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Journal articles on the topic 'Design pattern detection'

Author: Grafiati

Published: 9 March 2023

Last updated: 31 July 2025

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1

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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11

Al-Obeidallah, Mohammed Ghazi, Miltos Petridis, and Stelios Kapetanakis. "A Multiple Phases Approach for Design Patterns Recovery Based on Structural and Method Signature Features." International Journal of Software Innovation 6, no. 3 (2018): 36–52. http://dx.doi.org/10.4018/ijsi.2018070103.

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Design patterns describe both structure, behavior of classes and their relationships. They can improve software documentation, speed up the development process and enable large-scale reuse of software architectures. This article presents a multiple levels detection approach (MLDA) to recover design pattern instances from Java source code. MLDA is able to recover design pattern instances based on a generated class level representation of a subject system. Specifically, MLDA presents what is the so-called Structural Search Model (SSM) which incrementally builds the structure of each design patte

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12

Pettersson, Niklas, Welf Löwe, and Joakim Nivre. "Evaluation of Accuracy in Design Pattern Occurrence Detection." IEEE Transactions on Software Engineering 36, no. 4 (2010): 575–90. http://dx.doi.org/10.1109/tse.2009.92.

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Bafandeh Mayvan, Bahareh, and Abbas Rasoolzadegan. "Design pattern detection based on the graph theory." Knowledge-Based Systems 120 (March 2017): 211–25. http://dx.doi.org/10.1016/j.knosys.2017.01.007.

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Sidhi, Thomas Adi Purnomo, B. Yudi Dwiandiyanta, and Findra Kartika Sari Dewi. "Batik Motifs Detection Using Pattern Recognition Method." Jurnal Buana Informatika 11, no. 1 (2020): 55. http://dx.doi.org/10.24002/jbi.v11i1.3234.

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Abstract. Batik motif is one of the factors that makes batik unique and attractive. There are various kinds of batik motif designs in various areas. Each of these design motifs implies symbols/illustrations that contain certain meanings.The design of the batik motif is used in different events according to the occasions. But unfortunately, not many people understand this, even though local wisdom on the design of batik motifs is one form of cultural heritage of the archipelago that must be preserved. Related to this, development of information technology and multimedia should be used as a solu

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Rupali, Baliram Navalkar, and Rajeshri R. Shelke Prof. "Design Pattern Classifiers under Attack for Security Evaluation using Multimodal System." International Journal of Trend in Scientific Research and Development 1, no. 4 (2017): 260–65. https://doi.org/10.31142/ijtsrd97.

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Pattern classification is a branch of machine learning that focuses on recognition of patterns and regularities in data. This Pattern classification system are commonly used in adversarial applications, like biometric authentication, network intrusion detection, and spam filtering, in which data can be purposely manipulated by humans to undermine their operation. As this adversarial scenario is not taken into account by classical design methods, pattern classification systems may exhibit vulnerabilities, whose exploitation may severely affect their performance, and consequently limit their pra

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Chaturvedi, A. "Present Approaches for Detection of Design Pattern A Survey." International Journal of Computer Sciences and Engineering 6, no. 8 (2018): 948–58. http://dx.doi.org/10.26438/ijcse/v6i8.948958.

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Zanoni, Marco, Francesca Arcelli Fontana, and Fabio Stella. "On applying machine learning techniques for design pattern detection." Journal of Systems and Software 103 (May 2015): 102–17. http://dx.doi.org/10.1016/j.jss.2015.01.037.

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18

YIN, HONGHUAN, HONGBIN YU, JUNQIANG PENG, and HONGYU SHAO. "Design of the detecting platform for the electronic control rotary dobby." Industria Textila 72, no. 03 (2021): 261–67. http://dx.doi.org/10.35530/it.072.03.1751.

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In order to meet the factory detection requirements of the rotary electronic dobby, a new design of the detecting platformfor the rotary electronic dobby was proposed in the present study. It was composed with three main modules to meetthe different levels of detecting process all over the factory, including the embedded control system, human machineinterface system and the information management system. For the information management system of the dobbyworkshop, the proposed platform performed the remote management, results monitor, and data analysis to the dobbymanufactured at the factory. F

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19

Tokunaga, Yusuke, Toshihide Hakukawa, and Takahiro Inoue. "Algorithm and Design of an Intelligent Digital Integrated Circuit for a Watermelon Harvesting Robot." Journal of Robotics and Mechatronics 11, no. 3 (1999): 173–82. http://dx.doi.org/10.20965/jrm.1999.p0173.

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We propose an algorithm and design of an intelligent digital integrated circuit for recognition of circular patterns in a binary image based on template matching using a modified matching degree. The proposed system consists of a preprocessor #1 (noise reduction, coarsening, and edge detection), a preprocessor #2 (noise filtering and location parameter detection), and a circular pattern recognition block. The proposed system is implementable onto field programmable gate arrays (FPGAs) and forming part of the vision system for a watermelon harvesting robot. Functional verification, logic synthe

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20

Sun, Ying, Zishu He, and Jun Li. "Cognitive Space-Time Transmit Pattern Design." International Journal of Antennas and Propagation 2014 (2014): 1–6. http://dx.doi.org/10.1155/2014/141568.

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This paper provides a cognitive space-time (angle-Doppler) transmit pattern design method for mitigating clutter effect. This pattern takes full advantage of degrees-of-freedom (DOF) on transmit, which can preserve the maximum response for the target of interest while prenulling the mainlobe clutter on transmit, potentially simplifying processing on receiver and reducing the requirement for receiver dynamic range. The output signal-to-clutter-and-noise ratio (SCNR) can be improved significantly after applying the cognitive space-time transmit pattern to airborne-phased array radar. In addition

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21

Almadi, Sara H. S., Danial Hooshyar, and Rodina Binti Ahmad. "Bad Smells of Gang of Four Design Patterns: A Decade Systematic Literature Review." Sustainability 13, no. 18 (2021): 10256. http://dx.doi.org/10.3390/su131810256.

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Gang of Four (GoF) design patterns are widely approved solutions for recurring software design problems, and their benefits to software quality are extensively studied. However, the occurrence of bad smells in design patterns increases the crisis of degenerating design patterns’ structure and behavior. Their occurrences are detrimental to the benefits of design patterns and they influence software sustainability by increasing maintenance costs and energy consumption. Despite the destructive roles of bad smells in such designs, there are an absence of studies systematically reviewing bad smells

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22

Aladib, Loay, and Sai Peck Lee. "Pattern detection and design rationale traceability: an integrated approach to software design quality." IET Software 13, no. 4 (2019): 249–59. http://dx.doi.org/10.1049/iet-sen.2017.5017.

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23

Arcelli Fontana, Francesca, and Marco Zanoni. "A tool for design pattern detection and software architecture reconstruction." Information Sciences 181, no. 7 (2011): 1306–24. http://dx.doi.org/10.1016/j.ins.2010.12.002.

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24

Yarahmadi, Hadis, and Seyed Mohammad Hossein Hasheminejad. "Design pattern detection approaches: a systematic review of the literature." Artificial Intelligence Review 53, no. 8 (2020): 5789–846. http://dx.doi.org/10.1007/s10462-020-09834-5.

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25

Issaoui, Imène, Nadia Bouassida, and Hanêne Ben-Abdallah. "Using metric-based filtering to improve design pattern detection approaches." Innovations in Systems and Software Engineering 11, no. 1 (2014): 39–53. http://dx.doi.org/10.1007/s11334-014-0241-3.

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26

Bernardi, Mario Luca, Marta Cimitile, and Giuseppe Di Lucca. "Design pattern detection using a DSL-driven graph matching approach." Journal of Software: Evolution and Process 26, no. 12 (2014): 1233–66. http://dx.doi.org/10.1002/smr.1674.

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27

WANG, LUSHENG, and LIANG DONG. "RANDOMIZED ALGORITHMS FOR MOTIF DETECTION." Journal of Bioinformatics and Computational Biology 03, no. 05 (2005): 1039–52. http://dx.doi.org/10.1142/s0219720005001508.

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Motivation: Motif detection for DNA sequences has many important applications in biological studies, e.g. locating binding sites regulatory signals, designing genetic probes etc. In this paper, we propose a randomized algorithm, design an improved EM algorithm and combine them to form a software tool. Results: (1) We design a randomized algorithm for consensus pattern problem. We can show that with high probability, our randomized algorithm finds a pattern in polynomial time with cost error at most ∊ × l for each string, where l is the length of the motif and ∊ can be any positive number given

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28

Waili, Abdul Rasul AL. "Design System Using Matlab to Recognize Patterns as Face Detection." April-May 2023, no. 33 (May 24, 2023): 9–21. http://dx.doi.org/10.55529/jipirs.33.9.21.

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This paper presents the design and implementation of a face detection system using MATLAB. The system utilizes various techniques, including preprocessing, feature extraction, and pattern recognition algorithms, to accurately detect faces in images. The methodology section provides a detailed explanation of the system's workflow, highlighting the preprocessing techniques for enhancing image quality, the feature extraction methods for capturing discriminative facial characteristics, and the utilization of SVM-based algorithms for pattern recognition. The system's performance is evaluated using

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29

Guo, Junbo, Jintao Li, Yongdong Zhang, Dongming Zhang, and Xiao Wu. "Video Copy Detection Based on Trajectory Behavior Pattern." Journal of Computer-Aided Design & Computer Graphics 22, no. 6 (2010): 943–48. http://dx.doi.org/10.3724/sp.j.1089.2010.10842.

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30

Ravichandran, S., and M. Umamaheswari. "Design and Development of Humiliating of C-Worm Utilizing an Arbitrary Visualizing." Asian Journal of Computer Science and Technology 5, no. 1 (2016): 1–5. http://dx.doi.org/10.51983/ajcst-2016.5.1.1766.

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A worm is a malicious self-replicating programs, it is intended to feast via computer links. The computer worms are one method of malware beside with Trojans and Viruses. The active worms impersonate main refuge threats to that an Internet. This is the ability of active worms to continuously propagate in the computers on the Internet as an automated fashion. The Active worms changes through their circulation, and thus, pose large tasks to preserve alongside them. This manuscript, to explore an original class of active worms, denoted to as Camouflaging Worm (Abbreviated to as C-Worm) respective

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31

Ahmed, Sajjad, Ariffuddin Joret, Norshidah Katiran, Muhammad Faiz Liew Abdullah, Zahriladha Zakaria, and Muhammad Suhaimi Sulong. "Ultra-wide band antipodal Vivaldi antenna design using target detection algorithm for detection application." Bulletin of Electrical Engineering and Informatics 12, no. 4 (2023): 2165–72. http://dx.doi.org/10.11591/beei.v12i4.5081.

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This work presents a technique for detecting targets between two walls using ultra-wide band (UWB) modified antipodal Vivaldi antenna (MAVA). The detection system works on principle of time domain reflectrometry (TDR) using through wall imaging (TWI). This technique utilized a vector network analyzer (VNA) to produced short and small pluses to irradiate through an antenna array system onto the wall under study. The purposed detection system operated in UWB frequency spectrum (3.1 GHz to 10.6 GHz). Furthermore, an algorithm for hidden target detection has been developed. The results of the simu

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Ahmed, Sajjad, Ariffuddin Joret, Norshidah Katiran, Muhammad Faiz Liew Abdullah, Zahriladha Zakaria, and Muhammad Suhaimi Sulong. "Ultra-wide band antipodal Vivaldi antenna design using target detection algorithm for detection application." Bulletin of Electrical Engineering and Informatics 12, no. 4 (2023): 2165–72. http://dx.doi.org/10.11591/eei.v12i4.5081.

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This work presents a technique for detecting targets between two walls using ultra-wide band (UWB) modified antipodal Vivaldi antenna (MAVA). The detection system works on principle of time domain reflectrometry (TDR) using through wall imaging (TWI). This technique utilized a vector network analyzer (VNA) to produced short and small pluses to irradiate through an antenna array system onto the wall under study. The purposed detection system operated in UWB frequency spectrum (3.1 GHz to 10.6 GHz). Furthermore, an algorithm for hidden target detection has been developed. The results of the simu

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33

Bonello, D. K., Y. Iano, and U. B. Neto. "An Algorithm for the Detection of Circular Elements in Engineering Design." Journal of Engineering Sciences 7, no. 1 (2020): E6—E9. http://dx.doi.org/10.21272/jes.2020.7(1).e2.

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Various concentrated works have been done in the area of computational vision regarding the circle and texture detections. Detection of circles in images can be beneficial for PCB components industries for the detection of capacitors in printed circuit boards, also for medicine in the detection of red cells, white blood cells, and leukocytes, and for applications which requires precision and assignments regarding the detection of circles in a digital image. In this work is utilized a benchmarking of images to detection circle boards of different radio values for the comparison with the work [1

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34

Chihada, Abdullah, Saeed Jalili, Seyed Mohammad Hossein Hasheminejad, and Mohammad Hossein Zangooei. "Source code and design conformance, design pattern detection from source code by classification approach." Applied Soft Computing 26 (January 2015): 357–67. http://dx.doi.org/10.1016/j.asoc.2014.10.027.

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35

Xiang, Zhong, Yujia Shen, Zhitao Cheng, Miao Ma, and Feng Lin. "Periodic Pattern Detection of Printed Fabric Based on Deep Learning Algorithm." Journal of Physics: Conference Series 2148, no. 1 (2022): 012013. http://dx.doi.org/10.1088/1742-6596/2148/1/012013.

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Abstract Printed fabric patterns contain multiple repeat pattern primitives, which have a significant impact on fabric pattern design in the textile industry. The pattern primitive is often composed of multiple elements, such as color, form, and texture structure. Therefore, the more pattern elements it contains, the more complex the primitive is. In order to segment fabric primitives, this paper proposes a novel convolutional neural network (CNN) method with spatial pyramid pooling module as a feature extractor, which enables to learn the pattern feature information and determine whether the

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Gan, Yuanying, Chuntong Liu, Zhenxin He, Hongcai Li, and Zhongye Liu. "Digital Camouflage Pattern Design Based on the Biased Random Walk." Modelling and Simulation in Engineering 2022 (June 16, 2022): 1–12. http://dx.doi.org/10.1155/2022/2986346.

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Digital camouflage is a common countermeasure against military reconnaissance. In the face of high-tech imaging reconnaissance, battlefield detection means tend to be automated and refined. In order to adapt to the concealment requirements under various environmental backgrounds, combined with the camouflage performance of digital camouflage and its feedback mechanism in camouflage pattern design, this paper proposed a digital camouflage pattern design method based on biased random walk. Firstly, the original background is preprocessed, and the background texture’s direction, corner, step leng

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37

LIU, JINZHU, and LEQUAN MIN. "ROBUST DESIGNS FOR GRAY-SCALE GLOBAL CONNECTIVITY DETECTION CNN TEMPLATES." International Journal of Bifurcation and Chaos 17, no. 08 (2007): 2827–38. http://dx.doi.org/10.1142/s0218127407018816.

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The cellular neural/nonlinear network (CNN) is a powerful tool for image and video signal processing, as well as robotic and biological visions. Practically, an engineer always hopes to design a CNN that has both universality and robustness. Based on research on the designs for the global connectivity detection (GCD) CNN [Chua, 1997] used in binary pattern, this paper establishes a theorem on robust designs for gray-scale global connectivity detection (GGCD) CNN templates. The theorem provides template parameter inequalities for determining parameter intervals for implementing the GCD function

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38

Omprakash Hajari, Kamal, Ujwalla Haridas Gawande, and Yogesh Golhar. "Motion Pattern Based Anomalous Pedestrian Activity Detection." International Journal of Image, Graphics and Signal Processing 14, no. 6 (2022): 15–25. http://dx.doi.org/10.5815/ijigsp.2022.06.02.

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Augusto, Gonçalo, Rui Duarte, Carlos Cunha, and Ana Matos. "Pattern Recognition in Older Adults’ Activities of Daily Living." Future Internet 16, no. 12 (2024): 476. https://doi.org/10.3390/fi16120476.

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Monitoring daily activities and behaviors is essential for improving quality of life in elderly care, where early detection of behavioral anomalies can lead to timely interventions and enhanced well-being. However, monitoring systems often struggle with scalability, high rates of false positives and negatives, and lack of interpretability in understanding anomalies within collected data. Addressing these limitations requires an adaptable, accurate solution to detect patterns and reliably identify outliers in elderly behavior data. This work aims to design a scalable monitoring system that iden

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40

Nie, Liming, Yangyang Zhao, Chenglin Li, Xuqiong Luo, and Yang Liu. "Shadows in the Interface: A Comprehensive Study on Dark Patterns." Proceedings of the ACM on Software Engineering 1, FSE (2024): 204–25. http://dx.doi.org/10.1145/3643736.

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As digital interfaces become increasingly prevalent, a series of ethical issues have surfaced, with dark patterns emerging as a key research focus. These manipulative design strategies are widely employed in User Interfaces (UI) with the primary aim of steering user behavior in favor of service providers, often at the expense of the users themselves. This paper aims to address three main challenges in the study of dark patterns: inconsistencies and incompleteness in classification, limitations of detection tools, and inadequacies in data comprehensiveness. In this paper, we introduce a compreh

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V. Purushothama Raju. "Supervised Learning Models for Enhancing Financial Fraud Detection Systems." Journal of Information Systems Engineering and Management 10, no. 17s (2025): 644–52. https://doi.org/10.52783/jisem.v10i17s.2786.

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Companies require complex machine learning methods to detect financial fraud effectively because prejudice detection demands accurate identification of illegal activities. The proposed model merges three components including LSTM networks with transaction-based features alongside autoencoders for advanced financial fraud detection in transaction processing. LSTM networks enable the approach to achieve both pattern analysis and detection of irregular patterns in transaction sequences. The abnormal transaction detection task of Autoencoders involves learning regular patterns in transactions whil

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42

Ordin, Mikhail, Leona Polyanskaya, David Maximiliano Gómez, and Arthur G. Samuel. "The Role of Native Language and the Fundamental Design of the Auditory System in Detecting Rhythm Changes." Journal of Speech, Language, and Hearing Research 62, no. 4 (2019): 835–52. http://dx.doi.org/10.1044/2018_jslhr-s-18-0299.

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Purpose We investigated whether rhythm discrimination is mainly driven by the native language of the listener or by the fundamental design of the human auditory system and universal cognitive mechanisms shared by all people irrespective of rhythmic patterns in their native language. Method In multiple experiments, we asked participants to listen to 2 continuous acoustic sequences and to determine whether their rhythms were the same or different (AX discrimination). Participants were native speakers of 4 languages with different rhythmic properties (Spanish, French, English, and German) to unde

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Gu, Xiaohong, and Shuyuan Shang. "Pattern segmentation based on PoolNet and boundary connectivity." SHS Web of Conferences 166 (2023): 01069. http://dx.doi.org/10.1051/shsconf/202316601069.

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Traditional image segmentation algorithms need to design features manually. Therefore, based on the advantage of PoolNet in object detection, this paper proposes a clothing pattern segmentation algorithm combining PoolNet detection and boundary connectivity. This algorithm has more fine edges than traditional segmentation. Especially in the case of similar background before and after, we can get more complete pattern elements, and have better results in segmentation accuracy.

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Wang, Jianming, and Jing Chen. "Design and Research of Dynamic Evolution System in Football Tactics Under Computational Intelligence." Mathematical Problems in Engineering 2022 (May 11, 2022): 1–12. http://dx.doi.org/10.1155/2022/3772236.

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With the rapid development of computer vision, it has been widely used in football. Aiming at the problems of incomplete collection of information, poor operability of system, and bad practical application in the field of football match, an analysis system of football tactics is designed in this paper. Combining the requirements of functions and performance, the analysis system is divided into management of basic information, collection of tactical information, detection of passing pattern, inquiry of tactical information, and visual display, which puts forward the method of the detection of p

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Wu, Qinghong, and Minghui Zhu. "Application of Image Processing Sensor and Pattern Recognition in Detection of Bearing Surface Defects." Journal of Sensors 2022 (July 1, 2022): 1–7. http://dx.doi.org/10.1155/2022/7924982.

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In order to solve the problem that the traditional detection technology can not meet the requirements of online detection, a visual detection device for bearing inner ring defects based on image processing and pattern recognition is proposed in this paper. The device systematically designs an image acquisition device of bearing inner ring based on CCD. In the hardware scheme, the appropriate lens, camera, light source, and other related hardware are selected according to the actual needs, a complete image acquisition platform of bearing inner ring is built, and the software function design is

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Chavat, Juan, Sergio Nesmachnow, Andrei Tchernykh, and Vladimir Shepelev. "Active Safety System for Urban Environments with Detecting Harmful Pedestrian Movement Patterns Using Computational Intelligence." Applied Sciences 10, no. 24 (2020): 9021. http://dx.doi.org/10.3390/app10249021.

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This article presents a system for detecting pedestrian movement patterns in urban environments, by applying computational intelligence methods for image processing and pattern detection. The proposed system is capable of processing multiple images and video sources in real-time. Furthermore, it has a flexible design, as it is based on a pipes and filters architecture that makes it easy to evaluate different computational intelligence techniques to address the subproblems involved in each stage of the process. Two main stages are implemented in the proposed system: the first stage is in charge

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Li, Xiaotong, Anthony Gachagan, and Paul Murray. "Design of 2D Sparse Array Transducers for Anomaly Detection in Medical Phantoms." Sensors 20, no. 18 (2020): 5370. http://dx.doi.org/10.3390/s20185370.

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Aperiodic sparse 2D ultrasonic array configurations, including random array, log spiral array, and sunflower array, have been considered for their potential as conformable transducers able to image within a focal range of 30–80 mm, at an operating frequency of 2 MHz. Optimisation of the imaging performance of potential array patterns has been undertaken based on their simulated far field directivity functions. Two evaluation criteria, peak sidelobe level (PSL) and integrated sidelobe ratio (ISLR), are used to access the performance of each array configuration. Subsequently, a log spiral array

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Barbudo, Rafael, Aurora Ramírez, Francisco Servant, and José Raúl Romero. "GEML: A grammar-based evolutionary machine learning approach for design-pattern detection." Journal of Systems and Software 175 (May 2021): 110919. http://dx.doi.org/10.1016/j.jss.2021.110919.

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Liu, Lilong, Xuelin Yang, and Weisheng Hu. "Experimental evaluation of pilot pattern design in direct-detection optical OFDM transmission." Optics Communications 294 (May 2013): 83–87. http://dx.doi.org/10.1016/j.optcom.2012.12.014.

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Jumba Gin, AYUBA, SANUSI Mohammed, and JIMOH Abdurrahman Annivbassa. "Robust Design and Implementation of a Network IntrusionDetection System." International Journal of Scientific and Academic Research 03, no. 12 (2023): 01–07. http://dx.doi.org/10.54756/ijsar.2023.v3.12.1.

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A Network Intrusion Detection System (NIDS) is an essential component of network security that helps to identify and responds to potential security branches and attacks within a network infrastructure. Computer security has become a challenge and various tools and mechanisms have been developed in order to guarantee a safety level up to the requirements of modern life. Information security is of great concern these days due to the activities of hackers and malicious users on the Internet. Securing informationhas become a critical issue and is of growing concern as computer systems worldwide be

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