• Journal of the Korean association of regional geographers
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• v.12 no.4
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• pp.508-521
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• 2006

The results of environmental equity analysis vary dramatically depending on different methods used. The information and data available to the researcher are also often uncertain and imprecise in empirical studies. A sensitivity analysis approach was used too handle uncertainties and methodological inconsistencies in environmental equity analysis. This paper explores the sensitivity of environmental equity analysis to two spatial measures such as proximity and scale. Two experiments were implemented to evaluate the effects of two spatial measures on the environmental equity analysis using a combination of control and experimental factors. Fulton County, Georgia was selected as a case study area for these experiments. Two major data sets including demographic characteristics and toxic release inventory (TRI) database for the study area in 1990 were integrated into a GIS environment. Two statistical analyses such as independent samples t-test and coefficient of variation were performed to determine the environmental equity in the study area and to compare the relative variability in the socioeconomic characteristics of populations over different spatial measures. The findings from two experiments indicate that the outcomes of environmental equity analysis are slightly sensitive to the buffer distance used to determine the impact zones of TRI facilities, but not to the geographic scale used in the analysis. The findings also suggest that the consequences of these choices can alter spatially and statistically the results in environmental equity analysis.

• The KIPS Transactions:PartA
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• v.16A no.2
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• pp.113-124
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• 2009

With increasing multicore system, much effort has been put on the performance improvement of its application. Because multicore system has multiple processing devices in one system, its processing power increases compared to the single core system. However in many cases the advantages of multicore can not be exploited fully because the existing software and hardware were designed to be suitable for single core. When the existing software runs on multicore, its performance improvement is limited by the bottleneck of sharing resources and the inefficient use of cache memory on multicore. Therefore, according as the number of core increases, it doesn't show performance improvement and shows performance drop in the worst case. In this paper we propose a method of performance improvement of multicore system by applying Flow-Level Parallelism to the existing TCP/IP network application and operating system. The proposed method sets up the execution environment so that each core unit operates independently as much as possible in network application, TCP/IP stack on operating system, device driver, and network interface. Moreover it distributes network traffics to each core unit through L2 switch. The proposed method allows to minimize the sharing of application data, data structure, socket, device driver, and network interface between each core. Also it allows to minimize the competition among cores to take resources and increase the hit ratio of cache. We implemented the proposed methods with 8 core system and performed experiment. Experimental results show that network access speed and bandwidth increase linearly according to the number of core.

• International Journal of Highway Engineering
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• v.16 no.1
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• pp.11-19
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• 2014

PURPOSES : The purpose of this article is to investigate the predicted life of jointed concrete pavement (JCP) with two variables effecting on axle load spectra (ALS). The first variable is different data acquisition methods whether using high-speed weigh-in-motion (HS-WIM) or not and the other one is spectra distribution due to overweight enforcement on main-lane of expressway using HS-WIM. METHODS : Three sets of ALS had been collected i) ALS provided by Korea Pavement Research Program (KPRP), which had been obtained without using HS-WIM ii) ALS collected by HS-WIM before the enforcement at Kimcheon and Seonsan site iii) ALS collected after the enforcement at the same sites. And all ALS had been classified into twelve vehicle classes and four axle types to compare each other. Among the vehicle classes, class 6, 7, 10 and 12 were selected as the major target for comparing each ALS because these were considered as the primary trucks with a high rate of overweight loading. In order to analyze the performance of JCP based on pavement life, fatigue crack and International Roughness Index (IRI) were predicted using road pavement design program developed by KPRP and each ALS with same annual average daily traffic (AADT) was applied to design slab thickness. RESULTS : Comparison ALS of KPRP with those of HS-WIM shows that the ALS of KPRP has a low percentage of heavy spectra such as 6~9 tonnes for single axle, 18~21 tonnes for tandem axle and 27~30 tonnes for tridem axle than other two ALS of HS-WIM in most vehicle classes and axle types. It means that ALS of KPRP was underestimated. And after the enforcement, percentage of heavy spectra close to 10 tonnes per an axle are lowered than before the enforcement by the effect of overweight enforcement because the spectra are related to overweight regulation. Prediction results of pavement life for each ALS present that the ALS of HS-WIM collected before the enforcement makes the pavement life short more than others. On the other hand, the ALS of KPRP causes the longest life under same thickness of slab. Thus, it is possible that actual performance life of JCP under the traffic like ALS of HS-WIM could be short than predicted life if the pavement was designed based on ALS provided by KPRP. CONCLUSIONS : It is necessary to choose more reliable and practical ALS when designing JCP because ALS can be fairly affected by acquisition methods. In addition, it is important to extend performance life of the pavement in service by controlling traffic load such as overweight enforcement.

• Informatization Policy
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• v.24 no.3
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• pp.3-26
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• 2017

The amount of unstructured data generated online is increasing exponentially and the analysis of text data is being done in various fields. In order to identify the research trends on the platform government, the title, year, academic society, and abstract information of the academic papers on the subject of platform government were collected from the database of the domestic papers, DBPIA(www.dbpia.co.kr). The results of the existing research on the platform government and related fields were analyzed based on each stage of the national informatization promotion. The technology, service, and governance topics were extracted from papers on platform government and the trends of core topics were analyzed by year. Entering the era of the intelligent information society, this study has significance for providing the basis for defining a new role of government - the platform government that sets the stage for the private sector to lead the innovation, and plays the role of an 'enabler' and 'facilitator' instead. The purpose of this study is to understand the platform government research through objective analysis of its trends. Looking for future directions, this study will contribute to future research by providing reference materials.

• Childhood Kidney Diseases
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• v.14 no.1
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• pp.51-61
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• 2010

Purpose : Previous studies have suggested that Chemokine (C-C motif) ligand-2 (CCL-2; also known as MCP-1) and CCL-5 (also known as RANTES) are possibly associated with the pathogenesis of various inflammatory and non-inflammatory renal diseases. The present study was conducted to investigate association of polymorphisms of CCL-2 and CCL-5 genes with childhood IgA nephropathy (IgAN). Methods : The authors analyzed six single nucleotide polymorphisms (SNPs) of CCL-2 and CCL-5 in 196 pediatric IgAN patients and in 285 healthy controls. We compared variations in SNPs between two several sets of IgAN subgroups, allocated by presence of proteinuria (>4 mg/$m^2$/hour), podocyte foot process effacement, and pathologically advanced disease markers, such as interstitial fibrosis, tubular atrophy, or global sclerosis. Results : Genotypic data of IgAN patients and controls showed no significant SNP frequency difference in both of of CCL-2 and CCL-5. Even though two linkage disequilibrium blocks were formed, there was no significance in the haplotype analysis. In the patient subgroup analysis, no SNP of CCL-2 and CCL-5 was found to be associated with the presence of proteinuria, podocyte foot process effacement, and pathologically advanced disease markers. Conclusion : Our data indicate that no association exists between CCL-2 and CCL-5 SNPs and childhood IgAN susceptibility, and presence of proteinuria, podocyte foot process effacement, and pathologic progression of IgAN.

• Journal of Distribution Science
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• v.4 no.2
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• pp.21-40
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• 2006

Small and middle sized Franchise system channels experience conflicts because of constant interaction between franchiser and franchisee. However, it is rarely that attempt has been made to identify causes of conflicts in distribution of franchise industry. The purpose of this study was to explore cause of conflicts from the franchisee. For the study, data were collected from the owner or the shop-manager with a contractor in franchise systems. By means of in-depth interviews with multiple informants, their statement was analyzed qualitatively. From analysis of the resulting data, the causes of conflicts were associated with two broad sets, attitudinal and structural differences between franchisers and franchisees. First, attitudinal sources of conflict were identified as perception of subordinated relationships between channel members, delayed announcement on order changes, difficulties in communication by doing irresponsible behavior, different expectations between channel members in market territory and lack of consistent-supporting. Second, structural sources of conflict involved unilateral decision on interior, payment method, unreasonable delivery issue, treat franchisee with discrimination by the sales, in controlling against free management. There are limitations on generalization due to the results based on interview, but this study will be a useful exploratory step before designing a large scale survey.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.3
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• pp.59-66
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• 2016

This paper presents an empirical evaluation on dimensionality reduction strategies by which dissimilarity-based classifications (DBC) can be implemented efficiently. In DBC, classification is not based on feature measurements of individual objects (a set of attributes), but rather on a suitable dissimilarity measure among the individual objects (pair-wise object comparisons). One problem of DBC is the high dimensionality of the dissimilarity space when a lots of objects are treated. To address this issue, two kinds of solutions have been proposed in the literature: prototype selection (PS)-based methods and dimension reduction (DR)-based methods. In this paper, instead of utilizing the PS-based or DR-based methods, a way of performing DBC in Eigen spaces (ES) is considered and empirically compared. In ES-based DBC, classifications are performed as follows: first, a set of principal eigenvectors is extracted from the training data set using a principal component analysis; second, an Eigen space is expanded using a subset of the extracted and selected Eigen vectors; third, after measuring distances among the projected objects in the Eigen space using $l_p$-norms as the dissimilarity, classification is performed. The experimental results, which are obtained using the nearest neighbor rule with artificial and real-life benchmark data sets, demonstrate that when the dimensionality of the Eigen spaces has been selected appropriately, compared to the PS-based and DR-based methods, the performance of the ES-based DBC can be improved in terms of the classification accuracy.

• Korean Journal of Remote Sensing
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• v.22 no.4
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• pp.265-274
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• 2006

Extracting ground points is the kernel of DTM generation being considered as one of the most popular LIDAR applications. The previous extraction approaches can be mostly characterized as a point based approach, which sequentially examines every individual point to determine whether it is measured from ground surfaces. The number of examinations to be performed is then equivalent to the number of points. Particularly in a large set, the heavy computational requirement associated with the examinations is obviously an obstacle to employing more sophisticated criteria for the examination. To reduce the number of entities to be examined and produce more robust results, we developed an approach based on features rather than points, where a feature indicates an entity constructed by grouping some points. In the proposed approach, we first generate a set of features by organizing points into surface patches and grouping the patches into surface clusters. Among these features, we then attempt to identify the ground features with the criteria based on the attributes of the features. The points grouped into these identified features are labeled ground points, being used for DTM generation afterward. The Proposed approach was applied to many real airborne LIDAR data sets. The analysis on the results strongly supports the prominent performance of the proposed approach in terms of not only the computational requirement but also the quality of the DTM.

• Korean Journal of Remote Sensing
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• v.26 no.5
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• pp.549-559
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• 2010

In geo-spatial information system building and operation, metadata is one of the crucial factors. Therefore, international and domestic organizations or associations for standardization have developed and distributed geo-based standard metadata to meet public demands. However, because metadata is composed of complicated elements and needs XML storage and management, individual organization which implement and operate practical application system is inclined to define and use its own metadata specifications. In this study, metadata extraction program, that metadata elements are directly extracted from geo-based file formats was developed to easily utilize standard metadata such as ISO/TC 19115, TTAS.KO-10.0139 and TTAS.IS-19115, and those elements are processed into XML. Furthermore, geo-based images sets are applied to another metadata of ISO/TC 19115-2. As well, metadata transformation is needed due to inconsistent or non-corresponding definition among standard metadata; in this program, transformation modules are also implemented to interoperable uses between standard metadata specifications. Widely used data formats are dealt with in this program, but extension for other formats and other metadata specifications is possible, and it is expected that availability of standard metadata is increased, through this kind of development.

• Nuclear Engineering and Technology
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• v.53 no.8
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• pp.2534-2546
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• 2021

Nuclear emergency preparedness and response is an essential part to ensure the safety of nuclear power plant (NPP). Key support technologies of nuclear emergency decision-making usually consist of accident diagnosis, source term estimation, accident consequence assessment, and protective action recommendation. Source term estimation is almost the most difficult part among them. For example, bad communication, incomplete information, as well as complicated accident scenario make it hard to determine the reactor status and estimate the source term timely in the Fukushima accident. Subsequently, it leads to the hard decision on how to take appropriate emergency response actions. Hence, this paper aims to develop a method for rapid source term estimation to support nuclear emergency decision making in pressurized water reactor NPP. The method aims to make our knowledge on NPP provide better support nuclear emergency. Firstly, this paper studies how to build a Bayesian network model for the NPP based on professional knowledge and engineering knowledge. This paper presents a method transforming the PRA model (event trees and fault trees) into a corresponding Bayesian network model. To solve the problem that some physical phenomena which are modeled as pivotal events in level 2 PRA, cannot find sensors associated directly with their occurrence, a weighted assignment approach based on expert assessment is proposed in this paper. Secondly, the monitoring data of NPP are provided to the Bayesian network model, the real-time status of pivotal events and initiating events can be determined based on the junction tree algorithm. Thirdly, since PRA knowledge can link the accident sequences to the possible release categories, the proposed method is capable to find the most likely release category for the candidate accidents scenarios, namely the source term. The probabilities of possible accident sequences and the source term are calculated. Finally, the prototype software is checked against several sets of accident scenario data which are generated by the simulator of AP1000-NPP, including large loss of coolant accident, loss of main feedwater, main steam line break, and steam generator tube rupture. The results show that the proposed method for rapid source term estimation under nuclear emergency decision making is promising.