• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.933-942
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• 2024

With the development of AI, Chat GPT, an artificial intelligence chatbot that appeared in 2022, is rapidly spreading to a wide range of people and expanding its usefulness. This study was conducted to examine college students' intention to continue using Chat GPT using a technology acceptance model. As a result of the study, all of Chat GPT's features had a positive effect on college students' perceived usefulness and perceived ease of use. However, among the features of Chat GPT, system quality and relative advantages did not directly affect the intention to continue using it. However, it was confirmed that it had an effect when perceived usefulness and perceived ease of use were mediated. The perceived usefulness and perceived ease of Chat GPT were verified to have a positive effect on the intention to continue using it.

• Journal of Information Processing Systems
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• v.16 no.1
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• pp.155-170
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• 2020

Passive ranging is a critical part of machine vision measurement. Most of passive ranging methods based on machine vision use binocular technology which need strict hardware conditions and lack of universality. To measure the distance of an object placed on horizontal plane, we present a passive ranging method based on monocular vision system by smartphone. Experimental results show that given the same abscissas, the ordinatesis of the image points linearly related to their actual imaging angles. According to this principle, we first establish a depth extraction model by assuming a linear function and substituting the actual imaging angles and ordinates of the special conjugate points into the linear function. The vertical distance of the target object to the optical axis is then calculated according to imaging principle of camera, and the passive ranging can be derived by depth and vertical distance to the optical axis of target object. Experimental results show that ranging by this method has a higher accuracy compare with others based on binocular vision system. The mean relative error of the depth measurement is 0.937% when the distance is within 3 m. When it is 3-10 m, the mean relative error is 1.71%. Compared with other methods based on monocular vision system, the method does not need to calibrate before ranging and avoids the error caused by data fitting.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.96-106
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• 2020

To solve the limitation of traffic monitoring that occur from embedded sensor such as loop and piezo sensors, the thermal imaging camera was installed on the roadside. As the length of Class 1(passenger car) is getting longer, it is becoming difficult to classify from Class 3(2-axle truck) by using an embedded sensor. The collected images were labeled to generate training data. A total of 17,536 vehicle images (640x480 pixels) training data were produced. CNN (Convolutional Neural Network) was used to achieve vehicle classification based on thermal image. Based on the limited data volume and quality, a classification accuracy of 97.7% was achieved. It shows the possibility of traffic monitoring system based on AI. If more learning data is collected in the future, 12-class classification will be possible. Also, AI-based traffic monitoring will be able to classify not only 12-class, but also new various class such as eco-friendly vehicles, vehicle in violation, motorcycles, etc. Which can be used as statistical data for national policy, research, and industry.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.1
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• pp.221-228
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• 2018

Big data is an important keyword in World's Fourth Industrial Revolution in public and private division including IoT(Internet of Things), AI(Artificial Intelligence) and Cloud system in the fields of science, technology, industry and society. Big data based on services are available in various fields such as transportation, weather, medical care, and marketing. In particular, in the field of sports, various types of bio-signals can be collected and managed by the appearance of a wearable device that can measure vital signs in training or rehabilitation for daily life rather than a hospital or a rehabilitation center. However, research on big data with vital signs from wearable devices for training and rehabilitation for baseball players have not yet been stimulated. Therefore, in this paper, we propose a system for baseball infield and outfield players, especially which can store and analyze the momentum measurement vital signals based on big data.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.4
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• pp.210-219
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• 2023

The decline in the rural populace and an aging workforce have led to fatalities due to worsening environments and hazards within vinyl greenhouses. Therefore, it is necessary to automate crop cultivation and disease detection system in greenhouses to prevent labor loss. In this paper, an object detection-based model is used to detect diseased crop in greenhouses. In addition, the system proposed configures the environment of the artificial intelligence model in the cloud to ensure stability. The system captures images taken inside the vinyl greenhouse and stores them in a database, and then downloads the images to the cloud to perform inference based on Yolo-v4 for detection, generating JSON files for the results. Analyze this file and send it to the database for storage. From the experimental results, it was confirmed that disease detection through object detection showed high performance in real environments like vinyl greenhouses. It was also verified that efficient monitoring is possible through the database

• The Journal of the Convergence on Culture Technology
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• v.6 no.2
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• pp.437-447
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• 2020

The purpose of this study is to research the countermeasures and expected effects through the use of drones in the field of disaster prevention as a drone-based smart quarantine performance method. The environmental, market, and technological approaches to the review of the current quarantine performance task and its countermeasures are as follows. First, in terms of the environment, the effectiveness of the quarantine performance business using drone-based control is to broaden the utilization of forest, bird flu, livestock, facility areas, mosquito larvae, pests, and to simplify and provide various effective prevention systems such as AI and cholera. Second, in terms of market, the standardization of livestock and livestock quarantine laws and regulations according to the use of disinfection and quarantine missions using domestic standardized drones through the introduction of new technologies in the quarantine method, shared growth of related industries and discovery of new markets, and animal disease prevention It brings about the effect of annual budget savings. Third, the technical aspects are (1) on-site application of disinfection and prevention using multi-drone, a new form of animal disease prevention, (2) innovation in the drone industry software field, and (3) diversification of the industry with an integrated drone control / control system applicable to various markets. (4) Big data drone moving path 3D spatial information analysis precise drone traffic information ensures high flight safety, (5) Multiple drones can simultaneously auto-operate and fly, enabling low-cost, high-efficiency system deployment, (6) High precision that this was considered due to the increase in drone users by sector due to the necessity of airplane technology. This study was prepared based on literature surveys and expert opinions, and the future research field needs to prove its effectiveness based on empirical data on drone-based services. The expected effect of this study is to contribute to the active use of drones for disaster prevention work and to establish policies related to them.

• Smart Structures and Systems
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• v.25 no.4
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• pp.401-408
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• 2020

This paper deals with the problem of global stabilization for a class of nonlinear control systems. An effective approach is proposed for controlling the system interaction of structures through a combination of parallel distributed compensation (PDC) intelligent controllers and fuzzy observers. An efficient approximate inference algorithm using expectation propagation and a Bayesian additive model is developed which allows us to predict the total number of control systems, thereby contributing to a more adaptive trajectory for the closed-loop system and that of its corresponding model. The closed-loop fuzzy system can be made as close as desired, so that the behavior of the closed-loop system can be rigorously predicted by establishing that of the closed-loop fuzzy system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.873-879
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• 2020

The importance of data as a core resource of the 4th industrial revolution is emerging, and companies illegally collect and use personal data. In the financial sector, active research is conducted to safely manage personal data and provide better services using blockchain, big data, and AI technology. In this paper, we propose a system that can safely manage personal data by using blockchain technology, which can be used without changing the existing system. The composition of this system consists of a blockchain, blockchain linkages, a service provider, and a user (i.e., an app). Blockchain can be used regardless of its type and form, and services are provided by classifying blockchains and services in the blockchain linkages. Service providers can access personal data only after requesting and receiving delegated permission from users. Existent MyData services store all data in a user's mobile phone, so information may get leaked due to jailbreaks or rooting. But in the proposed system, personal data are stored in blockchain so information leakage can be prevented. In the future, we will study ways to provide customized services using personal data stored in blockchain.

• Journal of Information Technology Services
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• v.20 no.2
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• pp.57-76
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• 2021

Today's ERP system has become a core system of IT·SW that not only supports and manages enterprise resources efficiently, but also encompasses major business tasks. In other words, the ERP system is an essential strategic element for the survival of a company as a powerful means to innovate the management of an organization. This study analyzed the impact on the utilization of IT·SW from the perspective of the entire organization's process without limiting the performance evaluation of the ERP system itself, which is a core system of a company. The measurement data for evaluating the performance of the ERP system was the 2018 domestic company IT·SW utilization survey result report (subject to survey : 3,017 domestic companies with 10 or more employees). Based on this data, this study analyzed the impact of the ERP system on the entire enterprise's IT·SW utilization. In particular, attention was paid to whether there would be a difference in the use of IT·SW if the type of ERP system introduction was changed through the improvement of the business process of the company. Multiple regression analysis was performed using the statistical package SPSS 25. As a result, among the ERP system introduction types, the greatest degree of (+)influence on the company's IT·SW utilization is when the ERP package SW or ASP service is used as it is. Although the difference is insignificant, the second case was to build an ERP system through self-development or outsourcing, followed by customizing the package SW or system through self-development or outsourcing. Through the results of this study, it is expected that the organization will improve the business process and use the standard ERP package SW as it is without modification, thereby effectively enhancing the use of IT·SW of the company and leading to management performance.

• Journal of Animal Environmental Science
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• v.18 no.2
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• pp.85-90
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• 2012

In Korea, livestock has grown into the most value-added business in the agricultural and forest industry. But due to the recent outbreak of deadly infectious diseases such as foot-and-mount disease and avian influenza (AI), the demand for IT-enabled cutting-edge management system is getting stronger. As for humans, pilot projects and researches concerning U-healthcare have been carried out since early 2000. So this study explored the current progress of U-healthcare introduction, and suggested the strategies to develop technologies of collecting, processing, and utilizing information; to apply elements for a service model development and prioritization; to provide policy and institutional support. Therefore it is expected to vitalize the livestock U-healthcare in the future through continuous study based on these results.