• The Journal of Asian Finance, Economics and Business
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• 제7권11호
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• pp.657-668
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• 2020

This paper investigates the effect of market structure, including some bank-specific variables and macroeconomic conditions, on the profitability of Indonesian Islamic rural banks. We apply the structure conduct performance (SCP) and the relative market power (RMP) hypothesis. Panel data comprising 142 Islamic rural banks from 2013Q1 to 2018Q4 are employed. This study breaks them apart, associated with the level of economic development consisting of Java as developed regions and outside Java as less developed regions. This study employs static and dynamic panel regression. The GMM method, however, is appropriate because of the dynamic nature of profitability. Our results confirm the SCP hypothesis and fail to support the RMP hypothesis. The higher market concentration allows Islamic rural banks to generate a significantly higher profit by conducting a collusive strategy. More interestingly, the collusive behavior may result in more profit for Islamic rural banks located in the developed regions than those in less developed regions. Evidence also highlights the importance of operating efficiency and impaired financing on profitability. High operating efficiency and low impaired financing can improve profit. Our results suggest that capitalizing market share by improving efficiency and optimizing financing contracts between PLS and non-PLS contracts also improve profit.

• The Journal of Asian Finance, Economics and Business
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• 제7권11호
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• pp.835-842
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• 2020

The study aims to investigate the impact of debt on corporate profitability in the context of Vietnam. The paper investigates the impact of debt on corporate profitability in non-finance listed companies on the Vietnam stock market. The panel data of the research sample includes 118 non-financial listed companies on the Vietnam stock market for a period of nine years, from 2009 to 2017. The Generalized Method of Moments (GMM) is employed to address econometric issues and to improve the accuracy of the regression coefficients. In this research, corporate profitability is measured as the return of EBIT on total assets. The debt ratio is a ratio that indicates the proportion of a company's debt to its total assets. Firm sizes, tangible assets, growth rate, and taxes are control variables in the study. The empirical results show that debt has a statistically significant negative effect on corporate profitability. The result also shows this effect is stronger in a non-linear (concave) way, we show that the debt ratio has nonlinear effects on corporate profitability. From this, experimental evidence shows that the optimal debt ratio is 38.87%. This evidence provides a new insight to managers of the non-finance companies on how to improve the firm's profitability with debt.

• 제어로봇시스템학회논문지
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• 제22권1호
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• pp.1-7
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• 2016

ADAS (Advanced Driver Assistance Systems) requires not only real-time robust lane detection, both straight and curved, but also predicting upcoming steering direction by detecting the curvature of lanes. In this paper, a curvature lane detection algorithm is proposed to enhance the accuracy and detection rate based on using inverse perspective images and Gaussian Mixture Model (GMM) to segment the lanes from the background under various illumination condition. To increase the speed and accuracy of the lane detection, this paper used template matching, RANSAC and proposed post processing method. Through experiments, it is validated that the proposed algorithm can detect both straight and curved lanes as well as predicting the upcoming direction with 92.95% of detection accuracy and 50fps speed.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2004년도 ICEIC The International Conference on Electronics Informations and Communications
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• pp.237-243
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• 2004

A multichannel smart sound sensor capable to detect and identify sound events in noisy conditions is presented in this paper. Sound information extraction is a complex task and the main difficulty consists is the extraction of high­level information from an one-dimensional signal. The input of smart sound sensor is composed of data collected by 5 microphones and its output data is sent through a network. For a real time working purpose, the sound analysis is divided in three steps: sound event detection for each sound channel, fusion between simultaneously events and sound identification. The event detection module find impulsive signals in the noise and extracts them from the signal flow. Our smart sensor must be capable to identify impulsive signals but also speech presence too, in a noisy environment. The classification module is launched in a parallel task on the channel chosen by data fusion process. It looks to identify the event sound between seven predefined sound classes and uses a Gaussian Mixture Model (GMM) method. Mel Frequency Cepstral Coefficients are used in combination with new ones like zero crossing rate, centroid and roll-off point. This smart sound sensor is a part of a medical telemonitoring project with the aim of detecting serious accidents.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2004년도 ICEIC The International Conference on Electronics Informations and Communications
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• pp.92-96
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• 2004

The researches of the emotions are currently great interest in speech processing as well as in human-machine interaction domain. In the recent years, more and more of researches relating to emotion synthesis or emotion recognition are developed for the different purposes. Each approach uses its methods and its various parameters measured on the speech signal. In this paper, we proposed using a short-time parameter: MFCC coefficients (Mel­Frequency Cepstrum Coefficients) and a simple but efficient classifying method: Vector Quantification (VQ) for speaker-dependent emotion recognition. Many other features: energy, pitch, zero crossing, phonetic rate, LPC... and their derivatives are also tested and combined with MFCC coefficients in order to find the best combination. The other models: GMM and HMM (Discrete and Continuous Hidden Markov Model) are studied as well in the hope that the usage of continuous distribution and the temporal behaviour of this set of features will improve the quality of emotion recognition. The maximum accuracy recognizing five different emotions exceeds $88\%$ by using only MFCC coefficients with VQ model. This is a simple but efficient approach, the result is even much better than those obtained with the same database in human evaluation by listening and judging without returning permission nor comparison between sentences [8]; And this result is positively comparable with the other approaches.

• 한국지능시스템학회논문지
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• 제18권3호
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• pp.387-391
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• 2008

움직이는 객체를 검출하기 위해서 정확한 배경을 사용하기 위해 널리 사용되는 방법으로는 가우시안 혼합 모델이다. 가우시안 혼합 모델은 확률적 학습 방법을 사용하는데, 이 방법은 움직이는 배경일 경우와 이동하던 물체가 정지하는 경우 배경을 정확히 모델링하지 못한다. 본 논문에서는 확률적 모델링을 통해 혼잡한 배경을 모델링하고 객체의 계층적 처리를 통해 보다 정확한 배경으로 갱신할 수 있는 학습 방법을 제안한다.

• 한국표면공학회지
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• 제54권5호
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• pp.278-284
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• 2021

Corrosion of steel plate is common phenomenon which results in the gradual destruction caused by a wide variety of environments. Corrosion monitoring is the tracking of the degradation progress for a long period of time. Corrosion on steel plate appears as a discoloration and any irregularities on the surface. In this study, we developed a quantitative evaluation method of the rust formed on steel plate by using k-means clustering from the corroded area in a given image. The k-means clustering for automated corrosion detection was based on the GrabCut segmentation and Gaussian mixture model(GMM). Image color of the corroded surface at cut-edge area was analyzed quantitatively based on HSV(Hue, Saturation, Value) color space.

• 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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• 제8권12호
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• pp.117-127
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• 2021

This study was conducted to comprehensively identify factors that potentially influence corporate investment behavior, including micro, macro, and sectoral variables. Furthermore, investment behavior was studied across nations based on their participation in the global value chain (GVC), which was evaluated based on commodities, limited manufacturing, advanced manufacturing, and innovative activities. The study uses the dynamic panel data analysis and Generalized Method of Moment (GMM) estimation for a sample of 800 corporations, with data spanning over 2000-2019. The study result shows that in all types of countries, the coefficient lag indicator of capital expenditure statistically has a significant effect on capital expenditure. Sales growth, exchange rate, and GDP have a significant positive effect on corporate investment growth, while DER has a negative effect. In commodity countries, corporate investment is influenced by sales growth, exchange rate, and FCI. The variables that influence corporate investment in manufacturing countries are the FCI, exchange rate, sales growth, GDP, and DER. In innovative countries, variables that significantly affect capital expenditure are DER, GDP, and Tobin Q. In each type of country, the interaction terms between exchange rate and commodity price are positive and statistically significant.

• 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.