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  • Open Access

    ARTICLE

    An Uncertainty Analysis and Reliability-Based Multidisciplinary Design Optimization Method Using Fourth-Moment Saddlepoint Approximation

    Yongqiang Guo1,2,*, Zhiyuan Lv3

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 1855-1870, 2023, DOI:10.32604/cmes.2022.022211 - 20 September 2022

    Abstract In uncertainty analysis and reliability-based multidisciplinary design and optimization (RBMDO) of engineering structures, the saddlepoint approximation (SA) method can be utilized to enhance the accuracy and efficiency of reliability evaluation. However, the random variables involved in SA should be easy to handle. Additionally, the corresponding saddlepoint equation should not be complicated. Both of them limit the application of SA for engineering problems. The moment method can construct an approximate cumulative distribution function of the performance function based on the first few statistical moments. However, the traditional moment matching method is not very accurate generally. In… More >

  • Open Access

    ARTICLE

    User Interface-Based Repeated Sequence Detection Method for Authentication

    Shin Jin Kang1, Soo Kyun Kim2,*

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2573-2588, 2023, DOI:10.32604/iasc.2023.029893 - 17 August 2022

    Abstract In this paper, we propose an authentication method that use mouse and keystroke dynamics to enhance online privacy and security. The proposed method identifies personalized repeated user interface (UI) sequences by analyzing mouse and keyboard data. To this end, an Apriori algorithm based on the keystroke-level model (KLM) of the human–computer interface domain was used. The proposed system can detect repeated UI sequences based on KLM for authentication in the software. The effectiveness of the proposed method is verified through access testing using commercial applications that require intensive UI interactions. The results show using our More >

  • Open Access

    ARTICLE

    New Preamble Sequence for WiMAX System with Improved Synchronization Accuracy

    Suma Sekhar1,*, Sakuntala S. Pillai2, S. Santhosh Kumar3

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3187-3197, 2023, DOI:10.32604/iasc.2023.028702 - 17 August 2022

    Abstract Worldwide Interoperability for Microwave Access (WiMAX) trusts Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO-OFDM) combination for the deployment of physical layer functions and for connecting the medium access control to the wireless media. Even though Orthogonal Frequency Division Multiplexing (OFDM) facilitates reliable digital broadband transmission in the fading wireless channels, the presence of synchronization errors in the form of Carrier Frequency Offset (CFO) and Time Offset (TO) adversely affect the performance of OFDM based physical layers. The objective of this work is to improve the accuracy of the frequency and the time offset estimation More >

  • Open Access

    ARTICLE

    Ext-ICAS: A Novel Self-Normalized Extractive Intra Cosine Attention Similarity Summarization

    P. Sharmila1,*, C. Deisy1, S. Parthasarathy2

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 377-393, 2023, DOI:10.32604/csse.2023.027481 - 16 August 2022

    Abstract With the continuous growth of online news articles, there arises the necessity for an efficient abstractive summarization technique for the problem of information overloading. Abstractive summarization is highly complex and requires a deeper understanding and proper reasoning to come up with its own summary outline. Abstractive summarization task is framed as seq2seq modeling. Existing seq2seq methods perform better on short sequences; however, for long sequences, the performance degrades due to high computation and hence a two-phase self-normalized deep neural document summarization model consisting of improvised extractive cosine normalization and seq2seq abstractive phases has been proposed… More >

  • Open Access

    ARTICLE

    Assessing Conscientiousness and Identify Leadership Quality Using Temporal Sequence Images

    T. S. Kanchana*, B. Smitha Evelin Zoraida

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2003-2013, 2023, DOI:10.32604/iasc.2023.029412 - 19 July 2022

    Abstract Human Facial expressions exhibits the inner personality. Evaluating the inner personality is performed through questionnaires during recruitment process. However, the evaluation through questionnaires performs less due to anxiety, and stress during interview and prediction of leadership quality becomes a challenging problem. To the above problem, Temporal sequence based SENet architecture (TSSA) is proposed for accurate evaluation of personality trait for employing the correct person for leadership position. Moreover, SENet is integration with modern architectures for performance evaluation. In Proposed TSSA, face book facial images of a particular person for a period of one month and… More >

  • Open Access

    ARTICLE

    Toughening of Unsaturated Polyester Resin by Blending with Polyether Telechelics. Dependency of Toughening Efficacy on End Groups

    JEEMOL. P. A1, SURESH MATHEW1, REGHUNADHAN NAIR C.P.2,*

    Journal of Polymer Materials, Vol.39, No.1-2, pp. 111-120, 2022, DOI:10.32381/JPM.2022.39.1-2.7

    Abstract Polyether telechelics based on ethylene glycol,1,2-propylene glycol and 1,4- butylene glycol of with various molar masses and bearing at both terminals functional groups such as maleimide, itaconimide, nadimide and hydroxyl groups were individually examined as toughening agents for an unsaturated polyester resin (UPER). For a given telechelic, the toughening effect was evaluated at different mass ratios. The difference in toughening efficacy arose from the differential reactivity of the telechelics end groups combined with the unsaturation of the UPER with the reactive diluent, styrene. This causes a differential distribution of the polyether groups in the UPER… More >

  • Open Access

    ARTICLE

    Fault Ride-Through (FRT) Behavior in VSC-HVDC as Key Enabler of Transmission Systems Using SCADA Viewer Software

    Samuel Bimenyimana1, Chen Wang1,*, Godwin Norense Osarumwense Asemota2, Aphrodis Nduwamungu2, Francis Mulolani6, Jean De Dieu Niyonteze8, Shilpi Bora1,7, Chun-Ling Ho1, Noel Hagumimana3, Theobald Habineza4, Waqar Bashir5, Yiyi Mo1

    Energy Engineering, Vol.119, No.6, pp. 2369-2406, 2022, DOI:10.32604/ee.2022.019257 - 14 September 2022

    Abstract The world’s energy consumption and power generation demand will continue to rise. Furthermore, the bulk of the energy resources needed to satisfy the rising demand is far from the load centers. The aforementioned requires long-distance transmission systems and one way to accomplish this is to use high voltage direct current (HVDC) transmission systems. The main technical issues for HVDC transmission systems are loss of synchronism, variation of quadrature currents, amplitude, the inability of station 1 (rectifier), and station 2 (inverter) to either inject, or absorb active, or reactive power in the network in any circumstances… More >

  • Open Access

    ARTICLE

    Aortic Dissection Diagnosis Based on Sequence Information and Deep Learning

    Haikuo Peng1, Yun Tan1,*, Hao Tang2, Ling Tan2, Xuyu Xiang1, Yongjun Wang2, Neal N. Xiong3

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2757-2771, 2022, DOI:10.32604/cmc.2022.029727 - 16 June 2022

    Abstract Aortic dissection (AD) is one of the most serious diseases with high mortality, and its diagnosis mainly depends on computed tomography (CT) results. Most existing automatic diagnosis methods of AD are only suitable for AD recognition, which usually require preselection of CT images and cannot be further classified to different types. In this work, we constructed a dataset of 105 cases with a total of 49021 slices, including 31043 slices expert-level annotation and proposed a two-stage AD diagnosis structure based on sequence information and deep learning. The proposed region of interest (RoI) extraction algorithm based More >

  • Open Access

    ARTICLE

    Detection of DDoS Attack in IoT Networks Using Sample Selected RNN-ELM

    S. Hariprasad1,*, T. Deepa1, N. Bharathiraja2

    Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1425-1440, 2022, DOI:10.32604/iasc.2022.022856 - 25 May 2022

    Abstract The Internet of Things (IoT) is a global information and communication technology which aims to connect any type of device to the internet at any time and in any location. Nowadays billions of IoT devices are connected to the world, this leads to easily cause vulnerability to IoT devices. The increasing of users in different IoT-related applications leads to more data attacks is happening in the IoT networks after the fog layer. To detect and reduce the attacks the deep learning model is used. In this article, a hybrid sample selected recurrent neural network-extreme learning… More >

  • Open Access

    ARTICLE

    Grid-Connected Control Strategy of VSG under Complex Grid Voltage Conditions

    Bin Zhang, Yanjun Jin*

    Energy Engineering, Vol.119, No.4, pp. 1467-1482, 2022, DOI:10.32604/ee.2022.018233 - 23 May 2022

    Abstract Under complex grid conditions, the grid voltage usually has an imbalance, low order harmonics, and a small of DC bias. When the grid voltage contains low order harmonics and a small amount of DC bias component, the inverter's output current cannot meet the grid connection requirements, and there is a three-phase current imbalance in the control strategy of common VSG under unbalanced voltage. A theoretical analysis of non-ideal power grids is carried out, and a VSG control strategy under complex operating conditions is proposed. Firstly, the third-order generalized integrator (TOGI) is used to eliminate the… More >

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