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  • Open Access

    ARTICLE

    Multi Criteria Decision Making for Evaluation and Ranking of Cancer Information

    Shahid Mahmood1,*, 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 - 31 October 2022

    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… More >

  • Open Access

    ARTICLE

    Weighted PageRank Algorithm Search Engine Ranking Model for Web Pages

    S. Samsudeen Shaffi1,*, I. Muthulakshmi2

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 183-192, 2023, DOI:10.32604/iasc.2023.031494 - 29 September 2022

    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… More >

  • Open Access

    ARTICLE

    Application of Intuitionistic Z-Numbers in Supplier Selection

    Nik Muhammad Farhan Hakim Nik Badrul Alam1,2, Ku Muhammad Naim Ku Khalif1,*, Nor Izzati Jaini1

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 47-61, 2023, DOI:10.32604/iasc.2023.024660 - 06 June 2022

    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… More >

  • Open Access

    ARTICLE

    Ensemble Classifier-Based Features Ranking on Employee Attrition

    Yok-Yen Nguwi*

    Journal on Artificial Intelligence, Vol.4, No.3, pp. 189-199, 2022, DOI:10.32604/jai.2022.034064 - 01 December 2022

    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 More >

  • Open Access

    ARTICLE

    Association Rule Analysis-Based Identification of Influential Users in the Social Media

    Saqib Iqbal1, Rehan Khan2, Hikmat Ullah Khan2,*, 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 - 28 July 2022

    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.… More >

  • Open Access

    ARTICLE

    New Decision-Making Technique Based on Hurwicz Criteria for Fuzzy Ranking

    Deepak Sukheja1, Javaid Ahmad Shah2, G. Madhu3, K. Sandeep Kautish4, Fahad A. Alghamdi5, Ibrahim. S. Yahia6,7,8, El-Sayed M. El-Kenawy9,10, Ali Wagdy Mohamed11,12,*

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4595-4609, 2022, DOI:10.32604/cmc.2022.029122 - 28 July 2022

    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… More >

  • Open Access

    ARTICLE

    Explainable Software Fault Localization Model: From Blackbox to Whitebox

    Abdulaziz Alhumam*

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1463-1482, 2022, DOI:10.32604/cmc.2022.029473 - 18 May 2022

    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 More >

  • Open Access

    ARTICLE

    Selecting Best Software Vulnerability Scanner Using Intuitionistic Fuzzy Set TOPSIS

    Navneet Bhatt1, Jasmine Kaur2, Adarsh Anand2, Omar H. Alhazmi3,*

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3613-3629, 2022, DOI:10.32604/cmc.2022.026554 - 29 March 2022

    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… More >

  • Open Access

    ARTICLE

    Modelling an Efficient Clinical Decision Support System for Heart Disease Prediction Using Learning and Optimization Approaches

    Sridharan Kannan*

    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 677-694, 2022, DOI:10.32604/cmes.2022.018580 - 14 March 2022

    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… More >

  • Open Access

    ARTICLE

    An Enhanced Re-Ranking Model for Person Re-Identification

    Jayavarthini Chockalingam*, Malathy Chidambaranathan

    Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 697-710, 2022, DOI:10.32604/iasc.2022.024142 - 08 February 2022

    Abstract Presently, Person Re-IDentification (PRe-ID) acts as a vital part of real time video surveillance to ensure the rising need for public safety. Resolving the PRe-ID problem includes the process of matching observations of persons among distinct camera views. Earlier models consider PRe-ID as a unique object retrieval issue and determine the retrieval results mainly based on the unidirectional matching among the probe and gallery images. But the accurate matching might not be present in the top-k ranking results owing to the appearance modifications caused by the difference in illumination, pose, viewpoint, and occlusion. For addressing… More >

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