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  • Open Access

    ARTICLE

    Red Deer Optimization with Artificial Intelligence Enabled Image Captioning System for Visually Impaired People

    Anwer Mustafa Hilal1,*, Fadwa Alrowais2, Fahd N. Al-Wesabi3, Radwa Marzouk4,5

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 1929-1945, 2023, DOI:10.32604/csse.2023.035529

    Abstract The problem of producing a natural language description of an image for describing the visual content has gained more attention in natural language processing (NLP) and computer vision (CV). It can be driven by applications like image retrieval or indexing, virtual assistants, image understanding, and support of visually impaired people (VIP). Though the VIP uses other senses, touch and hearing, for recognizing objects and events, the quality of life of those persons is lower than the standard level. Automatic Image captioning generates captions that will be read loudly to the VIP, thereby realizing matters happening around them. This article introduces… More >

  • Open Access

    ARTICLE

    An Improved Bald Eagle Search Algorithm with Cauchy Mutation and Adaptive Weight Factor for Engineering Optimization

    Wenchuan Wang1,*, Weican Tian1, Kwok-wing Chau2, Yiming Xue1, Lei Xu3, Hongfei Zang1

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1603-1642, 2023, DOI:10.32604/cmes.2023.026231

    Abstract The Bald Eagle Search algorithm (BES) is an emerging meta-heuristic algorithm. The algorithm simulates the hunting behavior of eagles, and obtains an optimal solution through three stages, namely selection stage, search stage and swooping stage. However, BES tends to drop-in local optimization and the maximum value of search space needs to be improved. To fill this research gap, we propose an improved bald eagle algorithm (CABES) that integrates Cauchy mutation and adaptive optimization to improve the performance of BES from local optima. Firstly, CABES introduces the Cauchy mutation strategy to adjust the step size of the selection stage, to select… More >

  • Open Access

    ARTICLE

    A Novel Motor Fault Diagnosis Method Based on Generative Adversarial Learning with Distribution Fusion of Discrete Working Conditions

    Qixin Lan, Binqiang Chen*, Bin Yao

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 2017-2037, 2023, DOI:10.32604/cmes.2023.025307

    Abstract Many kinds of electrical equipment are used in civil and building engineering. The motor is one of the main power components of this electrical equipment, which can provide stable power output. During the long-term use of motors, various motor faults may occur, which affects the normal use of electrical equipment and even causes accidents. It is significant to apply fault diagnosis for the motors at the construction site. Aiming at the problem that signal data of faulty motor lack diversity, this research designs a multi-layer perceptron Wasserstein generative adversarial network, which is used to enhance training data through distribution fusion.… More >

  • Open Access

    ARTICLE

    Relational Logging Design Pattern

    Savas Takan1,*, Gokmen Katipoglu2

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 51-65, 2023, DOI:10.32604/cmc.2023.035282

    Abstract Observability and traceability of developed software are crucial to its success in software engineering. Observability is the ability to comprehend a system’s internal state from the outside. Monitoring is used to determine what causes system problems and why. Logs are among the most critical technology to guarantee observability and traceability. Logs are frequently used to investigate software events. In current log technologies, software events are processed independently of each other. Consequently, current logging technologies do not reveal relationships. However, system events do not occur independently of one another. With this perspective, our research has produced a new log design pattern… More >

  • Open Access

    ARTICLE

    An Early Warning Model of Telecommunication Network Fraud Based on User Portrait

    Wen Deng1, Guangjun Liang1,2,3,*, Chenfei Yu1, Kefan Yao1, Chengrui Wang1, Xuan Zhang1

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1561-1576, 2023, DOI:10.32604/cmc.2023.035016

    Abstract With the frequent occurrence of telecommunications and network fraud crimes in recent years, new frauds have emerged one after another which has caused huge losses to the people. However, due to the lack of an effective preventive mechanism, the police are often in a passive position. Using technologies such as web crawlers, feature engineering, deep learning, and artificial intelligence, this paper proposes a user portrait fraud warning scheme based on Weibo public data. First, we perform preliminary screening and cleaning based on the keyword “defrauded” to obtain valid fraudulent user Identity Documents (IDs). The basic information and account information of… More >

  • Open Access

    ARTICLE

    Automated Artificial Intelligence Empowered White Blood Cells Classification Model

    Mohammad Yamin1, Abdullah M. Basahel1, Mona Abusurrah2, Sulafah M Basahel3, Sachi Nandan Mohanty4, E. Laxmi Lydia5,*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 409-425, 2023, DOI:10.32604/cmc.2023.032432

    Abstract White blood cells (WBC) or leukocytes are a vital component of the blood which forms the immune system, which is accountable to fight foreign elements. The WBC images can be exposed to different data analysis approaches which categorize different kinds of WBC. Conventionally, laboratory tests are carried out to determine the kind of WBC which is erroneous and time consuming. Recently, deep learning (DL) models can be employed for automated investigation of WBC images in short duration. Therefore, this paper introduces an Aquila Optimizer with Transfer Learning based Automated White Blood Cells Classification (AOTL-WBCC) technique. The presented AOTL-WBCC model executes… More >

  • Open Access

    REVIEW

    Research on Career Identity in China: A Literature Review

    Huaruo Chen1,2, Ya Wen3,*, Fei Liu4,5, Yihong Zhao6, Zhiyao Xie7, Xuehui Zhang4

    International Journal of Mental Health Promotion, Vol.25, No.2, pp. 153-172, 2023, DOI:10.32604/ijmhp.2022.025546

    Abstract Career identity is one of the important topics to study the psychological problems of employees, especially after the outbreak of CoV-19. Being a populous country in the world, China has a large number of employees from all walks of life, and its research on career identity has attracted more and more attention. Thus, this study aims to sort out the history, characteristics, and trends of the research on career identity in China through a literature review, which can help more scholars pay attention to China’s career identity research. In this study, Citespace is used to statistically analyze the selected literature… More > Graphic Abstract

    Research on Career Identity in China: A Literature Review

  • Open Access

    ARTICLE

    Analysis of the Applicability of a Risk Quantitative Evaluation Method to High Temperature-Pressure Drilling Engineering

    Renjun Xie1, Xingquan Zhang1, Baolun He2,*, Ningyu Zheng2, Yuqiang Xu2,*

    FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.6, pp. 1385-1395, 2023, DOI:10.32604/fdmp.2023.025454

    Abstract The optimization of methods for the quantitative evaluation of risks in drilling engineering is an effective means to ensure safety in situations where high temperature and high pressure blocks are considered. In such a context, this study analyzes the complexity of the drilled wells in such blocks. It is shown that phenomena such as well kick, loss, circulation, and sticking, are related to the imbalance of wellbore pressure. A method for risk quantitative evaluation is proposed accordingly. The method is used to evaluate the risk for 9 drilled wells. By comparing the predictions of the method with actual historical data… More > Graphic Abstract

    Analysis of the Applicability of a Risk Quantitative Evaluation Method to High Temperature-Pressure Drilling Engineering

  • Open Access

    ARTICLE

    Improved Beam Steering Method Using OAM Waves

    Nidal Qasem*, Ahmad Alamayreh

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 417-431, 2023, DOI:10.32604/csse.2023.035603

    Abstract Orbital Angular Momentum (OAM) is an intrinsic feature of electromagnetic waves which has recently found many applications in several areas in radio and optics. In this paper, we use OAM wave characteristics to present a simple method for beam steering over both elevation and azimuth planes. The design overcomes some limitations of traditional steering methods, such as limited dynamic range of steering, the design complexity, bulky size of the steering structure, the limited bandwidth of operation, and low gain. Based on OAM wave characteristics, the proposed steering method avoids design complexities by adopting a simple method for generating the OAM-carrying… More >

  • Open Access

    ARTICLE

    A Multi-Module Machine Learning Approach to Detect Tax Fraud

    N. Alsadhan*

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 241-253, 2023, DOI:10.32604/csse.2023.033375

    Abstract Tax fraud is one of the substantial issues affecting governments around the world. It is defined as the intentional alteration of information provided on a tax return to reduce someone’s tax liability. This is done by either reducing sales or increasing purchases. According to recent studies, governments lose over $500 billion annually due to tax fraud. A loss of this magnitude motivates tax authorities worldwide to implement efficient fraud detection strategies. Most of the work done in tax fraud using machine learning is centered on supervised models. A significant drawback of this approach is that it requires tax returns that… More >

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