Atif Naseer^1,*, Enrique Nava Baro¹, Sultan Daud Khan², Yolanda Vila³, Jennifer Doyle⁴

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5321-5344, 2022, DOI:10.32604/cmc.2022.020886 - 11 October 2021

Abstract The Norway lobster, Nephrops norvegicus, is one of the main commercial crustacean fisheries in Europe. The abundance of Nephrops norvegicus stocks is assessed based on identifying and counting the burrows where they live from underwater videos collected by camera systems mounted on sledges. The Spanish Oceanographic Institute (IEO) and Marine Institute Ireland (MI-Ireland) conducts annual underwater television surveys (UWTV) to estimate the total abundance of Nephrops within the specified area, with a coefficient of variation (CV) or relative standard error of less than 20%. Currently, the identification and counting of the Nephrops burrows are carried out manually by… More >

Taher M. Ghazal^1,2, Sagheer Abbas³, Sundus Munir^3,4, M. A. Khan⁵, Munir Ahmad³, Ghassan F. Issa², Syeda Binish Zahra⁴, Muhammad Adnan Khan^6,*, Mohammad Kamrul Hasan¹

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5005-5019, 2022, DOI:10.32604/cmc.2022.020866 - 11 October 2021

Abstract Alzheimer's disease is a severe neuron disease that damages brain cells which leads to permanent loss of memory also called dementia. Many people die due to this disease every year because this is not curable but early detection of this disease can help restrain the spread. Alzheimer's is most common in elderly people in the age bracket of 65 and above. An automated system is required for early detection of disease that can detect and classify the disease into multiple Alzheimer classes. Deep learning and machine learning techniques are used to solve many medical problems More >

K. S. Bhuvaneshwari¹, K. Venkatachalam², S. Hubálovský^3,*, P. Trojovský⁴, P. Prabu⁵

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5949-5965, 2022, DOI:10.32604/cmc.2022.020769 - 11 October 2021

Abstract With the rapid growth of internet based services and the data generated on these services are attracted by the attackers to intrude the networking services and information. Based on the characteristics of these intruders, many researchers attempted to aim to detect the intrusion with the help of automating process. Since, the large volume of data is generated and transferred through network, the security and performance are remained an issue. IDS (Intrusion Detection System) was developed to detect and prevent the intruders and secure the network systems. The performance and loss are still an issue because… More >

Abrar M. Alajlan^*

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4241-4259, 2022, DOI:10.32604/cmc.2022.020585 - 11 October 2021

Abstract Detection of the wormhole attacks is a cumbersome process, particularly simplex and duplex over the wireless sensor networks (WSNs). Wormhole attacks are characterized as distributed passive attacks that can destabilize or disable WSNs. The distributed passive nature of these attacks makes them enormously challenging to detect. The main objective is to find all the possible ways in which how the wireless sensor network’s broadcasting character and transmission medium allows the attacker to interrupt network within the distributed environment. And further to detect the serious routing-disruption attack “Wormhole Attack” step by step through the different network More >

Mohamed Yacin Sikkandar^1,*, S. Sabarunisha Begum², Abdulaziz A. Alkathiry³, Mashhor Shlwan N. Alotaibi¹, Md Dilsad Manzar⁴

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4279-4291, 2022, DOI:10.32604/cmc.2022.020571 - 11 October 2021

Abstract Knee Osteoarthritis (KOA) is a degenerative knee joint disease caused by ‘wear and tear’ of ligaments between the femur and tibial bones. Clinically, KOA is classified into four grades ranging from 1 to 4 based on the degradation of the ligament in between these two bones and causes suffering from impaired movement. Identifying this space between bones through the anterior view of a knee X-ray image is solely subjective and challenging. Automatic classification of this process helps in the selection of suitable treatment processes and customized knee implants. In this research, a new automatic classification More >

Aayesha¹, Muhammad Bilal Qureshi², Muhammad Afzaal³, Muhammad Shuaib Qureshi⁴, Jeonghwan Gwak^5,6,7,8,*

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5601-5630, 2022, DOI:10.32604/cmc.2022.020348 - 11 October 2021

Abstract Detection of epileptic seizures on the basis of Electroencephalogram (EEG) recordings is a challenging task due to the complex, non-stationary and non-linear nature of these biomedical signals. In the existing literature, a number of automatic epileptic seizure detection methods have been proposed that extract useful features from EEG segments and classify them using machine learning algorithms. Some characterizing features of epileptic and non-epileptic EEG signals overlap; therefore, it requires that analysis of signals must be performed from diverse perspectives. Few studies analyzed these signals in diverse domains to identify distinguishing characteristics of epileptic EEG signals.… More >

Azam Zaka¹, Riffat Jabeen^2,*, Kanwal Iqbal Khan³

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4781-4802, 2022, DOI:10.32604/cmc.2022.020316 - 11 October 2021

Abstract The continuous monitoring of the machine is beneficial in improving its process reliability through reflected power function distribution. It is substantial for identifying and removing errors at the early stages of production that ultimately benefit the firms in cost-saving and quality improvement. The current study introduces control charts that help the manufacturing concerns to keep the production process in control. It presents an exponentially weighted moving average and extended exponentially weighted moving average and then compared their performance. The percentiles estimator and the modified maximum likelihood estimator are used to constructing the control charts. The More >

Abeer D. Algarni^1,*, Walid El-Shafai², Ghada M. El Banby³, Fathi E. Abd El-Samie^1,2, Naglaa F. Soliman^1,4

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4393-4410, 2022, DOI:10.32604/cmc.2022.020265 - 11 October 2021

Abstract COVID-19 remains to proliferate precipitously in the world. It has significantly influenced public health, the world economy, and the persons’ lives. Hence, there is a need to speed up the diagnosis and precautions to deal with COVID-19 patients. With this explosion of this pandemic, there is a need for automated diagnosis tools to help specialists based on medical images. This paper presents a hybrid Convolutional Neural Network (CNN)-based classification and segmentation approach for COVID-19 detection from Computed Tomography (CT) images. The proposed approach is employed to classify and segment the COVID-19, pneumonia, and normal CT… More >

Raniyah Wazirali¹, Rami Ahmad^2,*

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4922-4946, 2022, DOI:10.32604/cmc.2022.020044 - 11 October 2021

Abstract Energy and security remain the main two challenges in Wireless Sensor Networks (WSNs). Therefore, protecting these WSN networks from Denial of Service (DoS) and Distributed DoS (DDoS) is one of the WSN networks security tasks. Traditional packet deep scan systems that rely on open field inspection in transport layer security packets and the open field encryption trend are making machine learning-based systems the only viable choice for these types of attacks. This paper contributes to the evaluation of the use machine learning algorithms in WSN nodes traffic and their effect on WSN network life time.… More >

Anwer Mustafa Hilal^1,*, Fahd N. Al-Wesabi^2,3, Mohammed Alamgeer⁴, Manar Ahmed Hamza¹, Mohammad Mahzari⁵, Murad A. Almekhlafi⁶

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5583-5600, 2022, DOI:10.32604/cmc.2022.019686 - 11 October 2021

Abstract Due to the rapid increase in the exchange of text information via internet networks, the security and authenticity of digital content have become a major research issue. The main challenges faced by researchers are how to hide the information within the text to use it later for authentication and attacks tampering detection without effects on the meaning and size of the given digital text. In this paper, an efficient text-based watermarking method has been proposed for detecting the illegal tampering attacks on the Arabic text transmitted online via an Internet network. Towards this purpose, the accuracy… More >