• Water for future
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• v.23 no.4
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• pp.421-434
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• 1990

The problems of hydrologic similarity among river basins was analyzed by a geomorphologic response model using Hortons*s ordering scheme. The Nash model was used for deriving the geomorphologic response function, and for the optimization of the responsefunction, imcomplete gamma function andRosso*s regression equation were used. The application of this method was tested on some observed flood data of Pyungchang river basin and Wi Stream basin and Bocheong stream, and predictions of hydrologic response were compared with that of the Moment method. The results show that the proposed model and dimensionless instantaneous unit hydrograph can be used for the runoff analysis of an ungauged basin and the analysis of hydrologic similarity.

• Transactions of Materials Processing
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• v.10 no.1
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• pp.67-74
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• 2001

The cold forging process to produce a long-neck flange is investigated by using model material test. The two stage process with optimum design condition is examined using plasticine, which is suitable to model steel at room temperature. The similarity theory is employed to estimate the forging load of each sequence by strict application of similarity condition between steel(AISI 1015) and plasticine material The model test results are compared with the simulation results and shows good agreement. The proper forging process with least forming energy can be resulted in $25^{\circ}$ of extrusion semi-die angle.

• Asia pacific journal of information systems
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• v.30 no.4
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• pp.695-718
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• 2020

Based on the Construal Level Theory, we aim to study a most favorable fit among the advertising model, media type, and message construals, which are important factors in an advertisement. A two (social distance of the ad model in an ad: distal (low similarity) vs proximal (high similarity) by two (social distance of a media type: distal (portal) vs. proximal (SNS)) by two (message construal: abstract vs concrete) laboratory experiment was conducted to examine attitude changes on ad messages. The results show that abstract messages were more effective in attitude toward advertisement and purchase intention under the distal social distance (i.e. advertising model in low-similarity and portal media type) while concrete messages were so under the proximal social distance and SNS media type.

• Journal of Information Technology Applications and Management
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• v.28 no.5
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• pp.41-50
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• 2021

As COVID-19 spread widely, and rapidly, the number of misinformation is also increasing, which WHO has referred to this phenomenon as "Infodemic". The purpose of this research is to develop detection and rectification of COVID-19 misinformation based on Open-domain QA system and text similarity. 9 testing conditions were used in this model. For open-domain QA system, 6 conditions were applied using three different types of dataset types, scientific, social media, and news, both datasets, and two different methods of choosing the answer, choosing the top answer generated from the QA system and voting from the top three answers generated from QA system. The other 3 conditions were the Closed-Domain QA system with different dataset types. The best results from the testing model were 76% using all datasets with voting from the top 3 answers outperforming by 16% from the closed-domain model.

• Journal of Advanced Marine Engineering and Technology
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• v.34 no.2
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• pp.275-281
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• 2010

In this paper, a geometric similarity law is introduced to the performance test of a large-sized silencer used in ship engine or plant system. A test of scale-down model enable to yield the cost and time saving in developing large-sized silencer considerably. Two types of silencer, resonator and expansion chamber, were analyzed by a theoretical method and an acoustical FEM(finite element method) in order to obtain geometric similarity variables. A method is proposed to estimate the transmission loss of prototype model using the test results of scale-down model. Two actual large-sized silencer, which consist of resonator and expansion chamber, were analysed by an acoustical FE analysis. Consequently, the proposed method predicts effectively the performance of prototype silencers using those of scale-down models.

• The Journal of Korean Institute of Information Technology
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• v.16 no.12
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• pp.109-114
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• 2018

Collaborative filtering has been widely utilized in recommender systems as typical algorithm for outstanding performance. Since it depends on item rating history structurally, The more sparse rating matrix is, the lower its recommendation accuracy is, and sometimes it is totally useless. Variety of hybrid approaches have tried to combine collaborative filtering and content-based method for improving the sparsity issue in rating matrix. In this study, a new method is suggested for the same purpose, but with different perspective, it deals with no-match situation in person-person similarity evaluation. This method is called the transitive similarity model because it is based on relation graph of people, and it compares recommendation accuracy by applying to Movielens open dataset.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.284-291
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• 2022

Historical data from comparable projects can serve as benchmarking data for an ongoing project's planning during the project scoping phase. As project owners typically store substantial amounts of data generated throughout project life cycles in digitized databases, they can capture appropriate data to support various project planning activities by accessing digital databases. One of the most important work tasks in this process is identifying one or more past projects comparable to a new project. The uniqueness and complexity of construction projects along with unorganized data, impede the reliable identification of comparable past projects. A project scope document provides the preliminary overview of a project in terms of the extent of the project and project requirements. However, narratives and free-formatted descriptions of project scopes are a significant and time-consuming barrier if a human needs to review them and determine similar projects. This study proposes an Artificial Intelligence-driven model for analyzing project scope descriptions and evaluating project similarity using natural language processing (NLP) techniques. The proposed algorithm can intelligently a) extract major work activities from unstructured descriptions held in a database and b) quantify similarities by considering the semantic features of texts representing work activities. The proposed model enhances historical comparable project identification by systematically analyzing project scopes.

• The KIPS Transactions:PartD
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• v.10D no.4
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• pp.577-590
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• 2003

The shape-based retrieval is defined as the operation that searches for the (sub) sequences whose shapes are similar to that of a query sequence regardless of their actual element values. In this paper, we propose a similarity model suitable for shape-based retrieval and present an indexing method for supporting the similarity model. The proposed similarity model enables to retrieve similar shapes accurately by providing the combination of various shape-preserving transformations such as normalization, moving average, and time warping. Our indexing method stores every distinct subsequence concisely into the disk-based suffix tree for efficient and adaptive query processing. We allow the user to dynamically choose a similarity model suitable for a given application. More specifically, we allow the user to determine the parameter p of the distance function $L_p$ when submitting a query. The result of extensive experiments revealed that our approach not only successfully finds the subsequences whose shapes are similar to a query shape but also significantly outperforms the sequence search.

• Korean Journal of Cognitive Science
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• v.23 no.3
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• pp.295-322
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• 2012

In this paper, we cluster similar word senses applying vector space model and HAL (Hyperspace Analog to Language). HAL measures corelation among words through a certain size of context (Lund and Burgess 1996). The similarity measurement between a word pair is cosine similarity based on the vector space model, which reduces distortion of space between high frequency words and low frequency words (Salton et al. 1975, Widdows 2004). We use PCA (Principal Component Analysis) and SVD (Singular Value Decomposition) to reduce a large amount of dimensions caused by similarity matrix. For sense similarity clustering, we adopt supervised and non-supervised learning methods. For non-supervised method, we use clustering. For supervised method, we use SVM (Support Vector Machine), Naive Bayes Classifier, and Maximum Entropy Method.

• Journal of the Korean Society of Clothing and Textiles
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• v.33 no.3
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• pp.477-488
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• 2009

As the Korean cultural contents, such as drama, films, music, gained popularity in China, Korean fashion brands used Korean celebrities as their models to as a sales promotion strategy for Chinese consumers. With the point of view that the advertising model as a human capital as well, the purpose of this study is to investigate the factors of attributes of Korean celebrity advertising model, and to analyze effects on fashion brand recognition, preference, trust and purchase intention. With convenience sampling, the research surveyed Shanghai consumers in their 20's to early 30's who had purchased Korean fashion items. The 291 responses were analyzed by frequency analysis, reliability test, factor analysis, multiple regression analysis, The results are as follows. Frist, Korean celebrity advertising model attribute factors were divided into similarity, familiarity, popularity, attractiveness and trust. Second, the brand recognition was affected by similarity, familiarity and popularity factors, and the brand preference was affected by similarity, familiarity, popularity and attractiveness factors. Third, the trust of Korean fashion brands was affected by similarity, familiarity, attractiveness, trust, brand recognition and brand preference. Lastly, the intention to purchase Korean Fashion brand was affected by similarity, familiarity, attractiveness, brand recognition, brand preference and brand trust.