Hasan Han¹, Oguzcan Karadeniz¹, Tugba Dalyan^2,*, Elena Battini Sonmez², Baykal Sarioglu¹

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 1209-1224, 2023, DOI:10.32604/iasc.2023.030674

Abstract Robot companions will soon be part of our everyday life and students in the engineering faculty must be trained to design, build, and interact with them. The two affordable robots presented in this paper have been designed and constructed by two undergraduate students; one artificial agent is based on the Nvidia Jetson Nano development board and the other one on a remote computer system. Moreover, the robots have been refined with an empathetic system, to make them more user-friendly. Since automatic facial expression recognition skills is a necessary pre-processing step for acknowledging emotions, this paper tested different variations of Convolutional… More >

Yuling Chen^1,2, Junhong Tao¹, Tao Li^1,*, Jiangyuan Cai³, Xiaojun Ren⁴

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5141-5158, 2023, DOI:10.32604/cmc.2023.037783

Abstract With the development of cloud computing technology, more and more data owners upload their local data to the public cloud server for storage and calculation. While this can save customers’ operating costs, it also poses privacy and security challenges. Such challenges can be solved using secure multi-party computation (SMPC), but this still exposes more security issues. In cloud computing using SMPC, clients need to process their data and submit the processed data to the cloud server, which then performs the calculation and returns the results to each client. Each client and server must be honest. If there is cooperation or… More >

Zhifang Liao¹, Bolin Zhang¹, Xuechun Huang¹, Song Yu^1,*, Yan Zhang²

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 687-704, 2023, DOI:10.32604/cmes.2023.027466

Abstract Currently, open-source software is gradually being integrated into industrial software, while industry protocols in industrial software are also gradually transferred to open-source community development. Industrial protocol standardization organizations are confronted with fragmented and numerous code PR (Pull Request) and informal proposals, and different workflows will lead to increased operating costs. The open-source community maintenance team needs software that is more intelligent to guide the identification and classification of these issues. To solve the above problems, this paper proposes a PR review prediction model based on multi-dimensional features. We extract 43 features of PR and divide them into five dimensions: contributor,… More >

Zibo Wang^1,3, Chaobin Huo², Yaofang Zhang^1,3, Shengtao Cheng^1,3, Yilu Chen^1,3, Xiaojie Wei⁵, Chao Li⁴, Bailing Wang^1,3,*

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2957-2979, 2023, DOI:10.32604/cmc.2023.035694

Abstract With the growing discovery of exposed vulnerabilities in the Industrial Control Components (ICCs), identification of the exploitable ones is urgent for Industrial Control System (ICS) administrators to proactively forecast potential threats. However, it is not a trivial task due to the complexity of the multi-source heterogeneous data and the lack of automatic analysis methods. To address these challenges, we propose an exploitability reasoning method based on the ICC-Vulnerability Knowledge Graph (KG) in which relation paths contain abundant potential evidence to support the reasoning. The reasoning task in this work refers to determining whether a specific relation is valid between an… More >

Leilei Li¹, Yansheng Fu², Dongjie Zhu^2,*, Xiaofang Li³, Yundong Sun², Jianrui Ding², Mingrui Wu², Ning Cao^4,*, Russell Higgs⁵

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3295-3307, 2023, DOI:10.32604/iasc.2023.035257

Abstract The knowledge graph with relational abundant information has been widely used as the basic data support for the retrieval platforms. Image and text descriptions added to the knowledge graph enrich the node information, which accounts for the advantage of the multi-modal knowledge graph. In the field of cross-modal retrieval platforms, multi-modal knowledge graphs can help to improve retrieval accuracy and efficiency because of the abundant relational information provided by knowledge graphs. The representation learning method is significant to the application of multi-modal knowledge graphs. This paper proposes a distributed collaborative vector retrieval platform (DCRL-KG) using the multimodal knowledge graph VisualSem… More >

KAMILA CZUBAK-PROWIZOR^*, MARIA SWIATKOWSKA

BIOCELL, Vol.47, No.4, pp. 731-737, 2023, DOI:10.32604/biocell.2023.025677

Abstract Junctional adhesion molecule-A (JAM-A), also known as the F11 receptor (F11R), is one of the tight junction components. JAM-A is a transmembrane glycoprotein that regulates many cellular processes, i.e., angiogenesis, leukocyte transendothelial migration, intercellular permeability, epithelial-to-mesenchymal transition, and platelet activation. Of note, it is involved in the pathogenesis of various cancer types, including gynecological cancers. Only a few studies are available about this cancer type. Observed aberrant JAM-A expression in gynecological cancers correlates with poor patient prognosis. To the best of our knowledge, conflicting JAM-A roles in various cancer types suggest that its involvement is complex and tumor-type specific. The… More >

Heesup Han¹, Hong Ngoc Nguyen², Hyerin Lee³, Sanghyeop Lee^4,*

International Journal of Mental Health Promotion, Vol.25, No.4, pp. 449-469, 2023, DOI:10.32604/ijmhp.2023.025379

Abstract Since the outbreak of COVID-19, tourists have been increasingly concerned over various risks of international travel, while knowledge of the pandemic appears to vary significantly. In addition, as travel restrictions continue to impact adversely on international tourism, tourism efforts should be placed more on the domestic markets. Via structural equation modeling, this study unearthed different risk factors impacting Korean travelers’ choices of alternative local destinations in the post-pandemic era. In addition, this study extended the goal-directed behavior framework with the acquisition of perceived risk and knowledge of COVID-19, which was proven to hold a significantly superior explanatory power of tourists’… More >

Yuxuan Gu, Meng Wu^*, Qian Wang, Siguang Chen, Lijun Yang

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 493-512, 2023, DOI:10.32604/cmc.2023.035974

Abstract In this paper, a deep learning-based method is proposed for crowd-counting problems. Specifically, by utilizing the convolution kernel density map, the ground truth is generated dynamically to enhance the feature-extracting ability of the generator model. Meanwhile, the “cross stage partial” module is integrated into congested scene recognition network (CSRNet) to obtain a lightweight network model. In addition, to compensate for the accuracy drop owing to the lightweight model, we take advantage of “structured knowledge transfer” to train the model in an end-to-end manner. It aims to accelerate the fitting speed and enhance the learning ability of the student model. The… More >

Jingqi Li^1,*, Yijie Bian¹, Jun Guan², Lu Yang²

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1119-1137, 2023, DOI:10.32604/cmc.2023.035369

Abstract Promoting the co-constructing and sharing of organizational knowledge and improving organizational performance have always been the core research subject of knowledge management. Existing research focuses on the construction of knowledge management systems and knowledge sharing and transfer mechanisms. With the rapid development and application of cloud computing and big data technology, knowledge management is faced with many problems, such as how to combine with the new generation of information technology, how to achieve integration with organizational business processes, and so on. To solve such problems, this paper proposes a reciprocal collaborative knowledge management model (RCKM model) based on cloud computing… More >

Huaruo Chen^1,2, Ya Wen^3,*, Fei Liu^4,5, 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