• The Journal of the Convergence on Culture Technology
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• v.5 no.1
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• pp.361-369
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• 2019

With the commercialization of the ADAS functions, the need for the experience of the autonomous driving system is increasing, and the role of the artificial intelligence agent is attracting attention. This study is an autonomous driving experience experiment that verifies the effect of self-efficacy and agent embodiment. Through a simulator experiment, we measured the effect of existence of self-efficacy and agent embodiment on social presence, perceived risk, and perceived ease of use. Results show that self-efficacy had a positive effect on social presence and perceived risk, and agent embodiment negatively affected perceived ease of use. Based on the results of the study, we proposed guidelines for agent design that can increase the acceptance of the semi-autonomous driving system.

• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.217-223
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• 2022

In this paper, the needs and environment of the 'AI Convergence Education Method' were analyzed for elementary and secondary teachers, and based on this, teaching efficacy of informatics education was verified. For the research, elementary and secondary teachers who take the subject were selected, and based on the results of analyzing the general characteristics, pre-knowledge level, and needs of the subject, curriculum for 15 weeks was developed. As a result of verifying the teaching efficacy effectiveness of the developed 'AI Convergence Education Method' subject for 15 weeks, the effectiveness of the information education teaching efficacy was verified. Among the factors, there were statistically significant differences in information teaching values and information teaching strategies. In the future, it is necessary to conduct follow-up research to secure teachers' professionalism, such as linking with schools and convergence with other subjects. Various teaching and learning materials and teaching and learning methods such as educational contents and materials, reference literature, and artificial intelligence education platforms need to be prepared.

• The Journal of the Korea Contents Association
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• v.19 no.9
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• pp.1-10
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• 2019

The purpose of this study is to investigate the influence of exogenous variables on the intention to use AI speaker. An online survey was administrated to 305 AI speaker users in order to examine the effect of the personal characteristics (self-efficacy, innovativeness, suitability, and enjoyment) and social impact (social conformity and social image) on perceived usefulness and easiness. The results indicate that (1) self-efficacy and social conformity have positively effect on perceived easiness; (2) suitability and social image have positively effect on perceived usefulness whereas innovativeness has negatively effect on perceived usefulness; (3) perceived usefulness and perceived easiness have significant effect on the intention to use AI speaker.

• Journal of Information Technology Services
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• v.23 no.1
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• pp.81-95
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• 2024

ChatGPT, a generative artificial intelligence(AI) technology that analyzes conversations to identify users' intentions and generates responses in consideration of the context of the conversation, is attracting attention from a user interface (UI) perspective that it can provide information through natural conversations with users. This study examined the effect of functional and playful values experienced by early users of ChatGPT on reuse intention and verified the structural relationship between technological efficacy, experiential values, and reuse intention. To verify the research model and hypotheses, a survey was conducted on college students who used ChatGPT for the first time. A total of 156 responses were received and 154 responses were used for analysis. As a result, both the functional experiential value and playful experiential value in the initial use process had significant effects on the intention to use ChatGPT. In addition, it was found that technological efficiency had a significant effect on functional and playful experiential values.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.283-291
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• 2021

In this paper, we propose the development and application of a software education program for underachievers. The software education program for underachieving students was developed in consideration of the characteristics of learner's suffering from underachievement and the educational effects of software education, and is meaningful in that it proposes a plan to improve the learning gap in distance learning. Learners can acquire digital literacy and learning skills by solving structured tasks in the form of courseware, intelligent tutoring, debugging, and artificial intelligence learning models in educational programs. Based on the effects of software education, such as enhancing logical thinking ability and problem solving ability, this program provides opportunities to solve fusion tasks to underachievers. Based on this, it is expected that it can have a positive effect on the overall academic work.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1797-1808
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• 2021

Artificial intelligence is considered one of the core technologies leading the 4th industrial revolution. It is adopted in various fields bringing about a huge paradigm shift throughout our society. The field of biotechnology is no exception. It is undergoing innovative development by converging with other disciplines such as computers, electricity, electronics, and so on. In drug discovery and development, big data-based AI technology has a great potential of improving the efficiency and quality of drug development, rapidly advancing to overcome the limitations in the existing drug development process. AI technology is to be specialized and developed for the purpose including clinical efficacy and safety-related end points based on the multidisciplinary knowledge such as biology, chemistry, toxicology, pharmacokinetics, etc. In this paper, we review the current status of AI technology applied for drug discovery and consider its limitations and future direction.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.119-124
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• 2023

Deep learning has recently demonstrated conspicuous efficacy across diverse domains than traditional machine learning techniques, as the most popular approach for pattern recognition. The classification problems for tabular data, however, are remain for the area of traditional machine learning. This paper introduces a novel network module designed to tabular data into high-dimensional tensors. The module is integrated into conventional deep learning networks and subsequently applied to the classification of structured data. The proposed method undergoes training and validation on four datasets, culminating in an average accuracy of 90.22%. Notably, this performance surpasses that of the contemporary deep learning model, TabNet, by 2.55%p. The proposed approach acquires significance by virtue of its capacity to harness diverse network architectures, renowned for their superior performance in the domain of computer vision, for the analysis of tabular data.

• Structural Engineering and Mechanics
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• v.91 no.1
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• pp.1-23
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• 2024

This paper formulates a new integral shear deformation shell theory to investigate the free vibration response of carbon nanotube (CNT) reinforced structures with only four independent variables, unlike existing shell theories, which invariably and implicitly induce a host of unknowns. This approach guarantees traction-free boundary conditions without shear correction factors, using a non-polynomial hyperbolic warping function for transverse shear deformation and stress. By introducing undetermined integral terms, it will be possible to derive the motion equations with a low order of differentiation, which can facilitate a closed-form solution in conjunction with Navier's procedure. The mechanical properties of the CNT reinforcements are modeled to vary smoothly and gradually through the thickness coordinate, exhibiting different distribution patterns. A comparison study is performed to prove the efficacy of the formulated shell theory via obtained results from existing literature. Further numerical investigations are current and comprehensive in detailing the effects of CNT distribution patterns, volume fractions, and geometrical configurations on the fundamental frequencies of CNT-reinforced nanocomposite shells present here. The current shell theory is assumed to serve as a potent conceptual framework for designing reinforced structures and assessing their mechanical behavior.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.4
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• pp.46-55
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• 1997

This paper presents the development of intelligent performance management of computer communication networks for larger-scale integrated systems and the demonstration of its efficacy using computer simula- tion. The innermost core of the performance management is based on fuzzy set theory. This fuzzy perfor- mance manager has learning ability by using principles of neuro-fuzzy model, neuralnetwork, genetic algo- rithm(GA). Two types of performance managers are described in this paper. One is the Neuro-Fuzzy Per- formance Manager(NFPM) of which learning ability is based on the conventional gradient method, and the other is GA-based Neuro-Fuzzy Performance Manager(GNFPM)with its learning ability based on a genetic algorithm. These performance managers have been evaluated via discrete event simulation of a computer network.

• Proceedings of the Korea Contents Association Conference
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• 2016.05a
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• pp.285-286
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• 2016

본 연구는 가상현실시스템을 이용한 훈련이 뇌졸중 환자의 균형과 낙상효능감에 미치는 영향을 알아보기 위해 실시하였다. 연구 대상자는 뇌졸중 환자 20명으로 실험군 10명 대조군 10명씩 각각 배정하였다. 실험군과 대조군 모두 일반적인 주 5회의 물리치료와 작업치료를 받았다. 실험군은 추가적으로 가상현실 프로그램을 이용하여 8주간 1일 20분 주 3회 시행하였다. 본 연구의 측정은 균형수행 능력검사, 낙상효능감 척도검사를 사용하였다. 두 군 간 훈련 후 측정 사이에 균형수행 능력검사와, 낙상효능감 검사에서 통계적으로 유의한 차이를 보였다(p<0.05). 또한 각 군 간 훈련 후 측정 사이에 균형수행 능력검사와, 낙상효능감 검사에서 통계적으로 유의한 차이를 보였다(p<0.05). 따라서 가상현실 프로그램 병행한 훈련이 뇌졸중 환자의 균형과 낙상효능감을 향상시키는데 긍적적인 도움을 주어 유용한 뇌졸중 환자의 치료 프로그램으로 사용될 수 있을 것으로 보여 진다.