T. Gopalakrishnan¹, Mohamed Yacin Sikkandar², Raed Abdullah Alharbi³, P. Selvaraj⁴, Zahraa H. Kareem⁵, Ahmed Alkhayyat^6,*, Ali Hashim Abbas⁷

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6195-6212, 2023, DOI:10.32604/cmc.2023.033252 - 28 December 2022

Abstract The Coronavirus Disease (COVID-19) pandemic has exposed the vulnerabilities of medical services across the globe, especially in underdeveloped nations. In the aftermath of the COVID-19 outbreak, a strong demand exists for developing novel computer-assisted diagnostic tools to execute rapid and cost-effective screenings in locations where many screenings cannot be executed using conventional methods. Medical imaging has become a crucial component in the disease diagnosis process, whereas X-rays and Computed Tomography (CT) scan imaging are employed in a deep network to diagnose the diseases. In general, four steps are followed in image-based diagnostics and disease classification… More >

Fuat Türk^*

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1357-1373, 2023, DOI:10.32604/csse.2023.030772 - 03 November 2022

Abstract Covid-19 is a deadly virus that is rapidly spread around the world towards the end of the 2020. The consequences of this virus are quite frightening, especially when accompanied by an underlying disease. The novelty of the virus, the constant emergence of different variants and its rapid spread have a negative impact on the control and treatment process. Although the new test kits provide almost certain results, chest X-rays are extremely important to detect the progression and degree of the disease. In addition to the Covid-19 virus, pneumonia and harmless opacity of the lungs also… More >

S. Sadhasivam¹, P. Valarmathie², K. Dinakaran^3,*

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 461-479, 2023, DOI:10.32604/iasc.2023.028650 - 29 September 2022

Abstract With the vast advancements in Information Technology, the emergence of Online Social Networking (OSN) has also hit its peak and captured the attention of the young generation people. The clone intends to replicate the users and inject massive malicious activities that pose a crucial security threat to the original user. However, the attackers also target this height of OSN utilization, explicitly creating the clones of the user’s account. Various clone detection mechanisms are designed based on social-network activities. For instance, monitoring the occurrence of clone edges is done to restrict the generation of clone activities.… More >

Narendran Sobanapuram Muruganandam, Umamakeswari Arumugam^*

Computer Systems Science and Engineering, Vol.44, No.2, pp. 979-989, 2023, DOI:10.32604/csse.2023.024943 - 15 June 2022

Abstract In forecasting real time environmental factors, large data is needed to analyse the pattern behind the data values. Air pollution is a major threat towards developing countries and it is proliferating every year. Many methods in time series prediction and deep learning models to estimate the severity of air pollution. Each independent variable contributing towards pollution is necessary to analyse the trend behind the air pollution in that particular locality. This approach selects multivariate time series and coalesce a real time updatable autoregressive model to forecast Particulate matter (PM) PM2.5. To perform experimental analysis the… More >

Amel Ali Alhussan¹, El-Sayed M. El-kenawy^2,3, Hussah Nasser AlEisa^1,*, M. El-SAID^4,5, Sayed A. Ward^6,7, Doaa Sami Khafaga¹

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2619-2635, 2022, DOI:10.32604/cmc.2022.030445 - 16 June 2022

Abstract Effective technology for wind direction forecasting can be realized using the recent advances in machine learning. Consequently, the stability and safety of power systems are expected to be significantly improved. However, the unstable and unpredictable qualities of the wind predict the wind direction a challenging problem. This paper proposes a practical forecasting approach based on the weighted ensemble of machine learning models. This weighted ensemble is optimized using a whale optimization algorithm guided by particle swarm optimization (PSO-Guided WOA). The proposed optimized weighted ensemble predicts the wind direction given a set of input features. The… More >

Abdelaziz A. Abdelhamid^1,3,*, Sultan R. Alotaibi²

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 917-933, 2022, DOI:10.32604/cmc.2022.027653 - 18 May 2022

Abstract Employing machine learning techniques in predicting the parameters of metamaterial antennas has a significant impact on the reduction of the time needed to design an antenna with optimal parameters using simulation tools. In this paper, we propose a new approach for predicting the bandwidth of metamaterial antenna using a novel ensemble model. The proposed ensemble model is composed of two levels of regression models. The first level consists of three strong models namely, random forest, support vector regression, and light gradient boosting machine. Whereas the second level is based on the ElasticNet regression model, which… More >

Heba A. Elzeheiry^*, Sherief Barakat, Amira Rezk

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1283-1305, 2022, DOI:10.32604/cmc.2022.027345 - 18 May 2022

Abstract Electronic Health Records (EHRs) are the digital form of patients’ medical reports or records. EHRs facilitate advanced analytics and aid in better decision-making for clinical data. Medical data are very complicated and using one classification algorithm to reach good results is difficult. For this reason, we use a combination of classification techniques to reach an efficient and accurate classification model. This model combination is called the Ensemble model. We need to predict new medical data with a high accuracy value in a small processing time. We propose a new ensemble model MDRL which is efficient… 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 >

CANGZHI JIA¹, DONG JIN¹, XIN WANG¹, QI ZHAO^2,*

BIOCELL, Vol.46, No.4, pp. 1105-1121, 2022, DOI:10.32604/biocell.2022.016655 - 15 December 2021

Abstract N⁶-Methyladenine is a dynamic and reversible post translational modification, which plays an essential role in various biological processes. Because of the current inability to identify m6A-containing mRNAs, computational approaches have been developed to identify m6A sites in DNA sequences. Aiming to improve prediction performance, we introduced a novel ensemble computational approach based on three hybrid deep neural networks, including a convolutional neural network, a capsule network, and a bidirectional gated recurrent unit (BiGRU) with the self-attention mechanism, to identify m6A sites in four tissues of three species. Across a total of 11 datasets, we selected different More >

Abdelhameed Ibrahim^1,*, Hattan F. Abutarboush², Ali Wagdy Mohamed^3,4, Mohamad Fouad¹, El-Sayed M. El-kenawy^5,6

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 199-213, 2022, DOI:10.32604/cmc.2022.021886 - 03 November 2021

Abstract Metamaterial Antenna is a special class of antennas that uses metamaterial to enhance their performance. Antenna size affects the quality factor and the radiation loss of the antenna. Metamaterial antennas can overcome the limitation of bandwidth for small antennas. Machine learning (ML) model is recently applied to predict antenna parameters. ML can be used as an alternative approach to the trial-and-error process of finding proper parameters of the simulated antenna. The accuracy of the prediction depends mainly on the selected model. Ensemble models combine two or more base models to produce a better-enhanced model. In… More >