• Journal of Practical Engineering Education
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• v.14 no.2
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• pp.361-366
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• 2022

Recently, with the development of virtual and augmented reality technology, metaverse is emerging as a new paradigm that will lead the next-generation internet era, and social and economic activities are spreading around the game, entertainment, music, and content industries. Moreover, as non-face-to-face conversion accelerated after the outbreak of COVID-19, lifestyles and industrial sites are becoming untact and further rapidly becoming a metaverse. In particular, the application of metaverse to the education field is attracting attention because realistic classes using real-time voice conversations using avatars, 3D objects, and 360-degree images can increase immersion and overcome the limitations of distance education. This study examines the concept of metaverse and examines that education using metaverse can be an alternative that can increase the efficiency of education in the non-face-to-face era. In particular, it shows that it is effective in language education and suggests an actual metaverse-based Korea language education program.

• Journal of the Korean Society of Physical Medicine
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• v.18 no.2
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• pp.103-114
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• 2023

PURPOSE: This study compared the effects of computer-based and virtual reality-based cognitive rehabilitation programs on the cognitive function, upper limb function, activities of daily living, and their impact on the prefrontal cortex in convalescent stroke patients. METHODS: Ten recovering stroke patients were assessed for their cognitive function, upper limb function, and daily living activities using the Neurobehavioral Cognitive Status Examination, the Korean version of the Fugl-Meyer Assessment, and the Korean version of the Modified Barthel Index. The prefrontal cortex activity was measured with functional Near Infrared Spectroscopy. The virtual reality-based cognitive rehabilitation group utilized a program of daily living activities delivered via a laptop and Oculus Rift. The computer-based cognitive rehabilitation group performed various cognitive tasks on an all-in-one PC. Both groups underwent cognitive rehabilitation training for 30 minutes per day, three times a week, for six weeks, with identical conventional rehabilitation therapies in the hospital. RESULTS: Both programs positively impacted the cognitive and physical functions. On the other hand, the virtual reality-based cognitive rehabilitation program had a larger influence on improving the cognitive and physical functions of convalescing stroke patients. CONCLUSION: The virtual reality program suggests its potential to enhance cognitive and physical functions in convalescent stroke patients through increased engagement, focus, real-time feedback, and game elements, making it a promising rehabilitation approach.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.113-120
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• 2023

Smart farms are steadily increasing in research to minimize labor, energy, and quantity put into crops as IoT technology and artificial intelligence technology are combined. However, research on efficiently managing crop growth information in smart farms has been insufficient to date. In this paper, we propose a management technique that can efficiently monitor crop growth information by applying autonomous sensors to smart farms. The proposed technique focuses on collecting crop growth information through autonomous sensors and then recycling the growth information to crop cultivation. In particular, the proposed technique allocates crop growth information to one slot and then weights each crop to perform load balancing, minimizing interference between crop growth information. In addition, when processing crop growth information in four stages (sensing detection stage, sensing transmission stage, application processing stage, data management stage, etc.), the proposed technique computerizes important crop management points in real time, so an immediate warning system works outside of the management criteria. As a result of the performance evaluation, the accuracy of the autonomous sensor was improved by 22.9% on average compared to the existing technique, and the efficiency was improved by 16.4% on average compared to the existing technique.

• Journal of Korea Entertainment Industry Association
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• v.13 no.4
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• pp.71-82
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• 2019

Today's media environment is becoming very complicated and the trend of media convergence is getting clearer. The convergence of media is the supreme hot issue. In this wave of convergence, there has also been a huge change between movies and electronic games. The remake boom between them showed a tremendous economic effect that can be achieved by exchanging two media of essentially different characteristics. As computer virtual reality technologies evolve, electronic games will provide a virtual world that can satisfy the demands of the visual, auditory, and tactile aspects very real to the public with the Internet. At that time, movies and other media will be thoroughly melted into the virtual world created by electronic games, and they will become an element of the virtual world as those media that exist in the truth world.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.279-282
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• 2017

Kinect depth sensor, a depth camera developed by Microsoft as a natural user interface for game appeared as a very useful tool in computer vision field. In this paper, due to kinect's depth sensor and its high frame rate, we developed a distance measurement system using Kinect camera to test it for unmanned vehicles which need vision systems to perceive the surrounding environment like human do in order to detect objects in their path. Therefore, kinect depth sensor is used to detect objects in its field of view and enhance the distance measurement system from objects to the vision sensor. Detected object is identified in accuracy way to determine if it is a real object or a pixel nose to reduce the processing time by ignoring pixels which are not a part of a real object. Using depth segmentation techniques along with Open CV library for image processing, we can identify present objects within Kinect camera's field of view and measure the distance from them to the sensor. Tests show promising results that this system can be used as well for autonomous vehicles equipped with low-cost range sensor, Kinect camera, for further processing depending on the application type when they reach a certain distance far from detected objects.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.187-201
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• 2011

KOSPI200 index is the Korean stock price index consisting of actively traded 200 stocks in the Korean stock market. Its base value of 100 was set on January 3, 1990. The Korea Exchange (KRX) developed derivatives markets on the KOSPI200 index. KOSPI200 index futures market, introduced in 1996, has become one of the most actively traded indexes markets in the world. Traders can make profit by entering a long position on the KOSPI200 index futures contract if the KOSPI200 index will rise in the future. Likewise, they can make profit by entering a short position if the KOSPI200 index will decline in the future. Basically, KOSPI200 index futures trading is a short-term zero-sum game and therefore most futures traders are using technical indicators. Advanced traders make stable profits by using system trading technique, also known as algorithm trading. Algorithm trading uses computer programs for receiving real-time stock market data, analyzing stock price movements with various technical indicators and automatically entering trading orders such as timing, price or quantity of the order without any human intervention. Recent studies have shown the usefulness of artificial intelligent systems in forecasting stock prices or investment risk. KOSPI200 index data is numerical time-series data which is a sequence of data points measured at successive uniform time intervals such as minute, day, week or month. KOSPI200 index futures traders use technical analysis to find out some patterns on the time-series chart. Although there are many technical indicators, their results indicate the market states among bull, bear and flat. Most strategies based on technical analysis are divided into trend following strategy and non-trend following strategy. Both strategies decide the market states based on the patterns of the KOSPI200 index time-series data. This goes well with Markov model (MM). Everybody knows that the next price is upper or lower than the last price or similar to the last price, and knows that the next price is influenced by the last price. However, nobody knows the exact status of the next price whether it goes up or down or flat. So, hidden Markov model (HMM) is better fitted than MM. HMM is divided into discrete HMM (DHMM) and continuous HMM (CHMM). The only difference between DHMM and CHMM is in their representation of state probabilities. DHMM uses discrete probability density function and CHMM uses continuous probability density function such as Gaussian Mixture Model. KOSPI200 index values are real number and these follow a continuous probability density function, so CHMM is proper than DHMM for the KOSPI200 index. In this paper, we present an artificial intelligent trading system based on CHMM for the KOSPI200 index futures system traders. Traders have experienced on technical trading for the KOSPI200 index futures market ever since the introduction of the KOSPI200 index futures market. They have applied many strategies to make profit in trading the KOSPI200 index futures. Some strategies are based on technical indicators such as moving averages or stochastics, and others are based on candlestick patterns such as three outside up, three outside down, harami or doji star. We show a trading system of moving average cross strategy based on CHMM, and we compare it to a traditional algorithmic trading system. We set the parameter values of moving averages at common values used by market practitioners. Empirical results are presented to compare the simulation performance with the traditional algorithmic trading system using long-term daily KOSPI200 index data of more than 20 years. Our suggested trading system shows higher trading performance than naive system trading.

• Korean Journal of Construction Engineering and Management
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• v.23 no.4
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• pp.3-14
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• 2022

Autonomous equipment requires a large amount of data from various environments. However, it takes a lot of time and cost for an experiment in a real construction sites, which are difficulties in data collection and processing. Therefore, this study aims to develop a virtual environment for autonomous tower cranes technology development and validation. The authors defined automation functions and operation conditions of tower cranes with three performance criteria: operational design domain, object and event detection and response, and minimum functional conditions. Afterward, this study developed a virtual environment for learning and validation for autonomous functions such as recognition, decision making, and control using the Unity game engine. Validation was conducted by construction industry experts with a fidelity which is the representative matrix for virtual environment assessment. Through the virtual environment platform developed in this study, it will be possible to reduce the cost and time for data collection and technology development. Also, it is also expected to contribute to autonomous driving for not only tower cranes but also other construction equipment.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.1
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• pp.56-63
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• 2007

In this paper, an eye tracking method is presented using a neural network (NN) and mean-shift algorithm that can accurately detect and track user's eyes under the cluttered background. In the proposed method, to deal with the rigid head motion, the facial region is first obtained using skin-color model and con-nected-component analysis. Thereafter the eye regions are localized using neural network (NN)-based tex-ture classifier that discriminates the facial region into eye class and non-eye class, which enables our method to accurately detect users' eyes even if they put on glasses. Once the eye region is localized, they are continuously and correctly tracking by mean-shift algorithm. To assess the validity of the proposed method, it is applied to the interface system using eye movement and is tested with a group of 25 users through playing a 'aligns games.' The results show that the system process more than 30 frames/sec on PC for the $320{\times}240$ size input image and supply a user-friendly and convenient access to a computer in real-time operation.

• The KIPS Transactions:PartC
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• v.12C no.6 s.102
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• pp.881-890
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• 2005

Over for the past 10 years, the increase in geometric progression for the internet traffic, has allowed the IP protocol framework to be the most important network technology. In addition, the internet service is being developed as a service mode differentiated, aiming to support the new-mode real-time multimedia services such as internet phone, video conference, cyber reality, and internet game, focusing on offering a latest service. These days, aiming to solve the need for broad bandwidth along with guaranteeing QoS, the WDM technology of offering multiple gigabit wavelengths is emerging as the core technology of next-generation optical internet backbone network. In the next-generation optical internet backbone network based on WDM, the QoS framework is one of fore subjects aiming to offer a service of guaranteeing QoS This study analyzes the requirements of performance related to QoS framework in IP Subnet and in WDM optical backbone network, and suggests optical QoS service framework differentiated. in order to guarantee end-to-end QoS through the next-generation optical internet backbone network, using GMPLS control protocol.

• Journal of Internet Computing and Services
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• v.12 no.5
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• pp.171-179
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• 2011

In this paper it is hypothesized that word stimuli that are presented by Google’s search word, would improve the quality of the design solution, so this research examines the effect of related search word stimuli in concept generation and analyzes the results through the processes of creative cognition. In the process of concept generation, words are given as stimuli which are generated through Google's related search and these search words are given by 5 levels. Google search is based on the collaboration philosophy. People's participation and contribution recreate knowledge and information, so these renewed and related search words update in real time by people are used as stimuli. Two problems are provided with related search words. After the design concept generation the results are analyzed by 3 bases: the usage of related search words and those of frequency, creativity, and Finke's 12 Geneplore model. These are the results of the research. Many levels of related search words are used in design concept generation but especially higher levels which are more related to search words are more used than lower levels. The usage of multi words and conjunction with higher levels and lower levels words are observed in creative results. On the creative cognitive processes, it is more creative when using association and mental transformation with the related search words than using the related search words simply. Creative outputs also use conceptual interpretation, functional inference, and contextual shifting of creative cognitive processes of Finke's 12 Geneplore model.