Jaleel Nazir^1,2, Muhammad Waseem Iqbal¹, Tahir Alyas², Muhammad Hamid³, Muhammad Saleem⁴, Saadia Malik⁵, Nadia Tabassum^6,*

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1479-1490, 2022, DOI:10.32604/cmc.2022.019344

Abstract Load balancing is a technique for identifying overloaded and underloaded nodes and balancing the load between them. To maximize various performance parameters in cloud computing, researchers suggested various load balancing approaches. To store and access data and services provided by the different service providers through the network over different regions, cloud computing is one of the latest technology systems for both end-users and service providers. The volume of data is increasing due to the pandemic and a significant increase in usage of the internet has also been experienced. Users of the cloud are looking for services that are intelligent, and,… More >

R. Chithra Devi^1,*, D. Jemi Florinabel², Narayanan Prasanth³

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1527-1540, 2022, DOI:10.32604/cmc.2022.019343

Abstract The high-performance computing paradigm needs high-speed switching fabrics to meet the heavy traffic generated by their applications. These switching fabrics are efficiently driven by the deployed scheduling algorithms. In this paper, we proposed two scheduling algorithms for input queued switches whose operations are based on ranking procedures. At first, we proposed a Simple 2-Bit (S2B) scheme which uses binary ranking procedure and queue size for scheduling the packets. Here, the Virtual Output Queue (VOQ) set with maximum number of empty queues receives higher rank than other VOQ’s. Through simulation, we showed S2B has better throughput performance than Highest Ranking First… More >

P. Baskaran^1,*, K. Karuppasamy²

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1975-1992, 2022, DOI:10.32604/cmc.2022.019342

Abstract In a wireless sensor network (WSN), data gathering is more effectually done with the clustering process. Clustering is a critical strategy for improving energy efficiency and extending the longevity of a network. Hierarchical modeling-based clustering is proposed to enhance energy efficiency where nodes that hold higher residual energy may be clustered to collect data and broadcast it to the base station. Moreover, existing approaches may not consider data redundancy while collecting data from adjacent nodes or overlapping nodes. Here, an improved clustering approach is anticipated to attain energy efficiency by implementing MapReduction for regulating mapping and reducing complexity in routing… More >

Iram Mushtaq¹, Muhammad Umer¹, Muhammad Imran², Inzamam Mashood Nasir³, Ghulam Muhammad^4,*, Mohammad Shorfuzzaman⁵

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 59-72, 2022, DOI:10.32604/cmc.2022.019337

Abstract During COVID-19, the escalated demand for various pharmaceutical products with the existing production capacity of pharmaceutical companies has stirred the need to prioritize its customers in order to fulfill their demand. This study considers a two-echelon pharmaceutical supply chain considering various pharma-distributors as its suppliers and hospitals, pharmacies, and retail stores as its customers. Previous studies have generally considered a balanced situation in terms of supply and demand whereas this study considers a special situation of COVID-19 pandemic where demand exceeds supply Various criteria have been identified from the literature that influences the selection of customers. A questionnaire has been… More >

M. Buvana¹, K. Muthumayil², S. Senthil kumar³, Jamel Nebhen⁴, Sultan S. Alshamrani⁵, Ihsan Ali^6,*

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 43-58, 2022, DOI:10.32604/cmc.2022.019331

Abstract Coronavirus (COVID-19) outbreak was first identified in Wuhan, China in December 2019. It was tagged as a pandemic soon by the WHO being a serious public medical condition worldwide. In spite of the fact that the virus can be diagnosed by qRT-PCR, COVID-19 patients who are affected with pneumonia and other severe complications can only be diagnosed with the help of Chest X-Ray (CXR) and Computed Tomography (CT) images. In this paper, the researchers propose to detect the presence of COVID-19 through images using Best deep learning model with various features. Impressive features like Speeded-Up Robust Features (SURF), Features from… More >

Zelin Deng^1,*, Bo Zhou¹, Pei He², Jianfeng Huang³, Osama Alfarraj⁴, Amr Tolba^4,5

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 2065-2081, 2022, DOI:10.32604/cmc.2022.019328

Abstract Image captioning aims to generate a corresponding description of an image. In recent years, neural encoder-decoder models have been the dominant approaches, in which the Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM) are used to translate an image into a natural language description. Among these approaches, the visual attention mechanisms are widely used to enable deeper image understanding through fine-grained analysis and even multiple steps of reasoning. However, most conventional visual attention mechanisms are based on high-level image features, ignoring the effects of other image features, and giving insufficient consideration to the relative positions between image features.… More >

R. Sujitha^*, B. Paramasivan

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1557-1572, 2022, DOI:10.32604/cmc.2022.019323

Abstract With the modernization of machine learning techniques in healthcare, different innovations including support vector machine (SVM) have predominantly played a major role in classifying lung cancer, predicting coronavirus disease 2019, and other diseases. In particular, our algorithm focuses on integrated datasets as compared with other existing works. In this study, parallel-based SVM (P-SVM) and multiclass-based multiple submodels (MMSM-SVM) were used to analyze the optimal classification of lung diseases. This analysis aimed to find the optimal classification of lung diseases with id and stages, such as key-value pairs in MapReduce combined with P-SVM and MMSVM for binary and multiclasses, respectively. For… More >

Mohammad Sh. Daoud¹, Areej Fatima², Waseem Ahmad Khan³, Muhammad Adnan Khan^4,5,*, Sagheer Abbas³, Baha Ihnaini⁶, Munir Ahmad³, Muhammad Sheraz Javeid⁷, Shabib Aftab³

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 109-121, 2022, DOI:10.32604/cmc.2022.019295

Abstract The numbers of multimedia applications and their users increase with each passing day. Different multi-carrier systems have been developed along with varying techniques of space-time coding to address the demand of the future generation of network systems. In this article, a fuzzy logic empowered adaptive backpropagation neural network (FLeABPNN) algorithm is proposed for joint channel and multi-user detection (CMD). FLeABPNN has two stages. The first stage estimates the channel parameters, and the second performs multi-user detection. The proposed approach capitalizes on a neuro-fuzzy hybrid system that combines the competencies of both fuzzy logic and neural networks. This study analyzes the… More >

Awais Mahmood^1,*, Muhammad Imran², Aun Irtaza³, Qammar Abbas⁴, Habib Dhahri^1,5, Esam Mohammed Asem Othman¹, Arif Jamal Malik⁶, Aaqif Afzaal Abbasi⁶

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 963-979, 2022, DOI:10.32604/cmc.2022.019291

Abstract Searching images from the large image databases is one of the potential research areas of multimedia research. The most challenging task for nay CBIR system is to capture the high level semantic of user. The researchers of multimedia domain are trying to fix this issue with the help of Relevance Feedback (RF). However existing RF based approaches needs a number of iteration to fulfill user's requirements. This paper proposed a novel methodology to achieve better results in early iteration to reduce the user interaction with the system. In previous research work it is reported that SVM based RF approach generating… More >

Ishaani Priyadarshini^*, Chase Cotton

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 781-800, 2022, DOI:10.32604/cmc.2022.019284

Abstract

The increasing capabilities of Artificial Intelligence (AI), has led researchers and visionaries to think in the direction of machines outperforming humans by gaining intelligence equal to or greater than humans, which may not always have a positive impact on the society. AI gone rogue, and Technological Singularity are major concerns in academia as well as the industry. It is necessary to identify the limitations of machines and analyze their incompetence, which could draw a line between human and machine intelligence. Internet memes are an amalgam of pictures, videos, underlying messages, ideas, sentiments, humor, and experiences, hence the way an internet… More >