• The Transactions of the Korea Information Processing Society
• /
• v.6 no.6
• /
• pp.1458-1467
• /
• 1999

Existing index structures such as extendable hashing and B+-tree do not support partial string searches perfectly. The inverted file method and the signature file method that are used in the web retrieval engine also have problems that they do not provide partial string searches and suffer from serious retrieval performance degradation respectively. In this paper, we propose an efficient index method that supports partial string searches and achieves good retrieval performance. The proposed index method is based on the Inverted file structure. It constructs the index file with patterns that result from dividing terms by two syllables to support partial string searches. We analyze the characteristics of our proposed method through simulation experiments using wide range of parameter values. We analyze the derive analytic performance evaluation models of the existing inverted file method, signature file method and the proposed index method in terms of retrieval time and storage overhead. We show through performance comparison based on analytic models that the proposed method significantly improves retrieval performance over the existing method.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.53 no.12
• /
• pp.637-644
• /
• 2004

This paper proposes an expert system with the knowledge learning capability which can enhance the safety and effectiveness of substation operation in the automated substation as well as existing substation by inferring multiple events such as main transformer fault, busbar fault and main transformer work schedule under multiple inference mode and multiple objective mode and by considering totally the switch status and the main transformer operating constraints. Especially inference mode includes the local minimum tree search method and pattern recognition method to enhance the performance of real-time bus reconfiguration strategy. The inference engine of the expert system consists of intuitive inferencing part and logical inferencing part. The intuitive inferencing part offers the control strategy corresponding to the event which is most similar to the real event by searching based on a minimum distance classification method of pattern recognition methods. On the other hand, logical inferencing part makes real-time control strategy using real-time mode(best-first search method) when the intuitive inferencing is failed. Also, it builds up a knowledge base or appends a new knowledge to the knowledge base using pattern learning function. The expert system has main transformer fault, main transformer maintenance work and bus fault processing function. It is implemented as computer language, Visual C++ which has a dynamic programming function for implementing of inference engine and a MFC function for implementing of MMI. Finally, it's accuracy and effectiveness is proved by several event simulation works for a typical substation.

• Journal of Internet Computing and Services
• /
• v.10 no.4
• /
• pp.161-176
• /
• 2009

As the Internet has been growing, WWW(World Wide Web) based services were popularized and users using the service were increased excessively. To support these environments, a processing of many transactions became an essential consideration. There are many researches regarding the user profiling on web services to support those transactions effectively. Most of them are just for grasping the comsumer's preferences. However, a trend of recent web service is not limited what they are doing between consumers and providers; a consumer can become a provider and also a provider can become a consumer virtual open environments such as open market on the internet. For this reason, it is necessary to inspect a preference of consumers as well as providers one. In this paper, we proposed personal preference tree(PPT) reflecting the preferences for providers and implemented the module applying to the web service, and evaluated the applicability the personal preference module through a simulation.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.10
• /
• pp.5260-5275
• /
• 2019

In the process of constructing the traditional offensive and defensive game theory model, these are some shortages for considering the dynamic change of security risk problem. By analysing the critical indicators of the incomplete information game theory model, incomplete information attack and defense game theory model and the mathematical engineering method for solving Bayes-Nash equilibrium, the risk-averse income function for information assets is summarized as the problem of maximising the return of the equilibrium point. To obtain the functional relationship between the optimal strategy combination of the offense and defense and the information asset security probability and risk probability. At the same time, the offensive and defensive examples are used to visually analyse and demonstrate the incomplete information game and the Harsanyi conversion method. First, the incomplete information game and the Harsanyi conversion problem is discussed through the attack and defense examples and using the game tree. Then the strategy expression of incomplete information static game and the engineering mathematics method of Bayes-Nash equilibrium are given. After that, it focuses on the offensive and defensive game problem of unsafe information network based on risk aversion. The problem of attack and defense is obtained by the issue of maximizing utility, and then the Bayes-Nash equilibrium of offense and defense game is carried out around the security risk of assets. Finally, the application model in network security penetration and defense is analyzed by designing a simulation example of attack and defense penetration. The analysis results show that the constructed income function model is feasible and practical.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.35 no.2A
• /
• pp.112-120
• /
• 2010

In this paper, we propose semi-ML adaptive parallel QRDM (APQRDM) and iterative QRDM (AIQRDM) algorithms based on set grouping. Using the set grouping, the tree-search stage of QRDM algorithm is divided into partial detection phases (PDP). Therefore, when the treesearch stage of QRDM is divided into 4 PDPs, the APQRDM latency is one fourth of that of the QRDM, and the hardware requirements of AIQRDM is approximately one fourth of that of QRDM. Moreover, simulation results show that in $4{\times}4$ system and at Eb/N0 of 12 dB, APQRDM decreases the average computational complexity to approximately 43% of that of the conventional QRDM. Also, at Eb/N0 of 0dB, AIQRDM reduces the computational complexity to about 54% and the average number of metric comparisons to approximately 10% of those required by the conventional QRDM and AQRDM.

• The Journal of Society for e-Business Studies
• /
• v.17 no.2
• /
• pp.149-163
• /
• 2012

Logistics systems provide their service to customers by coordinating the resources with limited capacity throughout the underlying processes involved to each other. To maintain the high level of service under such complicated condition, it is essential to carry out the real-time monitoring and continuous management of logistics processes. In this study, we propose a method of estimating the service completion time of key processes based on process-state information collected in real time. We first identify the factors that influence the process completion time by modeling and analyzing an influence diagram, and then suggest algorithms for quantifying the factors. We suppose the container terminal logistics and the process of discharging and loading containers to a vessel. The remaining service time of a vessel is estimated using a decision tree which is the result of machine-learning using historical data. We validated the estimation model using container terminal simulation. The proposed model is expected to improve competitiveness of logistics systems by forecasting service completion in real time, as well as to prevent the waste of resources.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.6
• /
• pp.85-94
• /
• 2015

In this paper, an enhanced QoS multicast routing scheduling scheme is proposed to adapt to a dynamic mobile traffic condition for wireless mesh networks (WMNs). It handles the network QoS by controlling the delay constraints for multimedia applications. The group size will be controlled according to both the current network state and QoS requirements. The dynamic reconstruction of QoS multicast tree can be obtained from preprocessing with both the partial multicast routing scheme and the traffic estimation. Performance evaluation of the proposed scheme is carried out on randomly generated graph derived from the wireless mesh network, by choosing the optimal value related to the appropriate delay bounds. Simulation results show that the proposed scheme can improve the performance of QoS multicast routing for WMNs.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.20 no.10
• /
• pp.1887-1894
• /
• 2016

In the RFID system, the reader transmits a query message to tags in order to identify a unique ID of tags within its detection range. The procedures for arbitrating a collision is essential because the multiple tags can response simultaneously in the same to the query of the Reader. This procedure is known as conflict resolution algorithm and it is a key technology in the RFID system. In this paper, we proposed a variable bits M-ary QT algorithm based on Manchester coding techniques. The proposed algorithm use the location information of the collision bits in the reader and tags. The proposed algorithm can reduce the number of the query-response cycle because it is capable of recognizing discontinuous bits and a variable number of bits. From computer simulation, the proposed method give better performance than the conventional M-ary QT techniques in terms of response, recognition efficiency, communication overhead.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.19 no.12
• /
• pp.2364-2375
• /
• 1994

For the efficient recognition of printed Korean characters, a multiplexed minimum average correlation energy(MMACE) filter is proposed. Proposed method solved the disadvantages of the tree structure algorithm which recognition system is very huge and recognition method is sophisticated. Using only one consonant MMACE filter and one vowel one, we recognized the full Korean character. Each MMACE filter is multiplexed by 4 K-tuple MACE filters which are synthesized by 24 consonants and vowels. Hence the proposed MMACE filter and the correlation distribution plane are divided by 4 subregion. We obtained the binary codes for the Korean character recognition from each correlation distribution subplane. And the obtained codes are compared with the truth table for consonants and vowels in computer. We can recognize the full Korean characters when substitute the corresponded consonant or vowel font of the consistent code to the correlation peak place in the output correlation plane. The computer simulation and optical experiment results show that the proposed compact Korean character recognition system using the MMACE filters has high discrimination capability.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.35 no.9B
• /
• pp.1295-1304
• /
• 2010

This paper proposes a fault-tolerant data aggregation which provides energy efficient and reliable data collection in wireless sensor networks. The traditional aggregation scheme does not provide the countermeasure to packet loss or the countermeasure scheme requires a large amount of energy. The proposed scheme applies caching and re-transmission based on the track topology to the adaptive timeout scheduling. The proposed scheme uses a single-path routing based on the traditional tree topology at normal, which reduces the dissipated energy in sensor nodes without any countermeasure against packet loss. The proposed scheme, however, retransmits the lost packet using track topology under event occurrences in order to fulfill more accurate data aggregation. Extensive simulation work under various workloads has revealed that the proposed scheme decrease by 8% in terms of the dissipated energy and enhances data accuracy 41% when the potential of event occurrence exists as compared with TAG data aggregation. And the proposed scheme decrease by 53% in terms of the dissipated energy and shows a similar performance in data accuracy when the potential of event occurrence exists as compared with PERLA data aggregation.