• The Korean Journal of Applied Statistics
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• v.25 no.6
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• pp.877-887
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• 2012

The Bank of Korea changed its method of GDP estimation from a fixed-weighted to a chain-weighted measure in 2009. The fixed-weighted method had had problems such as substitution bias and the rewriting of economic history. As a result of the change, annual growth rates calculated using the chain-weighted method from 1970 through 2008 turned out to be 0.8%p higher on average than the existing rates. The quarterly average chain-weighted growth rates were 0.19%p higher than the fixed-weighted ones, but they changed in the same directions. In this paper we analyze whether the differences in rates between the two calculation methods would bring about a difference in the cyclical characteristics of GDP. We conclude that although there were differences in growth rates after introduction of the chain-weighted method, there was no difference in the cyclical fluctuation.

• Korean Journal of Construction Engineering and Management
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• v.16 no.2
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• pp.46-53
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• 2015

Electrical construction cost index is composed of the cost of albor and material. The producer price index is used to the cost of material. The Bank of Korea restructured the formation method and the basic period of the producer price index in 2013. Because fixed-weighted method can't faithfully reflect industrial structure changes. The weighted value and price index of fixed-weighted method is fixed on the basicp eriod. Electrical construction cost index is changed from fixed-weighted method to chain-weighted method in september 2014, because of these on the need. But the change of organization in formation method changes the weighted value. So there is the need of analysis about the statistical continuity of electrical construction cost index. This study is focused on the time series analysis between fixed-weighted and chain-weighted electrical construction cost index. We uses unit root test, cointegration test, regression analysis of long and short term equation, fitness for the estimation of static forecast as time series analysis. We verify that chain-weighted electrical construction cost index can be replaced to fixed-weighted construction cost index accounting analyses result. So users of it recognize that chain-weighted electrical construction cost index has statistical continuity.

• Korean Journal of Construction Engineering and Management
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• v.15 no.5
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• pp.49-60
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• 2014

Electrical construction cost index has been applied fixed-weighted method. But fixed-weighted method can't faithfully reflect industrial structure changes. Because the weighted value and price index of fixed-weighted method is fixed on the basic period. Electrical construction cost index is composed of the cost of labor and material. So it fluctuates sharply whenever the construction association of korea announces the laborer's wage of electrical construction. And it depends on only the producer price index changes that is related to electrical construction since then. So a study is focused on developing electrical construction cost index applied chain-weighted method. Because chain-weighted method can reflect the realities of the electrical construction and alleviate the sudden changes of labor cost with link index. We verify that chain-weighted method relieves the step states of electrical construction cost index applied fixed-weighted method.

• Genomics & Informatics
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• v.14 no.4
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• pp.173-180
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• 2016

The meta-analysis has become a widely used tool for many applications in bioinformatics, including genome-wide association studies. A commonly used approach for meta-analysis is the fixed effects model approach, for which there are two popular methods: the inverse variance-weighted average method and weighted sum of z-scores method. Although previous studies have shown that the two methods perform similarly, their characteristics and their relationship have not been thoroughly investigated. In this paper, we investigate the optimal characteristics of the two methods and show the connection between the two methods. We demonstrate that the each method is optimized for a unique goal, which gives us insight into the optimal weights for the weighted sum of z-scores method. We examine the connection between the two methods both analytically and empirically and show that their resulting statistics become equivalent under certain assumptions. Finally, we apply both methods to the Wellcome Trust Case Control Consortium data and demonstrate that the two methods can give distinct results in certain study designs.

• Structural Engineering and Mechanics
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• v.37 no.4
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• pp.351-365
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• 2011

This study proposes an inverse estimation method for the input forces of a fixed beam structural system. The estimator includes the fuzzy Kalman Filter (FKF) technology and the fuzzy weighted recursive least square method (FWRLSM). In the estimation method, the effective estimator are accelerated and weighted by the fuzzy accelerating and weighting factors proposed based on the fuzzy logic inference system. By directly synthesizing the robust filter technology with the estimator, this study presents an efficient robust forgetting zone, which is capable of providing a reasonable trade-off between the tracking capability and the flexibility against noises. The period input of the fixed beam structure system can be effectively estimated by using this method to promote the reliability of the dynamic performance analysis. The simulation results are compared by alternating between the constant and adaptive and fuzzy weighting factors. The results demonstrate that the application of the presented method to the fixed beam structure system is successful.

• The KIPS Transactions:PartA
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• v.10A no.3
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• pp.225-230
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• 2003

In this paper, we develope algorithms that distribute the load on the heterogeneously clustered web system, The response time based on the concurrent user is examined for the suggested algorithms. Simulation experience shows that the response time using the dynamically weighted methods seems to have a good results compare to that with the fixed weighted methods. And, also the effectiveness of clustered system becomes better as long as the number of concurrent user increases.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1407-1423
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• 2020

A graph is a data structure consisting of nodes and edges between these nodes. Graph embedding is to generate a low dimensional vector for a given graph that best represents the characteristics of the graph. Recently, there have been studies on graph embedding, especially using deep learning techniques. However, until now, most deep learning-based graph embedding techniques have focused on unweighted graphs. Therefore, in this paper, we propose a graph embedding technique for weighted graphs based on long short-term memory (LSTM) autoencoders. Given weighted graphs, we traverse each graph to extract node-weight sequences from the graph. Each node-weight sequence represents a path in the graph consisting of nodes and the weights between these nodes. We then train an LSTM autoencoder on the extracted node-weight sequences and encode each nodeweight sequence into a fixed-length vector using the trained LSTM autoencoder. Finally, for each graph, we collect the encoding vectors obtained from the graph and combine them to generate the final embedding vector for the graph. These embedding vectors can be used to classify weighted graphs or to search for similar weighted graphs. The experiments on synthetic and real datasets show that the proposed method is effective in measuring the similarity between weighted graphs.

• The KIPS Transactions:PartD
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• v.15D no.3
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• pp.399-410
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• 2008

This paper suggests a new retrieval method using weighted vector sum to resolve a problem of traditional location-based retrieval method, nearest neighbor (NN) query, and NN query using direction. The proposed method filters out data with the radius, and then the remained retrieval area is filtered by a direction information compounded of a user's moving direction, a pre-fixed interesting direction, and a pre-fixed retrieval angle. The moving direction is computed from a vector or a weighted vector sum of several vectors using a weight to adopt several cases. The retrieval angle can be set from traditional $360^{\circ}$ to any degree you want. The retrieval data for this method can be a still and moving image recorded shooting location, and also several type of media like text, web, picture offering to customer with location of company or resort. The suggested method guarantees more accurate retrieval than traditional location-based retrieval methods because that the method selects data within the radius and then removes data of useless areas like passed areas or an area of different direction. Moreover, this method is more flexible and includes the direction based NN.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.420-423
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• 2015

This paper proposes a method of non-linearity error detection and calibration for binary-weighted charge-driven DACs. In general, the non-linearity errors of DACs often occur due to the mismatch of layout designs or process variation, even when careful layout design methods and process calibration are adopted. Since such errors can substantially degrade the SNDR performance of DAC, it is crucial to accurately measure the errors and calibrate the design mismatches. The proposed method employs 2 identical DAC circuits. The 2 DACs are sweeped, respectively, by using 2 digital input counters with a fixed difference. A comparator identifies any non-linearity errors larger than an acceptable discrepancy. We also propose a calibration method that can fine-tune the DAC's capacitor sizes iteratively until the comparator finds no further errors. Simulations are presented, which show that the proposed method is effective to detect the non-linearity errors and calibrate the capacitor mismatches of a 12-bit DAC design of binary-weighted charge-driven structure.

• Journal of the Korean Data and Information Science Society
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• v.25 no.2
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• pp.423-429
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• 2014

This paper discusses a method for getting Type I sums of squares by projections under a two-way fixed-effects model when variances of errors are not equal. The method of weighted least squares is used to estimate the parameters of the assumed model. The model is fitted to the data in a sequential manner by using the model comparison technique. The vector space generated by the model matrix can be composed of orthogonal vector subspaces spanned by submatrices consisting of column vectors related to the parameters. It is discussed how to get the Type I sums of squares by using the projections into the orthogonal vector subspaces.