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Search Results (14)
  • Open Access

    ARTICLE

    Research on a Simulation Platform for Typical Internal Corrosion Defects in Natural Gas Pipelines Based on Big Data Analysis

    Changchao Qi1, Lingdi Fu1, Ming Wen1, Hao Qian2, Shuai Zhao1,*

    Structural Durability & Health Monitoring, Vol.19, No.4, pp. 1073-1087, 2025, DOI:10.32604/sdhm.2025.061898 - 30 June 2025

    Abstract The accuracy and reliability of non-destructive testing (NDT) approaches in detecting interior corrosion problems are critical, yet research in this field is limited. This work describes a novel way to monitor the structural integrity of steel gas pipelines that uses advanced numerical modeling techniques to anticipate fracture development and corrosion effects. The objective is to increase pipeline dependability and safety through more precise, real-time health evaluations. Compared to previous approaches, our solution provides higher accuracy in fault detection and quantification, making it ideal for pipeline integrity monitoring in real-world applications. To solve this issue, statistical… More >

  • Open Access

    ARTICLE

    Loss Aware Feature Attention Mechanism for Class and Feature Imbalance Issue

    Yuewei Wu1, Ruiling Fu1, Tongtong Xing1, Fulian Yin1,2,*

    CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 751-775, 2025, DOI:10.32604/cmc.2024.057606 - 03 January 2025

    Abstract In the Internet era, recommendation systems play a crucial role in helping users find relevant information from large datasets. Class imbalance is known to severely affect data quality, and therefore reduce the performance of recommendation systems. Due to the imbalance, machine learning algorithms tend to classify inputs into the positive (majority) class every time to achieve high prediction accuracy. Imbalance can be categorized such as by features and classes, but most studies consider only class imbalance. In this paper, we propose a recommendation system that can integrate multiple networks to adapt to a large number… More >

  • Open Access

    ARTICLE

    Twitter Media Sentiment Analysis to Convert Non-Informative to Informative Using QER

    C. P. Thamil Selvi1,*, P. Muneeshwari2, K. Selvasheela3, D. Prasanna4

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3545-3555, 2023, DOI:10.32604/iasc.2023.031097 - 17 August 2022

    Abstract The term sentiment analysis deals with sentiment classification based on the review made by the user in a social network. The sentiment classification accuracy is evaluated using various selection methods, especially those that deal with algorithm selection. In this work, every sentiment received through user expressions is ranked in order to categorise sentiments as informative and non-informative. In order to do so, the work focus on Query Expansion Ranking (QER) algorithm that takes user text as input and process for sentiment analysis and finally produces the results as informative or non-informative. The challenge is to More >

  • Open Access

    ARTICLE

    Foundation Treatment in Urban Underground Engineering Using Big Data Analysis for Smart City Applications

    Fei Liu1,2, Yunkai Zhang1,2, Jian Zhang3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.1, pp. 153-172, 2022, DOI:10.32604/cmes.2022.017967 - 02 June 2022

    Abstract A core element of the sustainable approach to global living quality improvement can now become the intensive and organized usage of underground space. There is a growing interest in underground building and growth worldwide. The reduced consumption of electricity, effective preservation of green land, sustainable wastewater and sewage treatment, efficient reverse degradation of the urban environment, and reliable critical infrastructure management can improve the quality of life. At the same time, technological innovations such as artificial intelligence (AI), cloud computing (CC), the internet of things (IoT), and big data analytics (BDA) play a significant role… More >

  • Open Access

    ARTICLE

    Analyzing the Implications of Healthcare Data Breaches through Computational Technique

    Ahmed H. Almulihi1, Fawaz Alassery2, Asif Irshad Khan3, Sarita Shukla4, Bineet Kumar Gupta4, Rajeev Kumar4,*

    Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1763-1779, 2022, DOI:10.32604/iasc.2022.023460 - 09 December 2021

    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… More >

  • Open Access

    ARTICLE

    Tracking Dengue on Twitter Using Hybrid Filtration-Polarity and Apache Flume

    Norjihan Binti Abdul Ghani1,*, 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 - 24 September 2021

    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… More >

  • Open Access

    ARTICLE

    Abnormal Event Correlation and Detection Based on Network Big Data Analysis

    Zhichao Hu1, Xiangzhan Yu1,*, Jiantao Shi1, Lin Ye1,2

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 695-711, 2021, DOI:10.32604/cmc.2021.017574 - 04 June 2021

    Abstract With the continuous development of network technology, various large-scale cyber-attacks continue to emerge. These attacks pose a severe threat to the security of systems, networks, and data. Therefore, how to mine attack patterns from massive data and detect attacks are urgent problems. In this paper, an approach for attack mining and detection is proposed that performs tasks of alarm correlation, false-positive elimination, attack mining, and attack prediction. Based on the idea of CluStream, the proposed approach implements a flow clustering method and a two-step algorithm that guarantees efficient streaming and clustering. The context of an… More >

  • Open Access

    ARTICLE

    A Sensor Network Web Platform Based on WoT Technology

    Shun-Yuan Wang1, Yun-Jung Hsu1, Sung-Jung Hsiao2, Wen-Tsai Sung3,*

    Computer Systems Science and Engineering, Vol.38, No.2, pp. 197-214, 2021, DOI:10.32604/csse.2021.015713 - 23 April 2021

    Abstract This study proposes a Web platform, the Web of Things (WoT), whose Internet of Things (IoT) architecture is used to develop the technology behind a new standard Web platform. When a remote sensor passes data to a microcontroller for processing, the protocol is often not known. This study proposes a WoT platform that enables the use of a browser in a mobile device to control a remote hardware device. An optimized code is written using an artificial intelligence-based algorithm in a microcontroller. Digital data convergence technology is adopted to process the packets of different protocols… More >

  • Open Access

    ARTICLE

    Utilizing Blockchain Technology to Improve WSN Security for Sensor Data Transmission

    Sung-Jung Hsiao1, Wen-Tsai Sung2,*

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1899-1918, 2021, DOI:10.32604/cmc.2021.015762 - 13 April 2021

    Abstract This paper proposes a method for improving the data security of wireless sensor networks based on blockchain technology. Blockchain technology is applied to data transfer to build a highly secure wireless sensor network. In this network, the relay stations use microcontrollers and embedded devices, and the microcontrollers, such as Raspberry Pi and Arduino Yun, represents mobile databases. The proposed system uses microcontrollers to facilitate the connection of various sensor devices. By adopting blockchain encryption, the security of sensing data can be effectively improved. A blockchain is a concatenated transaction record that is protected by cryptography.… More >

  • Open Access

    ARTICLE

    Computing the User Experience via Big Data Analysis: A Case of Uber Services

    Jang Hyun Kim1,2, Dongyan Nan1,*, Yerin Kim2, Min Hyung Park2

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 2819-2829, 2021, DOI:10.32604/cmc.2021.014922 - 01 March 2021

    Abstract As of 2020, the issue of user satisfaction has generated a significant amount of interest. Therefore, we employ a big data approach for exploring user satisfaction among Uber users. We develop a research model of user satisfaction by expanding the list of user experience (UX) elements (i.e., pragmatic, expectation confirmation, hedonic, and burden) by including more elements, namely: risk, cost, promotion, anxiety, sadness, and anger. Subsequently, we collect 125,768 comments from online reviews of Uber services and perform a sentiment analysis to extract the UX elements. The results of a regression analysis reveal the following:… More >

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