• The Journal of the Korea Contents Association
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• v.11 no.7
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• pp.179-191
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• 2011

This study aims to elucidate the relationship between the characteristics of adult learners and flow in cyber-class along with relationships among flow, stress, and problem-solving ability. The research subjects were 1044 enrolled students at Cyber University located in Seoul through voluntary on-line questionnaire. The analysis is following: The components of flow on cyber-class including enjoyment, engagement, focused attention, and time-distortion show the significant difference upon the characteristics of adult learners such as school grade, age, marital status, and number of registered classes. In addition, the flow on cyber-class has the negative relationship with stress and the positive relationship with problem-solving ability. To improve the level of flow on cyber-class, it is important to develop the new on-line class and class materials with the consideration of characteristics and diverse backgrounds of adult learners. The incorporation of various interactive evaluation can also improve the flow level of adult learners in cyber class. Finally, the learning counselling service might be essential for adult learners to experience flow on cyber-class.

• Journal of the Korea Computer Industry Society
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• v.4 no.10
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• pp.611-620
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• 2003

This paper presents improved GUI based analysis tool o( load flow of power system (or contingency. It is effective tool to facilitate the teaching and learning of load flow of power system. This software is the named of PFGUI(Power Flow GUI) that written in TooIBookII of Asymetrix. The PFGUI is friendly for study for power system operation and control because picture provide a better visualizing of relationships between input parameters and effects than a tabula type result. This PFGUI enables topology and the output data of load flow for line outages to be shown on same picture page. Users can input the system data for power flow on the the picture and can easily see the the result diagram of bus voltage, bus power, line flow. It is also observe the effects of different types of variation of tap, shunt capacitor, loads level, line outages. Proposed PFGUI has been studied on the Ward-Hale 6-Bus system.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.5 no.4
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• pp.198-205
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• 2012

This study deals with development of an evaluating tool for flow experience and presence to evaluate interactive digital contents. The tool is able to measure the grade of flow and presence by surveying with their factors which are known to affect flow experience and presence. One of reasons for reducing flow experience and presence in 3D digital contents is that the experience in the virtual world is different from user's prerequisite learning in the real life. The recent interactive contents using physical movement of users as an input is possible to provide unsafe situation to users due to the different experience. The suggested flow measurement tool is able to evaluate presence and flow experience of an interactive 3D contents as well as flow and presence factors are possible to use as a general guideline for all stages of producing interactive 3D digital contents.

• Journal of the Korea Society of Computer and Information
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• v.25 no.11
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• pp.9-16
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• 2020

The TA-50 aircraft is conducting simulated training on various situations, including air-to-air and air-to-ground fire training, in preparation for air warfare. It is also used for pilot training before actual deployment. However, the TA-50 does not have the ability to operate smart weapon forces, limiting training. Therefore, the purpose of this study is to implement the TA-50 aircraft to enable virtual training of one of the smart weapons, the Point Direct Attack Munition (JDAM). First, JDAM functions implemented in FA-50 aircraft, a model similar to TA-50 aircraft, were analyzed. In addition, since functions implemented in FA-50 aircraft cannot be directly utilized by source code, algorithms were extracted using machine learning techniques(TensorFlow). The implementation of this function is expected to enable realistic training without actually having to be armed. Finally, based on the results of this study, we would like to propose ways to supplement the limitations of the research so that it can be implemented in the same way as it is.

• Journal of Convergence for Information Technology
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• v.11 no.11
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• pp.38-43
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• 2021

As the number of augmented reality games using augmented reality technology increases, the demands of users are also increasing. Game technologies used in augmented reality games are mainly games using MARKER, MARKERLESS, GPS, etc. Games using this technology can augment the background and other objects. To solve this problem, we want to help develop augmented reality games by analyzing objects in the background, which is an important element of augmented reality. To analyze the background in the augmented reality game, the background object was analyzed by applying a deep learning model using TensorFlow Lite in the UNITY engine. Using this result, we obtained the result that augmented objects can be placed in the game according to the types of objects analyzed in the background. By utilizing this research, it will be possible to develop advanced augmented reality games by augmenting objects that fit the background.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.47-52
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• 2021

Recently, demand for artificial intelligence solutions for production process management has been increasing in the manufacturing industry. However, through the application of AI solutions in the manufacturing industry, there are limitations to legacy smart factory solutions such as POP and MES.Therefore, in order to overcome this, this paper aims to improve production management efficiency by applying guidance, an artificial intelligence concept, to image recognition systems. In the system flow, As_is To be separated and actual work flow was applied, and the process was improved for overall productivity efficiency. The pre-processing plan for AI guidance learning was established and the relevant AI model was designed, developed, and simulated, resulting in a 97% recognition rate.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.587-593
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• 2021

In this thesis, we will break away from the classic DDoS response system for large-scale denial-of-service attacks that develop day by day, and effectively endure intelligent denial-of-service attacks by utilizing artificial intelligence-based technology, one of the core technologies of the 4th revolution. A possible service model development plan was proposed. That is, a method to detect denial of service attacks and minimize damage through machine learning artificial intelligence learning targeting a large amount of data collected from multiple security devices and web servers was proposed. In particular, the development of a model for using artificial intelligence technology is to detect a Western service attack by focusing on the fact that when a service denial attack occurs while repeating a certain traffic change and transmitting data in a stable flow, a different pattern of data flow is shown. Artificial intelligence technology was used. When a denial of service attack occurs, a deviation between the probability-based actual traffic and the predicted value occurs, so it is possible to respond by judging as aggressiveness data. In this paper, a service denial attack detection model was explained by analyzing data based on logs generated from security equipment or servers.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.3
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• pp.215-222
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• 2022

The purpose of air traffic flow management is to balance demand and capacity in the national airspace, and its performance relies on an accurate capacity prediction of the airport or airspace. This paper developed a regression model that predicts the number of aircraft actually departing and arriving in a terminal maneuvering area. The regression model is based on a boosting ensemble learning algorithm that learns past aircraft operational data such as time, weather, scheduled demand, and unfulfilled demand at a specific airport in the terminal maneuvering area. The developed model was tested using historical departure and arrival flight data at Incheon International Airport, and the coefficient of determination is greater than 0.95. Also, the capacity of the terminal maneuvering area of interest is implicitly predicted by using the model.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.285-301
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• 2023

Due to the increasing demand and importance of non-face-to-face education, open online learning platforms are getting interests both domestically and internationally. These platforms exhibit different characteristics from online courses by universities and other educational institutions. In particular, students engaged in these platforms can receive more learner autonomy, and the development of tools to assist learning is required. From the past, researchers have attempted to utilize process mining to understand realistic study behaviors and derive learning patterns. However, it has a deficiency to employ it to the open online learning platforms. Moreover, existing research has primarily focused on the process model perspective, including process model discovery, but lacks a method for the process pattern and instance perspectives. In this study, we propose a method to identify learning patterns within an open online learning platform using process mining techniques. To achieve this, we suggest three different viewpoints, e.g., model-level, variant-level, and instance-level, to comprehend the learning patterns, and various techniques are employed, such as process discovery, conformance checking, autoencoder-based clustering, and predictive approaches. To validate this method, we collected a learning log of machine learning-related courses on a domestic open education platform. The results unveiled a spaghetti-like process model that can be differentiated into a standard learning pattern and three abnormal patterns. Furthermore, as a result of deriving a pattern classification model, our model achieved a high accuracy of 0.86 when predicting the pattern of instances based on the initial 30% of the entire flow. This study contributes to systematically analyze learners' patterns using process mining.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.1
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• pp.66-73
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• 2010

The curriculum of programming education including algorithm has been recognized as a very important subject to many students majoring in natural sciences and engineering including electronic engineering and computer related departments. However, many students have had difficulties with it due to its characteristics; as a consequence, they have been in trouble taking upper-level subjects. Flow chart is a diagram that expresses logical stages necessary to solve certain problems and has been widely used to have an understanding of the flow of algorithm. The practice-oriented education of algorithm and programming would be very important to assist the understanding of operation processes. Furthermore, it has been desperately required to the necessity of auxiliary programs that could enhance an understanding of the concept of algorithm and program execution process. This study was aimed to design and embody the learning system of programming languages using basic algorithms so as for students to easily learn basic algorithm among the entire programming curriculum.