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  • Open Access


    Research on Enhanced Contraband Dataset ACXray Based on ETL

    Xueping Song1,*, Jianming Yang1, Shuyu Zhang1, Jicun Zhang1,2,*

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4551-4572, 2024, DOI:10.32604/cmc.2024.049446

    Abstract To address the shortage of public datasets for customs X-ray images of contraband and the difficulties in deploying trained models in engineering applications, a method has been proposed that employs the Extract-Transform-Load (ETL) approach to create an X-ray dataset of contraband items. Initially, X-ray scatter image data is collected and cleaned. Using Kafka message queues and the Elasticsearch (ES) distributed search engine, the data is transmitted in real-time to cloud servers. Subsequently, contraband data is annotated using a combination of neural networks and manual methods to improve annotation efficiency and implemented mean hash algorithm for… More >

  • Open Access


    Applying an Improved Dung Beetle Optimizer Algorithm to Network Traffic Identification

    Qinyue Wu, Hui Xu*, Mengran Liu

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4091-4107, 2024, DOI:10.32604/cmc.2024.048461

    Abstract Network traffic identification is critical for maintaining network security and further meeting various demands of network applications. However, network traffic data typically possesses high dimensionality and complexity, leading to practical problems in traffic identification data analytics. Since the original Dung Beetle Optimizer (DBO) algorithm, Grey Wolf Optimization (GWO) algorithm, Whale Optimization Algorithm (WOA), and Particle Swarm Optimization (PSO) algorithm have the shortcomings of slow convergence and easily fall into the local optimal solution, an Improved Dung Beetle Optimizer (IDBO) algorithm is proposed for network traffic identification. Firstly, the Sobol sequence is utilized to initialize the… More >

  • Open Access


    Predicting the International Roughness Index of JPCP and CRCP Rigid Pavement: A Random Forest (RF) Model Hybridized with Modified Beetle Antennae Search (MBAS) for Higher Accuracy

    Zhou Ji1, Mengmeng Zhou2, Qiang Wang2, Jiandong Huang3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1557-1582, 2024, DOI:10.32604/cmes.2023.046025

    Abstract To improve the prediction accuracy of the International Roughness Index (IRI) of Jointed Plain Concrete Pavements (JPCP) and Continuously Reinforced Concrete Pavements (CRCP), a machine learning approach is developed in this study for the modelling, combining an improved Beetle Antennae Search (MBAS) algorithm and Random Forest (RF) model. The 10-fold cross-validation was applied to verify the reliability and accuracy of the model proposed in this study. The importance scores of all input variables on the IRI of JPCP and CRCP were analysed as well. The results by the comparative analysis showed the prediction accuracy of… More > Graphic Abstract

    Predicting the International Roughness Index of JPCP and CRCP Rigid Pavement: A Random Forest (RF) Model Hybridized with Modified Beetle Antennae Search (MBAS) for Higher Accuracy

  • Open Access


    An Overview of ETL Techniques, Tools, Processes and Evaluations in Data Warehousing

    Bilal Khan1, Saifullah Jan1,*, Wahab Khan1, Muhammad Imran Chughtai2

    Journal on Big Data, Vol.6, pp. 1-20, 2024, DOI:10.32604/jbd.2023.046223

    Abstract The extraction, transformation, and loading (ETL) process is a crucial and intricate area of study that lies deep within the broad field of data warehousing. This specific, yet crucial, aspect of data management fills the knowledge gap between unprocessed data and useful insights. Starting with basic information unique to this complex field, this study thoroughly examines the many issues that practitioners encounter. These issues include the complexities of ETL procedures, the rigorous pursuit of data quality, and the increasing amounts and variety of data sources present in the modern data environment. The study examines ETL… More >

  • Open Access


    L’évolution de l’occupation du sol et des inégalités environnementales dans la ville minière de Métlaoui par le biais d’un SIG-AMC

    Bilel Salhi1 , Mohsen Dhieb2,3, Yamna Djellouli4

    Revue Internationale de Géomatique, Vol.29, No.3, pp. 381-399, 2019, DOI:10.3166/rig.2020.00094

    Abstract La ville de Métlaoui constitue le noyau urbain central du bassin minier de Gafsa (BMG) au sud-ouest de la Tunisie. À l’instar des autres villes du bassin, Métlaoui est traditionnellement caractérisée par la mono-activité industrielle d’enrichissement de phosphate ; elle observe par ailleurs une dichotomie spatiale entre « le village européen relativement favorisé qui constitue le cœur de la ville et les cités périphériques ouvrières très déshéritées. Cette dichotomie ne semble pas faiblir aujourd’hui ; bien au contraire, la recherche montre aujourd’hui les prémices d’une accentuation des ségrégations socio-spatiales héritées de la période coloniale et… More >

  • Open Access


    Intelligent Beetle Antenna Search with Deep Transfer Learning Enabled Medical Image Classification Model

    Mohamed Ibrahim Waly*

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3159-3174, 2023, DOI:10.32604/csse.2023.035900

    Abstract Recently, computer assisted diagnosis (CAD) model creation has become more dependent on medical picture categorization. It is often used to identify several conditions, including brain disorders, diabetic retinopathy, and skin cancer. Most traditional CAD methods relied on textures, colours, and forms. Because many models are issue-oriented, they need a more substantial capacity to generalize and cannot capture high-level problem domain notions. Recent deep learning (DL) models have been published, providing a practical way to develop models specifically for classifying input medical pictures. This paper offers an intelligent beetle antenna search (IBAS-DTL) method for classifying medical… More >

  • Open Access


    Feature Selection with Deep Reinforcement Learning for Intrusion Detection System

    S. Priya1,*, K. Pradeep Mohan Kumar2

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3339-3353, 2023, DOI:10.32604/csse.2023.030630

    Abstract An intrusion detection system (IDS) becomes an important tool for ensuring security in the network. In recent times, machine learning (ML) and deep learning (DL) models can be applied for the identification of intrusions over the network effectively. To resolve the security issues, this paper presents a new Binary Butterfly Optimization algorithm based on Feature Selection with DRL technique, called BBOFS-DRL for intrusion detection. The proposed BBOFSDRL model mainly accomplishes the recognition of intrusions in the network. To attain this, the BBOFS-DRL model initially designs the BBOFS algorithm based on the traditional butterfly optimization algorithm More >

  • Open Access


    ETL Maturity Model for Data Warehouse Systems: A CMMI Compliant Framework

    Musawwer Khan1, Islam Ali1, Shahzada Khurram2, Salman Naseer3, Shafiq Ahmad4, Ahmed T. Soliman4, Akber Abid Gardezi5, Muhammad Shafiq6,*, Jin-Ghoo Choi6

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3849-3863, 2023, DOI:10.32604/cmc.2023.027387

    Abstract The effectiveness of the Business Intelligence (BI) system mainly depends on the quality of knowledge it produces. The decision-making process is hindered, and the user’s trust is lost, if the knowledge offered is undesired or of poor quality. A Data Warehouse (DW) is a huge collection of data gathered from many sources and an important part of any BI solution to assist management in making better decisions. The Extract, Transform, and Load (ETL) process is the backbone of a DW system, and it is responsible for moving data from source systems into the DW system.… More >

  • Open Access


    Optimization of Cognitive Femtocell Network via Oppositional Beetle Swarm Optimization Algorithm

    K. Rajesh Kumar1,*, M. Vijayakumar2

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 819-832, 2023, DOI:10.32604/iasc.2023.030961

    Abstract In past decades, cellular networks have raised the usage of spectrum resources due to the victory of mobile broadband services. Mobile devices create massive data than ever before, facing the way cellular networks are installed presently for satisfying the increased traffic requirements. The development of a new exclusive spectrum offered to meet up the traffic requirements is challenging as spectrum resources are limited, hence costly. Cognitive radio technology is presented to increase the pool of existing spectrum resources for mobile users via Femtocells, placed on the top of the available macrocell network for sharing the… More >

  • Open Access


    Energy Efficient Load Balancing and Routing Using Multi-Objective Based Algorithm in WSN

    Hemant Kumar Vijayvergia1,*, Uma Shankar Modani2

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3227-3239, 2023, DOI:10.32604/iasc.2023.031357

    Abstract In wireless sensor network (WSN), the gateways which are placed far away from the base station (BS) forward the collected data to the BS through the gateways which are nearer to the BS. This leads to more energy consumption because the gateways nearer to the BS manages heavy traffic load. So, to overcome this issue, loads around the gateways are to be balanced by presenting energy efficient clustering approach. Besides, to enhance the lifetime of the network, optimal routing path is to be established between the source node and BS. For energy efficient load balancing… More >

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