Supriya Gupta^*, Aakanksha Sharaff, Naresh Kumar Nagwani

Computer Systems Science and Engineering, Vol.45, No.3, pp. 2333-2349, 2023, DOI:10.32604/csse.2023.030385

Abstract Text Summarization models facilitate biomedical clinicians and researchers in acquiring informative data from enormous domain-specific literature within less time and effort. Evaluating and selecting the most informative sentences from biomedical articles is always challenging. This study aims to develop a dual-mode biomedical text summarization model to achieve enhanced coverage and information. The research also includes checking the fitment of appropriate graph ranking techniques for improved performance of the summarization model. The input biomedical text is mapped as a graph where meaningful sentences are evaluated as the central node and the critical associations between them. The proposed framework utilizes the top… More >

Yok-Yen Nguwi^*

Journal on Artificial Intelligence, Vol.4, No.3, pp. 189-199, 2022, DOI:10.32604/jai.2022.034064

Abstract The departure of good employee incurs direct and indirect cost and impacts for an organization. The direct cost arises from hiring to training of the relevant employee. The replacement time and lost productivity affect the running of business processes. This work presents the use of ensemble classifier to identify important attributes that affects attrition significantly. The data consists of attributes related to job function, education level, satisfaction towards work and working relationship, compensation, and frequency of business travel. Both bagging and boosting classifiers were used for testing. The results show that the selected features (nine selected features) achieve the same… More >

Shahid Mahmood^1,*, Muhammad Amin², Mubashir Baig Mirza¹, Salem Abu-Ghumsan¹, Muhammad Akram³, Zahid Mahmood Janjua⁴, Arslan Shahid⁵, Usman Shahid⁶

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4469-4481, 2023, DOI:10.32604/cmc.2023.030728

Abstract Cancer is a disease that is rapidly expanding in prevalence all over the world. Cancer cells can metastasize, or spread, across the body and impact several different cell types. Additionally, the incidence rates of several subtypes of cancer have been on the rise in India. The countermeasures for the cancer disease can be taken by determining the specific expansion rate of each type. To rank the various forms of cancer’s rate of progression, we used some of the available data. Numerous studies are available in the literature which show the growth rate of cancer by different techniques. The accuracy of… More >

S. Samsudeen Shaffi^1,*, I. Muthulakshmi²

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 183-192, 2023, DOI:10.32604/iasc.2023.031494

Abstract As data grows in size, search engines face new challenges in extracting more relevant content for users’ searches. As a result, a number of retrieval and ranking algorithms have been employed to ensure that the results are relevant to the user’s requirements. Unfortunately, most existing indexes and ranking algorithms crawl documents and web pages based on a limited set of criteria designed to meet user expectations, making it impossible to deliver exceptionally accurate results. As a result, this study investigates and analyses how search engines work, as well as the elements that contribute to higher ranks. This paper addresses the… More >

Saqib Iqbal¹, Rehan Khan², Hikmat Ullah Khan^2,*, Fawaz Khaled Alarfaj⁴, Abdullah Mohammed Alomair³, Muzamil Ahmed²

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6479-6493, 2022, DOI:10.32604/cmc.2022.030881

Abstract The exchange of information is an innate and natural process that assist in content dispersal. Social networking sites emerge to enrich their users by providing the facility for sharing information and social interaction. The extensive adoption of social networking sites also resulted in user content generation. There are diverse research areas explored by the researchers to investigate the influence of social media on users and confirmed that social media sites have a significant impact on markets, politics and social life. Facebook is extensively used platform to share information, thoughts and opinions through posts and comments. The identification of influential users… More >

Deepak Sukheja¹, Javaid Ahmad Shah², G. Madhu³, K. Sandeep Kautish⁴, Fahad A. Alghamdi⁵, Ibrahim. S. Yahia^6,7,8, El-Sayed M. El-Kenawy^9,10, Ali Wagdy Mohamed^11,12,*

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4595-4609, 2022, DOI:10.32604/cmc.2022.029122

Abstract Efficient decision-making remains an open challenge in the research community, and many researchers are working to improve accuracy through the use of various computational techniques. In this case, the fuzzification and defuzzification processes can be very useful. Defuzzification is an effective process to get a single number from the output of a fuzzy set. Considering defuzzification as a center point of this research paper, to analyze and understand the effect of different types of vehicles according to their performance. In this paper, the multi-criteria decision-making (MCDM) process under uncertainty and defuzzification is discussed by using the center of the area… More >

Nik Muhammad Farhan Hakim Nik Badrul Alam^1,2, Ku Muhammad Naim Ku Khalif^1,*, Nor Izzati Jaini¹

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 47-61, 2023, DOI:10.32604/iasc.2023.024660

Abstract Intuitionistic fuzzy numbers incorporate the membership and non-membership degrees. In contrast, Z-numbers consist of restriction components, with the existence of a reliability component describing the degree of certainty for the restriction. The combination of intuitionistic fuzzy numbers and Z-numbers produce a new type of fuzzy numbers, namely intuitionistic Z-numbers (IZN). The strength of IZN is their capability of better handling the uncertainty compared to Zadeh's Z-numbers since both components of Z-numbers are characterized by the membership and non-membership functions, exhibiting the degree of the hesitancy of decision-makers. This paper presents the application of such numbers in fuzzy multi-criteria decision-making problems.… More >

Abdulaziz Alhumam^*

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1463-1482, 2022, DOI:10.32604/cmc.2022.029473

Abstract The most resource-intensive and laborious part of debugging is finding the exact location of the fault from the more significant number of code snippets. Plenty of machine intelligence models has offered the effective localization of defects. Some models can precisely locate the faulty with more than 95% accuracy, resulting in demand for trustworthy models in fault localization. Confidence and trustworthiness within machine intelligence-based software models can only be achieved via explainable artificial intelligence in Fault Localization (XFL). The current study presents a model for generating counterfactual interpretations for the fault localization model's decisions. Neural system approximations and disseminated presentation of… More >

Navneet Bhatt¹, Jasmine Kaur², Adarsh Anand², Omar H. Alhazmi^3,*

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3613-3629, 2022, DOI:10.32604/cmc.2022.026554

Abstract Software developers endeavor to build their products with the least number of bugs. Despite this, many vulnerabilities are detected in software that threatens its integrity. Various automated software i.e., vulnerability scanners, are available in the market which helps detect and manage vulnerabilities in a computer, application, or a network. Hence, the choice of an appropriate vulnerability scanner is crucial to ensure efficient vulnerability management. The current work serves a dual purpose, first, to identify the key factors which affect the vulnerability discovery process in a network. The second, is to rank the popular vulnerability scanners based on the identified attributes.… More >

Sridharan Kannan^*

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 677-694, 2022, DOI:10.32604/cmes.2022.018580

Abstract With the worldwide analysis, heart disease is considered a significant threat and extensively increases the mortality rate. Thus, the investigators mitigate to predict the occurrence of heart disease in an earlier stage using the design of a better Clinical Decision Support System (CDSS). Generally, CDSS is used to predict the individuals’ heart disease and periodically update the condition of the patients. This research proposes a novel heart disease prediction system with CDSS composed of a clustering model for noise removal to predict and eliminate outliers. Here, the Synthetic Over-sampling prediction model is integrated with the cluster concept to balance the… More >