• 산업경영시스템학회지
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• 제23권60호
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• pp.83-89
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• 2000

As customer's needs change rapidly in recent days, the evaluation scale about service quality is changing against the variation of the customer's needs. It is fact that the need of change which established evaluation ways about service quality rise more and more. 6-Sigma activity, called "most innovative management strategy in 20th Century", have many problems apply to service company. The important one between these problems is the problem about Critical To Quality(CTQ) Selection caused from the absence of more precise evaluation system. The objective of this study is the development of methodology for CTQ selection coincide to service company. It is the basic logic that the way to regard MOT mainly effects about total customer satisfaction index(CSI) as CTQ, after the development of the evaluation system based on MOT with customers. Also, the study focused on the case of department store progress to exhibit the reasonableness of this logic.

• 정보처리학회논문지B
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• 제19B권4호
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• pp.237-242
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• 2012

웹 문서 정보 서비스는 관리자의 효율적 문서관리와 사용자의 문서검색 편의성을 위해 문서 분류 시스템을 필요로 한다. 기존의 문서 분류 시스템은 분류하고자 하는 문서 내 선택된 자질어의 개수가 적거나, 특정 범주의 문서 비율이 높아 그 범주에서 대부분의 자질어가 선택되어 모델이 생성된 경우 분류 정확도가 저하되는 문제점을 가진다. 이러한 문제점을 해결하기 위해 본 논문에서는 'Modified ECCD' 기법 및 '문서별 범주 가중치' 특징 변수를 사용한 문서 분류 시스템을 제안한다. 실험 결과, 제안 방법인 'Modified ECCD' 기법이 ${\chi}^2$ 및 ECCD 기법에 비해 높은 분류 성능을 보였으며, '문서별 범주 가중치' 특징 변수를 'Modified ECCD' 기법으로 선택된 자질어 변수에 추가하여 학습하였을 경우에 더 높은 분류 성능을 보였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권10호
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• pp.5023-5038
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• 2017

Big data is an emerging technology which deals with wide range of data sets with sizes beyond the ability to work with software tools which is commonly used for processing of data. When we consider a huge network, we have to process a large amount of network information generated, which consists of both normal and abnormal activity logs in large volume of multi-dimensional data. Intrusion Detection System (IDS) is required to monitor the network and to detect the malicious nodes and activities in the network. Massive amount of data makes it difficult to detect threats and attacks. Sequential Pattern mining may be used to identify the patterns of malicious activities which have been an emerging popular trend due to the consideration of quantities, profits and time orders of item. Here we propose a sequential pattern mining algorithm with fuzzy logic feature selection and fuzzy weighted support for huge volumes of network logs to be implemented in Apache Hadoop YARN, which solves the problem of speed and time constraints. Fuzzy logic feature selection selects important features from the feature set. Fuzzy weighted supports provide weights to the inputs and avoid multiple scans. In our simulation we use the attack log from NS-2 MANET environment and compare the proposed algorithm with the state-of-the-art sequential Pattern Mining algorithm, SPADE and Support Vector Machine with Hadoop environment.

• 한국통신학회논문지
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• 제39B권12호
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• pp.870-872
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• 2014

본 논문에서는 피어의 소모 에너지와 잔여 에너지를 고려한 비용함수를 설계하고 시스템 내에 비용이 최소인 피어가 부모 피어로 선택될 수 있는 분산적 부모 피어 결정 방법을 제안한다. 각 피어가 자신의 이웃 피어 정보만을 이용하여 비용이 최소인 이웃 피어를 부모 피어로 선정하는 기존 기법과는 달리 제안 기법은 피어들 사이에 집단지성을 구축하고 이를 통해 부모 피어를 결정한다. 집단지성을 형성하여 부모 피어 검색 범위를 분산적으로 확장함으로써 제안기법은 기존 기법에 비해 최소 비용 피어가 부모 피어로 선택될 확률을 증가시키며 알고리즘 운영을 위한 시그널링 부하를 감소시킨 다는 것을 모의실험을 통해 검증하였다.

• 한국측량학회지
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• 제9권2호
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• pp.127-138
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• 1991

본 연구는 지형정보시스템을 활용한 최적 노선선정에 관한 연구이다. 일반적으로 노선의 선정은 후보노선대, 최적노선대, 최적노선의 선정 순으로 이루어지는데 본 연구에서는 노선선정계획의 마지막 부분인 최적노선선정부분을 고려하였다. 최적노선의 선정은 연구대상지역을 일정한 크기의 정규형격자로 구분하고, 각 정규형격자에 토지이용현황, 지가, 경상도 등을 고려하여 얻어진 가중치를 적용하였다. 이를 지형 정보시스템의 속성 데이타로 활용하여 노선선정에 적용되는 가중치의 특정부분으로 고려하고, 세개의 노선을 선정하였다. 이들 세개의 노선을 비교ㆍ분석하여 실제노선의 선정과정에서 지형정보시스템의 활용 가능성을 제시하고자 하였다.

• 디지털산업정보학회논문지
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• 제10권1호
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• pp.99-104
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• 2014

Nowadays, various researches fulfill in many communication engineering area for B4G (Beyond Forth Generation). Next LTE-A (Long Term Evolution Advanced), MU-MIMO (Multi-User Multi Input Multi Output) method raises to upgrade throughput performance. However, the method of user selection is not decided because of many types and discussions in MU-MIMO system. Many existing methods are powerful for enhancing performance but have various restrictions in practical implementation. Fairness problem is primary restriction in this area. Existing papers emphasis algorithm to increase sum-rate but we introduce an algorithm about dealing with fairness problem for real commercialization implementation. Therefore, this paper introduces new user selection method in MU-MIMO system. This method overcomes a fairness problem in SUS (Semiorthogonal User Selection) algorithm. We can use the method to get a similar sum-rate with SUS and a high fairness performance. And this paper uses a hybrid method with SC-SUS (Superposition Coding SUS) algorithm and SUS algorithm. We find a threshold value of optimal performance by experimental method. We show this performance by computer simulation with MATLAB and analysis that results. And we compare the results with another paper's that different way to solve fairness problem.

• KIEAE Journal
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• 제7권6호
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• pp.91-97
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• 2007

This research examines the characteristics of the "rammed earth form" based on the criteria for the selection of forms. For this purpose, the paper first reviews the characteristics and orientation of the earth-construction and looks into the outline, the prerequisite, the current status and the tendency of the rammed earth form system through previous studies. Consequently, we aims to contribute to the criteria for the selection of rammed earth forms in the future through a comparative analysis of the construction cost, quality, safety and easiness of works between the veneer board form and the euroform, which are most widely used at earth housing project in the domestic country. The results reveals that the euroform is better than the veneer board with 21% of total cost in the cost analysis. But this better than that in the side of easiness of construction. In both cases, the buckling of wall panel form and the labor-oriented characteristics of the methods are the future research issues in the rammed earth form system.

• International Journal of Quality Innovation
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• 제3권2호
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• pp.113-131
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• 2002

The relationships among multi-dimensional data (such as medical examination data) with ambiguity and variation are difficult to explore. The traditional approach to building a data classification system requires the formulation of rules by which the input data can be analyzed. The formulation of such rules is very difficult with large sets of input data. This paper first describes two classification approaches using back-propagation (BP) neural network and Mahalanobis distance (MD) classifier, and then proposes two classification approaches for multi-dimensional feature selection. The first one proposed is a feature selection procedure from the trained back-propagation (BP) neural network. The basic idea of this procedure is to compare the multiplication weights between input and hidden layer and hidden and output layer. In order to simplify the structure, only the multiplication weights of large absolute values are used. The second approach is Mahalanobis-Taguchi system (MTS) originally suggested by Dr. Taguchi. The MTS performs Taguchi's fractional factorial design based on the Mahalanobis distance as a performance metric. We combine the automatic thresholding with MD: it can deal with a reduced model, which is the focus of this paper In this work, two case studies will be used as examples to compare and discuss the complete and reduced models employing BP neural network and MD classifier. The implementation results show that proposed approaches are effective and powerful for the classification.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권5호
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• pp.2469-2490
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• 2019

A low-energy adaptive clustering hierarchy (LEACH) protocol is a low-power adaptive cluster routing protocol which was proposed by MIT's Chandrakasan for sensor networks. In the LEACH protocol, the selection mode of cluster-head nodes is a random selection of cycles, which may result in uneven distribution of nodal energy and reduce the lifetime of the entire network. Hence, we propose a new selection method to enhance the lifetime of network, in this selection function, the energy consumed between nodes in the clusters and the power consumed by the transfer between the cluster head and the base station are considered at the same time. Meanwhile, the improved FTBA algorithm integrating the curve strategy is proposed to enhance local and global search capabilities. Then we combine the improved BA with LEACH, and use the intelligent algorithm to select the cluster head. Experiment results show that the improved BA has stronger optimization ability than other optimization algorithms, which the method we proposed (FTBA-TC-LEACH) is superior than the LEACH and LEACH with standard BA (SBA-LEACH). The FTBA-TC-LEACH can obviously reduce network energy consumption and enhance the lifetime of wireless sensor networks (WSNs).

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권11호
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• pp.5276-5298
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• 2019

Internet of Things (IoT) based sensor networks have gained unprecedented popularity in recent years. With the exponential explosion of the objects (sensors and mobiles), the bandwidth and the speed of data transmission are dwarfed by the anticipated emergence of IoT. In this paper, we propose a novel heterogeneous IoT model integrated the power line communication (PLC) and WiFi network to increase the network capacity and cope with the rapid growth of the objects. We firstly propose the mean transmission delay calculation algorithm based the 3D Markov chain according to the multi-priority of the objects. Then, the attractor selection algorithm, which is based on the adaptive behavior of the biological system, is exploited. The combined the 3D Markov chain and the attractor selection model, named MASM, can select the optimal path adaptively in the heterogeneous IoT according to the environment. Furthermore, we verify that the MASM improves the transmission efficiency and reduce the transmission delay effectively. The simulation results show that the MASM is stable to changes in the environment and more applicable for the heterogeneous IoT, compared with the other algorithms.