Zhen Zhen¹, Jian Gao^1,2,*

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 299-323, 2023, DOI:10.32604/cmc.2023.042090

Abstract In recent years, cyber attacks have been intensifying and causing great harm to individuals, companies, and countries. The mining of cyber threat intelligence (CTI) can facilitate intelligence integration and serve well in combating cyber attacks. Named Entity Recognition (NER), as a crucial component of text mining, can structure complex CTI text and aid cybersecurity professionals in effectively countering threats. However, current CTI NER research has mainly focused on studying English CTI. In the limited studies conducted on Chinese text, existing models have shown poor performance. To fully utilize the power of Chinese pre-trained language models (PLMs) and conquer the problem… More >

Ankush Kapoor¹, Pradeep Kumar^2,*, Ranjan Mishra³

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 341-361, 2023, DOI:10.32604/cmc.2023.028874

Abstract Frequency selective surfaces (FSSs) play an important role in wireless systems as these can be used as filters, in isolating the unwanted radiation, in microstrip patch antennas for improving the performance of these antennas and in other 5G applications. The analysis and design of the double concentric ring frequency selective surface (DCRFSS) is presented in this research. In the sub-6 GHz 5G FR1 spectrum, a computational synthesis technique for creating DCRFSS based spatial filters is proposed. The analytical tools presented in this study can be used to gain a better understanding of filtering processes and for constructing the spatial filters.… More >

T. Mithila^1,*, R. Arunprakash², A. Ramachandran³

Computer Systems Science and Engineering, Vol.42, No.3, pp. 1165-1179, 2022, DOI:10.32604/csse.2022.023308

Abstract In today’s real world, an important research part in image processing is scene text detection and recognition. Scene text can be in different languages, fonts, sizes, colours, orientations and structures. Moreover, the aspect ratios and layouts of a scene text may differ significantly. All these variations appear assignificant challenges for the detection and recognition algorithms that are considered for the text in natural scenes. In this paper, a new intelligent text detection and recognition method for detectingthe text from natural scenes and forrecognizing the text by applying the newly proposed Conditional Random Field-based fuzzy rules incorporated Convolutional Neural Network (CR-CNN)… More >

K. Sangeetha^1,*, D. Prabha²

Computer Systems Science and Engineering, Vol.40, No.2, pp. 735-747, 2022, DOI:10.32604/csse.2022.019310

Abstract Educational institutions showing interest to find the opinion of the students about their course and the instructors to enhance the teaching-learning process. For this, most research uses sentiment analysis to track students’ behavior. Traditional sentence-level sentiment analysis focuses on the whole sentence sentiment. Previous studies show that the sentiments alone are not enough to observe the feeling of the students because different words express different sentiments in a sentence. There is a need to extract the targets in a given sentence which helps to find the sentiment towards those targets. Target extraction is the subtask of targeted sentiment analysis. In… More >

Yongjin Hu¹, Yuanbo Guo¹, Junxiu Liu², Han Zhang^{3, *}

CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1297-1315, 2020, DOI:10.32604/cmc.2020.010855

Abstract In the field of information security, a gap exists in the study of coreference resolution of entities. A hybrid method is proposed to solve the problem of coreference resolution in information security. The work consists of two parts: the first extracts all candidates (including noun phrases, pronouns, entities, and nested phrases) from a given document and classifies them; the second is coreference resolution of the selected candidates. In the first part, a method combining rules with a deep learning model (Dictionary BiLSTM-Attention-CRF, or DBAC) is proposed to extract all candidates in the text and classify them. In the DBAC model,… More >