Nitin Mittal¹, Harbinder Singh¹, Vikas Mittal², Shubham Mahajan³, Amit Kant Pandit³, Mehedi Masud⁴, Mohammed Baz⁵, Mohamed Abouhawwash^6,7,*

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3821-3835, 2022, DOI:10.32604/cmc.2022.020592

Abstract Cognitive Radio (CR) has been developed as an enabling technology that allows the unused or underused spectrum to be used dynamically to increase spectral efficiency. To improve the overall performance of the CR system it is extremely important to adapt or reconfigure the system parameters. The Decision Engine is a major module in the CR-based system that not only includes radio monitoring and cognition functions but also responsible for parameter adaptation. As meta-heuristic algorithms offer numerous advantages compared to traditional mathematical approaches, the performance of these algorithms is investigated in order to design an efficient CR system that is able… More >

Muhammad Ibrahim Khalil¹, Samabia Tehsin¹, Mamoona Humayun², N.Z Jhanjhi^3,4,*, Mohammed A. AlZain⁵

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3251-3265, 2022, DOI:10.32604/cmc.2022.020561

Abstract Medical Imaging Segmentation is an essential technique for modern medical applications. It is the foundation of many aspects of clinical diagnosis, oncology, and computer-integrated surgical intervention. Although significant successes have been achieved in the segmentation of medical images, DL (deep learning) approaches. Manual delineation of OARs (organs at risk) is vastly dominant but it is prone to errors given the complex irregularities in shape, low texture diversity between tissues and adjacent blood area, patient-wide location of organisms, and weak soft tissue contrast across adjacent organs in CT images. Till now several models have been implemented on multi organs segmentation but… More >

Kailash Kumar^*, Ahmad Abdullah Aljabr

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3781-3801, 2022, DOI:10.32604/cmc.2022.020510

Abstract On average, every two years, the amount of data existing globally doubles. Software development will be affected and improved by Cyber-Physical Systems (CPS). The number of problems remained even though developments helped Information Technology experts extract better value from their storage investments. Because of poor interoperability between different vendors and devices, countless numbers of Storage Area Networks were created. Network setup used for data storage includes a complex and rigid arrangement of routers, switch, hosts/servers, storage arrays. We have evaluated the performance of routing protocol Transmission Control Protocol (TCP) and Fibre Channel Protocol (FCP) under different network scenario by Network… More >

Chih-Ta Yen^1,*, Sheng-Nan Chang², Liao Jia-Xian³, Yi-Kai Huang³

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2937-2952, 2022, DOI:10.32604/cmc.2022.020493

Abstract This study proposed a measurement platform for continuous blood pressure estimation based on dual photoplethysmography (PPG) sensors and a deep learning (DL) that can be used for continuous and rapid measurement of blood pressure and analysis of cardiovascular-related indicators. The proposed platform measured the signal changes in PPG and converted them into physiological indicators, such as pulse transit time (PTT), pulse wave velocity (PWV), perfusion index (PI) and heart rate (HR); these indicators were then fed into the DL to calculate blood pressure. The hardware of the experiment comprised 2 PPG components (i.e., Raspberry Pi 3 Model B and analog-to-digital… More >

Raissa Uskenbayeva¹, Aigerim Altayeva^1,*, Faryda Gusmanova², Gluyssya Abdulkarimova³, Saule Berkimbaeva⁴, Kuralay Dalbekova⁴, Azizah Suiman⁵, Akzhunis Zhanseitova⁶, Aliya Amreyeva²

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3837-3853, 2022, DOI:10.32604/cmc.2022.020491

Abstract Providing comfortable indoor air quality control in residential construction is an exceedingly important issue. This is due to the structure of the fast response controller of air quality. The presented work shows the breakdown and creation of a mathematical model for an interactive, nonlinear system for the required comfortable air quality. Furthermore, the paper refers to designing traditional proportional integral derivative regulators and proportional, integral, derivative regulators with independent parameters based on a backpropagation neural network. In the end, we perform the experimental outputs of a suggested backpropagation neural network-based proportional, integral, derivative controller and analyze model results by applying… More >

Suruchi Talwani¹, Khaled Alhazmi^2,*, Jimmy Singla¹, Hasan J. Alyamani³, Ali Kashif Bashir⁴

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3349-3364, 2022, DOI:10.32604/cmc.2022.020473

Abstract Cloud computing promises the advent of a new era of service boosted by means of virtualization technology. The process of virtualization means creation of virtual infrastructure, devices, servers and computing resources needed to deploy an application smoothly. This extensively practiced technology involves selecting an efficient Virtual Machine (VM) to complete the task by transferring applications from Physical Machines (PM) to VM or from VM to VM. The whole process is very challenging not only in terms of computation but also in terms of energy and memory. This research paper presents an energy aware VM allocation and migration approach to meet… More >

Fayez Alqahtani^1,*, Mohammed Amoon^2,3, Walid El-Shafai⁴

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3133-3150, 2022, DOI:10.32604/cmc.2022.020454

Abstract Patient medical information in all forms is crucial to keep private and secure, particularly when medical data communication occurs through insecure channels. Therefore, there is a bad need for protecting and securing the color medical images against impostors and invaders. In this paper, an optical medical image security approach is introduced. It is based on the optical bit-plane Jigsaw Transform (JT) and Fractional Fourier Transform (FFT). Different kernels with a lone lens and a single arbitrary phase code are exploited in this security approach. A preceding bit-plane scrambling process is conducted on the input color medical images prior to the… More >

Nebojsa Bacanin¹, Khaled Alhazmi^2,*, Miodrag Zivkovic¹, K. Venkatachalam³, Timea Bezdan¹, Jamel Nebhen⁴

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 4199-4215, 2022, DOI:10.32604/cmc.2022.020449

Abstract In the domain of artificial neural networks, the learning process represents one of the most challenging tasks. Since the classification accuracy highly depends on the weights and biases, it is crucial to find its optimal or suboptimal values for the problem at hand. However, to a very large search space, it is very difficult to find the proper values of connection weights and biases. Employing traditional optimization algorithms for this issue leads to slow convergence and it is prone to get stuck in the local optima. Most commonly, back-propagation is used for multi-layer-perceptron training and it can lead to vanishing… More >

S. Sharmila Devi^1,*, V. Bhanumathi²

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3609-3624, 2022, DOI:10.32604/cmc.2022.020426

Abstract Now a days, MOS Current Mode Logic (MCML) has emerged as a better alternative to Complementary Metal Oxide Semiconductor (CMOS) logic in digital circuits. Recent works have only traditional logic gates that have issues with information loss. Reversible logic is incorporated with MOS Current Mode Logic (MCML) in this proposed work to solve this problem, which is used for multiplier design, D Flip-Flop (DFF) and register. The minimization of power and area is the main aim of the work. In reversible logic, the count of outputs and inputs is retained as the same value for creating one-to-one mapping. A unique… More >

Ahmed Abdullah Alqarni¹, Nizar Alsharif¹, Nayeem Ahmad Khan^1,*, Lilia Georgieva², Eric Pardade³, Mohammed Y. Alzahrani¹

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 4075-4085, 2022, DOI:10.32604/cmc.2022.020389

Abstract The rapid growth and uptake of network-based communication technologies have made cybersecurity a significant challenge as the number of cyber-attacks is also increasing. A number of detection systems are used in an attempt to detect known attacks using signatures in network traffic. In recent years, researchers have used different machine learning methods to detect network attacks without relying on those signatures. The methods generally have a high false-positive rate which is not adequate for an industry-ready intrusion detection product. In this study, we propose and implement a new method that relies on a modular deep neural network for reducing the… More >