• Journal of Digital Contents Society
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• v.18 no.6
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• pp.1175-1182
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• 2017

Recent trend in the manufacturing industry is focused on the convergence with IoT and Big Data, by emergence of the 4th Industrial Revolution. To realize a smart factory, the proposed system based on MTConnect technology collects and integrates various status information of machines from many production facilities including heterogeneous devices. Also it can distribute the acquisited status of heterogeneous manufacturing machines to the remote devices. As a key technology of a flexible automated production line, the proposed system can provide much possibility to manage important information such as error detection and processing state management in the unmanned automation line.

• Journal of the Korea Society of Computer and Information
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• v.20 no.3
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• pp.47-56
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• 2015

Automated detection of interesting web pages could be used in many different application domains. Determining a user's interesting web pages can be performed implicitly by observing the user's behavior. The task of distinguishing interesting web pages belongs to a classification problem, and we choose white box learning methods (fixed effect logit regression and support vector machine) to test empirically. The result indicated that (1) fixed effect logit regression, fixed effect SVMs with both polynomial and radial basis kernels showed higher performance than the linear kernel model, (2) a personalization is a critical issue for improving the performance of a model, (3) when asking a user explicit grading of web pages, the scale could be as simple as yes/no answer, (4) every second the duration in a web page increases, the ratio of the probability to be interesting increased 1.004 times, but the number of scrollbar clicks (p=0.56) and the number of mouse clicks (p=0.36) did not have statistically significant relations with the interest.

• Journal of Korea Game Society
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• v.16 no.2
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• pp.51-60
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• 2016

The incidents of massive personal information being leaked are occurring continuously over recent years. Personal information leaked outside is used for an illegal use of other's name and account theft. Especially it is happening on online games whose virtual goods, online game money and game items can be exchanged with real cash. When we research the real identity theft cases that happened in an online game, we can see that they happen massively in a short time. In this study, we define the characteristics of the mass attacks of the automated identity theft cases that occur in online games. Also we suggest a system to detect and prevent identity theft attacks in real time.

• Bioinformatics and Biosystems
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• v.1 no.1
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• pp.28-37
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• 2006

Recent studies in molecular biology and proteomics have identified a significant number of novel diagnostic, prognostic, and therapeutic disease markers. However, validation of these markers in clinical specimens with traditional histopathological techniques involves low throughput and is time consuming and labor intensive. Tissue microarrays (TMAs) offer a means of combining tens to hundreds of specimens of tissue onto a single slide for simultaneous analysis. This capability is particularly pertinent in the field of cancer for target verification of data obtained from cDNA micro arrays and protein expression profiling of tissues, as well as in epidemiology-based investigations using histochemical/immunohistochemical staining or in situ hybridization. In combination with automated image analysis, TMA technology can be used in the global cellular network analysis of tissues. In particular, this potential has generated much excitement in cardiovascular disease research. The following review discusses recent advances in the construction and application of TMAs and the opportunity for developing novel, highly sensitive diagnostic tools for the early detection of cardiovascular disease.

• Journal of the Korean Society of Tobacco Science
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• v.30 no.2
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• pp.117-124
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• 2008

A solid phase microextraction (SPME) method in combination with gas chromatography/mass spectrometric techniques was used for the extraction and quantification of 12 selected agrochemical residues in tobacco. The parameters such as the type of SPME fiber, adsorption/desorption time and the extraction temperature affecting the precision and accuracy of the SPME method were investigated and optimized. Among three types of fibers investigated, polyacrylate (PA), polydimethylsiloxane (PDMS) and polydimethylsiloxane-divinylbenzene (PDMS-DVB), PDMS fiber was selected for the extractions of the agrochemicals. The SPME device was automated and on-line coupled to a gas chromatograph with a mass spectrometer. Mass spectrometry (MS) was used and two different instruments, a quadrupole MS and triple quadrupole MS-MS mode, were compared. The performances of the two GC-MS instruments were comparable in terms of linearity (in the range of 0.01$\sim$0.5 $\mu$g/mL) and sensitivity (limits of detection were in the low ng/mL range). The triple quadrupole MS-MS instrument gave better precision than that of quadrupole MS system, but generally the relative standard deviations for replicates were acceptable for both instruments (< 15%). The LODs was fully satisfied the requirements of the CORESTA GRL. Recoveries of 12 selected agrochemicals in tobacco yielded more than 80% and reproducibility was found to be better than 10% RSD so that SPME procedure could be applied to the quantitative analysis of agrochemical residues in tobacco.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.3
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• pp.323-328
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• 2014

Recently, there has been demand for the convergence of IT (Information and communication Technologies, ICT) with defense, as has already been achieved in civilian fields such as healthcare and construction. It is expected that completely new and common requirements would emerge from the civilian and military domains and that the shape of war field would change rapidly. Many military scientists forecast that future wars would be network-centric and be based on C4I(Command, Control, Communication & Computer, Intelligence), ISR(Intelligence, Surveillance & Reconnaissance), and PGM(Precision Guided Munitions). For realizing the smart defense concept, IT should act as a baseline technology even for simulating a real combat field using virtual reality. In this paper, we propose the concept of IT-based smart defense with a focus on accurate detection in real and cyber wars, effective data communication, automated and unmanned operation, and modeling and simulation.

• Journal of KIISE:Software and Applications
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• v.35 no.9
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• pp.538-546
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• 2008

It has limits that system administrator deals with many problems occurred in systems because computing environments are increasingly complex. It is issued that systems have an ability to recognize system's situations and adapt them by itself in order to resolve these limits. But it requires much experiences and knowledge to build the Self-Adaptive System. The difficulty that builds the Self-Adaptive System has been problems. This paper proposes a technique that generates automatically the codes of the Self-Adaptive System in order to make the system to be built more easily. This Self-Adaptive System resolves partially the problems about ineffectiveness of the exceeded usage of the system resource that was previous research's problem and incorrect operation that is occurred by external factors such as virus. In this paper, we applied the proposed approach to the file transfer module that is in the video conferencing system in order to evaluate it. We compared the length of the codes, the number of Classes that are created by the developers, and development time. We have confirmed this approach to have the effectiveness.

• Journal of Korea Multimedia Society
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• v.20 no.12
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• pp.1960-1969
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• 2017

There have been ongoing researches to identify and analyze the patterns of electric power IoT data inside sensor nodes to supplement the stable supply of power and the efficiency of energy consumption. This study set out to propose an analysis process for electric power IoT data with the K-means algorithm, which is an unsupervised learning technique rather than a supervised one. There are a couple of problems with the old K-means algorithm, and one of them is the selection of cluster number K in a heuristic or random method. That approach is proper for the age of standardized data. The investigator proposed an analysis process of selecting an automated cluster number K through principal component analysis and the space division of normal distribution and incorporated it into electric power IoT data. The performance evaluation results show that it recorded a higher level of performance than the old algorithm in the cluster classification and analysis of pitches and rolls included in the communication bodies of utility poles.

• Proceedings of the KSRS Conference
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• v.1
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• pp.500-503
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• 2006

To adjust the discrepancy between Light Detection and Ranging (LIDAR) strips, previous researches generally have been conducted using conjugate features, which are called feature-based approaches. However, irrespective of the type of features used, the adjustment process relies upon the existence of suitable conjugate features within the overlapping area and the ability of employed methods to detect and extract the features. These limitations make the process complex and sometimes limit the applicability of developed methodologies because of a lack of suitable features in overlapping areas. To address these drawbacks, this paper presents a methodology using area-based algorithms. This approach is based on the scheme that discrepancies make complex the local height variations of LIDAR data whithin overlapping area. This scheme can be helpful to determine an appropriate transformation for adjustment in the way that minimizes the geographical complexity. During the process, the contour tree (CT) was used to represent the geological characteristics of LIDAR points in overlapping area and the Iterative Closest Points (ICP) algorithm was applied to automatically determine parameters of transformation. After transformation, discrepancies were measured again and the results were evaluated statistically. This research provides a robust methodology without restrictions involved in methods that employ conjugate features. Our method also makes the overall adjustment process generally applicable and automated.

• Journal of the Korean Vacuum Society
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• v.15 no.5
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• pp.506-511
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• 2006

ZnO nanorods were prepared by the hydrothermal reaction of a solution containing $Zn(NO_3)_2{\cdot}6H_2O$, NaOH, cyclohexylamine, ethanol and water, and their $NO_2$ and CO sensing behaviors were investigated. By the control of water concentration in solution, the morphology and agglomeration of ZnO nanorods could be manipulated, which is associated with the variation of $[OH^-]$ resulted from an interaction between water and cyclohexylamine. Sea-urchin-like and well-dispersed ZnO nanorods were prepared at low and high water content, respectively. Well-dispersed ZnO nanorods showed 1.8 fold change in resistance at 1 ppm $NO_2$ while there was no significant change in resistance at 50 ppm CO. This selective detection of $NO_2$ in the presence of CO can be used in automated car ventilation systems.