Changfu Wan^1,2, Wenqiang Li^1,2,*, Sitong Ling^1,2, Yingdong Liu^1,2, Jiahao Chen^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 321-348, 2024, DOI:10.32604/cmes.2023.029053

Abstract Regarding the spatial profile extraction method of a multi-field co-simulation dataset, different extraction directions, locations, and numbers of profiles will greatly affect the representativeness and integrity of data. In this study, a multi-field co-simulation data extraction method based on adaptive infinitesimal elements is proposed. The multi-field co-simulation dataset based on related infinitesimal elements is constructed, and the candidate directions of data profile extraction undergo dimension reduction by principal component analysis to determine the direction of data extraction. Based on the fireworks algorithm, the data profile with optimal representativeness is searched adaptively in different data extraction intervals to realize the adaptive… More > Graphic Abstract

Ahmad M. Al-Omari^1,*, Shefa M. Tawalbeh¹, Yazan H. Akkam², Mohammad Al-Tawalbeh³, Shima’a Younis¹, Abdullah A. Mustafa⁴, Jonathan Arnold⁵

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4155-4173, 2023, DOI:10.32604/cmc.2023.036956

Abstract There are quintillions of data on deoxyribonucleic acid (DNA) and protein in publicly accessible data banks, and that number is expanding at an exponential rate. Many scientific fields, such as bioinformatics and drug discovery, rely on such data; nevertheless, gathering and extracting data from these resources is a tough undertaking. This data should go through several processes, including mining, data processing, analysis, and classification. This study proposes software that extracts data from big data repositories automatically and with the particular ability to repeat data extraction phases as many times as needed without human intervention. This software simulates the extraction of… More >

Yang Li, Fei Yin, Xianghui Hui^*

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4047-4063, 2023, DOI:10.32604/cmc.2023.036945

Abstract With the rapid development of the Internet globally since the 21st century, the amount of data information has increased exponentially. Data helps improve people’s livelihood and working conditions, as well as learning efficiency. Therefore, data extraction, analysis, and processing have become a hot issue for people from all walks of life. Traditional recommendation algorithm still has some problems, such as inaccuracy, less diversity, and low performance. To solve these problems and improve the accuracy and variety of the recommendation algorithms, the research combines the convolutional neural networks (CNN) and the attention model to design a recommendation algorithm based on the… More >

Jongyun Choi¹, Hyesoo Kong², Hwamook Yoon², Heungseon Oh³, Yuchul Jung^1,*

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 4019-4037, 2022, DOI:10.32604/cmc.2022.025711

Abstract The volume of academic literature, such as academic conference papers and journals, has increased rapidly worldwide, and research on metadata extraction is ongoing. However, high-performing metadata extraction is still challenging due to diverse layout formats according to journal publishers. To accommodate the diversity of the layouts of academic journals, we propose a novel LAyout-aware Metadata Extraction (LAME) framework equipped with the three characteristics (e.g., design of automatic layout analysis, construction of a large meta-data training set, and implementation of metadata extractor). In the framework, we designed an automatic layout analysis using PDFMiner. Based on the layout analysis, a large volume… More >

Hafiz Abid Mahmood Malik^*

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.3, pp. 1737-1750, 2022, DOI:10.32604/cmes.2022.018015

Abstract To discover and identify the influential nodes in any complex network has been an important issue. It is a significant factor in order to control over the network. Through control on a network, any information can be spread and stopped in a short span of time. Both targets can be achieved, since network of information can be extended and as well destroyed. So, information spread and community formation have become one of the most crucial issues in the world of SNA (Social Network Analysis). In this work, the complex network of twitter social network has been formalized and results are… More >

Malik Javed Akhtar¹, Zahur Ahmad¹, Rashid Amin^{1, *}, Sultan H. Almotiri², Mohammed A. Al Ghamdi², Hamza Aldabbas³

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2639-2663, 2020, DOI:10.32604/cmc.2020.011485

Abstract A large amount of data is present on the web which can be used for useful purposes like a product recommendation, price comparison and demand forecasting for a particular product. Websites are designed for human understanding and not for machines. Therefore, to make data machine-readable, it requires techniques to grab data from web pages. Researchers have addressed the problem using two approaches, i.e., knowledge engineering and machine learning. State of the art knowledge engineering approaches use the structure of documents, visual cues, clustering of attributes of data records and text processing techniques to identify data records on a web page.… More >

Wenbin Bi¹, Fang Yu², Ning Cao³, Wei Huo³, Guangsheng Cao^{4, *}, Xiuli Han⁵, Lili Sun⁶, Russell Higgs⁷

CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1837-1854, 2020, DOI:10.32604/cmc.2020.010420

Abstract Software defect feature selection has problems of feature space dimensionality reduction and large search space. This research proposes a defect prediction feature selection framework based on improved shuffled frog leaping algorithm (ISFLA).Using the two-level structure of the framework and the improved hybrid leapfrog algorithm's own advantages, the feature values are sorted, and some features with high correlation are selected to avoid other heuristic algorithms in the defect prediction that are easy to produce local The case where the convergence rate of the optimal or parameter optimization process is relatively slow. The framework improves generalization of predictions of unknown data samples… More >

Jinlin Wang¹, Xing Wang^{1, *}, Hongli Zhang¹, Binxing Fang¹, Yuchen Yang¹, Jianan Liu²

CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 2057-2073, 2020, DOI:10.32604/cmc.2020.011158

Abstract As a real-time and authoritative source, the official Web pages of organizations contain a large amount of information. The diversity of Web content and format makes it essential for pre-processing to get the unified attributed data, which has the value of organizational analysis and mining. The existing research on dealing with multiple Web scenarios and accuracy performance is insufficient. This paper aims to propose a method to transform organizational official Web pages into the data with attributes. After locating the active blocks in the Web pages, the structural and content features are proposed to classify information with the specific model.… More >