• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.4
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• pp.811-817
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• 2009

The rapid growth of network based IT systems has resulted in continuous research of security issues. Probe intrusion detection is an area of increasing concerns in the internet community. Recently, a number of probe intrusion detection schemes have been proposed based on various technologies. However, the techniques, which have been applied in many systems, are useful only for the existing patterns of probe intrusion. They can not detect new patterns of probe intrusion. Therefore, it is necessary to develop a new Probe Intrusion Detection technology that can find new patterns of probe intrusion. In this paper, we proposed a new network based probe intrusion detector(NePID) using anomaly traffic analysis and fuzzy cognitive maps that can detect intrusion by the denial of services attack detection method utilizing the packet analyses. The probe intrusion detection using fuzzy cognitive maps capture and analyze the packet information to detect syn flooding attack. Using the result of the analysis of decision module, which adopts the fuzzy cognitive maps, the decision module measures the degree of risk of denial of service attack and trains the response module to deal with attacks. For the performance evaluation, the "IDS Evaluation Data Set" created by MIT was used. From the simulation we obtained the max-average true positive rate of 97.094% and the max-average false negative rate of 2.936%. The true positive error rate of the NePID is similar to that of Bernhard's true positive error rate.

• Journal of the Korean Society of Radiology
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• v.82 no.5
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• pp.1186-1195
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• 2021

Purpose In the adult emergency department of a university hospital, we investigated the frequency of major discrepancies between the preliminary reports by radiology residents and the final reports by certified radiologists. Materials and Methods Based on CT and MRI scans obtained between December 2016 and November 2019, we selected cases with diagnoses or treatment plans that could be changed due to discrepancies between preliminary and final reports and classified them by the type of discrepancy. We also examined the distributions of the major discrepancies and stratified them by residents' working time zone, experience, and subspecialty. Results Based on the 72137 preliminary reports evaluated, 1348 tests (1.9%) showed major discrepancies. Most of the major discrepancies were false negatives (72.0%), followed by misdiagnosis (26.3%) and false positives (1.7%). Acute findings (87.2%) were more common than non-acute findings (12.8%). The major discrepancy rate increased toward the second half of the 24-hour shift, with the highest rate of 2.9% occurring between 2 am and 4 am. The major discrepancy rate did not vary with experience, and it varied from 0.6% to 4.5% for each subspecialty. Conclusion The major discrepancy rate was less than 2%, and it increased with longer working hours during a 24-hour shift.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.4 s.310
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• pp.88-102
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• 2006

In multimedia information retrieval, multimedia data are represented as vectors in high dimensional space. To search these vectors effectively, a variety of indexing methods have been proposed. However, the performance of these indexing methods degrades dramatically with increasing dimensionality, which is known as the dimensionality curse. To resolve the dimensionality curse, dimensionality reduction methods have been proposed. They map feature vectors in high dimensional space into the ones in low dimensional space before indexing the data. This paper proposes a method for dimensionality reduction based on a function approximating the Euclidean distance, which makes use of the norm and angle components of a vector. First, we identify the causes of the errors in angle estimation for approximating the Euclidean distance, and discuss basic directions to reduce those errors. Then, we propose a novel method for dimensionality reduction that composes a set of subvectors from a feature vector and maintains only the norm and the estimated angle for every subvector. The selection of a good reference vector is important for accurate estimation of the angle component. We present criteria for being a good reference vector, and propose a method that chooses a good reference vector by using Levenberg-Marquardt algorithm. Also, we define a novel distance function, and formally prove that the distance function lower-bounds the Euclidean distance. This implies that our approach does not incur any false dismissals in reducing the dimensionality effectively. Finally, we verify the superiority of the proposed method via performance evaluation with extensive experiments.

• The Mathematical Education
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• v.43 no.4
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• pp.419-440
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• 2004

The purpose of this paper is to know the effects on number and operation abilities of the 1st grade children of elementary school by applying teaching and learning activity throught communication. For this purpose, we have studied according to the following procedure. 1. We divised teaching and learning model through communication and applied in the actual teaching and learning activity. 2. We investigated the effects of number and operations abilities of the 1st grade children by applying teaching and learning activity through communication. To accomplish this purpose, we applied learning activity through communication to the 1st grade of 40 elementary school children for about six months(September 1, 1999 ～ February 20, 2000). In process of applying this model, we collected all sorts of cases in the children's learning activity and investigated children's response on learning activity through communication, interview with children and researcher's observation. We applied the model through communication in class and compared with the traditional learning. 1. In learning through communication, children could solve the problem in themselves with a sense of responsibility. 2. It was impossible to find out the degree of children's comprehension in the explanatory learning. But in the learning through communication, it was a great help to individualize and plan the learning because children express their ideas clearly. It has conclusion as follows. The learning activity through communication has effected on forming number and operations abilities of the 1st grade of elementary school children importantly. 1. Children have improved in the abilities through communication to express their own ideas. 2. Children have studied with a sense of responsibility not in the teacher-oriented learning but in the self-directed learning 3. Children could find out the mathematical concepts in themselves - correcting false concepts, reguiding concepts by errors, finding invisible errors, solving problems variously and knowing the easy method. 4. The activity through communication in mathematics was a base of children's individual learning and important data of next learning plan. 5. The mathematical concepts formed through communication had a high transfer of learning. 6. Children have taken pleasure of discovery and had affirmative attitude about mathematics learning. We can make sure that number and operations abilities of the 1st grade children are formed by applying teaching and learning activity through communication. However, help and control of teacher have to be with it.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.3
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• pp.112-118
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• 2009

Skin color segmentation techniques have been widely utilized for face/hand detection and tracking in many applications such as a diagnosis system using facial information, human-robot interaction, an image retrieval system. In case of a video image, it is common that the skin color model for a target is updated every frame for the robust target tracking against illumination change. As for a single image, however, most of studies employ a fixed skin color model which may result in low detection rate or high false positive errors. In this paper, we propose a novel method for effective skin color segmentation in a single image, which modifies the conditions for skin color segmentation iteratively by the image feedback of segmented skin color region in a given image.

• Proceedings of the Korean Vacuum Society Conference
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• 2016.02a
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• pp.378.2-378.2
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• 2016

Biosensors currently suffer from severe non-specific adsorption of proteins, which causes false positive errors in detection through overestimation of the affinity value. Overcoming this technical issue motivates our research. Polyethylene glycol (PEG) is well known for its ability to reduce the adsorption of biomolecules; hence, it is widely used in various areas of medicine and other biological fields. Likewise, amine functionalized surfaces are widely used for biochemical analysis, drug delivery, medical diagnostics and high throughput screening such as biochips. As a result, many coating techniques have been introduced, one of which is plasma polymerization - a powerful coating method due to its uniformity, homogeneity, mechanical and chemical stability, and excellent adhesion to any substrate. In our previous works, we successfully fabricated plasmapolymerized PEG (PP-PEG) films [1] and amine functionalized films [2] using the plasma enhanced chemical vapor deposition (PECVD) technique. In this research, an amine functionalized PP-PEG film was fabricated by using the plasma co-polymerization technique with PEG 200 and ethylenediamine (EDA) as co-precursors. A biocompatible amine functionalized film was surface characterized by X-ray photoelectron spectroscopy (XPS) and Fourier-transform infrared spectroscopy (FT-IR). The density of the surface amine functional groups was carried out by quantitative analysis using UV-visible spectroscopy. We found through surface plasmon resonance (SPR) analysis that non-specific protein adsorption was drastically reduced on amine functionalized PP-PEG films. Our functionalized PP-PEG films show considerable potential for biotechnological applications such as biosensors.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.6
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• pp.2452-2457
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• 2012

When a quality inspection process rejects a product unit, consecutive repeated inspections are sometimes conducted for the rejected unit to reduce a false reject possibility. This paper analyzes a special inspection process that allows up to two times of consecutive testing for each product to decrease type I inspection errors. This study uses a Markov chain to model the steps of the inspection process and a product unit's quality states during inspection. Historical inspection results from a company are used as the data for the Markov chain model. Using the Markov chain model and data, this study analyzes the effect of this special inspection rule on the proportion of the final quality levels and scrap rate. The results demonstrate that this inspection process of possible double testing could help reduce unnecessary rejects and consequently decrease material and production costs.

• Journal of Korea Multimedia Society
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• v.10 no.7
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• pp.923-933
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• 2007

In this paper, we present a method for performance enhancement of the marker detection system by using SVM(Support Vector Machine) and LDA(Linear Discriminant Analysis). It converts the input image to a binary image and extracts contours of objects in the binary image. After that, it approximates the contours to a list of line segments. It finds quadrangle by using geometrical features which are extracted from the approximated line segments. It normalizes the shape of extracted quadrangle into exact squares by using the warping technique and scale transformation. It extracts feature vectors from the square image by using principal component analysis. It then checks if the square image is a marker image or a non-marker image by using a SVM classifier. After that, it computes feature vectors by using LDA for the extracted marker images. And it calculates the distance between feature vector of input marker image and those of standard markers. Finally, it recognizes the marker by using minimum distance method. Experimental results show that the proposed method achieves enhancement of recognition rate with smaller feature vectors by using LDA and it can decrease false detection errors by using SVM.

• Proceedings of the KSRS Conference
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• v.1
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• pp.471-474
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• 2006

Several planktonic dinoflagellates, including Cochlodinium polykrikoides (p), are known to produce red tides responsible for massive fish kills and serious economic loss in turbid Northwest Pacific (Korean and neighboring) coastal waters during summer and fall seasons. In order to mitigate the impacts of these red tides, it is therefore very essential to detect, monitor and forecast their development and movement using currently available remote sensing technology because traditional ship-based field sampling and analysis are very limited in both space and temporal frequency. Satellite ocean color sensors, such as Sea-viewing Wide Field-of-view Sensor (SeaWiFS), are ideal instruments for detecting and monitoring these blooms because they provide relatively high frequency synoptic information over large areas. Thus, the present study attempts to evaluate the red tide index methods (previously developed by Ahn and Shanmugam et al., 2006) to identify potential areas of red tides from SeaWiFS imagery in Korean and neighboring waters. Findings revealed that the standard spectral ratio algorithms (OC4 and LCA) applied to SeaWiFS imagery yielded large errors in Chl retrievals for coastal areas, besides providing false information about the encountered red tides in the focused waters. On the contrary, the RI coupled with the standard spectral ratios yielded comprehensive information about various ranges of algal blooms, while RCA Chl showing a good agreement with in-situ data led to enhanced understanding of the spatial and temporal variability of the recent red tide occurrences in high scattering and absorbing waters off the Korean and Chinese coasts. The results suggest that the red tide index methods for the early detection of red tides blooms can provide state managers with accurate identification of the extent and location of blooms as a management tool.

• Journal of Korean Society on Water Environment
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• v.30 no.6
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• pp.585-595
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• 2014

The temporal trends of the prioritized toxic water pollutants generated and discharged from the industrial facilities in the Geum-River basin, Korea were analyzed with the results of the nationwide Water Pollution Source Survey conducted in 2001 - 2012. The statistical results indicated rapid increase in the volume of raw toxic wastewaters whereas the amount of each toxic pollutant kept fluctuating for 12 years. Serious discrepancies in the survey data of the same type of industries demonstrated a low reliability of the survey result, which stemmed from several error factors. A unit-load for each type of industrial facility was devised to estimate the amount of prioritized toxic water pollutant based on the total volume of industrial wastewater generated from the same type of industrial facilities. The supplementary measures with an effective permit issuance policy and adding survey parameters of terminal wastewater treatment plants to use them as references to the Water Pollution Source Survey were suggested as means to minimize the errors associated with the false reports from the industries.