Mahmoud Ragab^1,2,3, Ehab Bahauden Ashary⁴, Maha Farouk S. Sabir⁵, Adel A. Bahaddad⁵, Romany F. Mansour^6,*

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5441-5457, 2022, DOI:10.32604/cmc.2022.024545

Abstract This study presents a novel method to detect the medical application based on Quantum Computing (QC) and a few Machine Learning (ML) systems. QC has a primary advantage i.e., it uses the impact of quantum parallelism to provide the consequences of prime factorization issue in a matter of seconds. So, this model is suggested for medical application only by recent researchers. A novel strategy i.e., Quantum Kernel Method (QKM) is proposed in this paper for data prediction. In this QKM process, Linear Tunicate Swarm Algorithm (LTSA), the optimization technique is used to calculate the loss function initially and is aimed… More >

Khudran M. Alzhrani^*

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 483-500, 2022, DOI:10.32604/iasc.2022.023914

Abstract Individuals inadvertently allow emotions to drive their rational thoughts to predetermined conclusions regarding political partiality issues. Being well-informed about the subject in question mitigates emotions’ influence on humans’ cognitive reasoning, but it does not eliminate bias. By nature, humans tend to pick a side based on their beliefs, personal interests, and principles. Hence, journalists’ political leaning is defining factor in the rise of the polarity of political news coverage. Political bias studies usually align subjects or controversial topics of the news coverage to a particular ideology. However, politicians as private citizens or public officials are also consistently in the media… More >

Ahmed H. Almulihi¹, Fawaz Alassery², Asif Irshad Khan³, Sarita Shukla⁴, Bineet Kumar Gupta⁴, Rajeev Kumar^4,*

Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1763-1779, 2022, DOI:10.32604/iasc.2022.023460

Abstract The contributions of the Internet of Medical Things (IoMT), cloud services, information systems, and smart devices are useful for the healthcare industry. With the help of digital healthcare, our lives have been made much more secure and effortless and provide more convenient and accessible treatment. In current, the modern healthcare sector has become more significant and convenient for the purpose of both external and internal threats. Big data breaches affect clients, stakeholders, organisations, and businesses, and they are a source of concern and complication for security professionals. This research examines the many types and categories of big data breaches that… More >

Wenquan Jin¹, Naeem Iqbal², Hee-Cheal Kang³, Dohyeun Kim^2,*

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3763-3780, 2022, DOI:10.32604/cmc.2022.020336

Abstract The earthquake is considered one of the most devastating disasters in any area of the world due to its potentially destructive force. Based on the various earthquake-related parameters, the risk assessment is enabled in advance to prevent future earthquake disasters. In this paper, for providing the shelter space demands to reduce the damage level and prevention costs, an earthquake risk assessment approach is proposed for deriving the risk index based on multiple spatial parameters in the gridded map. The proposed assessment approach is comprised of pre-processing, methodology model, and data visualization. The risk index model derives the earthquake risk index… More >

Nataliya Shakhovska¹, Nataliia Melnykova^1,*, Valentyna Chopiyak², Michal Gregus ml³

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3969-3984, 2022, DOI:10.32604/cmc.2022.019882

Abstract The paper reports three new ensembles of supervised learning predictors for managing medical insurance costs. The open dataset is used for data analysis methods development. The usage of artificial intelligence in the management of financial risks will facilitate economic wear time and money and protect patients’ health. Machine learning is associated with many expectations, but its quality is determined by choosing a good algorithm and the proper steps to plan, develop, and implement the model. The paper aims to develop three new ensembles for individual insurance costs prediction to provide high prediction accuracy. Pierson coefficient and Boruta algorithm are used… More >

Eman H. Alkhammash^*

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3733-3750, 2022, DOI:10.32604/cmc.2022.015987

Abstract Formal methods use mathematical models to develop systems. Ontologies are formal specifications that provide reusable domain knowledge representations. Ontologies have been successfully used in several data-driven applications, including data analysis. However, the creation of formal models from informal requirements demands skill and effort. Ambiguity, inconsistency, imprecision, and incompleteness are major problems in informal requirements. To solve these problems, it is necessary to have methods and approaches for supporting the mapping of requirements to formal specifications. The purpose of this paper is to present an approach that addresses this challenge by using the Web Ontology Language (OWL) to construct Event-B formal… More >

Norjihan Binti Abdul Ghani^1,*, Suraya Hamid¹, Muneer Ahmad¹, Younes Saadi¹, N.Z. Jhanjhi², Mohammed A. Alzain³, Mehedi Masud⁴

Computer Systems Science and Engineering, Vol.40, No.3, pp. 913-926, 2022, DOI:10.32604/csse.2022.018467

Abstract The world health organization (WHO) terms dengue as a serious illness that impacts almost half of the world’s population and carries no specific treatment. Early and accurate detection of spread in affected regions can save precious lives. Despite the severity of the disease, a few noticeable works can be found that involve sentiment analysis to mine accurate intuitions from the social media text streams. However, the massive data explosion in recent years has led to difficulties in terms of storing and processing large amounts of data, as reliable mechanisms to gather the data and suitable techniques to extract meaningful insights… More >

Tossapon Boongoen, Natthakan Iam-On^*

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1993-2011, 2022, DOI:10.32604/cmc.2022.019776

Abstract A mix between numerical and nominal data types commonly presents many modern-age data collections. Examples of these include banking data, sales history and healthcare records, where both continuous attributes like age and nominal ones like blood type are exploited to characterize account details, business transactions or individuals. However, only a few standard clustering techniques and consensus clustering methods are provided to examine such a data thus far. Given this insight, the paper introduces novel extensions of link-based cluster ensemble, and that are accurate for analyzing mixed-type data. They promote diversity within an ensemble through different initializations of the k-prototypes algorithm… More >

Jurgita Markevičiūtė^1,*, Jolita Bernatavičienė², Rūta Levulienė¹, Viktor Medvedev², Povilas Treigys², Julius Venskus²

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 695-714, 2022, DOI:10.32604/cmc.2022.018735

Abstract The growing number of COVID-19 cases puts pressure on healthcare services and public institutions worldwide. The pandemic has brought much uncertainty to the global economy and the situation in general. Forecasting methods and modeling techniques are important tools for governments to manage critical situations caused by pandemics, which have negative impact on public health. The main purpose of this study is to obtain short-term forecasts of disease epidemiology that could be useful for policymakers and public institutions to make necessary short-term decisions. To evaluate the effectiveness of the proposed attention-based method combining certain data mining algorithms and the classical ARIMA… More >

Yonghun Jang, Chang-Hyeon Park, Dong-Gun Lee, Yeong-Seok Seo^*

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3563-3579, 2021, DOI:10.32604/cmc.2021.018901

Abstract Following the development of communication techniques and smart devices, the era of Artificial Intelligence (AI) and big data has arrived. The increased connectivity, referred to as hyper-connectivity, has led to the development of smart cities. People in these smart cities can access numerous online contents and are always connected. These developments, however, also lead to a lack of standardization and consistency in the propagation of information throughout communities due to the consumption of information through social media channels. Information cannot often be verified, which can confuse the users. The increasing influence of social media has thus led to the emergence… More >