• The Journal of Asian Finance, Economics and Business
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• 제8권11호
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• pp.191-201
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• 2021

This article examines the role of financial development in economic growth in a number of transitional economies where the financial systems were newly established or reformed only in the early 1990s to facilitate their transition from centrally planned economies to market-based ones. Based on a dataset collected from 29 transitional economies and 5 Asian developing economies covering the period 1990-2020, an empirical endogenous growth model is specified and estimated using the generalized method of moments (GMM). Three measures of financial development are used to investigate the relative role of the banking system and stock exchange market in the process of transition and growth. The results show that the three measures of financial development are crucial determinants of economic growth in transitional economies but the link seems to be in an inverted U-shape. This suggests the existence of thresholds for different channels of the financial sector to expand to positively influence growth. When becoming too large relative to the size of the economy, the financial system would have become a factor not conducive to growth. The growth convergence hypothesis is also confirmed and the impacts of other growth determinants are overall consistent with the extant literature.

• The Journal of Asian Finance, Economics and Business
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• 제8권10호
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• pp.327-339
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• 2021

This study examines the impact of bank restructuring on the financial performance of commercial banks in Vietnam. The data for this study was obtained from the audited financial statements of 30 Vietnamese commercial banks from 2007 to 2019. Multiple regression analysis was used for investigation. Financial performance, as evaluated by ROAA, ROEA, and NIM, is the dependent variable. Financial restructuring, ownership restructuring, and operational restructuring are the independent variables. Pooled least squares (Pooled OLS), fixed effects model (FEM), random effects model (REM), and system generalized moment regression model (System GMM) are the estimate methods used to increase the accuracy of the regression coefficient. The research results show that the variables of financial restructuring activities such as government intervention and the ratio of equity to total assets; variables of ownership restructuring such as capital adequacy ratio, privatization of state-owned commercial banks, mergers, and acquisitions; variables of operational restructuring such as employees, branches, the cost to total assets; GDP variables and the second restructuring period have a positive impact on financial performance. Variables such as debt-to-capital ratio, bad debt ratio, state ownership ratio, expense-income ratio, and inflation have a negative effect on financial performance.

• 한국컴퓨터정보학회논문지
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• 제23권11호
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• pp.51-57
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• 2018

In this paper, we studied about the extraction of the parameter and implementation of speechreading system to recognize the Korean 8 vowel. Face features are detected by amplifying, reducing the image value and making a comparison between the image value which is represented for various value in various color space. The eyes position, the nose position, the inner boundary of lip, the outer boundary of upper lip and the outer line of the tooth is found to the feature and using the analysis the area of inner lip, the hight and width of inner lip, the outer line length of the tooth rate about a inner mouth area and the distance between the nose and outer boundary of upper lip are used for the parameter. 2400 data are gathered and analyzed. Based on this analysis, the neural net is constructed and the recognition experiments are performed. In the experiment, 5 normal persons were sampled. The observational error between samples was corrected using normalization method. The experiment show very encouraging result about the usefulness of the parameter.

• 한국도로학회논문집
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• 제14권3호
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• pp.77-85
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• 2012

자동사고검지 알고리즘의 대부분은 사고가 발생했을 때 사고로 검지하지 못하고, 혼잡으로 검지하는 경우가 많다는 문제점을 가지고 있다. 또한 교통정보센터 운영자들은 교통사고검지시스템을 운영하면서 대부분 CCTV 육안감시 또는 운전자들의 신고에 의존하여 사고처리를 하고 있는 실정이다. 그 이유는 현재 운영되고 있는 교통사고검지시스템에서는 실제 사고가 아닌데도 불구하고, 사고라는 오검지 경고가 많이 발생되어 시스템 전체의 신뢰도가 떨어진다는 문제점이 있기 때문이다. 다시 말해 교통사고검지시스템의 알고리즘은 검지율(Detection probability)이 높아야 함과 동시에, 오검지율(False alarm probability)은 낮아야 하고, 정확한 사고지점과 시간을 검지해 낼 수 있어야 한다. 이에 본 연구는 검지율을 높이고 동시에, 오검지율을 낮추는 방법으로 기 개발된 가우시안 혼합모델(Gaussian Mixture Model)과 개별차량 Tracking을 이용하여 개발한 사고검지 알고리즘을 교통정보센터 관리시스템(Center Management System)에 적용하고, 실제 교통상황에서 사고검지율과 오검지의 빈도를 측정하여 그 효과를 검증 및 평가하고자 한다.

• 재무관리연구
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• 제24권1호
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• pp.109-147
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• 2007

코스닥 기업의 자본구조 결정요인을 연구하기 위하여 정태적 모형과 동태적 모형을 이용하였다. 레버리지와 기업특성변수들과의 관계, 자본구조의 조정속도, 목표자본구조의 존재여부 등을 실증분석 하였다. 정태적 모형의 결과에서 코스닥 기업의 수익성과 레버리지, 유동성과 레버리지는 음(-)의 유의적인 관계가 있어 정보비대칭으로 인하여 경영자는 자본비용이 낮은 내부자금조달을 선호한다는 자본조달우선순위이론과 부합하였다. 기업규모는 레버리지와 양(+)의 관계가 존재하여 대기업은 소기업보다 파산비용이 상대적으로 낮아 부채발행을 증가시킨다는 절충이론의 내용과 부합하였다. 코스닥 50기업에서 이익변동성은 레버리지와 양(+)의 유의적인 관계가 있었다. 이익변동성이 큰 기업은 부채의 대리인비용이 낮아 부채발행으로 자본조달을 증가시킨다는 주장을 지지하였다. 동태적 모형의 분석 결과 코스닥기업은 목표자본구조를 가지고 있는 것으로 나타났다. 최적자본구조로의 조정속도의 검증에서 코스닥 50기업의 조정속도가 코스닥 전체기업의 조정속도보다 느렸다. 이런 결과로 볼 때 코스닥 50기업은 은행과의 밀접한 관계 그리고 기업퇴출제도의 미비 등으로 목표자본구조로 부터의 이탈비용이 코스닥 전체기업보다는 전반적으로 낮음을 알 수 있었다.

• 한국해양공학회지
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• 제28권6호
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• pp.552-559
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• 2014

In general, the number of underwater transient signals is very limited for research on automatic recognition. Data-dependent feature extraction is one of the most effective methods in this case. Therefore, we suggest WPCC (Wavelet packet ceptsral coefficient) as a feature extraction method. A wavelet packet best tree for each data set is formed using an entropy-based cost function. Then, every terminal node of the best trees is counted to build a common wavelet best tree. It corresponds to flexible and non-uniform filter bank reflecting characteristics for the data set. A GMM (Gaussian mixture model) is used to classify five classes of underwater transient data sets. The error rate of the WPCC is compared using MFCC (Mel-frequency ceptsral coefficients). The error rates of WPCC-db20, db40, and MFCC are 0.4%, 0%, and 0.4%, respectively, when the training data consist of six out of the nine pieces of data in each class. However, WPCC-db20 and db40 show rates of 2.98% and 1.20%, respectively, while MFCC shows a rate of 7.14% when the training data consists of only three pieces. This shows that WPCC is less sensitive to the number of training data pieces than MFCC. Thus, it could be a more appropriate method for underwater transient recognition. These results may be helpful to develop an automatic recognition system for an underwater transient signal.

• 유통과학연구
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• 제15권1호
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• pp.123-130
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• 2017

Purpose - This research aims to examine the effect of e-business adoption on firm's growth and profitability in the distribution industry. The value added from the distribution industry acts as the cost of other industries. As the distribution industry develops, its stage becomes shorter and the distribution margin becomes smaller. Therefore, e-business is expected to have a different effect on the distribution industry than other industries. Research design, data and methodology - The previous research generally used e-business adoption as an independent variable and firm's performance as a dependent variable. This study elaborated the model using a dynamic panel model that includes the performance variable of the previous year as an independent variable. By employing system GMM (Generalized Method of Moments), the endogeneity problem in the dynamic panel model can be solved. For the analysis, I extracted the distribution companies as the raw data in the National Statistical Office's Business Activity Survey over the period 2006 to 2012. Results - The growth rate of firms adopting e-business was 0.299%p higher than that of the non-adopter. However, only ERP (Enterprise Resource Planning), KMS (Knowledge Management System) and SCM (Supply Chain Management) contributed positively to the growth rate. In the case of profitability, it was 0.04%p higher than the distribution companies that did not adopt e-business. ERP and LMS (Learning Management System) improve profitability, while SCM reduces profitability. Consequently, while ERP improves both growth and profitability, SCM improves growth but reduces profitability. In addition, KMS improves firm's growth only, and LMS does only profitability, showing that each e-business has a differentiated effect. Conclusions - Since the distribution industry has different characteristics from manufacturing and other service industries, the introduction of e-business may not guarantee the growth and profitability of distribution companies. Careful introduction considering the characteristics of the distribution industry is required. In particular, it is necessary to select an e-business meeting the characteristics and needs of a distribution company, and thereafter, it is required for the company's own efforts to internalize it within the system.

• 한국통신학회논문지
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• 제39C권4호
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• pp.315-325
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• 2014

유비쿼터스 환경에서 실내 공간의 사용자 위치정보는 다양한 응용분야에서 사용자에 특화된 서비스를 제공하는데 필요한 필수적인 정보이기 때문에 매우 중요하다. 기존연구들은 규모가 큰 건물에서의 사용자 위치 예측만 고려하고 있고 실험 대상이 되는 공간에서 고정된 AP가 다수 존재한다고 가정한다. 그러나 일반 가정은 면적이 좁은 공간들로 구성되며 고정된 AP가 소수이고 변화가 유동적인 환경이다. 본 논문에서는 기존 연구들이 AP환경이 비교적 안정적인 큰 건물에서의 사용자 위치 예측에 집중한 것과 달리, 일반 가정환경에서 와이파이 핑거프린트 방식을 기반으로 하여 공간을 식별하고 사용자의 위치를 Room-level로 예측하는 사용자 공간 예측 시스템을 제안한다. 실제 가정에서 실험을 한 결과 제안하는 시스템이 모든 가정에서 평균 80%이상의 정확도로 사용자가 위치한 공간을 예측함을 알 수 있었다.

• The Journal of Asian Finance, Economics and Business
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• 제6권3호
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• pp.67-79
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• 2019

This study examines the impact of corporate governance on capital structure decisions based on a large panel of Chinese listed firms. Using the system Generalized Method of Moments (GMM) estimator to control for unobserved heterogeneity, endogeneity, and persistency in capital structure decisions, we document that the ownership structure plays a significant role in determining leverage ratios. More specially, we find that managerial ownership has a positive and significant impact on firms' leverage, consistent with the incentive alignment hypothesis. We also find that managerial ownership only affects the leverage decisions of private firms in the post-2005 split share reform period. State ownership negatively influence leverage decisions implying that SOEs may face fewer restrictions in equity issuance and may receive favourable treatments when applying for seasoned equity ¿nancing, thus use less debt. Furthermore, our results show that while foreign ownership negatively influences leverage decisions, legal person shareholding positively influences firms' leverage decisions only for state controlled firms. We also find that the board structure variables (board size and the proportion of independent directors) do not influence firms' capital structure decisions. Our findings suggest that recent ownership reforms have been successful in terms of providing incentive to managers through managerial shareholdings to take risky financial choices.

• 로봇학회논문지
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• 제10권1호
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• pp.33-41
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• 2015

Recent developments in robotics and intelligent vehicle area, bring interests of people in an autonomous driving ability and advanced driving assistance system. Especially fully automatic parking ability is one of the key issues of intelligent vehicles, and accurate parked vehicles detection is essential for this issue. In previous researches, many types of sensors are used for detecting vehicles, 2D LiDAR is popular since it offers accurate range information without preprocessing. The L shape feature is most popular 2D feature for vehicle detection, however it has an ambiguity on different objects such as building, bushes and this occurs misdetection problem. Therefore we propose the accurate vehicle detection method by using a 3D complete vehicle model in 3D point clouds acquired from front inclined 2D LiDAR. The proposed method is decomposed into two steps: vehicle candidate extraction, vehicle detection. By combination of L shape feature and point clouds segmentation, we extract the objects which are highly related to vehicles and apply 3D model to detect vehicles accurately. The method guarantees high detection performance and gives plentiful information for autonomous parking. To evaluate the method, we use various parking situation in complex urban scene data. Experimental results shows the qualitative and quantitative performance efficiently.