Venkatesan Rajinikanth¹, Shabnam Mohamed Aslam², Seifedine Kadry³, Orawit Thinnukool^4,*

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 4087-4105, 2022, DOI:10.32604/cmc.2022.019786

Abstract The incident rate of the Gastrointestinal-Disease (GD) in humans is gradually rising due to a variety of reasons and the Endoscopic/Colonoscopic-Image (EI/CI) supported evaluation of the GD is an approved practice. Extraction and evaluation of the suspicious section of the EI/CI is essential to diagnose the disease and its severity. The proposed research aims to implement a joint thresholding and segmentation framework to extract the Gastric-Polyp (GP) with better accuracy. The proposed GP detection system consist; (i) Enhancement of GP region using Aquila-Optimization-Algorithm supported tri-level thresholding with entropy (Fuzzy/Shannon/Kapur) and between-class-variance (Otsu) technique, (ii) Automated (Watershed/Markov-Random-Field) and semi-automated (Chan-Vese/Level-Set/Active-Contour) segmentation… More >

Razi J. Al-Azawi¹, Nadia M. G. Al-Saidi², Hamid A. Jalab^3,*, Rabha W. Ibrahim⁴, Dumitru Baleanu^5,6,7

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3903-3915, 2021, DOI:10.32604/cmc.2021.020368

Abstract Over the past years, image manipulation tools have become widely accessible and easier to use, which made the issue of image tampering far more severe. As a direct result to the development of sophisticated image-editing applications, it has become near impossible to recognize tampered images with naked eyes. Thus, to overcome this issue, computer techniques and algorithms have been developed to help with the identification of tampered images. Research on detection of tampered images still carries great challenges. In the present study, we particularly focus on image splicing forgery, a type of manipulation where a region of an image is… More >

Amer I. Al-Omari¹, Amal S. Hassan², Heba F. Nagy², Ayed R. A. Al-Anzi^3,*, 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 >

Sk Sarif Hassan¹, Ranjeet Kumar Rout², Kshira Sagar Sahoo³, Nz Jhanjhi⁴, Saiyed Umer⁵, Thamer A. Tabbakh^6,*, Zahrah A. Almusaylim⁷

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3477-3493, 2021, DOI:10.32604/cmc.2021.017206

Abstract Coronaviruses are responsible for various diseases ranging from the common cold to severe infections like the Middle East syndromes and the severe acute respiratory syndrome. However, a new coronavirus strain known as COVID-19 developed into a pandemic resulting in an ongoing global public health crisis. Therefore, there is a need to understand the genomic transformations that occur within this family of viruses in order to limit disease spread and develop new therapeutic targets. The nucleotide sequences of SARS-CoV-2 are consist of several bases. These bases can be classified into purines and pyrimidines according to their chemical composition. Purines include adenine… More >

Ahmed B. Khoshaim¹, Saleem Abdullah², Shahzaib Ashraf^3,*, Muhammad Naeem⁴

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 4077-4094, 2021, DOI:10.32604/cmc.2021.016973

Abstract With the frequent occurrences of emergency events, emergency decision making (EDM) plays an increasingly significant role in coping with such situations and has become an important and challenging research area in recent times. It is essential for decision makers to make reliable and reasonable emergency decisions within a short span of time, since inappropriate decisions may result in enormous economic losses and social disorder. To handle emergency effectively and quickly, this paper proposes a new EDM method based on the novel concept of q-rung orthopair fuzzy rough (q-ROPR) set. A novel list of q-ROFR aggregation information, detailed description of the… More >

Ibrahim M. Almanjahie^1,2,*, Javid Gani Dar³, Amer Ibrahim Al-Omari⁴, Aijaz Mir⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 907-925, 2021, DOI:10.32604/cmes.2021.014896

Abstract Many researchers measure the uncertainty of a random variable using quantile-based entropy techniques. These techniques are useful in engineering applications and have some exceptional characteristics than their distribution function method. Considering order statistics, the key focus of this article is to propose new quantile-based Mathai-Haubold entropy and investigate its characteristics. The divergence measure of the Mathai-Haubold is also considered and some of its properties are established. Further, based on order statistics, we propose the residual entropy of the quantile-based Mathai-Haubold and some of its property results are proved. The performance of the proposed quantile-based Mathai-Haubold entropy is investigated by simulation… More >

Yabin Xu^1,2,*, Peiyuan Gu², Xiaowei Xu³

Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 113-127, 2021, DOI:10.32604/iasc.2021.018895

Abstract In order to effectively detect interest flooding attack (IFA) in Named Data Networking (NDN), this paper proposes a detection method of interest flooding attack based on chi-square test and similarity test. Firstly, it determines the detection window size based on the distribution of information name prefixes (that is information entropy) in the current network traffic. The attackers may append arbitrary random suffix to a certain prefix in the network traffic, and then send a large number of interest packets that cannot get the response. Targeted at this problem, the sensitivity of chi-square test is used to detect the change of… More >

Simy Mary Kurian¹, Sujitha Juliet Devaraj^1,*, Vinodh P. Vijayan²

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2093-2109, 2021, DOI:10.32604/cmc.2021.018090

Abstract Magnetic resonance imaging (MRI) is an essential tool for detecting brain tumours. However, identification of brain tumours in the early stages is a very complex task since MRI images are susceptible to noise and other environmental obstructions. In order to overcome these problems, a Gamma MAP denoised Strömberg wavelet segmentation based on a maximum entropy classifier (GMDSWS-MEC) model is developed for efficient tumour detection with high accuracy and low time consumption. The GMDSWS-MEC model performs three steps, namely pre-processing, segmentation, and classification. Within the GMDSWS-MEC model, the Gamma MAP filter performs the pre-processing task and achieves a significant increase in… More >

Lina Wang^1,2,*, Qixiang Zhang¹, Xiling Niu¹, Yongjun Ren³, Jinyue Xia⁴

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1765-1781, 2021, DOI:10.32604/cmc.2021.017516

Abstract Outlier detection is a key research area in data mining technologies, as outlier detection can identify data inconsistent within a data set. Outlier detection aims to find an abnormal data size from a large data size and has been applied in many fields including fraud detection, network intrusion detection, disaster prediction, medical diagnosis, public security, and image processing. While outlier detection has been widely applied in real systems, its effectiveness is challenged by higher dimensions and redundant data attributes, leading to detection errors and complicated calculations. The prevalence of mixed data is a current issue for outlier detection algorithms. An… More >

Lei Hong^1,*, Jie Yin¹, Ling-Ling Xia¹, Chao-Fan Gong¹, Qi Huang²

Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 437-449, 2021, DOI:10.32604/iasc.2021.016259

Abstract The short-video platform is a social network where users’ content accelerates the speed of information dissemination. Hence, it is necessary to identify important users to effectively obtain information. Four algorithms (Followers Rank, Average Forwarding, K Coverage, and Expert Survey and Evaluation) have been proposed to calculate users’ influence and determine their importance. These methods simply take the number of a user’s fans or posts as the standard of influence evaluation, ignoring factors such as the paid posters, which makes such evaluations inaccurate. To solve these problems, we propose the short-video user influence rank (SVUIR) algorithm, which combines direct and indirect… More >