• Journal of Digital Contents Society
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• v.18 no.7
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• pp.1249-1257
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• 2017

Due to the 4th industrial revolution and an aged society, many studies are being conducted to apply virtual reality to medical field. Research on dementia is especially active. This paper proposes virtual reality based on cognitive rehabilitation contents using image recognition and clustering method to improve cognitive and physical disabilities caused by dementia. Unlike the existing cognitive rehabilitation system, this paper uses travel photos that reflect the memories of the subjects to be treated. In order to generate automated cognitive rehabilitation contents, we extract face information, food pictures, place information, and time information from photographs, and normalization is performed for clustering. And we present scenarios that can be used as cognitive rehabilitation contents using travel photos in virtual reality space.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.668-670
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• 1999

We have developed a automatic surface inspection system for cold Rolled strips in steel making process for several years. We have experienced the various kinds of surface inspection systems, including linear CCD camera type and the laser type inspection system which was installed in cold rolled strips production lines. But, we did not satisfied with these inspection systems owing to insufficient detection and classification rate, real time processing performance and limited line speed of real production lines. In order to increase detection and computing power, we have used the Dark Field illumination with Infra_Red LED, Bright Field illumination with Xenon Lamp, Parallel Computing Processor with Area typed CCD camera and full software based image processing technique for the ease up_grading and maintenance. In this paper, we introduced the automatic inspection system and real time image processing technique using the Object Detection, Defect Detection, Classification algorithms. As a result of experiment, under the situation of the high speed processed line(max 1000 meter per minute) defect detection is above 90% for all occurred defects in real line, defect name classification rate is about 80% for most frequently occurred 8 defect, and defect grade classification rate is 84% for name classified defect.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.2236-2257
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• 2020

Ransomware is malicious software that encrypts the user-related files and data and holds them to ransom. Such attacks have become one of the serious threats to cyberspace. The avoidance techniques that ransomware employs such as obfuscation and/or packing makes it difficult to analyze such programs statically. Although many ransomware detection studies have been conducted, they are limited to a small portion of the attack's characteristics. To this end, this paper proposed a framework for the behavioral-based dynamic analysis of high survivable ransomware (HSR) with integrated valuable feature sets. Term Frequency-Inverse document frequency (TF-IDF) was employed to select the most useful features from the analyzed samples. Support Vector Machine (SVM) and Artificial Neural Network (ANN) were utilized to develop and implement a machine learning-based detection model able to recognize certain behavioral traits of high survivable ransomware attacks. Experimental evaluation indicates that the proposed framework achieved an area under the ROC curve of 0.987 and a few false positive rates 0.007. The experimental results indicate that the proposed framework can detect high survivable ransomware in the early stage accurately.

• Korean Journal of Computational Design and Engineering
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• v.13 no.6
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• pp.459-468
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• 2008

A web-based Computer-Aided Engineering (CAE) supporting system is connected with a Product Data Management (PDM) system for Small and Medium Enterprises (SMEs) suffering from the lack of building hardware, software and related experts. An analysis of current business models and worksite requirements provides an improved process model and data to be shared between the PDM system and the CAE supporting system. Since all engineering tasks such as geometric modeling, mesh generation, static stress and modal analysis, and fatigue durability analysis are automated in the CAE supporting system, the user in charge of the CAE have only to configure the concerned values of design variables and result data through the web page. The existing Change Management module of the PDM system is modified for seamless data exchange, i.e. sending the Engineering Change Order (ECO) data to the CAE supporting system and receiving the CAE result data bark. The hi-directional data transfers between the PDM system and the CAE supporting system is made possible by adaptors bused on the Simple Object Access Protocol (SOAP). The current approach will be very helpful for SMEs that only have the PDM system and have no adequate infrastructure for CAE.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.8
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• pp.91-97
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• 2010

Micro-abrasive Jet Machining is one of the new technology which enables micro-scale machining on the surface of high brittle materials. In this technology it is very important to fabricate a mask that prevents excessive abrasives not to machine un-intend surface. Our previous work introduced the micro-stereolithography technology for the mask fabrication. And is good to not only planar material but also for non-planar materials. But the technology requires a 3 dimensional mask CAD model which is perfectly matched with the surface topology of parent material as an input. Therefore there is strong need to develop an automated modeling technology which produce adequate 3D mask CAD model in fast and simple way. This paper introduces a fast and simple mask modeling algorithm which represents geometry of models in voxel. Input of the modeling system is 2D pattern image, 3D CAD model of parent material and machining parameters for Micro-abrasive Jet Machining. And the output is CAD model of 3D mask which reflects machining parameters and geometry of the parent material. Finally the suggested algorithm is implemented as software and verified by some test cases.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.8
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• pp.21-29
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• 2003

This paper describes a research work on the development of computer-aided design system for deep drawing & ironing of a high pressure vessel. An approach to the system is based on the knowledge-based rules. Knowledge for the system is formulated from plasticity theories, handbook, experimental results and empirical knowledge of field experts. An attempt is made to link programs incorporating a number of expert design rules with the process variables obtained by commercial FEM software, DEFORM and ANSYS, to form a useful package. It is composed of five main modules, which are calculation of product thickness, input, production feasibility check, process planning, and autofrettage process modules and two submodules, which are folding check and process variable verification submodules. Programs for the system have been written in AutoLISP on the AutoCAD 2000 using personal computer. The developed system makes it possible to design and manufacture large high pressure vessel requiring D.D.I. process more efficiently.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.10
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• pp.168-177
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• 2001

Reverse engineering has been widely used for the shape reconstruction of an object without CAD data and the measurement of clay or wood models fur the development of new products. To generate a surface from measured points by a laser scanner, typical steps include the scanning of a clay or wood model, the generation of compatible input curves, the generation of a surface and manufacturing data like G code or STL file. A laser scanner has a great potential to get geometrical data of a model for its frost measuring speed and higher precision. The data from a laser scanner are composed of many line stripes of points including small spikes and noise. A new approach using automated surface generating algorithm is introduced to deal with problems during reverse engineering process. And the input data and the generated surface are represented in IGES format, thus can be supplied to other CAD/CAM software without any data manipulation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.8
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• pp.1989-2009
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• 2013

How to discover router vulnerabilities effectively and automatically is a critical problem to ensure network and information security. Previous research on router security is mostly about the technology of exploiting known flaws of routers. Fuzzing is a famous automated vulnerability finding technology; however, traditional Fuzzing tools are designed for testing network applications or other software. These tools are not or partly not suitable for testing routers. This paper designs a framework of discovering router protocol vulnerabilities, and proposes a mathematical model Two-stage Fuzzing Test Cases Generator(TFTCG) that improves previous methods to generate test cases. We have developed a tool called RPFuzzer based on TFTCG. RPFuzzer monitors routers by sending normal packets, keeping watch on CPU utilization and checking system logs, which can detect DoS, router reboot and so on. RPFuzzer' debugger based on modified Dynamips, which can record register values when an exception occurs. Finally, we experiment on the SNMP protocol, find 8 vulnerabilities, of which there are five unreleased vulnerabilities. The experiment has proved the effectiveness of RPFuzzer.

• Journal of Communications and Networks
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• v.13 no.6
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• pp.567-582
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• 2011

The growing popularity of the Internet has caused the size and complexity of communications and computing systems to greatly increase in recent years. To alleviate this increased management complexity, novel autonomic management architectures have emerged, in which many automated components manage the network's resources in a distributed fashion. However, in order to achieve effective collaboration between these management components, they need to be able to efficiently exchange information in a timely fashion. In this article, we propose a context dissemination framework that addresses this problem. To achieve scalability, the management components are structured in a hierarchy. The framework facilitates the aggregation and translation of information as it is propagated through the hierarchy. Additionally, by way of semantics, context is filtered based on meaning and is disseminated intelligently according to dynamically changing context requirements. This significantly reduces the exchange of superfluous context and thus further increases scalability. The large size of modern federated cloud computing infrastructures, makes the presented context dissemination framework ideally suited to improve their management efficiency and scalability. The specific context requirements for the management of a cloud data center are identified, and our context dissemination approach is applied to it. Additionally, an extensive evaluation of the framework in a large-scale cloud data center scenario was performed in order to characterize the benefits of our approach, in terms of scalability and reasoning time.

• Proceedings of the Korean Society of Computer Information Conference
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• 2012.01a
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• pp.87-90
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• 2012

본 연구는 일상생활에서 빈번히 발생되는 정지의 위급상황에 대처하기 위해 심폐소생술의 방법을 스마트폰으로 습득할 수 있게 제작하였으며, 심폐소생 자동기기가 비치되어 있는 경우, AED(자동심장제세동기, Automated External Defibrillator)를 사용하여 심폐소생할 수 있는 방법을 단계별로 제공하고 동영상으로 따라해 볼 수 있도록 제작하였다. 신체의 위급한 상황에 대한 발견 및 응급대처 후 인접한 병원에 접근하기 위한 위치정보를 바로 찾아 볼 수 있도록 메뉴를 설정하였으며, 부가적으로 화재시 일반차량들이 소방차의 길을 터주는 안내 동영상도 탑재하여 공익홍보 효과를 더하였다. 따라서 본 논문은 공익적인 특성의 국민 대상 안내, 지침을 App으로 홍보에 효과적으로 적용 가능하며, 앞으로 일반적인 상업용 기업의 메뉴얼로 확장 가능하다.