• Journal of Korea Spatial Information System Society
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• v.11 no.1
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• pp.127-136
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• 2009

This paper proposes an on-line mining algorithm of moving trajectory patterns in RFID data streams considering changing characteristics over time and constraints of single-pass data scan. Since RFID, sensor, and mobile network technology have been rapidly developed, many researchers have been recently focused on the study of real-time data gathering from real-world and mining the useful patterns from them. Previous researches for sequential patterns or moving trajectory patterns based on stream data have an extremely time-consum ing problem because of multi-pass database scan and tree traversal, and they also did not consider the time-changing characteristics of stream data. The proposed method preserves the sequential strength of 2-lengths frequent patterns in binary relationship table using the time-evolving graph to exactly reflect changes of RFID data stream from time to time. In addition, in order to solve the problem of the repetitive data scans, the proposed algorithm infers candidate k-lengths moving trajectory patterns beforehand at a time point t, and then extracts the patterns after screening the candidate patterns by only one-pass at a time point t+1. Through the experiment, the proposed method shows the superior performance in respect of time and space complexity than the Apriori-like method according as the reduction ratio of candidate sets is about 7 percent.

• Journal of Korean Society of Transportation
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• v.25 no.6
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• pp.99-109
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• 2007

There have been few studies on the impacts of independent recurrent and non-recurrent congestion on freeway networks. The main reason is due partly to the lack of traffic data collected during those periods of recurrent and non-recurrent congestion and partly to the difficulty of using the simulation tools effectively. This study has suggested a methodology to analyze the independent impacts of the recurrent and non-recurrent congestion on target freeway segments. The proposed methodology is based on an elaborately calibrated simulation analysis, using real traffic data obtained during the recurrent and non-recurrent congestion periods. This paper has also summarized the evaluation results from the field tests of two ITS technologies, which were developed to provide drivers with real-time traffic information under traffic congestion. As a result, their accuracy may not be guaranteed during the transition periods such as the non-recurrent congestion. In summary, this study has been focused on the importance of non-recurrent congestion compared to recurrent congestion, and the proposed methodology is expected to provide a basic foundation for prioritizing limited government investments for improving freeway network performance degraded by recurrent or non-recurrent congestion.

• International Commerce and Information Review
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• v.13 no.3
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• pp.229-248
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• 2011

The increasing complexity of business and social settings bas lead to innovation becoming a strategic imperative. The need for innovation in the quest for competitive advantage also means that firms must be dynamic and flexible. This is often achieved through collaborative arrangements such as strategic alliances or strategic network Many organizations form alliances by leveraging their resources to gain access to the partner's skills and capabilities; ultimately to enhance innovation and performance. We demonstrate empirically that the "chain of innovation" is central to the process of innovation in global alliances. This chain comprises the creativity and learning processes and knowledge stock in alliances. Our empirical analysis is based on a survey of alliances that resulted in 114 responses. For management, this research bas significant potential in guiding attention to the chain of innovation, to better manage the overall process of innovation in alliances. Our work shows that more effective creativity and learning processes and a greater knowledge stock lead to a more effective alliance innovation process. Managers therefore, need to concentrate on creating environments wherein the processes of creativity and learning are fostered, increasing the alliance knowledge stock and in turn, increasing innovative output via an effective innovation process.

• Journal of Intelligence and Information Systems
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• v.13 no.3
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• pp.17-29
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• 2007

Inference engine that performs the brain of software agent in next generation's web with various standards based on standard language of the web, XML has to understand SWRL (Semantic Web Rule Language) that is a language to express the rule in the Semantic Web. In this research, we want to develop a forward inference engine, SMART-F (SeMantic web Agent Reasoning Tools-Forward chaining inference engine) that uses SWRL as a rule express method, and OWL as a fact express method. In the traditional inference field, the Rete algorithm that improves effectiveness of forward rule inference by converting if-then rules to network structure is often used for forward inference. To apply this to the Semantic Web, we analyze the required functions for the SWRL-based forward inference, and design the forward inference algorithm that reflects required functions of next generation's Semantic Web deducted by Rete algorithm. And then, to secure each platform's independence and portability in the ubiquitous environment and overcome the gap of performance, we developed management tool of fact and rule base and forward inference engine. This is compatible with fact and rule base of SMART-B that was developed. So, this maximizes a practical use of knowledge in the next generation's Web environment.

• Journal of Intelligence and Information Systems
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• v.13 no.3
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• pp.119-140
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• 2007

Recommender systems enable a user to decide which information is interesting and valuable in our world of information overload. As the recent studies of distributed computing environment have been progressing actively, recommender systems, most of which were centralized, have changed toward a peer-to-peer approach. Collaborative Filtering (CF), one of the most successful technologies in recommender systems, presents several limitations, namely sparsity, scalability, cold start, and the shilling problem, in spite of its popularity. The move from centralized systems to distributed approaches can partially improve the issues; distrust of recommendation and abuses of personal information. However, distributed systems can be vulnerable to attackers, who may inject biased profiles to force systems to adapt their objectives. In this paper, we consider both effective CF in P2P environment in order to improve overall performance of system and efficient solution of the problems related to abuses of personal data and attacks of malicious users. To deal with these issues, we propose a multi-agent framework for a distributed CF focusing on the trust relationships between individuals, i.e. web of trust. We employ an agent-based approach to improve the efficiency of distributed computing and propagate trust information among users with effect. The experimental evaluation shows that the proposed method brings significant improvement in terms of the distributed computing of similarity model building and the robustness of system against malicious attacks. Finally, we are planning to study trust propagation mechanisms by taking trust decay problem into consideration.

• Journal of KIISE:Information Networking
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• v.36 no.1
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• pp.34-42
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• 2009

In this paper, we propose a practical hybrid transport error control scheme to provide SVC video streaming service over error-prone IP networks. Many error control mechanisms for various video coding standards have been proposed in the literature. However, there is little research result which can be practically applicable to the multilayered coding structure of SVC(the scalable extension of H.264/AVC). We present a new hybrid transport error control scheme that efficiently combines layered Forward Error Correction(FEC) and Automatic Repeat Request(ARQ) for better packet-loss resilience. In the proposed hybrid error control, we adopt ACK-based ARQ instead of NACK-based ARQ to maximize throughput which is the amount of effective data packets delivered over a physical link per time unit. In order to prove the effectiveness of the proposed hybrid error control scheme, we adopt NIST-Net network emulator which is a general-purpose tool for emulating performance dynamics in IP networks. It is shown by simulations over the NIST-Net that the proposed hybrid error control scheme shows improved packet-loss resilience even with much less number of overhead packets compared to various conventional error control schemes.

• Journal of KIISE:Information Networking
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• v.35 no.3
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• pp.192-206
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• 2008

Multihop is the main communication style for wireless sensor networks composed of tiny sensor nodes. Until now, most applications have treated the periodic small sized sensing data. Recently, the burst traffic with the transient and continuous nature is increasingly introduced due to the advent of wireless multimedia sensor networks. Therefore, the efficient communication protocol to support this trend is required. In this paper, we propose a novel PIGAB(Packet Interval Gap based on Adaptive Backoff) protocol to efficiently transmit the burst data in multihop wireless sensor networks. The contention-based PIGAB protocol consists of the PIG(Packet Interval Gap) control algorithm in the source node and the MF(MAC-level Forwarding) algorithm in the relay node. The PIGAB is on basis of the newly proposed AB(Adaptive Backoff), CAB(Collision Avoidance Backoff), and UB(Uniform Backoff). These innovative algorithms and schemes can achieve the performance of network by adjusting the gap of every packet interval, recognizing the packet transmission of the hidden node. Through the simulations and experiments, we identify that the proposed PIGAB protocol considerably has the stable throughput and low latency in transmitting the burst data in multihop wireless sensor networks.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.4
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• pp.593-607
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• 2013

The In-Vehicle-Networking(IVN) of modern cars is constituted by an small electronic control device called ECU. In the past, there was no way to be able to access the IVN of a driving car. so IVN has been recognized as a closed environment so there is no need to exist authentication protocol between devices which are to configure the internal network and to communicate with other devices. However, constant improvements made it possible to access the IVN in many different ways as the communication technology evolves. This possibility created a need for device authentication in IVN. HB-Family are representative authentication schemes in RFID environment which has similar restrictions to IVN. In this paper, we propose an implementation method of HB-Family for device authentication between ECU considering ECU has low computing power and the message field of CAN protocol has restricted size of 8 bytes. In order to evaluate the efficiency and availability of the authentication schemes adopted our method, we have evaluated the performance based on DSP-28335 device. Further, it was possible to improve the efficiency rate of at lest 10%, up to 36%, and we then analyze this result in various aspects of the IVN.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.3
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• pp.99-106
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• 2018

In the process of acquiring information through the cyber ISR (Intelligence Surveillance Reconnaissance) and research into the agent to help decision-making, periodic communication between the C&C (Command and Control) server and the agent may not be possible. In this case, we have studied how to effectively surveillance and reconnaissance. Due to the network configuration, agents planted on infiltrated computers can not communicate seamlessly with C&C servers. In this case, the agent continues to collect data continuously, and in order to analyze the collected data within a short time in When communication is possible with the C&C server, it can utilize limited resources and time to continue its mission without being discovered. This research shows the superiority of incremental learning method over batch method through experiments. At an experiment with the restricted memory of 500 mega bytes, incremental learning method shows 10 times decrease in learning time. But at an experiment with the reuse of incorrectly classified data, the required time for relearn takes twice more.

• The KIPS Transactions:PartC
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• v.12C no.4 s.100
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• pp.571-580
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• 2005

In fast long-distance networks, TCP's congestion control algorithm has the problem of utilizing bandwidth effectively. Several window-based congestion control protocols for high-speed and large delay networks have been proposed to solve this problem. These protocols deliberate mainly three properties : scalability, TCP-friendliness, and RTT-fairness. These protocols, however, cannot satisfy above three properties at the same time because of the trade-off among them This paper presents a new window-based congestion control algorithm, called EM (Exponential Increase/ Multiplicative Decrease), that simultaneously supports all four properties including fast convergence, which is another important constraint for fast long-distance networks; it can support scalability by increasing congestion window exponentially proportional to the time elapsed since a packet loss; it can support RTT-fairness and TCP-friendliness by considering RTT in its response function; it can support last fair-share convergence by increasing congestion window inversely proportional to the congestion window just before packet loss. We evaluate the performance of EIMD and other algorithms by extensive computer simulations.