• KIEAE Journal
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• v.15 no.2
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• pp.27-35
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• 2015

Purpose: Healthcare is on the whole a personal and critical service that consumer's use, whereas hospitalization is as a rule painful, because nature nurtures and Sun Light Luminosity for healthcare settings is considered healing. The performance and design of climate responsive buildings such as AKU requires a detailed study of attributes of climate both at micro as well as macro level. The therapeutic value of contact with nature through window view, greenery and landscape is calculated there. Method: A two prong strategy is been devised for this article, at micro level three typical morphologies are analysed by creating same environment of neighboring building on sun shading chart, radiation and temperature range. Since the analysis of local climate helps to determine the design strategies for hospital Healing Environment which is suitable for Karachi climate; in order to track the macro climatic behaviour, a considerable analysis of psychometrics chart for AKU Karachi are designed on Climate Consultant (CC) and analysed by Machine Learning. Climate Consultant proposes different design strategies suitable for Karachi. And on the other hand time wise illumination sources for clinical area which are then measured on psychrometric chart- according to singular space: multi patient admission, secondly: acute ambulatory ward, and tertiary: multi windowed space according to the mushrabiyah and sky light pattern. Result: Our findings support the hypothesis that windowed wall is 75-80% more healing wall; an accelerated evidence was found for healing at macro level if the form of the hospital is designed according to the climatologically preferences, whereas at micro level: the light resource becomes the staff attentiveness determinant. In Conclusion evidence was provided that the actual form of luminosity results consequently in satisfaction while light entering from several set of windows and other sources might be valued if design according to the healing environment. The data added on the sun shading chart to calculate rays entraining into space in patient room equal to 124416.21 Watts/ meter $m^2$ is calculated as precise healing rate-and is confirmed by questionnaire from patients belonging from each clinical stage having different illnesses.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.10
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• pp.3048-3057
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• 1996

Analysis model containing two inclined surface cracks on semi-infinite elastic body is established and analyzed on the basis of linear fracture mechanics to examine mutual interference of two surface cracks. Muskhelishvili's complex stress functions are introduced and a set of singular integral equations is obtained for a dislocation density function. The stress intensity factors at crack tip are obtained by using the Gerasoulis'method. When two surface cracks are parallel and have the same length, the values of $K_1$and $\Delta K_11$(variation of $K_11$) for crack 1 and crack 2 decrease by the mutual interference of two surface cracks as the distance between the two surface cracks shortens. The effect of mutual interference is remarkable in high friction coefficient. In case that two surface cracks are parallel, the values of $K_1$and $\Delta K_11$for crack 2 decrease as the length ratio ot crack 2 to crack 1 becomes small. As the crack inclination angle rises, the value of $K_1$ and the mutual interference of $K_1$for crack 2 increase and the value of$\Delta K_11$ for crack 1 becomes smaller than that for crack 2.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.3 s.174
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• pp.701-709
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• 2000

As the welding spot forms a singular geometry of an external crack type, fatigue failure of spot-welded specimens can be evaluated by means of a fracture parameter. Recasting the load vs. fatigue life relationships experimentally obtained, we predicted the fatigue life of spot-weld specimens with a single parameter denoted the equivalent stress intensity factor. This crack driving parameter is demonstrated to successfully describe the effects of specimen geometry and loading type in a comprehensive manner. The suggested fatigue life formula for a single spot weld can play a key role in the design and assessment of spot-welded panel structures, in that the fatigue strength of multi-spots is eventually determined by the fatigue strength of each single spot. We therefore attempt to evaluate the effectiveness and validity of $K_e$ in predicting the fatigue life of auto seat belt anchor panel. We first establish finite element models reflecting the actual mechanical behavior of 3 types of seat belt anchor specimens. Using finite element models elaborately established, we then obtain the effective crack driving parameter $K_e$ composed of its ductility -dependent modal components. It is confirmed that the $K_e$ concept successfully predicts the fatigue life of multi-spot welded panel structures represented by auto seat belt anchors here.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.6
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• pp.88-100
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• 1998

In this paper, an algorithm for a real-time automatic fingerprint identification system is proposed. The fingerprint feature volume is extracted by considering distinct and local characteristics(such as intensity and image quality difference etc.) in fingerprint images, which makes the algorithm properly adaptive to various image acquisitionj methods. Also the matching technique is designed to be invariant on rotation, scaling and translation (RST) changes while being capable of real-time processing. And the classification of fingerprints is performed based on the ridge flow and the relations among singular points such as cores and deltas. The developed fingerprint identification algorithm has been applied to various sets of fingerprint images such as one from NIST(National Institute of Standards and Technology, USA), a pressed fingerprint database constructed according to Korean population distributions in sex, ages and jobs, and a set of rolled-than-scanned fingerprint images. The overall performance of the algorithm has been analyzed and evaluated to the false rejection ratio of 0.07% while holding the false acceptance ratio of 0%.

• Journal of computational fluids engineering
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• v.22 no.1
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• pp.59-66
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• 2017

The guideline of selecting the number of snapshot dataset, $N_s$ in proper orthogonal decomposition(POD) was presented via the analysis of Eigen values based on the singular value decomposition(SVD). In POD, snapshot datasets from the solutions of Euler or Navier-Stokes equations are utilized to SVD and a reduced order model(ROM) is constructed as the combination of Eigen vectors. The ROM is subsequently applied to reconstruct the flowfield data with new set of flow conditions, thereby enhancing the computational efficiency. The overall computational efficiency and accuracy of POD is dependent on the number of snapshot dataset; however, there is no reliable guideline of determining $N_s$. In order to resolve this problem, the order of maximum to minimum Eigen value ratio, O(R) from SVD was analyzed and presented for the decision of $N_s$; in case of steady flow, $N_s$ should be determined to make O(R) be $10^9$. For unsteady flow, $N_s$ should be increased to make O(R) be $10^{11\sim12}$. This strategy of selecting the snapshot dataset was applied to two dimensional NACA0012 airfoil and vortex flow problems including steady and unsteady cases and the numerical accuracies according to $N_s$ and O(R) were discussed.

• Journal of KIISE:Software and Applications
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• v.31 no.10
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• pp.1386-1399
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• 2004

This paper presents correlation-based automatic image captioning. Given a training set of annotated images, we want to discover correlations between visual features and textual features, so that we can automatically generate descriptive textual features for a new unseen image. We develop models with multiple design alternatives such as 1) adaptively clustering visual features, 2) weighting visual features and textual features, and 3) reducing dimensionality for noise sup-Pression. We experiment thoroughly on 10 data sets of various content styles from the Corel image database, about 680MB. The major contributions of this work are: (a) we show that careful weighting visual and textual features, as well as clustering visual features adaptively leads to consistent performance improvements, and (b) our proposed methods achieve a relative improvement of up to 45% on annotation accuracy over the state-of-the-art, EM approach.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.6
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• pp.779-787
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• 2007

This paper presents a highly efficient moving least squares finite difference method (MLS FDM) for a heat transfer problem of bi-material with interfacial boundary. The MLS FDM directly discretizes governing differential equations based on a node set without a grid structure. In the method, difference equations are constructed by the Taylor polynomial expanded by moving least squares method. The wedge function is designed on the concept of hyperplane function and is embedded in the derivative approximation formula on the moving least squares sense. Thus interfacial singular behavior like normal derivative jump is naturally modeled and the merit of MLS FDM in fast derivative computation is assured. Numerical experiments for heat transfer problem of bi-material with different heat conductivities show that the developed method achieves high efficiency as well as good accuracy in interface problems.

• Journal of the Korean Data and Information Science Society
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• v.28 no.4
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• pp.721-731
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• 2017

In this study, principal component analysis methods using Lasso penalty are introduced. There are two popular methods that apply Lasso penalty to principal component analysis. The first method is to find an optimal vector of linear combination as the regression coefficient vector of regressing for each principal component on the original data matrix with Lasso penalty (elastic net penalty in general). The second method is to find an optimal vector of linear combination by minimizing the residual matrix obtained from approximating the original matrix by the singular value decomposition with Lasso penalty. In this study, we have reviewed two methods of principal components using Lasso penalty in detail, and shown that these methods have an advantage especially in applying to data sets that have more variables than cases. Also, these methods are compared in an application to a real data set using R program. More specifically, these methods are applied to the crime data in Ahamad (1967), which has more variables than cases.

• Journal of English Language & Literature
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• v.55 no.1
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• pp.177-198
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• 2009

How are we approach the fourteenth chapter of Ulysses known as 'The Oxen of the Sun' in this globalized age of hyper-theorization? My paper argues that examining the wide reverberations set off by Derrida's comment in "Ulysses Gramophone"-"Everything has already happened to us with Ulysses"-in relation to the central textual theme of cosmopolitanism may provide a reading that not only pays due respect to the critical legacy of the early structuralist interpretations but equally takes into account the political sensibilities of our time. The neologism 'chaosmopolitanism,'in fact, serves as that very critical measure designed to bridge the gap separating the long tradition of Western Eurocentric discourse on cosmopolitanism on the one hand and the geopolitical background conditioning its discursive possibility, namely, the chaotic condition of international colonialism on the other, whose exemplary, and exemplarily creative, fusion bears none other name than Ulysses. But the idea of chaosmopolitanism gains its conceptual leverage on yet another, no less pivotal register, for, just as with Derrida's first-person plural pronoun, the trope leads us to reflect on our own situatedness in the East Asian region in light of Joyce's unabashedly universalist vision, whose over-arching textual purview nonetheless leaves the space called the Far East in the singular position of virtual exclusion. What does it then mean to enjoy Joyce's "chaffering allincluding most farraginous chronicle" in light of our East Asian perspective? To this second question, my inquiry turns to the dual theme of enjoyment and debt as they are problematized by Stephen Dedalus' telegram to Mulligan, which reads, "the sentimentalist is he who would enjoy without incurring the immense debtorship for a thing done." Itself a quotation from George Meredith's novel The Ordeal of Richard Feverel, the transcribed message invites us to reconsider the scrupulous endeavor underwriting Joyce's signatory gusto, but at the same time forcing us to confront and reassess our own debt to the problematic heritage known as Western literature or, to borrow Derrida's expression, Abrahamic language.

• Science of Emotion and Sensibility
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• v.13 no.1
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• pp.47-60
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• 2010

Most of the researches about classification usually have used kNN(k-Nearest Neighbor), SVM(Support Vector Machine), which are known as learn-based model, and Bayesian classifier, NNA(Neural Network Algorithm), which are known as statistics-based methods. However, there are some limitations of space and time when classifying so many web pages in recent internet. Moreover, most studies of classification are using uni-gram feature representation which is not good to represent real meaning of words. In case of Korean web page classification, there are some problems because of korean words property that the words have multiple meanings(polysemy). For these reasons, LSA(Latent Semantic Analysis) is proposed to classify well in these environment(large data set and words' polysemy). LSA uses SVD(Singular Value Decomposition) which decomposes the original term-document matrix to three different matrices and reduces their dimension. From this SVD's work, it is possible to create new low-level semantic space for representing vectors, which can make classification efficient and analyze latent meaning of words or document(or web pages). Although LSA is good at classification, it has some drawbacks in classification. As SVD reduces dimensions of matrix and creates new semantic space, it doesn't consider which dimensions discriminate vectors well but it does consider which dimensions represent vectors well. It is a reason why LSA doesn't improve performance of classification as expectation. In this paper, we propose new LSA which selects optimal dimensions to discriminate and represent vectors well as minimizing drawbacks and improving performance. This method that we propose shows better and more stable performance than other LSAs' in low-dimension space. In addition, we derive more improvement in classification as creating and selecting features by reducing stopwords and weighting specific values to them statistically.