K. Lavanya^1,*, K. Vimala Devi², B. R. Tapas Bapu³

Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 837-848, 2022, DOI:10.32604/iasc.2022.023055 - 03 May 2022

Abstract Multipath TCP (SMPTCP) has gained more attention as a valuable approach for IoT systems. SMPTCP is introduced as an evolution of Transmission Control Protocol (TCP) to pass packets simultaneously across several routes to completely exploit virtual networks on multi-homed consoles and other network services. The current multipath networking algorithms and simulation software strategies are confronted with sub-flow irregularity issues due to network heterogeneity, and routing configuration issues can be fixed adequately. To overcome the issues, this paper proposes a novel deep reinforcement-based extreme learning machines (DRLELM) approach to examine the complexities between routes, pathways, sub-flows, More >

Hiam Alquran^1,2, Wan Azani Mustafa^3,4,*, Isam Abu Qasmieh², Yasmeen Mohd Yacob^3,4, Mohammed Alsalatie⁵, Yazan Al-Issa⁶, Ali Mohammad Alqudah²

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5117-5134, 2022, DOI:10.32604/cmc.2022.025692 - 21 April 2022

Abstract Cervical cancer is screened by pap smear methodology for detection and classification purposes. Pap smear images of the cervical region are employed to detect and classify the abnormality of cervical tissues. In this paper, we proposed the first system that it ables to classify the pap smear images into a seven classes problem. Pap smear images are exploited to design a computer-aided diagnoses system to classify the abnormality in cervical images cells. Automated features that have been extracted using ResNet101 are employed to discriminate seven classes of images in Support Vector Machine (SVM) classifier. The… More >

Nawaf Alhebaishi¹, Abdulrhman M. Alshareef¹, Tawfiq Hasanin¹, Raed Alsini¹, Gyanendra Prasad Joshi², Seongsoo Cho³, Doo Ill Chul^4,*

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5233-5250, 2022, DOI:10.32604/cmc.2022.025596 - 21 April 2022

Abstract In recent times, internet of things (IoT) applications on the cloud might not be the effective solution for every IoT scenario, particularly for time sensitive applications. A significant alternative to use is edge computing that resolves the problem of requiring high bandwidth by end devices. Edge computing is considered a method of forwarding the processing and communication resources in the cloud towards the edge. One of the considerations of the edge computing environment is resource management that involves resource scheduling, load balancing, task scheduling, and quality of service (QoS) to accomplish improved performance. With this… More >

Mahmoud Ragab^1,2,3,*, Diaa Hamed^4,5

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 4185-4200, 2022, DOI:10.32604/cmc.2022.027074 - 29 March 2022

Abstract Medical data classification becomes a hot research topic in the healthcare sector to aid physicians in the healthcare sector for decision making. Besides, the advances of machine learning (ML) techniques assist to perform the effective classification task. With this motivation, this paper presents a Fuzzy Clustering Approach Based on Breadth-first Search Algorithm (FCA-BFS) with optimal support vector machine (OSVM) model, named FCABFS-OSVM for medical data classification. The proposed FCABFS-OSVM technique intends to classify the healthcare data by the use of clustering and classification models. Besides, the proposed FCABFS-OSVM technique involves the design of FCABFS technique More >

S. Prakash^1,*, P. Vishnu Raja², A. Baseera³, D. Mansoor Hussain⁴, V. R. Balaji⁵, K. Venkatachalam⁶

Computer Systems Science and Engineering, Vol.42, No.3, pp. 1273-1287, 2022, DOI:10.32604/csse.2022.021784 - 08 February 2022

Abstract Urban living in large modern cities exerts considerable adverse effects on health and thus increases the risk of contracting several chronic kidney diseases (CKD). The prediction of CKDs has become a major task in urbanized countries. The primary objective of this work is to introduce and develop predictive analytics for predicting CKDs. However, prediction of huge samples is becoming increasingly difficult. Meanwhile, MapReduce provides a feasible framework for programming predictive algorithms with map and reduce functions. The relatively simple programming interface helps solve problems in the scalability and efficiency of predictive learning algorithms. In the… More >

Marwa M. Eid^1,*, Fawaz Alassery², Abdelhameed Ibrahim³, Mohamed Saber⁴

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4627-4641, 2022, DOI:10.32604/cmc.2022.024043 - 14 January 2022

Abstract Digital signal processing of electroencephalography (EEG) data is now widely utilized in various applications, including motor imagery classification, seizure detection and prediction, emotion classification, mental task classification, drug impact identification and sleep state classification. With the increasing number of recorded EEG channels, it has become clear that effective channel selection algorithms are required for various applications. Guided Whale Optimization Method (Guided WOA), a suggested feature selection algorithm based on Stochastic Fractal Search (SFS) technique, evaluates the chosen subset of channels. This may be used to select the optimum EEG channels for use in Brain-Computer Interfaces More >

El-Sayed M. El-kenawy^1,2, Abdelhameed Ibrahim^3,*, Seyedali Mirjalili^4,5, Yu-Dong Zhang⁶, Shaima Elnazer^7,8, Rokaia M. Zaki^9,10

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4989-5003, 2022, DOI:10.32604/cmc.2022.023884 - 14 January 2022

Abstract Metamaterial Antenna is a subclass of antennas that makes use of metamaterial to improve performance. Metamaterial antennas can overcome the bandwidth constraint associated with tiny antennas. Machine learning is receiving a lot of interest in optimizing solutions in a variety of areas. Machine learning methods are already a significant component of ongoing research and are anticipated to play a critical role in today's technology. The accuracy of the forecast is mostly determined by the model used. The purpose of this article is to provide an optimal ensemble model for predicting the bandwidth and gain of… More >

J. Sampathkumar^*, N. Malmurugan

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2107-2123, 2022, DOI:10.32604/cmc.2022.019983 - 07 December 2021

Abstract Wireless Sensor Network is considered as the intermediate layer in the paradigm of Internet of things (IoT) and its effectiveness depends on the mode of deployment without sacrificing the performance and energy efficiency. WSN provides ubiquitous access to location, the status of different entities of the environment and data acquisition for long term IoT monitoring. Achieving the high performance of the WSN-IoT network remains to be a real challenge since the deployment of these networks in the large area consumes more power which in turn degrades the performance of the networks. So, developing the robust… More >

Tahir Alyas¹, Iqra Javed¹, Abdallah Namoun², Ali Tufail², Sami Alshmrany², Nadia Tabassum^3,*

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3019-3033, 2022, DOI:10.32604/cmc.2022.019836 - 07 December 2021

Abstract Efforts were exerted to enhance the live virtual machines (VMs) migration, including performance improvements of the live migration of services to the cloud. The VMs empower the cloud users to store relevant data and resources. However, the utilization of servers has increased significantly because of the virtualization of computer systems, leading to a rise in power consumption and storage requirements by data centers, and thereby the running costs. Data center migration technologies are used to reduce risk, minimize downtime, and streamline and accelerate the data center move process. Indeed, several parameters, such as non-network overheads… More >

Fuad A.M. Al-Yarimi^1,*, Sami Althahabi¹, Majdy Mohammed Eltayeb²

Computer Systems Science and Engineering, Vol.41, No.3, pp. 919-932, 2022, DOI:10.32604/csse.2022.021272 - 10 November 2021

Abstract Cloud resource scheduling is gaining prominence with the increasing trends of reliance on cloud infrastructure solutions. Numerous sets of cloud resource scheduling models were evident in the literature. Cloud resource scheduling refers to the distinct set of algorithms or programs the service providers engage to maintain the service level allocation for various resources over a virtual environment. The model proposed in this manuscript schedules resources of virtual machines under potential volatility aspects, which can be applied for any priority metric chosen by the server administrators. Also, the model can be flexible for any time frame-based More >