Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (46)
  • Open Access

    ARTICLE

    IoT-Based Women Safety Gadgets (WSG): Vision, Architecture, and Design Trends

    Sharad Saxena1, Shailendra Mishra2,*, Mohammed Baljon2,*, Shamiksha Mishra3, Sunil Kumar Sharma2, Prakhar Goel1, Shubham Gupta1, Vinay Kishore1

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 1027-1045, 2023, DOI:10.32604/cmc.2023.039677

    Abstract In recent years, the growth of female employees in the commercial market and industries has increased. As a result, some people think travelling to distant and isolated locations during odd hours generates new threats to women’s safety. The exponential increase in assaults and attacks on women, on the other hand, is posing a threat to women’s growth, development, and security. At the time of the attack, it appears the women were immobilized and needed immediate support. Only self-defense isn’t sufficient against abuse; a new technological solution is desired and can be used as quickly as hitting a switch or button.… More >

  • Open Access

    ARTICLE

    Predicting Bitcoin Trends Through Machine Learning Using Sentiment Analysis with Technical Indicators

    Hae Sun Jung1, Seon Hong Lee1, Haein Lee1, Jang Hyun Kim2,*

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 2231-2246, 2023, DOI:10.32604/csse.2023.034466

    Abstract Predicting Bitcoin price trends is necessary because they represent the overall trend of the cryptocurrency market. As the history of the Bitcoin market is short and price volatility is high, studies have been conducted on the factors affecting changes in Bitcoin prices. Experiments have been conducted to predict Bitcoin prices using Twitter content. However, the amount of data was limited, and prices were predicted for only a short period (less than two years). In this study, data from Reddit and LexisNexis, covering a period of more than four years, were collected. These data were utilized to estimate and compare the… More >

  • Open Access

    EDITORIAL

    Introduction to the Special Issue on New Trends in Statistical Computing and Data Science

    Christophe Chesneau1,*, Hassan Doosti2

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 981-983, 2023, DOI:10.32604/cmes.2023.028283

    Abstract This article has no abstract. More >

  • Open Access

    ARTICLE

    Emerging Trends in Social Networking Systems and Generation Gap with Neutrosophic Crisp Soft Mapping

    Muhammad Riaz1, Masooma Raza Hashmi1, Faruk Karaaslan2, Aslıhan Sezgin3, Mohammed M. Ali Al Shamiri4,5,*, Mohammed M. Khalaf6,7

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1759-1783, 2023, DOI:10.32604/cmes.2023.023327

    Abstract This paper aims to introduce the novel concept of neutrosophic crisp soft set (NCSS), including various types of neutrosophic crisp soft sets (NCSSs) and their fundamental operations. We define NCS-mapping and its inverse NCS-mapping between two NCS-classes. We develop a robust mathematical modeling with the help of NCS-mapping to analyze the emerging trends in social networking systems (SNSs) for our various generations. We investigate the advantages, disadvantages, and natural aspects of SNSs for five generations. With the changing of the generations, it is analyzed that emerging trends and the benefits of SNSs are increasing day by day. The suggested modeling… More > Graphic Abstract

    Emerging Trends in Social Networking Systems and Generation Gap with Neutrosophic Crisp Soft Mapping

  • Open Access

    ARTICLE

    New Trends in Fuzzy Modeling Through Numerical Techniques

    M. M. Alqarni1, Muhammad Rafiq2, Fazal Dayan3,*, Jan Awrejcewicz4, Nauman Ahmed5, Ali Raza6, Muhammad Ozair Ahmad5, Witold Pawłowski7, Emad E. Mahmoud8

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6371-6388, 2023, DOI:10.32604/cmc.2023.033553

    Abstract Amoebiasis is a parasitic intestinal infection caused by the highly pathogenic amoeba Entamoeba histolytica. It is spread through person-to-person contact or by eating or drinking food or water contaminated with feces. Its transmission rate depends on the number of cysts present in the environment. The traditional models assumed a homogeneous and contradictory transmission with reality. The heterogeneity of its transmission rate is a significant factor when modeling disease dynamics. The heterogeneity of disease transmission can be described mathematically by introducing fuzzy theory. In this context, a fuzzy SEIR Amoebiasis disease model is considered in this study. The equilibrium analysis and… More >

  • Open Access

    ARTICLE

    New Trends in the Modeling of Diseases Through Computational Techniques

    Nesreen Althobaiti1, Ali Raza2,*, Arooj Nasir3,4, Jan Awrejcewicz5, Muhammad Rafiq6, Nauman Ahmed7, Witold Pawłowski8, Muhammad Jawaz7, Emad E. Mahmoud1

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2935-2951, 2023, DOI:10.32604/csse.2023.033935

    Abstract The computational techniques are a set of novel problem-solving methodologies that have attracted wider attention for their excellent performance. The handling strategies of real-world problems are artificial neural networks (ANN), evolutionary computing (EC), and many more. An estimated fifty thousand to ninety thousand new leishmaniasis cases occur annually, with only 25% to 45% reported to the World Health Organization (WHO). It remains one of the top parasitic diseases with outbreak and mortality potential. In 2020, more than ninety percent of new cases reported to World Health Organization (WHO) occurred in ten countries: Brazil, China, Ethiopia, Eritrea, India, Kenya, Somalia, South… More >

  • Open Access

    ARTICLE

    Current Status and Development Trends of Chinese Intelligent Furniture Industry

    Xianqing Xiong1,2,*, Xinyi Yue2, Zhihui Wu1,2

    Journal of Renewable Materials, Vol.11, No.3, pp. 1353-1366, 2023, DOI:10.32604/jrm.2022.023447

    Abstract In this work, the current status, technical capabilities, and development trends of the Chinese intelligent furniture industry were in focus. Based on combining a literature review with field investigations and analysis of major scientific research projects in Zhejiang Province, China, an in-depth overview and discussion about previous experience, features, technologies, products and control methods in the intelligent furniture industry in China were conducted. The key technologies in current Chinese intelligent furniture industry include embedded systems, sensors, short-range wireless communication, artificial intelligence and intelligent interaction techniques. This work also mentions the challenges and opportunities for the industry, pointing out how to… More > Graphic Abstract

    Current Status and Development Trends of Chinese Intelligent Furniture Industry

  • Open Access

    ARTICLE

    Information Extraction Based on Multi-turn Question Answering for Analyzing Korean Research Trends

    Seongung Jo1, Heung-Seon Oh1,*, Sanghun Im1, Gibaeg Kim1, Seonho Kim2

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2967-2980, 2023, DOI:10.32604/cmc.2023.031983

    Abstract Analyzing Research and Development (R&D) trends is important because it can influence future decisions regarding R&D direction. In typical trend analysis, topic or technology taxonomies are employed to compute the popularities of the topics or codes over time. Although it is simple and effective, the taxonomies are difficult to manage because new technologies are introduced rapidly. Therefore, recent studies exploit deep learning to extract pre-defined targets such as problems and solutions. Based on the recent advances in question answering (QA) using deep learning, we adopt a multi-turn QA model to extract problems and solutions from Korean R&D reports. With the… More >

  • Open Access

    ARTICLE

    Big Data Testing Techniques: Taxonomy, Challenges and Future Trends

    Iram Arshad1,*, Saeed Hamood Alsamhi1, Wasif Afzal2

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2739-2770, 2023, DOI:10.32604/cmc.2023.030266

    Abstract Big Data is reforming many industrial domains by providing decision support through analyzing large data volumes. Big Data testing aims to ensure that Big Data systems run smoothly and error-free while maintaining the performance and quality of data. However, because of the diversity and complexity of data, testing Big Data is challenging. Though numerous research efforts deal with Big Data testing, a comprehensive review to address testing techniques and challenges of Big Data is not available as yet. Therefore, we have systematically reviewed the Big Data testing techniques’ evidence occurring in the period 2010–2021. This paper discusses testing data processing… More >

  • Open Access

    ARTICLE

    Identification and Visualization of Spatial and Temporal Trends in Textile Industry

    Umair Yousaf1, Muhammad Asif1, Shahbaz Ahmed1, Noman Tahir1, Azeem Irshad2, Akber Abid Gardezi3, Muhammad Shafiq4,*, Jin-Ghoo Choi4, Habib Hamam5,6,7,8

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4165-4181, 2023, DOI:10.32604/cmc.2023.026607

    Abstract The research volume increases at the study rate, causing massive text corpora. Due to these enormous text corpora, we are drowning in data and starving for information. Therefore, recent research employed different text mining approaches to extract information from this text corpus. These proposed approaches extract meaningful and precise phrases that effectively describe the text's information. These extracted phrases are commonly termed keyphrases. Further, these key phrases are employed to determine the different fields of study trends. Moreover, these key phrases can also be used to determine the spatiotemporal trends in the various research fields. In this research, the progress… More >

Displaying 11-20 on page 2 of 46. Per Page