• Journal of the Korean Data and Information Science Society
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• v.19 no.3
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• pp.735-749
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• 2008

This article suggests application of logit model for analysis of multicategory responses. Referring to the reference category, characteristic of each category is obtained from analysis of polytomous logit model. With National Pension data it is illustrated that application of logit model helps it possible to find significant factors which may not be found only with polytomous logit model. Application of the logit model is done by reducing the number of categories. Categories are grouped into the former and the latter group according to reference category. Extra finding of significant factor was possible from logistic regression analysis for the two groups after removing the reference category. It is expected that this application would be helpful for finding information and characteristics on ordered multicategory responses where the proportional odds model does not fit.

• Journal of Environmental Impact Assessment
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• v.25 no.2
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• pp.124-140
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• 2016

Using the Korea Labor Institute Panel Study(KLIPS), this study investigates the impacts of water pollution on life satisfaction in Korea. Panel random-effects ordered probit model is used to consider the ordered property of life satisfaction data and heterogeneity of panel data. The proxy variables to reflect the degree of water pollution are biochemical oxygen demand(BOD) and total phosphorus(TP). In addition to the environmental variables above, other determinants used in various studies on life satisfaction such as economic, social, and demographic characteristics are included. Estimation results show that water pollution is negative and significant for life satisfaction. Other indicators such as income, age, house ownership, gender, education are positively related while urban residence and own business are shown to be negatively related.

• Journal of KIISE:Information Networking
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• v.30 no.2
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• pp.143-154
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• 2003

There is a growing trend in developing system for distributed mobile system that supports services - job flow management, video conference, replicated data management and resource allocation. Supporting these services, applications have to use causally ordered message delivery. Previous proposals that provide causally ordered message delivery have problems such as communication overhead, message delaying, scalability, computing overload of mobile host. In this paper, we proposed efficient protocol for causally ordered message delivery using the methods that MSS maintains dependency information matrix between MSS and MH, Piggybacking dependency information about each immediate predecessor message. Proposed algorithm, when compared with previous proposals, provides a low message overhead, and low probability of unnecessary inhibition in delivering messages. Also, it consider resource restriction of MH and low bandwidth of wireless communication by computing most of algorithm at MSS, and reduce processing delay by executing causally ordered message delivery a unit of MH.

• Journal of Information Technology Applications and Management
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• v.23 no.4
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• pp.41-53
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• 2016

According to the price-decline effect, the art auction prices are known to decrease with the order of auction sale. Our empirical study investigates the presence for the price-decline effect using the data for Korean antique art hosted by the Seoul Auction in September, 2015. We apply the Hedonic price model to the data and examine the relation between the sale order and auction price. Our empirical evidences show that the well-known price decline effect is not present for the case of Korean antique auction in 2015. We confirm our results by estimating the ordered probit model. From the view of the price-decline effect, our results suggest that the Korean antique auction data exhibits different characteristics from most of the foreign art auction data.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.6
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• pp.27-34
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• 2009

Block truncation coding (BTC) is a simple and efficient image compression technique. However, it yields images of unacceptable quality and significant blocking effects are seen when the block size is increasing. Ordered dither block truncation coding (ODBTC) was proposed to solve above problem maintaining the same compression capability. In this paper, we propose a data hiding method which can be applied to halftone images. EMD was developed by Zhang and Wang [6] for data hiding in the grayscale image. Therefore, EMD is not proper for bitmap images. In this paper, we show that EMD can be used to apply bitmap halftone image. In our experiments, we prove that our method is efficient in a halftone image.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.5
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• pp.875-885
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• 2010

Recently, the role of Ubiquitous Sensor Network(USN) has been considered to be essential for supporting the near future Network Centric Warfare(NCW) and Tactical Information Communication Network(TICN). In this paper, we explore a set of data storage methods(external storage, local storage and data storage) and query processing methods in WSN. In particular, we focus on analyzing a novel data structure for supporting the local storage method, named the partial ordered tree(POT). The main idea behind POT is that sensor readings are usually correlated with the physical spatial domain. With the help of POT, only a small portion of sensor nodes participate in query processing tasks, and thus network lifetime is greatly increased. Through a series of simulation experiments, we demonstrate that the POT based local storage method clearly outperforms the existing data storage methods in terms of the energy-efficiency, which directly affects the network lifetime, for processing exact match queries, range queries and top-k queries.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.321-323
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• 2006

The IEEE 802.15.4 uses a CSMA/CA algorithm on access of media. The CSMA/CA algorithm does Random Backoff before the data is transmitted to avoid collisions. The random backoff is a kind of unavoidable delays and introduces the side effect of energy consumptions. To cope with those problems we propose a new media access algorithm, the Priority Based Ordered Media Access (PBOMA) algorithm, which uses different IFSs. The PBOMA algorithm uses Sampling Rate and Beacon Interval to get a different access probability(or IFS). The access probability is higher, the IFS is shorter. Note that The transfer of urgent data uses tone signal to transmit it immediately. The proposed algorithm is expected to reduce the energy consumptions and the delay.

• Biomaterials and Biomechanics in Bioengineering
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• v.3 no.1
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• pp.1-14
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• 2016

Well-ordered porous materials are very promising in orthopedics since they allow tailoring the mechanical properties. Finite element (FE) analysis is commonly used to evaluate the mechanical behavior of well-ordered porous materials. However, FE results generally differ importantly from experimental data. In the present article, three types of manufacturing irregularities were characterized on an additive manufactured porous titanium sample having a simple cubic unit-cell: strut diameter variation, strut inclination and fractured struts. These were included in a beam FE model. Results were compared with experimental data in terms of the apparent elastic modulus (Eap) and apparent yield strength (SY,ap). The combination of manufacturing irregularities that yielded the closest results to experimental data was determined. The idealized FE model resulted in an Eap one order of magnitude larger than experimental data and a SY,ap almost twice the experimental values. The strut inclination and fractured struts showed the strongest effects on Eap and SY,ap, respectively. Combining the three manufacturing irregularities produced the closest results to experimental data. The model also performed well when applied to samples having different structural dimensions. We recommend including the three proposed manufacturing irregularities in the FE models to predict the mechanical behavior of such porous structures.

• Proceedings of the Korean Magnestics Society Conference
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• 2007.05a
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• pp.32.2-32.2
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• 2007

• Journal of the Korean Data and Information Science Society
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• v.22 no.5
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• pp.967-976
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• 2011

The Box-Cox transformation is a well known family of power transformations that brings a set of data into agreement with the normality assumption of the residuals and hence the response variable of a postulated model in regression analysis. Normalization (studentization) of the regressors is a common practice in analyzing microarray data. Here, we implement Box-Cox transformation in normalizing regressors in microarray data. Pridictabilty of the model can be improved using data transformation compared to studentization.