• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.11a
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• pp.187-188
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• 2007

• Proceedings of the KSME Conference
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• 2005.11a
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• pp.169.2-169.2
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• 2005

• Communications of the Korean Mathematical Society
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• v.12 no.1
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• pp.165-176
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• 1997

In order to overcome computational ill-posedness which arises when we solve the least square problems, nonlinear smoothing splines are used. The existence and the convergence on nonlinear smoothing spline are shown with numerical experiments.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.27-31
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• 1988

A study has been carried out on the implementation of IMCA (Linear Moving Voice Coil Actuator) to a flexible robot arm modelled as cantilever beam. Control performances are evaluated by computer simulation and theoretical analysis is validated by experiments. From this study, it is proved that the LMVCA can be applied easily to the control system and suppress vibration effectively.

• Journal of the Korean Statistical Society
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• v.6 no.2
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• pp.103-115
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• 1977

A strategy for selecting subsets of variables from a given linear model in a mixture system is discussed. The purpose is to achieve better fitting surfaces for estimation of the response in an experimental region of interest. A criterion is proposed for screening variables and illustrated with an example.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.2
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• pp.793-810
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• 2015

The TWINE is a new Generalized Feistel Structure (GFS) lightweight cryptosystem in the Internet of Things. It has 36 rounds and the key lengths support 80 bits and 128 bits, which are flexible to provide security for the RFID, smart cards and other highly-constrained devices. Due to the strong attacking ability, fast speed, simple implementation and other characteristics, the differential fault analysis has become an important method to evaluate the security of lightweight cryptosystems. On the basis of the 4-bit fault model and the differential analysis, we propose an effective differential fault attack on the TWINE cryptosystem. Mathematical analysis and simulating experiments show that the attack could recover its 80-bit and 128-bit secret keys by introducing 8 faulty ciphertexts and 18 faulty ciphertexts on average, respectively. The result in this study describes that the TWINE is vulnerable to differential fault analysis. It will be beneficial to the analysis of the same type of other iterated lightweight cryptosystems in the Internet of Things.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.26 no.1
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• pp.6-12
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• 2017

In a large 3D printer when the cooler, which cools the filament, acts in one direction, the area directly exposed to the cooling is cooled to the proper temperature. However, the cooling effect on the opposite area is relatively less. It was found in experiments that filaments with a thickness of over 2 mm exhibit the cooling problem in one directional cooling. Consequently, cooling was performed to prevent the flow-down and to produce firm support leading to an improvement in product quality in extrusion. Further, the lay-up of a 3D printer with five guides combined with a duct was achieved. Analysis showed that the improvement in the cooling effect enables stable extrusion and lay-up and thus, reduces fabrication time.

• Journal of the Korea Computer Graphics Society
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• v.8 no.2
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• pp.9-14
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• 2002

In cases of densely occluded urban scenes, it is effective to determine the visibility of scenes, since only small parts of the scene are visible from a given cell. In this paper, we introduce a new visibility preprocessing method that efficiently computes potentially visible objects for volumetric cells. The proposed method deals with general 3D polygonal models and invisible objects jointly blocked by multiple occluders. The proposed approach decomposes volume visibility into a set of point visibilities, and then computes point visibility using hardware visibility queries, in particular HP_occlusion_test and NV_occlusion_query. We carry out experiments on various large-scale scenes, and show the performance of our algorithm.

• Journal of Information Processing Systems
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• v.14 no.3
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• pp.709-726
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• 2018

Database classification is an important preprocessing step for the multi-database mining (MDM). In fact, when a multi-branch company needs to explore its distributed data for decision making, it is imperative to classify these multiple databases into similar clusters before analyzing the data. To search for the best classification of a set of n databases, existing algorithms generate from 1 to ($n^2-n$)/2 candidate classifications. Although each candidate classification is included in the next one (i.e., clusters in the current classification are subsets of clusters in the next classification), existing algorithms generate each classification independently, that is, without taking into account the use of clusters from the previous classification. Consequently, existing algorithms are time consuming, especially when the number of candidate classifications increases. To overcome the latter problem, we propose in this paper an efficient approach that represents the problem of classifying the multiple databases as a problem of identifying the connected components of an undirected weighted graph. Theoretical analysis and experiments on public databases confirm the efficiency of our algorithm against existing works and that it overcomes the problem of increase in the execution time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2381-2399
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• 2019

Traditional recommendation algorithms on Collaborative Filtering (CF) mainly focus on the rating prediction with explicit ratings, and cannot be applied to the top-N recommendation with implicit feedbacks. To tackle this problem, we propose a new collaborative filtering approach namely Maximize MAP with Matrix Factorization (MFMAP). In addition, in order to solve the problem of non-smoothing loss function in learning to rank (LTR) algorithm based on pairwise, we also propose a smooth MAP measure which can be easily implemented by standard optimization approaches. We perform experiments on three different datasets, and the experimental results show that the performance of MFMAP is significantly better than other recommendation approaches.