• Journal of the Korea Convergence Society
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• v.8 no.2
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• pp.27-33
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• 2017

To efficiently provide cloud computing services to users over the Internet, IT resources must be configured in the data center based on virtualization and distributed computing technology. This paper focuses specifically on the problem that new training data can be added at any time in a wide range of fields, and new attributes can be added to training data at any time. In such a case, rule generated by the training data with the former attribute set can not be used. Moreover, the rule can not be combined with the new data set(with the newly added attributes). This paper proposes further development of the new inference engine that can handle the above case naturally. Rule generated from former data set can be combined with the new data set to form the refined rule.

• The KIPS Transactions:PartD
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• v.8D no.4
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• pp.421-426
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• 2001

A formal development method is used to develop software rigorously and systematically. In a formal development method, we specify system by a formal specification language and gradually develop the system more concretely until we can implement the system. VDM is one of formal specification languages. VDM uses mathematical data structures such as sets, sequences, and maps to specify the system, but most programming languages do not have such data structures. Therefore, these data structures should be converted. We can convert mathematical data structures in VDM to a linked list, a data structure in a programming language. In this article, we propose a method to convert a set, a sequence, and a map in VDM to a linked list in a programming language and prove the correctness of this conversion mathematically.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.353-360
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• 2023

This paper explores notable shifts in the restaurant startup market following the lifting of social distancing measures. Key trends identified include an escalated interest in startups, a heightened focus on the quality and diversity of food, a relative decline in the importance of delivery services, and a growing interest in specific industry sectors. The study's data collection spanned three years, from April 2021 to May 2023, encompassing the period before and after social distancing. Data were sourced from a range of online platforms, including blogs, news sites, cafes, web documents, and intellectual forums, provided by Naver, Daum, and Google. From this collected data, the top 50 words were identified through a refinement process. The analysis was structured around the social distancing application period, comparing data from April 2021 to April 2022 with data from May 2022 to May 2023. These observed trend changes provide founders with valuable insights to seize new market opportunities and formulate effective startup strategies. In summary, We offer crucial insights for founders, enabling them to comprehend the evolving dynamics in food service startups and to adapt their strategies to the current market environment.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.166-171
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• 2024

Recently, there has been an increasing trend in the role of social media in tourism marketing. We analyze changes in tourism marketing trends using tourism marketing keywords through social media networks. The aim is to understand marketing trends based on the analyzed data and effectively create, maintain, and manage customers, as well as efficiently supply tourism products. Data was collected using web data from platforms such as Naver, Google, and Daum through TexTom. The data collection period was set for one year, from December 1, 2022, to December 1, 2023. The collected data, after undergoing refinement, was analyzed as keyword networks based on frequency analysis results. Network visualization and CONCOR analysis were conducted using the Ucinet program. The top words in frequency were 'tourists,' 'promotion,' 'travel,' and 'research.' Clusters were categorized into four: tourism field, tourism products, marketing, and motivation for visits. Through this, it was confirmed that tourism marketing is being conducted in various tourism sectors such as MICE, medical tourism, and conventions. Utilizing digital marketing via online platforms, tourism products are promoted to tourists, and unique tourism products are developed to increase city branding and tourism demand through integrated tourism content. We identify trends in tourism marketing, providing tourists with a positive image and contributing to the activation of local tourism.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.103-106
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• 2004

Extrapolation off the boundaries of scattered data is an intrinsic feature of interpolation. However, extrapolation causes serious problems in stereo-vision and mapping, which has not been investigated carefully. In this paper, we present novel schemes to eliminate the extrapolation effects for the generation of a digital elevation model (DEM). As a first step, we devise point distribution criteria, namely COG (Center of Gravity) and ECI (Empty Center Index), and apply rigorous and robust elimination based on the criteria. Compared with other methods, the proposed schemes are computationally fast and applicable to a wide range of interpolation techniques.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.515-520
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• 2012

In brain computer interface (BCI) system, the most important part is classification of human thoughts in order to translate into commands. The more accuracy result in classification the system gets, the more effective BCI system is. To increase the quality of BCI system, we proposed to reduce noise and artifact from the recording data to analyzing data. We used auditory stimuli instead of visual ones to eliminate the eye movement, unwanted visual activation, gaze control. We applied independent component analysis (ICA) algorithm to purify the sources which constructed the raw signals. One of the most famous spatial filter in BCI context is common spatial patterns (CSP), which maximize one class while minimize the other by using covariance matrix. ICA and CSP also do the filter job, as a raw filter and refinement, which increase the classification result of linear discriminant analysis (LDA).

• The Journal of Information Technology and Database
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• v.4 no.2
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• pp.33-45
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• 1998

Database summarization is the procedure to obtain generalized and representative descriptions expressing the content of a large amount of database at a glance. We present a top-down summary refinement procedure to discover database summaries. The procedure exploits attribute concept hierarchies that represent ISA relationships among domain concepts. It begins with the most generalized summary and proceeds to find more specialized ones by stepwise refinements. This top-down paradigm reveals at least two important advantages compared to the previous bottom-up methods. Firstly, it provides a natural way of reflecting the user's own discovery preference interactively. Secondly, it does not produce too large intermediate result that makes it hard for the bottom-up approach to be applied in practical environment. The proposed procedure can also be easily extended for distributed databases. Information content measure of a database summary is derived in order to identify more informative summaries among the discovered results.

• Journal of the Korean Solar Energy Society
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• v.23 no.4
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• pp.21-27
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• 2003

The comparative performance of the WAsP in calculating the wind climate in complex terrain has been examined in order to test the predictability of the wind resource assessment computer code in our country. An analysis was carried out of predicted and experimental 10-min averaged wind data collected over 8 months at four monitoring sites in SongDang province, Jeju island, composed of sea, inland flat terrain, a high and a low slope craters. The comparisons show that the WAsP preditions give better agreement with experimental data by adjusting the roughness descriptions, the obstacle list.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.1
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• pp.41-49
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• 2010

In this paper, we propose a hierarchical RAM simulation model framework which are used to analyze the RAM specifications on the concept refinement phase. The hierarchical RAM simulation model framework consists of RAM simulation models, class library and each model's input and output data lists. The hierarchical RAM simulation models are co-operated with 3 kinds of model - type I, II, III. Type I, II models are used to analyze the target operational availability and Type III is used to establish the initial RAM specifications. Each model's input and output data lists are defined by considering each model's purpose of RAM analysis. The class library is arranged with each model's classes for implementing the hierarchical simulation models. The proposed framework may be applied for executing the RAM activities effectively.

• International Journal of CAD/CAM
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• v.7 no.1
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• pp.103-112
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• 2007

This paper presents a practical approach for surface reconstruction from unoriented point clouds. Instead of estimating local surface orientation, we first generate a set of depth images from the input point clouds, and a coarse mesh is then generated based on them by space carving techniques. The resultant mesh is progressively refined by local mesh refinement and optimization according to surface distance measure. A manifold mesh approximating the input points within an given tolerance is finally obtained. Our approach is easy to implement, but has the ability to outputs high quality meshes in different resolutions. We show that the proposed approach is not sensitive to several types of data disfigurement and is able to reconstruct models robustly from variance input data.