• Journal of Radiation Protection and Research
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• v.44 no.2
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• pp.64-71
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• 2019

Background: It is very difficult to distinguish between a radioactive contamination source and background radiation from natural radionuclides in the marine environment by means of online monitoring system. The objective of this study was to investigate a statistical process for triggering abnormal level of count rate data measured from our on-line seawater radioactivity monitoring. Materials and Methods: Count rate data sets in time series were collected from 9 monitoring posts. All of the count rate data were measured every 15 minutes from the region of interest (ROI) for $^{137}Cs$ ($E_{\gamma}=661.6keV$) on the gamma-ray energy spectrum. The Shewhart ($3{\sigma}$), CUSUM, and Bayesian S-R control chart methods were evaluated and the comparative analysis of determination methods for count rate data was carried out in terms of the false positive incidence rate. All statistical algorithms were developed using R Programming by the authors. Results and Discussion: The $3{\sigma}$, CUSUM, and S-R analyses resulted in the average false positive incidence rate of $0.164{\pm}0.047%$, $0.064{\pm}0.0367%$, and $0.030{\pm}0.018%$, respectively. The S-R method has a lower value than that of the $3{\sigma}$ and CUSUM method, because the Bayesian S-R method use the information to evaluate a posterior distribution, even though the CUSUM control chart accumulate information from recent data points. As the result of comparison between net count rate and gross count rate measured in time series all the year at a monitoring post using the $3{\sigma}$ control charts, the two methods resulted in the false positive incidence rate of 0.142% and 0.219%, respectively. Conclusion: Bayesian S-R and CUSUM control charts are better suited for on-line seawater radioactivity monitoring with an count rate data in time series than $3{\sigma}$ control chart. However, it requires a continuous increasing trend to differentiate between a false positive and actual radioactive contamination. For the determination of count rate, the net count method is better than the gross count method because of relatively a small variation in the data points.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.593-596
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• 1999

In this paper, we propose an image retrieval system using the MBCM(Modified Borda Count method) in CME(Combining Multiple Experts). It combines color-, shape- and texture-based retrieval sub-systems. CME method can complementarily combine results of each retrieval system, which uses different features. There are some problems when the Borda count method in pattern recognition is applied to image retrieval. Thus, we propose a modified Borda count method to solve these problems. In the experiment, our method reduces false positive errors and produces better results than that of each retrieval module that uses only one feature.

• Journal of IKEEE
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• v.26 no.4
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• pp.622-627
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• 2022

This paper proposes an intrusion detection system for in-vehicle network to improve detection performance considering attack counts and attack types. In intrusion detection system, both FNR (False Negative Rate), where intrusion frame is misjudged as normal frame, and FPR (False Positive Rate), where normal frame is misjudged as intrusion frame, seriously affect vechicle safety. This paper proposes a novel intrusion detection algorithm to improve both FNR and FPR, where data frame previously detected as intrusion above certain attack counts is automatically detected as intrusion and the automatic intrusion detection method is adaptively applied according to attack types. From the simulation results, the propsoed method effectively improve both FNR and FPR in DoS(Denial of Service) attack and spoofing attack.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.6
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• pp.1462-1470
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• 2013

This paper proposes an SWAD-KNH(Sybil & Wormhole Attack Detection using Key, Neighbor list and Hop count) technique which consists of an SWAD(Sybil & Wormhole Attack Detection) module detecting an Worm attack and a KGDC(Key Generation and Distribution based on Cluster) module generating and an sense node key and a Group key by the cluster and distributing them. The KGDC module generates a group key and an sense node key by using an ECDH algorithm, a hash function, and a key-chain technique and distributes them safely. An SWAD module strengthens the detection of an Sybil attack by accomplishing 2-step key acknowledgement procedure and detects a Wormhole attack by using the number of the common neighbor nodes and hop counts of an source and destination node. As the result of the SWAD-KNH technique shows an Sybil attack detection rate is 91.2% and its average FPR 3.82%, a Wormhole attack detection rate is 90%, and its average FPR 4.64%, Sybil and wormhole attack detection rate and its reliability are improved.

• Journal of the Korea Society for Simulation
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• v.21 no.4
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• pp.91-102
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• 2012

Network port scan attack is the method for finding ports opening in a local network. Most existing IDSs(intrusion detection system) record the number of packets sent to a system per unit time. If port scan count from a source IP address is higher than certain threshold, it is regarded as a port scan attack. The degree of risk about source IP address performing network port scan attack depends on attack count recorded by IDS. However, the measurement of risk based on the attack count may reduce port scan detection rates due to the increased false negative for slow port scan. This paper proposes a method of summarizing 4 types of information to differentiate network port scan attack more precisely and comprehensively. To integrate the riskiness, we present a risk index that quantifies the risk of port scan attack by using PCA. The proposed detection method using risk index shows superior performance than Snort for the detection of network port scan.

• Fashion & Textile Research Journal
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• v.12 no.4
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• pp.500-507
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• 2010

In this study, physical properties were studied by using latent stretching yarn in order to develop the texturing yarn technique for super bulky yarn, which is better in bulkiness and handle than natural wool and also adds property of synthetic fiber to natural wool. In order to obtain textured conditions by analysing basic properties for manufacturing DTY yarn with super bulky property, DTY 50d/12 after spinning latent yarn spined POY 80d/12 was obtained under the two conditions of (i) false twist(T/M) level 3 in DTY texturing and (ii) draw ratio level 4 in draw texturing. For DTY texturing yarn, Elongation rate increased as the heat treatment time and temperatures increased. In addition, shrinkage became higher as false twist was higher, so that elongation rate became lower. When annealing became longer in time and higher in temperature, initial modulus increased. In addition, as the count of false twist increased, the initial modulus showed higher values. For draw texturing yarn, under the conditions of heat temperature 180 and heating time 30 minutes, shrinkage rate in draw ratio 1.55 and 1.6 draw ratio was 7%, and that in 1.65 and 1.7 draw ratio was 8.5%. High draw ratio samples' tenacity was much influenced by heating time and temperature, but low draw ratio samples' tenacity was influenced not by treated time, but by treated temperature.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.3
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• pp.547-554
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• 1992

Response characteristics and false counts of laser and white light optical particle counters (OPC) have been studied as a function of particle size using monodisperse polystylen laterx (PSL) particles. Theoretical light scattering calculations for He-Ne laser based counter have been compared with the experimental results and thus good agreements have been found. The light scattering intensity in monochromatic light shows an oscillatory character for the transparent and spherical particles of PSL due to Mie resonance. Because of this effect, the response of the LAS-X OPC showed almost same responses in the diameter ranges of 0.4mu.m to 0.6mu.m and 0.7mu.m to 1.0mu.m for PSL particles. A laser optical particle counter with high flow rate applied for clean room has been studied to identify the noise sources. Three different manufacturer's clean room optical particle counters alos have been tested to measure the background noise level.

• Communications for Statistical Applications and Methods
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• v.19 no.6
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• pp.899-904
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• 2012

High-dimensional categorical data models with small sample sizes have not been used extensively in genomic sequences that involve count (or discrete) or purely qualitative responses. A basic task is to identify differentially expressed genes (or positions) among a number of genes. It requires an appropriate test statistics and a corresponding multiple testing procedure so that a multivariate analysis of variance should not be feasible. A family wise error rate(FWER) is not appropriate to test thousands of genes simultaneously in a multiple testing procedure. False discovery rate(FDR) is better than FWER in multiple testing problems. The data from the 2002-2003 SARS epidemic shows that a conventional FDR procedure and a proposed test statistic based on a pseudo-marginal approach with Hamming distance performs better.

• 한국공간정보시스템학회:학술대회논문집
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• 2004.12a
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• pp.69-74
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• 2004

Selectivity estimation for spatial query is very important process in finding the most efficient execution plan. Many works have been performed to estimate accurately selectivity. Although they deal with some problems such as false-count, multi-count, they require a large amount of memory to retain accurate selectivity, so they can not get good results in little memory environments such as mobile-based small database. In order to solve this problem, we propose a new technique called MW histogram which is able to compress summary data and get reasonable results. It also has a flexible structure to react dynamic update. The experimental results showed that the MW histogram has lower relative error than MinSkew histogram and gets a good selectivity in little memory.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.766-768
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• 2003

Selectivity estimation for spatial query is curial in Spatial Database Management Systems(SDBMS). Many works have been performed to estimate accurate selectivity. Although they deal with some problems such as false-count, multi-count arising from properties of spatial dataset, they can not get such effects in little memory space.* Therefore, we need to compress spatial dataset into little memory. In this paper, we propose a new technique called MW Histogram which is able to compress summary data and get reasonable results. Our method is based on two techniques:(a)MinSkew partitioning algorithm which deal with skewed spatial datasets. efficiently (b) Wavelet transformation which compression effect is proven. We evaluate our method via real datasets. The experimental result shows that the MW Histogram has the ability of providing estimates with low relative error and retaining the similar estimates even if memory space is small.