• Nuclear Engineering and Technology
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• v.41 no.3
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• pp.247-270
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• 2009

This paper reviews studies on information searching behavior in process control systems and discusses some implications learned from previous studies for use in human factors studies on nuclear power plants (NPPs) main control rooms (MCRs). Information searching behavior in NPPs depends on expectancy, value, salience, and effort. The first quantitative scanning model developed by Senders for instrument panel monitoring considered bandwidth (change rate) of instruments as a determining factor in scanning behavior. Senders' model was subsequently elaborated by other researchers to account for value in addition to bandwidth. There is also another type of model based on the operator's situation awareness (SA) which has been developed for NPP application. In these SA-based models, situation-event relations or rules on system dynamics are considered the most significant factor forming expectancy. From the review of previous studies it is recommended that, for NPP application, (1) a set of symptomatic information sources including both changed and unchanged symptoms should be considered along with bandwidth as determining factors governing information searching (or visual sampling) behavior; (2) both data-driven monitoring and knowledge-driven monitoring should be considered and balanced in a systematic way; (3) sound models describing mechanisms of cognitive activities during information searching tasks should be developed so as to bridge studies on information searching behavior and design improvement in HMI; (4) the attention-situation awareness (A-SA) modeling approach should be recognized as a promising approach to be examined further; and (5) information displays should be expected to have totally different characteristics in advanced control rooms. Hence much attention should be devoted to information searching behavior including human-machine interface (HMI) design and human cognitive processes.

• Journal of the Economic Geographical Society of Korea
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• v.15 no.2
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• pp.192-205
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• 2012

This study estimates how much climate variables affect the land price and acreage of rice paddy and dry farm field in agriculture with the case of Gangwon-do in Korea. To this end, we capitalize upon the Ricardian approach based upon the panel data on climate, soil and geography, farmland prices and acreage, other economic and social variables for 11 municipal units comprising Gangwon-do during the period of 1992-2010. Our empirical analysis shows that the temperature variable has negative economic impacts on the price and acreage of rice paddy and dry farm field, confirming that the temperature variable is much significant than that of precipitation in global warming. On the other hand, the other determinants of farmland price and acreage are different with the type of farmland in Gangwon-do.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.3
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• pp.98-105
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• 2021

The sensory stimulation of a cosmetic product has been deemed to be an ancillary aspect until a decade ago. That point of view has drastically changed on different levels in just a decade. Nowadays cosmetic formulators should unavoidably meet the needs of consumers who want sensory satisfaction, although they do not have much time for new product development. The selection of new products from candidate products largely depend on the panel of human sensory experts. As new product development cycle time decreases, the formulators wanted to find systematic tools that are required to filter candidate products into a short list. Traditional statistical analysis on most physical property tests for the products including tribology tests and rheology tests, do not give any sound foundation for filtering candidate products. In this paper, we suggest a deep learning-based analysis method to identify hand cream products by raw electric signals from tribological sliding test. We compare the result of the deep learning-based method using raw data as input with the results of several machine learning-based analysis methods using manually extracted features as input. Among them, ResNet that is a deep learning model proved to be the best method to identify hand cream used in the test. According to our search in the scientific reported papers, this is the first attempt for predicting test cosmetic product with only raw time-series friction data without any manual feature extraction. Automatic product identification capability without manually extracted features can be used to narrow down the list of the newly developed candidate products.

• Asia-Pacific Journal of Business
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• v.12 no.3
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• pp.175-192
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• 2021

Purpose - In this study, we investigate the effects of government environmental subsidies and the globalization Chinese firms on their profitability using return on assets (ROA). Design/methodology/approach - In this study, a merged data including accounting, financial market, subsidization of the Chinese governments, local and the central, and export activities of 19,563 year-firms, for those listed on Shanghai Stock and Shenzhen Stock Exchange for 11 years from 2008 to 2018 is used. We collect subsidy data from RESSET database and financial data from CSMAR database. Then, we empirically test the test hypotheses using fixed effects models (FEM) separately and in a simultaneous equation model (SEM). Findings - Firstly, the globalization of Chinese firms has a negative impact on their profitability for some years after the year. Secondly, environmental subsidies just like other subsidies have ameliorating effects on financial performance for global firms. Such effects have lasted some years. Thirdly, environmental investments have a mostly negative impact on short- and long-term profitability for global firms. Lastly, the government's environmental subsidies in China have a positive effect on their profitability for both global and domestic firms. Research implications or Originality - We can infer that environmental investments with the help of the governmental subsidies can help Chinese firms deploy global strategies to expand markets to surpass competitors in the long run despite worsening profitability in global markets in the short run.

• Asia-Pacific Journal of Business
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• v.15 no.3
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• pp.17-45
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• 2024

Purpose - This paper studies the impact of digital transformation on corporate performance based on the stakeholder and dynamic capability theories. Digital transformation is divided into digital technologies (big data, artificial intelligence, blockchain, and cloud computing) and digital technology practical applications. Corporate performance includes financial performance and non-financial performance. The mechanism of dynamic capabilities (innovation capability, absorptive capacity, and adaptive capacity) is further explored. Design/methodology/approach - A fixed-effects model is used to construct a panel data of China's Shanghai and Shenzhen A-share listed companies from 2011 to 2023, and Stata is used for empirical analysis. Findings - In general, digital transformation directly improves corporate performance and indirectly promotes corporate performance through dynamic capabilities (innovation, absorptive capacity, and adaptive capacity). After robustness and endogeneity tests, the conclusion still support. In terms of subdivision, the two dimensions of digital transformation and the practical application of digital technology have different effects on corporate financial performance and non-financial performance. Research implications or Originality - Theoretically, the mechanism of digital transformation on corporate performance is fully and deeply explored, filling the research gap whiting this study. Additionally, the model is constructed using the innovation, absorption and adaptability of dynamic capabilities, providing a different perspective. Practically, it helps to alleviate the current situation of some companies "not wanting to transform" or "not daring to transform", and also clarifies how digital transformation can help companies use dynamic capabilities to improve performance. It provides a decision-making basis for government departments to promote the integration of digital economy and real economy, so that digital transformation can better empower and release corporate performance, thereby promoting the development of China's economy.

• International Journal of Automotive Technology
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• v.4 no.2
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• pp.77-86
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• 2003

How to compare the environmental damage caused by vehicles with different foe]s and drive trains\ulcorner This paper describes a methodology to assess the environmental impact of vehicles, using different approaches, and evaluating their benefits and limitations. Rating systems are analysed as tools to compare the environmental impact of vehicles, allowing decision makers to dedicate their financial and non-financial policies and support measures in function of the ecological damage. The paper is based on the "Clean Vehicles" research project, commissioned by the Brussels Capital Region via the BIM-IBGE (Brussels Institute for the Conservation of the Environment) (Van Mierlo et at., 2001). The VriJe Universiteit Brussel (ETEC) and the universite Libre do Bruxelles (CEESE) have jointly carried out the workprogramme. The most important results of this project are illustrated in this paper. First an overview of environmental, economical and technical characteristics of the different alternative fuels and drive trains is given. Afterward the basic principles to identify the environmental impact of cars are described. An outline of the considered emissions and their environmental impact leads to the definition of the calculation method, named Ecoscore. A rather simple and pragmatic approach would be stating that all alternative fuelled vehicles (LPG, CNG, EV, HEV, etc.) can be considered as ′clean′. Another basic approach is considering as ′clean′ all vehicles satisfying a stringent omission regulation like EURO IV or EEV. Such approaches however don′t tell anything about the real environmental damage of the vehicles. In the paper we describe "how should the environmental impact of vehicles be defined\ulcorner", including parameters affecting the emissions of vehicles and their influence on human beings and on the environment and "how could it be defined \ulcorner", taking into account the availability of accurate and reliable data. We take into account different damages (acid rain, photochemical air pollution, global warming. noise, etc.) and their impacts on several receptors like human beings (e.g., cancer, respiratory diseases, etc), ecosystems, or buildings. The presented methodology is based on a kind of Life Cycle Assessment (LCA) in which the contribution of all emissions to a certain damage are considered (e.g. using Exposure-Response damage function). The emissions will include oil extraction, transportation refinery, electricity production, distribution, (Well-to-Wheel approach), as well as the emission due to the production, use and dismantling of the vehicle (Cradle-to-Grave approach). The different damages will be normalized to be able to make a comparison. Hence a reference value (determined by the reference vehicle chosen) will be defined as a target value (the normalized value will thus measure a kind of Distance to Target). The contribution of the different normalized damages to a single value "Ecoscore" will be based on a panel weighting method. Some examples of the calculation of the Ecoscore for different alternative fuels and drive trains will be calculated as an illustration of the methodology.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.6
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• pp.2038-2045
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• 2010

Households' monthly average income is composed of various factors. This study paper studies focuses on estimating the determinants of a households' monthly average income. The region for analysis consist of three groups, that is, the whole country, a metropolitan city(such as Busan, Daegu, Incheon, Gwangiu, Daejeon, Ulsan.) and Seoul. Analyzing period be formed over a 57 time points(2005. 01~2009. 09). In this paper the dependent variable setting up the households' monthly average income, explanatory (independent) variables are composed of the consumer price index, employment to population ratio, Index of housing sale price, the preceding composite index, loans of housing mortgage, spending rate for care medical expense and the composite stock price index. In looking at the factors which determine the monthly average income, evidence was produced supporting the hypothesis that there is a significant positive relationship between the composite index and housing loans. The study also produced evidence supporting the view that there is a significant negative relationship between employment ratios, the house sale pricing index and spending rates for care or medical needs. The study found that the consumer price index and composite stock price index were not significant variables. The implications of these findings are discussed for further research.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.1
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• pp.272-277
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• 2010

In respect complication of group, rate of arrearage in domestic bank is composed of various factors. This paper studies focus on estimating the determinants of the rate of arrearage in domestic bank using panel data model. The volume of analysis consist of 3 groups(loaned patterns of enterprise, housekeeping, credit card). Analyzing period be formed over a 54 point(2005. 1~ 2009. 06). In this paper dependent variable setting up rate of arrearage in domestic bank, explanatory(independent) variables composed of the consumer price index, composite stock price index, rate of exchange, the coincident composite index, national housing bonds and employment rate. The result of estimating the rate of arrearage in domestic bank provides empirical evidences of significance positive relationships between the consumer price index However this study provides empirical evidences of significance negative relationships between the coincident composite index and the composite stock price index. The explanatory variables, that is, rate of exchange, national housing bonds and the employment rate are non-significance variables of negative factor. Implication of these findings are discussed for content research and practices.

• Journal of Digital Convergence
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• v.14 no.4
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• pp.11-17
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• 2016

This study is to examine the effect that the degree of alcohol use and the factor of family relationship have on alcohol related problem with elderly people over 65 years old. The study utilized the data from Korea Welfare Panel Study in 2014 published in 2015, which is annually conducted nationwide study. AUDIT (Alcohol Use Disorder Identification Test) of the World Health Organization scale to assess the drinking problem in the study was used. The collected data were analyzed using SPSS 21.0. Presenting some discussions on the basis of the results of this study is as follows. First, looking at a cross-analysis of gender differences in drinking problems, elderly men and elderly women showed different degrees of alcohol problems. Second, looking at demographic characteristics that influence whether a drinking problem, younger age showed a serious drinking problem. Third, looking at the effect that depression and family relationship have on alcohol problem, depression appeared to have relatively more serious effect than the family relationship. According to the above finding, physical and mental health for healthy aging are important factors of the quality of life so a preventive approach to maintain healthy habits is considered to be essential.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.5
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• pp.879-886
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• 2008

This paper addresses the analysis and the design optimization of differential interconnects for Low-Voltage Differential Signaling (LVDS) applications. Thanks to the differential transmission and the low voltage swing, LVDS offers high data rates and improved noise immunity with significantly reduced power consumption in data communications, high-resolution display, and flat panel display. We present an improved model and new equations to reduce impedance mismatch and signal degradation in cascaded interconnects using optimization of interconnect design parameters such as trace width, trace height and trace space in differential flexible printed circuit board (FPCB) transmission lines. We have carried out frequency-domain full-wave electromagnetic simulations, time-domain transient simulations, and S-parameter simulations to evaluate the high-frequency characteristics of the differential FPCB interconnects. The 10% change in trace width produced change of approximately 6% and 5.6% in differential impedance for trace thickness of $17.5{\mu}m$ and $35{\mu}m$, respectively. The change in the trace space showed a little change. We believe that the proposed approach is very helpful to optimize high-speed differential FPCB interconnects for LVDS applications.