• Journal of Welding and Joining
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• v.25 no.1
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• pp.57-62
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• 2007

In the coarse grained HAZ of conventional TiN steel, most TiN particles are dissolved and austenite grain growth easily occurrs during high heat input welding. To avoid this difficulty, thermal stability of TiN particles is improved by increasing nitrogen content in EH36-TM steel. Increased thermal stability of TiN particle is helpful for preventing austenite grain growth by the pinning effect. In this study, the mechanical properties and microstructures of high heat input welded Tandem EGW joint in EH36-TM steel with high nitrogen content were investigated. The austenite grain size in simulated HAZ of the steel at $1400^{\circ}C$ was much smaller than that of conventional TiN steel. Even for high heat input welding, the microstructure of coarse grained HAZ consisted of fine ferrite and pearlite and the mechanical properties of the joint were sufficient to meet all the requirements specified in classification rule.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.735-743
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• 2020

Secure coding is a technique that detects malicious attack or unexpected errors to make software systems resilient against such circumstances. In many cases secure coding relies on static analysis tools to find vulnerable patterns and contaminated data in advance. However, secure coding has the disadvantage of being dependent on rule-sets, and accurate diagnosis is difficult as the complexity of static analysis tools increases. In order to support secure coding, we apply machine learning techniques, such as DNN, CNN and RNN to investigate into finding major weakness patterns shown in secure development coding guides and present machine learning models and experimental results. We believe that machine learning techniques can support detecting security weakness along with static analysis techniques.

• Journal of Korean Society for Atmospheric Environment
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• v.9 no.3
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• pp.207-215
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• 1993

In order to statistically predict $O_3$ levels in Seoul, the study used the TMS (telemeted air monitoring system) data from the Department of Environment, which have monitored at 20 sites in 1989 and 1990. Each data in each site was characterized by 6 major criteria pollutants ($SO_2, TSP, CO, NO_2, THC, and O_3$) and 2 meteorological parameters, such as wind speed and wind direction. To select proper variables and to determine each pollutant's behavior, univariate statistical analyses were extensively studied in the beginning, and then various applied statistical techniques like cluster analysis, regression analysis, and expert system have been intensively examined. For the initial study of high level $O_3$ prediction, the raw data set in each site was separated into 2 group based on 60 ppb $O_3$ level. A hierarchical cluster analysis was applied to classify the group based on 60 ppb $O_3$ into small calsses. Each class in each site has its own pattern. Next, multiple regression for each class was repeatedly applied to determine an $O_3$ prediction submodel and to determine outliers in each class based on a certain level of standardized redisual. Thus, a prediction submodel for each homogeneous class could be obtained. The study was extended to model $O_3$ prediction for both on-time basis and 1-hr after basis. Finally, an expect system was used to build a unified classification rule based on examples of the homogenous classes for all of sites. Thus, a concept of high level $O_3$ prediction model was developed for one of $O_3$ alert systems.

• Journal of the Korea Computer Industry Society
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• v.2 no.2
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• pp.151-156
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• 2001

We describe a new representation for learning concepts that differs from the traditional decision tree and rule induction algorithms. Our algorithm PROLEARN learns one or more prototype per class and follows instance based classification with them. Prototype here differs from psychological term in that we can have more than one prototype per concept and also differs from other instance based algorithms since the prototype is a "ficticious ideal example". We show that PROLEARN is as good as the traditional machine learning algorithms but much move stable than them in an environment that has noise or changing training set, what we call 'stability’.tability’.

• Korean Journal of Artificial Intelligence
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• v.4 no.1
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• pp.11-13
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• 2016

These days, medical technology has been developed rapidly to meet desire of living healthy life. Average lifespan was extended to let people see a doctor because of many reasons. This study has shown rate of leaving of hospitals to investigate the rate of not only department of surgery but also department of internal medicine. Linear model, tree, classification rule, association and algorithm of data mining were used. This study investigated by using J48 and AD tree of decision-making tree In this study, J48 and AD tree of decision-making tree of data mining were used to investigate based on result of both data. Both algorithms were found to have similar performance. Both algorithms were not equivalent to require detailed experiment. Collect more experimental data in the future to apply from various points of view. Development of medical technology gives dream, hope and pleasure. The ones who suffer from incurable diseases need developed medical technology. Environment being similar to the reality shall be made to experiment exactly to investigate data carefully and to let the ones of various ages visit hospital and to increase survival rate.

• Proceedings of KOSOMES biannual meeting
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• 2006.11a
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• pp.283-289
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• 2006

This study is a preparation for the application of FSA (Formal Safety Assessment) to the fire safety of ships. FSA is the new-fashioned methodology proposed to prevent ships from the accidents. To make a base of the fire safety assessment about ship's fire protection design and Classification Society rule, statistical informations for the fire safety engineering are investigated. From results, the necessity of new criterion for ship's fire safety design, the need to study the human behavior in the evacuation from fire, and the development of new fire progress model considering special situations in ships are acknowledged.

• Journal of information and communication convergence engineering
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• v.15 no.1
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• pp.43-48
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• 2017

Movie ratings are crucial for recommendation engines that track the behavior of all users and utilize the information to suggest items the users might like. It is intuitively appealing that information about the viewing preferences in terms of movie genres is sufficient for predicting a genre of an unlabeled movie. In order to predict movie genres, we treat ratings as a feature vector, apply a Bernoulli event model to estimate the likelihood of a movie being assigned a certain genre, and evaluate the posterior probability of the genre of a given movie by using the Bayes rule. The goal of the proposed technique is to efficiently use movie ratings for the task of predicting movie genres. In our approach, we attempted to answer the question: "Given the set of users who watched a movie, is it possible to predict the genre of a movie on the basis of its ratings?" The simulation results with MovieLens 1M data demonstrated the efficiency and accuracy of the proposed technique, achieving an 83.8% prediction rate for exact prediction and 84.8% when including correlated genres.

• Journal of Korean Library and Information Science Society
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• v.34 no.2
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• pp.1-18
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• 2003

Chosundoseohaeje, a book type catalog was published three times under the rule of Japanese imperialism. This catalog has several characteristics of modem catalog as fellows : First, each record of this catalog includes title, volume no., statements of responsibility, printing type, annotated bibliography containing date, author, background, structure, contents of the book, and biographies. Second, this catalog has a subject retrieval system by the four-part classification(Kyung, Sa, Ja, Jib), title retrieval system by Japanese alphabetical index, and authorㆍeditor retrieval system by their family name index or king's name index. Third, this catalog has a system indicating the location of described books by Gyujanggak book numbers.

• Proceedings of the KSRS Conference
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• v.2
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• pp.868-871
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• 2006

Mortality of domestic people from cardiovascular disease ranked second, which followed that of from cancer last year. Therefore, it is very important and urgent to enhance the reliability of medical examination and treatment for cardiovascular disease. Heart Rate Variability (HRV) is the most commonly used noninvasive methods to evaluate autonomic regulation of heart rate and conditions of a human heart. In this paper, our aim is to extract a quantitative measure for HRV to enhance the reliability of medical examination for cardiovascular disease, and then develop a prediction method for extracting multi-parametric features by analyzing HRV from ECG. In this study, we propose a hybrid Bayesian classifier called FP-based Bayesian. The proposed classifier use frequent patterns for building Bayesian model. Since the volume of patterns produced can be large, we offer a rule cohesion measure that allows a strong push of pruning patterns in the pattern-generating process. We conduct an experiment for the FP-based Bayesian classifier, which utilizes multiple rules and pruning, and biased confidence (or cohesion measure) and dataset consisting of 670 participants distributed into two groups, namely normal and patients with coronary artery disease.

• Journal of the Society of Naval Architects of Korea
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• v.36 no.3
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• pp.115-121
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• 1999

Marine casualties of dangerous cargo carriers lead to not only the loss of human life and properties, but also marine pollution caused by spilled oil and hazardous cargo. So the prevention of marine casualties and emergence response to minimize pollution are very important problems to be settled. But until now, most of salvage assistance jobs have been done based on rule of thumb without any technical support. It is not easy to cope with the incidents safely and rapidly under the current situation. The purpose of this paper is to develop a systematic and engineering salvage assistance tool available in the casualty sites. This paper contains the construction of salvage system, classification of technical items, and prototype system for the safety assessment. The developed system enable a salvage engineer in his/her salvaging jobs to perform safely and promptly.