• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.1
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• pp.124-132
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• 2018

This paper presents a shelf life assessment for K-1 military gas masks in the Republic of Korea using test data of Chemical Materiels Stockpile Reliability Program(CSRP). For the shelf life assessment, over 2,500 samples between 2006 and 2015 were collected from field tests and analyzed to estimate a probability of proper and improper functionality using Bayesian estimation. For this, three stages were considered; a pre-processing, a processing and an assessment. In the pre-processing, major components which directly influence the shelf life of the mask were statistically analyzed and selected by applying principal component analysis from all test components. In the processing, with the major components chosen in the previous stage, both proper and improper probability of gas masks were computed by applying Bayesian estimation. In the assessment, the probability model of the mask shelf life was analyzed with respect to storage periods between 0 and 29 years resulting in between 66.1 % and 100 % performances in accuracy, sensitivity, positive predictive value, and negative predictive value.

• Journal of the Korea Safety Management & Science
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• v.19 no.2
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• pp.31-39
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• 2017

Classify of explosion hazardous areas must be made at the site where flammable materials are used. This reason is that it is necessary to manage ignition sources in of explosion hazardous areas in order to reduce the risk of explosion. If such an explosion hazard area is widened, it becomes difficult to increase the number of ignition sources to be managed. The method using the virtual volume currently used is much wider than the result using CFD(Computational Fluid Dynamics). Therefore, we tried to improve the current method to compare with the new method using leakage characteristics. The result is a realistic explosion hazard if the light gas is calibrated to the mass and the heavy gas is calibrated to the lower explosion limit. However, it is considered that the safety factors should be taken into account in the calculated correction formula because such a problem should be considered as a buffer for safety.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.72-79
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• 2008

The weak point of the artificial neural network(ANN) is that it is easy to fall in local minima when it learns too much nonlinear data. Accordingly, the classification ratio must be low. To overcome this weakness, the hybrid method has been proposed. That is, the ANN learns data selectively after detecting the defect position by the support vector machine(SVM). First, the SVM has been used for determination of the defect position and then the magnitude of the defect has been measured by the ANN. In off-design condition, the operation region of the engine is wide and the nonlinearity of learning data increases. The module system, dividing the whole operating region into reasonably small-size sections, has been suggested to solve this problem. In this study, the proposed algorithm has diagnosed the defects of triple components as well as single and dual components of the gas turbine engine in off-design condition.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.6_1
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• pp.907-915
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• 2020

Specification selection, Layout, specifications and combinations of Power Drives, and Ship motions were studied for FGPP(Floating Gas-fired Power Plants), which are still needed in areas such as the Caribbean, Latin America, and Southeast Asia where electricity is not sufficiently supplied. From this study, the optimal equipment layout in ships was derived. In addition, the difference between engine and turbine was verified through LCOE(Levelized Cost of Energy) comparison according to the type and combination of Power Drives. Analysis of Hs(Significant Height of wave) and Tp(spectrum Peak Period of wave) for places where this FGPP will be tested or applied enables design according to wave characteristics in Brazil and Indonesia. Normalized Sloshing Pressures of FGPP and LNG Carrier are verified using a sloshing analysis program, which is CFD(Computational Fluid Dynamics) software developed by ABS(American Bureau of Shipping). Power Transmission System is studied with Double bus with one Circuit Breaker Topology. A nd the CFD analysis allowed us to calculate linear roll damping coefficients for more accurate full load conditions and ballast conditions. Through RAO(Response Amplitude Operator) analysis, we secured data that could minimize the movement of ships according to the direction of waves and ship placement by identifying the characteristics of large movements in the beam sea conditions. The FGPP has been granted an AIP(Approval in Principle) from a classification society, the ABS.

• Spatial Information Research
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• v.23 no.3
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• pp.67-77
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• 2015

This Study aimed to construction the plan of the statistics for national greenhouse gas inventories of international standards. Currently, the statistics of the greenhouse gas inventories of South Korea, has a problem that is not able to build the changed information. In previous studies, it has been limited to the construction of the information within each category. In order to solve these problems, targeting Gyeonggi province, we analyzed the land use change by utilizing the various information such as satellite images, KLIS, UPIS. As a result, we suggested the following implementation, classification system of LULUCF category, improvement of accuracy by utilizing satellite images of high resolution, additional research for methodology. Based on these contents, we suggested the construction plan of the statistics for national greenhouse gas inventories(LULUCF sector). Frist, it is necessary to construct of land use change informations for the past 20 years, Then, it need to create the matrix of land use change by utilizing satellite images and various land information systems.

• Journal of the Korea Institute of Military Science and Technology
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• v.7 no.2 s.17
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• pp.81-87
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• 2004

Semiconductor thick film gas sensors based on tin oxide are fabricated and their gas response characteristics are examined for four simulant gases of chemical warfare agent (CWA)s. The sensing materials are prepared in three different sets. 1) The Pt or Pd $(1,\;2,\;3\;wt.\%)$ as catalyst is impregnated in the base material of $SnO_2$ by impregnation method.2) $Al_2O_3\;(0,\;4,\;12,\;20\;wt.\%),\;In_2O_3\;(1,\;2,\;3\;wt.\%),\;WO_3\;(1,\;2,\;3\;wt.\%),\;TiO_2\;(3,\;5,\;10\;wt.\%)$ or $SiO_2\;(3,\;5,\;10\;wt.\%)$ is added to $SnO_2$ by physical ball milling process. 3) ZnO $(1,\;2,\;3,\;4,\;5\;wt.\%)$ or $ZrO_2\;(1,\;3,\;5\;wt.\%)$ is added to $SnO_2$ by co-precipitation method. Surface morphology, particle size, and specific surface area of fabricated sensing films are performed by the SEM, XRD and BET respectively. Response characteristics are examined for simulant gases with temperature in the range 200 to $400^{\circ}C$, with different gas concentrations. These sensors have high sensitivities more than $50\%$ at 500ppb concentration for test gases and also have shown good repetition tests. Four sensing materials are selected with good sensitivity and stability and are fabricated as a sensor array A sensor array Identities among the four simulant gases through the principal component analysis (PCA). High sensitivity is acquired by using the semiconductor thick film gas sensors and four CWA gases are classified by using a sensor array through PCA.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.24 no.2
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• pp.135-144
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• 2021

Purpose: Although ultrasonography is the gold standard of diagnosing intussusception, plain abdomen radiograph (AXR) is often used to make differential diagnosis for pediatric patients with abdominal pain. In intussusception patients, we aimed to analyze the AXR and clinical data to determine the characteristics of early AXR findings associated with diagnosis of intussusception and recurrence after reduction. Methods: Between January 2011 and June 2018, 446 patients diagnosed with intussusception based on International Classification of Diseases-10 code of K56.1 were admitted. We retrospectively reviewed medical records of 398 patients who received air reduction; 51 of them have recurred after initial reduction. We evaluated six AXR features including absent ascending colon gas, absent transverse colon gas, target sign, meniscus sign, mass, and ileus. Clinical data and AXR features were compared between single episode and recurrence groups. Results: Two groups did not show significant differences regarding clinical data. Mean time to recurrence from air reduction was 3.4±3.2 days. Absent ascending colon gas (63.9%) was the most common feature in intussusception, followed by mass (29.1%). All of six AXR features were observed more frequently in the recurrence group. Absent transverse colon gas was the most closely associated AXR finding for recurrence (odds ratio, 2.964; 95% confidence interval, 1.327-6.618; p=0.008). Conclusion: In our study, absence of ascending colon gas was the most frequently seen AXR factor in intussusception patients. Extended and careful observation after reduction may be beneficial if such finding on AXR is found in intussusception patients.

• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.33-41
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• 2022

In this article, we proposed to predict natural gas (NG) leakage levels through feature selection based on a factor analysis (FA) of the integrating the Korean Meteorological Agency data and natural gas leakage data for considering complex factors. The paper has been divided into three modules. First, we filled missing data based on the linear interpolation method on the integrated data set, and selected essential features using FA with OrdinalEncoder (OE)-based normalization. The dataset is labeled by K-means clustering. The final module uses four algorithms, K-nearest neighbors (KNN), decision tree (DT), random forest (RF), Naive Bayes (NB), to predict gas leakage levels. The proposed method is evaluated by the accuracy, area under the ROC curve (AUC), and mean standard error (MSE). The test results indicate that the OrdinalEncoder-Factor analysis (OE-F)-based classification method has improved successfully. Moreover, OE-F-based KNN (OE-F-KNN) showed the best performance by giving 95.20% accuracy, an AUC of 96.13%, and an MSE of 0.031.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.1
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• pp.87-95
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• 1996

A new design scheme for the fuzzy pattern matching classifier (FPMC) is proposed. in conventional design of FPMC, there are no exact information about the membership function of which shape and number critically affect the performance of classifier. So far, a trial and error or heuristic method is used to find membership functions for the input patterns. But each of them have limits in its application to the various types of pattern recognition problem. In this paper, a new method to find the appropriate shape and number of membership functions for the input patterns which minimize classification error is proposed using genetic algorithms(GAs). Genetic algorithms belong to a class of stochastic algorithms based on biological models of evolution. They have been applied to many function optimization problems and shown to find optimal or near optimal solutions. In this paper, GAs are used to find the appropriate shape and number of membership functions based on fitness function which is inversely proportional to classification error. The strings in GAs determine the membership functions and recognition results using these membership functions affect reproduction of next generation in GAs. The proposed design scheme is applied to the several patterns such as tire tread patterns and handwritten alphabetic characters. Experimental results show the usefulness of the proposed scheme.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.6
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• pp.531-536
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• 2002

In this paper, we have applied Genetic Algorithms(GAs) to Intrusion Detection System(TDS), and then proposed and simulated the misuse detection model firstly. We have implemented with the KBD contest data, and tried to simulated in the same environment. In the experiment, the set of record is regarded as a chromosome, and GAs are used to produce the intrusion patterns. That is, the intrusion rules are generated. We have concentrated on the simulation and analysis of classification among the Data Mining techniques and then the intrusion patterns are produced. The generated rules are represented by intrusion data and classified between abnormal and normal users. The different rules are generated separately from three models "Time Based Traffic Model", "Host Based Traffic Model", and "Content Model". The proposed system has generated the update and adaptive rules automatically and continuously on the misuse detection method which is difficult to update the rule generation. The generated rules are experimented on 430M test data and almost 94.3% of detection rate is shown.3% of detection rate is shown.