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  • Open Access


    Analysis of Iterative Process for Nauru Voting System

    Neelam Gohar1,*, Sidra Niaz1, Mamoona Naveed Asghar2, Salma Noor1

    Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 241-259, 2021, DOI:10.32604/iasc.2021.015461

    Abstract Game theory is a popular area of artificial intelligence in which the voter acknowledges his own desires and favors the person he wants to be his representative. In multi-agent systems, social choice functions help aggregate agents’ different preferences over alternatives into a single choice. Since all voting rules are susceptible to manipulation, the analysis of elections is complicated by the possibility of voter manipulation attempts. One approach to understanding elections is to treat them as an iterative process and see if we can reach an equilibrium point. Meir et al. proposed an iterative process to reach a stable outcome, i.e.,… More >

  • Open Access


    Impact of COVID-19 Pandemic: A Cybersecurity Perspective

    Mohammed Baz1, Hosam Alhakami2, Alka Agrawal3, Abdullah Baz4, Raees Ahmad Khan3,*

    Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 641-652, 2021, DOI:10.32604/iasc.2021.015845

    Abstract Inspite of the world being at a complete standstill in the wake of unprecedented health emergency of COVID-19 pandemic, people have managed to retain their digital interactions through Information Technology. Cloud networks, departmental servers, data centres, and the digital devices have ensured that businesses and industries as well as workers across the world remain associated with each other and are connected to the organizations’ data. In such a scenario, the requirements placed on digital frames have increased rapidly. While this has proved to be a boon in the combat against the spread of Coronavirus, alarming increase in the instances of… More >

  • Open Access


    Web Application Commercial Design for Financial Entities Based on Business Intelligence

    Carlos Andrés Tavera Romero1,*, Jesus Hamilton Ortiz2, Osamah Ibrahim Khalaf3, Andrea Ríos Prado4

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3177-3188, 2021, DOI:10.32604/cmc.2021.014738

    Abstract Multiple customer data management has become a focus of attention in big organizations. Although much information is available, it does not translate into significant profitable value-added services. We present a design of a commercial web application based on business intelligence that generates information on social and financial behavior of clients in an organization; with the purpose of obtain additional information that allows to get more profits. This app will provide a broader perspective for making strategic decisions to increase profits and reduce internal investment costs. A case in point is the financial sector, a group of financial entities were used… More >

  • Open Access


    Power Aggregation Operators and Similarity Measures Based on Improved Intuitionistic Hesitant Fuzzy Sets and their Applications to Multiple Attribute Decision Making

    Tahir Mahmood1, Wajid Ali1, Zeeshan Ali1, Ronnason Chinram2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.3, pp. 1165-1187, 2021, DOI:10.32604/cmes.2021.014393

    Abstract Intuitionistic hesitant fuzzy set (IHFS) is a mixture of two separated notions called intuitionistic fuzzy set (IFS) and hesitant fuzzy set (HFS), as an important technique to cope with uncertain and awkward information in realistic decision issues. IHFS contains the grades of truth and falsity in the form of the subset of the unit interval. The notion of IHFS was defined by many scholars with different conditions, which contain several weaknesses. Here, keeping in view the problems of already defined IHFSs, we will define IHFS in another way so that it becomes compatible with other existing notions. To examine the… More >

  • Open Access


    Medical Diagnosis Using Machine Learning: A Statistical Review

    Kaustubh Arun Bhavsar1, Jimmy Singla1, Yasser D. Al-Otaibi2, Oh-Young Song3,*, Yousaf Bin Zikria4, Ali Kashif Bashir5

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 107-125, 2021, DOI:10.32604/cmc.2021.014604

    Abstract Decision making in case of medical diagnosis is a complicated process. A large number of overlapping structures and cases, and distractions, tiredness, and limitations with the human visual system can lead to inappropriate diagnosis. Machine learning (ML) methods have been employed to assist clinicians in overcoming these limitations and in making informed and correct decisions in disease diagnosis. Many academic papers involving the use of machine learning for disease diagnosis have been increasingly getting published. Hence, to determine the use of ML to improve the diagnosis in varied medical disciplines, a systematic review is conducted in this study. To carry… More >

  • Open Access


    An LSTM Based Forecasting for Major Stock Sectors Using COVID Sentiment

    Ayesha Jabeen1, Sitara Afzal1, Muazzam Maqsood1, Irfan Mehmood2, Sadaf Yasmin1, Muhammad Tabish Niaz3, Yunyoung Nam4,*

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 1191-1206, 2021, DOI:10.32604/cmc.2021.014598

    Abstract Stock market forecasting is an important research area, especially for better business decision making. Efficient stock predictions continue to be significant for business intelligence. Traditional short-term stock market forecasting is usually based on historical market data analysis such as stock prices, moving averages, or daily returns. However, major events’ news also contains significant information regarding market drivers. An effective stock market forecasting system helps investors and analysts to use supportive information regarding the future direction of the stock market. This research proposes an efficient model for stock market prediction. The current proposed study explores the positive and negative effects of… More >

  • Open Access


    Fuzzy Based Decision-Making Approach for Estimating Usable-Security of Healthcare Web Applications

    Fahad A. Alzahrani*

    CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2599-2625, 2021, DOI:10.32604/cmc.2021.013124

    Abstract Usability and security are often considered contradictory in nature. One has a negative impact on the other. In order to satisfy the needs of users with the security perspective, the relationship and trade-offs among security and usability must be distinguished. Security practitioners are working on developing new approaches that would help to secure healthcare web applications as well increase usability of the web applications. In the same league, the present research endeavour is premised on the usable-security of healthcare web applications. For a compatible blend of usability and security that would fulfill the users’ requirments, this research proposes an integration… More >

  • Open Access


    Multi Criteria Decision Making System for Parking System

    Manjur Kolhar*, Abdalla Alameen

    Computer Systems Science and Engineering, Vol.36, No.1, pp. 101-116, 2021, DOI:10.32604/csse.2021.014915

    Abstract System supported smart parking can reduce traffic by making it stress free to locate empty parking spaces, hence lowering the risk of unfocussed driving. In this study, we propose a smart parking system using deep learning and an application-based approach. This system has two modules, one module detects and recognizes a license plate (LP), and the other selects a parking space; both modules use deep learning techniques. We used two modules that work independently to detect and recognize an LP by using an image of the vehicle. To detect parking space, only deep learning techniques were used. The two modules… More >

  • Open Access


    Fuzzy Based Decision Making Approach for Evaluating the Severity of COVID-19 Pandemic in Cities of Kingdom of Saudi Arabia

    Abdullah Baz1,*, Hosam Alhakami2

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1155-1174, 2021, DOI:10.32604/cmc.2020.013215

    Abstract The World Health Organization declared COVID-19 a pandemic on March 11, 2020 stating that it is a worldwide danger and requires imminent preventive strategies to minimise the loss of lives. COVID-19 has now affected millions across 211 countries in the world and the numbers continue to rise. The information discharged by the WHO till June 15, 2020 reports 8,063,990 cases of COVID-19. As the world thinks about the lethal malady for which there is yet no immunization or a predefined course of drug, the nations are relentlessly working at the most ideal preventive systems to contain the infection. The Kingdom… More >

  • Open Access


    Prospect Theory Based Hesitant Fuzzy Multi-Criteria Decision Making for Low Sulphur Fuel of Maritime Transportation

    Changli Lu1, Ming Zhao1,2, Imran Khan3, Peerapong Uthansakul4,*

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1511-1528, 2021, DOI:10.32604/cmc.2020.012556

    Abstract The environmental impact of maritime transport has now become a relevant issue in sustainable policy formulation and has attracted increasing interest from academia. For the sustainable development of maritime transport, International Maritime Organization stipulates that the sulfur content of ship emissions will reach 0.5 from 2020. With the approaching of the stipulated implementation date, shipowners need to adopt scientific methods to make decision on low sulfur fuel. In this study, we applied a prospect theory based hesitant fuzzy multi-criteria decision-making model to obtain the optimal decision of low Sulphur marine fuel. For this purpose, the hesitant fuzzy decision matrix is… More >

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