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  • Open Access

    ARTICLE

    Sentiment Analysis Based on Performance of Linear Support Vector Machine and Multinomial Naïve Bayes Using Movie Reviews with Baseline Techniques

    Mian Muhammad Danyal1, Sarwar Shah Khan2,4, Muzammil Khan2,*, Muhammad Bilal Ghaffar1, Bilal Khan1, Muhammad Arshad3

    Journal on Big Data, Vol.5, pp. 1-18, 2023, DOI:10.32604/jbd.2023.041319

    Abstract Movies are the better source of entertainment. Every year, a great percentage of movies are released. People comment on movies in the form of reviews after watching them. Since it is difficult to read all of the reviews for a movie, summarizing all of the reviews will help make this decision without wasting time in reading all of the reviews. Opinion mining also known as sentiment analysis is the process of extracting subjective information from textual data. Opinion mining involves identifying and extracting the opinions of individuals, which can be positive, neutral, or negative. The task of opinion mining also… More >

  • Open Access

    ARTICLE

    Federated Learning Model for Auto Insurance Rate Setting Based on Tweedie Distribution

    Tao Yin1, Changgen Peng2,*, Weijie Tan3, Dequan Xu4, Hanlin Tang5

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 827-843, 2024, DOI:10.32604/cmes.2023.029039

    Abstract In the assessment of car insurance claims, the claim rate for car insurance presents a highly skewed probability distribution, which is typically modeled using Tweedie distribution. The traditional approach to obtaining the Tweedie regression model involves training on a centralized dataset, when the data is provided by multiple parties, training a privacy-preserving Tweedie regression model without exchanging raw data becomes a challenge. To address this issue, this study introduces a novel vertical federated learning-based Tweedie regression algorithm for multi-party auto insurance rate setting in data silos. The algorithm can keep sensitive data locally and uses privacy-preserving techniques to achieve intersection… More >

  • Open Access

    ARTICLE

    On the Effect of Mist Flow on the Heat Transfer Performances of a Three-CopperSphere Configuration

    Karema A. Hamad*, Yasser A. Mahmood

    FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.11, pp. 2863-2875, 2023, DOI:10.32604/fdmp.2023.029049

    Abstract The cooling of a (pebble bed) spent fuel in a high-temperature gas-cooled reactor (HTGR) is adversely affected by an increase in the temperature of the used gas (air). To investigate this problem, a configuration consisting of three copper spheres arranged in tandem subjected to a forced mist flow inside a cylindrical channel is considered. The heat transfer coefficients and related variations as a function of Reynolds number are investigated accordingly. The experimental results show that when compared to those with only airflow, the heat transfer coefficient of the spherical elements with mist flow (j = 112 kg/m2 hr, Re =… More >

  • Open Access

    ARTICLE

    Active Learning Strategies for Textual Dataset-Automatic Labelling

    Sher Muhammad Daudpota1, Saif Hassan1, Yazeed Alkhurayyif2,*, Abdullah Saleh Alqahtani3,4, Muhammad Haris Aziz5

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1409-1422, 2023, DOI:10.32604/cmc.2023.034157

    Abstract The Internet revolution has resulted in abundant data from various sources, including social media, traditional media, etcetera. Although the availability of data is no longer an issue, data labelling for exploiting it in supervised machine learning is still an expensive process and involves tedious human efforts. The overall purpose of this study is to propose a strategy to automatically label the unlabeled textual data with the support of active learning in combination with deep learning. More specifically, this study assesses the performance of different active learning strategies in automatic labelling of the textual dataset at sentence and document levels. To… More >

  • Open Access

    ARTICLE

    MBB-IoT: Construction and Evaluation of IoT DDoS Traffic Dataset from a New Perspective

    Yi Qing1, Xiangyu Liu2, Yanhui Du2,*

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2095-2119, 2023, DOI:10.32604/cmc.2023.039980

    Abstract Distributed Denial of Service (DDoS) attacks have always been a major concern in the security field. With the release of malware source codes such as BASHLITE and Mirai, Internet of Things (IoT) devices have become the new source of DDoS attacks against many Internet applications. Although there are many datasets in the field of IoT intrusion detection, such as Bot-IoT, Constrained Application Protocol–Denial of Service (CoAP-DoS), and LATAM-DDoS-IoT (some of the names of DDoS datasets), which mainly focus on DDoS attacks, the datasets describing new IoT DDoS attack scenarios are extremely rare, and only N-BaIoT and IoT-23 datasets used IoT… More >

  • Open Access

    ARTICLE

    A Survey on Deep Learning-Based 2D Human Pose Estimation Models

    Sani Salisu1,2, A. S. A. Mohamed1,*, M. H. Jaafar3, Ainun S. B. Pauzi1, Hussain A. Younis1,4

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2385-2400, 2023, DOI:10.32604/cmc.2023.035904

    Abstract In this article, a comprehensive survey of deep learning-based (DL-based) human pose estimation (HPE) that can help researchers in the domain of computer vision is presented. HPE is among the fastest-growing research domains of computer vision and is used in solving several problems for human endeavours. After the detailed introduction, three different human body modes followed by the main stages of HPE and two pipelines of two-dimensional (2D) HPE are presented. The details of the four components of HPE are also presented. The keypoints output format of two popular 2D HPE datasets and the most cited DL-based HPE articles from… More >

  • Open Access

    ARTICLE

    3D Model Occlusion Culling Optimization Method Based on WebGPU Computing Pipeline

    Liming Ye1,2, Gang Liu1,2,3,4,*, Genshen Chen1,2, Kang Li1,2, Qiyu Chen1,2,3, Wenyao Fan1,2, Junjie Zhang1,2

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2529-2545, 2023, DOI:10.32604/csse.2023.041488

    Abstract Nowadays, Web browsers have become an important carrier of 3D model visualization because of their convenience and portability. During the process of large-scale 3D model visualization based on Web scenes with the problems of slow rendering speed and low FPS (Frames Per Second), occlusion culling, as an important method for rendering optimization, can remove most of the occluded objects and improve rendering efficiency. The traditional occlusion culling algorithm (TOCA) is calculated by traversing all objects in the scene, which involves a large amount of repeated calculation and time consumption. To advance the rendering process and enhance rendering efficiency, this paper… More >

  • Open Access

    ARTICLE

    An Innovative Technique for Constructing Highly Non-Linear Components of Block Cipher for Data Security against Cyber Attacks

    Abid Mahboob1, Muhammad Asif2, Rana Muhammad Zulqarnain3,*, Imran Siddique4, Hijaz Ahmad5, Sameh Askar6, Giovanni Pau7

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2547-2562, 2023, DOI:10.32604/csse.2023.040855

    Abstract The rapid advancement of data in web-based communication has created one of the biggest issues concerning the security of data carried over the internet from unauthorized access. To improve data security, modern cryptosystems use substitution-boxes. Nowadays, data privacy has become a key concern for consumers who transfer sensitive data from one place to another. To address these problems, many companies rely on cryptographic techniques to secure data from illegal activities and assaults. Among these cryptographic approaches, AES is a well-known algorithm that transforms plain text into cipher text by employing substitution box (S-box). The S-box disguises the relationship between cipher… More >

  • Open Access

    ARTICLE

    Towards Generating a Practical SUNBURST Attack Dataset for Network Attack Detection

    Ehab AlMasri1, Mouhammd Alkasassbeh1, Amjad Aldweesh2,*

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2643-2669, 2023, DOI:10.32604/csse.2023.040626

    Abstract Supply chain attacks, exemplified by the SUNBURST attack utilizing SolarWinds Orion updates, pose a growing cybersecurity threat to entities worldwide. However, the need for suitable datasets for detecting and anticipating SUNBURST attacks is a significant challenge. We present a novel dataset collected using a unique network traffic data collection methodology to address this gap. Our study aims to enhance intrusion detection and prevention systems by understanding SUNBURST attack features. We construct realistic attack scenarios by combining relevant data and attack indicators. The dataset is validated with the J48 machine learning algorithm, achieving an average F-Measure of 87.7%. Our significant contribution… More >

  • Open Access

    ARTICLE

    Business Blockchain Suitability Determinants: Decision-Making through an Intuitionistic Fuzzy Method

    Tomader Almeshal1,*, Jawad Berri1, Tarifa Almulhim2, Areej Alhogail1, Emam Ahmed3

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 1665-1690, 2023, DOI:10.32604/csse.2023.038871

    Abstract Blockchain is one of the innovative and disruptive technologies that has a wide range of applications in multiple industries beyond cryptocurrency. The widespread adoption of blockchain technology in various industries has shown its potential to solve challenging business problems, as well as the possibility to create new business models which can increase a firm’s competitiveness. Due to the novelty of the technology, whereby many companies are still exploring potential use cases, and considering the complexity of blockchain technology, which may require huge changes to a company’s existing systems and processes, it is important for companies to carefully evaluate suitable use… More >

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