• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.1
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• pp.165-170
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• 2015

The topic of this paper is the advanced absolute altitude determination for 3-D positioning using barometric altimeter and the reference station. Barometric altimeter does not provide absolute altitude because atmosphere pressure always varies over the time and geographical location. Also, since Global Navigation Satellites system such as GPS, GLONASS has geometric error, the altitude information is not available. It is the reason why we suggested the new method to improve the altitude accuracy. This paper shows 3-D positioning algorithm using absolute altitude determination method and evaluates the algorithm by real field tests. We used an accurate altitude from RTK system in Seoul as a reference data and acquired the differential value of pressure data between a reference station and a mobile station equipped in low cost barometric altimeter. In addition, the performance and advantage of the proposed method was evaluated by 3-D experiment analysis of PNS and CNS. We expect that the proposed method can expand 2-D positioning system 3-D position determination system simply and this 3-D position determination technique can be very useful for the workers in the field of fire-fighting and construction.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.8
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• pp.561-570
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• 2004

In this paper, new architectures and comprehensive design methodologies of Genetic Algorithms(GAs) based Genetically optimized Neurofuzzy Networks(GoNFN) are introduced, and a series of numeric experiments are carried out. The proposed GoNFN is based on the rule-based Neurofuzzy Networks(NFN) with the extended structure of the premise and the consequence parts of fuzzy rules being formed within the networks. The premise part of the fuzzy rules are designed by using space partitioning in terms of fuzzy sets defined in individual variables. In the consequence part of the fuzzy rules, three different forms of the regression polynomials such as constant, linear and quadratic are taken into consideration. The structure and parameters of the proposed GoNFN are optimized by GAs. GAs being a global optimization technique determines optimal parameters in a vast search space. But it cannot effectively avoid a large amount of time-consuming iteration because GAs finds optimal parameters by using a given space. To alleviate the problems, the dynamic search-based GAs is introduced to lead to rapidly optimal convergence over a limited region or a boundary condition. In a nutshell, the objective of this study is to develop a general design methodology o GAs-based GoNFN modeling, come up a logic-based structure of such model and propose a comprehensive evolutionary development environment in which the optimization of the model can be efficiently carried out both at the structural as well as parametric level for overall optimization by utilizing the separate or consecutive tuning technology. To evaluate the performance of the proposed GoNFN, the models are experimented with the use of several representative numerical examples.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.10 no.7
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• pp.1085-1094
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• 1999

In the global system for the mobile communication (GSM) system, the class of training sequences used in a TDMA frame is a preamble sequence with a period of 16 bits for the channel impulse response measurement and the start up equalization during the training period. If the transmitted preamble sequence and the binary sequence in the receiver properly satisfy a condition, this training sequences used for fastly adjusting the tap coefficients and impulse response can be measured by calculating the crosscorrelation function. In this paper, it is used that training sequences have zero values of the autocorrelation at all delays except zero and middle shifts. A comparison of convergence rate, a mathematical approach for fast start-up equalization and correctly channel impulse response measurement are proposed.

• The KIPS Transactions:PartA
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• v.12A no.2 s.92
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• pp.171-180
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• 2005

In distributed systems data are replicated and stored at several nodes to increase the availability and overall performance. Here Quorum protocol doffing a certain set of replicas required for read/write operation exists for global concurrency control. One of the representative replication Protocols - the Tree Quorum protocol - has a drawback of rapidly growing number of replicas as the level increases, while the Grid protocol requires the same operation cost even without any failure. In this paper, thus, we propose a new replication protocol called hybrid protocol which capitalizes the merits of the existing protocols and solves the problems of them at the same time. The proposed hybrid protocol has very low operation cost in the absence of failure like the tree quorum protocol, and has relatively lower operation cost and higher availability than existing protocols when failure occurs by employing tree architecture as the overall organization while each level of the tree is organized as a row of a grid architecture. It is thus effective to be applied to survival storage system. We conduct cost and availability analysis of the proposed protocol through mathematical modeling, and response time and throughput are compared with those of the Tree Quorum protocol through computer simulation.

• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.4
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• pp.95-106
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• 2013

It is now generally known that dynamical climate modeling outputs include systematic biases in reproducing the properties of atmospheric variables such as, preciptation and temerature. There is thus, general consensus among the researchers about the need of bias-correction process prior to using climate model results especially for hydrologic applications. Among the number of bias-correction methods, distribution (e.g., cumulative distribution fuction, CDF) mapping based approach has been evaluated as one of the skillful techniques. This study investigates the uncertainty of using various CDF mapping-based methods for bias-correciton in assessing regional climate change Impacts. Two different dynamicailly-downscaled Global Circulation Model results (CCSM and GFDL under ARES4 A2 scenario) using Regional Spectial Model for retrospective peiod (1969-2000) and future period (2039-2069) were collected over the west central Florida. Total 12 possible methods (i.e., 3 for developing distribution by each of 4 for estimating biases in future projections) were examined and the variations among the results using different methods were evaluated in various ways. The results for daily temperature showed that while mean and standard deviation of Tmax and Tmin has relatively small variation among the bias-correction methods, monthly maximum values showed as significant variation (~2'C) as the mean differences between the retrospective simulations and future projections. The accuracy of raw preciptiation predictions was much worse than temerature and bias-corrected results appreared to be more significantly influenced by the methodologies. Furthermore the uncertainty of bias-correction was found to be relevant to the performance of climate model (i.e., CCSM results which showed relatively worse accuracy showed larger variation among the bias-correction methods). Concludingly bias-correction methodology is an important sourse of uncertainty among other processes that may be required for cliamte change impact assessment. This study underscores the need to carefully select a bias-correction method and that the approach for any given analysis should depend on the research question being asked.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.33 no.6
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• pp.490-494
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• 2020

Sulphur hexafluoride (SF₆) is mostly used as a current-insulating medium in gas-insulated switchgears (GIS), owing to its excellent dielectric strength and arc-extinguishing performance. The global warming potential (GWP) of SF₆, however, is 23,900 times that of CO₂, and its life time in the atmosphere is 3,200 years. For these reasons, new eco-friendly gases to replace SF₆ are required. In this study, the partial discharge (PD) characteristics of green gas for grid (g³) and dry air (N₂/O₂) were analyzed to compare with those of SF₆. A PD electrode system was designed to simulate the protrusion defect in GISs and fabricated for experimentation. To compare the PD characteristics of each gas, the discharge inception voltage (DIV), discharge extinction voltage (DEV), discharge magnitude, discharge pulse number, and phase pattern were analyzed. Results from this study are expected to provide fundamental materials for the design of eco-friendly GISs.

• Journal of the Korea Institute of Building Construction
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• v.10 no.6
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• pp.77-85
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• 2010

Recently, with development of core technology for supertall building construction projects, the need for an improvement of the related legal system is increasing dramatically. Therefore, the supertall Buildings R&DB Center, which is funded by the Ministry of Land, Transport and Maritime affairs (MLTM), is studying the legal system for supertall buildings. This research, as one part of the 1st year research results, aimed at studying supertall building project related issues and problems to develop supertall building elements, and conducting an importance-performance analysis (IPA) of these elements in order to conclude a strategy and direction for an improvement of the related legal system. A total of 68 supertall building elements were derived, and the IPA method was used to analyze these elements based on attribute types. Furthermore, an improvement strategy and directions were suggested for upgrading the legal system related to supertall buildings to the level of global standards. These efforts can be the base for advancing the legal systems of the domestic construction industry in all areas, including supertall building construction.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.3
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• pp.608-618
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• 2007

Image binarization is an important preprocessing to identify the object of interest by dividing pixels into the background and object. We proposes efficient binarization method and a stroke reconstruction method of the low quality character image for an effective character recognition. First, the character image is binarized by using the both advantages of local and global thresholding method and then the noise elimination around the character stroke and the hole filling on the stoke by the analysis of the binarized stroke image are performed to enhance the quality of the character stroke. Proposed binarization algorithm for character image achieved an efficiency of both processing speed and performance by the adaptive threshold selection. Moreover, We could get a high qualify binary image by a stroke reconstruction of the step-by-step denoising process.

• Journal of the Korean Society for Railway
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• v.20 no.3
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• pp.382-388
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• 2017

In response to the global warming crisis, the Kyoto protocol was established by major developed countries in 1997. The Paris Agreement, which imposes a carbon reduction obligation for both developed countries and developing countries, was signed in 2015. Regulations and efforts to reduce greenhouse gas emissions accordingly have been implemented. In this study, we analyzed the reduction of carbon emissions computerizing of the traditional project management system for efficient railway construction at Korea Rail Network Authority. We suggest a model that measures two major effects of carbon reduction, stemming from transportation and from a decrease of paper use. In this paper, we calculate the amount of carbon reduction and the economic effect of carbon reduction with application of the construction project management system at Korea Rail Network Authority. The model and methodology in this study are expected to be helpful to measure the carbon reduction performance for similar e-transformation.

• Journal of Convergence for Information Technology
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• v.9 no.1
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• pp.116-122
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• 2019

In recent years, small and medium-sized businesses are rapidly changing to an industrial structure where process/quality/energy data aggregates can be automatically or real-time to achieve global competitiveness. In particular, real-time information analysis produced in the production process of small businesses is evolving into a new process process that analyzes, predicts, prescribes and implements significant performance of small businesses. In this paper, we propose a platform-building model that can transform the automated production information system of small businesses into big data so that they can upgrade data that is generated by small businesses. The proposed model has the capability to support operational efficiency (consulting and training) and strategic decision making of small businesses by utilizing a variety of data on the basic information of products produced by small businesses for data collection by smart SMEs. In addition, the proposed model is characterized by close cooperation between small and medium-sized businesses with different regional characteristics and areas of information sharing and system linkage.