• Journal of KIISE
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• v.41 no.12
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• pp.1081-1089
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• 2014

Context-sensitive spelling-error correction methods are largely classified into rule-based methods and statistical data-based methods, the latter of which is often preferred in research. Statistical error correction methods consider context-sensitive spelling error problems as word-sense disambiguation problems. The method divides a vocabulary pair, for correction, which consists of a correction target vocabulary and a replacement candidate vocabulary, according to the context. The present paper proposes a method that integrates a word-phrase n-gram model into a conventional model in order to improve the performance of the probability model by using a correction vocabulary pair, which was a result of a previous study performed by this research team. The integrated model suggested in this paper includes a method used to interpolate the probability of a sentence calculated through each model and a method used to apply the models, when both methods are sequentially applied. Both aforementioned types of integrated models exhibit relatively high accuracy and reproducibility when compared to conventional models or to a model that uses only an n-gram.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.1
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• pp.62-66
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• 2009

Recently developed compilers perform some optimizations in order to speed up the execution time of source program. These optimizations require the transformation of the sequence of program statements. This transformation does not give any problems in a single-threaded program. However, the transformation gives some significant errors in a multi-threaded program. State-of-the-art model checkers such as Java-Pathfinder do not consider the transformation resulted in the optimization step in a compiler since they just consider a single memory model. In this paper, we describe a new technique which is based on SMT solver. The Java Memory Model Simulator based on SMT Solver can compute all possible output of given multi-thread program within one second which, in contrast, Traditional Java Memory Model Simulator takes one minute.

• The Korean Journal of Applied Statistics
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• v.24 no.4
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• pp.677-693
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• 2011

In this paper, we consider Bayesian approaches to zero inflated Poisson model, one of the popular models to analyze zero inflated count data. To generate posterior samples, we deal with a Markov Chain Monte Carlo method using a Gibbs sampler and an exact sampling method using an Inverse Bayes Formula(IBF). Posterior sampling algorithms using two methods are compared, and a convergence checking for a Gibbs sampler is discussed, in particular using posterior samples from IBF sampling. Based on these sampling methods, a real data analysis is performed for Trajan data (Marin et al., 1993) and our results are compared with existing Trajan data analysis. We also discuss model selection issues for Trajan data between the Poisson model and zero inflated Poisson model using various criteria. In addition, we complement the previous work by Rodrigues (2003) via further data analysis using a hierarchical Bayesian model.

• Journal of KIISE:Software and Applications
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• v.35 no.2
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• pp.105-117
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• 2008

Generally, project audit provides the service which accomplishes a project successfully by checking the management activity of information system project, indicating a controversial point and reflecting the improvement issues based on project audit check list. In addition, the projects are managed by using the project management maturity model based on process. However, the effect is not big as we except projects performance of real world. In this paper. to solve these problems, the project management maturity evaluation model which is connected with project audit check list and organizational maturity model survey items is designed. Thus, we propose the model which can improve the project performance through the project evaluation of customer's project and development part and the evaluation of organization level as we design that it is possible to not only audit the project but also evaluate it before and after the project.

• Journal of KIISE:Software and Applications
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• v.32 no.2
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• pp.119-127
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• 2005

Product line analysis is an activity for analyzing requirements, their relationships, and constraints in a product line before engineering product line assets (e.g., architectures and components). A feature-oriented commonality and variability analysis (called feature modeling) has been considered an essential part of product line analysis. Commonality and variability analysis, although critical, is not sufficient to develop reusable and adaptable product line assets. Dependencies among features and feature binding time also have significant influences on the design of product line assets. In this paper. we propose a feature-oriented product line analysis model that extends the existing feature model in terms of three aspects (i.e., feature commonality and variability, feature dependency, and feature binding time). To validate the consistency among the three aspects we formally define the feature-oriented product line analysis model and provide rules for checking consistency.

• Journal of Korea Society of Industrial Information Systems
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• v.26 no.1
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• pp.55-65
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• 2021

In this paper, a methodology for reinforcing reverse logistics (RL) activities in a closed-loop supply chain (CLSC) model is proposed. For the methodology, the activities of the recovery center (RC) which can be considered as one of the facilities in the RL are reinforced. By the reinforced activities in the RC, the recovered parts and products after checking and recovering processes of the returned product from customer can be reused in the forward logistics (FL) of the CLSC model. A mathematical formulation is suggested for representing the CLSC model with reinforced RL activities, and implemented using a hybrid genetic algorithm (HGA) approach. In numerical experiment, two different scales of the CLSC model are presented and the performance of the HGA approach is compared with those of some conventional approaches. The experimental results show that the former outperforms the latter in most of performance measures. The robustness of the CLSC model is also proved by regulating various rates of the recovered parts and products in the RC.

• Journal of Digital Contents Society
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• v.8 no.1
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• pp.93-106
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• 2007

Web Applications are rapidly increasing and the structure becomes very complicated. However, when users explore such complex Web applications, they cannot often grasp the current location and get the information that they want. Therefore, a novel approach to model the navigation of Web application contents is required. In this study, a framework has been presented for modeling adaptive context-based contents navigation of Web applications. The framework performs activities including navigation analysis, navigation design, and navigation realization. first, in navigation analysis domain is analyzed by using use case, focusing on navigation. Next, in navigation design three models have been produced: a navigation information model, a profile, and a navigation interface model. Finally, in navigation realization a Webpage navigation model and a component navigation model have been produced. In this work, several formal definitions and rules for checking validity of navigation model have also been provided.

• Management & Information Systems Review
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• v.24
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• pp.97-124
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• 2008

This study aimed to explore how the involvement of environment influenced eight subjects group. Thus, experiment was performed to clarify the role that the attitude of university student consumer plays in the communication process depending on the level of engagement of consumer in the environment and method to raise donation for preservation of environment. Analyzing as per the type of appeal, the mark in altruistic appeal type was higher in all variables than egoistic appeal type. Finally, checking the average mark of each variable as per the condition of donation, the value in unconditional donation was higher than in all variables than conditional donation. It was found 3 groups composed of 2 groups with high level of environmental engagement and 1 group with low level of environmental engagement were suitable to double mediation model among the 8 experimental groups. The group where double mediation model best corresponds than any other group was high level related to environment and the group that contacts altruistic appeal and the message in the form of conditional donation. It was also found that the group that has low level of environmental engagement and contacts egoistic appeal type and conditional donation shows the group that corresponds to double mediation model in the second place among the 8 groups. Finally, it was found that the group that has high level of environmental engagement and is stimulated by altruistic appeal and unconditional donation corresponds to double mediation model. Depending on the condition of message stimulation, unconditional donation is found to better correspond to double mediation model than conditional donation. However, opposite phenomena is observed when the level of environmental engagement is high and appeal type is egoistic. Namely, it was found that conditional donation better corresponds to double mediation model than unconditional donation.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.9
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• pp.379-390
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• 2019

In this paper, we propose a novel deep neural network model for Vision-and-Language Navigation (VLN) named LVLN (Landmark-based VLN). In addition to both visual features extracted from input images and linguistic features extracted from the natural language instructions, this model makes use of information about places and landmark objects detected from images. The model also applies a context-based attention mechanism in order to associate each entity mentioned in the instruction, the corresponding region of interest (ROI) in the image, and the corresponding place and landmark object detected from the image with each other. Moreover, in order to improve the success rate of arriving the target goal, the model adopts a progress monitor module for checking substantial approach to the target goal. Conducting experiments with the Matterport3D simulator and the Room-to-Room (R2R) benchmark dataset, we demonstrate high performance of the proposed model.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.358-362
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• 2004

Verification and testing are complementary techniques that are used to increase the level of confidence in the correct functioning of communication systems as prescribed by their specifications. This paper presents an experience of model checking for a formal railway signaling protocol specified in LTS (Labeled Transition System). This formal approach checks deadlock, livelock and reachability for the state and action to verify whether properties expressed in modal logic are true on specifications. We also propose a formal method for semi-automated test case generation for a railway signaling protocol described in I/O FSM (Input/Output Finite State Machine). This enables the generation of more complete and consistent test sequence for conformance testing. The above functions are implemented by C++ language and included within RSPVTE (Railway Signaling Protocol Verification and Testing Environment).