• Journal of Practical Engineering Education
• /
• v.14 no.3
• /
• pp.573-577
• /
• 2022

In this paper, the operation of the Korean digital key talent training project (K-Digital Training) supported by the Ministry of Labor in 2022 began in 2021, and through public offering in the second half of 2022, 403 training courses are held to secure 33,000 annual training personnel. Accordingly, because of performance analysis on learning satisfaction in each field of the state-led talent development program to respond quickly to future industrial changes by fostering digital talent, the overall satisfaction with the program was very high at 4.27 on average. However, the initial expectation for employment linkage is decreasing from 4.2 to 3.91 at the end of learning. Therefore, it is expected that the satisfaction level of the program can be continuously improved only when the organizations participating in the program are prepared in advance for employment linkage

• Journal of Practical Engineering Education
• /
• v.14 no.3
• /
• pp.491-498
• /
• 2022

In this paper, as a liberal arts course for non-major students, a case study of recurrent neural network SW practice, which is essential for designing a basic recurrent neural network subject curriculum, was developed. The developed SW practice case focused on understanding the operation principle of the recurrent neural network, and used a spreadsheet to check the entire visualized operation process. The developed recurrent neural network practice case consisted of creating supervised text completion training data, implementing the input layer, hidden layer, state layer (context node), and output layer in sequence, and testing the performance of the recurrent neural network on text data. The recurrent neural network practice case developed in this paper automatically completes words with various numbers of characters. Using the proposed recurrent neural network practice case, it is possible to create an artificial intelligence SW practice case that automatically completes by expanding the maximum number of characters constituting Korean or English words in various ways. Therefore, it can be said that the utilization of this case of basic practice of recurrent neural network is high.

• Journal of Korea Society of Industrial Information Systems
• /
• v.28 no.5
• /
• pp.31-39
• /
• 2023

The evolution of Natural Language Processing (NLP) and the rise of large language models (LLM) like ChatGPT have paved the way for specialized question-answering (QA) systems tailored to specific domains. This study outlines a system harnessing the power of LLM in conjunction with document search algorithms to interpret and address user inquiries using documents from the Korea Atomic Energy Research Institute (KAERI). Initially, the system refines multiple documents for optimized search and analysis, breaking the content into managable paragraphs suitable for the language model's processing. Each paragraph's content is converted into a vector via an embedding model and archived in a database. Upon receiving a user query, the system matches the extracted vectors from the question with the stored vectors, pinpointing the most pertinent content. The chosen paragraphs, combined with the user's query, are then processed by the language generation model to formulate a response. Tests encompassing a spectrum of questions verified the system's proficiency in discerning question intent, understanding diverse documents, and delivering rapid and precise answers.

• Journal of Internet of Things and Convergence
• /
• v.9 no.6
• /
• pp.45-50
• /
• 2023

In software development, the elicitation and analysis of requirements is a crucial phase, and it involves considerable time and effort due to the involvement of various stakeholders. ChatGPT, having been trained on a diverse array of documents, is a large language model that possesses not only the ability to generate code and perform debugging but also the capability to be utilized in the domain of software analysis and design. This paper proposes a method of requirements engineering that leverages ChatGPT's capabilities for eliciting software requirements, analyzing them to align with system goals, and documenting them in the form of use cases. In software requirements engineering, it suggests that stakeholders, analysts, and ChatGPT should engage in a collaborative model. The process should involve using the outputs of ChatGPT as initial requirements, which are then reviewed and augmented by analysts and stakeholders. As ChatGPT's capability improves, it is anticipated that the accuracy of requirements elicitation and analysis will increase, leading to time and cost savings in the field of software requirements engineering.

• Journal of the Korea Society of Computer and Information
• /
• v.28 no.12
• /
• pp.67-77
• /
• 2023

This study represents an innovative research conducted in the smart farm environment, developing a deep learning-based disease and pest detection model and applying it to the Intelligent Internet of Things (IoT) platform to explore new possibilities in the implementation of digital agricultural environments. The core of the research was the integration of the latest ImageNet models such as Pseudo-Labeling, RegNet, EfficientNet, and preprocessing methods to detect various diseases and pests in complex agricultural environments with high accuracy. To this end, ensemble learning techniques were applied to maximize the accuracy and stability of the model, and the model was evaluated using various performance indicators such as mean Average Precision (mAP), precision, recall, accuracy, and box loss. Additionally, the SHAP framework was utilized to gain a deeper understanding of the model's prediction criteria, making the decision-making process more transparent. This analysis provided significant insights into how the model considers various variables to detect diseases and pests.

• International Journal of Advanced Culture Technology
• /
• v.11 no.4
• /
• pp.310-316
• /
• 2023

This study aims to predict uncertain future scenarios that may unfold in South Korea in the near future, utilizing the theory of extreme events(X-events). A group of 32 experts, consisting of government emergency planning officers, was selected as the focus group to achieve this objective. Using the Focus Group Interview (FGI) technique, opinions were gathered from this focus group regarding potential X-events that may occur within the advanced science and technology domains over the next 10 years. The analysis of these opinions revealed that government emergency planning officers regarded the "Obsolescence of current technology and systems," particularly in the context of cyber network paralysis as the most plausible X-event within science and technology. They also put forth challenging and intricate opinions, including the emergence of new weapon systems and ethical concerns associated with artificial intelligence (AI). Given that X-events are more likely to emerge in unanticipated areas rather than those that are widely predicted, the results obtained from this study carry significant importance. However, it's important to note that this study is grounded in a limited group of experts, highlighting the necessity for subsequent research involving a more extensive group of experts. This research seeks to stimulate studies on extreme events at a national level and contribute to the preparation for future X-event predictions and strategies for addressing them.

• KIPS Transactions on Computer and Communication Systems
• /
• v.12 no.12
• /
• pp.357-362
• /
• 2023

Bridges are important transportation infrastructure, but they are subject to damage and cracking due to various environmental factors and constant traffic loads, which accelerate their aging. With many bridges now older than their original construction, there is a need for systems to ensure safety and diagnose deterioration. Bridges are already utilizing structural health monitoring (SHM) technology to monitor the condition of bridges in real time or periodically. Along with this technology, the development of intelligent bridge monitoring technology utilizing artificial intelligence and Internet of Things technology is underway. In this paper, we study an edge system technique for predicting bridge safety using fast Fourier transform and dimensionality reduction algorithm for maintenance of aging bridges. In particular, unlike previous studies, we investigate whether it is possible to form a dataset using sensor data collected from actual bridges and check the safety of bridges.

• KIPS Transactions on Software and Data Engineering
• /
• v.12 no.12
• /
• pp.525-534
• /
• 2023

Gas leak detection system is a key to minimize the loss of life due to the explosiveness and toxicity of gas. Most of the leak detection systems detect by gas sensors or thermal imaging cameras. To improve the performance of gas leak detection system using single-modal methods, the paper propose multimodal approach to gas sensor data and thermal camera data in developing a gas type identification model. MultimodalGasData, a multimodal open-dataset, is used to compare the performance of the four models developed through multimodal approach to gas sensors and thermal cameras with existing models. As a result, 1D CNN and GasNet models show the highest performance of 96.3% and 96.4%. The performance of the combined early fusion model of 1D CNN and GasNet reached 99.3%, 3.3% higher than the existing model. We hoped that further damage caused by gas leaks can be minimized through the gas leak detection system proposed in the study.

• Journal of Korean Elementary Science Education
• /
• v.43 no.1
• /
• pp.148-157
• /
• 2024

The purpose of this study was to develop an artificial intelligence-based marine ecological education program to improve the ecological sensitivity of elementary school students. The program was taught 11 times within 4 weeks, and an ecological sensitivity test was conducted before and after the program. The statistical results of the tests showed that the developed program improved the ecological sensitivity of elementary school students. Through in-depth interviews, improvements were found in all the areas, such as empathy for the living things, interest in nature, enjoyment of nature, and wonder about nature. Through the marine ecological classes, which used artificial intelligence and virtual reality, the students were able to get closer to nature, and the student participation activities showed a positive effect on their ecological sensitivity. This indicates that experience-oriented education methods are more effective than simple explanatory classes to improve the students' ecological sensitivity, and artificial intelligence technology proved effective in increasing the students' immersion in the class.

• Journal of Society of Preventive Korean Medicine
• /
• v.28 no.1
• /
• pp.31-42
• /
• 2024

Objective : In order to understand the changes in domestic approval regulations applicable to traditional Korean medical device companies, this article will explain the major amendments 「Regulation on Medical Device Approval Report Review, etc.」 from 2005 to the present on a year-by-year basis, and provide a counter plan to the recent changes in approval regulations. Methods : We analysed the changes in approval regulatory amendments related to the traditional Korean medical devices from 2005 to the present. Results : The Ministry of Food and Drug Safety is continuously improving medical device approval regulations to ensure the global competitiveness of domestic medical devices and contribute to the improvement of public health. Recent major approval regulatory amendments include the establishment of a review system for software medical devices and digital therapeutics, the recognition of real world evidence materials, the introduction of a biological evaluation of medical devices within a risk management process and a medical device approval licence renewal system. Conclusions : It is expected that the range of medical devices available to Korean medicine doctors will continue to expand in the future through the provision of non-face-to-face medical services and the development of advanced and new medical devices, as well as wearable medical devices and digital therapeutics. In order to increase the market entry potential of traditional Korean medical devices that incorporate advanced technologies such as digital technology and AI-based diagnosis and prediction technology, it is urgent that the government provide significant support to traditional Korean medical device companies to improve approval regulatory compliance.