• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.406-409
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• 2008

We consider the problem of exploiting a taxonomy of propositionalized attributes in order to learn compact and robust classifiers. We introduce Propositionalized Attribute Taxonomy guided Naive Bayes Learner (PAT-NBL), an inductive learning algorithm that exploits a taxonomy of propositionalized attributes as prior knowledge to generate compact and accurate classifiers. PAT-NBL uses top-down and bottom-up search to find a locally optimal cut that corresponds to the instance space from propositionalized attribute taxonomy and data. Our experimental results on University of California-Irvine (UCI) repository data sets show that the proposed algorithm can generate a classifier that is sometimes comparably compact and accurate to those produced by standard Naive Bayes learners.

• The KIPS Transactions:PartB
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• v.12B no.3 s.99
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• pp.291-300
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• 2005

We are required to adequately adjust the distributed contents to each device and users' demands on the network and to obtain authentication of ownership for our information to prevent the illegal usage of our digital information by non-owners. In this paper, we propose scalable digital watermarking of contents within a compression domain based on Orthogonal Forward Wavelet Transforms, and the proposed method focuses on robust watermark algorithms that are not visually recognizable to embedded ownership information. Therefore, it proposes a watermark insertion methods based on spread spectrum techniques and Provides a watermark key. As a result, it not only extracted the contained watermark from the intentionally altered images, but also secured the watermark information extraction from partial images and ensure the decrease of BER (Bit Error Rate) in the images containing watermarks even when more watermark inserted images are transmitted.

• The KIPS Transactions:PartB
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• v.12B no.5 s.101
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• pp.587-594
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• 2005

This paper proposes a multi-level thresholding method for image segmentation using fuzzy clustering algorithm in transition region. Most of threshold-based image segmentation methods determine thresholds based on the histogram distribution of a given image. Therefore, the methods have difficulty in determining thresholds for real-image, which has a complex and undistinguished distribution, and demand much computational time and memory size. To solve these problems, we determine thresholds for real-image using fuzzy clustering algorithm after extracting transition region consisting of essential and important components in image. Transition region is extracted based on Inか entropy, which is robust to noise and is well-known as a tool that describes image information. And fuzzy clustering algorithm can determine optimal thresholds for real-image and be easily extended to multi-level thresholding. The experimental results demonstrate the effectiveness of the proposed method for performance.

• KSBB Journal
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• v.30 no.5
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• pp.230-238
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• 2015

Abnormal glycosylation can significantly affect the intrinsic functions (i.e., stability and solubility) of proteins and the extrinsic protein interactions with other biomolecules. For example, recombinant glycoprotein therapeutics needs proper glycosylation for optimal drug efficacy. Therefore, there has been a strong demand for rapid, sensitive and high-through-put glycomics tools for real-time monitoring and fast validation of the biotherapeutics glycosylation. Although liquid chromatography tandem mass spectrometry (LC-MS/MS) is one of the most powerful tools for the characterization of glycan structures, it is generally time consuming and requires highly skilled personnel to collect the data and analyze the results. Recently, as an alternative method, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-MS), which is a fast, robust and easy-to-use instrumentation, has been used for quantitative glycomics with various chemical derivatization techniques. In this review, we highlight the recent advances in MALDI-MS based quantitative glycan analysis according to the chemical derivatization strategies. Moreover, we address the application of MALDI-MS for high-throughput glycan analysis in many fields of clinical and biochemical engineering.

• Journal of Computing Science and Engineering
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• v.6 no.1
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• pp.1-11
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• 2012

Computed tomography (CT) images are widely used for the analysis of the temporal evaluation or monitoring of the progression of a disease. The follow-up examinations of CT scan images of the same patient require a 3D registration technique. In this paper, an automatic and robust registration is proposed for the rigid registration of 3D CT images. The proposed method involves two steps. Firstly, the two CT volumes are aligned based on their principal axes, and then, the alignment from the previous step is refined by the optimization of the similarity score of the image's voxel. Normalized cross correlation (NCC) is used as a similarity metric and a downhill simplex method is employed to find out the optimal score. The performance of the algorithm is evaluated on phantom images and knee synthetic CT images. By the extraction of the initial transformation parameters with principal axis of the binary volumes, the searching space to find out the parameters is reduced in the optimization step. Thus, the overall registration time is algorithmically decreased without the deterioration of the accuracy. The preliminary experimental results of the study demonstrate that the proposed method can be applied to rigid registration problems of real patient images.

• Journal of Energy Engineering
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• v.25 no.3
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• pp.51-58
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• 2016

MLCC is key parts of many electronic products and mixer is used to make MLCC. Currently, non-contact mixer is increasingly used due to its many merits. In case of large capacity non-contact mixer, function of driving gear is important. In this study, therefore, in order to reduce manufacturing cost through optimal design of driving gear of large capacity non-contact mixer, study on shape optimization of driving gear without excessive design modification was performed. As the results, because safety factors of modification model were decreased about 3.0 ~ 3.5 times compared with those of model with robust design, the possibility for saving manufacturing cost was confirmed.

• Steel and Composite Structures
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• v.34 no.4
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• pp.467-485
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• 2020

Genetic Algorithm (GA) is a meta-heuristic algorithm which is capable of providing robust solutions for optimal design of structural components, particularly those one needs considering many design requirements. Hence, it has been successfully used by engineers in the typology optimization of structural members. As a novel approach, this study employs GA in order for conducting a case study with high constraints on the optimum mechanical properties of reinforced concrete (RC) beams under different load combinations. Accordingly, unified optimum sections through a computer program are adopted to solve the continuous beams problem. Genetic Algorithms proved in finding the optimum resolution smoothly and flawlessly particularly in case of handling many complicated constraints like a continuous beam subjected to different loads as moments shear - torsion regarding the curbs of design codes.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.2
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• pp.72-82
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• 2005

The objective of this paper is to describe the optimization of design parameters in a large-sized commercial bus heater system by using CFD(computational fluid dynamics) analysis and Taguchi method. In order to obtain the best combination of each control factor which results in a desired performance of heater system, the parameter design of the Taguchi method is adopted for the robust design considering the dynamic characteristic. The research activity may be divided into four phases. The first one is analyzing the problem, i.e., ascertaining the influential factors. In the second phase the levels were set in such a way that their variation would significantly influence the response. In the third phase the experimental runs were designed. In the final phase the planned runs were carried out numerically to evaluate the optimal combination of factors which is able to provide the best response. In this study, eight factors were considered for the analysis: one with two level and seven with three level combinations comprising the $L_{18}(2^1{\times}3^7)$ orthogonal array. The results of this study can be summarized as follows ; (i)The optimum condition of control factor is a set of <$A_2\;B_1\;C_3\;D_3\;E_1\;F_2\;G_3\;H_2$> where A is shape of the outer fin, B is pitch of the outer fin, C is height of the outer fin, D is the inner fin number, E is the inner fin height, F is length of the flame guide, G is diameter of the heating element and H is clearance between air guide and heating element. (ii)The heat capacity of heated discharge air under the optimum condition satisfies the equation y=0.6M w here M is a signal factor. (iii)The warm-up rate improves about three times, more largely as com pared with the current condition, which results in about 9.2minutes reduction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1569-1586
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• 2015

This paper considers the optimal cell association and resource allocation for load balancing in a heterogeneous cellular network subject to user's quality-of-service (QoS) constraints. We adopt the proportional fairness (PF) utility maximization formulation which also accommodates the QoS constraints in terms of minimum rate requirements. With equal resource allocation this joint optimization problem is either infeasible or requires relaxation that yields a solution which is difficult to implement. Nevertheless, we show that this joint optimization problem can be effectively solved without any priori assumption on resource allocation and yields a cell association scheme which enforces single BS association for each user. We re-formulated the joint optimization problem as a network-wide resource allocation problem with cardinality constraints. A reweighted heuristic l₁-norm regularization method is used to obtain a sparse solution to the re-formulated problem. The cell association scheme is then derived from the sparsity pattern of the solution, which guarantees a single BS association for each user. Compared with the previously proposed method based on equal resource allocation, the proposed framework results in a feasible cell association scheme and yields a robust solution on resource allocation that satisfies the QoS constraints. Our simulations illustrate the impact of user's minimum rate requirements on cell association and demonstrate that the proposed approach achieves load balancing and enforces single BS association for users.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.11C
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• pp.1118-1122
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• 2003

In this paper, we propose a new invisible digital watermarking scheme based on wavelet transform using singular value decomposition. Embedding process is started by decomposing the lowest frequency band image with 3${\times}$3 block among which we define the watermark block chosen by a key set; entropy and condition number of the block. A watermark is embedded in the singular values of each watermark blocks. This provides a robust watermarking in lowest possible time-frequency domain. To detect the watermark, we are locally modeling an attack as 3${\times}$3 matrices on the watermark blocks. Combining with the SVD and the attack matrices, we estimate watermark set corresponding to the watermark blocks. In each watermark block, we determine an optimal watermark which is justified by the T-testing. A numerical experiment shows that the proposed watermarking scheme efficiently detects the watermarks from several JPEG attacks.