• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.4
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• pp.97-107
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• 2009

In image-based gait recognition systems, physical factors, such as the camera angle and the lens distortion, and environmental factors such as illumination determines the performance of recognition. In this paper we present a robust gait recognition method by compensating various types of image distortions. The proposed method is compared with existing gait recognition algorithm with consideration of both physical and environmental distortion factors in the input image. More specifically, we first present an efficient compensation algorithm of image distortion by using the projective transform, and test the feasibility of the proposed algorithm by comparing the recognition performances with and without the compensation process. Proposed method gives universal gait data which is invariant to both distance and environment. Gained data improved gait recognition rate about 41.5% in indoor image and about 55.5% in outdoor image. Proposed method can be used effectively in database(DB) construction, searching and tracking of specific objects.

• The Journal of Society for e-Business Studies
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• v.22 no.2
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• pp.123-136
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• 2017

The evaluation and analysis method of information system (IS) is studied from the system perspective, the user perspective, and the management viewpoint. The detailed analysis method performs qualitative evaluation by user questionnaire or expert opinion. In this study, Measures the productivity and the effect of building administrative information systems. In the previous study, qualitative productivity and universal effect indicators were used, but in this study, quantitative productivity indicators and indicators specific to administrative complaints were selected. KONEPS, an administrative service system, used electronic contract records and information recorded in the intermediate process. The information was converted into the number of days, and the productivity based on the input manpower was calculated. The effect analysis analyzed the questionnaire related to civil affairs, which is the goal of the administrative work system. Each factor was divided into reflective structural variable and formal structural variable, and internal consistency and multi-collinearity were diagnosed. In order to verify the model, the influence of the work was set as a hypothesis, the reliability was verified according to the descriptive statistics method, the influence was measured through the regression analysis, and the model was analyzed by the multiple regression model path coefficient. Model validation methods are Chi-square (df, p), RMR, GFI, AGFI, NFI, CFI and GFI as indicators according to CFA.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.21 no.5
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• pp.465-474
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• 2008

The real-time hybrid testing method(RT-HYTEM) is a structural testing technique in which the numerical integration of the equation of motion for a numerical substructure and the physical testing for an experimental substructure are performed simultaneously in real-time. This study presents the quantitative evaluation of the seismic performance of a building structure installed with an passive and semi-active MR damper by using RT-HYTEM. The building model that was identified from the force-vibration testing results of a real-scaled 5-story building is used as the numerical substructure, and an MR damper corresponding to an experimental substructure is physically tested by using the universal testing machine(UTM). The RT-HYTEM implemented in this study is validated because the real-time hybrid testing results obtained by application of sinusoidal and earthquake excitations and the corresponding analytical results obtained by using the Bouc-Wen model as the control force of the MR damper respect to input currents were in good agreement. Also for preliminary study, some semi-active control algorithms were applied to the MR damper in order to control the structural responses optimally. Comparing between the test results of semi-active control using RT-HYTEM and numerical analysis results show that the RT-HYTEM is more resonable than numerical analysis to evaluate the performance of semi-active control algorithms.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.9
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• pp.10-17
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• 2007

It opens a new horizon on spintronics for the potential application of MTJ as a universal logic element, to employ the magneto-logic in substitution for the transistor-based logic device. The magneto-logic based on the MTJ element shows many potential advantages, such as high density, and nonvolatility. Moreover, the MTJ element has programmability and can therefore realize the full logic functions just by changing the input signals. This magneto-logic using MTJ elements can embody the reconfigurable circuit to overcome the rigid architecture. The established magneto-logic element has been designed and fabricated on a triple-layer MTJ. We present a novel magneto-logic structure that consists of a single layer MTJ and a current driver, which requires less processing steps with enhanced functional flexibility and uniformity. A 4-bit gray counter is designed to verify the magneto-logic functionality of the proposed single-layer MTJ and the simulation results are presented with the HSPICE macro-model of MTJ that we have developed.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.2
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• pp.112-121
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• 2007

In occasion of soil loss happened in a basin, soil in the near of a stream may flow into the stream easily, but in case that soil is far away from the stream, sediment yield transferred to rivers by rainfall diminishes. To forecast sediment yield of a stream is an essential item for management of basins and streams. Therefore, sediment yield of soil loss produced from a basin is needed to be calculated as accurate as possible. Purpose of the present research is to calculate soil erosion amount in a basin and to forecast sediment yield flowed into a stream by rainfall and analyze sediment yield in the stream. There are various methods that analyze sediment yield of rivers. In the present study, the soil erosion amount was calculated using Revised Universal Soil Loss Equation(RUSLE) and GRID, and sediment yield was calculated using sediment delivery ratio and empirical methods. DEM data, slope of basin, soil map and landuse constructed by GIS were used for input data of RUSLE. The upstream area of the Yeongsan river basin in Gwangju metropolitan city was selected for the study area. Three methods according to the calculation of LS factor were applied to estimate the soil erosion amount. Two sediment delivery ratio methods for the respective methods were applied and, correspondingly, six occasions in sediment yield were calculated. In addition, the above results were compared by relative amount with estimation by the empirical method of Ministry of Construction & Transportation. Sediment yield calculated in the present study may be utilized for the plan, design and management of dams and channels, and evaluation of disaster impact.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.12
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• pp.1343-1350
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• 2012

This paper presents a new method for designing a dual-band WIFI antenna using the third-order harmonic mode of a monopole antenna whose first-order mode operates at the low frequency band of WIFI. As analysing the current distribution of the third-order mode of this monopole antenna, the strongest point of electric field can be found. Then by attaching a stub at this point, the resonant frequency of the stub radiator can be adjusted from the third-order mode of the monopole antenna into the high frequency band of WIFI and the input impedance at this resonant frequency can be controlled with the width of the branch, without affecting the low frequency band of WIFI (the first-order mode of the monopole antenna). The compact dual-band antenna is designed at the size of an USB(universal serial bus) dongle and the bandwidth covers 600 MHz(2.3~3 GHz) at 2 GHz and 1 GHz(4.9~5.9 GHz) at 5 GHz under -10 dB which is satisfied with WLAN frequency. Efficiency of proposed antenna achieves over 50 % at WLAN frequency.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.260-260
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• 2016

Soil erosion is a very serious problem from agricultural as well as environmental point of view. Various computer models have been used to estimate soil erosion and assess erosion control practice. Universal Soil loss equation (USLE) is a popular model which has been used in many countries around the world. Erosivity (USLE R-factor) is one of the USLE input parameters to reflect impacts of rainfall in computing soil loss. Value of R factor depends upon Energy (E) and maximum rainfall intensity of specific period ($I30_{max}$) of that rainfall event and thus can be calculated using higher temporal resolution rainfall data such as 10 minute interval. But 10 minute interval rainfall data may not be available in every part of the world. In that case we can use hourly rainfall data to compute this R factor. Maximum 60 minute rainfall ($I60_{max}$) can be used instead of maximum 30 minute rainfall ($I30_{max}$) as suggested by USLE manual. But the value of Average annual R factor computed using hourly rainfall data needs some correction factor so that it can be used in USLE model. The objective of our study are to derive relation between averages annual R factor values using 10 minute interval and hourly rainfall data and to determine correction coefficient for R factor using hourly Rainfall data.75 weather stations of Korea were selected for our study. Ten minute interval rainfall data for these stations were obtained from Korea Meteorological Administration (KMA) and these data were changed to hourly rainfall data. R factor and $I60_{max}$ obtained from hourly rainfall data were compared with R factor and $I30_{max}$ obtained from 10 minute interval data. Linear relation between Average annual R factor obtained from 10 minute interval rainfall and from hourly data was derived with $R^2=0.69$. Correction coefficient was developed for the R factor calculated using hourly rainfall data.. Similarly, the relation was obtained between event wise $I30_{max}$ and $I60_{max}$ with higher $R^2$ value of 0.91. Thus $I30_{max}$ can be estimated from I60max with higher accuracy and thus the hourly rainfall data can be used to determine R factor more precisely by multiplying Energy of each rainfall event with this corrected $I60_{max}$.

• The Journal of Bigdata
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• v.3 no.2
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• pp.59-70
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• 2018

In order to provide stable district heat supplying service to the certain limited residential area, it is the most important to forecast the short-term future demand more accurately and produce and supply heat in efficient way. However, it is very difficult to develop a universal heat demand forecasting model that can be applied to general situations because the factors affecting the heat consumption are very diverse and the consumption patterns are changed according to individual consumers and regional characteristics. In particular, considering all of the various variables that can affect heat demand does not help improve performance in terms of accuracy and versatility. Therefore, this study aims to develop a demand forecasting model using deep learning based on only limited information that can be acquired in real time. A demand forecasting model was developed by learning the artificial neural network of the Tensorflow using past data consisting only of the outdoor temperature of the area and date as input variables. The performance of the proposed model was evaluated by comparing the accuracy of demand predicted with the previous regression model. The proposed heat demand forecasting model in this research showed that it is possible to enhance the accuracy using only limited variables which can be secured in real time. For the demand forecasting in a certain region, the proposed model can be customized by adding some features which can reflect the regional characteristics.

• Journal of Korea Entertainment Industry Association
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• v.15 no.8
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• pp.423-432
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• 2021

In this study, we investigated and the following conclusions are presented by identifying the current status and problems in order to expand the future's value of the community care project introduced and implemented to improve the quality and care for the elderly's life. First, the needs analysis of the elderly receiving services is composed of patient-centered rather than investigator-centered, and in particular, medical management through medical staff visits should be strengthened, and specialized service items according to gender, age, disability type, and personal preference should be strengthened. This will have to be gradually strengthened. Second, by analyzing the satisfaction, redundancy, and effectiveness of service items, we save money, and consider the consumer-oriented service item composition and application of items necessary for new services. Third, through the introduction of an integrated schedule management system, it is necessary to specialize in pre-booking and visit schedule management between the elderly and the direct service organizations that provide services. Fourth, as an effort to solve the financial problem, it is necessary to prepare a rational resource sharing system with health and medical finance, long-term care insurance system, and social welfare financial project. and it may consider that putting the medical personnel who are from local public medical college input. Through these proposals, the community care business will be able to complete and have future value as a universal aged care system.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.21-41
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• 2019

Thanks to the rapid development of information technologies, the data available on Internet have grown rapidly. In this era of big data, many studies have attempted to offer insights and express the effects of data analysis. In the tourism and hospitality industry, many firms and studies in the era of big data have paid attention to online reviews on social media because of their large influence over customers. As tourism is an information-intensive industry, the effect of these information networks on social media platforms is more remarkable compared to any other types of media. However, there are some limitations to the improvements in service quality that can be made based on opinions on social media platforms. Users on social media platforms represent their opinions as text, images, and so on. Raw data sets from these reviews are unstructured. Moreover, these data sets are too big to extract new information and hidden knowledge by human competences. To use them for business intelligence and analytics applications, proper big data techniques like Natural Language Processing and data mining techniques are needed. This study suggests an analytical approach to directly yield insights from these reviews to improve the service quality of hotels. Our proposed approach consists of topic mining to extract topics contained in the reviews and the decision tree modeling to explain the relationship between topics and ratings. Topic mining refers to a method for finding a group of words from a collection of documents that represents a document. Among several topic mining methods, we adopted the Latent Dirichlet Allocation algorithm, which is considered as the most universal algorithm. However, LDA is not enough to find insights that can improve service quality because it cannot find the relationship between topics and ratings. To overcome this limitation, we also use the Classification and Regression Tree method, which is a kind of decision tree technique. Through the CART method, we can find what topics are related to positive or negative ratings of a hotel and visualize the results. Therefore, this study aims to investigate the representation of an analytical approach for the improvement of hotel service quality from unstructured review data sets. Through experiments for four hotels in Hong Kong, we can find the strengths and weaknesses of services for each hotel and suggest improvements to aid in customer satisfaction. Especially from positive reviews, we find what these hotels should maintain for service quality. For example, compared with the other hotels, a hotel has a good location and room condition which are extracted from positive reviews for it. In contrast, we also find what they should modify in their services from negative reviews. For example, a hotel should improve room condition related to soundproof. These results mean that our approach is useful in finding some insights for the service quality of hotels. That is, from the enormous size of review data, our approach can provide practical suggestions for hotel managers to improve their service quality. In the past, studies for improving service quality relied on surveys or interviews of customers. However, these methods are often costly and time consuming and the results may be biased by biased sampling or untrustworthy answers. The proposed approach directly obtains honest feedback from customers' online reviews and draws some insights through a type of big data analysis. So it will be a more useful tool to overcome the limitations of surveys or interviews. Moreover, our approach easily obtains the service quality information of other hotels or services in the tourism industry because it needs only open online reviews and ratings as input data. Furthermore, the performance of our approach will be better if other structured and unstructured data sources are added.