• Journal of Digital Convergence
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• v.13 no.1
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• pp.85-92
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• 2015

Recently more and more shortened of corporation's sustainable longevity at the enterprise, and enterprise environment is also changing drastically. In this study, we wanted to obtain a solution that enable to continue the company's corporate longevity through critical factor analysis of the Japan Shinise. In the analysis results of Japan corporation as Doraya, Deicoko, Shinise longevity, we can explain about critical factors like that credit, tradition, customization, products development, changes of management methods and finding a global new markets. Also, In this study, analyzed a significance of critical factors for focusing on each cases and theories using Analytic Hierarchy Process(AHP), and did prediction and analysis about critical longevity factors. However, it need to collect sufficient data and a lots of variables for input. because the sample may be it insufficient. Results of the study, will be expected to be a useful guide for analysis of longevity factors at the company in the future.

• Survey Research
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• v.11 no.1
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• pp.123-144
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• 2010

In new sample design for Korea Housing Survey to research about housing policy, total strata are forty five because individual results of sixteen regions are estimated. The sample size is determined by sample errors of several variables which are the living area, family income, householder income, and living expenses. The sample size of each region is determined by relative standard error of existing result, and the strata sample size is to use the square root proportion allocation. Enumeration districts are sampled by the probability proportion to size systematic sampling in proportion to the enumeration district size, and the systemic sampling to use assortment characteristics. We considered a new apartment complex because of variation reflections which are rebuilder and redevelopment of houses. To get estimators of mean and variance, we used the design weighting, non-response adjusting, and post-stratification. In order to consider estimation efficiency, we calculate the design effect using estimators of variance.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.6
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• pp.607-614
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• 2015

In this paper, structural analysis for the 16 core competencies of aircraft maintenance crew using FSM is carried out for the purpose of improving the capability of aircraft maintenance. As a result, the three groups of layers are composed of the 3 top layers, 3 middle layers and 10 lowest layers. These results make it possible to grasp the impact and importance. In addition, the core competency of aircraft maintenance crew can improve the maintenance quality and productivity through working on the spot. In this viewpoint, fuzzy relational matrix, which is used as a basis for evaluating the work, can be obtained from the data of the 100 aircraft maintenance crew for core competencies. In this paper, the efficiency of this model is shown by utilizing the 100 modeling data and the 67 checking data.

• Journal of Korea Game Society
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• v.3 no.2
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• pp.35-41
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• 2003

There arose problems of double investment about the game engine part when a lot of game software similar to the property and procedure processed in the game engine develop new game without the reference or reuse in the other games. In particular, using various software development processes is one of main problems of double investment when the enterprises for the game software development develop games now Accordingly, because it does not make standardization of process about the game engine, it does not understand and reuse products created in process of the other software development process in development now. Accordingly, the newly analyzed and designed software was big problems with the present game software about the game engine process similar to the other game software when the enterprises for any game software develop a special game. For solving these problems, this study is to suggest the process improvement about the game engine development, analysis of structure and relation, classification and combination method by the class and module, implementation of storage, and processor model in order to apply the development method based on the component.

• Smart Media Journal
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• v.5 no.3
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• pp.35-41
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• 2016

In this paper, we propose hand-gesture signal recognition based on EPS(Electronic Potential Sensor) using Deep learning model. Extracted signals which from Electronic field based sensor, EPS have much of the noise, so it must remove in pre-processing. After the noise are removed with filter using frequency feature, the signals are reconstructed with dimensional transformation to overcome limit which have just one-dimension feature with voltage value for using convolution operation. Then, the reconstructed signal data is finally classified and recognized using multiple learning layers model based on deep learning. Since the statistical model based on probability is sensitive to initial parameters, the result can change after training in modeling phase. Deep learning model can overcome this problem because of several layers in training phase. In experiment, we used two different deep learning structures, Convolutional neural networks and Recurrent Neural Network and compared with statistical model algorithm with four kinds of gestures. The recognition result of method using convolutional neural network is better than other algorithms in EPS gesture signal recognition.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.1
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• pp.167-177
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• 2018

As the number of attacks on vehicles has increased, studies on CAN-based security technologies are actively being carried out. However, since the upper layer protocol of CAN differs for each vehicle manufacturer and model, there is a great difficulty in researches such as developing anomaly detection for CAN or finding vulnerabilities of ECUs. In this paper, we propose a method to infer the detailed structure of the data field of CAN frame by analyzing CAN trace to mitigate this problem. In the existing Internet environment, many researches for reverse engineering proprietary protocols have already been carried out. However, CAN bus has a structure difficult to apply the existing protocol reverse engineering technology as it is. In this paper, we propose new field classification methods with low computation-cost based on the characteristics of data in CAN frame and existing field classification method. The proposed methods are verified through implementation that analyze CAN traces generated by simulations of CAN communication and actual vehicles. They show higher accuracy of field classification with lower computational cost compared to the existing method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.1
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• pp.176-183
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• 2013

This study is focused on analyzing the quality importance of hotel SNS(social network service). And by reviewing precedent papers and references regarding concept and quality factors about SNS in hotel industry, it drew proper criteria to select priorities and evaluate hotel SNS quality using AHP. The important factors based upon related theories are suggested in this paper such as information quality, system quality, service quality, interface quality and emotional quality. The survey for empirical study was executed with hotel employees and total 149 questionnaires were used for this study. We used AHP for statistical analysis, As the results, the most important factor is emotional quality factor and the next is interface quality factor.

• The KIPS Transactions:PartB
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• v.13B no.2 s.105
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• pp.171-178
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• 2006

Most approaches for extracting hypernyms of a noun from its definitions in an MRD rely on lexical patterns compiled by human experts. Not only these approaches require high cost for compiling lexical patterns but also it is very difficult for human experts to compile a set of lexical patterns with a broad-coverage because in natural languages there are various expressions which represent same concept. To alleviate these problems, this paper proposes a new method for extracting hypernyms of a noun from its definitions in an MRD. In proposed approach, we use only syntactic (part-of-speech) patterns instead of lexical patterns in identifying hypernyms to reduce the number of patterns with keeping their coverage broad. Our experiment has shown that the classification accuracy of the proposed method is 92.37% which is significantly much better than that of previous approaches.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.247-249
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• 2004

마이크로어레이 기술은 근래에 개발된 신기술로써 동시에 수천-수만 개의 유전자 발현을 측정할 수 있어 다양한 생물학적 연구에 이용되고 있다. 여러 단계의 실험 과정과 이를 통해 얻은 다량의 데이터를 처리하기 위해서는 이를 효율적으로 관리. 저장, 분석할 수 있는 통할 정보 관리 시스템을 필요로 한다. 현재 외국에서는 몇몇 관리시스템이 개발되어 있고. 국내에서도 WEMA 등이 있지만 아직 데이터 관리부분에 기능이 치우쳐 있다. 따라서 우리는 복잡한 자료구조를 가지는 마이크로어레이의 실험 정보와 각 단계별 처리 정보 등을 사용자의 관점에서 효과적이고 체계적으로 관리할 수 있고, 데이터 정규화 및 다양한 통계적 분석 기능을 갖춰 불필요한 시간과 비용을 줄임으로써 마이크로어레이 연구에 도움을 주고자 통합 분석관리 시스템 cMAMS (cDNA Microarray Analysis and Management System)를 개발하였다. 웹 기반으로 구현된 cMAMS는 데이터를 저장, 관리하는 부분과 데이터를 분석하는 부분, 그리고 모든 관련 점보가 저장되는 데이터베이스 부분으로 구성되어 있다 데이터관리부분에서는 WEMA의 계층적 데이터구조론 도입해 관리의 효율성을 높이고 시스템의 이용자를 시스템운영자, 프로젝트관리자, 일반사용자로 구분하여 데이터 접근을 제한함으로써 보안성을 높였다. 통계처리 언어 R로 구현된 데이터분석 부분은 7 단계의 다양한 분석(전처리 정규화, 가시화, 군집분석. 판별분석, 특이적 발현 유전자 선뿐, 마이크로어레이 간의 상판분석)이 가능하도록 구현하였고, 분석결과는 데이터베이스에 저장되어 추후에 검토 및 연구자간의 공유가 가능하도록 하였다. 데이터베이스는 실험정보가 저장된 데이터베이스, 분석결과가 저장된 데이터베이스, 그리고 유전자 정보 탐색을 위한 데이터베이스로 분류해 데이터를 효율적으로 관리할 수 있게 하였다. 본 시스템은 LiNUX를 운영체계로 하고 데이터베이스는 MYSQL로 하여 JSP, Perl. 통계처리 언어인 R로 구현되었다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.8
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• pp.1493-1499
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• 2007

Real-time applications in a wireless sensor network environment require real-time transmissions from sensing nodes to sink nodes. Existing congestion control mechanisms have treated congestion problems in sensor networks, but they only adjust the reporting frequency or the sending rate in intermediate nodes. They were not suitable for real-time applications from the transmission delays point of view. In this paper, we suggest a new mechanism that can reduce the transmission delay and can increase the throughput for real-time applications in sensor network. This mechanism classifies data on the real-time characteristics, processes the data maintaining the real-time characteristics prior to the other data such as the non real-time data or the data lost the real-time characteristics. A modified frame format is also proposed in order to apply the mechanism to IEEE 802.15.4 MAC layer. The simulation based on ns-2 is accomplished in order to verify the performance of the suggested scheme from transmission delay and throughput standpoints. The simulation results show that the proposed algorithm has a better performance specifically when It applies to the real-time applications in sensor networks.