Mohanapriya Marimuthu¹, Santhosh Rajendran², Reshma Radhakrishnan², Kalpana Rengarajan³, Shahzada Khurram⁴, Shafiq Ahmad⁵, Abdelaty Edrees Sayed⁵, Muhammad Shafiq^6,*

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 4729-4745, 2023, DOI:10.32604/cmc.2023.033020

Abstract Continuous improvements in very-large-scale integration (VLSI) technology and design software have significantly broadened the scope of digital signal processing (DSP) applications. The use of application-specific integrated circuits (ASICs) and programmable digital signal processors for many DSP applications have changed, even though new system implementations based on reconfigurable computing are becoming more complex. Adaptable platforms that combine hardware and software programmability efficiency are rapidly maturing with discrete wavelet transformation (DWT) and sophisticated computerized design techniques, which are much needed in today’s modern world. New research and commercial efforts to sustain power optimization, cost savings, and improved runtime effectiveness have been initiated… More >

V. Harshini¹, T. Dhanwin¹, A. Shahina^1,*, N. Safiyyah², A. Nayeemulla Khan²

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1851-1867, 2023, DOI:10.32604/csse.2023.028136

Abstract Biometrics, which has become integrated with our daily lives, could fall prey to falsification attacks, leading to security concerns. In our paper, we use Transient Evoked Otoacoustic Emissions (TEOAE) that are generated by the human cochlea in response to an external sound stimulus, as a biometric modality. TEOAE are robust to falsification attacks, as the uniqueness of an individual’s inner ear cannot be impersonated. In this study, we use both the raw 1D TEOAE signals, as well as the 2D time-frequency representation of the signal using Continuous Wavelet Transform (CWT). We use 1D and 2D Convolutional Neural Networks (CNN) for… More >

R. Vidhya^1,*, P. Vanaja Ranjan², N. R. Shanker³

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 153-168, 2023, DOI:10.32604/iasc.2023.031942

Abstract Preventive maintenance in the transformer is performed through a differential relay protection system, and it protects the transformer from internal and external faults. However, the Current Transformer (CT) in the differential protection system mal-operates during inrush currents. CT saturates due to magnetizing inrush currents and causes false tripping of the differential relays. Moreover, identification of tripping in protection relay either due to inrush current or internal faults needs to be diagnosed. For the above problem, continuous monitoring of transformer breather and CT terminals with thermal camera helps detect the tripping in relay due to inrush or internal fault. The transformer’s… More >

P. P. Fathimathul Rajeena^1,*, R. Sivakumar²

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2837-2855, 2023, DOI:10.32604/iasc.2023.030144

Abstract An accurate and early diagnosis of brain tumors based on medical imaging modalities is of great interest because brain tumors are a harmful threat to a person’s health worldwide. Several medical imaging techniques have been used to analyze brain tumors, including computed tomography (CT) and magnetic resonance imaging (MRI). CT provides information about dense tissues, whereas MRI gives information about soft tissues. However, the fusion of CT and MRI images has little effect on enhancing the accuracy of the diagnosis of brain tumors. Therefore, machine learning methods have been adopted to diagnose brain tumors in recent years. This paper intends… More >

Tariq T. Alshammari¹, Mohd Tahir Ismail¹, Nawaf N. Hamadneh^3,*, S. Al Wadi², Jamil J. Jaber², Nawa Alshammari³, Mohammad H. Saleh²

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2589-2601, 2023, DOI:10.32604/iasc.2023.024001

Abstract In this study, we proposed a new model to improve the accuracy of forecasting the stock market volatility pattern. The hypothesized model was validated empirically using a data set collected from the Saudi Arabia stock Exchange (Tadawul). The data is the daily closed price index data from August 2011 to December 2019 with 2027 observations. The proposed forecasting model combines the best maximum overlapping discrete wavelet transform (MODWT) function (Bl14) and exponential generalized autoregressive conditional heteroscedasticity (EGARCH) model. The results show the model's ability to analyze stock market data, highlight important events that contain the most volatile data, and improve… More >

Shui-Hua Wang¹, Muhammad Attique Khan², Ziquan Zhu¹, Yu-Dong Zhang^1,*

Computer Systems Science and Engineering, Vol.45, No.1, pp. 21-34, 2023, DOI:10.32604/csse.2023.031330

Abstract Community-acquired pneumonia (CAP) is considered a sort of pneumonia developed outside hospitals and clinics. To diagnose community-acquired pneumonia (CAP) more efficiently, we proposed a novel neural network model. We introduce the 2-dimensional wavelet entropy (2d-WE) layer and an adaptive chaotic particle swarm optimization (ACP) algorithm to train the feed-forward neural network. The ACP uses adaptive inertia weight factor (AIWF) and Rossler attractor (RA) to improve the performance of standard particle swarm optimization. The final combined model is named WE-layer ACP-based network (WACPN), which attains a sensitivity of 91.87 ± 1.37%, a specificity of 90.70 ± 1.19%, a precision of 91.01 ± 1.12%, an accuracy of 91.29 ± 1.09%,… More >

Navleen S Rekhi^1,2,*, Jagroop S Sidhu², Amit Arora²

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2791-2807, 2023, DOI:10.32604/csse.2023.026976

Abstract Due to improper acquisition settings and other noise artifacts, the image degraded to yield poor mean preservation in brightness. The simplest way to improve the preservation is the implementation of histogram equalization. Because of over-enhancement, it failed to preserve the mean brightness and produce the poor quality of the image. This paper proposes a multi-scale decomposition for brightness preservation using gamma correction. After transformation to hue, saturation and intensity (HSI) channel, the 2D- discrete wavelet transform decomposed the intensity component into low and high-pass coefficients. At the next phase, gamma correction is used by auto-tuning the scale value. The scale… More >

Jun Zhao¹, Shuguo Gao¹, Yunpeng Liu^2,3, Quan Wang^2,*, Ziqiang Xu², Yuan Tian¹, Lu Sun¹

Energy Engineering, Vol.119, No.5, pp. 1811-1828, 2022, DOI:10.32604/ee.2022.020490

Abstract Aiming at the problem of abnormal data generated by a power transformer on-line monitoring system due to the influences of transformer operation state change, external environmental interference, communication interruption, and other factors, a method of anomaly recognition and differentiation for monitoring data was proposed. Firstly, the empirical wavelet transform (EWT) and the autoregressive integrated moving average (ARIMA) model were used for time series modelling of monitoring data to obtain the residual sequence reflecting the anomaly monitoring data value, and then the isolation forest algorithm was used to identify the abnormal information, and the monitoring sequence was segmented according to the… More >

Srilekha Muthukaruppankaruppiah^1,*, Shanker Rajendiran Nagalingam², Priya Murugasen³, Rajesh Nandaamarnath⁴

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2309-2323, 2023, DOI:10.32604/iasc.2023.029598

Abstract Malfunction of human liver happens due to non-alcoholic fatty liver. Fatty liver measurement is used for grading hepatic steatosis, fibrosis and cirrhosis. The various imaging techniques for measuring fatty liver are Magnetic Resonance Imaging, Ultrasound and Computed Tomography. Imaging modalities lead to the exposure of harmful radiation of electromagnetic waves because of frequent measurement. The continuous monitoring of fatty liver is never achieved through imaging techniques. In this paper, the human fatty liver measured through a Fatty Liver Sensor (FLS). The continuous monitoring of the fatty liver is achieved through the FLS. FLS is fabricated through the screen-printing with materials… More >

Wajdi Elhamzi^1,2,*, Malika Jallouli³, Yassine Bouteraa^1,4

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4329-4347, 2022, DOI:10.32604/cmc.2022.030954

Abstract Since 3D mesh security has become intellectual property, 3D watermarking algorithms have continued to appear to secure 3D meshes shared by remote users and saved in distant multimedia databases. The novelty of our approach is that it uses a new Clifford-multiwavelet transform to insert copyright data in a multiresolution domain, allowing us to greatly expand the size of the watermark. After that, our method does two rounds of insertion, each applying a different type of Clifford-wavelet transform. Before being placed into the Clifford-multiwavelet coefficients, the watermark, which is a mixture of the mesh description, source mesh signature (produced using SHA512),… More >