• Journal of the Korean Data and Information Science Society
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• v.18 no.4
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• pp.955-961
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• 2007

Population projections provides useful basic information for the need of economic resources and labor forces. The National Office of Statistics(NSO) presents population projections for the whole country and some of higher level local governments, but not do projections of the lower level local governments. Here are some projection methods as Hamilton-Perry methods and modified auto regression methods, which are compared to cohort method published by NSO in case of Daegu metropolitan city. The simulation results are a little stagnant with modified auto regression, but a little declines are shown with NSO and HP method, for 2010, 2015 and 2020 year, respectively.

• The Pure and Applied Mathematics
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• v.6 no.2
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• pp.87-93
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• 1999

A holomorphic function f on D = {z : │z│ ＜ 1} is called uniformly locally univalent if there exists a positive constant $\rho$ such that f is univalent in every hyperbolic disk of hyperbolic radius $\rho$. We establish a characterization of uniformly locally univalent functions and investigate uniform local univalence of holomorphic universal covering projections.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.9
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• pp.4429-4447
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• 2018

Local binary descriptors are well-suited for many real-time and/or large-scale computer vision applications, while their low computational complexity is usually accompanied by the limitation of performance. In this paper, we propose a new optimization framework, RLDB (Robust-LDB), to improve a typical region-based binary descriptor LDB (local difference binary) and maintain its computational simplicity. RLDB extends the multi-feature strategy of LDB and applies a more complete region-comparing configuration. A cascade bit selection method is utilized to select the more representative patterns from massive comparison pairs and an online learning strategy further optimizes descriptor for each specific patch separately. They both incorporate LDP (linear discriminant projections) principle to jointly guarantee the robustness and distinctiveness of the features from various scales. Experimental results demonstrate that this integrated learning framework significantly enhances LDB. The improved descriptor achieves a performance comparable to floating-point descriptors on many benchmarks and retains a high computing speed similar to most binary descriptors, which better satisfies the demands of applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.2991-3007
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• 2022

Two dimensional locality preserving projections (2D-LPP) is an improved algorithm of 2D image to solve the small sample size (SSS) problems which locality preserving projections (LPP) meets. It's able to find the low dimension manifold mapping that not only preserves local information but also detects manifold embedded in original data spaces. However, 2D-LPP is simple and elegant. So, inspired by the comparison experiments between two dimensional linear discriminant analysis (2D-LDA) and linear discriminant analysis (LDA) which indicated that matrix based methods don't always perform better even when training samples are limited, we surmise 2D-LPP may meet the same limitation as 2D-LDA and propose a novel matrix exponential method to enhance the performance of 2D-LPP. 2D-MELPP is equivalent to employing distance diffusion mapping to transform original images into a new space, and margins between labels are broadened, which is beneficial for solving classification problems. Nonetheless, the computational time complexity of 2D-MELPP is extremely high. In this paper, we replace some of matrix multiplications with multiple multiplications to save the memory cost and provide an efficient way for solving 2D-MELPP. We test it on public databases: random 3D data set, ORL, AR face database and Polyu Palmprint database and compare it with other 2D methods like 2D-LDA, 2D-LPP and 1D methods like LPP and exponential locality preserving projections (ELPP), finding it outperforms than others in recognition accuracy. We also compare different dimensions of projection vector and record the cost time on the ORL, AR face database and Polyu Palmprint database. The experiment results above proves that our advanced algorithm has a better performance on 3 independent public databases.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2016.09a
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• pp.54-59
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• 2016

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.8
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• pp.87-98
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• 1994

Object-oriented analysis-synthesis coding subdivides each image of a sequence into moving objects and compensates the motion of each object. Thus it can reconstruct real motion better than conventional motion-compensated coding techniques at very-low-bit-rates. It uses a mapping parameter technique for estimating motion information of each object. Since a mapping parameter technique uses gradient operators it is sensitive to redundant details and noise. To accurately determine mapping parameters, we propose a new analysis method using integral projections for estimation of gradient values. Also to reconstruct correctly the local motion the proposed algorithm divides an image into segmented objects each of which having uniform motion information while the conventional one assumes a large object having the same motion information. Computer simulation results with several test sequences show that the proposed image analysis method in object-oriented analysis-synthesis coding shows better performance than the conventional one.

• The Korean Journal of Applied Statistics
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• v.25 no.2
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• pp.239-249
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• 2012

We estimate nonlinear impulse responses of stock indices by asset class by the Local Projection method as suggested by Jorda (2005) to compute impulse responses. The method estimates impulse responses without the specification and estimation of the underlying multivariate dynamic system unlike the usual way of vector autoregression(VAR). It estimates Local Projections at each period of interest rather than extrapolating into increasingly distant horizons with the advantages of easy estimation and non-linear flexible specification. The Local Projection method adequately captures the nonlinearity and asymmetry of the impulse responses of the stock indices compared to those from VARs.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.154-154
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• 2018

To interpret the climate projections for the future as well as present, recognition of the consequences of the climate internal variability and quantification its uncertainty play a vital role. The Korean Peninsula belongs to the Far East Asian Monsoon region and its rainfall characteristics are very complex from time and space perspective. Its internal variability is expected to be large, but this variability has not been completely investigated to date especially using models of high temporal resolutions. Due to coarse spatial and temporal resolutions of General Circulation Models (GCM) projections, several studies adopted dynamic and statistical downscaling approaches to infer meterological forcing from climate change projections at local spatial scales and fine temporal resolutions. In this study, stochastic downscaling methodology was adopted to downscale daily GCM resolutions to hourly time scale using an hourly weather generator, the Advanced WEather GENerator (AWE-GEN). After extracting factors of change from the GCM realizations, these were applied to the climatic statistics inferred from historical observations to re-evaluate parameters of the weather generator. The re-parameterized generator yields hourly time series which can be considered to be representative of future climate conditions. Further, 30 ensemble members of hourly precipitation were generated for each selected station to quantify uncertainty. Spatial map was generated to visualize as separated zones formed through K-means cluster algorithm which region is more inconsistent as compared to the climatological norm or in which region the probability of occurrence of the extremes event is high. The results showed that the stations located near the coastal regions are more uncertain as compared to inland regions. Such information will be ultimately helpful for planning future adaptation and mitigation measures against extreme events.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.6
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• pp.3581-3585
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• 2013

Background: Accurate statistics on the cancer burden are essential, both for purposes of research and for setting priorities in healthcare management. So that in vast countries with partial registration coverage, such as Iran, local data are more useful. We here estimated the incidence, prevalence and mortality time trend of four major cancer site, lung, stomach, breast and prostate, over the period 2001-2010 and provided short-range projections to 2015 in Isfahan. Materials and Methods: Estimates were derived by applying the mortality-incidence analysis method, a back-calculation approach to estimate and project incidence, prevalence and mortality of chronic degenerative disease, starting from knowledge of mortality and relative survival information. Results: Age adjusted incidence, mortality and prevalence rates in Isfahan exhibited a clear upward trend for all four sites during the period 2001-2015, with marked increasees in prostate and breast predicted for the future. Difference in incidence trends between males and females might be attributable to the difference in risk factors specific to certain cancer sites, with smoking being the main risk factor. Conclusions: In this study, males and females displayed an increasing pattern for incidence and mortality rate over the entire study period until 2015. This information can be used as basis for planning healthcare management and allocating recourses in public health.

• KDI Journal of Economic Policy
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• v.42 no.4
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• pp.59-90
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• 2020

U.S. monetary policy has been claimed to generate global spillover and to destabilize other small open economies. We analyze the effects of certain identified U.S. monetary shocks on gross capital flows in the Korean economy using the local projection method. Consistent with previous results on other small open economies, we initially confirm that U.S. interest rate hikes are dynamically correlated with foreign outflows and residents' inflows. That is, not only are they correlated with withdrawals by foreigners but they are also correlated with those by domestic (Korean) investors. The results are mostly driven by portfolio flows. Second, however, the marginal response to a U.S. monetary policy shock is, on average, subdued if we focus on the sample periods after the Global financial crisis of 2007-2008 (henceforth, global financial crisis). We conjecture a possible reason behind the change, an institutional change related to financial friction. If the degree of pledgeability of the value of net worth increases, the marginal responses by both investors would drop with a U.S. monetary policy shock, consistent with our findings.