Atif Ishaq Khan¹, Syed Asad Raza Kazmi¹, Ayesha Atta^1,*, Muhammad Faheem Mushtaq², Muhammad Idrees³, Ilyas Fakir¹, Muhammad Safyan¹, Muhammad Adnan Khan⁴, Awais Qasim¹

CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 519-528, 2021, DOI:10.32604/cmc.2021.013865

Abstract Cloud computing is seeking attention as a new computing paradigm to handle operations more efficiently and cost-effectively. Cloud computing uses dynamic resource provisioning and de-provisioning in a virtualized environment. The load on the cloud data centers is growing day by day due to the rapid growth in cloud computing demand. Elasticity in cloud computing is one of the fundamental properties, and elastic load balancing automatically distributes incoming load to multiple virtual machines. This work is aimed to introduce efficient resource provisioning and de-provisioning for better load balancing. In this article, a model is proposed in which the fuzzy logic approach… More >

Ebrahim Heidary¹, Hamïd Parvïn^2,3,4,*, Samad Nejatian^5,6, Karamollah Bagherifard^1,6, Vahideh Rezaie^6,7, Zulkefli Mansor⁸, Kim-Hung Pho⁹

CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 1085-1101, 2021, DOI:10.32604/cmc.2021.013836

Abstract Taking into account the increasing volume of text documents, automatic summarization is one of the important tools for quick and optimal utilization of such sources. Automatic summarization is a text compression process for producing a shorter document in order to quickly access the important goals and main features of the input document. In this study, a novel method is introduced for selective text summarization using the genetic algorithm and generation of repetitive patterns. One of the important features of the proposed summarization is to identify and extract the relationship between the main features of the input text and the creation… More >

Lewis Nkenyereye^1,*, S. M. Riazul Islam², Mahmud Hossain³, M. Abdullah-Al-Wadud⁴, Atif Alamri⁴

CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 211-221, 2021, DOI:10.32604/cmc.2021.013796

Abstract The Internet of Medical Things (IoMT) offers an infrastructure made of smart medical equipment and software applications for healthcare services. Through the internet, the IoMT is capable of providing remote medical diagnosis and timely health services. The patients can use their smart devices to create, store and share their electronic health records (EHR) with a variety of medical personnel including medical doctors and nurses. However, unless the underlying commination within IoMT is secured, malicious users can intercept, modify and even delete the sensitive EHR data of patients. Patients also lose full control of their EHR since most healthcare services within… More >

Mavra Mehmood¹, Ember Ayub¹, Fahad Ahmad^1,6,*, Madallah Alruwaili², Ziyad A. Alrowaili³, Saad Alanazi², Mamoona Humayun², Muhammad Rizwan¹, Shahid Naseem⁴, Tahir Alyas⁵

CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 641-657, 2021, DOI:10.32604/cmc.2021.013774

Abstract Clinical image processing plays a significant role in healthcare systems and is currently a widely used methodology. In carcinogenic diseases, time is crucial; thus, an image’s accurate analysis can help treat disease at an early stage. Ductal carcinoma in situ (DCIS) and lobular carcinoma in situ (LCIS) are common types of malignancies that affect both women and men. The number of cases of DCIS and LCIS has increased every year since 2002, while it still takes a considerable amount of time to recommend a controlling technique. Image processing is a powerful technique to analyze preprocessed images to retrieve useful information… More >

Hussain A. Younis^1,2, A. S. A. Mohamed^2,*, R. Jamaludin³, M. N. Ab Wahab²

CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 687-707, 2021, DOI:10.32604/cmc.2021.013746

Abstract The coronavirus disease 2019 (COVID-19) is characterized as a disease caused by a novel coronavirus known as severe acute respiratory coronavirus syndrome 2 (SARS-CoV-2; formerly known as 2019-nCoV). In December 2019, COVID-19 began to appear in a few countries. By the beginning of 2020, it had spread to most countries across the world. This is when education challenges began to arise. The COVID-19 crisis led to the closure of thousands of schools and universities all over the world. Such a situation requires reliance on e-learning and robotics education for students to continue their studies to avoid the mingling between people… More >

Priya Baldoss^1,2,*, Gnanasekaran Thangavel³

CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 253-265, 2021, DOI:10.32604/cmc.2021.013695

Abstract In the present scenario, cloud computing service provides on-request access to a collection of resources available in remote system that can be shared by numerous clients. Resources are in self-administration; consequently, clients can adjust their usage according to their requirements. Resource usage is estimated and clients can pay according to their utilization. In literature, the existing method describes the usage of various hardware assets. Quality of Service (QoS) needs to be considered for ascertaining the schedule and the access of resources. Adhering with the security arrangement, any additional code is forbidden to ensure the usage of resources complying with QoS.… More >

Peter Kvasnica^*

CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 159-170, 2021, DOI:10.32604/cmc.2021.013587

Abstract This article acquaints the public with the insights gained from conducting document searches in the Slovak public administration information system, when supported by knowledge of its management. Additionally, it discusses the advantages of simulating performance parameters and comparing the obtained results with the real parameters of the eZbierka (eCollection) legislation webpage. This comparison was based upon simulated results, obtained through the Gatling simulation tool, versus those obtained from measuring the properties of the public administration legislation webpage. Both sets of data (simulated and real), were generated via the the document search technologies in place on the eZbierka legislation webpage. The… More >

Ehsan Alibagheri¹, Bohayra Mortazavi², Timon Rabczuk^3,4,*

CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 1287-1300, 2021, DOI:10.32604/cmc.2021.013564

Abstract Machine-learning (ML) models are novel and robust tools to establish structure-to-property connection on the basis of computationally expensive ab-initio datasets. For advanced technologies, predicting novel materials and identifying their specification are critical issues. Two-dimensional (2D) materials are currently a rapidly growing class which show highly desirable properties for diverse advanced technologies. In this work, our objective is to search for desirable properties, such as the electronic band gap and total energy, among others, for which the accelerated prediction is highly appealing, prior to conducting accurate theoretical and experimental investigations. Among all available componential methods, gradient-boosted (GB) ML algorithms are known… More >

Lingyun Xiang^1,2, Guohan Zhao¹, Qian Li³, Gwang-Jun Kim^4,*, Osama Alfarraj⁵, Amr Tolba^5,6

CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 267-284, 2021, DOI:10.32604/cmc.2021.013488

Abstract Multiple kernel clustering is an unsupervised data analysis method that has been used in various scenarios where data is easy to be collected but hard to be labeled. However, multiple kernel clustering for incomplete data is a critical yet challenging task. Although the existing absent multiple kernel clustering methods have achieved remarkable performance on this task, they may fail when data has a high value-missing rate, and they may easily fall into a local optimum. To address these problems, in this paper, we propose an absent multiple kernel clustering (AMKC) method on incomplete data. The AMKC method first clusters the… More >

Jingming Xia¹, Yi Lu¹, Ling Tan^2,*, Ping Jiang³

CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 613-624, 2021, DOI:10.32604/cmc.2021.013457

Abstract Multi-source information can be obtained through the fusion of infrared images and visible light images, which have the characteristics of complementary information. However, the existing acquisition methods of fusion images have disadvantages such as blurred edges, low contrast, and loss of details. Based on convolution sparse representation and improved pulse-coupled neural network this paper proposes an image fusion algorithm that decompose the source images into high-frequency and low-frequency subbands by non-subsampled Shearlet Transform (NSST). Furthermore, the low-frequency subbands were fused by convolutional sparse representation (CSR), and the high-frequency subbands were fused by an improved pulse coupled neural network (IPCNN) algorithm,… More >