• Journal of Korea Multimedia Society
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• v.7 no.6
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• pp.832-840
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• 2004

In ubiquitous environments, context is any information that can be used to characterize the situation of an entity such as a person or an object. Many sensors and small computers collect contexts and provide applications with them. Thus, ubiquitous applications need to represent contexts and exploit them effectively. In this paper, we design and implement a context-aware messaging system, called UMS (Ubiquitous Messaging System), based on Java and Jini. UMS can represent various contexts using XML scripts, and communicate text messages regardless of user's location using the proxy mechanism of Jini.

• Science of Emotion and Sensibility
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• v.12 no.1
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• pp.55-64
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• 2009

Previous research has mainly investigated the characteristics of expertise by using typical and routine tasks. This research to overcome these limitations included non-routine task situations and observed expert and novice pilots' situation awareness (SA) performance in routine and non-routine situations. Additionally, whether the ability to aware or perceive the environmental information in limited time varies with the level of expertise was tested. To this end, $2^*2^*2$ mixed factorial design was employed, including expertise (novice/expert) as a between-subjects variable and normality of fight situation (routine/non-routine) and stimulus display time (long/short) as within-subjects variables. As results, there was no performance difference in routine situations between experts and novices, while experts significantly outperformed novices in non-routine situations. When the display time became shorter, overall SA accuracy was decreased for both experts and novices, whereas experts' performance remained significantly higher than novices in short and long conditions. When we examined the interaction between the normality of fight situation and stimulus display time, there was no difference between experts and novices in routine situations for both short and long conditions. In non-routine situations, however, experts' SA accuracy was significantly higher than novices both in short and long conditions. Overall, non-routineness of flight situation does not have any impact on SA performance of experts, while it has a critical impact on SA performance of novices.

• The Journal of Society for e-Business Studies
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• v.18 no.3
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• pp.17-43
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• 2013

This research is to assess the relationship Big Data attributes and disaster response process. The hypothesis are designed to form decision making between situation awareness and disaster response by defining major attribute of Big Data(Volume, Variety, Velocity, Complexity). It is proved whether there is a moderating effect in cause-and-effect relationship by visualizing Big Data. To test the hypotheses, it was conducted a questionnaire survey of civil servants in charge of disaster-related government employees, and collected 320 data(without 12 undependable responses). The research findings are suggested the attributes of accumulation, expandability, flexibility, real-time, analytical, combination of Big Data have a strong effect on disaster manager's situation awareness.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.12
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• pp.2352-2360
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• 2011

In this paper, we introduce a comprehensive design methodology of Radial Basis Function Neural Networks (RBFNN) that is based on mechanism of clustering and optimization algorithm. We can divide some clusters based on similarity of input dataset by using clustering algorithm. As a result, the number of clusters is equal to the number of nodes in the hidden layer. Moreover, the centers of each cluster are used into the centers of each receptive field in the hidden layer. In this study, we have applied Fuzzy-C Means(FCM) and K-Means(KM) clustering algorithm, respectively and compared between them. The weight connections of model are expanded into the type of polynomial functions such as linear and quadratic. In this reason, the output of model consists of relation between input and output. In order to get the optimal structure and better performance, Particle Swarm Optimization(PSO) is used. We can obtain optimized parameters such as both the number of clusters and the polynomial order of weights connection through structural optimization as well as the widths of receptive fields through parametric optimization. To evaluate the performance of proposed model, NXT equipment offered by National Instrument(NI) is exploited. The situation awareness system-related intelligent model was built up by the experimental dataset of distance information measured between object and diverse sensor such as sound sensor, light sensor, and ultrasonic sensor of NXT equipment.

• Science of Emotion and Sensibility
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• v.16 no.2
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• pp.235-248
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• 2013

In this study, the effects of driver's neuroticism on situation awareness(SA), eye movement(EM), and driving performance were examined. In Experiment 1, in which static driving scenes were presented, it was found that the drivers of higher neuroticism showed shorter percentage of dwell time and less percentage of fixation counts for the peripheral area than those of lower neuroticism, although SA scores yielded no difference between the two neuroticism groups. In Experiment 2, differences in the drivers' driving performances as well as SA and EM as a function of neuroticism were compared using driving simulation. The results of Experiment 2 showed the followings. First, contrasting to Experiment 1, the high neuroticism group showed lower SA score than low neuroticism group. Second, the pattern of EM was similar to those of Experiment 1. Third, high neuroticism group deviated more from center of road, and drove slower than low neuroticism group.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.3039-3056
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• 2020

Beaches have many risk factors that cause various accidents, such as drifting and drowning, these accidents have many risk factors. To analyze them, in this paper, we identify beach risk factors, and define the criteria and correlation for each risk factor. Then, we generate new risk factors based on Fuzzy theory, and define Situation Awareness for each time. Finally, we propose a beach risk assessment and prediction model based on linear regression using the calculated risk result and pre-defined risk factors. We use national public data of the Korea Meteorological Administration (KMA), and the Korea Hydrographic and Oceanographic Agency (KHOA). The results of the experiment showed the prediction accuracy of beach risk to be 0.90%, and the prediction accuracy of drifting and drowning accidents to be 0.89% and 0.86%, respectively. Also, through factor correlation analysis and risk factor assessment, the influence of each of the factors on beach risk can be confirmed. In conclusion, we confirmed that our proposed model can assess and predict beach risks.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.7
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• pp.907-912
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• 2007

The present level of ubiquitous computing technology have developed to the point where Home-server provides services that user require directly for user in the intelligent space. But it will need intelligent system to provides more active services for user in the near future. In this paper, we define the environment information about situation that user is in as Context, and collect the Context that stereotype as 4W1H form for construct the system that can decision service will be provide from information about a situation that user is in, without user's involvement. Additionally we collect information about user's emotional state, use these informations as nodes of Bayesian network for probabilistic reasoning. From that, we materialize Context Awareness system about it that what kind of situation user is in. And, we propose the Context-based Service reasoning model using Bayesian Network from the result of Context Awareness.

• Journal of Digital Contents Society
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• v.19 no.1
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• pp.113-122
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• 2018

In level 3 automated vehicles, drivers are expected to encounter transition of control when the system reaches its limit. Drivers need to refocus their attention on the road ahead and gain situational awareness. Appropriate information should be conveyed during this period in order to prevent human errors. In this paper, we defined the takeover process as 'in-the-middle-of-the-loop' and conducted Task Analysis and Work Domain Analysis to find out information requirements. As a result, we specified required information types and interface considerations. Moreover, we conducted an experimental study to find how the information types affect drivers on situation awareness, cognitive load and reaction time. Consequently, we found different information on system transparency should be conveyed depending on the urgency of takeover situation and driver guidance could help drivers with better situation awareness after the takeover.

• Nuclear Engineering and Technology
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• v.48 no.1
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• pp.153-163
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• 2016

Environments in nuclear power plants (NPPs) are changing as the design of instrumentation and control systems for NPPs is rapidly moving toward fully digital instrumentation and control, and modern computer techniques are gradually introduced into main control rooms (MCRs). Within the context of these environmental changes, the level of performance of operators in a digital MCR is a major concern. Situation awareness (SA), which is used within human factors research to explain to what extent operators of safety-critical systems know what is transpiring in the system and the environment, is considered a prerequisite factor to guarantee the safe operation of NPPs. However, the safe operation of NPPs can be guaranteed through a team effort. In this regard, the operating team's SA in a conventional and digital MCR should be measured in order to assess whether the new design features implemented in a digital MCR affect this parameter. This paper explains the team SA measurement method used in this study and the results of applying this measurement method to operating teams in different MCR environments. The paper also discusses several empirical lessons learned from the results.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.6
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• pp.807-816
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• 2018

Threat hunting is defined as a process of proactively and iteratively searching through networks to detect and isolate advanced threats that evade existing security solutions. The main concept of threat hunting is to find out weak points and remedy them before actual cyber threat has occurred. And HMM(Hunting Maturity Matrix) is suggested to evolve hunting processes with five levels, therefore, CSOC(Cyber Security Operations Center) can refer HMM how to make them safer from complicated and organized cyber attacks. We are developing a system for cyber situation awareness system with pro-active threat hunting process called unMazeTM. With this unMaze, it can be upgraded CSOC's HMM level from initial level to basic level. CSOC with unMaze do threat hunting process not only detecting existing cyber equipment post-actively, but also proactively detecting cyber threat by fusing and analyzing cyber asset data and threat intelligence.