Raisa Nazir Ahmed Kazi^1,*, Manjur Kolhar², Faiza Rizwan²

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1237-1250, 2021, DOI:10.32604/cmc.2020.012707 - 26 November 2020

Abstract The widespread use of smartwatches has increased their specific and complementary activities in the health sector for patient’s prognosis. In this study, we propose a framework referred to as smart forecasting CardioWatch (SCW) to measure the heart-rate variation (HRV) for patients with myocardial infarction (MI) who live alone or are outside their homes. In this study, HRV is used as a vital alarming sign for patients with MI. The performance of the proposed framework is measured using machine learning and deep learning techniques, namely, support vector machine, logistic regression, and decision-tree classification techniques. The results More >

Ashutosh Kumar Dubey^1,*, Sushil Narang¹, Abhishek Kumar¹, Satya Murthy Sasubilli², Vicente García-Díaz³

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1921-1936, 2021, DOI:10.32604/cmc.2020.012151 - 26 November 2020

Abstract Novel Coronavirus Disease (COVID-19) is a communicable disease that originated during December 2019, when China officially informed the World Health Organization (WHO) regarding the constellation of cases of the disease in the city of Wuhan. Subsequently, the disease started spreading to the rest of the world. Until this point in time, no specific vaccine or medicine is available for the prevention and cure of the disease. Several research works are being carried out in the fields of medicinal and pharmaceutical sciences aided by data analytics and machine learning in the direction of treatment and early… More >

Muhammad Adnan Khan^1,*, Mubashar Habib¹, Shazia Saqib¹, Tahir Alyas¹, Khalid Masood Khan¹, Mohammed A. Al Ghamdi², Sultan H. Almotiri²

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 691-706, 2021, DOI:10.32604/cmc.2020.012542 - 30 October 2020

Abstract The innovation and development in data science have an impact in all trades of life. The commercialization of sport has encouraged players, coaches, and other concerns to use technology to be in better position than r their opponents. In the past, the focus was on improved training techniques for better physical performance. These days, sports analytics identify the patterns in the performance and highlight strengths and weaknesses of potential players. Sports analytics not only predict the performance of players in the near future but it also performs predictive modeling for a particular behavior of a… More >

Sadaf Qazi¹, Muhammad Usman¹, Azhar Mahmood¹, Aaqif Afzaal Abbasi², Muhammad Attique³, Yunyoung Nam^4,*

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 589-602, 2021, DOI:10.32604/cmc.2020.012507 - 30 October 2020

Abstract Immunization is a noteworthy and proven tool for eliminating lifethreating infectious diseases, child mortality and morbidity. Expanded Program on Immunization (EPI) is a nation-wide program in Pakistan to implement immunization activities, however the coverage is quite low despite the accessibility of free vaccination. This study proposes a defaulter prediction model for accurate identification of defaulters. Our proposed framework classifies defaulters at five different stages: defaulter, partially high, partially medium, partially low, and unvaccinated to reinforce targeted interventions by accurately predicting children at high risk of defaulting from the immunization schedule. Different machine learning algorithms are… More >

Muhammad Adnan Khan^1,*, Abdur Rehman², Khalid Masood Khan¹, Mohammed A. Al Ghamdi³, Sultan H. Almotiri³

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 467-480, 2021, DOI:10.32604/cmc.2020.013121 - 30 October 2020

Abstract Networks provide a significant function in everyday life, and cybersecurity therefore developed a critical field of study. The Intrusion detection system (IDS) becoming an essential information protection strategy that tracks the situation of the software and hardware operating on the network. Notwithstanding advancements of growth, current intrusion detection systems also experience dif- ficulties in enhancing detection precision, growing false alarm levels and identifying suspicious activities. In order to address above mentioned issues, several researchers concentrated on designing intrusion detection systems that rely on machine learning approaches. Machine learning models will accurately identify the underlying variations… More >

Muhammad Adnan Khan^1,*, Wajhe Ul Husnain Abidi^1,2, Mohammed A. Al Ghamdi³, Sultan H. Almotiri³, Shazia Saqib¹, Tahir Alyas¹, Khalid Masood Khan¹, Nasir Mahmood⁴

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 331-340, 2021, DOI:10.32604/cmc.2020.012148 - 30 October 2020

Abstract Forecasting future outbreaks can help in minimizing their spread. Influenza is a disease primarily found in animals but transferred to humans through pigs. In 1918, influenza became a pandemic and spread rapidly all over the world becoming the cause behind killing one-third of the human population and killing one-fourth of the pig population. Afterwards, that influenza became a pandemic several times on a local and global levels. In 2009, influenza ‘A’ subtype H1N1 again took many human lives. The disease spread like in a pandemic quickly. This paper proposes a forecasting modeling system for the… More >

Abdu Gumaei^1,2,*, Mabrook Al-Rakhami¹, Mohamad Mahmoud Al Rahhal³, Fahad Raddah H. Albogamy³, Eslam Al Maghayreh³, Hussain AlSalman¹

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 315-329, 2021, DOI:10.32604/cmc.2020.012045 - 30 October 2020

Abstract The fast spread of coronavirus disease (COVID-19) caused by SARSCoV-2 has become a pandemic and a serious threat to the world. As of May 30, 2020, this disease had infected more than 6 million people globally, with hundreds of thousands of deaths. Therefore, there is an urgent need to predict confirmed cases so as to analyze the impact of COVID-19 and practice readiness in healthcare systems. This study uses gradient boosting regression (GBR) to build a trained model to predict the daily total confirmed cases of COVID-19. The GBR method can minimize the loss function More >

Dongfang Yu, Jinwei Wang^*

Journal of Information Hiding and Privacy Protection, Vol.2, No.4, pp. 165-174, 2020, DOI:10.32604/jihpp.2020.010466 - 07 January 2021

Abstract Chemical spectral analysis is contemporarily undergoing a revolution and drawing much attention of scientists owing to machine learning algorithms, in particular convolutional networks. Hence, this paper outlines the major machine learning and especially deep learning methods contributed to interpret chemical images, and overviews the current application, development and breakthrough in different spectral characterization. Brief categorization of reviewed literatures is provided for studies per application apparatus: X-Ray spectra, UV-Vis-IR spectra, Micro-scope, Raman spectra, Photoluminescence spectrum. End with the overview of existing circumstances in this research area, we provide unique insight and promising directions for the chemical More >

Iftikhar Ahmad^1,*, Mohammed A. Alqarni², Abdulwahab Ali Almazroi³, Abdullah Tariq¹

Intelligent Automation & Soft Computing, Vol.26, No.6, pp. 1335-1344, 2020, DOI:10.32604/iasc.2020.013861 - 24 December 2020

Abstract The exponential growth of social media has been instrumental in directing the news outlets to rely on the stated platform for the dissemination of news stories. While social media has helped in the fast propagation of breaking news, it also has allowed many bad actors to exploit this medium for political and monetary purposes. With such an intention, tempting headlines, which are not aligned with the content, are being used to lure users to visit the websites that often post dodgy and unreliable information. This phenomenon is commonly known as clickbait. A number of machine… More >

Junhui Wang¹, Wanzi Yan¹, Zhijun Wan^1,*, Yi Wang^2,*, Jiakun Lv¹, Aiping Zhou³

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.3, pp. 1135-1157, 2020, DOI:10.32604/cmes.2020.014313 - 15 December 2020

Abstract Precise recovery of Coalbed Methane (CBM) based on transparent reconstruction of geological conditions is a branch of intelligent mining. The process of permeability reconstruction, ranging from data perception to real-time data visualization, is applicable to disaster risk warning and intelligent decision-making on gas drainage. In this study, a machine learning method integrating the Random Forest (RF) and the Genetic Algorithm (GA) was established for permeability prediction in the Xishan Coalfield based on Uniaxial Compressive Strength (UCS), effective stress, temperature and gas pressure. A total of 50 sets of data collected by a self-developed apparatus were… More >