• The Journal of Asian Finance, Economics and Business
• /
• v.7 no.6
• /
• pp.157-172
• /
• 2020

This study attempts to analyze trade flows between Vietnam and China in order to understand the mutual influence of bilateral trade relations. China is a country with the world's leading economic potential. China and Vietnam are neighboring countries sharing a border of 1,281 km. Trade relations between the two countries are a necessity and, with a right policy, are beneficial to both. Vietnam has a trade deficit with China. This situation is exacerbated by the continuing rise in the gap. Vietnam trade deficit from China was USD12.5 billion in 2010, increasing to USD24 billion in 2018. Data are extracted from the 2015 national input-output tables of Vietnam and China as well as Vietnam Household Living Standard Survey statistics. The research identified 36 sectors of bilateral input-output trade between Vietnam and China. A bilateral output-input model is applied to analyze how final demand and use of input in the production of this country induces output and value added of the other country. The results show that China benefits more from Vietnam's production and consumption than Vietnam does. Vietnam's inter-sector structure does not stimulate domestic production due to the absence of supporting products as inputs in the production process.

• Journal of Internet of Things and Convergence
• /
• v.9 no.2
• /
• pp.71-76
• /
• 2023

In this paper, we propose a smoothed received signal strength indicator (RSSI)-based distance estimation using deep neural network (DNN) for accurate distance estimation in an environment where a single receiver is used. The proposed scheme performs a data preprocessing consisting of data splitting, missing value imputation, and smoothing steps to improve distance estimation accuracy, thereby deriving the smoothed RSSI values. The derived smoothed RSSI values are used as input data of the Multi-Input Single-Output (MISO) DNN model, and are finally returned as an estimated distance in the output layer through input layer and hidden layer. To verify the superiority of the proposed scheme, we compared the performance of the proposed scheme with that of the linear regression-based distance estimation scheme. As a result, the proposed scheme showed 29.09% higher distance estimation accuracy than the linear regression-based distance estimation scheme.

• 한국정보디스플레이학회:학술대회논문집
• /
• 2002.08a
• /
• pp.567-570
• /
• 2002

The LVDS (Low Voltage Differential Signaling) I/O cells, fully compatible with ANSI TIA/ EIA-644 LVDS standard, are designed using a 0.35${\mu}m$ standard CMOS technology. With a single 3V supply, the core cells operate at 1.34Gbps and power consumption of the output driver and the input receiver is 10. 5mW and 4.2mW, respectively. In the output driver, we employ the DCMFB (Dynamic Common-Mode FeedBack) circuit which can control the DC offset voltage of differential output signals. The SPICE simulation result of the proposed output driver shows that the variation of the DC offset voltage is 15.6% within a permissible range. In the input receiver, the proposed dual input stage with a positive feedback latch covers rail-to-rail input common-mode range and enables a high-speed, low-power operation. 5-channels of the proposed LVDS I/O pair can handle display data up to 8-bit gray scale and UXGA resolution.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.27 no.1
• /
• pp.50-58
• /
• 2017

For nonlinear control system design, there are many studies based on TSK fuzzy model. However, TSK fuzzy modelling needs nonlinear dynamic equations of the object system or a data set fully distributed in input-output space. This paper proposes an modelling technique using only step input response data. The technique uses also the genetic algorithm. The object systems in this paper are nonlinear to control input variable or output variable. In the case of nonlinear to control input, response data obtained with several step input values are used. In the case of nonlinear to output, step input response data and zero input response data are used. This paper also presents a fuzzy controller design technique from TSK fuzzy model. The effectiveness of the proposed techniques is verified with numerical examples.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2004.11a
• /
• pp.999-1004
• /
• 2004

In this study, we identify contribution of structure-borne-noise of vehicle HVAC system using Multi-Dimensional spectral analysis (MDSA) method. Firstly, to identify the applicability of MDSA method, the case of HVAC system was modeled with four input / single output system. The four inputs which is given vibration data is composed of blower, evaporator, heater and duct. The single output is noise data from driver's seat. When the blower motor is operating, we analyze the contributions of four input / single output. As a result of experiment, we identify efficiency of systems modeled with four input / single output through ordinary coherence function (OCF) and multiple coherence function (MCF).

• Journal of Institute of Control, Robotics and Systems
• /
• v.8 no.7
• /
• pp.556-562
• /
• 2002

This paper studies the identification of a combustion model, which is used to design a linear controller of a steam generation quantity and harmful exhaust gases of a Refuse Incineration Plant(RIP). Even though the RIP has strong nonlinearities and complexities, it is identified as a MIMO parametric ARX model from experimental input-output data sets. Unknown model parameters are decided from experimental input-output data sets, using system identification algorithm based on Instrumental Variables(IV) method. It is shown that the identified model well approximates the input-output combustion characteristics.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2006.05a
• /
• pp.1707-1714
• /
• 2006

In order to enhance sustainable war fighting capabilities, it is important to maintain a good ammunition support system. In this paper, we evaluate the performance of Ammunition companies using Imprecise Data Envelopment Analysis (IDEA)-BCC and IDEA-Additive model, which can deal with imprecise data in DEA. In order to select a list of input and output variables, we used a multiple regression analysis. We could choose input variables that have significant effects on the output performance with stepwise regression model. From the regression analysis, the number of soldiers, officers, and ammunition warehouses were selected as the input variables. Seven out of sixteen Ammunition companies were found to be inefficient by the IDEA-BCC model. And using IDEA-Additive model, we could identify the input excess and the output shortfall in reaching at a point on the efficiency frontier.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.45 no.3
• /
• pp.57-65
• /
• 2022

DEA(data envelopment analysis) is a technique for evaluation of relative efficiency of decision making units (DMUs) that have multiple input and output. A DEA model measures the efficiency of a DMU by the relative position of the DMU's input and output in the production possibility set defined by the input and output of the DMUs being compared. In this paper, we proposed several DEA models measuring the multi-period efficiency of a DMU. First, we defined the input and output data that make a production possibility set as the spanning set. We proposed several spanning sets containing input and output of entire periods for measuring the multi-period efficiency of a DMU. We defined the production possibility sets with the proposed spanning sets and gave DEA models under the production possibility sets. Some models measure the efficiency score of each period of a DMU and others measure the integrated efficiency score of the DMU over the entire period. For the test, we applied the models to the sample data set from a long term university student training project. The results show that the suggested models may have the better discrimination power than CCR based results while the ranking of DMUs is not different.

• The Korean Journal of Applied Statistics
• /
• v.15 no.1
• /
• pp.33-43
• /
• 2002

Various kinds of estimation methods have been developed for imputation of categorical missing data. They include category method, logistic regression, and association rule. In this study, we propose two fusions algorithms based on both neural network and voting scheme that combine the results of individual imputation methods. A Mont-Carlo simulation is used to compare the performance of these methods. Five factors used to simulate the missing data pattern are (1) input-output function, (2) data size, (3) noise of input-output function (4) proportion of missing data, and (5) pattern of missing data. Experimental study results indicate the following: when the data size is small and missing data proportion is large, modal category method, association rule, and neural network based fusion have better performances than the other methods. However, when the data size is small and correlation between input and missing output is strong, logistic regression and neural network barred fusion algorithm appear better than the others. When data size is large with low missing data proportion, a large noise, and strong correlation between input and missing output, neural networks based fusion algorithm turns out to be the best choice.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2001.10a
• /
• pp.213-217
• /
• 2001

This paper deals with the estimation of efficiency of Telecommunication Operators(TOs) using DEA (Data Envelopment Analysis). The measure of efficiency using DEA accomplishes next two steps. First, the efficient frontier is derived using the data of input and output. And then the efficiency of the decision making units are measured by the distances from this frontier To measure efficiency, we consider a one-output, three-input production function. We use the tangible assets, investment cost, the number of employees for input data and measure the output by the revenue. After measuring the efficiency, We can compare the domestic TOs with the international TOs and the wire TOs with wireless ones by average efficiency. After accomplishing the analysis of efficiency, the internal/external efficiency is measured simultaneously through correlation between efficiency and profitability, quality level.