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  • Open Access

    ARTICLE

    A Novel Color Image Watermarking Method with Adaptive Scaling Factor Using Similarity-Based Edge Region

    Kali Gurkahraman1,*, Rukiye Karakis2, Hidayet Takci1

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 55-77, 2023, DOI:10.32604/csse.2023.037798

    Abstract This study aimed to deal with three challenges: robustness, imperceptibility, and capacity in the image watermarking field. To reach a high capacity, a novel similarity-based edge detection algorithm was developed that finds more edge points than traditional techniques. The colored watermark image was created by inserting a randomly generated message on the edge points detected by this algorithm. To ensure robustness and imperceptibility, watermark and cover images were combined in the high-frequency subbands using Discrete Wavelet Transform and Singular Value Decomposition. In the watermarking stage, the watermark image was weighted by the adaptive scaling factor calculated by the standard deviation… More >

  • Open Access

    ARTICLE

    A Unique Discrete Wavelet & Deterministic Walk-Based Glaucoma Classification Approach Using Image-Specific Enhanced Retinal Images

    Krishna Santosh Naidana, Soubhagya Sankar Barpanda*

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 699-720, 2023, DOI:10.32604/csse.2023.036744

    Abstract Glaucoma is a group of ocular atrophy diseases that cause progressive vision loss by affecting the optic nerve. Because of its asymptomatic nature, glaucoma has become the leading cause of human blindness worldwide. In this paper, a novel computer-aided diagnosis (CAD) approach for glaucomatous retinal image classification has been introduced. It extracts graph-based texture features from structurally improved fundus images using discrete wavelet-transformation (DWT) and deterministic tree-walk (DTW) procedures. Retinal images are considered from both public repositories and eye hospitals. Images are enhanced with image-specific luminance and gradient transitions for both contrast and texture improvement. The enhanced images are mapped… More >

  • Open Access

    ARTICLE

    An Experimental Study on the Interaction between Hydrate Formation and Wax Precipitation in Waxy Oil-in-Water Emulsions

    Xincan Song1,3,4, Lin Wang1,3,4,*, Cheng Yu1,2, Jiaxin Chen1,3,4, Linjie Ma1,3,4

    Energy Engineering, Vol.120, No.8, pp. 1837-1852, 2023, DOI:10.32604/ee.2023.027637

    Abstract The coupled formation of wax crystals and hydrates is a critical issue for the safety of deep-sea oil and gas exploration and subsea transport pipeline flow. Therefore, this paper conducts an experimental study on the characteristics of methane hydrate formation in a water-in-oil (W/O) system with different wax crystal contents and explores the influence of different initial experimental pressures on the induction period and maximum rate of hydrate formation. The wavelet function was introduced to process the reaction rate and calculate the maximum speed of hydrate formation. Notably, the higher the pressure, the smaller the maximum rate of hydrate formation.… More >

  • Open Access

    ARTICLE

    Meta-Heuristic Optimized Hybrid Wavelet Features for Arrhythmia Classification

    S. R. Deepa1, M. Subramoniam2,*, R. Swarnalatha3, S. Poornapushpakala2, S. Barani2

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 745-761, 2023, DOI:10.32604/iasc.2023.034211

    Abstract The non-invasive evaluation of the heart through EectroCardioGraphy (ECG) has played a key role in detecting heart disease. The analysis of ECG signals requires years of learning and experience to interpret and extract useful information from them. Thus, a computerized system is needed to classify ECG signals with more accurate results effectively. Abnormal heart rhythms are called arrhythmias and cause sudden cardiac deaths. In this work, a Computerized Abnormal Heart Rhythms Detection (CAHRD) system is developed using ECG signals. It consists of four stages; preprocessing, feature extraction, feature optimization and classifier. At first, Pan and Tompkins algorithm is employed to… More >

  • Open Access

    ARTICLE

    APST-Flow: A Reversible Network-Based Artistic Painting Style Transfer Method

    Meng Wang*, Yixuan Shao, Haipeng Liu

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5229-5254, 2023, DOI:10.32604/cmc.2023.036631

    Abstract In recent years, deep generative models have been successfully applied to perform artistic painting style transfer (APST). The difficulties might lie in the loss of reconstructing spatial details and the inefficiency of model convergence caused by the irreversible en-decoder methodology of the existing models. Aiming to this, this paper proposes a Flow-based architecture with both the en-decoder sharing a reversible network configuration. The proposed APST-Flow can efficiently reduce model uncertainty via a compact analysis-synthesis methodology, thereby the generalization performance and the convergence stability are improved. For the generator, a Flow-based network using Wavelet additive coupling (WAC) layers is implemented to… More >

  • Open Access

    ARTICLE

    ANALYSIS OF LAMINAR BOUNDARY-LAYER FLOW OVER A MOVING WEDGE USING A UNIFORM HAAR WAVELET METHOD

    Harinakshi Karkeraa , Nagaraj N. Katagia,† , Ramesh B. Kudenattib

    Frontiers in Heat and Mass Transfer, Vol.18, pp. 1-10, 2022, DOI:10.5098/hmt.18.41

    Abstract In this paper, we study the characteristics of laminar boundary-layer flow of a viscous incompressible fluid over a moving wedge. The transformed boundary-layer equation given by the Falkner-Skan equation is solved by an efficient easy-to-use approximate method based on uniform Haar wavelets in conjunction with quasilinearization and collocation approach. The residual and error estimates are computed to confirm the validity of the obtained results. A meaningful comparison between the present solutions with existing numerical results in the literature is carried out to highlight the benefits and efficiency of proposed method. Furthermore, the influence of variable pressure gradient and the wedge… More >

  • Open Access

    ARTICLE

    Fusing Satellite Images Using ABC Optimizing Algorithm

    Nguyen Hai Minh1, Nguyen Tu Trung2,*, Tran Thi Ngan2, Tran Manh Tuan2

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3901-3909, 2023, DOI:10.32604/csse.2023.032311

    Abstract Fusing satellite (remote sensing) images is an interesting topic in processing satellite images. The result image is achieved through fusing information from spectral and panchromatic images for sharpening. In this paper, a new algorithm based on based the Artificial bee colony (ABC) algorithm with peak signal-to-noise ratio (PSNR) index optimization is proposed to fusing remote sensing images in this paper. Firstly, Wavelet transform is used to split the input images into components over the high and low frequency domains. Then, two fusing rules are used for obtaining the fused images. The first rule is “the high frequency components are fused… More >

  • Open Access

    ARTICLE

    Optimal Wavelet Neural Network-Based Intrusion Detection in Internet of Things Environment

    Heba G. Mohamed1, Fadwa Alrowais2, Mohammed Abdullah Al-Hagery3, Mesfer Al Duhayyim4,*, Anwer Mustafa Hilal5, Abdelwahed Motwakel5

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4467-4483, 2023, DOI:10.32604/cmc.2023.036822

    Abstract As the Internet of Things (IoT) endures to develop, a huge count of data has been created. An IoT platform is rather sensitive to security challenges as individual data can be leaked, or sensor data could be used to cause accidents. As typical intrusion detection system (IDS) studies can be frequently designed for working well on databases, it can be unknown if they intend to work well in altering network environments. Machine learning (ML) techniques are depicted to have a higher capacity at assisting mitigate an attack on IoT device and another edge system with reasonable accuracy. This article introduces… More >

  • Open Access

    ARTICLE

    Power Quality Improvement Using ANN Controller For Hybrid Power Distribution Systems

    Abdul Quawi1,*, Y. Mohamed Shuaib1, M. Manikandan2

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3469-3486, 2023, DOI:10.32604/iasc.2023.035001

    Abstract In this work, an Artificial Neural Network (ANN) based technique is suggested for classifying the faults which occur in hybrid power distribution systems. Power, which is generated by the solar and wind energy-based hybrid system, is given to the grid at the Point of Common Coupling (PCC). A boost converter along with perturb and observe (P&O) algorithm is utilized in this system to obtain a constant link voltage. In contrast, the link voltage of the wind energy conversion system (WECS) is retained with the assistance of a Proportional Integral (PI) controller. The grid synchronization is tainted with the assistance of… More >

  • Open Access

    ARTICLE

    Spectral Analysis and Validation of Parietal Signals for Different Arm Movements

    Umashankar Ganesan1,*, A. Vimala Juliet2, R. Amala Jenith Joshi3

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2849-2863, 2023, DOI:10.32604/iasc.2023.033759

    Abstract Brain signal analysis plays a significant role in attaining data related to motor activities. The parietal region of the brain plays a vital role in muscular movements. This approach aims to demonstrate a unique technique to identify an ideal region of the human brain that generates signals responsible for muscular movements; perform statistical analysis to provide an absolute characterization of the signal and validate the obtained results using a prototype arm. This can enhance the practical implementation of these frequency extractions for future neuro-prosthetic applications and the characterization of neurological diseases like Parkinson’s disease (PD). To play out this handling… More >

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