• The KIPS Transactions:PartB
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• v.15B no.6
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• pp.561-574
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• 2008

The spot detection phase of the 2-DE image analysis program segments a gel image into spot regions by an image segmentation algorithm and fits the spot regions to a spot shape model and quantifies the spot informations for the next phases. Currently the watershed algorithm is generally used as the segmentation algorithm and there are the Gaussian model and the diffusion model for the shape model. The diffusion model is closer to real spot shapes than the Gaussian model however spots have very various shapes and especially an asymmetric formation in x-coordinate and y-coordinate. The reason for asymmetric formation of spots is known that a protein could not be diffused completely because the 2-DE could not be processed under the ideal environment usually. Accordingly we propose an asymmetric diffusion model in this paper. The asymmetric diffusion model assumes that a protein spot is diffused from a disc at initial time of diffusing process, but is diffused asymmetrically for x-axis and y-axis respectively as time goes on. In experiments we processed spot matching for 19 gel images by using three models respectively and evaluated averages of SNR for comparing three models. As averages of SNR we got 14.22dB for the Gaussian model, 20.72dB for the diffusion model and 22.85dB for the asymmetric diffusion model. By experimental results we could confirm the asymmetric diffusion model is more efficient and more adequate for spot matching than the Gaussian model and the diffusion model.

• The KIPS Transactions:PartB
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• v.15B no.6
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• pp.575-584
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• 2008

According to the network condition, the communication network overload could be occurred when media transmitting. Many researches are being carried out to lessen the network overload, such as the filtering, load distributing, frame dropping and many other methods. Among these methods, one of effective method is frame dropping that reduces specified video frames for bandwidth diminution. B frames are dropped and then I, P frames are dropped according to dependency among the frames in frame dropping. This paper proposes a scheme for protecting copyrights by encryption, when we apply frame dropping to reduce bandwidth of media following MPEG-4 file format. We designed two kinds of frame dropping: first one stores and then sends the dropped files and the other drops frames in real-time when transmitting. We designed three kinds of encryption methods in which DES algorithm is used to encrypt MPEG-4 data: macro block encryption in I-VOP, macro block and motion vector encryption in P-VOP, and macro block and motion vector encryption in I, P-VOP. Based on these three methods, we implemented a digital right management solution for MPEG-4 data streaming. We compared the results of dropping, encryption, decryption and quality of video sequences to select an optimal method, and there is no noticeable difference between the video sequences recovered after frame dropping and the ones recovered without frame dropping. The best performance in encryption and decryption of frames was obtained when we apply the macro block and motion vector encryption in I, P-VOP.

• The KIPS Transactions:PartD
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• v.15D no.4
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• pp.513-522
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• 2008

Service-Oriented Architecture(SOA) is an method to develop applications by developing and publishing reusable services which potentially be used in various applications, and discovering and composing right services dynamically. SOA adopts a paradigm of publish-discover-invoke, which is considerably different from object-oriented and component-based development(CBD) approaches. The service in SOA is different from function in procedural programming, object in object-oriented programming, and component in CBD, and its fundamental requirement is a high level of reusability and applicability. In SOA, service providers and service consumers are loosely coupled since the providers try to develop reusable services and the consumers try to locate right services without knowing much about the providers and their published services. Moreover, the process of searching, choosing and invoking right services is not presented in conventional programming paradigms. Therefore, conventional approaches to developing user interfaces and invoking the functionality on servers through JSP, and RMI in object-oriented programming cannot well be applicable to designing clients’ programs in SOA. Therefore, there is a high demand for a practical and systematic process for developing clients’ applications, and the such a process should be devised by considering key characteristics of services and SOA. However, little work on this area is known to date, and there has not a process for client side just except few guide lines for developing service client. In this paper, we propose a practical and systematic development process for developing clients' applications in SOA. Then, we define instructions for carrying out each activity in the process. To show the applicability of the proposed work, we show the result of applying our process in developing a services application for searching and booking hotels.

• The KIPS Transactions:PartD
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• v.15D no.4
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• pp.485-494
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• 2008

Huge amounts of various web items such as keywords, images, and web pages are being made widely available on the Web. The popularities of such web items continuously change over time, and mining temporal patterns in popularities of web items is an important problem that is useful for several web applications. For example, the temporal patterns in popularities of search keywords help web search enterprises predict future popular keywords, enabling them to make price decisions when marketing search keywords to advertisers. However, presence of millions of web items makes it difficult to scale up previous techniques for this problem. This paper proposes an efficient method for mining temporal patterns in popularities of web items. We treat the popularities of web items as time-series, and propose gapmeasure to quantify the similarity between the popularities of two web items. To reduce the computation overhead for this measure, an efficient method using the Fast Fourier Transform (FFT) is presented. We assume that the popularities of web items are not necessarily following any probabilistic distribution or periodic. For finding clusters of web items with similar popularity trends, we propose to use a density-based clustering algorithm based on the gap measure. Our experiments using the popularity trends of search keywords obtained from the Google Trends web site illustrate the scalability and usefulness of the proposed approach in real-world applications.

• The KIPS Transactions:PartA
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• v.15A no.2
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• pp.125-134
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• 2008

We implemented a system being able to suggest example sentences for multiple choice tests, considering the level of students. To build the system, we designed an automatic method for sentence generation, which made it possible to control the difficulty degree of questions. For the proper evaluation in the multiple choice tests, proper size of question pools is required. To satisfy this requirement, a system which can generate various and numerous questions and their example sentences in a fast way should be used. In this paper, we designed an automatic generation method using a linguistic resource called WordNet. For the automatic generation, firstly, we extracted keywords from the existing sentences with the morphological analysis and candidate terms with similar meaning to the keywords in Korean WordNet space are suggested. When suggesting candidate terms, we transformed the existing Korean WordNet scheme into a new scheme to construct the concept similarity matrix. The similarity degree between concepts can be ranged from 0, representing synonyms relationships, to 9, representing non-connected relationships. By using the degree, we can control the difficulty degree of newly generated questions. We used two methods for evaluating semantic similarity between two concepts. The first one is considering only the distance between two concepts and the second one additionally considers positions of two concepts in the Korean Wordnet space. With these methods, we can build a system which can help the instructors generate new questions and their example sentences with various contents and difficulty degree from existing sentences more easily.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.1
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• pp.19-30
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• 2014

For the expansion of the Semantic Web, studies in converting the data stored in the relational database into the ontology are actively in process. Such studies mainly use an RDB to RDF mapping model, the model to map relational database components to RDF components. However, pre-proposed mapping models have got different expression modes and these damage the accessibility and reusability of the users. As a consequence, the necessity of the standardized mapping language was raised and the W3C suggested the R2RML as the standard mapping language for the RDB to RDF model. The R2RML has a characteristic that converts only the relational database schema data to RDF. For the same reasons above, the ontology about the relation data between table name and column name of the relational database cannot be added. In this paper, we propose an RDB to RDF mapping system considering semantic relations of RDB components in order to solve the above issue. The proposed system generates the mapping data by adding the RDFS attribute data into the schema data defined by the R2RML in the relational database. This mapping data converts the data stored in the relational database into RDF which includes the RDFS attribute data. In this paper, we implement the proposed system as a Java-based prototype, perform the experiment which converts the data stored in the relational database into RDF for the comparison evaluation purpose and compare the results against D2RQ, RDBToOnto and Morph. The proposed system expresses semantic relations which has richer converted ontology than any other studies and shows the best performance in data conversion time.

• The KIPS Transactions:PartD
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• v.17D no.2
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• pp.129-146
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• 2010

Nowadays, XML has been favored by many companies internally and externally as a means of sharing and distributing data. there are many researches and systems for modeling and storing XML documents by an object-oriented method as for the method of saving and managing web-based multimedia document more easily. The representative tool for the object-oriented modeling of XML documents is UML (Unified Modeling Language). UML at the beginning was used as the integrated methodology for software development, but now it is used more frequently as the modeling language of various objects. Currently, UML supports various diagrams for object-oriented analysis and design like class diagram and is widely used as a tool of creating various database schema and object-oriented codes from them. This paper proposes an Efficinet Query Modelling of XML-GL using the UML class diagram and OCL for searching XML document which its application scope is widely extended due to the increased use of WWW and its flexible and open nature. In order to accomplish this, we propose the modeling rules and algorithm that map XML-GL. which has the modeling function for XML document and DTD and the graphical query function about that. In order to describe precisely about the constraint of model component, it is defined by OCL (Object Constraint Language). By using proposed technique creates a query for the XML document of holding various properties of object-oriented model by modeling the XML-GL query from XML document, XML DTD, and XML query while using the class diagram of UML. By converting, saving and managing XML document visually into the object-oriented graphic data model, user can prepare the base that can express the search and query on XML document intuitively and visually. As compared to existing XML-based query languages, it has various object-oriented characteristics and uses the UML notation that is widely used as object modeling tool. Hence, user can construct graphical and intuitive queries on XML-based web document without learning a new query language. By using the same modeling tool, UML class diagram on XML document content, query syntax and semantics, it allows consistently performing all the processes such as searching and saving XML document from/to object-oriented database.

• The KIPS Transactions:PartD
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• v.16D no.6
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• pp.851-858
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• 2009

Mobbing is not restricted to problem of young people but the bigger recent problem occurs in workspaces. According to reports of ILO and domestic case mobbing in the workplace is increasing more and more numerically from 9.1%('03) to 30.7%('08). These mobbing brings personal and social losses. The proposed algorithm makes it possible to grasp not only current mobbing victims but also potential mobbing victims through user profile and contribute to efficient personnel management. This paper extracts user profile related to mobbing, in a way of selecting seven factors and fifty attributes that are related to this matter. Next, expressing extracting factors as '1' if they are related me or not '0'. And apply similarity function to attributes summation included in factors to calculate similarity between the users. Third, calculate optimizing weight choosing factors included attributes by applying neural network algorithm of SPSS Clementine and through this summation Mobbing-Value(MV) can be calculated . Finally by mapping MV of online social network users to G2 mobbing propensity classification model(4 Groups; Ideal Group of the online social network, Bullies, Aggressive victims, Victims) which is designed in this paper, can grasp mobbing propensity of users, which will contribute to efficient personnel management.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.9
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• pp.279-292
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• 2014

Energy aware server cluster aims to reduce power consumption at maximum while keeping QoS(quality of service) as much as energy non-aware server cluster. In the existing methods of energy aware server cluster, they calculate the minimum number of active servers needed to handle current user requests and control server power mode in a fixed time interval to make only the needed servers ON. When loads change rapidly, QoS of the existing methods become degraded because they cannot increase the number of active servers so quickly. To solve this QoS problem, we classify load change situations into five types of rapid growth, growth, normal, decline, and rapid decline, and apply five different thresholds respectively in calculating the number of active servers. Also, we use a flexible scheme to adjust the above classification criterion for multi threshold, considering not only load change but also the remaining capacity of servers to handle user requests. We performed experiments with a cluster of 15 servers. A special benchmarking tool called SPECweb was used to generate load patterns with rapid change. Experimental results showed that QoS of the proposed method is improved up to the level of energy non-aware server cluster and power consumption is reduced up to about 50 percent, depending on the load pattern.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.9
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• pp.361-368
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• 2014

The LPR(License plate recognition) system has been developed to efficient control for complex traffic environment and currently be used in many places. However, because of light, noise, background changes, environmental changes, damaged plate, it only works limited environment, so it is difficult to use in real-time. This paper presents a heuristic segmentation algorithm for robust to noise and illumination changes and introduce a real-time license plate recognition system using it. In first step, We detect the plate utilized Haar-like feature and Adaboost. This method is possible to rapid detection used integral image and cascade structure. Second step, we determine the type of license plate with adaptive histogram equalization, bilateral filtering for denoise and segment accurate character based on adaptive threshold, pixel projection and associated with the prior knowledge. The last step is character recognition that used histogram of oriented gradients (HOG) and multi-layer perceptron(MLP) for number recognition and support vector machine(SVM) for number and Korean character classifier respectively. The experimental results show license plate detection rate of 94.29%, license plate false alarm rate of 2.94%. In character segmentation method, character hit rate is 97.23% and character false alarm rate is 1.37%. And in character recognition, the average character recognition rate is 98.38%. Total average running time in our proposed method is 140ms. It is possible to be real-time system with efficiency and robustness.