• Journal of the Ergonomics Society of Korea
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• v.31 no.4
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• pp.507-513
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• 2012

Objective: This study developed a hierarchy of conditions of applications(devices), situations and functions which are applicable to gesture interface. Background: Gesture interface is one of the promising interfaces for our natural and intuitive interaction with intelligent machines and environments. Although there were many studies related to developing new gesture-based devices and gesture interfaces, it was little known which applications, situations and functions are applicable to gesture interface. Method: This study searched about 120 papers relevant to designing and applying gesture interfaces and vocabulary to find the gesture applicable conditions of applications, situations and functions. The conditions which were extracted from 16 closely-related papers were rearranged, and a hierarchy of them was developed to evaluate the applicability of applications, situations and functions to gesture interface. Results: This study summarized 10, 10 and 6 conditions of applications, situations and functions, respectively. In addition, the gesture applicable condition hierarchy of applications, situation and functions were developed based on the semantic similarity, ordering and serial or parallel relationship among them. Conclusion: This study collected gesture applicable conditions of application, situation and functions, and a hierarchy of them was developed to evaluate the applicability of gesture interface. Application: The gesture applicable conditions and hierarchy can be used in developing a framework and detailed criteria to evaluate applicability of applications situations and functions. Moreover, it can enable for designers of gesture interface and vocabulary to determine applications, situations and functions which are applicable to gesture interface.

• Journal of Digital Convergence
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• v.18 no.7
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• pp.47-56
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• 2020

The purpose of this study is to comprehensively analyze elementary school teachers' perceptions of the use of artificial intelligence in education. Recently, interest in the use of artificial intelligence has increased in the field of education. However, there is a lack of research on the perceptions of elementary school teachers using AI in education. Using descriptive statistics, multiple linear regression analysis, and semantic differential meaning scale, 69 elementary school teachers' perceptions of using AI in education were analyzed. As a results, artificial intelligence technology was perceived as most suitable method for assisting activities in class and for problem-based learning. Factors which influence the use of AI in education were learning contents, learning materials, and AI tools. AI in education had the features of personalized learning, promoting students' participation, and provoking students' interest. Further, instructional strategies or models that enable optimized educational operation should be developed.

• Journal of Digital Contents Society
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• v.8 no.4
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• pp.509-519
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• 2007

For Knowledge Information Governance, integration search mechanism of Knowledge Information is required in various industries. But when Knowledge Information system constructs in each professional field, it developed and used its own metadata format. Accordingly, if distributed information system searches using metadata, heterogeneous problems are occurred among metadata. For integration search, it needs a consistency management of metadata. Therefore, this paper defines a standard metadata that represent standard metadata as surveying a used metadata in each field systems. Also, we propose a metadata registry integration framework for Knowledge Information Governance. It enables an integration search service without a metadata modification of existing system. Through the proposed framework, it can registries and manages efficiently the existing metadata. Also, it enables a semantically extended search using semantic relation between metadata.

• Journal of the Korea Society of Computer and Information
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• v.13 no.2
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• pp.1-9
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• 2008

As the size of software becomes larger and the features of it become complex. it is really hard to successfully complete the project without following development guidelines. Software process is the best practices and procedures that organizations of high maturity and capability of software development carry out in common, and it is a set of progressive ideas of management. However, complicated and unfamiliar concepts can interrupt the introduction and improvement of software process of the organizations. Even though many kinds of frameworks such as standard of process and maturity measurement models are introduced, it is still difficult to follow software process without fully understanding their relations. The purpose of this study is to support successful internalization of organizations that introduce and use software process. It also suggests the design of standard ontology, standard relationship domain ontology, and the lifestyle of software process and the relations between them.

• Journal of Digital Convergence
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• v.19 no.8
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• pp.301-310
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• 2021

The purpose of the study was to induce meaning of the UX design from users' interview. The study covers interviews from 20 untact finance application users in their twenties in written form. It aims to examine previous studies on UX design and to overcome their shortcomings by categorizing usability qualities focusing on verbs used in the interview. The followings are the result: Usability of UX design can be summarized into Unity, Trust, Persistency, Recognition and Approachability of the information to the 20 users in their twenties. As for the data earned from interviews focusing on verbs, usability included Security, Familiarity, Accessibility, Convenience of Operation and Visibility. Each of the qualities fell into related categories such as Security, Information, Brand and Design. In conclusion, analysis based on verb choices led to better understanding of the user-based experience compared to using objective means in previous studies and can be a suggestion to make up for errors in the former evaluation process.

• Journal of Digital Convergence
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• v.17 no.6
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• pp.427-431
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• 2019

The purpose of this study was to investigate whether the mirror environment influences the attitude of the client when counselling. A group of 16 experimenters, 16 controls, a group with a mirror environment, and 32 men and women according to the presence or absence of interventional mirror environments in the control group. There was a statistically significant difference in the 'self - alienation' factor of the Authentic Scale(AS) in the experimental group that provided the mirror environment. There was no significant difference in the Semantic Differential Scale(SDS) between the experimental group and the control group. This study was conducted to investigate whether the presence of the mirror environment affects the client 's authenticity. There were significant differences in some of the factors of the Authentic Scale.

• The Journal of Society for e-Business Studies
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• v.23 no.4
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• pp.19-39
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• 2018

Recently, fake news has attracted worldwide attentions regardless of the fields. The Hyundai Research Institute estimated that the amount of fake news damage reached about 30.9 trillion won per year. The government is making efforts to develop artificial intelligence source technology to detect fake news such as holding "artificial intelligence R&D challenge" competition on the title of "searching for fake news." Fact checking services are also being provided in various private sector fields. Nevertheless, in academic fields, there are also many attempts have been conducted in detecting the fake news. Typically, there are different attempts in detecting fake news such as expert-based, collective intelligence-based, artificial intelligence-based, and semantic-based. However, the more accurate the fake news manipulation is, the more difficult it is to identify the authenticity of the news by analyzing the news itself. Furthermore, the accuracy of most fake news detection models tends to be overestimated. Therefore, in this study, we first propose a method to secure the fairness of false news detection model accuracy. Secondly, we propose a method to identify the authenticity of the news using the social data broadly generated by the reaction to the news as well as the contents of the news.

• Journal of Convergence for Information Technology
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• v.9 no.8
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• pp.221-232
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• 2019

This study aimed at finding out special education teachers' failure and success factors in teacher recruitment examinations. Total of 24 special education teachers participated in the semi-structured interview and 12 separate semantic themes were extracted via continuous comparative analysis on the interview contents. The findings were the following. First, the identified factors for the failures on the examinations were merely following what others do, failure-causing learning strategies, unconditional memorization, ineffective study groups, anxiety and lack of confidence, and lack self-management issue. Second, the identified factors for the success on the examinations were my style of study habits, success-causing learning strategies, balance of understanding and memorization, effective study groups, positivity, and strong self routine. The research proposes several practical applications to prepare the exam regarding this results.

• The Journal of Society for e-Business Studies
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• v.26 no.3
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• pp.119-132
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• 2021

Identification of associated knowledge based on content relevance is a fundamental functionality in managing service and security of core knowledge. This study compares the performance of methods to identify associated knowledge based on content relevance, i.e., the associated document network composition performance of keyword-based and word-embedding approach, to examine which method exhibits superior performance in terms of quantitative and qualitative perspectives. As a result, the keyword-based approach showed superior performance in core document identification and semantic information representation, while the word embedding approach showed superior performance in F1-Score and Accuracy, association intensity representation, and large-volume document processing. This study can be utilized for more realistic associated knowledge service management, reflecting the needs of companies and users.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.307-313
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• 2021

In this paper, a lightweight network with fewer parameters compared to the existing object detection method is proposed. In the case of the currently used detection model, the network complexity has been greatly increased to improve accuracy. Therefore, the proposed network uses EfficientNet as a feature extraction network, and the subsequent layers are formed in a pyramid structure to utilize low-level detailed features and high-level semantic features. An attention process was applied between pyramid structures to suppress unnecessary noise for prediction. All computational processes of the network are replaced by depth-wise and point-wise convolutions to minimize the amount of computation. The proposed network was trained and evaluated using the PASCAL VOC dataset. The features fused through the experiment showed robust properties for various objects through a refinement process. Compared with the CNN-based detection model, detection accuracy is improved with a small amount of computation. It is considered necessary to adjust the anchor ratio according to the size of the object as a future study.