• The Korean Journal of Applied Statistics
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• v.33 no.4
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• pp.439-449
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• 2020

Meta-analysis provides a way of integrating several independent studies of interest. Since small studies with statistically significant results are more likely to be published, publication bias, which is a special case of selection bias, often occurs in meta analysis. Conditional likelihood and weighted estimating equation have been proposed to deal with publication bias, but they require to specify a correct selection probability model. In contrast, the pairwise pseudolikelihood approach can correct publication bias without fully specifying the correct selection probability model, but its performance in meta-analysis was not investigated. In this paper, we perform a numerical study about whether the pairwise pseudolikelihood approach is effective for solving publication bias arising from typical meta-analysis settings.

• The Korean Journal of Applied Statistics
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• v.17 no.1
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• pp.119-134
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• 2004

Generally to estimate the priority vector in AHP, an eigen-vector method or a log-arithmic least square method is applied to pairwise comparison matrix itself. In this paper an estimating method is suggested, which is applied to pairwise comparison matrix adjusted by using the eigen-decomposition of skew-symmetric matrix. We also show theoretical background, meanings, and several advantages of this method by example. This method may be useful in case that pairwise comparison matrix is quite inconsistent.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.5
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• pp.505-511
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• 2003

Production rule based knowledge representation method has many advantages, but has the difficulties in maintaining the consistency of knowledge. Since the consistency maintenance of knowledge exercises a marked effect on the reliability of inference results, the system for consistency maintenance of knowledge is indispensable to increase the reliability. In the most popular pairwise checking method among consistency verification methods, the valuable rules can be omitted and it takes much time in checking the consistency when the rules are numerous. So, this paper is to propose and implement the verification system which can remove the structural errors and semantic ones, making up for the defects of pairwise checking method by using the certain property list and eventual property list and improving the steps of verification.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.3
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• pp.129-136
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• 2019

There are a variety of entities in natural language such as people, organizations, places, and products. These entities can have many various meanings. The ambiguity of entity is a very challenging task in the field of natural language processing. Entity Linking(EL) is the task of linking the entity in the text to the appropriate entity in the knowledge base. Pairwise based approach, which is a representative method for solving the EL, is a method of solving the EL by using the association between two entities in a sentence. This method considers only the interdependence between entities appearing in the same sentence, and thus has a limitation of global interdependence. In this paper, we developed an Entity2vec model that uses Word2vec based on knowledge base of RDF type in order to solve the EL. And we applied the algorithms using the generated model and ranked each entity. In this paper, to overcome the limitations of a pairwise approach, we devised a pairwise approach based on comprehensive interdependency and compared it.

• Journal of IKEEE
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• v.28 no.3
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• pp.390-396
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• 2024

Vision Transformer (ViT) learns relationships between patches, but it may overlook important features such as color, texture, and boundaries, which can result in performance limitations in fields like medical imaging or facial recognition. To address this issue, this study proposes the Pairwise Attention Reinforcement (PAR) model. The PAR model takes both the training image and a reference image as input into the encoder, calculates the similarity between the two images, and matches the attention score maps of images with high similarity, reinforcing the matching areas of the training image. This process emphasizes important features between images and allows even subtle differences to be distinguished. In experiments using clock-drawing test data, the PAR model achieved a Precision of 0.9516, Recall of 0.8883, F1-Score of 0.9166, and an Accuracy of 92.93%. The proposed model showed a 12% performance improvement compared to API-Net, which uses the pairwise attention approach, and demonstrated a 2% performance improvement over the ViT model.

• Journal of Korean Society for Quality Management
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• v.40 no.4
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• pp.589-598
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• 2012

Purpose: Determination of the importance values of quality attributes is very important to integrate the Kano model with QFD. A new method to determine the importance values of quality attributes is proposed. Methods: ASC(Average Satisfaction Coefficient) is proposed in order to determine the importance values of quality attributes. To evaluate the effectiveness of ASC, a case study of modern TV sets is conducted, and the performance of ASC is compared with direct importance evaluation and AHP pairwise comparisons. Results: The result of ASC application is similar with those of direct importance evaluation and AHP pairwise comparison. Conclusion: ASC is an effective instrument to determine the importance values of quality attributes. It doesn't need a cumbersome process like AHP pairwise comparison, and can be calculated using the data for the conventional Kano model.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10c
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• pp.552-555
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• 2006

센서네트워크는 유비쿼터스 컴퓨팅 사회에서 핵심 기술로 부각되고 있다. 이러한 센서네트워크는 노드들이 노출되거나 데이터 전송 시 일반 네트워크보다 보안에 취약하므로 안전한 통신을 위하여 센서 노드간 키를 설정하는 것은 보안을 위한 기본적인 요구사항이 되고 있다. 본 논문에서는 배치된 센서네트워크에서 셋업서버의 오버헤드를 줄이기 위하여 네트워크를 클러스터링하고 각 셀 안에 클러스터 헤더와 노드들을 배치한 후 클러스터내의 노드사이의 안전한 통신을 하기위한 pairwise key를 설정하는 기법을 제안하였다.

• Bulletin of the Korean Mathematical Society
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• v.50 no.2
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• pp.611-626
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• 2013

In the paper we study the finite-time ruin probability in a general risk model with constant interest force, in which the claim sizes are pairwise quasi-asymptotically independent and arrive according to an arbitrary counting process, and the premium process is a general stochastic process. For the case that the claim-size distribution belongs to the consistent variation class, we obtain an asymptotic formula for the finite-time ruin probability, which holds uniformly for all time horizons varying in a relevant infinite interval. The obtained result also includes an asymptotic formula for the infinite-time ruin probability.

• Proceedings of the Korea Contents Association Conference
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• 2015.05a
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• pp.331-332
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• 2015

스키 입문자의 경우 부상 등에 따른 두려움을 느끼거나 부정확한 자세가 익숙해져 바로잡기가 힘든 경우가 발생한다. 스키 트레이닝 시뮬레이터는 이러한 단점을 보완하여 스키 선수의 정확한 자세를 바탕으로 정확한 자세를 취할 수 있도록 유도하는 시스템이다. 본 논문에서는 스키 선수의 자세와 시뮬레이터 사용자의 자세를 비교하여 유사도를 측정하기 위해 사용한 알고리즘의 효율성을 향상하기 위해 특정 센서에 가중치를 부여하고 이들의 좌표값을 받아 계산하는 Pairwise testing 기법을 적용한다. 이는 센서간의 거리를 실시간으로 계산하여 두 자세의 유사도를 검출하는데 있어 비교 테스트 케이스를 감소시켜 유사도 측정의 효율성을 높일 수 있다.

• The Korean Journal of Applied Statistics
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• v.25 no.3
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• pp.531-541
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• 2012

In this study, we consider various methods to estimate the weights of a pairwise comparison matrix in the Analytic Hierarchy Process widely applied in various decision-making fields. This paper uses a data dependent simulation to evaluate the statistical accuracy, minimum violation and minimum norm of the obtaining weight methods from a reciprocal symmetric matrix. No method dominates others in all criteria. Least squares methods perform best in point of mean squared errors; however, the eigenvectors method has an advantage in the minimum norm.