• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.11 no.3
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• pp.37-41
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• 2007

The semi-convexity for planar shapes has been recently introduced in [2]. As a generalization of the convextiy, semi-convexity is closed under the Minkowski sum. But the definition of semi-convexity requires that the shape boundary should satifisfy a differentiability condition $C^{1:1}$, which means that it should be possible to take the normal vector field along the domain's extended boundary. In view of the fact that the semi-convextiy is a most natural generalization of the convexity in many respects, this is a severe restriction for the semi-convexity, since the convexity requires no such a priori differentiability condition. In this paper, we generalize the semi-convexity to the closure of the class of semi-convex $\mathcal{M}$-domains for any Minkowski class $\mathcal{M}$, and show that this generalized semi-convexity is also closed under Minkowski sum.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.24 no.1
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• pp.1-6
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• 2021

Next-generation sequencing (NGS) technologies have changed the process of genetic diagnosis from a gene-by-gene approach to syndrome-based diagnostic gene panel sequencing (DPS), diagnostic exome sequencing (DES), and diagnostic genome sequencing (DGS). A priori information on the causative genes that might underlie a genetic condition is a prerequisite for genetic diagnosis before conducting clinical NGS tests. Theoretically, DPS, DES, and DGS do not require any information on specific candidate genes. Therefore, clinical NGS tests sometimes detect disease-related pathogenic variants in genes underlying different conditions from the initial diagnosis. These clinical NGS tests are expensive, but they can be a cost-effective approach for the rapid diagnosis of rare disorders with genetic heterogeneity, such as the glycogen storage disease, familial intrahepatic cholestasis, lysosomal storage disease, and primary immunodeficiency. In addition, DES or DGS may find novel genes that that were previously not linked to human diseases.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.44.2-44.2
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• 2021

Detecting lensed quasar systems and estimating their time delays using the unresolved joint light curves can be the next frontier among the cosmological probes in the near future. One can get the independent measurement of the Hubble constant from the time delays but without requiring the systems to be resolved a priori followed by monitoring the image light curves using high-resolution telescopes for years. In this work, we propose a novel technique that can identify lensed quasars only using the observed unresolved light curves and without assuming a template or any prior information. Following a set of conservative selection criteria that gives zero false-positive outcome, we can accurately estimate the time delay for almost all the lensed systems with marginal noise in the data. For the case of noisy data, our approach can still correctly identify a substantial number of lensed systems with high certainty and measure the time delay accurately.

• Educational Technology International
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• v.9 no.1
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• pp.49-77
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• 2008

As clearly suggested in the case of Wikipedia, collective intelligence is predicted to develop into the most important platform of knowledge and information in the future society. But it just remains at the level of activities for group projects in the present frame of education and so it doesn't lead to creating collective intelligence. This study looks into an 'information repository model of collective intelligence' that makes it possible to deliver an education process a priori of Shared Knowledge Reservoir to "Junior Digital Nomad", who is definitely and will be in existence, and that further enables them to be active there in reality. Based on this storage model, it suggests a practicable web system model; Junior Maphistory e-encyclopedia, which is appropriately consistent with the features of Web 2.0 and can grow into a general historical and geographical information service.

• Journal of Mechanical Science and Technology
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• v.16 no.11
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• pp.1522-1539
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• 2002

In the present study, an explicit algebraic stress model is shown to be the exact tensor representation of algebraic stress model by directly solving a set of algebraic equations without resort to tensor representation theory. This repeals the constraints on the Reynolds stress, which are based on the principle of material frame indifference and positive semi-definiteness. An a priori test of the explicit algebraic stress model is carried out by using the DNS database for a fully developed channel flow at Rer = 135. It is confirmed that two-point correlation function between the velocity fluctuation and the Laplacians of the pressure-gradient i s anisotropic and asymmetric in the wall-normal direction. Thus, a novel composite algebraic Reynolds stress model is proposed and applied to the channel flow calculation, which incorporates non-local effect in the algebraic framework to predict near-wall behavior correctly.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.905-908
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• 2008

In this paper, an Adaptive Modulation (AM) system with an efficient turbo-coded Vertical-Bell-lab Layered Space-Time (V-BLAST) technique is proposed. The proposed decoding algorithm adopts iteratively the extrinsic information from a Maximum a Posteriori (MAP) decoder as a priori probability in the two decoding procedures of the V-BLAST scheme of ordering and slicing. In this analysis, each MIMO channel is assumed to be a part of the system of performance improvement.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.348-353
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• 2003

This paper considers the optimal control problem in real-time control systems with random time-delays. It proposes an algorithm which uses the linear quadratic (LQ) control method and a dedicated technique to compensate for the time-delay effects. Since it is assumed that the time-delays are unknown but the probability distribution of the delays are known a priori, the algorithm considers the mean value of the time-delays as a nominal value for random delay compensation. An example is given to show the performance of the proposed algorithm, where an inverted pendulum system is controlled over a controller-area network (CAN). Simulation results show that the proposed algorithm provides good performance results. It is shown that our algorithm is comparable to existing algorithms in both computation cost and performance.

• Journal of Information Processing Systems
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• v.12 no.1
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• pp.149-168
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• 2016

The Active Appearance Model (AAM) is a class of deformable models, which, in the segmentation process, integrates the priori knowledge on the shape and the texture and deformation of the structures studied. This model in its sequential form is computationally intensive and operates on large data sets. This paper presents another framework to implement the standard version of the AAM model. We suggest a distributed and parallel approach justified by the characteristics of the model and their potentialities. We introduce a schema for the representation of the overall model and we study of operations that can be parallelized. This approach is intended to exploit the benefits build in the area of advanced image processing.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.4
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• pp.36-44
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• 1997

An efficient context-free multiple-object segmentation using attention operator based on modified generalized symmetry transform is proposed and implemented by modifying a radial basis function network. By using the difference of intensity gradient, instead of te intensity gradient itself, in generalized symmetry tranform so as to make the attention operator to preserve the edges of the objects shape, an efficient context-free multiple-object segementation is proposed in which no a priori shape informtion on the objects is requried. The attention operator is implemented by using a modified radial basis function network which can reflect symmetry, and by using te edge pyramid of the input image, both of the local and the global symmetry of the objects are reflected simultaneously to make the multiple-object with different sizes be segmented with a singel fixed-size $n\timesm$ can be done with O(n) complexity. The simulaton results show that the proposed algorithm can efficiently be used in context-free multiple-object segmentation even for the low contrast IR images as well as for the images from the camera.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.8
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• pp.1939-1951
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• 1994

This study introduces a new tool breakage detecting technology comprised of an unsupervised neural network combined with adaptive time series autoregressive(AR) model where parameters are estimated recursively at each sampling instant using a parameter adaptation algorithm based on an RLS(Recursive Least Square). Experiment indicates that AR parameters are good features for tool breakage, therefore it can be detected by tracking the evolution of the AR parameters during milling process. an ART 2(Adaptive Resonance Theory 2) neural network is used for clustering of tool states using these parameters and the network is capable of self organizing without supervised learning. This system operates successfully under the wide range of cutting conditions without a priori knowledge of the process, with fast monitoring time.