• Journal of the Korea Society for Simulation
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• v.4 no.2
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• pp.61-68
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• 1995

The performance of event-driven logic simulation frequently used for VLSI design verification depends on the data structures for event queues. This paper improves the existing Timing Wheel as a data structure for an event queue. In case of the use of B+ tree, an efficient node degree is also presented based on the experiment results. A new Timing Wheel index structure, which eliminates the insertion and deletion overhead of B+ tree, is proposed and analyzed.

• Journal of KIISE:Databases
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• v.35 no.2
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• pp.169-181
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• 2008

Because moving objects usually move on spatial networks, efficient trajectory index structures are required to achieve good retrieval performance on their trajectories. However, there has been little research on trajectory index structures for spatial networks such as FNR-tree and MON-tree. But, because FNR-tree and MON-tree are stored by the unit of the moving object's segment, they can't support the whole moving objects' trajectory. In this paper, we propose an efficient trajectory index structure, named Trajectory of Moving objects on Network Tree(TMN Tree), for moving objects. For this, we divide moving object data into spatial and temporal attribute, and preserve moving objects' trajectory. Then, we design index structure which supports not only range query but trajectory query. In addition, we divide user queries into spatio-temporal area based trajectory query, similar-trajectory query, and k-nearest neighbor query. We propose query processing algorithms to support them. Finally, we show that our trajectory index structure outperforms existing tree structures like FNR-Tree and MON-Tree.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.04a
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• pp.203-206
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• 2009

Articulation Index(AI) is the one of the evaluating methods for the interior sound of the automobiles. The AI measures the articulation level of the sound in the vehicle cabin as passengers talk to another. In this study, the effects of AI were investigated according to the various structures of tire. As the structures of tire were changed, the road noise of the vehicle tire was measured using objective measurement. From this measurement data, the AI was calculated. The AI of front is larger than that of rear. Increasing the tread hardness of tire or decreasing the apex height the AI is improved.

• Proceedings of the Korea Concrete Institute Conference
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• 2008.04a
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• pp.541-544
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• 2008

Recently, a variety of researches has been carried out to estimate the reliability-based analysis and design method of concrete structures and is attracted by probabilistic-based durability analysis/method of concrete structures subjected to chloride containing environment using MCS (Monte Carlo Simulation). Probabilistic-based durability analysis/method was proposed by lots of researches, but there is the lack of data for degradation factors for the calculation of probability distribution. The reliability based durability analysis method represents that the service life and reliability index varies with the probability distribution and coefficient of variation of each factor. Therefore, in this paper, the importance of experiment data for the degradation factors is confirmed and the study of reliability index in RC structures under chloride attack environments is performed considering the variation coefficient of degradation factors.

• Wind and Structures
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• v.2 no.3
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• pp.133-150
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• 1999

Significant costs to the public and private sectors due to recent extreme wind events have motivated the need for systematic post-hurricane damage data collection and analysis. Current post disaster data are collected by many different interested groups such as government agencies, voluntary disaster relief agencies, representatives of media companies, academicians and companies in the private sector. Each group has an interest in a particular type of data. However, members of each group collect data using different techniques. This disparity in data is not conducive to quantifying damage data and, therefore, inhibits the statistical and spatial description of damage and comparisons of damage among different extreme wind events. The data collection does not allow comparisons of data or results of analyses within a group and also prohibits comparison of damage data and information among different groups. Typically, analyses of data from a given event lead to different conclusion depending upon the definition of damage used by individual investigators and the type of data collected making it difficult for members of groups to compare the results of their analyses with a common language and basis. A formal method of data collection and analysis-within any single group-would allow comparisons to be made among different individuals, hazardous events and eventually among different groups, thus facilitating the management and reduction of damage due to future disaster. This research introduces a definition of damage to single family dwellings, and a common method of data collection and analysis suited for groups interested in regional characterization of damage. The current state-of-data is presented and a method for data collection is recommended based on these existing data collection methods. A fixed-scale damage index is proposed to consider the damage to a dwelling's feature. Finally, the damage index is applied to three dwellings damaged by Hurricane Iniki (1992). The damage index reflects the reduced functionality of a structure as a single family detached dwelling and provides a means to evaluate regional damage due to a single event or to compare damage due to events of different severity. Evaluation of the damage index and the data available support recommendation for future data collection efforts.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.8
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• pp.319-326
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• 2007

To perform fast searching in massive data such as DNA strings, the most efficient method is to construct full-text index data structures of given strings. The widely used full-text index structures are suffix trees and suffix arrays. Since the suffix may uses less space than the suffix tree, the suffix array is proper for DNA strings. Previously developed construction algorithms of suffix arrays are not suitable for DNA strings since those are designed for integer alphabets. We propose a fast algorithm to construct suffix arrays on DNA strings whose alphabet sizes are fixed by 4. We reduce the construction time by improving encoding and merging steps on Kim et al.[1]'s algorithm. Experimental results show that our algorithm constructs suffix arrays on DNA strings 1.3-1.6 times faster than Kim et al.'s algorithm, and also for other algorithms in most cases.

• Korean Journal of Child Studies
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• v.37 no.6
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• pp.107-117
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• 2016

Objective: This study examined the construct validity of K-WPPSI-IV. Factor structures of the structures of the K-WPPSI-IV full scale as well as primary index scales for two age ranges (2 years, 6 months to 3 years, 11 months; 4 years to 7 years, 7 months) were examined. Methods: Data were collected from 1,700 children aged 2 years, 6 months to 7 years, 7 months during the K-WPPSI-IV standardization. Confirmatory factor analyses were conducted using the K-WPPSI-IV subtest performances with maximum likelihood estimation using Amos 18. Results: First, the three-factor model (verbal comprehension, visual spatial, and working memory) fitted best for the younger age range. However, the five-factor model (verbal comprehension, visual spatial, fluid reasoning, working memory, and processing speed) fitted best for the older age range. Residuals suggest the presence of two nested subfactors within the verbal comprehension factor (broad/expressive and focused/simple). Second, the confirmatory factor analysis on primary index subtests identified factors that account for the intercorrelations among the reduced sets of primary index subtests. Conclusion: The findings showed that the theoretical structures of WPPSI-IV subtests were confirmed within K-WPPSI-IV.

• Structural Engineering and Mechanics
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• v.17 no.3_4
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• pp.331-346
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• 2004

A new sensor system is proposed for measuring damage indexes. The damage index is a physical value that is well correlated to a critical damage in a device or a structure. The mechanism proposed here utilizes elastic buckling of a thin wire and does not require any external power supply for memorizing the index. The mechanisms to detect peak strain, peak displacement, peak acceleration and cumulative deformation as examples of damage indexes are presented. Furthermore, passive and active wireless data retrieval mechanisms using electromagnetic induction are proposed. The passive wireless system is achieved by forming a closed LC circuit to oscillate at its natural frequency. The active wireless sensor can transmit the data much further than the passive system at the sacrifice of slightly complicated electric circuit for the sensor. For wireless data retrieval, no wire is needed for the sensor to supply electrical power. For the active system, electrical power is supplied to the sensor by radio waves emitted from the retrieval system. Thus, external power supply is only needed for the retrieval system when the retrieval becomes necessary. Theoretical and experimental studies to show excellent performance of the proposed sensor are presented. Finally, a prototype damage index sensor installed into a 7 storey base-isolated building is explained.

• Smart Structures and Systems
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• v.34 no.1
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• pp.9-15
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• 2024

Oversampling algorithms are methods employed in the field of machine learning to address the constraints associated with data quantity. This study aimed to explore the variations in reliability as data volume is progressively increased through the use of oversampling algorithms. For this purpose, the synthetic minority oversampling technique (SMOTE) and the borderline synthetic minority oversampling technique (BSMOTE) are chosen. The data inputs, which included air temperature, humidity, and wind speed, are parameters used in the Fosberg Fire-Weather Index (FFWI). Starting with a base of 52 entries, new data sets are generated by incrementally increasing the data volume by 10% up to a total increase of 100%. This augmented data is then utilized to predict FFWI using a deep neural network. The coefficient of determination (R²) is calculated for predictions made with both the original and the augmented datasets. Suggesting that increasing data volume by more than 50% of the original dataset quantity yields more reliable outcomes. This study introduces a methodology to alleviate the challenge of establishing a standard for data augmentation when employing oversampling algorithms, as well as a means to assess reliability.

• The KIPS Transactions:PartD
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• v.15D no.1
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• pp.23-30
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• 2008

The basic research of context aware in ubiquitous environment is an internet technique and XML. The XML data of continuous stream type are popular in network application through the internet. And also there are researches related to query processing for streaming XML data. As a basic research to efficiently query, we propose not only a labeled ordered tree model representing the XML but also a mining method to extract frequent structures from streaming XML data. That is, XML data to continuously be input are modeled by a stream tree which is called by XFP_tree and we exactly extract the frequent structures from the XFP_tree of current window to mine recent data. The proposed method can be applied to the basis of the query processing and index method for XML stream data.