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  • Open Access

    ARTICLE

    A Survey of Time Series Data Visualization Methods

    Wangdong Jiang1, Jie Wu1,*, Guang Sun1,2, Yuxin Ouyang3, Jing Li3, Shuang Zhou2

    Journal of Quantum Computing, Vol.2, No.2, pp. 105-117, 2020, DOI:10.32604/jqc.2020.07242 - 19 October 2020

    Abstract In the era of big data, the general public is more likely to access big data, but they wouldn’t like to analyze the data. Therefore, the traditional data visualization with certain professionalism is not easy to be accepted by the general public living in the fast pace. Under this background, a new general visualization method for dynamic time series data emerges as the times require. Time series data visualization organizes abstract and hard-to-understand data into a form that is easily understood by the public. This method integrates data visualization into short videos, which is more More >

  • Open Access

    ARTICLE

    3D Multilayered Turtle Shell Models for Image Steganography

    Ji-Hwei Horng1, Juan Lin2,*, Yanjun Liu3, Chin-Chen Chang3,4,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 879-906, 2020, DOI:10.32604/cmes.2020.09355 - 12 October 2020

    Abstract By embedding secret data into cover images, image steganography can produce non-discriminable stego-images. The turtle shell model for data hiding is an excellent method that uses a reference matrix to make a good balance between image quality and embedding capacity. However, increasing the embedding capacity by extending the area of basic structures of the turtle shell model usually leads to severe degradation of image quality. In this research, we innovatively extend the basic structure of the turtle shell model into a three-dimensional (3D) space. Some intrinsic properties of the original turtle shell model are well More >

  • Open Access

    ARTICLE

    Inverse Construction Methods of Heterogeneous NURBS Object Based on Additive Manufacturing

    Ting Zang1, Dongbin Zhu2,*, Guowang Mu1

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 597-610, 2020, DOI:10.32604/cmes.2020.09965 - 12 October 2020

    Abstract According to the requirement of heterogeneous object modeling in additive manufacturing (AM), the Non-Uniform Rational B-Spline (NURBS) method has been applied to the digital representation of heterogeneous object in this paper. By putting forward the NURBS material data structure and establishing heterogeneous NURBS object model, the accurate mathematical unified representation of analytical and free heterogeneous objects have been realized. With the inverse modeling of heterogeneous NURBS objects, the geometry and material distribution can be better designed to meet the actual needs. Radical Basis Function (RBF) method based on global surface reconstruction and the tensor product More >

  • Open Access

    ARTICLE

    A Bayesian Updating Method for Non-Probabilistic Reliability Assessment of Structures with Performance Test Data

    Jiaqi He1, Yangjun Luo1,2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 777-800, 2020, DOI:10.32604/cmes.2020.010688 - 12 October 2020

    Abstract For structures that only the predicted bounds of uncertainties are available, this study proposes a Bayesian method to logically evaluate the nonprobabilistic reliability of structures based on multi-ellipsoid convex model and performance test data. According to the given interval ranges of uncertainties, we determine the initial characteristic parameters of a multi-ellipsoid convex set. Moreover, to update the plausibility of characteristic parameters, a Bayesian network for the information fusion of prior uncertainty knowledge and subsequent performance test data is constructed. Then, an updated multi-ellipsoid set with the maximum likelihood of the performance test data can be More >

  • Open Access

    ARTICLE

    An Effective Non-Commutative Encryption Approach with Optimized Genetic Algorithm for Ensuring Data Protection in Cloud Computing

    S. Jerald Nirmal Kumar1,*, S. Ravimaran2, M. M. Gowthul Alam3

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 671-697, 2020, DOI:10.32604/cmes.2020.09361 - 12 October 2020

    Abstract Nowadays, succeeding safe communication and protection-sensitive data from unauthorized access above public networks are the main worries in cloud servers. Hence, to secure both data and keys ensuring secured data storage and access, our proposed work designs a Novel Quantum Key Distribution (QKD) relying upon a non-commutative encryption framework. It makes use of a Novel Quantum Key Distribution approach, which guarantees high level secured data transmission. Along with this, a shared secret is generated using Diffie Hellman (DH) to certify secured key generation at reduced time complexity. Moreover, a non-commutative approach is used, which effectively More >

  • Open Access

    ARTICLE

    The Data Classification Query Optimization Method for English Online Examination System Based on Grid Image Analysis

    Kun Liu*

    Intelligent Automation & Soft Computing, Vol.26, No.4, pp. 749-754, 2020, DOI:10.32604/iasc.2020.010109

    Abstract In the English network examination system, the big data distribution is highly coupled, the cost of data query is large, and the precision is not good. In order to improve the ability of the data classification and query in the English network examination system, a method of data classification and query in the English network examination system is proposed based on the grid region clustering and frequent itemset feature extraction of the association rules. Using the grid image analysis to improve the statistical analysis of the English performance analysis, the collection and storage structure analysis… More >

  • Open Access

    ARTICLE

    The Genetic Algorithm and Binary Search Technique in the Program Path Coverage for Improving Software Testing Using Big Data

    Aysh Alhroob1,*, Wael Alzyadat2, Ayad Tareq Imam1, Ghaith M. Jaradat3

    Intelligent Automation & Soft Computing, Vol.26, No.4, pp. 725-733, 2020, DOI:10.32604/iasc.2020.010106

    Abstract Software program testing is the procedure of exercising a software component with a selected set of test cases as a way to discover defects and assess quality. Using software testing automation, especially the generating of testing data increases the effectiveness and efficiency of software testing as a whole. Instead of creating testing data from scratch, Big Data (BD) offers an important source of testing data. Although it is a good source, there is a need to select a proper set of testing data for the sake of selecting an optimal sub-domain input values from the… More >

  • Open Access

    ARTICLE

    Object Detection and Fuzzy-Based Classification Using UAV Data

    Abdul Qayyum1,*, Iftikhar Ahmad2, Mohsin Iftikhar3, Moona Mazher4

    Intelligent Automation & Soft Computing, Vol.26, No.4, pp. 693-702, 2020, DOI:10.32604/iasc.2020.010103

    Abstract UAV (Unmanned Aerial Vehicle) equipped with remote sensing devices can acquire spatial data with a relevant area of interest. In this paper, we have acquired UAV data for high voltage power poles, urban areas and vegetation/trees near power lines. For object classification, the proposed approach based on the fuzzy classifier is compared with the traditional minimum distance classifier and maximum likelihood classifier on our three defined segments of UAV images. The performance evaluation of all the classifiers was based on the statistics parameters which included the mean, standard deviation and PDF (probability density function) of More >

  • Open Access

    ARTICLE

    Topp-Leone Odd Fréchet Generated Family of Distributions with Applications to COVID-19 Data Sets

    Sanaa Al-Marzouki1, Farrukh Jamal2, Christophe Chesneau3,*, Mohammed Elgarhy4

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 437-458, 2020, DOI:10.32604/cmes.2020.011521 - 18 September 2020

    Abstract Recent studies have pointed out the potential of the odd Fréchet family (or class) of continuous distributions in fitting data of all kinds. In this article, we propose an extension of this family through the so-called “Topp-Leone strategy”, aiming to improve its overall flexibility by adding a shape parameter. The main objective is to offer original distributions with modifiable properties, from which adaptive and pliant statistical models can be derived. For the new family, these aspects are illustrated by the means of comprehensive mathematical and numerical results. In particular, we emphasize a special distribution with More >

  • Open Access

    REVIEW

    Importance of Features Selection, Attributes Selection, Challenges and Future Directions for Medical Imaging Data: A Review

    Nazish Naheed1, Muhammad Shaheen1, Sajid Ali Khan1, Mohammed Alawairdhi2,*, Muhammad Attique Khan3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 315-344, 2020, DOI:10.32604/cmes.2020.011380 - 18 September 2020

    Abstract In the area of pattern recognition and machine learning, features play a key role in prediction. The famous applications of features are medical imaging, image classification, and name a few more. With the exponential growth of information investments in medical data repositories and health service provision, medical institutions are collecting large volumes of data. These data repositories contain details information essential to support medical diagnostic decisions and also improve patient care quality. On the other hand, this growth also made it difficult to comprehend and utilize data for various purposes. The results of imaging data… More >

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