• Journal of KIISE:Software and Applications
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• v.26 no.12
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• pp.1455-1467
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• 1999

소프트웨어 품질을 정의하기 위한 여러 가지 소프트웨어 품질 모형(SQM : Software Quality Model)이 개발되어 왔다. 이 모형들은 두 가지 목적을 가진다. 한 가지는 소프트웨어 품질 측정이고, 또 다른 목적은 개발 프로세스에서의 소프트웨어 품질 제어이다. 국제 표준인 ISO/IEC 9126은 소프트웨어 측정을 위한 소프트웨어 품질 모형을 제시하였다. ISO/IEC 9126의 품질 모형은 사용 관점에서 소프트웨어 품질을 정의한 모형이다. 이 모형은 개발 프로세스에서의 품질 제어를 하는 측면에서는 불완전한 모형이다. 소프트웨어의 품질이 프로세스 내에서 어떻게 만들어지는지 볼 수 없는 모형이기 때문이다. 따라서, 개발 관점에서의 소프트웨어 품질 모형이 필요하다.본 논문에서는 사용 관점인 ISO/IEC 9126 품질 모형을 기반으로 하여 개발 관점에서의 소프트웨어 품질 모형을 제안한다. 이 모형은 ISO/IEC 9126과 같이 하위 품질 요소가 중복되지 않는 계층적 품질 모형이면서, 개발 프로세스 내에서 제어 가능한 제품 특성에 기반을 둔 개발 관점의 소프트웨어 품질 모형이다. 본 논문에서는 소프트웨어 품질 모형 구축 시, 품질 속성간의 선후조건관계를 설정하여 품질 속성간 중복되었던 제품 특성을 한 품질 속성 내 귀속시킨다. 품질 속성 별 제품 특성을 기반으로, 프로세스 내에서 제품 특성을 측정하는 메트릭스를 제안한다. 본 논문에서 제안한 품질 모형과 ISO/IEC 9126을 비롯한 기존 품질 모형과 비교 분석한다.Abstract Several SQMs(Software Quality Models) have been developed to define a software quality. These models have two goals. One is to measure a software quality, the other is to control a software quality. The SQM of ISO/IEC 9126 is defined from the user's viewpoint. This model is an incomplete model in controlling a software quality in the development process. Since this model cannot show how to build a high quality software, the SQM of the developer's view is needed.We suggest the SQM of the developer's view. This model is a completely hierarchical model and is based on product properties. For this model, we define implicative relations among quality attributes for 1:m relations of quality attributes and product properties. So, we solve the problem of a quality attribute overlapping with other quality attributes. We suggest metrics based on our SQMs. Further, we evaluate our SQM by comparing our SQM with other SQMs.

• Journal of Digital Convergence
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• v.14 no.7
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• pp.93-102
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• 2016

The purpose of this study is to examine the effects of the Mobile Smart-Work IT resources on the work efficiency based on moderating effects of the perceived usefulness in the Resource Based View. The study has academic meanings and practical implications that studied widely based on moderating effects of the perceived usefulness through the Hierarchical regression furthermore on the existing study on hypothesis by standard multiple regression. The results showed that IT Infrastructure in the Mobile Smart-work IT resources by moderating effects of the perceived usefulness was found to bring positive effect on individual work efficiency and teamwork efficiency. On the other hand Business Application was found to bring positive effect on teamwork efficiency. Therefore, we expect that business firm and employees actively use the effects of the perceived usefulness with the trust that Mobile Smart-work IT resources bring positive effects on the work efficiency. It can improve this work efficiency and lead to strengthening the firm competitiveness.

• Journal of Information Processing Systems
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• v.9 no.1
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• pp.53-68
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• 2013

We investigate the rate-compatible punctured convolutional (RCPC) codes concatenated with hierarchical QAM for designing a cross-layer unequal error protection scheme for H.264 coded sequences. We first divide the H.264 encoded video slices into three priority classes based on their relative importance. We investigate the system constraints and propose an optimization formulation to compute the optimal parameters of the proposed system for the given source significance information. An upper bound to the significance-weighted bit error rate in the proposed system is derived as a function of system parameters, including the code rate and geometry of the constellation. An example is given with design rules for H.264 video communications and 3.5-4 dB PSNR improvement over existing RCPC based techniques for AWGN wireless channels is shown through simulations.

• KEPCO Journal on Electric Power and Energy
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• v.2 no.1
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• pp.61-69
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• 2016

Understanding load patterns and customer classification is a basic step in analyzing the behavior of electricity consumers. To achieve that, there have been many researches about clustering customers' daily load data. Nowadays, the deployment of advanced metering infrastructure (AMI) and big-data technologies make it easier to study customers' load data. In this paper, we study load clustering from the view point of yearly and daily load pattern. We compare four clustering methods; K-means clustering, hierarchical clustering (average & Ward's method) and DBSCAN (Density-Based Spatial Clustering of Applications with Noise). We also discuss the relationship between clustering results and Korean Standard Industrial Classification that is one of possible labels for customers' load data. We find that hierarchical clustering with Ward's method is suitable for clustering load data and KSIC can be well characterized by daily load pattern, but not quite well by yearly load pattern.

• Journal of the Korea Computer Graphics Society
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• v.16 no.4
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• pp.25-33
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• 2010

With the popularization of digital photography, people are now capturing and storing far more photos than ever before. However, the enormous number of photos often discourages the users to identify desired photos. In this paper, we present a novel method for fast and intuitive browsing through large collections of geo-referenced photographs. Given a set of photos, we construct a hierarchical structure of clusters such that each cluster includes a set of spatially adjacent photos and its sub-clusters divide the photo set disjointly. For each cluster, we pre-compute its convex hull and the corresponding polygon area. At run-time, this pre-computed data allows us to efficiently visualize only a fraction of the clusters that are inside the current view and have easily recognizable sizes with respect to the current zoom level. Each cluster is displayed as a single polygon representing its convex hull instead of every photo location included in the cluster. The users can quickly transfer from clusters to clusters by simply selecting any interesting clusters. Our system automatically pans and zooms the view until the currently selected cluster fits precisely into the view with a moderate size. Our user study demonstrates that these new visualization and interaction techniques can significantly improve the capability of navigating over large collections of geo-referenced photos.

• Journal of the Korea Society of Computer and Information
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• v.16 no.2
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• pp.289-305
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• 2011

To efficiently analyze complex and voluminous data, OLAP systems increasingly provide functionalities for visual exploration of the data allowing end-users to navigate the desired view of the data cube. This paper only deals with data cubes whose schemas represented like the exclusive symmetric hierarchy which is not addressed by current OLAP implementations. This paper presents a conceptual classification of abstraction hierarchies, and an approach to navigating data cubes with a hierarchical visualization technique. The hierarchical visualization technique is developed by using the transitive closure of a binary relation. The approach is exemplified using a real-world study from the domain of national license administration.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1516-1529
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• 2023

In this paper, a motor gearbox fault-detection system based on a hierarchical flow-based model is proposed. The proposed system is used for the anomaly detection of a motion sound-based actuator module. The proposed flow-based model, which is a generative model, learns by directly modeling a data distribution function. As the objective function is the maximum likelihood value of the input data, the training is stable and simple to use for anomaly detection. The operation sound of a car's side-view mirror motor is converted into a Mel-spectrogram image, consisting of a folding signal and an unfolding signal, and used as training data in this experiment. The proposed system is composed of an encoder and a decoder. The data extracted from the layer of the pretrained feature extractor are used as the decoder input data in the encoder. This information is used in the decoder by performing an interlayer cross-scale convolution operation. The experimental results indicate that the context information of various dimensions extracted from the interlayer hierarchical data improves the defect detection accuracy. This paper is notable because it uses acoustic data and a normalizing flow model to detect outliers based on the features of experimental data.

• Journal of the Ergonomics Society of Korea
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• v.12 no.1
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• pp.75-86
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• 1993

Hypermedia systems allow the retrieval and representation of multimedia in- formation such as text, graphics, image and voice/sound using navigation and browsing mechanisms. In this study we developed a hypermedia system which provides hierarchical group, local map and cluster view for effective navigation in hyperspace. The system also supports hot link, reference link, move-to link and multiple link to browse the multimedia information space effectively. This system has been designed to integrate the navigation, browsing and searching function of the hypermedia system in hyman factor perspective and provides the user-friendly user interface mechanism.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10a
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• pp.102-104
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• 1999

인터넷의 발전으로 WWW상에서 지도 정보를 서비스하는 사이트들이 늘어나고 있다. 본 논문은 이러한 WWW상의 지리 정보 서비스를 확장한 도로 주행 안내 시스템의 구현에 관하여 기술한다. 도로 주행 안내 시스템은 도로, 건물 등의 지리 정보를 표시해주며 사용자의 최단 경로질의를 받고 빠른 시간내에 최단경로를 탐색할 수 있어야 한다. 본 연구에서는 이러한 요구를 수용할 수 있도록 OODBMS, CORBA, Java를 사용하여 WWW상의 도로 주행 안내 시스템을 설계 및 구현하였다. 이를 위해 이 논문에서는 도로 데이터 캐싱과 그래프 모델링, HEPV (Hierarchical Encoded Path View) 알고리즘 구현 등의 사항을 기술하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05a
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• pp.106-109
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• 2004

Many reported methods assume that the faces in an image or an image sequence have been identified and localization. Face detection from image is a challenging task because of variability in scale, location, orientation and pose. In this paper, we present an efficient linear discriminant for multi-view face detection. Our approaches are based on linear discriminant. We define training data with fisher linear discriminant to efficient learning method. Face detection is considerably difficult because it will be influenced by poses of human face and changes in illumination. This idea can solve the multi-view and scale face detection problem poses. Quickly and efficiently, which fits for detecting face automatically. In this paper, we extract face using fisher linear discriminant that is hierarchical models invariant pose and background. We estimation the pose in detected face and eye detect. The purpose of this paper is to classify face and non-face and efficient fisher linear discriminant..