Implementing faceted classification for software reuse." Communications of the ACM 34, no. 5 (May 1991): 88–97. http://dx.doi.org/10.1145/103167.103176.

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Kozhevnikova, G. P., and A. A. Stognii. "Facet classification of software quality measures." Cybernetics 25, no. 4 (1990): 546–63. http://dx.doi.org/10.1007/bf01070378.

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Yusof, Yuhanis, and Qusai Hussein Ra. "Automation of Software Artifacts Classification." International Journal of Soft Computing 5, no. 3 (March 1, 2010): 109–15. http://dx.doi.org/10.3923/ijscomp.2010.109.115.

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Stutte, Gary W., and Elizabeth C. Stryjewski. "Computer Classification of Roots from Digitized Video Images." HortScience 30, no. 4 (July 1995): 906E—906. http://dx.doi.org/10.21273/hortsci.30.4.906e.

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Manual methods for estimating root length are tedious and time-consuming. Image capture and analysis systems can be used to obtain precise measurements of root length and growth angle. Root activity can also be determined through analysis of the mean pixel intensity of a digitized image. Both commercial (the IBM-compatible ICAS System) and public domain (the Macintosh-based NIH Image) image capture and analysis software have been used to analyze intact root systems. Examples of ICAS classification of hydroponic and soil-grown root systems will be presented. Advantages of the NIH Image software for analysis of micro-gravity experiments aboard the Space Shuttle will be discussed.
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Li, Zhong Kai, Tao Bai, and Le Miao Qiu. "Computer-Aided Material Classification Coding Model and Software System for Mechanical Product." Advanced Materials Research 443-444 (January 2012): 923–28. http://dx.doi.org/10.4028/www.scientific.net/amr.443-444.923.

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For the large numbers of material classification coding rules and components in manufacturing enterprises, a computer-aided material classification coding model is proposed, in order to improve the inputting efficiency of part codes. Based on the analysis of the material classification and coding rule for mechanical product, four types of code segments which suited for computer assisted are put forward. The application and database storage models of the coding rule are built up. Moreover, the paper describes the computational workflow of computer-aided coding and its kernel algorithm to acknowledging the related classified segment. The effectiveness and modularity of the prototype system is illustrated by the implementation in an electronics manufacturing corporation.
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Figueiredo, Marco A., Clay S. Gloster, Mark Stephens, Corey A. Graves, and Mouna Nakkar. "Implementation of Multispectral Image Classification on a Remote Adaptive Computer." VLSI Design 10, no. 3 (January 1, 2000): 307–19. http://dx.doi.org/10.1155/2000/31983.

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As the demand for higher performance computers for the processing of remote sensing science algorithms increases, the need to investigate new computing paradigms is justified. Field Programmable Gate Arrays enable the implementation of algorithms at the hardware gate level, leading to orders of magnitude performance increase over microprocessor based systems. The automatic classification of spaceborne multispectral images is an example of a computation intensive application that can benefit from implementation on an FPGA-based custom computing machine (adaptive or reconfigurable computer). A probabilistic neural network is used here to classify pixels of a multispectral LANDSAT-2 image. The implementation described utilizes Java client/server application programs to access the adaptive computer from a remote site. Results verify that a remote hardware version of the algorithm (implemented on an adaptive computer) is significantly faster than a local software version of the same algorithm (implemented on a typical general-purpose computer).
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Dwivedi, Ashish Kumar, Anand Tirkey, and Santanu Kumar Rath. "Software design pattern mining using classification-based techniques." Frontiers of Computer Science 12, no. 5 (May 19, 2018): 908–22. http://dx.doi.org/10.1007/s11704-017-6424-y.

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Dissertations / Theses on the topic "Computer software Classification"

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Manley, Gary W. "The classification and evaluation of Computer-Aided Software Engineering tools." Thesis, Monterey, California: Naval Postgraduate School, 1990. http://hdl.handle.net/10945/34910.

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Approved for public release; distribution unlimited.
The use of Computer-Aided Software Engineering (CASE) tools has been viewed as a remedy for the software development crisis by achieving improved productivity and system quality via the automation of all or part of the software engineering process. The proliferation and tremendous variety of tools available have stretched the understanding of experienced practitioners and has had a profound impact on the software engineering process itself. To understand what a tool does and compare it to similar tools is a formidable task given the existing diversity of functionality. This thesis investigates what tools are available, proposes a general classification scheme to assist those investigating tools to decide where a tool falls within the software engineering process and identifies a tool's capabilities and limitations. This thesis also provides guidance for the evaluation of a tool and evaluates three commercially available tools.
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Williams, Byron Joseph. "A FRAMEWORK FOR ASSESSING THE IMPACT OF SOFTWARE CHANGES TO SOFTWARE ARCHITECTURE USING CHANGE CLASSIFICATION." MSSTATE, 2006. http://sun.library.msstate.edu/ETD-db/theses/available/etd-04172006-150444/.

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Software developers must produce software that can be changed without the risk of degrading the software architecture. One way to address software changes is to classify their causes and effects. A software change classification mechanism allows engineers to develop a common approach for handling changes. This information can be used to show the potential impact of the change. The goal of this research is to develop a change classification scheme that can be used to address causes of architectural degradation. This scheme can be used to model the effects of changes to software architecture. This research also presents a study of the initial architecture change classification scheme. The results of the study indicated that the classification scheme was easy to use and provided some benefit to developers. In addition, the results provided some evidence that changes of different types (in this classification scheme) required different amounts of effort to implement.
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Mahmood, Qazafi. "LC - an effective classification based association rule mining algorithm." Thesis, University of Huddersfield, 2014. http://eprints.hud.ac.uk/id/eprint/24274/.

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Classification using association rules is a research field in data mining that primarily uses association rule discovery techniques in classification benchmarks. It has been confirmed by many research studies in the literature that classification using association tends to generate more predictive classification systems than traditional classification data mining techniques like probabilistic, statistical and decision tree. In this thesis, we introduce a novel data mining algorithm based on classification using association called “Looking at the Class” (LC), which can be used in for mining a range of classification data sets. Unlike known algorithms in classification using the association approach such as Classification based on Association rule (CBA) system and Classification based on Predictive Association (CPAR) system, which merge disjoint items in the rule learning step without anticipating the class label similarity, the proposed algorithm merges only items with identical class labels. This saves too many unnecessary items combining during the rule learning step, and consequently results in large saving in computational time and memory. Furthermore, the LC algorithm uses a novel prediction procedure that employs multiple rules to make the prediction decision instead of a single rule. The proposed algorithm has been evaluated thoroughly on real world security data sets collected using an automated tool developed at Huddersfield University. The security application which we have considered in this thesis is about categorizing websites based on their features to legitimate or fake which is a typical binary classification problem. Also, experimental results on a number of UCI data sets have been conducted and the measures used for evaluation is the classification accuracy, memory usage, and others. The results show that LC algorithm outperformed traditional classification algorithms such as C4.5, PART and Naïve Bayes as well as known classification based association algorithms like CBA with respect to classification accuracy, memory usage, and execution time on most data sets we consider.
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Lee, Kee Khoon. "Interpretable classification model for automotive material fatigue." Thesis, University of Southampton, 2002. https://eprints.soton.ac.uk/361578/.

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Nguyen, Victor Allen. "A Simplified Faceted Approach To Information Retrieval for Reusable Software Classification." NSUWorks, 1998. http://nsuworks.nova.edu/gscis_etd/749.

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Software Reuse is widely recognized as the most promising technique presently available in reducing the cost of software production. It is the adaptation or incorporation of previously developed software components, designs or other software-related artifacts (i.e. test plans) into new software or software development regimes. Researchers and vendors are doubling their efforts and devoting their time primarily to the topic of software reuse. Most have focused on mechanisms to construct reusable software but few have focused on the problem of discovering components or designs to meet specific needs. In order for software reuse to be successful, it must be perceived to be less costly to discover a software component or related artifact to satisfy a given need than to discover one anew. As results, this study will describe a method to classify software components that meet a specified need. Specifically, the purpose of the present research study is to provide a flexible system, comprised of a classification scheme and searcher system, entitled Guides-Search, in which processes can be retrieved by carrying out a structured dialogue with the user. The classification scheme provides both the structure of questions to be posed to the user, and the set of possible answers to each question. The model is not an attempt to replace current structures; but rather, seeks to provide a conceptual and structural method to support the improvement of software reuse methodology. The investigation focuses on the following goals and objectives for the classification scheme and searcher system: the classification will be flexible and extensible, but usable by the Searcher; the user will not be presented with a large number of questions; the user will never be required to answer a question not known to be germane to the query;
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Graham, Martin. "Visualising multiple overlapping classification hierarchies." Thesis, Edinburgh Napier University, 2001. http://researchrepository.napier.ac.uk/Output/2430.

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The revision or reorganisation of hierarchical data sets can result in many possible hierarchical classifications composed of the same or overlapping data sets existing in parallel with each other. These data sets are difficult for people to handle and conceptualise, as they try to reconcile the different perspectives and structures that such data represents. One area where this situation occurs is the study of botanical taxonomy, essentially the classification and naming of plants. Revisions, new discoveries and new dimensions for classifying plants lead to a proliferation of classifications over the same set of plant data. Taxonomists would like a method of exploring these multiple overlapping hierarchies for interesting information, correlations, or anomalies. The application and extension of Information Visualisation (IV) techniques, the graphical display of abstract information, is put forward as a solution to this problem. Displaying the multiple classification hierarchies in a visually appealing manner along with powerful interaction mechanisms for examination and exploration of the data allows taxonomists to unearth previously hidden information. This visualisation gives detail that previous visualisations and statistical overviews cannot offer. This thesis work has extended previous IV work in several respects to achieve this goal. Compact, yet full and unambiguous, hierarchy visualisations have been developed. Linking and brushing techniques have been extended to work on a higher class of structure, namely overlapping trees and hierarchies. Focus and context techniques have been pushed to achieve new effects across the visually distinct representations of these multiple hierarchies. Other data types, such as multidimensional data and large cluster hierarchies have also been displayed using the final version of the visualisation.
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Henningsson, Kennet. "A Fault Classification Approach to Software Process Improvement." Licentiate thesis, Karlskrona : Blekinge Institute of Technology [Blekinge tekniska högskola], 2005. http://www.bth.se/fou/Forskinfo.nsf/allfirst2/2b9d5998e26ed1b2c12571230047386b?OpenDocument.

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Masood, Khalid. "Histological image analysis and gland modelling for biopsy classification." Thesis, University of Warwick, 2010. http://wrap.warwick.ac.uk/3918/.

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The area of computer-aided diagnosis (CAD) has undergone tremendous growth in recent years. In CAD, the computer output is used as a second opinion for cancer diagnosis. Development of cancer is a multiphase process and mutation of genes is involved over the years. Cancer grows out of normal cells in the body and it usually occurs when growth of the cells in the body is out of control. This phenomenon changes the shape and structure of the tissue glands. In this thesis, we have developed three algorithms for classification of colon and prostate biopsy samples. First, we computed morphological and shape based parameters from hyperspectral images of colon samples and used linear and non-linear classifiers for the identification of cancerous regions. To investigate the importance of hyperspectral imagery in histopathology, we selected a single spectral band from its hyperspectral cube and performed an analysis based on texture of the images. Texture refers to an arrangement of the basic constituents of the material and it is represented by the interrelationships between the spatial arrangements of the image pixels. A novel feature selection method based on the quality of clustering is developed to discard redundant information. In the third algorithm, we used Bayesian inference for segmentation of glands in colon and prostate biopsy samples. In this approach, glands in a tissue are represented by polygonal models with variuos number of vertices depending on the size of glands. An appropriate set of proposals for Metropolis- Hastings-Green algorithm is formulated and a series of Markov chain Monte Carlo (MCMC) simulations are run to extract polygonal models for the glands. We demonstrate the performance of 3D spectral and spatial and 2D spatial analyses with over 90% classification accuracies and less than 10% average segmentation error for the polygonal models.
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Walia, Gursimran Singh. "Empirical Validation of Requirement Error Abstraction and Classification: A Multidisciplinary Approach." MSSTATE, 2006. http://sun.library.msstate.edu/ETD-db/theses/available/etd-05152006-151903/.

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Software quality and reliability is a primary concern for successful development organizations. Over the years, researchers have focused on monitoring and controlling quality throughout the software process by helping developers to detect as many faults as possible using different fault based techniques. This thesis analyzed the software quality problem from a different perspective by taking a step back from faults to abstract the fundamental causes of faults. The first step in this direction is developing a process of abstracting errors from faults throughout the software process. I have described the error abstraction process (EAP) and used it to develop error taxonomy for the requirement stage. This thesis presents the results of a study, which uses techniques based on an error abstraction process and investigates its application to requirement documents. The initial results show promise and provide some useful insights. These results are important for our further investigation.
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Albarrak, Abdulrahman. "Three-dimensional image classification using hierarchical spatial decomposition : a study using retinal data." Thesis, University of Liverpool, 2015. http://livrepository.liverpool.ac.uk/2006419/.

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This thesis describes research conducted in the field of image mining especially volumetric image mining. The study investigates volumetric representation techniques based on hierarchical spatial decomposition to classify three-dimensional (3D) images. The aim of this study was to investigate the effectiveness of using hierarchical spatial decomposition coupled with regional homogeneity in the context of volumetric data representation. The proposed methods involve the following: (i) decomposition, (ii) representation, (iii) single feature vector generation and (iv) classifier generation. In the decomposition step, a given image (volume) is recursively decomposed until either homogeneous regions or a predefined maximum level are reached. For measuring the regional homogeneity, different critical functions are proposed. These critical functions are based on histograms of a given region. Once the image is decomposed, two representation methods are proposed: (i) to represent the decomposition using regions identified in the decomposition (region-based) or (ii) to represent the entire decomposition (whole image-based). The first method is based on individual regions, whereby each decomposed sub-volume (region) is represented in terms of different statistical and histogram-based techniques. Feature vector generation techniques are used to convert the set of feature vectors for each sub-volume into a single feature vector. In the whole image-based representation method, a tree is used to represent each image. Each node in the tree represents a region (sub-volume) using a single value and each edge describes the difference between the node and its parent node. A frequent sub-tree mining technique was adapted to identified a set of frequent sub-graphs. Selected sub-graphs are then used to build a feature vector for each image. In both cases, a standard classifier generator is applied, to the generated feature vectors, to model and predict the class of each image. Evaluation was conducted with respect to retinal optical coherence tomography images in terms of identifying Age-related Macular Degeneration (AMD). Two types of evaluation were used: (i) classification performance evaluation and (ii) statistical significance testing using ANalysis Of VAriance (ANOVA). The evaluation revealed that the proposed methods were effective for classifying 3D retinal images. It is consequently argued that the approaches are generic.
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Books on the topic "Computer software Classification"

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Yang, Xiang, and SpringerLink (Online service), eds. Software Similarity and Classification. London: Springer London, 2012.

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Jain, Anil K. Real-Time Object Measurement and Classification. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988.

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Fedotova, Elena. Computer science. ru: INFRA-M Academic Publishing LLC., 2022. http://dx.doi.org/10.12737/1200564.

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The basic concepts in the field of computer science are given, the main categories of computer hardware and software, the principles of building the architecture of computer systems are described. The structural organization of data and the basics of algorithmization, types of software, classification of information technologies and systems, modern document management and office management automation systems, the basics of building artificial intelligence systems, geoinformation systems, virtual reality systems, as well as the basics of information security are considered. Meets the requirements of the federal state educational standards of higher education of the latest generation. It is intended for students of higher technical educational institutions studying the discipline "Computer Science", for teachers and specialists working in this field, as well as for those who study this subject area independently.
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Paget, François. Vers & virus: Classification, lutte anti-virale et perspectives. Paris: Dunod, 2005.

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Logunova, Oksana, Petr Romanov, and Elena Il'ina. Processing of experimental data on a computer. ru: INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1064882.

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The textbook provides information about the main methods and tools for automating computational processes used in data processing; methods for representing and generating models of experimental data; data models and classification of processing tasks; and the organization of the user interface in automated systems for processing experimental data. Contains structured chapters on the specifics of experimental research. The features of using software for processing experimental data are clearly and logically described. Theoretical material and basic algorithms for processing experimental data used in industrial statistics are presented. Examples of processing experimental data in the field of metallurgy and management in higher education are given. Meets the requirements of the Federal state educational standards of higher education of the latest generation. For students and postgraduates of higher educational institutions.
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Office, General Accounting. Computer security: FAA needs to improve controls over use of foreign nationals to remediate and review software : report to the Chairman, Committee on Science, House of Representatives. Washington, D.C. (P.O. Box 37050, Washington, D.C. 20013): The Office, 1999.

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Office, General Accounting. Computer security: Identification of sensitive systems operated on behalf of ten agencies : congressional requesters. Washington, D.C: The Office, 1989.

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Office, General Accounting. Computer security: FAA is addressing personnel weaknesses, but further action is required : report to the Chairman and Ranking Minority Member, Committee on Science, House of Representatives. Washington, D.C. (P.O. Box 37050, Washington, D.C. 20013): U.S. General Accounting Office, 2000.

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Office, General Accounting. Computer security: Governmentwide planning process had limited impact : report to the chairman, Committee on Science, Space, and Technology, House of Representatives. Washington, D.C: U.S. General Accounting Office, 1990.

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Office, General Accounting. Computer security: Virus highlights need for improved Internet management : report to the chairman, Subcommittee on Telecommunications and Finance, Committee on Energy and Commerce, House of Representatives. Washington, D.C: GAO, 1989.

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Book chapters on the topic "Computer software Classification"

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Ng, Hu, Hau-Lee Tong, Wooi-Haw Tan, and Junaidi Abdullah. "Gait Classification by Support Vector Machine." In Software Engineering and Computer Systems, 623–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22170-5_54.

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Abdullah, Zul Hilmi, Nur Izura Udzir, Ramlan Mahmod, and Khairulmizam Samsudin. "File Integrity Monitor Scheduling Based on File Security Level Classification." In Software Engineering and Computer Systems, 177–89. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22191-0_16.

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Yusoff, Mohd Najwadi, and Aman Jantan. "A Framework for Optimizing Malware Classification by Using Genetic Algorithm." In Software Engineering and Computer Systems, 58–72. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22191-0_5.

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Handaga, Bana, and Mustafa Mat Deris. "Similarity Approach on Fuzzy Soft Set Based Numerical Data Classification." In Software Engineering and Computer Systems, 575–89. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22191-0_50.

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Ramanna, Sheela, Rajen Bhatt, and Piotr Biernot. "A Rough-Hybrid Approach to Software Defect Classification." In Lecture Notes in Computer Science, 79–86. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-72530-5_9.

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Khan, Aurangzeb, Baharum Baharudin, and Khairullah Khan. "Sentiment Classification from Online Customer Reviews Using Lexical Contextual Sentence Structure." In Software Engineering and Computer Systems, 317–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22170-5_28.

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Ren, Peng, Armando Barreto, and Malek Adjouadi. "Multi-step EMG Classification Algorithm for Human-Computer Interaction." In Innovations in Computing Sciences and Software Engineering, 183–88. Dordrecht: Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-90-481-9112-3_31.

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Molinari, Giorgio. "Classification of Software Available and Criteria of Approach." In Industrial Application of Electromagnetic Computer Codes, 81–100. Dordrecht: Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-009-0697-6_4.

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Hamplová, Adéla, David Franc, and Jan Tyrychtr. "Historical Alphabet Transliteration Software Using Computer Vision Classification Approach." In Artificial Intelligence Trends in Systems, 34–45. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-09076-9_4.

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Bozorgi, Mohammadmehdi, Mohd Aizaini Maarof, and Lee Zhi Sam. "Multi-classifier Scheme with Low-Level Visual Feature for Adult Image Classification." In Software Engineering and Computer Systems, 793–802. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22203-0_66.

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Conference papers on the topic "Computer software Classification"

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Alrumaih, Hala, Abdulrahman Mirza, and Hessah Alsalamah. "Toward Automated Software Requirements Classification." In 2018 21st Saudi Computer Society National Computer Conference (NCC). IEEE, 2018. http://dx.doi.org/10.1109/ncg.2018.8593012.

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Ulku, Onur, Necip Gozuacik, Senem Tanberk, Muhammed Ali Aydin, and Abdul Halim Zaim. "Software Log Classification in Telecommunication Industry." In 2021 6th International Conference on Computer Science and Engineering (UBMK). IEEE, 2021. http://dx.doi.org/10.1109/ubmk52708.2021.9558985.

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Mustafa, Khaled M., Rafa E. Al-Qutaish, and Mohammad I. Muhairat. "Classification of Software Testing Tools Based on the Software Testing Methods." In 2009 Second International Conference on Computer and Electrical Engineering. IEEE, 2009. http://dx.doi.org/10.1109/iccee.2009.9.

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Akinin, Aleksandr, Alexey Zubkov, and Nikolay Shilov. "New Developments of the Computer Language Classification Knowledge Portal." In Spring/Summer Young Researchers' Colloquium on Software Engineering. Institute for System Programming of the Russian Academy of Sciences, 2012. http://dx.doi.org/10.15514/syrcose-2012-6-6.

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Bibi, S., G. Tsoumakas, I. Stamelos, and I. Vlahvas. "Software Defect Prediction Using Regression via Classification." In IEEE International Conference on Computer Systems and Applications, 2006. IEEE, 2006. http://dx.doi.org/10.1109/aiccsa.2006.205110.

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Andreou, Andreas, Dimitrios Vogiatzis, and George Papadopoulos. "Intelligent Classification and Retrieval of Software Components." In 30th Annual International Computer Software and Applications Conference (COMPSAC'06). IEEE, 2006. http://dx.doi.org/10.1109/compsac.2006.135.

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Ghoshal, Pritha, C. Jasson Casey, Paul V. Gratz, and Alex Sprintson. "Stochastic Pre-Classification for Software Defined Firewalls." In 2013 22nd International Conference on Computer Communication and Networks (ICCCN 2013). IEEE, 2013. http://dx.doi.org/10.1109/icccn.2013.6614198.

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Manjhi, Devesh, and Amrita Chaturvedi. "Software Component Reusability Classification in Functional Paradigm." In 2019 IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT). IEEE, 2019. http://dx.doi.org/10.1109/icecct.2019.8869123.

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Meslati, D., L. Souici, and S. Ghoul. "Classification of Software and Hardware Bio-inspired Systems." In IEEE International Conference on Computer Systems and Applications, 2006. IEEE, 2006. http://dx.doi.org/10.1109/aiccsa.2006.205213.

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Shetty, A. K. "Role of Classification Societies Towards Advances in Software Development." In International Conference on Computer Applications in Shipbuilding 2013. RINA, 2013. http://dx.doi.org/10.3940/rina.iccas.2013.67.

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Reports on the topic "Computer software Classification"

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Cheng, Peng, James V. Krogmeier, Mark R. Bell, Joshua Li, and Guangwei Yang. Detection and Classification of Concrete Patches by Integrating GPR and Surface Imaging. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317320.

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This research considers the detection, location, and classification of patches in concrete and asphalt-on-concrete pavements using data taken from ground penetrating radar (GPR) and the WayLink 3D Imaging System. In particular, the project seeks to develop a patching table for “inverted-T” patches. A number of deep neural net methods were investigated for patch detection from 3D elevation and image observation, but the success was inconclusive, partly because of a dearth of training data. Later, a method based on thresholding IRI values computed on a 12-foot window was used to localize pavement distress, particularly as seen by patch settling. This method was far more promising. In addition, algorithms were developed for segmentation of the GPR data and for classification of the ambient pavement and the locations and types of patches found in it. The results so far are promising but far from perfect, with a relatively high rate of false alarms. The two project parts were combined to produce a fused patching table. Several hundred miles of data was captured with the Waylink System to compare with a much more limited GPR dataset. The primary dataset was captured on I-74. A software application for MATLAB has been written to aid in automation of patch table creation.
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2

Cheng, Peng, James V. Krogmeier, Mark R. Bell, Joshua Li, and Guangwei Yang. Detection and Classification of Concrete Patches by Integrating GPR and Surface Imaging. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317320.

Full text
Abstract:
This research considers the detection, location, and classification of patches in concrete and asphalt-on-concrete pavements using data taken from ground penetrating radar (GPR) and the WayLink 3D Imaging System. In particular, the project seeks to develop a patching table for “inverted-T” patches. A number of deep neural net methods were investigated for patch detection from 3D elevation and image observation, but the success was inconclusive, partly because of a dearth of training data. Later, a method based on thresholding IRI values computed on a 12-foot window was used to localize pavement distress, particularly as seen by patch settling. This method was far more promising. In addition, algorithms were developed for segmentation of the GPR data and for classification of the ambient pavement and the locations and types of patches found in it. The results so far are promising but far from perfect, with a relatively high rate of false alarms. The two project parts were combined to produce a fused patching table. Several hundred miles of data was captured with the Waylink System to compare with a much more limited GPR dataset. The primary dataset was captured on I-74. A software application for MATLAB has been written to aid in automation of patch table creation.
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3

Chien, Stanley, Lauren Christopher, Yaobin Chen, Mei Qiu, and Wei Lin. Integration of Lane-Specific Traffic Data Generated from Real-Time CCTV Videos into INDOT's Traffic Management System. Purdue University, 2023. http://dx.doi.org/10.5703/1288284317400.

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The Indiana Department of Transportation (INDOT) uses about 600 digital cameras along populated Indiana highways in order to monitor highway traffic conditions. The videos from these cameras are currently observed by human operators looking for traffic conditions and incidents. However, it is time-consuming for the operators to scan through all video data from all the cameras in real-time. The main objective of this research was to develop an automatic and real-time system and implement the system at INDOT to monitor traffic conditions and detect incidents automatically. The Transportation and Autonomous Systems Institute (TASI) of the Purdue School of Engineering and Technology at Indiana University-Purdue University Indianapolis (IUPUI) and the INDOT Traffic Management Center have worked together to research and develop a system that monitors the traffic conditions based on the INDOT CCTV video feeds. The proposed system performs traffic flow estimation, incident detection, and the classification of vehicles involved in an incident. The goal was to develop a system and prepare for future implementation. The research team designed the new system, in­cluding the hardware and software components, the currently existing INDOT CCTV system, the database structure for traffic data extracted from the videos, and a user-friendly web-based server for identifying individual lanes on the highway and showing vehicle flowrates of each lane automatically. The preliminary prototype of some system components was implemented in the 2018–2019 JTRP projects, which provided the feasibility and structure of the automatic traffic status extraction from the video feeds. The 2019–2021 JTRP project focused on developing and improving many features’ functionality and computation speed to make the program run in real-time. The specific work in this 2021–2022 JTRP project is to improve the system further and implement it on INDOT’s premises. The system has the following features: vehicle-detection, road boundary detection, lane detection, vehicle count and flowrate detection, traffic condition detection, database development, web-based graphical user interface (GUI), and a hardware specification study. The research team has installed the system on one computer in INDOT for daily road traffic monitoring operations.
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