• International Journal of CAD/CAM
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• v.8 no.1
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• pp.41-44
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• 2009

This paper describes an implementation of virtual teeth modeling for a haptic dental simulation. The system allows dental students to practice dental procedures with realistic tactual feelings. The system requires fast and stable haptic rendering and volume modeling techniques working on the virtual tooth. In our implementation, a volumetric implicit surface is used for intuitive shape modification without topological constraints and haptic rendering. The volumetric implicit surface is generated from input geometric model by using a closest point transformation algorithm. And for visual rendering, we apply an adaptive polygonization method to convert volumetric teeth model to geometric model. We improve our previous system using new octree design to save memory requirement while increase the performance and visual quality.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.4
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• pp.744-752
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• 2017

ECQV implicit certificate reconstructs the public key from the certificate without validation of the signature unlike the explicit certificate. Like this, the certificate and the public key is implicitly validated when a public key is reconstructed from a certificate. Hence, ECQV implicit certificate is shorter than the explicit certificate due to be only comprised of the public key reconstruction data instead of the signature and the public key, and faster to reconstruct the public key from the certificate than validating the signature. Furthermore, ECQV is well suited for environments and application that resources such as memory and bandwidth are limited because it is shorter the key length, and faster the performance than other cipher cryptography due to be run on ECC. In this paper, we describe prerequisites of ECQV specified in the SECG SEC 4 and issuance of an implicit certificate, reconstruction of the public key from an implicit certificate. Also we designed and implemented ECQV, and measured the performance of it.

• Proceedings of the Korea Society of Design Studies Conference
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• 2004.05a
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• pp.166-167
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• 2004

• Journal of Korean Institute of Industrial Engineers
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• v.36 no.3
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• pp.193-202
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• 2010

The recommender system is a typical software solution for personalized services which are now popular in e-commerce sites. Most of the existing recommender systems are based on customers' explicit rating data on items (e.g., ratings on movies), and it is only recently that recommender systems based on implicit ratings have been proposed as a better alternative. Implicit ratings of a customer on those items that are clicked but not purchased can be inferred from the customer's navigational and behavioral patterns. In this article, a dimensionality reduction (DR) technique is newly applied to the implicit rating-based recommender system, and its effectiveness is assessed using an experimental e-commerce site. The experimental results indicate that the performance of the proposed approach is superior or at least similar to the conventional collaborative filtering (CF)-based approach unless the number of recommended products is 'large.' In addition, the proposed approach requires less memory space and is computationally more efficient.

• The Transactions of the Korea Information Processing Society
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• v.5 no.11
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• pp.2989-2996
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• 1998

As the circuit density of VLSI grows and its performance improves, delay fault testing of VLSI becomes very important. Delay faults in a circuit can be categorized into two classes, gate delay faults and path delay faults. This paper proposed two methods in dynamic memory usage in the path delay fault simulation. The first method is similar to that used in concurrent fault simulation for stuck-at faults and the second method reduces dynamic memory usage by not inserting a fault descriptor into the fault list when its value is X. The second method, called Implicit-X method, showed superior performance in both dynamic memory usage and simulation time than the first method, called Concurrent-Simulation-Like method.

• 한국전산유체공학회:학술대회논문집
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• 2001.05a
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• pp.38-44
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• 2001

An efficient Gauss-Seidel time integration scheme is developed for solving the Euler and Navier-Stokes equations on unstructured meshes. Roe's FDS is used for the explicit residual computations and van Leer's FVS for evaluating implicit flux Jacobian. To reduce the memory requirement to a minimum level, off-diagonal flux Jacobian contributions are repeatedly calculated during the Gauss-Seidel sub-iteration process. Computational results based on the present scheme show that approximately $15\%$ of CPU time reduction is achieved while maintaining the memory requirement level to $50-60\%$ of the original Gauss-Seidel scheme.

• Journal of the Optical Society of Korea
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• v.20 no.3
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• pp.368-380
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• 2016

There is no doubt that adaptive optics (AO) is the most promising method to compensate wavefront disturbance in free space optics communication (FSO). In order to improve the performance of the AO system described by discrete-time linear system model with time-delay and implicit phase turbulent model, new controllers based on a Kalman filter and its extensions are proposed. Based on the standard Kalman filter, we propose a fading memory filter to deal with the ruleless strong interference; sequential and U-D filters are applied to reduce implementation complexity for the embedded controllers. Theoretical analysis and the numerical simulations show that the proposed fading memory filter can upgrade the performance for AO systems in consideration of the unforeseen strong pulse interference, and the sequential and U-D filters perform well compared with a Kalman filter.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.223-224
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• 2019

스마트폰 애플리케이션 시장은 단기간 비약적인 성장을 거듭했다. 여러 각종 분야에서 애플리케이션 개발을 원하는 곳이 많아졌고 그만큼 앱 개발자들을 원하는 시장이 늘어나고 있다. 본 연구는 앱 개발을 도전하려는 1인 혹은 소규모 아마추어 개발자 입장에서 관련 실력을 효과적으로 늘릴 수 있는 방법을 제공하고 전반적인 애플리케이션 개발과 환경에 관한 유익한 정보들을 쉽게 접근함으로써 조금 더 애플리케이션 개발에 관심을 갖게 되는 계기가 될 것이다. 또한 본 연구의 게임 애플리케이션은 사용자들의 명시적 기억과 암묵적 기억 훈련에 도움을 줄 수 있도록 개발하였다.

• Korean Journal of Cognitive Science
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• v.11 no.3_4
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• pp.57-72
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• 2000

A Korean standardized set of pictures has been called for as more and more studies utilized picture stimuli among memory and representation research. This article presents a Korean standardized set of pictures for studies probing the cognitive mechanisms that underlie picture and word processing or studies that simply utilize pictures stimuli. This norm provides 213 pictures, data on several variables such as name agreement, appropriateness of pictures. and familiarity. Previous data on such variables as frequency. category. and frequency within a category have been integrated 1 into this norm. Limitation, usage. and application of this set are discussed in terms of 1 implicit and explicit memory, and those variables mentioned previously.

• Journal of Information Processing Systems
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• v.18 no.5
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• pp.614-627
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• 2022

Aspect-based sentiment analysis is to discover the sentiment polarity towards an aspect from user-generated natural language. So far, most of the methods only use the implicit position information of the aspect in the context, instead of directly utilizing the position relationship between the aspect and the sentiment terms. In fact, neighboring words of the aspect terms should be given more attention than other words in the context. This paper studies the influence of different position embedding methods on the sentimental polarities of given aspects, and proposes a position embedding interactive attention network based on a long short-term memory network. Firstly, it uses the position information of the context simultaneously in the input layer and the attention layer. Secondly, it mines the importance of different context words for the aspect with the interactive attention mechanism. Finally, it generates a valid representation of the aspect and the context for sentiment classification. The model which has been posed was evaluated on the datasets of the Semantic Evaluation 2014. Compared with other baseline models, the accuracy of our model increases by about 2% on the restaurant dataset and 1% on the laptop dataset.