• Journal of KIISE:Databases
• /
• v.34 no.6
• /
• pp.518-527
• /
• 2007

It is an important issue to find out the difference between RDF documents, because RDF documents are changed frequently. When RDF documents contain blank nodes, we need a matching technique for blank nodes in the change detection. Blank nodes have a nested form and they are used in most RDF documents. A RDF document can be modeled as a graph and it will contain many subtrees. We can consider a change detection problem as a minimum cost tree matching problem. In this paper, we propose a change detection technique for RDF documents using the labeling scheme for blank nodes. We also propose a method for improving the efficiency of general triple matching, which used predicate grouping and partitioning. In experiments, we showed that our approach was more accurate and faster than the previous approaches.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.6
• /
• pp.785-791
• /
• 2021

In this paper, we propose a methodology for estimating the optimal traversable destination from the location-based information of the object recognized by the mobile robot to perform the object delivery service. The location estimation process is to apply the generalized Voronoi graph to the grid map to create an initial topology map composed of nodes and links, recognize objects and extract location data using RGB-D sensors, and collect the shape and distance information of obstacles. Then, by applying the hybrid approach that combines the center of gravity and thinning method, the optimal moving position for the service robot to perform the task of grabbing is estimated. And then, the optimal node information for the robot's work destination is updated by comparing the geometric distance between the estimated position and the existing node according to the node update rule.

• Journal of Intelligence and Information Systems
• /
• v.27 no.4
• /
• pp.73-95
• /
• 2021

This study uses Node2vec graph embedding method and Light GBM link prediction to explore undeveloped export candidate countries in Korea's food and beverage industry. Node2vec is the method that improves the limit of the structural equivalence representation of the network, which is known to be relatively weak compared to the existing link prediction method based on the number of common neighbors of the network. Therefore, the method is known to show excellent performance in both community detection and structural equivalence of the network. The vector value obtained by embedding the network in this way operates under the condition of a constant length from an arbitrarily designated starting point node. Therefore, it has the advantage that it is easy to apply the sequence of nodes as an input value to the model for downstream tasks such as Logistic Regression, Support Vector Machine, and Random Forest. Based on these features of the Node2vec graph embedding method, this study applied the above method to the international trade information of the Korean food and beverage industry. Through this, we intend to contribute to creating the effect of extensive margin diversification in Korea in the global value chain relationship of the industry. The optimal predictive model derived from the results of this study recorded a precision of 0.95 and a recall of 0.79, and an F1 score of 0.86, showing excellent performance. This performance was shown to be superior to that of the binary classifier based on Logistic Regression set as the baseline model. In the baseline model, a precision of 0.95 and a recall of 0.73 were recorded, and an F1 score of 0.83 was recorded. In addition, the light GBM-based optimal prediction model derived from this study showed superior performance than the link prediction model of previous studies, which is set as a benchmarking model in this study. The predictive model of the previous study recorded only a recall rate of 0.75, but the proposed model of this study showed better performance which recall rate is 0.79. The difference in the performance of the prediction results between benchmarking model and this study model is due to the model learning strategy. In this study, groups were classified by the trade value scale, and prediction models were trained differently for these groups. Specific methods are (1) a method of randomly masking and learning a model for all trades without setting specific conditions for trade value, (2) arbitrarily masking a part of the trades with an average trade value or higher and using the model method, and (3) a method of arbitrarily masking some of the trades with the top 25% or higher trade value and learning the model. As a result of the experiment, it was confirmed that the performance of the model trained by randomly masking some of the trades with the above-average trade value in this method was the best and appeared stably. It was found that most of the results of potential export candidates for Korea derived through the above model appeared appropriate through additional investigation. Combining the above, this study could suggest the practical utility of the link prediction method applying Node2vec and Light GBM. In addition, useful implications could be derived for weight update strategies that can perform better link prediction while training the model. On the other hand, this study also has policy utility because it is applied to trade transactions that have not been performed much in the research related to link prediction based on graph embedding. The results of this study support a rapid response to changes in the global value chain such as the recent US-China trade conflict or Japan's export regulations, and I think that it has sufficient usefulness as a tool for policy decision-making.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.46 no.8
• /
• pp.22-30
• /
• 2009

Due to high levels of integration and complexity, the Network-on-Chip (NoC) approach has emerged as a new design paradigm to overcome on-chip communication issues and data bandwidth limits in conventional SoC(System-on-Chip) design. In particular, exponentially growing of energy consumption caused by high frequency, synchronization and distributing a single global clock signal throughout the chip have become major design bottlenecks. To deal with these issues, a globally asynchronous, locally synchronous (GALS) design combined with low power techniques is considered. Such a design style fits nicely with the concept of voltage-frequency-islands (VFI) which has been recently introduced for achieving fine-grain system-level power management. In this paper, we propose an efficient design methodology that minimizes energy consumption by VFI partitioning on an NoC architecture as well as assigning supply and threshold voltage levels to each VFI. The proposed algorithm which find VFI and appropriate core (or processing element) supply voltage consists of traffic-aware core graph partitioning, communication contention delay-aware tile mapping, power variation-aware core dynamic voltage scaling (DVS), power efficient VFI merging and voltage update on the VFIs Simulation results show that average 10.3% improvement in energy consumption compared to other existing works.

• Journal of KIISE:Computer Systems and Theory
• /
• v.34 no.11
• /
• pp.589-598
• /
• 2007

In the group communication which has multiple data streams and various access privileges, it is necessary to provide group access control. The group members having the same access privilege are classified into one class, and the classes form a hierarchy based on the access relations. Then each class is assigned to a secret key. In the previous schemes, a single logical key graph is constructed from the hierarchy and each member always holds all secret keys of the classes he can access in the proactive manner. Thus, higher-privileged members hold more keys then lower-privileged members. However, if the hierarchy is large, each member manages too many keys and the size of multicast message in rekeying increases in proportion to the size of the hierarchy. Moreover, most of the members access a small portion of multiple data streams simultaneously. Therefore, it is redundant to receive rekeying message and update the keys in which he is not currently interested. In this paper, we present a new key management scheme that takes a reactive approach in which each member obtains the key of a data stream only when he wants to access the stream. Each member holds and updates only the key of the class he belongs. If he wants to get the key of other class, he derives it from his key and the public parameter. Proposed scheme considerable reduces the costs for rekeying, especially in the group where access relations are very complex and the hierarchy is large. Moreover, the scheme has another advantage that it easily reflects the change of access relations.

• Journal of the Korean Society for Marine Environment & Energy
• /
• v.8 no.1
• /
• pp.46-52
• /
• 2005

A marine environmental information system (MEIS) useful for optimal route planning of ships running in the ocean was developed. Utilizing the simulated marine environmental data produced by the European Center for Medium-Range Weather Forecasts based on global environmental data observed by satellites, the real-time forecast and long-term statistics of marine environments around planned and probable ship routes are provided. The MEIS consists of a land-based data acquisition and analysis system(MEIS-Center) and a onboard information display system(MEIS-Ship) for graphic description of marine information and optimal route planning of ships. Also, it uses of satellite communication system for data transfer. The marine environmental components of winds, waves, air pressures and storms are provided, in which winds are described by speed and direction and waves are expressed in terms of height, direction and period for both of wind waves and swells. The real-time information is characterized by 0.5° resolution, 10 day forecast in 6 hour interval and daily update. The statistic information of monthly average and maximum value expected for a return period is featured by 1.5° resolution and based on 15 year database. The MEIS-Ship include an editing tool for route simulation and the forecasting and statistic information on planned routes can be displayed in graph or table. The MEIS enables for navigators to design an optimal navigational route that minimizes probable risk and operational cost.