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  • Open Access

    ARTICLE

    Arabic Feature-Based Text Watermarking Technique for Sensitive Detecting Tampering Attack

    Fahd N. Al-Wesabi1,2,*, Huda G. Iskandar2,3, Saleh Alzahrani4, Abdelzahir Abdelmaboud4, Mohammed Abdul4, Nadhem Nemri4, Mohammad Medani4, Mohammed Y. Alghamdi5

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3789-3806, 2021, DOI:10.32604/cmc.2021.017674

    Abstract In this article, a high-sensitive approach for detecting tampering attacks on transmitted Arabic-text over the Internet (HFDATAI) is proposed by integrating digital watermarking and hidden Markov model as a strategy for soft computing. The HFDATAI solution technically integrates and senses the watermark without modifying the original text. The alphanumeric mechanism order in the first stage focused on the Markov model key secret is incorporated into an automated, null-watermarking approach to enhance the proposed approach’s efficiency, accuracy, and intensity. The first-level order and alphanumeric Markov model technique have been used as a strategy for soft computing… More >

  • Open Access

    ARTICLE

    Maximizing Throughput in Wireless Multimedia Sensor Network using Soft Computing Techniques

    Krishnan Muthumayil1,*, Thangaiyan Jayasankar2, Nagappan Krishnaraj3, Mohamed Yacin Sikkandar4, Prakash Nattanmai Balasubramanian5, Chokkalingam Bharatiraja6

    Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 771-784, 2021, DOI:10.32604/iasc.2021.012462

    Abstract Wireless Multimedia Sensor Networks (WMSN) provides valuable information for scalar data, images, audio, and video processing in monitoring and surveillance applications. Multimedia streaming, however, is highly challenging for networks as energy restriction sensor nodes limit the potential data transmission bandwidth and lead to reduced throughput. WMSN’s two key design challenges, which can be achieved by the clustering process, are energy efficiency and throughput maximization. The use of the clustering technique helps to organise the sensor nodes into clusters, and between each cluster a cluster head (CH) will be chosen. This paper introduces a new Artificial… More >

  • Open Access

    ARTICLE

    Soft Computing Based Evolutionary Multi-Label Classification

    Rubina Aslam1,*, Manzoor Illahi Tamimy1, Waqar Aslam2

    Intelligent Automation & Soft Computing, Vol.26, No.6, pp. 1233-1249, 2020, DOI:10.32604/iasc.2020.013086

    Abstract Machine Learning (ML) has revolutionized intelligent systems that range from self-driving automobiles, search engines, business/market analysis, fraud detection, network intrusion investigation, and medical diagnosis. Classification lies at the core of Machine Learning and Multi-label Classification (MLC) is the closest to real-life problems related to heuristics. It is a type of classification problem where multiple labels or classes can be assigned to more than one instance simultaneously. The level of complexity in MLC is increased by factors such as data imbalance, high dimensionality, label correlations, and noise. Conventional MLC techniques such as ensembles-based approaches, Multi-label Stacking,… More >

  • Open Access

    ARTICLE

    Intelligent Power Compensation System Based on Adaptive Sliding Mode Control Using Soft Computing and Automation

    Qidan Zhua, Zhibo Yanga,*

    Computer Systems Science and Engineering, Vol.34, No.4, pp. 179-189, 2019, DOI:10.32604/csse.2019.34.179

    Abstract The approach power compensator system (APCS) plays a role in the automatic carrier landing system (ACLS), and the performance of the APCS is affected by the carrier air-wake in the final-approach . In this paper, the importance of the APCS is verified through the analysis of the signal flow chart of the ACLS. Hence, it is necessary to suppress the carrier air-wake in order to improve the anti-interference ability. The adaptive sliding mode control (ASMC) not only has better dynamic tracking performance compared to the nonlinear mode, but also can efficiently resist the disturbance caused More >

  • Open Access

    ARTICLE

    Hybrid Soft Computing Technique Based Trust Evaluation Protocol for Wireless Sensor Networks

    Supreet Kaur*, Vijay Kumar Joshi

    Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 217-226, 2020, DOI:10.31209/2018.100000064

    Abstract Wireless sensor networks (WSNs) are susceptible to safety threats due to cumulative dependence upon transmission, computing, and control mechanisms. Therefore, securing the end-to-end communication becomes a major area of research in WSNs. A majority of existing protocols are based upon signature and recommended-based trust evaluation techniques only. However, these techniques are vulnerable to wormhole attacks that happen due to lesser synchronization between the sensor nodes. Therefore, to handle this problem, a novel hybrid crossover-based ant colony optimization-based routing protocol is proposed. An integrated modified signature and recommendationbased trust evaluation protocol for WSNs is presented. Extensive More >

  • Open Access

    ARTICLE

    Soft Computing Techniques for Classification of Voiced/Unvoiced Phonemes

    Mohammed Algabria,c, Mohamed Abdelkader Bencherifc, Mansour Alsulaimanb,c, Ghulam Muhammadb, Mohamed Amine Mekhtichec

    Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 267-274, 2018, DOI:10.1080/10798587.2017.1278961

    Abstract A method that uses fuzzy logic to classify two simple speech features for the automatic classification of voiced and unvoiced phonemes is proposed. In addition, two variants, in which soft computing techniques are used to enhance the performance of fuzzy logic by tuning the parameters of the membership functions, are also presented. The three methods, manually constructed fuzzy logic (VUFL), fuzzy logic optimized with genetic algorithm (VUFL-GA), and fuzzy logic with optimized particle swarm optimization (VUFL-PSO), are implemented and then evaluated using the TIMIT speech corpus. Performance is evaluated using the TIMIT database in both More >

  • Open Access

    ARTICLE

    Special Issue on Recent Advances in Data Driven Modeling & Soft Computing

    Wen-Hsiang Hsieh, Jerzy W Rozenblit, Minvydas Ragulskis

    Intelligent Automation & Soft Computing, Vol.25, No.2, pp. 313-314, 2019, DOI:10.31209/2019.100000092

    Abstract This article has no abstract. More >

  • Open Access

    EDITORIAL

    Guest Editorial: Special Section on Recent Advances in Data Driven Modeling & Soft Computing

    Wen-Hsiang Hsieh, Jerzy W. Rozenblit, Minvydas Ragulskis

    Intelligent Automation & Soft Computing, Vol.25, No.2, pp. 315-317, 2019, DOI:10.31209/2019.100000091

    Abstract This article has no abstract. More >

  • Open Access

    ARTICLE

    Emerging Trends in Soft Computing Techniques for Metamaterial Design and Optimization

    Balamati Choudhury11, Sanjana Bisoyi1, R M Jha1

    CMC-Computers, Materials & Continua, Vol.31, No.3, pp. 201-228, 2012, DOI:10.3970/cmc.2012.031.201

    Abstract Soft computing methods play an important role in the design and optimization in diverse engineering disciplines including those in the electromagnetic applications. The aim of these soft computing methods is to tolerate imprecision, uncertainties, and approximations to achieve a quick solution, which is both robust and economically viable. Soft computing methods such as genetic algorithm, neural network and fuzzy logic have been widely used by researchers for microwave design since the last decade. The metamaterial multilayer concept in conjunction with transformation optics leads to exciting applications in the microwave regime with such examples as invisible More >

  • Open Access

    ARTICLE

    Soft Computing for Terahertz Metamaterial Absorber Design for Biomedical Application

    Balamati Choudhury1, Pavani Vijay Reddy1, Sanjana Bisoyi1, R. M. Jha1

    CMC-Computers, Materials & Continua, Vol.37, No.3, pp. 135-146, 2013, DOI:10.3970/cmc.2013.037.135

    Abstract The terahertz region of the electromagnetic spectrum plays a vital role in biomedical imaging because of its sensitivity to vibrational modes of biomolecules. Advances in broadband terahertz imaging have been emerging in the field of biomedical spectroscopy. Biomedical imaging is used to distinguish between the infected (cancer) and the non-infected tissue, which requires broad band and highly efficient radar absorbing material (RAM) designs (to obtain high resolution image of the tissue). In this paper, a metamaterial broadband RAM design is proposed towards biomedical spectroscopy applications in the THz region. The particle swarm optimization (PSO) algorithm More >

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