Muhammad Shahzeb Ali¹, Ali Alqahtani^2,*, Ansar Munir Shah¹, Adel Rajab², Mahmood Ul Hassan³, Asadullah Shaikh², Khairan Rajab², Basit Shahzad⁴

Computer Systems Science and Engineering, Vol.44, No.1, pp. 845-858, 2023, DOI:10.32604/csse.2023.025449

Abstract Throughout the use of the small battery-operated sensor nodes encourage us to develop an energy-efficient routing protocol for wireless sensor networks (WSNs). The development of an energy-efficient routing protocol is a mainly adopted technique to enhance the lifetime of WSN. Many routing protocols are available, but the issue is still alive. Clustering is one of the most important techniques in the existing routing protocols. In the clustering-based model, the important thing is the selection of the cluster heads. In this paper, we have proposed a scheme that uses the bubble sort algorithm for cluster head selection by considering the remaining… More >

Huakun Que¹, Guolong Lin², Wenchong Guo¹, Xiaofeng Feng¹, Zetao Jiang¹, Yunfei Cao^2,*, Jinmin Fan², Zhixian Ni³

Energy Engineering, Vol.119, No.4, pp. 1453-1466, 2022, DOI:10.32604/ee.2022.018448

Abstract In order to solve the failure of electricity anti-stealing detection device triggered by the noise mixed in high-frequency electricity stealing signals, a denoising method based on variational mode decomposition (VMD) and wavelet threshold denoising (WTD) was applied to extract the effective high-frequency electricity stealing signals. First, the signal polluted by noise was pre-decomposed using the VMD algorithm, the instantaneous frequency means of each pre-decomposed components was analyzed, so as to determine the optimal K value. The optimal K value was used to decompose the polluted signal into K intrinsic mode components, and the sensitive mode components were determined through the… More > Graphic Abstract

Mohammad Adnan Aladaileh, Mohammed Anbar^*, Iznan H. Hasbullah, Abdullah Ahmed Bahashwan, Shadi Al-Sarawn

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1403-1416, 2022, DOI:10.32604/cmc.2022.029369

Abstract The emergence of a new network architecture, known as Software Defined Networking (SDN), in the last two decades has overcome some drawbacks of traditional networks in terms of performance, scalability, reliability, security, and network management. However, the SDN is vulnerable to security threats that target its controller, such as low-rate Distributed Denial of Service (DDoS) attacks, The low-rate DDoS attack is one of the most prevalent attacks that poses a severe threat to SDN network security because the controller is a vital architecture component. Therefore, there is an urgent need to propose a detection approach for this type of attack… More >

Linshan Shen¹, Ye Tian^1,*, Liguo Zhang^1,2, Guisheng Yin¹, Tong Shuai³, Shuo Liang³, Zhuofei Wu⁴

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 465-476, 2022, DOI:10.32604/cmc.2022.027488

Abstract The semi-supervised deep learning technology driven by a small part of labeled data and a large amount of unlabeled data has achieved excellent performance in the field of image processing. However, the existing semi-supervised learning techniques are all carried out under the assumption that the labeled data and the unlabeled data are in the same distribution, and its performance is mainly due to the two being in the same distribution state. When there is out-of-class data in unlabeled data, its performance will be affected. In practical applications, it is difficult to ensure that unlabeled data does not contain out-of-category data,… More >

Wenzheng Yu¹, Yang Gao¹, Zhengyu Yuan¹, Xin Yao^1,*, Mingxuan Zhu¹, Hanxiaoya Zhang²

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 563-576, 2022, DOI:10.32604/cmc.2022.027008

Abstract

Poisson-Gumbel joint distribution model uses maximum wind speed corresponding to multiple typhoons to construct sample sequence. Thresholds are usually used to filter sample sequences to make them more consistent with Poisson distribution. However, few studies have discussed the threshold setting and its impact on Poisson-Gumbel joint distribution model. In this study, a sample sequence based on the data of Qinzhou meteorological station from 2005 to 2018 were constructed. We set 0%, 5%, 10%, 20% and 30% gradient thresholds. Then, we analyzed the influence of threshold change on the calculation results of maximum wind speed in different return periods. The results… More >

E. Kavitha^1,*, R. Tamilarasan², Arunadevi Baladhandapani³, M. K. Jayanthi Kannan⁴

Computer Systems Science and Engineering, Vol.43, No.3, pp. 871-886, 2022, DOI:10.32604/csse.2022.021215

Abstract Gene expression data represents a condition matrix where each row represents the gene and the column shows the condition. Micro array used to detect gene expression in lab for thousands of gene at a time. Genes encode proteins which in turn will dictate the cell function. The production of messenger RNA along with processing the same are the two main stages involved in the process of gene expression. The biological networks complexity added with the volume of data containing imprecision and outliers increases the challenges in dealing with them. Clustering methods are hence essential to identify the patterns present in… More >

Linguo Li^1,2, Xuwen Huang², Shunqiang Qian², Zhangfei Li², Shujing Li^2,*, Romany F. Mansour³

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3073-3090, 2022, DOI:10.32604/cmc.2022.026625

Abstract In order to address the problems of Coyote Optimization Algorithm in image thresholding, such as easily falling into local optimum, and slow convergence speed, a Fuzzy Hybrid Coyote Optimization Algorithm (hereinafter referred to as FHCOA) based on chaotic initialization and reverse learning strategy is proposed, and its effect on image thresholding is verified. Through chaotic initialization, the random number initialization mode in the standard coyote optimization algorithm (COA) is replaced by chaotic sequence. Such sequence is nonlinear and long-term unpredictable, these characteristics can effectively improve the diversity of the population in the optimization algorithm. Therefore, in this paper we first… More >

Khudhayr A. Rashedi^1,2,*, Mohd Tahir Ismail¹, Abdeslam Serroukh³, S. Al wadi⁴

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3835-3847, 2022, DOI:10.32604/cmc.2022.026476

Abstract We introduce a new wavelet based procedure for detecting outliers in financial discrete time series. The procedure focuses on the analysis of residuals obtained from a model fit, and applied to the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) like model, but not limited to these models. We apply the Maximal-Overlap Discrete Wavelet Transform (MODWT) to the residuals and compare their wavelet coefficients against quantile thresholds to detect outliers. Our methodology has several advantages over existing methods that make use of the standard Discrete Wavelet Transform (DWT). The series sample size does not need to be a power of 2 and the… More >

Jyoti Khandelwal¹, Vijay Kumar Sharma¹, Dilbag Singh^2,*, Atef Zaguia³

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3299-3312, 2022, DOI:10.32604/cmc.2022.023116

Abstract Digital image steganography technique based on hiding the secret data behind of cover image in such a way that it is not detected by the human visual system. This paper presents an image scrambling method that is very useful for grayscale secret images. In this method, the secret image decomposes in three parts based on the pixel's threshold value. The division of the color image into three parts is very easy based on the color channel but in the grayscale image, it is difficult to implement. The proposed image scrambling method is implemented in image steganography using discrete wavelet transform… More >

Yu Ren¹, Jiaohua Qin^1,*, Yun Tan¹, Neal N. Xiong²

Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1439-1453, 2022, DOI:10.32604/iasc.2022.025485

Abstract In the field of reversible data hiding in encrypted images (RDH-EI), predict an image effectively and embed a message into the image with lower distortion are two crucial aspects. However, due to the linear regression prediction being sensitive to outliers, it is a challenge to improve the accuracy of predictions. To address this problem, this paper proposes an RDH-EI scheme based on adaptive prediction-error label map. In the prediction stage, an adaptive threshold estimation algorithm based on local complexity is proposed. Then, the pixels selection method based on gradient of image is designed to train the parameters of the prediction… More >