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Relevant bibliographies by topics / Design pattern detection

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Academic literature on the topic 'Design pattern detection'

Author: Grafiati

Published: 9 March 2023

Last updated: 31 July 2025

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Journal articles on the topic "Design pattern detection"

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HAYASHI, S., J. KATADA, R. SAKAMOTO, T. KOBAYASHI, and M. SAEKI. "Design Pattern Detection by Using Meta Patterns." IEICE Transactions on Information and Systems E91-D, no. 4 (2008): 933–44. http://dx.doi.org/10.1093/ietisy/e91-d.4.933.

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Wang, Lei, Tian Song, Hui-Na Song, and Shuai Zhang. "Research on Design Pattern Detection Method Based on UML Model with Extended Image Information and Deep Learning." Applied Sciences 12, no. 17 (2022): 8718. http://dx.doi.org/10.3390/app12178718.

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Detecting relevant design patterns from system design or source code helps software developers and maintainers understand the ideas behind the design of large-scale, highly complicated software systems, thereby improving the quality of software systems. Currently, design pattern detection based on machine learning has become a hot research direction. Scholars have proposed many design pattern detection methods based on machine learning. However, most of the existing literature only reports the utilization of traditional machine learning algorithms such as KNN, decision trees, ANN, SVM, etc., w

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Vijayalakshmi, MM. "A Pattern Mining Approach for Identifying Identical Design Structures in Object Oriented Design Model." International Journal of Trend in Scientific Research and Development 2, no. 1 (2019): 1115–23. https://doi.org/10.31142/ijtsrd7177.

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Object oriented design patterns are frequently used in real world applications. Detection of design patterns is essential for comprehension of the intent and design of a software project. This paper presents a graph mining approach for detecting design patterns. Our approach is based on searching input design patterns in the space of model graph of the source code by isomorphic sub graph search method. We developed a tool called DesPaD to apply our pattern detection approach in an automated way. We successfully detected 23 GoF design patterns in the demo source code of the Applied Java Pattern

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Liu, Cong. "A General Framework to Detect Design Patterns by Combining Static and Dynamic Analysis Techniques." International Journal of Software Engineering and Knowledge Engineering 31, no. 01 (2021): 21–54. http://dx.doi.org/10.1142/s0218194021400027.

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Design pattern detection can provide useful insights to support software comprehension. Accurate and complete detection of pattern instances are extremely important to enable software usability improvements. However, existing design pattern detection approaches and tools suffer from the following problems: incomplete description of design pattern instances, inaccurate behavioral constraint checking, and inability to support novel design patterns. This paper presents a general framework to detect design patterns while solving these issues by combining static and dynamic analysis techniques. The

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Nazar, Najam, Aldeida Aleti, and Yaokun Zheng. "Feature-based software design pattern detection." Journal of Systems and Software 185 (March 2022): 111179. http://dx.doi.org/10.1016/j.jss.2021.111179.

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Tsantalis, Nikolaos, Alexander Chatzigeorgiou, George Stephanides, and Spyros Halkidis. "Design Pattern Detection Using Similarity Scoring." IEEE Transactions on Software Engineering 32, no. 11 (2006): 896–909. http://dx.doi.org/10.1109/tse.2006.112.

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Kouli, Mariam, and Abbas Rasoolzadegan. "A Feature-Based Method for Detecting Design Patterns in Source Code." Symmetry 14, no. 7 (2022): 1491. http://dx.doi.org/10.3390/sym14071491.

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Design patterns are common solutions to existing issues in software engineering. In recent decades, design patterns have been researched intensively because they increase the quality factors of software systems such as flexibility, maintainability, and reusability. Design pattern detection refers to the determination of the symmetry between a code fragment and the definition of a design pattern. One of the major challenges in design pattern detection is how to obtain accurate information about the design patterns used in the software system due to the existence of different design pattern vari

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BOUASSIDA, NADIA, HANENE BEN-ABDALLAH, and IMENE ISSAOUI. "EVALUATION OF AN AUTOMATED MULTI-PHASE APPROACH FOR PATTERNS DISCOVERY." International Journal of Software Engineering and Knowledge Engineering 23, no. 10 (2013): 1367–98. http://dx.doi.org/10.1142/s0218194013500435.

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Design patterns capitalize the knowledge of expert designers and offer reuse that provides for higher design quality and overall faster development. To attain these advantages, a designer must, however, overcome the difficulties in understanding design patterns and determining those appropriate for his/her particular application. On the other hand, one way to benefit from design patterns is to assist inexperienced designers in pattern detection during the design elaboration. Such detection should tolerate variations between the design and the pattern since the exact instantiation of a pattern

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Arcelli Fontana, Francesca, Marco Zanoni, and Stefano Maggioni. "Using Design Pattern Clues to Improve the Precision of Design Pattern Detection Tools." Journal of Object Technology 10 (2011): 4:1. http://dx.doi.org/10.5381/jot.2011.10.1.a4.

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Lee, Se-Yul, and Yong-Soo Kim. "Design and Analysis of Probe Detection Systems for TCP Networks." Journal of Advanced Computational Intelligence and Intelligent Informatics 8, no. 4 (2004): 369–72. http://dx.doi.org/10.20965/jaciii.2004.p0369.

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Advanced computer network technology enables the connectivity of computers in an open network environment. Despite the growing numbers of security threats to networks, most intrusion detection identifies security attacks mainly by detecting misuse using a set of rules based on past hacking patterns. This pattern matching has a high rate of false positives and cannot detect new hacking patterns, making it vulnerable to previously unidentified attack patterns and variations in attack and increasing false negatives. Intrusion detection and prevention technologies are thus required. We propose a n

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Dissertations / Theses on the topic "Design pattern detection"

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SAEKI, Motoshi, Takashi KOBAYASHI, Ryota SAKAMOTO, Junya KATADA, and Shinpei HAYASHI. "Design Pattern Detection by Using Meta Patterns." Institute of Electronics, Information and Communication Engineers, 2008. http://hdl.handle.net/2237/14977.

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Binun, Alexander [Verfasser]. "High Accuracy Design Pattern Detection / Alexander Binun." Bonn : Universitäts- und Landesbibliothek Bonn, 2012. http://d-nb.info/1043911294/34.

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Alshira'H, Mohammad H. "Integrating user knowledge into design pattern detection." Thesis, University of Leicester, 2015. http://hdl.handle.net/2381/36232.

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Design pattern detection is useful for a range of software comprehension and maintenance tasks. Tools that rely on static or dynamic analysis alone can produce inaccurate results, especially for patterns that rely on the run-time information. Some tools provide facilities for the developer to refine the results by adding their own knowledge. Currently, however, the ability of tools to accommodate this knowledge is very limited; it can only pertain to the detected patterns and cannot provide additional knowledge about the source code, or about its behaviour. In this thesis, we propose an approa

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ZANONI, MARCO. "Data mining techniques for design pattern detection." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2012. http://hdl.handle.net/10281/31515.

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The main objective of design pattern detection is to gain better comprehension of a software system, and of the kind of problems addressed during the development of the system itself. Design patterns have informal specifications, leading to many implementation variants caused by the subjective interpretation of the pattern by developers. This thesis applies a supervised classification approach to make the detection more subjective, bringing to developers the patterns they want to find, ranked by a confidence value.

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Hatzipantelis, Eleftherios. "The design and implementation of a statistical pattern recognition system for induction machine condition monitoring." Thesis, University of Aberdeen, 1995. http://digitool.abdn.ac.uk/R?func=search-advanced-go&find_code1=WSN&request1=AAIU086061.

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Automated fault diagnosis in induction machines is a difficult task and normally requires background information of electrical machines. Here a different methodology to the condition monitoring problem is devised. The approach is based entirely on Digital Signal Processing (DSP) and Statistical Pattern Recognition (PR). Description of machine conditions is extracted from empirical data. The main tasks that must be carried out by a PR-based condition monitoring system are: condition identification, knowledge reinforcement and knowledge creation for previously unseen conditions. The DSP operatio

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MAGGIONI, STEFANO. "Design pattern detection and software architecture reconstruction: an integrated approach based on software micro-structures." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2010. http://hdl.handle.net/10281/7817.

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Nikitina, Asya F. "Design and implementation of pattern recognition algorithms for the detection of chemicals with a microcantilever sensor array." abstract and full text PDF (free order & download UNR users only), 2007. http://0-gateway.proquest.com.innopac.library.unr.edu/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:1447605.

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Manhaeve, Hans A. R. "Single pattern detection and identification of of CMOS transistor faults, requirements and methods : design and realisation of the OCIMU Iâ†Dâ†Dâ†Q monitor; single pattern CMOS transistor fault testing." Thesis, University of Hull, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.361497.

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Karvir, Hrishikesh. "Design and Validation of a Sensor Integration and Feature Fusion Test-Bed for Image-Based Pattern Recognition Applications." Wright State University / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=wright1291753291.

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Atojoko, Achimugu A. "Design and Modelling of Passive UHF RFID Tags for Energy Efficient Liquid Level Detection Applications. A study of various techniques in the design, modelling, optimisation and deployment of RFID reader and passive UHF RFID tags to achieve effective performance for liquid sensing applications." Thesis, University of Bradford, 2016. http://hdl.handle.net/10454/15906.

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Sewer and oil pipeline spillage issues have become major causes of pollution in urban and rural areas usually caused by blockages in the water storage and drainage system, and oil spillage of underground oil pipelines. An effective way of avoiding this problem will be by deploying some mechanism to monitor these installations at each point in time and reporting unusual liquid activity to the relevant authorities for prompt action to avoid a flooding or spillage occurrence. This research work presents a low cost energy efficient liquid level monitoring technique using Radio Frequency Identifica

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Books on the topic "Design pattern detection"

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Jean, Jared St. Kinect Hacks: Tips and Tools for Motion and Pattern Detection. O'Reilly Media, Incorporated, 2012.

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Jean, Jared St. Kinect Hacks: Tips and Tools for Motion and Pattern Detection. O'Reilly Media, Incorporated, 2012.

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Darcy, Alison, and Shiri Sadeh-Sharvit. Mobile Device Applications for the Assessment and Treatment of Eating Disorders. Edited by W. Stewart Agras and Athena Robinson. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780190620998.013.27.

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Mobile devices and applications (apps) are increasingly used in clinical practice, offering reconceptualization of and novel avenues to tracking symptoms and delivery of more personalized interventions. This chapter reviews the burgeoning approaches to the integration of mobile in screening and treating individuals with eating disorders. Promising methods of data collection such as ecological momentary assessments enhance the capabilities of detecting symptoms and recognizing patterns—both are fundamental to the screening, evaluation, and monitoring of eating disorders and lay the foundations

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Favre, Diane. Coloring Book for Detective: Beautiful Adults Relaxation Funny Appreciation Gift Idea Coloring Book with Stress Relieving Patterns, Animals Designs, and More. Independently Published, 2020.

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Book chapters on the topic "Design pattern detection"

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Mzid, Rania, Ilyes Rezgui, and Tewfik Ziadi. "Attention-Based Method for Design Pattern Detection." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-70797-1_6.

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Bouassida, Nadia, and Hanêne Ben-Abdallah. "A New Approach for Pattern Problem Detection." In Notes on Numerical Fluid Mechanics and Multidisciplinary Design. Springer International Publishing, 2010. http://dx.doi.org/10.1007/978-3-642-13094-6_13.

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Issaoui, Imène, Nadia Bouassida, and Hanêne Ben-Abdallah. "A Design Pattern Detection Approach Based on Semantics." In Software Engineering Research, Management and Applications 2012. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30460-6_4.

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Lee, Byung-kwan, Seung-hae Yang, Dong-Hyuck Kwon, and Dai-Youn Kim. "PGNIDS(Pattern-Graph Based Network Intrusion Detection System) Design." In Computational Science and Its Applications - ICCSA 2006. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11751595_5.

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Yahia, Samah, Chahira Mahjoub, Ridha Ejbeli, and Mohamed Naceur Abdelkrim. "Epileptic Seizure Detection on EEG Images Using the Decimal Descriptor Pattern." In Intelligent Systems Design and Applications. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-64813-7_23.

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Lu, Tao, Xiaomeng Wang, and Tao Jia. "Design Pattern Representation and Detection Based on Heterogeneous Information Network." In Reuse and Software Quality. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-66459-5_5.

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Arcelli, Francesca, Fabrizio Perin, Claudia Raibulet, and Stefano Ravani. "Design Pattern Detection in Java Systems: A Dynamic Analysis Based Approach." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14819-4_12.

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Nikita, P., and Satyadhyan Chickerur. "Design and Implementation of Edge Detection Algorithms Using FPGA." In Proceedings of the 13th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2021). Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-96302-6_53.

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Neha, N., M. R. Gauthama Raman, Nivethitha Somu, R. Senthilnathan, and V. Shankar Sriram. "An Improved Feedforward Neural Network Using Salp Swarm Optimization Technique for the Design of Intrusion Detection System for Computer Network." In Computational Intelligence in Pattern Recognition. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-9042-5_74.

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Li, Runyu, Zhizhong Zhao, Zhiqiang Wang, Haifeng Wang, Wensheng Zhang, and Bowen Wang. "Design and Output Characteristics of Magnetostrictive Sensor Array for Tire Pattern Detection." In Proceedings of 2021 Chinese Intelligent Automation Conference. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-6372-7_11.

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Conference papers on the topic "Design pattern detection"

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Xiang, Yi. "Intelligent Fabric Pattern Detection and Design Based on Mask R-CNN." In 2024 IEEE 7th International Conference on Information Systems and Computer Aided Education (ICISCAE). IEEE, 2024. https://doi.org/10.1109/iciscae62304.2024.10761177.

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Li, Nan, Nong Zou, Junxiang Zhang, Xiaomeng Wang, and Tao Jia. "A Multi-Feature Fusion Approach for Design Pattern Detection Based on Graph Neural Networks." In 2025 28th International Conference on Computer Supported Cooperative Work in Design (CSCWD). IEEE, 2025. https://doi.org/10.1109/cscwd64889.2025.11033498.

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Gao, Lihua, Yilahun Hankiz, Shuxian Liu, and Hamdulla Askar. "Hardware acceleration design for infrared small target detection based on joint local contrast using FPGA." In International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2025), edited by Haiquan Zhao and Xinhua Tang. SPIE, 2025. https://doi.org/10.1117/12.3070547.

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Lebon, Maurice, and Vassilios Tzerpos. "Fine-Grained Design Pattern Detection." In 2012 IEEE 36th Annual Computer Software and Applications Conference - COMPSAC 2012. IEEE, 2012. http://dx.doi.org/10.1109/compsac.2012.37.

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Dabain, Haneen, Ayesha Manzer, and Vassilios Tzerpos. "Design pattern detection using FINDER." In SAC 2015: Symposium on Applied Computing. ACM, 2015. http://dx.doi.org/10.1145/2695664.2695900.

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Freitas, André Luis Castro de, and Ana Maria de Alencar Price. "Heuristics for Automatic Detection of Design Patterns in Object-Oriented Software." In Anais Estendidos do Simpósio Brasileiro de Engenharia de Software. Sociedade Brasileira de Computação - SBC, 2000. http://dx.doi.org/10.5753/sbes_estendido.2000.24196.

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Design patterns summarize the experience of expert designers. Patterns are not invented, rather they are extracted from existing systems. The extracting process of patterns had involved the observation of a number of systems designs, looking for patterns across those systems. A design pattern is a reusable implementation model or architecture that can be applied to solve a particular recurring class of problem. In general, it is hard to recognize a pattern use in real-world software systems, unless you know what you are looking for and go carefully and methodically searching for a particular p

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Nagy, Akos, and Bence Kovari. "Programming language neutral design pattern detection." In 2015 16th IEEE International Symposium on Computational Intelligence and Informatics (CINTI). IEEE, 2015. http://dx.doi.org/10.1109/cinti.2015.7382925.

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Ren, Wu, and Wenyun Zhao. "An observer design-pattern detection technique." In 2012 IEEE International Conference on Computer Science and Automation Engineering (CSAE). IEEE, 2012. http://dx.doi.org/10.1109/csae.2012.6273011.

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Arcelli, Francesca, Claudia Raibulet, Yann-gael Gueheneuc, Giuliano Antoniol, and Jason Smith. "Design Pattern Detection for Reverse Engineering." In 2006 13th Working Conference on Reverse Engineering. IEEE, 2006. http://dx.doi.org/10.1109/wcre.2006.23.

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Dong, Jing, Yongtao Sun, and Yajing Zhao. "Design pattern detection by template matching." In the 2008 ACM symposium. ACM Press, 2008. http://dx.doi.org/10.1145/1363686.1363864.

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Reports on the topic "Design pattern detection"

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Tao, Yang, Amos Mizrach, Victor Alchanatis, Nachshon Shamir, and Tom Porter. Automated imaging broiler chicksexing for gender-specific and efficient production. United States Department of Agriculture, 2014. http://dx.doi.org/10.32747/2014.7594391.bard.

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Extending the previous two years of research results (Mizarch, et al, 2012, Tao, 2011, 2012), the third year’s efforts in both Maryland and Israel were directed towards the engineering of the system. The activities included the robust chick handling and its conveyor system development, optical system improvement, online dynamic motion imaging of chicks, multi-image sequence optimal feather extraction and detection, and pattern recognition. Mechanical System Engineering The third model of the mechanical chick handling system with high-speed imaging system was built as shown in Fig. 1. This syst

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Christopher, Lauren, Stanley Chien, Yaobin Chen, Mei Qiu, William Reindl, and Liya Koshy. Anomaly Detection in Traffic Patterns Using the INDOT Camera System. Purdue University, 2025. https://doi.org/10.5703/1288284317778.

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The Transportation and Autonomous Systems Institute (TASI) of Purdue University Indianapolis (PUI) and the INDOT Traffic Management Center worked together to develop a system that monitors traffic conditions using INDOT CCTV video feeds. Computer vision-based traffic anomaly detection has been studied for the past 20 years, and a thorough state-of-the-art analysis was produced in a recent survey paper. Although AI has contributed to improving anomaly detection, several major challenges remain, such as tracking errors, illumination, weather, occlusion handling, camera pose, and perspective. In

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Guan, Xin, Richard Lance, and Sheena Feist. Environmental DNA (eDNA) assays for the detection of Ridgway’s Rail (Rallus obsoletus) in the United States. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/48757.

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We designed two novel environmental DNA (eDNA) assays for the detection of Ridgway’s Rail (Rallus obsoletus), and successfully validated each assay using eDNA samples collected from the species’ known distribution within the United States. These assays add to the suite of tools available for the monitoring of this rare and secretive marsh bird, and may help to further elucidate its movement patterns as well as identify important migration corridors. Observed sensitivity of the assays indicates exceptional performance, with limits of detection at ≤ 8 copies of the target eDNA fragment per react

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Kulhandjian, Hovannes. Detecting Driver Drowsiness with Multi-Sensor Data Fusion Combined with Machine Learning. Mineta Transportation Institute, 2021. http://dx.doi.org/10.31979/mti.2021.2015.

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In this research work, we develop a drowsy driver detection system through the application of visual and radar sensors combined with machine learning. The system concept was derived from the desire to achieve a high level of driver safety through the prevention of potentially fatal accidents involving drowsy drivers. According to the National Highway Traffic Safety Administration, drowsy driving resulted in 50,000 injuries across 91,000 police-reported accidents, and a death toll of nearly 800 in 2017. The objective of this research work is to provide a working prototype of Advanced Driver Ass

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Mizrach, Amos, Michal Mazor, Amots Hetzroni, et al. Male Song as a Tool for Trapping Female Medflies. United States Department of Agriculture, 2002. http://dx.doi.org/10.32747/2002.7586535.bard.

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This interdisciplinaray work combines expertise in engineering and entomology in Israel and the US, to develop an acoustic trap for mate-seeking female medflies. Medflies are among the world's most economically harmful pests, and monitoring and control efforts cost about $800 million each year in Israel and the US. Efficient traps are vitally important tools for medfly quarantine and pest management activities; they are needed for early detection, for predicting dispersal patterns and for estimating medfly abundance within infested regions. Early detection facilitates rapid response to invasio

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Gur, Amit, Edward Buckler, Joseph Burger, Yaakov Tadmor, and Iftach Klapp. Characterization of genetic variation and yield heterosis in Cucumis melo. United States Department of Agriculture, 2016. http://dx.doi.org/10.32747/2016.7600047.bard.

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Project objectives: 1) Characterization of variation for yield heterosis in melon using Half-Diallele (HDA) design. 2) Development and implementation of image-based yield phenotyping in melon. 3) Characterization of genetic, epigenetic and transcriptional variation across 25 founder lines and selected hybrids. The epigentic part of this objective was modified during the course of the project: instead of characterization of chromatin structure in a single melon line through genome-wide mapping of nucleosomes using MNase-seq approach, we took advantage of rapid advancements in single-molecule se

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