• Journal of Information Processing Systems
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• v.15 no.3
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• pp.520-537
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• 2019

This paper proposes a system that can detect the data leakage pattern using a convolutional neural network based on defining the behaviors of leaking data. In this case, the leakage detection scenario of data leakage is composed of the patterns of occurrence of security logs by administration and related patterns between the security logs that are analyzed by association relationship analysis. This proposed system then detects whether the data is leaked through the convolutional neural network using an insider malicious behavior graph. Since each graph is drawn according to the leakage detection scenario of a data leakage, the system can identify the criminal insider along with the source of malicious behavior according to the results of the convolutional neural network. The results of the performance experiment using a virtual scenario show that even if a new malicious pattern that has not been previously defined is inputted into the data leakage detection system, it is possible to determine whether the data has been leaked. In addition, as compared with other data leakage detection systems, it can be seen that the proposed system is able to detect data leakage more flexibly.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1810-1814
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• 2008

A small L-type megasonic module for nano-pattern cleaning was designed and manufactured. The impedance graph of the quartz waveguide with a piezoelectric actuator was predicted using finite element method (FEM). The peak value of the piezoelectric actuator alone was 3.373 MHz, which was the same as the experimentally measured value of 3.373 MHz (0.0% error). In addition, the maximum impedance value of the quartz waveguide with the actuator was 3.373 MHz, which agreed well with the measured value of 3.362 MHz (0.3% error). The acoustic pressures of a conventional megasonic system (3 MHz) and the developed system under similar conditions were measured and compared. The results showed that the maximum values and standard deviations of the developed system decreased by 29% and 18%, respectively, compared with the conventional type. This suggests that the small L-type would have higher particle removal efficiency with lower possibilities of pattern damages.

• Journal of the Korean Society of Costume
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• v.15
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• pp.21-45
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• 1990

The purpose of this thesis is to study the method of the reasonable pattern design. The studying method is based on the original principle of the trousers' cutting and I have a hypothesis about the trousers pattern which should be proved. When I selected the practical method, I made use of the international measuring rule, graph paper and tracing paper, in order to prove the new pattern design. The reasonable pattern design should be the one of the suitable original principles to be suited in the design through any measurement. Therefore, I have discussed the above mentioned design. I find out the conclusion to prove the hypothesis of pattern design with the experimental measure after showing the above mentiond design. The characteristics is as follows. First : To be convinient when walking, because of little degree as folding of the front part of trousers with the under-angle. Second : To be suitable in proportion to the length of trousers and the under-angle. Third ; When folding the center line of the Sapok (a name of one of the trousers parts), the length of the Sapoks is same and harmonized with the Sapoks because of the same angle of both Sapoks in any case of the measurement. Fourth : No correction of the lines when dressing, for the same points of the large Sapok and the small one. Fifth : To be easiness of the pattern design through the concrete measurement. I could find out a little extent errors of pattern showings, an easiness of dressing, scientification of formation in Korean trousers and standard of the practical measurement in the program to be presented as the result of studying.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1748-1759
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• 2018

Weber Local Descriptor (WLD) is a stable and effective feature extraction algorithm, which is based on Weber's Law. It calculates the differential excitation information and direction information, and then integrates them to get the feature information of the image. However, WLD only considers the center pixel and its contrast with its surrounding pixels when calculating the differential excitation information. As a result, the illumination variation is relatively sensitive, and the selection of the neighbor area is rather small. This may make the whole information is divided into small pieces, thus, it is difficult to be recognized. In order to overcome this problem, this paper proposes Weber Symmetrical Local Graph Structure (WSLGS), which constructs the graph structure based on the $5{\times}5$ neighborhood. Then the information obtained is regarded as the differential excitation information. Finally, we demonstrate the effectiveness of our proposed method on the database of ORL, JAFFE and our own built database, high-definition infrared faces. The experimental results show that WSLGS provides higher recognition rate and shorter image processing time compared with traditional algorithms.

• Journal of KIISE:Databases
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• v.32 no.5
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• pp.498-508
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• 2005

A shape data is used one oi most important feature for image retrieval as data to reflect meaning of image. Especially, structural feature of shape is widely studied because it represents primitive properties of shape and relation information between basic units well. However, most structural features of shape have the problem that it is not able to guarantee an efficient search time because the features are expressed as graph or tree. In order to solve this problem, we generate curvature-based morphological graph, End design key to cluster shapes from this graph. Proposed this graph have contour features and morphological features of a shape. Shape retrieval is accomplished by stages. We reduce a search space through clustering, and determine total similarity value through pattern matching of external curvature. Various experiments show that our approach reduces computational complexity and retrieval cost.

• Journal of Korean Society of Water and Wastewater
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• v.28 no.6
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• pp.647-655
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• 2014

To perform long-term sewer monitoring, It is important to understand the nature of the wastewater flow that occurs at the point on early stage of the monitor and to prevent in advance a problem which may caused. We can infer the flow properties and external factors by analyzing the scatter graph obtained from the measured data flow rate monitoring data since an field external factor affecting the sewage flow is reflected in the flow rate monitoring data. In this study, Selecting the three points having various external factors, and we Inferred the sewer flow characteristics from depth-velocity scatter graph and determined the analysis equation for the dry-weather flow rate data. At the'point 1' expected non-pressure flow, we were able to see the drawdown effect caused by the free fall in the manhole section. At the'point 2', existed weir and sediments, there was backwater effect caused by them, and each of size calculated from the scatter graph analysis were 400 mm and 130 mm. At the'Point 3', there is specific flow pattern that is coming from flood wave propagation generated by the pump station at upstream. In common, adequate equations to explain the dry weather flow data are flume equation and modified manning equation(SS method), and the equations had compatibility for explaining the data because all of $R^2$ values are over 0.95.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1158-1167
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• 2017

Many real-world applications information are organized and represented with graph structure which is often used for representing various ubiquitous networks, such as World Wide Web, social networks, and protein-protein interactive networks. In particular, similarity evaluation between graphs is a challenging issue in many fields such as graph searching, pattern discovery, neuroscience, chemical compounds exploration and so forth. There exist some algorithms which are based on vertices or edges properties, are proposed for addressing this issue. However, these algorithms do not take both vertices and edges similarities into account. Towards this end, this paper pioneers a novel approach for similarity evaluation between graphs based on formal concept analysis. The feature of this approach is able to characterize the relationships between nodes and further reveal the similarity between graphs. Therefore, the highlight of our approach is to take vertices and edges into account simultaneously. The proposed algorithm is evaluated using a case study for validating the effectiveness of the proposed approach on detecting and measuring the similarity between graphs.

• The Journal of the Korea Contents Association
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• v.18 no.3
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• pp.70-80
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• 2018

Due to the recent development of social media and mobile devices, graph data have been using in various fields. In addition, caching techniques for reducing I/O costs in the process of large capacity graph data have been studied. In this paper, we propose a multi-layer caching scheme considering the connectivity of the graph, which is the characteristics of the graph topology, and the history of the past subgraph usage. The proposed scheme divides a cache into Used Data Cache and Prefetched Cache. The Used Data Cache maintains data by weights according to the frequently used sub-graph patterns. The Prefetched Cache maintains the neighbor data of the recently used data that are not used. In order to extract the graph patterns, their past history information is used. Since the frequently used sub-graphs have high probabilities to be reused, they are cached. It uses a strategy to replace new data with less likely data to be used if the memory is full. Through the performance evaluation, we prove that the proposed caching scheme is superior to the existing cache management scheme.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.233-238
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• 1993

In this paper, two diagnosis algorithms using the simple fuzzy, cognitive map (FCM) that is an useful qualitative model are proposed. The first basic algorithm is considered as a simple transition of Shiozaki's signed directed graph approach to FCM framework. And the second one is an extended version of the basic algorithm. In the extension, three important concepts, modified temporal associative memory (TAM) recall, temporal pattern matching algorithm and hierarchical decomposition are adopted. As the resultant diagnosis scheme takes short computation time, it can be used for on-line fault diagnosis of large scale and complex processes that conventional diagnosis methods cannot be applied. The diagnosis system can be trained by the basic algorithm and generates FCM model for every experienced process fault. In on-line application, the self-generated fault model FCM generates predicted pattern sequences, which are compared with observed pattern sequences to declare the origin of fault. In practical case, observed pattern sequences depend on transport time. So if predicted pattern sequences are different from observed ones, the time weighted FCM with transport delay can be used to generate predicted ones. The fault diagnosis procedure can be completed during the actual propagation since pattern sequences of tvo different faults do not coincide in general.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.161-177
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• 2019

In this paper, we study the performance improvement of the answer extraction in Question-Answering system by using sentence dependency parsing result. The Question-Answering (QA) system consists of query analysis, which is a method of analyzing the user's query, and answer extraction, which is a method to extract appropriate answers in the document. And various studies have been conducted on two methods. In order to improve the performance of answer extraction, it is necessary to accurately reflect the grammatical information of sentences. In Korean, because word order structure is free and omission of sentence components is frequent, dependency parsing is a good way to analyze Korean syntax. Therefore, in this study, we improved the performance of the answer extraction by adding the features generated by dependency parsing analysis to the inputs of the answer extraction model (Bidirectional LSTM-CRF). The process of generating the dependency graph embedding consists of the steps of generating the dependency graph from the dependency parsing result and learning the embedding of the graph. In this study, we compared the performance of the answer extraction model when inputting basic word features generated without the dependency parsing and the performance of the model when inputting the addition of the Eojeol tag feature and dependency graph embedding feature. Since dependency parsing is performed on a basic unit of an Eojeol, which is a component of sentences separated by a space, the tag information of the Eojeol can be obtained as a result of the dependency parsing. The Eojeol tag feature means the tag information of the Eojeol. The process of generating the dependency graph embedding consists of the steps of generating the dependency graph from the dependency parsing result and learning the embedding of the graph. From the dependency parsing result, a graph is generated from the Eojeol to the node, the dependency between the Eojeol to the edge, and the Eojeol tag to the node label. In this process, an undirected graph is generated or a directed graph is generated according to whether or not the dependency relation direction is considered. To obtain the embedding of the graph, we used Graph2Vec, which is a method of finding the embedding of the graph by the subgraphs constituting a graph. We can specify the maximum path length between nodes in the process of finding subgraphs of a graph. If the maximum path length between nodes is 1, graph embedding is generated only by direct dependency between Eojeol, and graph embedding is generated including indirect dependencies as the maximum path length between nodes becomes larger. In the experiment, the maximum path length between nodes is adjusted differently from 1 to 3 depending on whether direction of dependency is considered or not, and the performance of answer extraction is measured. Experimental results show that both Eojeol tag feature and dependency graph embedding feature improve the performance of answer extraction. In particular, considering the direction of the dependency relation and extracting the dependency graph generated with the maximum path length of 1 in the subgraph extraction process in Graph2Vec as the input of the model, the highest answer extraction performance was shown. As a result of these experiments, we concluded that it is better to take into account the direction of dependence and to consider only the direct connection rather than the indirect dependence between the words. The significance of this study is as follows. First, we improved the performance of answer extraction by adding features using dependency parsing results, taking into account the characteristics of Korean, which is free of word order structure and omission of sentence components. Second, we generated feature of dependency parsing result by learning - based graph embedding method without defining the pattern of dependency between Eojeol. Future research directions are as follows. In this study, the features generated as a result of the dependency parsing are applied only to the answer extraction model in order to grasp the meaning. However, in the future, if the performance is confirmed by applying the features to various natural language processing models such as sentiment analysis or name entity recognition, the validity of the features can be verified more accurately.