• The KIPS Transactions:PartA
• /
• v.12A no.1 s.91
• /
• pp.23-30
• /
• 2005

Causal order of message delivery algorithm ensures that every transmitted message is delivered in causal order. It should be noted that control information should be transmitted with each message in order to enforce causal order. Hence, it is important to reduce this communication overhead because the impact of the overhead increases proportionally with the number of related processes. In this paper we propose and evaluate effective a ${\Delta}-causal$ order algorithm for multimedia data which have real-time property. To reduce transmission overhead, proposed algorithm eliminates redundant information as early as possible which is not explicitly required for preserving causal order. Average communication overhead of our algorithm is much smaller than other existing algorithms.

• Journal of KIISE:Computer Systems and Theory
• /
• v.27 no.2
• /
• pp.149-159
• /
• 2000

In this paper, we propose a new class of MIN (Multistage Interconnection Network) called SCMIN(ShortCut MIN) which can form a cheap and efficient packet switching interconnection network. SCMIN satisfies full access capability(FAC) and has multiple redundant paths between processor-memory pairs even though SCMIN is constructed with 2.5N-4 SEs which is far fewer SEs than that of MINs. SCMIN can be constructed suitable for localized communication by providing the shortcut path and multiple paths inside the processor-memory cluster which has frequent data communications. Therefore, SCMIN can be used as an attractive interconnection network for parallel applications with a localized communication pattern in shared-memory multiprocessor systems.

• Proceedings of the Korean Society for Bioinformatics Conference
• /
• 2003.10a
• /
• pp.133-138
• /
• 2003

The prediction of protein secondary structure has been an important bioinformatics tool that is an essential component of the template-based protein tertiary structure prediction process. It has been known that the predicted secondary structure information improves both the fold recognition performance and the alignment accuracy. In this paper, we describe several novel ideas that may improve the prediction accuracy. The main idea is motivated by an observation that the protein's structural information, especially when it is combined with the evolutionary information, significantly improves the accuracy of the predicted tertiary structure. From the non-redundant set of protein structures, we derive the 'potential' parameters for the protein secondary structure prediction that contains the structural information of proteins, by following the procedure similar to the way to derive the directional information table of GOR method. Those potential parameters are combined with the frequency matrices obtained by running PSI-BLAST to construct the feature vectors that are used to train the support vector machines (SVM) to build the secondary structure classifiers. Moreover, the problem of huge model file size, which is one of the known shortcomings of SVM, is partially overcome by reducing the size of training data by filtering out the redundancy not only at the protein level but also at the feature vector level. A preliminary result measured by the average three-state prediction accuracy is encouraging.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.66 no.8
• /
• pp.1187-1194
• /
• 2017

After North American wide area black out on August 14, 2003, various studies have been conducted to find out the reason of the disaster. One of main reasons was misoperation of generator protection system. Since then, protective coordination between generator protection system and excitation system controls has been hot issue among electrical engineers. Among various generator protection relays, in this paper, we focused on generator overvoltage and overexcitation relay, which protect the over-flux condition of the generator. Thus, at first, we modeled the generator overvoltage, overexcitation relay and detailed power system including excitation system, governor and etc., based on actual field data. And then, we reviewed the protective coordination of generator overvoltage and overexcitation relay using electromagnetic transient program. In addition, we discussed the protective coordination method for redundant protection relays in both automatic voltage regulator and generator side.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.22 no.3
• /
• pp.37-58
• /
• 1997

An AI approach with tabu search is designed to solve multi-level knapsack problems. The approach performs intelligent actions with memories of historic data and learning effect. These action are developed ont only by observing the attributes of the optimal solution, the solution space, and its corresponding path to the optimal, but also by applying human intelligence, experience, and intuition with respect to the search strategies. The approach intensifies, or diversifies the search process appropriately in time and space. In order to create a good neighborhood structure, this approach uses two powerful choice rules that emphasize the impact of candidate variables on the current solution with respect to their profit contribution. "Pseudo moves", similar to "aspirations", support these choice rules during the evaluation process. For the purpose of visiting as many relevant points as possible, strategic oscillation between feasible and infeasible solutions around the boundary is applied. To avoid redundant moves, short-term (tabu-lists), intemediate-term (cycle-detection), and long-term (recording frequency and significant solutions for diversfication) memories are used. Test results show that among the 45 generated problems (these problems pose significant or insurmountable challenges to exact methods) the approach produces the optimal solutions in 39 cases.lutions in 39 cases.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1996.04a
• /
• pp.514-517
• /
• 1996

In solving multi-level knapsack problems, conventional heuristic approaches often assume a short-sighted plan within a static decision enviornment to find a near optimal solution. These conventional approaches are inflexible, and lack the ability to adapt to different problem structures. This research approaches the problem from a totally different viewpoint, and a new method is designed and implemented. This method performs intelligent actions based on memories of historic data and learning. These actions are developed not only by observing the attributes of the optimal solution, the solution space, and its corresponding path to the optimal solution, but also by applying human intelligence, experience, and intuition with respect to the search strategies. The method intensifies, or diversifies the search process appropriately in time and space. In order to create a good neighborhood structure, this method uses two powerful choice rules that emphasize the impact of candidate variables on the current solution with respect to their profit contribution. A side effect of so-called "pseudo moves", similar to "aspirations", supports these choice rules during the evaluation process. For the purpose of visiting as many relevant points as possible, strategic oscillation between feasible and infeasible solutions around the boundary is applied for intensification. To avoid redundant moves, short-term (tabu-lists), intermediate-term (cycle detection), and long-term (recording frequency and significant solutions for diversification) memories are used. Test results show that among the 45 generated problems (these problems pose significant or insurmountable challenges to exact methods) the approach produces the optimal solutions in 39 cases.lutions in 39 cases.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.12 no.6
• /
• pp.43-48
• /
• 2012

In As the proliferation of wireless LAN and smart devices like smart phone, the importance of the wireless Internet local broadcasting service is increasing. In order to provide broadcasting data for the multiple devices, one-way roadcasting technology which could not support re-transmission, should be used and the receiving frame error is major problem. Furthermore unlicense devices cause interference to the receiver, burst frame error tends to be happened. In this paper, new method to overcome the burst and random frame error is proposed and the effect is analyzed.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.8 no.5
• /
• pp.13-19
• /
• 2008

A mobile ad-hoc network routing protocols for transmission of multimedia contents need to have low delay time and to maintain the established route because it should secure quality of service(QoS) of the network. In this paper, the proposed protocol, termed HODMRP (History-based On-Demand Multicast Routing Protocol), is enhanced On-Demand Multicast Routing Protocol (ODMRP) by adding the criterion which is the session history for establishing route. The characteristic of this protocol is that data can be transmitted using the redundant route which is already selected by session history, if it occurs that the route is broken, HODMRP have better Packet Delivery Ratio (PDR) value and lower delay time than ODMRP by the simulation results.

• Proceedings of the KIEE Conference
• /
• 1995.11a
• /
• pp.175-177
• /
• 1995

The sensor signal validation and failure detection system must be able to detect, isolate, and identify sensor degradation as well as provide a reconstruction of the measurements. In this study, this is accomplished by combining the neural network, the Generalized Consistency Checking(GCC), and the Sequential Probability Ratio Test(SPRT) method in a decision estimator module. The GCC method is a computationally efficient system for redundant sensors, while the SPRT provides the ability to make decisions based on the degradation history of a sensor. The methodology is also extended to the detection of noise degradation. The acceptability of the proposed method is demonstration by using the simulation data in safety injection accident of nuclear power plants. The results show that the signal validation and sensor failure detection system is able to detect and isolate a bias failure and noise type failures under transient conditions. And also, the system is able to provide the validated signal by reconstructing the measurement signals in the failure conditions considered.

• BMB Reports
• /
• v.46 no.8
• /
• pp.416-421
• /
• 2013

Genome-wide association studies (GWAS) have become popular as an approach for the identification of large numbers of phenotype-associated variants. However, differences in genetic architecture and environmental factors mean that the effect of variants can vary across populations. Understanding population genetic diversity is valuable for the investigation of possible population specific and independent effects of variants. EvoSNP-DB aims to provide information regarding genetic diversity among East Asian populations, including Chinese, Japanese, and Korean. Non-redundant SNPs (1.6 million) were genotyped in 54 Korean trios (162 samples) and were compared with 4 million SNPs from HapMap phase II populations. EvoSNP-DB provides two user interfaces for data query and visualization, and integrates scores of genetic diversity (Fst and VarLD) at the level of SNPs, genes, and chromosome regions. EvoSNP-DB is a web-based application that allows users to navigate and visualize measurements of population genetic differences in an interactive manner, and is available online at [http://biomi.cdc.go.kr/EvoSNP/].