• Journal of the Korea Computer Graphics Society
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• v.3 no.2
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• pp.15-25
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• 1997

In this paper, we describe the construction process of a large-scale virtual environment and navigation through it. We discuss on the problems found, future directions for improvements, and related research issues. KAIST campus was chosen as a target environment and was constructed as an integrated virtual world by modeling and configurating its terrain, buildings, and other objects. Constructing a large-scale virtual world itself is an important research issue. Moreover, it can be used not only in numerous applications such as campus information system, remote education, digital library, and internet application system but also as a testbed for the realtime computer graphics.

• Journal of Digital Convergence
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• v.11 no.2
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• pp.257-262
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• 2013

In mobile market which has been developed drastically, short distance mobile Near Field Communication is becoming the conversation topic. Google adopted this NFC technology to Android 플랫폼 for securing the leadership and many another countries including domestic companies are putting spurs to develop service and technology by connecting mobile carrier and the financial. Within this circumstance, most noticeable issue is securing stability of nfc application service. Android 플랫폼 is operating system of mobile device and also a software stack which is required limited hardware and immediate response. However, since its structural characteristic which is suitable for limited hardware, the response is not quite stable for real time process. That is, this paper researches by analyzing real time response of NFC related library provided from Android 플랫폼 and applying the result to NFC application for securing stable data process and response.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.3
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• pp.159-166
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• 2018

This paper introduces a manufacturing facility visualization system for the monitoring of smart factories. With the development of technology and the emergence of such terms as the Fourth Industrial Revolution and Industry 4.0, technologies for smart factories are becoming more important. A Manufacturing Execution System that can improve productivity and help decision making by monitoring production plants in real-time is one of the key technologies for smart factories. The application of digital twin technology for more accurate monitoring technology is also an important issue. However, digital twin implementations require an integrated infrastructure that can integrate facility data from multiple manufacturers. Therefore, this paper designs and develops a visualization program that can verify real-time information of facilities using data collection system based on international standard protocol for heterogeneous collection and monitoring of facility data. This allows a factory to consolidate equipment data from multiple manufacturers and to view them in real-time.

• Journal of Convergence for Information Technology
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• v.8 no.1
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• pp.201-206
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• 2018

Recently, as technologies for realizing artificial intelligence have become more common, machine learning is widely used. Machine learning provides insight into collecting large amounts of data, batch processing, and taking final action, but the effects of the work are not immediately integrated into the learning process. In this paper proposed an adaptive learning model to improve the performance of real-time stream analysis as a big business issue. Adaptive learning generates the ensemble by adapting to the complexity of the data set, and the algorithm uses the data needed to determine the optimal data point to sample. In an experiment for six standard data sets, the adaptive learning model outperformed the simple machine learning model for classification at the learning time and accuracy. In particular, the support vector machine showed excellent performance at the end of all ensembles. Adaptive learning is expected to be applicable to a wide range of problems that need to be adaptively updated in the inference of changes in various parameters over time.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.3
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• pp.135-142
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• 2017

DDoS (Distributed Denial of Service) exhausts the target server's resources using the large number of zombie pc, As a result normal users don't access to server. DDoS Attacks steadly increase by many attacker, and almost target of the attack is critical system such as IT Service Provider, Government Agency, Financial Institution. In this paper, We will introduce the CNN (Convolutional Neural Network) of deep learning based real-time detection system for DNS amplification Attack (DNS DDoS Attack). We use the dataset which is mixed with collected data in the real environment in order to overcome existing research limits that use only the data collected in the experiment environment. Also, we build a deep learning model based on Convolutional Neural Network (CNN) that is used in pattern recognition.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.1-9
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• 2018

In the fourth industrial revolution, which has become an issue now, we have been able to receive instant analysis results faster than the existing slow speed through various Big Data technologies, and to conduct real-time monitoring on mobile and web. First, various irregular sensor Data is generated using IoT device, Raspberry Pi. Sensor Data is collected in real time, and the collected data is distributed and stored using several nodes. Then, the stored Sensor Data is processed and refined. Visualize and output the analysis result after analysis. By using these methods, we can train the human resources required for Big Data and mobile related fields using IoT, and process data efficiently and quickly. We also provide information that can confirm the reliability of research results through real time monitoring.

• Tunnel and Underground Space
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• v.32 no.6
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• pp.478-490
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• 2022

TBM disc cutter, which is the main cutting tool of tunnel boring machine (TBM), is replaced when it is excessively worn during the boring process. Disc cutters are usually monitored by workers at cutterhead chamber, and they check the status and wear amount of cutters. Because cutterhead chamber is usually in dangerous circumstance due to high pressure and instability of excavation surface, the measurement by manpower occasionally results in inaccuracy of measurement result. In order to overcome the limitations, the real-time disc cutter monitoring techniques have been developed in some foreign countries. This paper collected the current status of disc cutter monitoring system from the literature. Several types of sensors are used to measure the cutter wear, and it is believed that the collected information can be useful reference when similar domestic technologies are developed in the future.

• Daejeon Development Forum
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• s.22
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• pp.97-103
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• 2007

민선지방자치제가 실시된 지 10년이 지난 지금 지방자치단체간 소모적인 경쟁보다는 생산적인 협력이 중요하다는 분위기가 고조되고 있으며, 행정구역 경계를 넘어선 지역개발 협력 모델이 구체적으로 논의되고 있다. 특히 도시가 점차 확장되면서 그 주변지역을 망라함에 따라 연담도시권은 생활권 경제권역을 공유하게 되어 각종 행정사무에 대한 상호 협력의 필요성이 증대되고 있으며, 교통, 공공시설, 수질, 대기 등의 문제들이 중요한 이슈로 부각되고 종종 지역간 갈등의 주원인으로 나타남에 따라 이러한 사안들을 협의할 수 있는 지역단체간 협력기구에 대한 중요성이 대두되고 있다. 금번 해외정책연수기간 중 방문한 SCAG(Southern California Association of Government) 와 ABAG(Association of Bay Area Governments) 는 미국의 광역도시계획기구 (Metropolitan Planning Organization: MPO) 중 하나로, 광역행정의 추진 및 정부간 갈등 조정, 협력 촉진의 역할을 수행하고 있어, 작금 우리의 행정현실에 대해서도 시사하는 바가 크다 하겠다.

• Journal of the Korea Society for Simulation
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• v.23 no.4
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• pp.181-188
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• 2014

Heterogeneous physical systems and computational devices are incorporated on a large-scale in a CPS (cyber-physical system) environment. Simulations can be useful for the reliable behaviors of CPSs. Time synchronization is one of major technical issues for the simulations. In the CPS, distributed systems control themselves by interacting with each other during runtime. When some simulation models have high complexity, wrong control commands as well as incorrect data can be exchanged due to the time error. We propose a time synchronization algorithm for the hybrid model that has characteristics of both continuous time systems and discrete event systems. In addition, we develop a CPS simulator based on our algorithm. For the verification of the algorithm and the execution of the simulator, we develop an example hybrid model and simulate considering user controls as well as interactions among the distributed systems.

• Journal of Internet Computing and Services
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• v.10 no.4
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• pp.55-70
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• 2009

Vision-based Human computer interaction is an emerging field of science and industry to provide natural way to communicate with human and computer. In that sense, inferring the emotional state of the person based on the facial expression recognition is an important issue. In this paper, we present a novel approach to recognize facial expression from a sequence of input images using emotional specific HMM (Hidden Markov Model) and facial motion tracking based on optical flow. Conventionally, in the HMM which consists of basic emotional states, it is considered natural that transitions between emotions are imposed to pass through neutral state. However, in this work we propose an enhanced transition framework model which consists of transitions between each emotional state without passing through neutral state in addition to a traditional transition model. For the localization of facial features from video sequence we exploit template matching and optical flow. The facial feature displacements traced by the optical flow are used for input parameters to HMM for facial expression recognition. From the experiment, we can prove that the proposed framework can effectively recognize the facial expression in real time.