• Journal of The Geomorphological Association of Korea
• /
• v.26 no.2
• /
• pp.1-14
• /
• 2019

This study analyzed the relativity between block stream and talus distributions by employing a likelihood ratio approach. Possible distribution sites for each debris slope landform were extracted by applying a spatial integration model, in which we combined fuzzy set model, Bayesian predictive model, and logistic regression model. Moreover, to verify model performance, a success rate curve was prepared by cross-validation. The results showed that elevation, slope, curvature, topographic wetness index, geology, soil drainage, and soil depth were closely related to the debris slope landform sites. In addition, all spatial integration models displayed an accuracy of over 90%. The accuracy of the distribution potential area map of the block stream was highest in the logistic regression model (93.79%). Eventually, the accuracy of the distribution potential area map of the talus was also highest in the logistic regression model (97.02%). We expect that the present results will provide essential data and propose methodologies to improve the performance of efficient and systematic micro-landform studies. Moreover, our research will potentially help to enhance field research and topographic resource management.

• The Transactions of the Korea Information Processing Society
• /
• v.13 no.5
• /
• pp.227-235
• /
• 2024

Since nuclear power plants (NPPs) increasingly employ digital I&C systems, reliability evaluation for NPP software has become crucial for NPP probabilistic risk assessment. Several methods for estimating software reliability have been proposed, but there is no available tool support for those methods. To support NPP software manufacturers, we propose a reliability measurement tool for NPP software. We designed our tool to provide reliability estimation depending on available qualitative and quantitative information that users can offer. We applied the proposed tool to an industrial reactor protection system to evaluate the functionality of this tool. This tool can considerably facilitate the reliability assessment of NPP software.

• Journal of the Korean Geographical Society
• /
• v.40 no.3 s.108
• /
• pp.296-309
• /
• 2005

In this study, we investigated the change of future land-surface and relationships of land-surface change with geo-spatial information, using a Bayesian prediction model based on a likelihood ratio function, for analysing the land-surface change of the Gongju area. We classified the land-surface satellite images, and then extracted the changing area using a way of post classification comparison. land-surface information related to the land-surface change is constructed in a GIS environment, and the map of land-surface change prediction is made using the likelihood ratio function. As the results of this study, the thematic maps which definitely influence land-surface change of rural or urban areas are elevation, water system, population density, roads, population moving, the number of establishments, land price, etc. Also, thematic maps which definitely influence the land-surface change of forests areas are elevation, slope, population density, population moving, land price, etc. As a result of land-surface change analysis, center proliferation of old and new downtown is composed near Gum-river, and the downtown area will spread around the local roads and interchange areas in the urban area. In case of agricultural areas, a small tributary of Gum-river or an area of local roads which are attached with adjacent areas showed the high probability of change. Most of the forest areas are located in southeast and from this result we can guess why the wide chestnut-tree cultivation complex is located in these areas and the capability of forest damage is very high. As a result of validation using a prediction rate curve, a capability of prediction of urban area is $80\%$, agriculture area is $55\%$, forest area is $40\%$ in higher $10\%$ of possibility which the land-surface change would occur. This integration model is unsatisfactory to Predict the forest area in the study area and thus as a future work, it is necessary to apply new thematic maps or prediction models In conclusion, we can expect that this way can be one of the most essential land-surface change studies in a few years.

• Journal of Navigation and Port Research
• /
• v.39 no.3
• /
• pp.149-156
• /
• 2015

The Dynamic Positioning System consists of 7 elements which are namely Power system, Human machine interface, DP Computer, Position Reference System(PRS), Sensors, Thruster system and DP Operator. Incidents like loss of position(LOP) on DP vessel usually occur due to errors in these 7 elements. The purpose of this study is to find out safety operation method of DP vessel through qualitative and quantitative analyze of DP LOP incidents which are submitted to IMCA every year. The 612 DP LOP incidents submitted from 2001 to 2010 were analyzed to find out the main cause of the incidents and its rate among other causes. Consequently, the highest rate of incidents involving DP elements are PRS errors. DP computer, Power system, Human error and thruster system came next. The PRS has been analyzed and a flowchart was drawn through expert brainstorming. Also, the conditional probability has been analyzed through Bayesian Networks based on this flowchart. Consequentially, the main causes of drive off incidents were DGPS, microwave radar and HPR. Also, this study identified the main causes of DGPS errors through Bayesian Networks. These causes are signal blocked, electric components failure, relative mode error, signal weak or fail.

• The KIPS Transactions:PartB
• /
• v.8B no.5
• /
• pp.455-462
• /
• 2001

The World Wide Web has become one of the major services provided through Internet. When searching the vast web space, users use bookmarking facilities to record the sites of interests encountered during the course of navigation. One of the typical problems arising from bookmarking is that the list of bookmarks lose coherent organization when the the becomes too lengthy, thus ceasing to function as a practical finding aid. In order to maintain the bookmark file in an efficient, organized manner, the user has to classify all the bookmarks newly added to the file, and update the folders. This paper introduces our learning agent called BClassifier that automatically classifies bookmarks by analyzing the contents of the corresponding web documents. The chief source for the training examples are the bookmarks already classified into several bookmark folders according to their subject by the user. Additionally, the web pages found under top categories of Yahoo site are collected and included in the training examples for diversifying the subject categories to be represented, and the training examples for these categories as well. Our agent employs naive Bayesian learning method that is a well-tested, probability-based categorizing technique. In this paper, the outcome of some experimentation is also outlined and evaluated. A comparison of naive Bayesian learning method alongside other learning methods such as k-Nearest Neighbor and TFIDF is also presented.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.26 no.1
• /
• pp.132-144
• /
• 2023

Recently, the frequency and intensity of heat waves due to the increase in climate change temperature are increasing. Therefore, this study tried to compare the evaluation process and evaluation results of the heat wave disaster evaluation, which is the government's analysis of the heat wave disaster vulnerability and the risk evaluation method recently emphasized by the IPCC. The analysis of climate change disaster vulnerability is evaluated based on manuals and guidelines prepared by the government. Risk evaluation can be evaluated as the product of the possibility of a disaster and its impact, and it is evaluated using the Markov chain Monte Carlo simulation based on Bayesian estimation method, which uses prior information to infer posterior probability. As a result of the analysis, the two evaluation results for Busan Metropolitan City differed slightly in the spatial distribution of areas vulnerable to heat waves. In order to properly evaluate disaster vulnerable areas due to climate change, the process and results of climate change disaster vulnerability analysis and risk assessment must be reviewed, and consider each methodology and countermeasures must be prepared.

• Journal of Intelligence and Information Systems
• /
• v.14 no.2
• /
• pp.157-177
• /
• 2008

Even in a single day, an enormous amount of content including digital videos, posts, photographs, and wikis are generated on the web. It's getting more difficult to recommend to a user what he/she prefers among these contents because of the difficulty of automatically grasping of content's meanings. CF (Collaborative Filtering) is one of useful methods to recommend proper content to a user under these situations because the filtering process is only based on historical information about whether or not a target user has preferred an item before. Collaborative Tagging is the process that allows many users to annotate content with descriptive tags. Recommendation using tags can partially improve, such as the limitations of CF, the sparsity and cold-start problem. In this research, a CF method with user-created tags is proposed. Collaborative tagging is employed to grasp and filter users' preferences for items. Empirical demonstrations using real dataset from del.icio.us show that our algorithm obtains improved performance, compared with existing works.

• Journal of KIISE:Software and Applications
• /
• v.28 no.9
• /
• pp.681-687
• /
• 2001

In order to raise a class discrimination power by combining multiple classifiers under the Bayesian decision theory, the upper bound of a Bayes error rate bounded by the conditional entropy of a class variable and decision variables obtained from training data samples should be minimized. Wang and Wong proposed a tree dependence first-order approximation scheme of a high order probability distribution composed of the class and multiple feature pattern variables for minimizing the upper bound of the Bayes error rate. This paper presents an extended high order product approximation scheme dealing with higher order dependency more than the first-order tree dependence, based on the minimization of the upper bound of the Bayes error rate. Multiple recognizers for unconstrained handwritten numerals from CENPARMI were combined by the proposed approximation scheme using the Bayesian formalism, and the high recognition rates were obtained by them.

• Journal of KIISE:Computing Practices and Letters
• /
• v.14 no.9
• /
• pp.906-910
• /
• 2008

As the mobile environment becomes widely used, there is a growth on the concern about recognizing and sharing user context. Sharing context makes the interaction between human more plentiful as well as helps to keep a good social relationship. Recently, it has been applied to some messengers or mobile applications with sharing simple contexts, but it is still required to recognize and share more complex and diverse contexts. In this paper, we propose a context-aware messenger that collects various sensory information, recognizes representative user contexts such as emotion, stress, and activity by using dynamic Bayesian networks, and visualizes them. It includes a modular model that is effective to recognize various contexts and displays them in the form of icons. We have verified the proposed method with the scenario evaluation and usability test.

• Journal of The Korean Association of Information Education
• /
• v.5 no.2
• /
• pp.279-287
• /
• 2001

In this paper, we have defined and designed the structure of standardized XML content for supplying efficient e-Learning contents. We have also implemented the prototype of XML contents generator to create the educational contents easily. In addition, we have suggested the contents searching method using Case Base Reasoning and Bayesian belief network to supply XML contents suitable to learners request. The existing e-Learning system based on HTML could not customize and standardize, but XML contents can be reused and made an intelligent learning by supplying an adaptive content according to learners level. For evaluating the efficiency of designed XML content, we make the standard XML content for learning JAVA program in e-Learning system as well as discussing about the integrity and expanding the educational content. Finally, we have shown the architecture and effectiveness of the knowledge-based XML contents retrieval manager.