• Knowledge Management Research
• /
• v.15 no.4
• /
• pp.35-56
• /
• 2014

This study examined the effect of perceived risk, an under-explored area in the knowledge sharing literature. We proposed that employee perceptions of risk relate positively with their knowledge sharing behaviors (donating and collecting), and examined the mediating role of impression management strategies in the hypothesized relationships. We also explored the moderating effect of leader-member exchange (LMX) in the relationship between perceived risk and impression management strategies. Valid and reliable self-report and supervisory evaluation measures were collected from a sample of 251 railroad employees in safety-sensitive positions. The results indicate that perceived risk was not significantly associated with knowledge sharing, but rather the risk perception impacts were indirect through impression management strategies such as exemplification and supplication. The study also found that LMX has no moderating effect on the perceived risk and impression management strategies. In discussing these results, we present significant insights in terms of subjective risk judgment as a potential mechanism which can encourage organizational politics.

• Journal of the Korean Society of Safety
• /
• v.23 no.2
• /
• pp.57-64
• /
• 2008

The Semiconductor industry in Korea has achieved a great contribution to the growth of its economy for the last 20 years with its product export ranked to #1 nowadays. However, the working environment in semiconductor industry is always exposed to a potential risk of critical safety issue for workers with many kinds of utilities used such as toxic chemicals, gases, high vacuum and high voltages of electricity. This study is focused on empirical research to find out the factors on safety climate and to examine the relationships of safety climate and safe work behaviour in the work site of Korea semiconductor industry. As a result of simulation, a strong positive relationships and safe work behaviour have been identified in this study. Its result and implications has been discussed and suggested further studies on its limitation from this study.

• Journal of Institute of Control, Robotics and Systems
• /
• v.15 no.10
• /
• pp.967-973
• /
• 2009

The model matching problem of asynchronous sequential machines is to design a corrective controller such that the stable-state behavior of the closed-loop system matches that of a prescribed model. In this paper, we address model matching when the external input set consists of controllable inputs and uncontrollable ones. Like in the frame of supervisory control of Discrete-Event Systems (DES), uncontrollable inputs cannot be disabled and must be transmitted to the plant without any change. We postulate necessary and sufficient conditions for the existence of a corrective controller that solves model matching despite the influence of uncontrollable events. Whenever a controller exists, the algorithm for its design is outlined. To illustrate the physical meaning of the proposed problem, the closed-loop system of an asynchronous machine with the proposed control scheme is implemented in VHDL code.

• Sleep Medicine and Psychophysiology
• /
• v.6 no.1
• /
• pp.26-31
• /
• 1999

"Attention" is not defined sufficiently. This term incorporates several dimensions or complex information processes such as alertness, spatial distribution, focused attention, sustained attention, divided attention and supervisory attentional control. In practice, however, various aspects of attention cannot be assessed separately with a single test. Moreover, a particular test is never assessing attention only, because the several intervening variables may influence the attentional component. Therefore, one can only assess a certain aspect of human behavior with special interest for its attentional component. This paper attempted to clarify various concepts of attention, reviewed signal detection theories with receiver operating characteristic(ROC) curves, and listed practical methods for assessment of attention.

• Journal of Korean Institute of Industrial Engineers
• /
• v.36 no.3
• /
• pp.203-211
• /
• 2010

This study examines a cointegrated vector autoregressive (VAR) model where parameters are subject to switch across the regimes in the term structure of interest rates. To employ the regime switching framework, the Markov-switching vector error correction model (MS-VECM) is allowed to the regime shifts in the vector of intercept terms, the variance-covariance terms, the error correction terms, and the autoregressive coefficient parts. The corresponding approaches are illustrated using the term structure of interest rates in the US Treasury bonds over the period of 1958 to 2009. Throughout the modeling procedure, we find that the MS-VECM can form a statistically adequate representation of the term structure of interest rate in the US Treasury bonds. Moreover, the regime switching effects are analyzed in connection with the historical government monetary policy and with the recent global financial crisis. Finally, the results from the comparisons both in information criteria and in forecasting exercises with and without the regime switching lead us to conclude that the models in the presence of regime dependence are superior to the linear VECM model.

• Nuclear Engineering and Technology
• /
• v.49 no.3
• /
• pp.484-494
• /
• 2017

In industrial plants such as nuclear power plants, system operations are performed by embedded controllers orchestrated by Supervisory Control and Data Acquisition (SCADA) software. A targeted attack (also termed a control aware attack) on the controller/SCADA software can lead a control system to operate in an unsafe mode or sometimes to complete shutdown of the plant. Such malware attacks can result in tremendous cost to the organization for recovery, cleanup, and maintenance activity. SCADA systems in operational mode generate huge log files. These files are useful in analysis of the plant behavior and diagnostics during an ongoing attack. However, they are bulky and difficult for manual inspection. Data mining techniques such as least squares approximation and computational methods can be used in the analysis of logs and to take proactive actions when required. This paper explores methodologies and algorithms so as to develop an effective monitoring scheme against control aware cyber attacks. It also explains soft computation techniques such as the computational geometric method and least squares approximation that can be effective in monitor design. This paper provides insights into diagnostic monitoring of its effectiveness by attack simulations on a four-tank model and using computation techniques to diagnose it. Cyber security of instrumentation and control systems used in nuclear power plants is of paramount importance and hence could be a possible target of such applications.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.22 no.5
• /
• pp.603-609
• /
• 2012

Wind energy is currently the fastest growing source of renewable energy used for electrical generation around world. Wind farms are adding a significant amount of electrical generation capacity. The increase in the number of wind farms has led to the need for more effective operation and maintenance procedures. Condition Monitoring System(CMS) can be used to aid plant owners in achieving these goals. Its aim is to provide operators with information regarding the health of their machines, which in turn, can help them improve operational efficiency. In this work, systematic design procedure for artificial neural network based normal behavior model which can be applied for fault detection of various devices is proposed. Furthermore, to verify the design method SCADA(Supervisor Control and Data Acquisition) data from 850KW wind turbine system installed in Beaung port were utilized.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.15 no.2
• /
• pp.1-18
• /
• 2020

This study is to identify the influence of major variables that affect the participation intention of securities type crowdfunding investors and how participation intention and perceived behavioral control affect investors' herd behavior including indirect effect analysis based on the theory of planned behavior. The ultimate purpose of this study is to understand the investment behavior of securities type crowdfunding investors and to help the relevant parties to develop various policies and business plans to revitalize the system and protect investors. An online survey was conducted on people who are interested or have experience in securities type crowdfunding to receive a total of 276 responses. Excluding outliers, a total of 261 responses were taken into account for the final analysis. For the data analysis, structural equation model analysis using SPSS 22.0 and Amos 22.0 statistical package was conducted. As a result, two of the major variables of the theory of planned behavior-attitude and subjective norm-have been found to have a positive effect on the participation intention of securities type crowdfunding investors. And after analyzing the indirect effect, the participation intention was found to play a mediating role between attitude, subjective norm and herd behavior. However, the perceived behavioral control presented as a major variable of behavioral intention in the theory of planned behavior showed that the effect on participation intention was statistically insignificant. Instead, it was found to have a direct positive effect on herd behavior. This is significant because it empirically confirmed that even if investors perceive securities type crowdfunding as easy to participate, perceived behavioral control does not seem to have a significant impact on participation intention because securities type crowdfunding is an investment in an early-stage business with a high risk of loss. On the other hand, the study has great significance in that it empirically confirmed that domestic securities type crowdfunding investors perceive the funding progress information provided by the platform as a signal and imitate many other investors, showing herd behavior when they actually make an investment. It is expected that this study will provide meaningful insights for the policy making of crowdfunding supervisory offices and platform operators by empirically identifying major variables that influence the participation intentions and herd behavior of domestic securities type crowdfunding investors.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.18 no.4
• /
• pp.97-110
• /
• 2022

The purpose of this study is to analyze the level of public data convergence capabilities of administrative organizations and to explore important variables in data-based organizational capabilities. The theoretical background was summarized on public data and use activation, joint use, convergence, administrative organization, and convergence constraints. These contents were explained Public Data Act, the Electronic Government Act, and the Data-Based Administrative Act. The research model was set as the data-based organizational capabilities effect by a data-based administrative capability, public data operation capabilities, and public data operation constraints. It was also set whether there is a capabilities difference data-based on an organizational operation by the level of data convergence capabilities. This study analysis was conducted with hierarchical cluster analysis and multiple regression analysis. As the research result, First, hierarchical cluster analysis was classified into three groups. It was classified into a group that uses only public data and structured data, a group that uses public data on both structured and unstructured data, and a group that uses both public and private data. Second, the critical variables of data-based organizational operation capabilities were found in the data-based administrative planning and administrative technology, the supervisory organizations and technical systems by public data convergence, and the data sharing and market transaction constraints. Finally, the essential independent variables on data-based organizational competencies differ by group. This study contributed. As a theoretical implication, this research is updated on management information systems by explaining the Public Data Act, the Electronic Government Act, and the Data-Based Administrative Act. As a practical implication, the activity reinforcement of public data should be promoting the establishment of data standardization and search convenience and elimination of the lukewarm attitudes and Selfishness behavior for data sharing.

• Asian-Australasian Journal of Animal Sciences
• /
• v.21 no.6
• /
• pp.861-867
• /
• 2008

The objective of this study was to evaluate the effect of exogenous ghrelin on the behaviors, weight gain, and feed intakes of weanling piglets. A total of 25 pairs of Duroc$\times$Landrace$\times$Large White piglets weaned at 21 days of age were used in this experiment which finished on day 36. Each pair of healthy piglets from the same litter with similar body weight and of the same gender were selected and randomly arranged to ghrelin or control groups. Thus, there were 50 piglets (ghrelin 25; control 25) kept in 10 pens (ghrelin 5; control 5) and 5 piglets per pen. Initial body weight of the pigs did not differ between the control and ghrelin treatment ($7.43{\pm}0.17kg$; p = 0.81). Experimental pigs were infused with ghrelin ($1{\mu}g/d$ pig) via the marginal ear vein between 0750 and 0800 h at 22, 23, 24 days of age. Control pigs were infused with 0.9% saline. Feed consumption was measured on days 23, 24, 25, 29 and 36. Body weight was measured on days 22, 23, 24, 25, 29 and 36. Behavior data of individual piglets were collected by real-time observation from 0800-1500 h through remote supervisory equipment at 22, 23 and 24 days of age. The results indicated that ghrelin infusion could increase drinking (p<0.05) and lying behaviors (p<0.01) and decrease mounting behaviors (p<0.05). No significant influence of ghrelin was found on average daily weight gain (ADG) and average daily feed intake (ADFI) in this experiment (p>0.05). In conclusion, exogenous ghrelin by the method above and at the dosage of $1{\mu}g/d$ pig could cause a variety of behavioral effects, but not improve performance of weanling piglets.