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  • Open Access

    ARTICLE

    Experimental Analyses of Flow Pattern and Heat Transfer in a Horizontally Oriented Polymer Pulsating Heat Pipe with Merged Liquid Slugs

    Zhengyuan Pei1, Yasushi Koito2,*

    Frontiers in Heat and Mass Transfer, Vol.22, No.5, pp. 1381-1397, 2024, DOI:10.32604/fhmt.2024.056624 - 30 October 2024

    Abstract Extended experiments were conducted on the oscillation characteristics of merged liquid slugs in a horizontally oriented polymer pulsating heat pipe (PHP). The PHP’s serpentine channel comprised 14 parallel channels with a width of 1.3 and a height of 1.1 . The evaporator and condenser sections were 25 and 50 long, respectively, and the adiabatic section in between was 75 mm long. Using a plastic 3D printer and semi-transparent filament made from acrylonitrile butadiene styrene, the serpentine channel was printed directly onto a thin polycarbonate sheet to form the PHP. The PHP was charged with hydrofluoroether-7100.… More >

  • Open Access

    ARTICLE

    Deep Learning-Based Action Classification Using One-Shot Object Detection

    Hyun Yoo1, Seo-El Lee2, Kyungyong Chung3,*

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1343-1359, 2023, DOI:10.32604/cmc.2023.039263 - 30 August 2023

    Abstract Deep learning-based action classification technology has been applied to various fields, such as social safety, medical services, and sports. Analyzing an action on a practical level requires tracking multiple human bodies in an image in real-time and simultaneously classifying their actions. There are various related studies on the real-time classification of actions in an image. However, existing deep learning-based action classification models have prolonged response speeds, so there is a limit to real-time analysis. In addition, it has low accuracy of action of each object if multiple objects appear in the image. Also, it needs… More >

  • Open Access

    ARTICLE

    Context Awareness by Noise-Pattern Analysis of a Smart Factory

    So-Yeon Lee1, Jihoon Park1, Dae-Young Kim2,*

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1497-1514, 2023, DOI:10.32604/cmc.2023.034914 - 30 August 2023

    Abstract Recently, to build a smart factory, research has been conducted to perform fault diagnosis and defect detection based on vibration and noise signals generated when a mechanical system is driven using deep-learning technology, a field of artificial intelligence. Most of the related studies apply various audio-feature extraction techniques to one-dimensional raw data to extract sound-specific features and then classify the sound by using the derived spectral image as a training dataset. However, compared to numerical raw data, learning based on image data has the disadvantage that creating a training dataset is very time-consuming. Therefore, we… More >

  • Open Access

    ARTICLE

    A Hybrid Approach for Plant Disease Detection Using E-GAN and CapsNet

    N. Vasudevan*, T. Karthick

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 337-356, 2023, DOI:10.32604/csse.2023.034242 - 20 January 2023

    Abstract Crop protection is a great obstacle to food safety, with crop diseases being one of the most serious issues. Plant diseases diminish the quality of crop yield. To detect disease spots on grape leaves, deep learning technology might be employed. On the other hand, the precision and efficiency of identification remain issues. The quantity of images of ill leaves taken from plants is often uneven. With an uneven collection and few images, spotting disease is hard. The plant leaves dataset needs to be expanded to detect illness accurately. A novel hybrid technique employing segmentation, augmentation,… More >

  • Open Access

    ARTICLE

    Pattern Analysis and Regressive Linear Measure for Botnet Detection

    B. Padmavathi1,2,*, B. Muthukumar3

    Computer Systems Science and Engineering, Vol.43, No.1, pp. 119-139, 2022, DOI:10.32604/csse.2022.021431 - 23 March 2022

    Abstract Capturing the distributed platform with remotely controlled compromised machines using botnet is extensively analyzed by various researchers. However, certain limitations need to be addressed efficiently. The provisioning of detection mechanism with learning approaches provides a better solution more broadly by saluting multi-objective constraints. The bots’ patterns or features over the network have to be analyzed in both linear and non-linear manner. The linear and non-linear features are composed of high-level and low-level features. The collected features are maintained over the Bag of Features (BoF) where the most influencing features are collected and provided into the… More >

  • Open Access

    ARTICLE

    Deriving Driver Behavioral Pattern Analysis and Performance Using Neural Network Approaches

    Meenakshi Malik1, Rainu Nandal1,*, Surjeet Dalal2, Vivek Jalglan3, Dac-Nhuong Le4,5

    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 87-99, 2022, DOI:10.32604/iasc.2022.020249 - 26 October 2021

    Abstract It has been observed that driver behavior has a direct and considerable impact upon factors like fuel consumption, environmentally harmful emissions, and public safety, making it a key consideration of further research in order to monitor and control such related hazards. This has fueled our decision to conduct a study in order to arrive at an efficient way of analyzing the various parameters of driver behavior and find ways and means of positively impacting such behavior. It has been ascertained that such behavioral patterns can significantly impact the analysis of traffic-related conditions and outcomes. In… More >

  • Open Access

    ARTICLE

    A Security Sensitive Function Mining Approach Based on Precondition Pattern Analysis

    Zhongxu Yin1, *, Yiran Song2, Huiqin Chen3, Yan Cao4

    CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 1013-1029, 2020, DOI:10.32604/cmc.2020.09345 - 01 May 2020

    Abstract Security-sensitive functions are the basis for building a taint-style vulnerability model. Current approaches for extracting security-sensitive functions either don’t analyze data flow accurately, or not conducting pattern analyzing of conditions, resulting in higher false positive rate or false negative rate, which increased manual confirmation workload. In this paper, we propose a security sensitive function mining approach based on preconditon pattern analyzing. Firstly, we propose an enhanced system dependency graph analysis algorithm for precisely extracting the conditional statements which check the function parameters and conducting statistical analysis of the conditional statements for selecting candidate security sensitive More >

  • Open Access

    ABSTRACT

    Fringe Pattern Analysis: Some Results and Discussions (III)

    Kemao Qian

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.21, No.1, pp. 4-4, 2019, DOI:10.32604/icces.2019.05557

    Abstract Fringe-based measurement techniques provide an accurate, straightforward and convenient means for optical metrology and experimental mechanics [1]. Consequently, fringe pattern analysis is an important issue. We have reported our works in this conference in 2011 [2] and 2014 [3]. In this paper, our recent developments since 2014 are introduced, as listed below:
    1. Among various fringe patterns, carrier fringe is more convenient to use but more difficult to characterize. We unified several prominent carrier fringe analysis techniques for deeper understanding. The background removal and the influence of high-order harmonics are also studied.
    2. Moving fringe analysis… More >

  • Open Access

    ARTICLE

    Simulations of Blood Drop Spreading and Impact for Bloodstain Pattern Analysis

    Chu Wang, Lucy T. Zhang1

    CMES-Computer Modeling in Engineering & Sciences, Vol.98, No.1, pp. 41-67, 2014, DOI:10.3970/cmes.2014.098.041

    Abstract Bloodstain pattern analysis (BPA) in forensic science is an important tool to solve crime scenes. The complex dynamic behavior of blood drops poses great challenges for accurate fluid dynamic simulations. In this paper, we specifically focus on simulations of blood drop spreading and impact, which may involve contact line hysteresis and spattering of drops as they interact with solid surfaces. Here, we set up a numerical framework that combines (1) the connectivity-free front tracking (CFFT) method for modeling multiphase (air and liquid) flows and (2) a dynamic contact line model for modeling fluid-solid contact line.… More >

  • Open Access

    ABSTRACT

    Fringe pattern analysis: some results and discussions

    Qian Kemao

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.18, No.1, pp. 19-20, 2011, DOI:10.3970/icces.2011.018.019

    Abstract When a fringe pattern is obtained, it needs to be analyzed in order to extract the desired information. In this talk, we are going to introduce some fringe pattern analysis techniques that we proposed recently, such as windowed Fourier transform (WFT) [1], coherence enhancing diffusion (CED) [2], and frequency-guided sequential demodulation (FSD) [3]. Some results, along with discussions, are given for the following cases:
    1. Filtering one fringe pattern
    2. Phase retrieval from one closed fringe pattern
    3. Phase retrieval from one carrier fringe pattern
    4. Phase shift retrieval from two fringe patterns
    5. Phase retrieval from a More >

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