• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.1393-1396
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• 2011

서비스기반 아키텍쳐 (SOA)는 웹기반의 표준화된 인터페이스 및 데이터 교환을 통하여 다양한 기능을 지원하기 위하여 유연성있는 비즈니스 시스템의 통합이 간편하다는 장점을 가지고 있어 현재 많은 IT 시스템에서 사용되고 있다. 하지만 기본적으로 SOA 는 call-and-return 방식으로 구현되어 있어 소프트웨어 개발 프로세스과 같이 시스템 또는 시스템 참여자간의 복잡한 상호작용이 수반되는 프로세스를 지원하는 시스템을 구축하기에는 한계를 보이고 있다. 따라서 개발 프로세스에 적용되는 시스템에서 복잡한 상호작용을 구현할 수 있는 SOA 기반 시스템이 필요하다고 판단된다. 우리는 이 논문에서 복잡한 상호작용을 지원할 수 있는 SOA 기반 프레임워크를 소개한다. SOA 기반 프레임워크에서 다양한 상호작용을 지원하기 위하여 우리는 semantic web 과 dialog act 이론을 사용하였으며 개발프로세스에 적용할 수 있는 ontology 를 개발, 사용함에 의하여 SOA 환경에서 다양한 메시지를 표현할 수 있도록 하였다. 또한 마지막으로 소프트웨어 개발 프로세스 사례연구를 통하여 우리의 접근방법의 타당성을 보인다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.3
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• pp.51-59
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• 2012

This paper suggests an efficient method which tracks articulated human body modeled with markov network using disparity map derived from stereo images. The conventional methods which only use color information to calculate likelihood for energy function tend to fail when background has same colors with objects or appearances of object are changed during the movement. In this paper, we present a method evaluating likelihood with both disparity information and color information to find human body parts. Since the human body part are cylinder projected to rectangles in 2D image plane, we use the properties of distribution of disparity of those rectangles that do not have discontinuous distribution. In addition to that we suggest a conditional-messages-update that is able to reduce unnecessary message update of belief propagation. Since the message update has comprised over 80% of the whole computation in belief propagation, the conditional-message-update yields 9~45% of improvements of computational time. Furthermore, we also propose an another speed up method called three dimensional dynamic models assumed the body motion is continuous. The experiment results show that the proposed method reduces the computational time as well as it increases tracking accuracy.

• The Journal of the Korea Contents Association
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• v.18 no.8
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• pp.544-560
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• 2018

Cause-Related Marketing is the process of formulating and implementing marketing activities that are characterized by an offer from the firm to contribute a specified amount to a designated cause when customers engage in revenue-providing exchanges that satisfy organizational and individual objectives. Many companies obtain benefits such as increasing sales profits and fulfilling social responsibility activities from Cause-Related Marketing as a strategic marketing activity. The purpose of this study is to analyze the effects of message of Cause-Related Marketing on consumer attitude, and to examine the moderating effects of ethical consumption propensity, social trust and types of product(utilitarian vs. hedonic) on consumer's product attitude. The research results show that consumers tend to adopt a positive attitude towards those advertisements with Cause-Related Marketing message. In the meanwhile, the ethical consumption propensity and social trust also have moderating effects on Cause-Related Marketing message's influence, but the types of product have no moderating effect. Based on the findings, the theoretical and managerial implication are discussed. In addition, some limitations of this study and future research directions are discussed.

• The KIPS Transactions:PartD
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• v.12D no.2 s.98
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• pp.259-266
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• 2005

Recently data centric routing or application dependent routing protocols are emerged in mobile ad hoc networks. In this paper, we propose a routing method for query processing in MANET(Mobile Ad hoc NETwork) environment, called road-based query routing, with consideration on real time traffic information of large number of vehicles. In particular, we focus on the method that process arrival time dependent shortest path query in MANET without a central server on the road networks. The main idea of our approach lies in a routing message that includes query predicates based on the road connectivity and on data gathering method in real time from vehicles on the road by ad-hoc network. We unify route discovery phase and data delivery(query processing) phase in our mechanism and reduce unnecessary flooding messages by pruning mobile nodes which are not on the same or neighboring road segments. In order to evaluate the performances of the proposed method, we established a model of road networks and mobile nodes which travel along the roads. The measurement factor is the number of nodes to whom route request is propagated according to each pruning strategy. Simulation result shows that road information is a dominant factor to reduce the number of messages.

• The Journal of the Korea Contents Association
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• v.10 no.3
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• pp.53-63
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• 2010

Recently, various monitoring systems are implemented actively by using wireless sensor networks(WSN). When implementing WSN-based monitoring system, there are three important issues to consider. At First, we need to consider a sensor node failure detection method to support the ongoing monitoring. Secondly, because sensor nodes use limited battery power, we need an efficient data filtering method to reduce energy consumption. At Last, a reducing processing overhead method is necessary. The existing Kalman filtering scheme has good performance on data filtering, but it causes too much processing overhead to estimate sensed data. To solve these problems, we, in this paper, propose a new data filtering scheme based on data statical analysis. First, the proposed scheme periodically aggregates node survival massages to support a node failure detection. Secondly, to reduce energy consumption, it sends the sample data with a node survival massage and do data filtering based on those messages. Finally, it analyzes the sample data to estimate filtering range in a server. As a result, each sensor node can use only simple compare operation for filtering data. In addition, we show from our performance analysis that the proposed scheme outperforms the Kalman filtering scheme in terms of the number of sending messages.

• KIISE Transactions on Computing Practices
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• v.23 no.1
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• pp.57-64
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• 2017

Short message service (SMS) is one of the most important communication methods for people who use mobile phones. However, illegal advertising spam messages exploit people because they can be used without the need for friend registration. Recently, spam message filtering systems that use machine learning have been developed, but they have some disadvantages such as requiring many calculations. In this paper, we implemented a spam message filtering system using the set-based POI search algorithm and sentence similarity without servers. This algorithm can judge whether the input query is a spam message or not using only letter composition without any server computing. Therefore, we can filter the spam message although the input text message has been intentionally modified. We added a specific preprocessing option which aims to enable spam filtering. Based on the experimental results, we observe that our spam message filtering system shows better performance than the original set-based POI search algorithm. We evaluate the proposed system through extensive simulation. According to the simulation results, the proposed system can filter the text message and show high accuracy performance against the text message which cannot be filtered by the 3 major telecom companies.

• Management & Information Systems Review
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• v.36 no.5
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• pp.195-222
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• 2017

Today's economy is becoming more and more convergence between different industries as the demarcation of the boundaries of all areas is leading to innovations such as mobile and social network services. So Fin-tech is a new technology that can combine the advantages of mobile and Internet with the technology revolution to easily handle financial and IT tasks. This Fin-tech is a compound word of finance and technology. The purpose of this study is to investigate the overall structural relationship between Fin-Tech use motivation (usefulness, enjoyment) on user attitude and word of mouth intention. In addition, we investigated how FinTech use motivation, user attitude, and word of mouth intention change according to innovation resistance tendency. And, we examined how the motivation, user attitude, and word of mouth intention of FinTech change according to the message type (rational and emotional). The main results of this study are as follows. First, the usefulness and enjoyment of motivation for using FinTech have a positive effect on user attitude, and user attitude also has a positive effect on word of mouse intention. Second, the relationship between FinTech use motivation, user attitude, and word of mouth intention was found to difference according to consumers' innovation resistance. Third, it was found that the relationship between FinTech use motivation, user attitude, and word of mouth intention differs according to type of message (rational, emotional). At the conclusion of the study, the summary of the research results, implications and limitations, and future research direction are described.

• Journal of KIISE:Databases
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• v.34 no.6
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• pp.473-482
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• 2007

Network-based IDS(Intrusion Detection System) gathers network packet data and analyzes them into attack or normal. They raise alarm when possible intrusion happens. But they often output a large amount of low-level of incomplete alert information. Consequently, a large amount of incomplete alert information that can be unmanageable and also be mixed with false alerts can prevent intrusion response systems and security administrator from adequately understanding and analyzing the state of network security, and initiating appropriate response in a timely fashion. So it is important for the security administrator to reduce the redundancy of alerts, integrate and correlate security alerts, construct attack scenarios and present high-level aggregated information. False alarm rate is the ratio between the number of normal connections that are incorrectly misclassified as attacks and the total number of normal connections. In this paper we propose a false alarm classification model to reduce the false alarm rate using classification analysis of data mining techniques. The proposed model can classify the alarms from the intrusion detection systems into false alert or true attack. Our approach is useful to reduce false alerts and to improve the detection rate of network-based intrusion detection systems.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.2
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• pp.73-86
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• 2009

This paper proposes a new data hiding scheme for binary image authentication with minimizing the distortion of host image. Based on the Hamming-Code-Based data embedding algorithm, the proposed scheme makes it possible to embed authentication information into host image with only flipping small number of pixels. To minimize visual distortion, the proposed scheme only modifies the values of the flippable pixels that are selected based on Yang et al's flippablity criteria. In addition to this, by randomly shuffling the bit-order of the authentication information to be embedded, only the designated receiver, who has the secret key that was used for data embedding, can extract the embedded data. To show the superiority of the proposed scheme, the two measurement metrics, the miss detection rate and the number of flipped pixels by data embedding, are used for the comparison analysis between the proposed scheme and the previous schemes. As a result of analysis, it has been shown that the proposed scheme flips smaller number of pixels than the previous schemes to embed the authentication information of the same bit-length. Moreover, it has been shown that the proposed scheme causes smaller visual distortion and more resilient against recent steg-analysis attacks than the previous schemes by the experimental results.

• Korean journal of communication and information
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• v.35
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• pp.250-291
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• 2006

This study examines the regulatory issues and introduction problems of TV-betting data broadcasts in Korea by in-depth interview with a panel group. TV-betting data broadcast services of card games and horse racing games are widely in use in Europe and other parts of the world. In order to carry out the study, a demo program of TV-betting data broadcast in the OCAP(OpenCableTM Application Platform Specification) system environment, which is the data broadcasting standard for digital cable broadcasts in Korea was exposed to the panel group and then they were interviewed after watching and using the program. The results could be summarized as below. First of all, while TV-betting data broadcasts have many elements of entertainment, the respondents thought that it would be difficult to introduce TV-betting in data broadcasts as in overseas countries largely due to social factors. In addition, in order to introduce TV-betting data broadcasts, they suggested that excessive speculativeness must be suppressed through a series of regulatory system devices, such as by guaranteeing credibility of the media based on safe security systems for transactions, scheduling programs with effective time constraints to prevent the games from running too frequently, limiting the betting values, and by prohibiting access to games through set-top boxes of other data broadcast subscribers. The general consensus was that TV-betting could be considered for gradual introduction within the governmental laws and regulations that would minimize its ill effects. Therefore, the government should formulate long-term regulations and policies for data broadcasts. Once the groundwork is laid for safe introduction of TV-betting on data broadcasts within the boundary of laws and regulations, interactive TV games are expected to be introduced in Korea not only for added functionality of entertainment but also for far-ranging development of data broadcast and new media industries.