• The Korean Journal of Pain
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• v.10 no.1
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• pp.5-10
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• 1997

Background : The Current Perception Threshold (CPT) provides an objective, quantitative gauge of sensory nerve integrity which is obtainable from any cutaneous site. CPT measurement can confirm and quantify or rule out dysfunction of nerve through comparison with established normative values ($Neuval^{TM}$ CPT database). The aim of this study is to compare collected data from Korean adults with $Neuval^{TM}$ CPT database. Method : Normative data from 5 standard test site in face, hand, toe were obtained from 50 healthy adults. Three frequencies(5, 250, 2000 Hz) were stimulated with $Neuromoter^{(R)}$ CPT device. Results : The results of our data were statistically significantly different than Neuval data except in face, but within normal range. Sensory Threshold increased as the frequency of the stimulus changed from 5 Hz to 250 Hz to 2000 Hz., and from face to hand to toe. Conclusion : CPT testing is a valuable neurologic testing modality that is noninvasive and highly reliable for diagnosis and evaluation of sensory nerves where neuropathy is suspected.

• The Journal of the Korean bone and joint tumor society
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• v.9 no.1
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• pp.93-100
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• 2003

Clinical outcome of malignant tumor heavily depends on early diagnosis and proper management of the patient. But it's very difficult to diagnose malignant tumor in early stage because of it's vague symptoms and inadequate evidences of malignancy in radiologic studies and biopsy. Malignant tumor mistaken for infection or fracture initially will undergo inadequate treatment and that will influence on it's prognosis. So it's very important to rule out the possibility of malignancy by repeated evaluation if it's diagnosis is not definite. We report 1 case of osteosarcoma initially mistaken for stress fracture and 3 cases of osteosarcoma, malignant lymphoma and Ewing's sarcoma initially mistaken for tuberculosis and review the literature.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.3
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• pp.344-349
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• 2006

The low-temperature processing is very important for fabrication of the very large scale ($60{\sim}70nm$) semiconductor devices since the submicron transistors are sensitive to the thermal budget. Hence, in this work, we propose a noble low-temperature LPCVD (Low-Pressure Chemical Vapor Deposition) process for the $SiO_2$ film and evaluate the electrical reliability of the LTO (Low-Temperature Oxide) by making the capacitors with ONO (Oxide/Nitride/Oxide) structure. The leak current of the LTO was similar to that of the high-temperature wet oxide until the electric field was lower than 5 MV/cm. However, when the electric field was higher, the LTO showed much better characteristics.

• The Journal of the Korea Contents Association
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• v.18 no.4
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• pp.48-59
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• 2018

Recently, network technology has been used in various fields due to development of network technology. However, there has been an increase in the number of attacks targeting public institutions and companies by exploiting the evolving network technology. Meanwhile, the existing network intrusion detection system takes much time to process logs as the amount of network log increases. Therefore, in this paper, we propose a Spark-based network log analysis system that detects unstructured network attack pattern. by using Snort. The proposed system extracts and analyzes the elements required for network attack pattern detection from large amount of network log data. For the analysis, we propose a rule to detect network attack patterns for Port Scanning, Host Scanning, DDoS, and worm activity, and can detect real attack pattern well by applying it to real log data. Finally, we show from our performance evaluation that the proposed Spark-based log analysis system is more than two times better on log data processing performance than the Hadoop-based system.

• The Journal of the Korea Contents Association
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• v.7 no.4
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• pp.66-73
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• 2007

Internet is a part of our common life and tremendous information is cumulated. In these trends, the personalization becomes a very important technology which could find exact information to present users. Previous personalized services use content based filtering which is able to recommend by analyzing the content and collaborative filtering which is able to recommend contents according to preference of users group. But, collaborative filtering needs the evaluation of some amount of data. Also, It cannot reflect all data of users because it recommends items based on data of some users who have similar inclination. Therefore, we need a new recommendation method which can recommend prefer items without preference data of users. In this paper, we proposed the apparel coordination system using personalized preference on the semantic web. This paper provides the results which this system can reduce the searching time and advance the customer satisfaction measurement according to user's feedback to system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.1
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• pp.459-466
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• 2011

In this paper, we proposed a data mining framework for the management of alerts in order to improve the performance of the intrusion detection systems. The proposed alert data mining framework performs alert correlation analysis by using mining tasks such as axis-based association rule, axis-based frequent episodes and order-based clustering. It also provides the capability of classify false alarms in order to reduce false alarms. We also analyzed the characteristics of the proposed system through the implementation and evaluation of the proposed system. The proposed alert data mining framework performs not only the alert correlation analysis but also the false alarm classification. The alert data mining framework can find out the unknown patterns of the alerts. It also can be applied to predict attacks in progress and to understand logical steps and strategies behind series of attacks using sequences of clusters and to classify false alerts from intrusion detection system. The final rules that were generated by alert data mining framework can be used to the real time response of the intrusion detection system.

• Journal of KIISE:Databases
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• v.35 no.3
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• pp.199-207
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• 2008

The FP-tree(Frequency Pattern Tree) mining association rules algorithm was proposed to improve mining performance by reducing DB scan overhead dramatically, and it is recognized that the performance of it is better than that of any other algorithms based on different approaches. But the FP-tree algorithm needs a few more memory because it has to store all transactions including frequent itemsets of the DB. This paper implements a FP-tree algorithm on a general purpose UNK system and compares it with the DHP(Direct Hashing and Pruning) algorithm which uses hash tree and direct hash table from the point of memory usage and execution time. The results show surprisingly that the FP-tree algorithm is poor than the DHP algorithm in some cases even if the system memory is sufficient for the FP-tree. The characteristics of the test data are as follows. The site of DB is look, the number of total items is $1K{\sim}7K$, avenrage length of transactions is $5{\sim}10$, avergage size of maximal frequent itemsets is $2{\sim}12$(these are typical attributes of data for large-scale convenience stores).

• Journal of Pharmaceutical Investigation
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• v.35 no.5
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• pp.355-360
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• 2005

The purpose of the present study was to evaluate the bioequivalence of two cetirizine HCl tablets, Zyrtec tablet (UCB Pharm. Co., Ltd. Korea, reference product) and Zyrix tablet (Kukje Pharm. Co., Ltd., Korea, test product), according to the guidelines of Korea Food and Drug Administration (KFDA). After adding an internal standard (diazepam), plasma samples were extracted using 1 mL of dichloromethane. Compounds extracted were analyzed by reverse-phase HPLC with ultra-violet detector. This method for determination cetirizine is proved accurate and reproducible with a limit of quantitation of 10 ng/mL in male plasma. Twenty-four healthy male Korean volunteers received each medicine at the cetirizine HCl dose of 10 mg in a $2{\times}2$ crossover study. There was a one-week wash out period between the doses. Plasma concentrations of cetirizine were monitored for over a period of 24 hr after the administration. AUC (the area under the plasma concentration-time curve) was calculated by the linear trapezoidal rule. $C_{max}$ (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 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 for the log transformed data were acceptable range of log 0.8 to log 1.25 $(e.g.,\;log\;0.93-log\;1.08\;for\;AUC_{0-t},\;log\;0.91-log\;1.08\;for\;AUC_{0-{\infty}}\;and\;log\;1.01-log\;1.11\;for\;C_{max})$. The major parameters, AUC and $C_{max}$ met the criteria of KFDA for bioequivalence indicating that Zyrix tablet is bioequivalent to Zyrtec tablet.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.1
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• pp.66-75
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• 2002

For the theoretical performance analysis of Viterbi Decoder for wireless LAN with data rate 12Mbps, code rate 1/2 and constraint length 7 defined in IEEE 802.11a, the transfer function is derived using Cramer's rule and the first-event error probability and bit error probability is derived under the AWGN. In the design process, input symbol is quantized into 16 steps for 4 bit soft decision and register exchange method instead of memory method is proposed for trace back, which enables the majority at the final decision stage. In the implementation, the Viterbi decoder based on parallel architecture with pipelined scheme for processing 12Mbps high speed data rate and AWGN generator are implemented using FPGA chips. And then its performance is verified in real time.

• Journal of Digital Convergence
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• v.11 no.6
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• pp.175-185
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• 2013

For effective information sharing, data provenance semantics need to be managed effectively. Based on a scheme to represent data provenance semantics, we propose a model to calculate information sharing costs. Information sharing costs are derived from probabilities of type I and type II errors that occur in organizational information sharing, costs related to these errors, and information sharing distances between organizational units which are determined by information sharing workflows. We apply the model to various types of information sharing workflows including departmental information systems, hierarchical information systems, a hub and a stand-alone system. The calculated information sharing costs show that the hub with data standardization is best in information sharing; however without standardization its information sharing cost deteriorates to that of a departmental information system. And, any information sharing workflow is better than a stand-alone system. It is proved that the model is useful in analyzing effectiveness of information sharing workflows and their characteristics.