• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.195-204
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• 2020

The aim of this study is to estimate the impact of ownership structure on the performance of listed firms in transition economy. Buiding upon agency theory, hypotheses on such relationship are proposed. A detailed panel data of 502 non-financial companies listed on Ho Chi Minh Stock Exchange and Hanoi Stock Exchange over the period from 2013 to 2018, and the system generalized method of moment estimation are employed to test the proposed hypotheses. To ensure the reliability of data, this study excludes companies that violate information disclosure regulations or that are subject to special supervision by the State Securities Commission of Vietnam. Some firms with inadequate information, firms that lack the financial data required for creating variable or firms that have inconsistent construction are also re-screened. We only collect the data of enterprises that have ownership structure of two or more components. Estimation results reveal that state ownership has an U-shaped relationship with the performance of Vietnamese listed firms, while foreign ownership and the degree of ownership concentration have an inverted U-shaped relationship with listed firms' performance. The article provides governance implications that Vietnamese listed firms should decrease state ownership and foreign ownership to improve firm performance in order to boost investors' confidence.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2004.11a
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• pp.173-178
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• 2004

The estimation of springing responses for recent ships are carried out and application to a ship design are described. To this aim, springing effects on hull girder were re-evaluated including non-linear wave excitations and torsional vibrations of the hull. The Timoshenko beam model was used to calculate stress distribution on the hull girder by the superposition method. The strip method was employed to calculate the hydrodynamic forces and moments on the hull. In order to remove the irregular frequencies, we adopted 'rigid lid' on the hull free surface level and added asymptotic interpolation along the high frequency range. Several applications to the existing ships were carried out. They are Bishop and Price's container ship, S-175 container ship, large container, VLCC and ore carrier. One of them is compared with ship measurement result while another with that of model test. Comparison between analytical solution and numerical one for homogeneous beam type artificial ship shows good agreement. It is found that most springing energy came from high frequency waves for the ships having low natural frequency and North Atlantic route etc. Therefore, the high frequency tail of the wave spectrum should be increased by $\omega^{-3}\;instead\;of\;\omega^{-4}\;or\;\omega^{-5}$ for springing calculation.

• The Transactions of the Korean Institute of Power Electronics
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• v.6 no.1
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• pp.74-81
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• 2001

The sensorless scheme for Switched Reluctance Motor(SRM) drives must have the robustness and reliability because the noise and error are sensitive. These elements make electrically noisy environments due to the proximity of high current power circuits with small signal electronic circuits when SRM drives. Also, due to the leakage inductances and finite coupling capacitances, these can cause the noise on any low voltage current and voltage measurement circuit. The position estimate error occurs because the current and voltage including the noise are sued as the inputs of sensorless algorithm. In this paper the high robustness and resistance of input noise re described. The fuzzy logic based rotor estimation algorithm and the observer model are used to reduce the tolerance of input data.

• Industrial Engineering and Management Systems
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• v.1 no.1
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• pp.64-72
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• 2002

In the field of plant maintenance, data that are gathered by sensors on multiple machines are handled and analyzed. Online or pseudo online data handling is required on such fields. When the data occurrence speed exceeds the data handling speed, multiple data should be handled at a time (batch data handling or pseudo online data handling). If l amount of data are received at one time following N amount of data, how to estimate the new parameters effectively is a great concern. A new simplified calculation method, which calculates the N data's weights, is introduced. Numerical examples show that this new method has a fairly god estimation accuracy and the calculation time is less than 1/10 compared with the case when the whole data are re-calculated. Even under the restriction calculation ability in the apparatus is limited, this proposed method makes the failure detection of equipments possible in early stages with a few new coming data. This method would be applicable in many data handling fields.

• Nuclear Engineering and Technology
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• v.53 no.11
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• pp.3465-3473
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• 2021

For a long time, research into integrated deterministic-probabilistic safety assessment has been continuously conducted to point out and overcome the limitations of classical ET (event tree)/FT (fault tree) based PSA (probabilistic safety assessment). The current paper also attempts to assert the reason why a technical transformation from classical PSA is necessary with a re-interpretation of the categories of risk. In this study, residual risk was classified into interpolating- and extrapolating-censored categories, which represent risks that are difficult to identify through an interpolation or extrapolation of representative scenarios due to potential nonlinearity between hardware and human behaviors intertwined in time and space. The authors hypothesize that such risk can be dealt with only if the classical ETs/FTs are freely relocated, entailing large-scale computation associated with physical models. The functional elements that are favorable to find residual risk were inferred from previous studies. The authors then introduce their under-development enabling techniques, namely DICE (Dynamic Integrated Consequence Evaluation) and DeBATE (Deep learning-Based Accident Trend Estimation). This work can be considered as a preliminary initiative to find the bridging points between deterministic and probabilistic assessments on the pillars of big data technology.

• Journal of Climate Change Research
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• v.6 no.1
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• pp.21-31
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• 2015

Various crop models have been extensively used for estimation of the crop yields. Compared to the other models, the EPIC model uses a unified approach to simulate more than 100 types of crops. It has been successfully applied in simulating crop yields for various combinations of weather conditions, soil properties, crops, and management schemes in many countries. The objective of this study was to estimate the rice and maize yield in South Korea using the EPIC model. The input datasets for the 30 types in the 11 categories were created for the EPIC model. The EPIC model simulated rice and maize yields. The performance of the EPIC model was evaluated with the goodness-of-fit measures including Root Mean Square Error (RMSE), Relative Error (RE), Nash-Sutcliffe Efficiency Coefficient (NSEC), Mean Absolute Error (MAE), and Pearson Correelation Coefficient (r). The rice yield showed to more high accuracy than maize yield on four type of method without NSEC. Theses results showed that the EPIC model better simulated rice yields than maize yields. The results suggest that the EPIC crop model can be useful to estimate crop yield in South Korea.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.36 no.3
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• pp.169-176
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• 2020

The authors developed a nodal network model that simulates the flow of moist air and the thermal behavior of a target area. The nodal network model was enhanced using a parameter estimation technique based on the measured temperature, humidity, and schedule data. However, the nodal model is not good enough for predicting humidity of the target space, having 55.6% of CVRMSE. It is because re-evaporation effect could not be modeled due to uncertain factors in the field measurement. Hence, a data-driven model was introduced using an artificial neural network (ANN). It was found that the data-driven model is suitable for predicting the condensation compared to the nodal model satisfying ASHRAE Guideline with 3.36% of CVRMSE for temprature, relative humidity, and surface temperature on average. The model will be embedded in automated devices for real-time predictive control, to minimize the risk of surface condensation at dressroom in an apartment housing.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.744-747
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• 2008

Quantity information focused on a design drawing plays a critical role in a decision making related to cost for project participants during project life cycles. Related participants absolutely depend on quantity take-off working which produces the quantity information by hand, and then a worker's mistake often causes many errors. The difference of quantity by the know-how of the person in charge of the estimation also occurs. In addition, the worker passes through the whole quantity take-off processes again in case of re-working for quantity take-off produced by a change order. The requirements about the automated estimation increase because of the needs for the accurate quantity take-off and dealing with the change order and recently, the studies about the automated estimation working process based on 34 cad model from 3d cad modeler are attempted in various viewpoints. However, the existing studies reach the limits such as common quantity data type framework for getting Quantity information. Focused on a certain 34 cad modeler and BIM based automation of estimation using it Therefore, the objective of this study is to develop the a series of system which can extract, analyze, and verify Quantity Data Type in modeler to automate quantity take-off originated from various 3d cad modelers as a foundation study for BIM based automation of estimation framework.

• Journal of Broadcast Engineering
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• v.14 no.2
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• pp.107-113
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• 2009

In Digital On-Channel Repeaters (DOCR) of Terrestrial-DMB (Digital Multimedia Broadcasting), there exist feedback signals generated from transmit antenna and re-entering at receive antenna. Therefore DOCR becomes unstable unless the feedback signal is properly eliminated. Previous research proposed a feedback canceller to estimate the feedback channel to deal with this problem. However formerly used estimation algorithms show unsatisfied performance in terms of convergence rate and quality although their implementations are simple. This paper applies PNLMS (Proportionate Normalized Least Mean Squares) adaptive algorithm to feedback channel estimation and evaluates the performances which solve the problem of feedback signal effectively.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.1
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• pp.232-238
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• 2013

This paper study the position estimation of MBK system according to the non-linear filter for non-Gaussian noise in underwater sensor networks. In the filter to estimate location, recently, the extended Kalman filter (EKF) and particle filter are getting attention. EKF is widely used due to the best algorithm in the Gaussian noise environment, but has many restrictions on the usage in non-Gaussian noise environment such as in underwater. In this paper, we propose the improved One-Dimension Particle Filter (ODPF) using the distribution re-interpretation techniques based on the maximum likelihood. Through the simulation, we compared and analyzed the proposed particle filter with the EKF in non-Gaussian underwater sensor networks. In the case of both the sufficient statistical sample and the sufficient calculation capacity, we confirm that the ODPF's result shows more accurate localization than EKF's result.