• Childhood Kidney Diseases
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• v.13 no.1
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• pp.26-32
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• 2009

Purpose : The increasing use of ultrasonography has allowed for an increase in the of the detection of congenital hydronephrosis, and the clinical outcomes of congenital hydronephrosis are widely varied. In this study, the necessity of voiding cystourethrography in neonate with hydronephrosis to rule out vesicoureteral reflux (VUR) was evaluated. Methods : Between January 2004 and December 2007, we reviewed the medical record of 157 childrens with congenital hydronephrosis detected within 1 month of age. The severity of hydronephrosis was graded by SFU (Society of Fetal Urology) system, and anterior posterior pelvic diameter (APPD). We evaluated the relationship between severity of hydronephrosis and incidence of VUR by using SPSS windows version 16.0. A P-value<0.05 is considered to be statistically significant. Results : Total renal unit number was 254, and 20(7.8%) renal units had VUR. We did not find any relationship between hydronephrosis grade the presence of VUR grade (P>0.05). In addition, there was no statistical significance between APPD, laterality of hydronephrosis and VUR incidence. However, renal units with VUR had lower spontaneous resolution rate (P<0.05), compared to renal units without VUR. Conclusion : In this study, there was no statistical significance between the severity of hydronephrosis and presence of VUR. Therefore, voiding cystourethrogram is recommended for all children with hydronephrosis to rule out VUR, regardless of the severity of hydronephrosis.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.32-40
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• 2008

Fuzzy rules are very useful and efficient to describe classification rules especially when the attribute values are continuous and fuzzy in nature. However, it is generally difficult to determine membership functions for generating efficient fuzzy classification rules. In this paper, we propose a method of automatic generation of efficient fuzzy classification rules using evolutionary algorithm. In our method we generate a set of initial membership functions for evolutionary algorithm by supervised clustering the training data set and we evolve the set of initial membership functions in order to generate fuzzy classification rules taking into consideration both classification accuracy and rule comprehensibility. To reduce time to evaluate an individual we also propose an evolutionary algorithm with data partition evaluation in which the training data set is partitioned into a number of subsets and individuals are evaluated using a randomly selected subset of data at a time instead of the whole training data set. We experimented our algorithm with the UCI learning data sets, the experiment results showed that our method was more efficient at average compared with the existing algorithms. For the evolutionary algorithm with data partition evaluation, we experimented with our method over the intrusion detection data of KDD'99 Cup, and confirmed that evaluation time was reduced by about 70%. Compared with the KDD'99 Cup winner, the accuracy was increased by 1.54% while the cost was reduced by 20.8%.

• Journal of the Korea Society for Simulation
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• v.27 no.4
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• pp.47-60
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• 2018

Today's unmanned technology, which is being used in various industries, is expected to be able to make autonomous judgements as autonomous technology matures, in the long run aspects. In order to improve the usability of unmanned system in the military field, it is necessary to develop a technique for systematically and quantitatively analyzing the efficiency and effectiveness of the unmanned system by means of a substitute for the tasks performed by humans. In this paper, we propose the method of representing rule-based tactical behavior and modeling manned and unmanned reconnaissance agents that can effectively analyze the path alternatives which is required for the future armored cavalry to establish a reconnaissance mission plan. First, we model the unmanned ground vehicle, small tactical vehicle, and combatant as an agent concept. Next, we implement the proposed agent behavior rules, e.g., maneuver, detection, route determination, and combatant's dismount point selection, by NetLogo. Considering the conditions of maneuver, enemy threat elements, reconnaissance assets, appropriate routes are automatically selected on the operation area. It is expected that it will be useful in analyzing unmanned ground system effects by calculating reconnaissance conducted area, time, and combat contribution ratio on the route.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.11
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• pp.2169-2177
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• 2015

This paper proposes a new pattern matching module to overcome the increased runtime of previous algorithm using RAM, which was designed to overcome cost limitation of hash-based algorithm using CAM (Content Addressable Memory). By adopting Merge FSM algorithm to reduce the number of state, the proposed module contains state block and entry block to use in RAM. In the proposed module, one input string is compared with multiple entry strings simultaneously using entry block. The effectiveness of the proposed pattern matching unit is verified by executing Snort 2.9 rule set. Experimental results show that the number of memory reads has decreased by 15.8%, throughput has increased by 47.1%, while memory usage has increased by 2.6%, when compared to previous methods.

• Journal of Internet Computing and Services
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• v.9 no.3
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• pp.51-58
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• 2008

Wireless sensor networks are used by various application areas to implement smart data processing and ubiquitous system. In the recent research of parking management system based on wireless sensor networks, adaptive sensing and efficient data processing are not considered. The effectiveness of implementing these distributed computing devices affects the performance of the applications in parking management. This paper proposes an adaptive sensing using fuzzy wireless sensor for the ubiquitous networks of parking management system. The fuzzy inference system is encoded in the sensor for efficient car presence detection. Moreover, a rule base adaptive module is proposed which wirelessly transmit the new values to each sensor for adapting the environment of car park area. The result of experiments shows that the fuzzy wireless sensor provides more throughputs and less time delays compared to a normal method of data gathering by wireless sensors.

• Annual Conference of KIPS
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• 2017.04a
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• pp.315-318
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• 2017

Nowadays, Distributed Denial of Service (DDoS) attacks have gained increasing popularity and have been a major factor in a number of massive cyber-attacks. It could easily exhaust the computing and communicating resources of a victim within a short period of time. Therefore, we have to find the method to detect and prevent the DDoS attack. Recently, there have been some researches that provide the methods to resolve above problem, but it still gets some limitations such as low performance of detecting and preventing, scope of method, most of them just use on cloud server instead of network, and the reliability in the network. In this paper, we propose solutions for (1) handling multiple DDoS attacks from multiple IP address and (2) handling the suspicious attacks in the network. For the first solution, we assume that there are multiple attacks from many sources at a times, it should be handled to avoid the conflict when we setup the preventing rule to switches. In the other, there are many attacks traffic with the low volume and same destination address. Although the traffic at each node is not much, the traffic at the destination is much more. So it is hard to detect that suspicious traffic with the sampling based method at each node, our method reroute the traffic to another server and make the analysis to check it deeply.

• Journal of Pharmaceutical Investigation
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• v.35 no.4
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• pp.287-293
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• 2005

The purpose of the present study was to evaluate the bioequivalence of two glimepiride tablets, Amaryl tablet (Handok & Aventis Korea, reference drug) and Mepiril tablet (Myungmoon Pharm. Co., Ltd., Korea, test drug), according to the guidelines of Korea Food and Drug Administration (KFDA). After adding an internal standard (glibenclamide) to human plasma, plasma samples were extracted using 1mL of methyl tertiary butyl ether. Compounds extracted were analyzed by reverse-phase HPLC with multiple reaction monitoring (MRM) mode analyte detection. This method for determination glimepiride proved accurate and reproducible, with a limit of quantitation of 2 ng/mL in human plasma. Twenty-four healthy male Korean volunteers received each medicine at the glimepiride dose of 2 mg in a $2{\times}2$ crossover study. There was a one-week washout period between the doses. Plasma concentrations of glimepiride were monitored by a LC-MS/MS for over a period of 12 hr after the administration. $AUC_t$ (the area under the plasma concentration-time curve from time zero to 12 hr) was calculated by the linear trapezoidal rule method. $C_{max}$ (maximum plasma drug concentration) and $T_{max}$ (time to reach $C_{max}$) were compiled from the plasma concentration-time data. Analysis of variance was carried out using logarithmically transformed $AUC_t$ and $C_{max}$. No significant sequence effect was found for all of the bioavailability parameters indicating that the crossover design was properly performed. The 90% confidence intervals of the $AUC_t$ ratio and the $C_{max}$ ratio for Amaryl/Mepiril were log 0.9583-log 1.1357 and log 1.0570-log 1.2376, respectively. These values were within the acceptable bioequivalence intervals of log 0.80-log 1.25. Taken together, our study demonstrated the bioequivalence of Amaryl and Mepiril with respect to the rate and extent of absorption.

• Journal of KIISE:Databases
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• v.31 no.1
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• pp.1-12
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• 2004

As network systems are developed rapidly and network architectures are more complex than before, it needs to use PBNM(Policy-Based Network Management) in network system. Generally, architecture of the PBNM consists of two hierarchical layers: management layer and enforcement layer. A security policy server in the management layer should be able to generate new policy, delete, update the existing policy and decide the policy when security policy is requested. And the security policy server should be able to analyze and manage the alert messages received from Policy enforcement system in the enforcement layer for the available information. In this paper, we propose an alert analyzer using data mining. First, in the framework of the policy-based network security management, we design and implement an alert analyzes that analyzes alert data stored in DBMS. The alert analyzer is a helpful system to manage the fault users or hosts. Second, we implement a data mining system for analyzing alert data. The implemented mining system can support alert analyzer and the high level analyzer efficiently for the security policy management. Finally, the proposed system is evaluated with performance parameter, and is able to find out new alert sequences and similar alert patterns.

• Journal of the Korea Society of Computer and Information
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• v.10 no.5 s.37
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• pp.65-76
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• 2005

A digital video is a very long data that requires large-capacity storage space. As such, prior to watching a long original video, video watchers want to watch a summarized version of the video. In the field of sports, in particular, highlights videos are frequently watched. In short, a highlights video allows a video watcher to determine whether the highlights video is well worth watching. This paper proposes a scheme for creating soccer video highlights using the structural features of captions in terms of time and space. Such structural features are used to extract caption frame intervals and caption keyframes. A highlights video is created through resetting shots for caption keyframes, by means of logical indexing, and through the use of the rule for creating highlights. Finally, highlights videos and video segments can be searched and browsed in a way that allows the video watcher to select his/her desired items from the browser.

• The Journal of the Korea Contents Association
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• v.11 no.10
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• pp.59-68
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• 2011

As the role of soccer game analyst who analyzes soccer games and creates soccer wining strategies is emphasized, it is required to have high-level analysis beyond the procedural ones such as main event detection in the context of IT based broadcasting soccer game research community. In this paper, we propose a novel approach to generate the high-level in-depth analysis results via real-time text based soccer Webcast and text mining. Proposed method creates a metadata such as attribute, action and event, build index, and then generate available knowledges via text mining techniques such as association rule mining, event growth index, and pathfinder network analysis using Webcast and domain knowledges. We carried out a feasibility experiment on the proposed technique with the Webcast text about Spain team's 2010 World Cup games.