Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (17)
  • Open Access



    N. Gnanasekaran, C. Balaji*

    Frontiers in Heat and Mass Transfer, Vol.2, No.2, pp. 1-6, 2011, DOI:10.5098/hmt.v2.2.3008

    Abstract This paper reports the results of an experimental investigation of transient, turbulent mixed convection in a vertical channel in which one of the walls is heated and the other is adiabatic. The goal is to simultaneously estimate the constants in a Nusselt number correlation whose form is assumed a priori by synergistically marrying the experimental results with repeated numerical calculations that assume guess values of the constants. The convective heat transfer coefficient “h”is replaced by the Nusselt number (Nu) and the constants in the Nusselt number are to be evaluated. From the experimentally obtained temperature time history and the simulated… More >

  • Open Access


    Application Research on Two-Layer Threat Prediction Model Based on Event Graph

    Shuqin Zhang, Xinyu Su*, Yunfei Han, Tianhui Du, Peiyu Shi

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3993-4023, 2023, DOI:10.32604/cmc.2023.044526

    Abstract Advanced Persistent Threat (APT) is now the most common network assault. However, the existing threat analysis models cannot simultaneously predict the macro-development trend and micro-propagation path of APT attacks. They cannot provide rapid and accurate early warning and decision responses to the present system state because they are inadequate at deducing the risk evolution rules of network threats. To address the above problems, firstly, this paper constructs the multi-source threat element analysis ontology (MTEAO) by integrating multi-source network security knowledge bases. Subsequently, based on MTEAO, we propose a two-layer threat prediction model (TL-TPM) that combines the knowledge graph and the… More >

  • Open Access


    Customer Segment Prediction on Retail Transactional Data Using K-Means and Markov Model

    A. S. Harish*, C. Malathy

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 589-600, 2023, DOI:10.32604/iasc.2023.032030

    Abstract Retailing is a dynamic business domain where commodities and goods are sold in small quantities directly to the customers. It deals with the end user customers of a supply-chain network and therefore has to accommodate the needs and desires of a large group of customers over varied utilities. The volume and volatility of the business makes it one of the prospective fields for analytical study and data modeling. This is also why customer segmentation drives a key role in multiple retail business decisions such as marketing budgeting, customer targeting, customized offers, value proposition etc. The segmentation could be on various… More >

  • Open Access


    Active Kriging-Based Adaptive Importance Sampling for Reliability and Sensitivity Analyses of Stator Blade Regulator

    Hong Zhang1, Lukai Song1,2,*, Guangchen Bai1

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 1871-1897, 2023, DOI:10.32604/cmes.2022.021880


    The reliability and sensitivity analyses of stator blade regulator usually involve complex characteristics like high-nonlinearity, multi-failure regions, and small failure probability, which brings in unacceptable computing efficiency and accuracy of the current analysis methods. In this case, by fitting the implicit limit state function (LSF) with active Kriging (AK) model and reducing candidate sample pool with adaptive importance sampling (AIS), a novel AK-AIS method is proposed. Herein, the AK model and Markov chain Monte Carlo (MCMC) are first established to identify the most probable failure region(s) (MPFRs), and the adaptive kernel density estimation (AKDE) importance sampling function is constructed to… More >

  • Open Access


    Intelligent Vehicular Communication Using Vulnerability Scoring Based Routing Protocol

    M. Ramya Devi*, I. Jasmine Selvakumari Jeya

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 31-45, 2023, DOI:10.32604/iasc.2023.026152

    Abstract Internet of Vehicles (IoV) is an intelligent vehicular technology that allows vehicles to communicate with each other via internet. Communications and the Internet of Things (IoT) enable cutting-edge technologies including such self-driving cars. In the existing systems, there is a maximum communication delay while transmitting the messages. The proposed system uses hybrid Co-operative, Vehicular Communication Management Framework called CAMINO (CA). Further it uses, energy efficient fast message routing protocol with Common Vulnerability Scoring System (CVSS) methodology for improving the communication delay, throughput. It improves security while transmitting the messages through networks. In this research, we present a unique intelligent vehicular… More >

  • Open Access


    Selfish Mining and Defending Strategies in the Bitcoin

    Weijian Zhang1,*, Hao Wang2, Hao Hua3, Qirun Wang4

    Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1861-1875, 2022, DOI:10.32604/iasc.2022.030274

    Abstract As a kind of distributed, decentralized and peer-to-peer transmitted technology, blockchain technology has gradually changed people’s lifestyle. However, blockchain technology also faces many problems including selfish mining attack, which causes serious effects to the development of blockchain technology. Selfish mining is a kind of mining strategy where selfish miners increase their profit by selectively publishing hidden blocks. This paper builds the selfish mining model from the perspective of node state conversion and utilize the function extremum method to figure out the optimal profit of this model. Meanwhile, based on the experimental data of honest mining, the author conducts the simulation… More >

  • Open Access


    Cost and Efficiency Analysis of Steganography in the IEEE 802.11ah IoT Protocol

    Akram A. Almohammedi1,2,*, Vladimir Shepelev1, Sam Darshi3, Mohammed Balfaqih4, Fayad Ghawbar5

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3929-3943, 2022, DOI:10.32604/cmc.2022.026307

    Abstract The widespread use of the Internet of Things (IoT) applications has enormously increased the danger level of data leakage and theft in IoT as data transmission occurs through a public channel. As a result, the security of the IoT has become a serious challenge in the field of information security. Steganography on the network is a critical tool for preventing the leakage of private information and enabling secure and encrypted communication. The primary purpose of steganography is to conceal sensitive information in any form of media such as audio, video, text, or photos, and securely transfer it through wireless networks.… More >

  • Open Access


    Distance Matrix and Markov Chain Based Sensor Localization in WSN

    Omaima Bamasaq1, Daniyal Alghazzawi2, Surbhi Bhatia3, Pankaj Dadheech4,*, Farrukh Arslan5, Sudhakar Sengan6, Syed Hamid Hassan2

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 4051-4068, 2022, DOI:10.32604/cmc.2022.023634

    Abstract Applications based on Wireless Sensor Networks (WSN) have shown to be quite useful in monitoring a particular geographic area of interest. Relevant geometries of the surrounding environment are essential to establish a successful WSN topology. But it is literally hard because constructing a localization algorithm that tracks the exact location of Sensor Nodes (SN) in a WSN is always a challenging task. In this research paper, Distance Matrix and Markov Chain (DM-MC) model is presented as node localization technique in which Distance Matrix and Estimation Matrix are used to identify the position of the node. The method further employs a… More >

  • Open Access


    Novel Kriging-Based Decomposed-Coordinated Approach for Estimating the Clearance Reliability of Assembled Structures

    Da Teng1, Yunwen Feng1,*, Cheng Lu1,2, Chengwei Fei2, Jiaqi Liu1, Xiaofeng Xue1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.2, pp. 1029-1049, 2021, DOI:10.32604/cmes.2021.016945

    Abstract Turbine blisks are assembled using blades, disks and casings. They can endure complex loads at a high temperature, high pressure and high speed. The safe operation of assembled structures depends on the reliability of each component. Monte Carlo (MC) simulation is commonly used to analyze structural reliability, but this method needs to run thousands of computations. In order to assess the clearance reliability of assembled structures in an efficient and precise manner, the novel Kriging-based decomposed-coordinated (DC) (DCNK) approach is proposed by integrating the DC strategy, the Kriging model and the importance sampling-based Markov chain (MCIS) technique. In this method,… More >

  • Open Access


    Entropy Bayesian Analysis for the Generalized Inverse Exponential Distribution Based on URRSS

    Amer I. Al-Omari1, Amal S. Hassan2, Heba F. Nagy2, Ayed R. A. Al-Anzi3,*, Loai Alzoubi1

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3795-3811, 2021, DOI:10.32604/cmc.2021.019061

    Abstract This paper deals with the Bayesian estimation of Shannon entropy for the generalized inverse exponential distribution. Assuming that the observed samples are taken from the upper record ranked set sampling (URRSS) and upper record values (URV) schemes. Formulas of Bayesian estimators are derived depending on a gamma prior distribution considering the squared error, linear exponential and precautionary loss functions, in addition, we obtain Bayesian credible intervals. The random-walk Metropolis-Hastings algorithm is handled to generate Markov chain Monte Carlo samples from the posterior distribution. Then, the behavior of the estimates is examined at various record values. The output of the study… More >

Displaying 1-10 on page 1 of 17. Per Page