• Journal of Intelligence and Information Systems
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• v.14 no.4
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• pp.69-87
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• 2008

The Web is evolving toward the Semantic Web. Ontologies are considered as a crucial component of the Semantic Web since it is the backbone of knowledge representation for this Web. However, most of these ontologies are still built manually. Manual building of an ontology is time-consuming activity which requires many resources. Consequently, the need for automatic ontology extraction tools has been increased for the last decade, and many tools have been developed for this purpose. Yet, there is no comprehensive framework for evaluating such tools. In this paper, we proposed a set of criteria for evaluating ontology extraction tools and carried out an experiment on four popular ontology extraction tools (i.e., OntoLT, Text-To-Onto, TERMINAE, and OntoBuilder) using our proposed evaluation framework. The proposed framework can be applied as a useful benchmark when developers want to develop ontology extraction tools.

• International journal of advanced smart convergence
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• v.10 no.3
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• pp.257-278
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• 2021

As the definition of the vendor-oriented implementation method, which was utilized in adopting an ERP system, has been centered around the project construction business, it was difficult for the EPR adopting organization to systematically prepare ERP projects and have enough deliberative opportunities to change-related policies. Furthermore, this method does not have a fully standardized construction process. Accordingly, by defining an organization that wants to adopt an ERP system as a customer, this paper develops the customer-based ERP construction process framework that assists both customers and developers who construct the system. For this purpose, this paper reviews the previous research and collects the construction processes of the commercial ERP SW vendor and ERP construction cases while proposing the three-layer process framework to construct ERP through the KJ method. The ERP process framework consists of 7 processes, 32 activities, 141 tasks while providing definitions for concepts of each component. Furthermore, the proposed processes and phases were set in order of the recommended execution, while the activities were suggested as an open-ended type so that the application and usability can be increased and polished by reflecting experts' opinions. The contribution of this study is to standardize the ERP project process by transforming the previous supplier-based ERP construction method into the customer-based one while providing important procedure and activity frameworks that apply to diverse ERP solutions per vendor. At the same time, this study provides an theoretical foundation to develop the construction process for the customer -based Cloud ERP. In practice, At the beginning of the ERP system construction project, it provides communication or process tailoring tools for the stakeholder.

• Journal of KIISE:Software and Applications
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• v.36 no.5
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• pp.386-395
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• 2009

Business entities with which most service components interact are kind of cross-cutting concerns in a multi-layered distributed application architecture. When business entities are modified, service components related to them should also be modified, even though they implement common functions of the application framework. This paper proposes what we call DTT (Data Type-Tolerant) component model to process the variability of business entities, or externalized data, which feature modern application architectures. The DTT component model expresses the data variability of product lines at the implementation level by means of SCDTs (Self-Contained Data Types) and variation point interfaces. The model improves the efficiency of application engineering through data type converters which support type conversion between SCDTs and business entities of particular applications. The value of this model lies in that data and functions are coupled locally in each component again by allowing service components to deal with SCDTs only instead of externalized business eutities.

• Journal of Korea Technology Innovation Society
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• v.18 no.3
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• pp.416-443
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• 2015

The resource-based view (RBV) explains that the competitive advantage is mainly based on the resources which have strategic characteristics. Therefore, finding, developing and maintaining strategically valuable resources has been one of main research topics and a starting point in the corporate strategy structure in RBV. In this regards, attempts to recognize strategically valuable resources have been one of crucial issues in RBV researches. Especially, Barney's VRIO has been widely used as a practical tool for finding strategically valuable resources. However, empirical studies on VRIO framework's effectiveness have not been sufficiently implemented, and there has been no proven relation among the components of the VRIO so far. This is mainly because the concepts or definitions on core components of the VRIO - Value, Rareness, Inimitability, and Organization - are too comprehensively explained and measurements of each component cannot be easily quantified. Considering these, this paper presents empirical results of the relation between VRIO components and competitive advantage, and tests effectiveness of VRIO Framework with utilizing sufficient technology evaluation cases and financial statements of 2,252 technology based SMEs in Korea. As a result, the components of the VRIO have a positive influence on competitive advantage. The attributes of strategic resources - Value, Rareness, and Inimitability - have a statistically meaningful positive effect on organization, while organization has a positive effect on the competitive advantage serving as a parameter between the attributes of strategic resources and competitive advantage.

• Communications for Statistical Applications and Methods
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• v.12 no.3
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• pp.759-771
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• 2005

Twin studies are one of the most widely used methods for quantifying the influence of genetic and environmental factors on some traits such as a life span or a disease. In this paper we propose a genetic mixed linear model for twin survival time data, which allows us to separate the genetic component from the environmental component. Inferences are based upon the hierarchical likelihood (h-likelihood), which provides a statistically efficient and simple unified framework for various random-effect models. We also propose a simple and fast computation method for analyzing a large data set on twin survival study. The new method is illustrated to the survival data in Swedish Twin Registry. A simulation study is carried out to evaluate the performance.

• Journal of Electrical Engineering and Technology
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• v.12 no.4
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• pp.1657-1662
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• 2017

Facial expression recognition systems using video devices have emerged as an important component of natural human-machine interfaces which contribute to various practical applications such as security systems, behavioral science and clinical practices. In this work, we present a new method to analyze, represent and recognize human facial expressions using a sequence of facial images. Under our proposed facial expression recognition framework, the overall procedure includes: accurate face detection to remove background and noise effects from the raw image sequences and align each image using vertex mask generation. Furthermore, these features are reduced by principal component analysis. Finally, these augmented features are trained and tested using Hidden Markov Model (HMM). The experimental evaluation demonstrated the proposed approach over two public datasets such as Cohn-Kanade and AT&T datasets of facial expression videos that achieved expression recognition results as 96.75% and 96.92%. Besides, the recognition results show the superiority of the proposed approach over the state of the art methods.

• Journal of Computing Science and Engineering
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• v.5 no.3
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• pp.223-235
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• 2011

Performing approximate data matching has always been an intriguing problem for both industry and academia. This task becomes even more challenging when the requirement of data privacy rises. In this paper, we propose a novel technique to address the problem of efficient privacy-preserving approximate record linkage. The secure framework we propose consists of two basic components. First, we utilize a secure blocking component based on phonetic algorithms statistically enhanced to improve security. Second, we use a secure matching component where actual approximate matching is performed using a novel private approach of the Levenshtein Distance algorithm. Our goal is to combine the speed of private blocking with the increased accuracy of approximate secure matching.

• The Journal of the Acoustical Society of Korea
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• v.25 no.3E
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• pp.89-94
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• 2006

For audio indexing and targeted search of specific audio or corresponding visual contents, the MPEG-7 standard has adopted a sound classification framework, in which dimension-reduced Audio Spectrum Projection (ASP) features are used to train continuous hidden Markov models (HMMs) for classification of various sounds. The MPEG-7 employs Principal Component Analysis (PCA) or Independent Component Analysis (ICA) for the dimensional reduction. Other well-established techniques include Non-negative Matrix Factorization (NMF), Linear Discriminant Analysis (LDA) and Discrete Cosine Transformation (DCT). In this paper we compare the performance of different dimensional reduction methods with Gaussian mixture models (GMMs) and HMMs in the classifying video sound clips.

• Wind and Structures
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• v.31 no.5
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• pp.381-392
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• 2020

Despite that the failure of sign structure may not have disastrous consequence, its sheer number still ensures the need for rigorous safety standard to regulate their maintenance and construction. During its service life, a sign structure is subject to extensive wind load, sometimes well over its permissible design load. A fragility analysis of a sign structure offers a tool for rational decision making and safety evaluation by using a probabilistic framework to consider the various sources of uncertainty that affect its performance. Wind fragility analysis was used to determine the performance of sign structure based on the performance of its connection components. In this study, basic wind fragility concepts and data required to support the fragility analysis of the sign structure such as sign panel's parameters, connection component's parameters, as well as wind load parameters were presented. Fragility and compound fragility analysis showed disparity between connection component. Additionally, reinforcement of the connection system was introduced as an example of the utilization of wind fragility results in the retrofit decision making.

• Earthquakes and Structures
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• v.5 no.3
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• pp.359-378
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• 2013

The problem of identification of multi-component and (or) spatially varying earthquake support motions based on measured responses in instrumented structures is considered. The governing equations of motion are cast in the state space form and a time domain solution to the input identification problem is developed based on the Kalman and particle filtering methods. The method allows for noise in measured responses, imperfections in mathematical model for the structure, and possible nonlinear behavior of the structure. The unknown support motions are treated as hypothetical additional system states and a prior model for these motions are taken to be given in terms of white noise processes. For linear systems, the solution is developed within the Kalman filtering framework while, for nonlinear systems, the Monte Carlo simulation based particle filtering tools are employed. In the latter case, the question of controlling sampling variance based on the idea of Rao-Blackwellization is also explored. Illustrative examples include identification of multi-component and spatially varying support motions in linear/nonlinear structures.