Hyun Yoo¹, Seo-El Lee², Kyungyong Chung^3,*

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

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 to be improved since it… More >

So-Yeon Lee¹, Jihoon Park¹, Dae-Young Kim^2,*

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

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 devised a two-step data preprocessing… More >

N. Vasudevan^*, T. Karthick

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

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, and a capsule neural network… More >

B. Padmavathi^1,2,*, B. Muthukumar³

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

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 classifier model. Here, the linearity… More >

Meenakshi Malik¹, Rainu Nandal^1,*, Surjeet Dalal², Vivek Jalglan³, Dac-Nhuong Le^4,5

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

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 such cases, the specific vehicular… More >

Zhongxu Yin^{1, *}, Yiran Song², Huiqin Chen³, Yan Cao⁴

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

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 functions of the target program.… More >

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 sequence of… More >

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 techniques from methodology to… More >

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. Both components are necessary in… More >