• Genomics & Informatics
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• v.20 no.3
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• pp.34.1-34.11
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• 2022

Multilevel analysis is an appropriate and powerful tool for analyzing hierarchical structure data widely applied from public health to genomic data. In practice, however, we may lose the information on multiple nesting levels in the multilevel analysis since data may fail to capture all levels of hierarchy, or the top or intermediate levels of hierarchy are ignored in the analysis. In this study, we consider a multilevel linear mixed effect model (LMM) with single imputation that can involve all data hierarchy levels in the presence of missing top or intermediate-level clusters. We evaluate and compare the performance of a multilevel LMM with single imputation with other models ignoring the data hierarchy or missing intermediate-level clusters. To this end, we applied a multilevel LMM with single imputation and other models to hierarchically structured cohort data with some intermediate levels missing and to simulated data with various cluster sizes and missing rates of intermediate-level clusters. A thorough simulation study demonstrated that an LMM with single imputation estimates fixed coefficients and variance components of a multilevel model more accurately than other models ignoring data hierarchy or missing clusters in terms of mean squared error and coverage probability. In particular, when models ignoring data hierarchy or missing clusters were applied, the variance components of random effects were overestimated. We observed similar results from the analysis of hierarchically structured cohort data.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.21 no.6
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• pp.333-339
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• 2009

The objective of this study is to predict optimal intermediate pressure of a 2-stage compression heat pump system using river water. To determine the maximum performance of the 2-stage compression heat pump system, the experimental evaluations on the 2-stage compression cycle were carried out under various operating conditions. Electronic expansion valves were applied to control intermediate pressure and superheat. Based on the experimental data, an empirical correlation for predicting optimal intermediate pressure which considering cycle operating parameters was developed. The present correlation was verified by comparing the predicted data with the measured data. The predictions showed a good agreement with the measured data within a relative deviation of ${\pm}4%$ at various operating conditions.

• Journal of the Korea Society of Computer and Information
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• v.23 no.12
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• pp.123-129
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• 2018

The purpose of this paper is to draw a conclusion on the impact of intermediate software on enterprise results. In this paper, product innovation and product reliability are especially used as analytical factors. An exploratory analytical study is conducted on the competitiveness of intermediate software, in the hope of gaining a new understanding of the competitiveness of intermediate software. Data are analyzed using such quantitative analytical tools as SPSS and AMOS. Using reliability analysis, validity analysis and structural equation model analysis, the final results are achieved. According to the analysis results, we can draw the following conclusions: the competitiveness of intermediate software has a positive impact on the innovation of software products. The competitiveness of intermediate software doesn't have a positive impact on the reliability of software products. Product innovation has a positive impact on enterprise results. Product reliability also has a positive impact on enterprise results. By analyzing the conclusions, we can make certain suggestions and draw implications on the competitiveness of China's software industry.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.5
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• pp.2590-2606
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• 2017

Generally, research of classical image classification algorithms assume that training data and testing data are derived from the same domain with the same distribution. Unfortunately, in practical applications, this assumption is rarely met. Aiming at the problem, a domain adaption image classification approach based on multi-sparse representation is proposed in this paper. The existences of intermediate domains are hypothesized between the source and target domains. And each intermediate subspace is modeled through online dictionary learning with target data updating. On the one hand, the reconstruction error of the target data is guaranteed, on the other, the transition from the source domain to the target domain is as smooth as possible. An augmented feature representation produced by invariant sparse codes across the source, intermediate and target domain dictionaries is employed for across domain recognition. Experimental results verify the effectiveness of the proposed algorithm.

• Korea Trade Review
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• v.46 no.5
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• pp.83-98
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• 2021

This study aims to examine the effects of international trade in intermediate input on the implications of international business cycle properties in Korea. To do this, I have extended standard one goods New Keynesian international business cycle model to incorporate the role of intermediate inputs. After constructing the DSGE model, I have analysed the impulse response function and varian decomposition results. The results show that the model could introduce a new channel, that is, "cost channel" like Eyquem and Kamber (2014). In other words, the model has changed the dynamics of aggregate inflation by the cost channel. When the trade in intermediate goods increase, which is measured by openness of foreign input, the volatility of output, consumption and inflation increase two or three times. However, the model itself fails to explain the full account of cycle behavior of historical data, but the results imply that the trade in intermediate input assumption can help to improve the forecasting ability of international business cycle models.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.07a
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• pp.258-261
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• 2018

The purpose of this paper is to draw a conclusion on the impact of intermediate software on enterprise results. In this paper, product innovation and product reliability are especially used as analytical factors. An exploratory analytical study is conducted on the competitiveness of intermediate software, in the hope of gaining a new understanding of the competitiveness of intermediate software. Data are analyzed using such quantitative analytical tools as SPSS and AMOS. Using reliability analysis, validity analysis and structural equation model analysis, the final results are achieved. According to the analysis results, we can draw the following conclusions: the competitiveness of intermediate software has a positive impact on the innovation of software products. The competitiveness of intermediate software doesn't have a positive impact on the reliability of software products. Product innovation has a positive impact on enterprise results. Product reliability also has a positive impact on enterprise results. By analyzing the conclusions, we can make certain suggestions and draw implications on the competitiveness of China's software industry.

• Journal of Sensor Science and Technology
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• v.28 no.4
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• pp.240-245
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• 2019

Phase interpolation is widely adopted in frequency synthesizers and clock-and-data recovery systems to produce an intermediate phase from two existing phases. The intermediate phase is typically generated by combining two input phases with different weights. Unfortunately, this results in non-uniform phase steps. Alternatively, the intermediate phase can be generated by successive approximation, where the interpolated phase at each approximation stage is obtained using the same weight for the two intermediate phases. As a proof of concept, this study presents a 2-GHz 8-bit successive approximation digital-to-phase converter that is designed using 65-nm CMOS technology. The converter receives an 8-phase clock signal as input, and the most significant bit (MSB) section selects four phases to create two sinusoidal waveforms using a harmonic rejection filter. The remaining least significant bit (LSB) section applies the successive approximation to generate the required intermediate phase. Monte-Carlo simulations show that the proposed converter exhibits 0.46-LSB integral nonlinearity and 0.31-LSB differential nonlinearity with a power consumption of 3.12 mW from a 1.2-V supply voltage.

• Journal of Korea Trade
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• v.25 no.8
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• pp.25-44
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• 2021

Purpose - This research aims to provide empirical evidence that highlights the importance of imported intermediate goods in long-term economic growth. To this end, this paper develops an index that measures the productivity gains associated with a country's intermediate goods imports using highly disaggregated trade data. Design/methodology - The basic hypothesis is that countries sourcing higher-productivity (or higher-quality) inputs from developed economies derive a larger benefit from foreign R&D. To explore this hypothesis, standard cross-country growth regressions are performed using the highly disaggregated data from the United Nations (UN) Commodity Trade Statistics Database (COMTRADE). To address the endogeneity issue, I apply an instrumental variable (IV) approach. Findings - The results of this study demonstrate that the index predicts subsequent economic growth in middle- and low-income countries. This finding is consistent with previous studies that have argued that developing countries can achieve substantial productivity gains by importing intermediate inputs from developed countries. By contrast, there is no evidence of a significant association between the index and economic growth in high-income countries. Originality/value - This paper contributes to our understanding of the causal relationship between international trade and economic growth. From an economic policy perspective, the results suggest that developing countries with limited technology endowment can boost growth from input-tariff liberalization.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.4
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• pp.1-9
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• 1998

This paper developments asecurity system for transmission data in the internetwork. Intermediate system of our model does not fulfill security service of confidentiality but authentication and integrity. Thus this model knows whether the transmission data on the intermediate system is authentic and integral or not, and it is practical and easy to be developmented. This system is developmented using a ONP of USL which prvides environments of the open system.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1311-1327
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• 2016

We propose a multi-state model for analyzing semi-competing risks data with interval-censored or missing intermediate events. This model is an extension of the 'illness-death model', which composes three states, such as 'healthy', 'diseased', and 'dead'. The state of 'diseased' can be considered as an intermediate event. Two more states are added into the illness-death model to describe missing events caused by a loss of follow-up before the end of the study. One of them is a state of 'LTF', representing a lost-to-follow-up, and the other is an unobservable state that represents the intermediate event experienced after LTF occurred. Given covariates, we employ the Cox proportional hazards model with a normal frailty and construct a full likelihood to estimate transition intensities between states in the multi-state model. Marginalization of the full likelihood is completed using the adaptive Gaussian quadrature, and the optimal solution of the regression parameters is achieved through the iterative Newton-Raphson algorithm. Simulation studies are carried out to investigate the finite-sample performance of the proposed estimation procedure in terms of the empirical coverage probability of the true regression parameter. Our proposed method is also illustrated with the dataset adapted from Helmer et al. (2001).