• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.3962-3980
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• 2019

To deal with single sample face recognition, this paper presents a patch based semi-supervised linear regression (PSLR) algorithm, which draws facial variation information from unlabeled samples. Each facial image is divided into overlapped patches, and a regression model with mapping matrix will be constructed on each patch. Then, we adjust these matrices by mapping unlabeled patches to $[1,1,{\cdots},1]^T$. The solutions of all the mapping matrices are integrated into an overall objective function, which uses ${\ell}_{2,1}$-norm minimization constraints to improve discrimination ability of mapping matrices and reduce the impact of noise. After mapping matrices are computed, we adopt majority-voting strategy to classify the probe samples. To further learn the discrimination information between probe samples and obtain more robust mapping matrices, we also propose a multistage PSLR (MPSLR) algorithm, which iteratively updates the training dataset by adding those reliably labeled probe samples into it. The effectiveness of our approaches is evaluated using three public facial databases. Experimental results prove that our approaches are robust to illumination, expression and occlusion.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.6
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• pp.267-275
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• 2023

This paper presents the development of specialized software for annotating volume-of-interest on ¹⁸F-FDG PET/CT images with the goal of facilitating the studies and diagnosis of head and neck cancer (HNC). To achieve an efficient annotation process, we employed the SE-Norm-Residual Layer-based U-Net model. This model exhibited outstanding proficiency to segment cancerous regions within ¹⁸F-FDG PET/CT scans of HNC cases. Manual annotation function was also integrated, allowing researchers and clinicians to validate and refine annotations based on dataset characteristics. Workspace has a display with fusion of both PET and CT images, providing enhance user convenience through simultaneous visualization. The performance of deeplearning model was validated using a Hecktor 2021 dataset, and subsequently developed semi-automatic annotation functionalities. We began by performing image preprocessing including resampling, normalization, and co-registration, followed by an evaluation of the deep learning model performance. This model was integrated into the software, serving as an initial automatic segmentation step. Users can manually refine pre-segmented regions to correct false positives and false negatives. Annotation images are subsequently saved along with their corresponding ¹⁸F-FDG PET/CT fusion images, enabling their application across various domains. In this study, we developed a semi-automatic annotation software designed for efficiently generating annotated lesion images, with applications in HNC research and diagnosis. The findings indicated that this software surpasses conventional tools, particularly in the context of HNC-specific annotation with ¹⁸F-FDG PET/CT data. Consequently, developed software offers a robust solution for producing annotated datasets, driving advances in the studies and diagnosis of HNC.

• The Pure and Applied Mathematics
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• v.5 no.2
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• pp.109-114
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• 1998

Let H be a separable complex H be a space and let (equation omitted)(H) be the *-algebra of all bounded linear operators on H. An operator T in (equation omitted)(H) is said to be p-hyponormal if ($T^{\ast}T)^p - (TT^{\ast})^{p}\geq$ 0 for 0 ＜ p ＜ 1. If p = 1, T is hyponormal and if p = $\frac{1}{2}$, T is semi-hyponormal. In this paper, by using a technique introduced by S. K. Berberian, we show that the approximate point spectrum $\sigma_{\alpha p}(T) of a pure p-hyponormal operator T is empty, and obtains the compact perturbation of T.

• Journal of applied mathematics & informatics
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• v.10 no.1_2
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• pp.83-99
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• 2002

Optimality conditions are derived for a nonlinear program in which a support function appears in the objective as well as in each constraint function. Wolfe and Mond-Weir type duals to this program are presented and various duality results are established under suitable convexity and generalized convexity assumptions. Special cases that often occur in the literature are those in which a support function is the square root of a positive semi- definite quadratic form or an Lp norm. It is pointed out that these special cases can easily be generated from our results.

• Journal of Ocean Engineering and Technology
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• v.10 no.3
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• pp.153-161
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• 1996

This paper presents a design method of dynamic positioning control system for floating platform with rotatable and retractable thruster using $H_{\infty}$ control technique. The norm band of uncertainty is captured by multiplicative perturbation between nominal model and reduced order model. A controller robust to the uncertainty is designed applying $H_{\infty}$ synthesis. The control law satisfying robust stabillity and nominal performance condition is determined through the mixed sensitivity approach. The evaluation for the resultant controller obtained by $H_{\infty}$ synthesis is done through simulations of the closed loop system. The results of $H_{\infty}$ synthesis are compared to those of the traditional LQ synthesis method.

• Journal of applied mathematics & informatics
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• v.5 no.2
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• pp.433-448
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• 1998

In this study we use inexact Newton-like methods to find solutions of nonlinear operator equations on Banach spaces with a convergence structure. Our technique involves the introduction of a generalized norm as an operator from a linear space into a par-tially ordered Banach space. In this way the metric properties of the examined problem can be analyzed more precisely. Moreover this approach allows us to derive from the same theorem on the one hand semi-local results of kantorovich-type and on the other hand 2global results based on monotonicity considerations. By imposing very general Lipschitz-like conditions on the operators involved on the other hand by choosing our operators appropriately we can find sharper error bounds on the distances involved than before. Furthermore we show that special cases of our results reduce to the corresponding ones already in the literature. Finally our results are used to solve integral equations that cannot be solved with existing methods.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.437-442
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• 1996

The paper presents a design method of dynamic positioning control system for floating platform with rotatable and retractable thruster using $H_{\infty}$control technique. The norm band of uncertaintyis captured by multiplicative perturbation between nominalmodel and reduced order model. A controller robust to theuncertainty is designed applying $H_{\infty}$synthesis. The control law satisfying robust stability and nominal performance condition is determined through the mixed sensitivity approach. The evaluation for the resultant controller obtained by $H_{\infty}$synthesis is done through simulations of the closed loop system. The results of $H_{\infty}$synthesis are compared to those of the traditional LQ synthesis method. method.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.19 no.4
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• pp.409-416
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• 2015

In many practical applications, we face the problem of reconstruction of an unknown function sampled at some data points. Among infinitely many possible reconstructions, the thin plate spline interpolation is known to be the least oscillatory one in the Beppo-Levi semi norm, when the data points are sampled in $\mathbb{R}^2$. The traditional proofs supporting the argument are quite lengthy and complicated, keeping students and researchers off its understanding. In this article, we introduce a simple and short proof for the optimal reconstruction. Our proof is unique and reguires only elementary mathematical background.

• Journal of the Korean Mathematical Society
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• v.56 no.1
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• pp.239-263
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• 2019

The $Calder{\acute{o}}n$-Zygmund type estimate is proved for elliptic obstacle problems in bounded non-smooth domains. The problems are related to divergence form nonlinear elliptic equation with measurable nonlinearities. Precisely, nonlinearity $a({\xi},x_1,x^{\prime})$ is assumed to be only measurable in one spatial variable $x_1$ and has locally small BMO semi-norm in the other spatial variables x', uniformly in ${\xi}$ variable. Regarding non-smooth domains, we assume that the boundaries are locally flat in the sense of Reifenberg. We also investigate global regularity in the settings of weighted Orlicz spaces for the weak solutions to the problems considered here.

• Journal of Electrical Engineering and information Science
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• v.1 no.1
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• pp.29-38
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• 1996

To improve the reliability of control systems, certain robustness to plant uncertainties and disturbance inputs is required in terms of well founded mathematical basis. Robust control theory was set up and developed until now from this motivation. In this field, H$_2$or H\ulcorner norm performance measures are frequently used nowadays. Moreover a mixed H$_2$/H\ulcorner control problem is introduced to combine the merits of each measure since H$_2$control usually makes more sense for performance while H\ulcorner control is better for robustness to plant perturbations. However only some partial analytic solutions are developed to this problem under certain special cases at this time. In this paper, the mixed H$_2$/H\ulcorner control problem is considered. The analytic(or semi-analytic) solutions of (sub)optimal mixed H$_2$/H\ulcorner state-feedback controller are derived for the scalar plant case and the multivariable plant case, respectively. An illustrative example is given to compare the proposed analytic solution with the existing numerical one.