• ETRI Journal
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• v.42 no.4
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• pp.585-595
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• 2020

Integration of multiple communication technologies in a smart grid (SG) enables employing cognitive radio (CR) technology for improving reliability and security with low latency by adaptively and effectively allocating spectral resources. The versatile features of the CR enable the smart meter to select either the unlicensed or the licensed band for transmitting data to the utility company, thus reducing communication outage. Demand response management is regarded as the control unit of the SG that balances the load by regulating the real-time price that benefits both the utility company and consumers. In this study, joint allocation of the transmission power to the smart meter and consumer's demand is formulated as a two stage multi-armed bandit game in which the players select their optimal strategies noncooperatively without having any prior information about the media. Furthermore, based on historical rewards of the player, a real-time pricing adaptation method is proposed. The latter is validated through numerical results.

• ETRI Journal
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• v.39 no.4
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• pp.558-569
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• 2017

In this study, a non-preemptive M/G/1 queueing model of a spectrum handoff scheme for cognitive wireless networks is proposed. Because spectrum handoff gives secondary users an opportunity to carry on their transmissions, it is crucially important to determine the actions of primary users. In our queueing model, prioritized data traffic is utilized to meet the requirements of the secondary users. These users' packets are categorized into three different priority classes: urgent, real-time, and non-real time. Urgent data packets have the highest priority, while non-real time data packets have the lowest priority. Riverbed (OPNET) Modeler simulation software was used to simulate both reactive and proactive decision spectrum handoff schemes. The simulation results were consistent with the analytical results obtained under different load and traffic conditions. This study also revealed that the cumulative number of handoffs can be drastically decreased by exploiting priority classes and utilizing a decent spectrum handoff strategy, such as a reactive or proactive decision-based strategy.

• Proceedings of the Korean Society for Cognitive Science Conference
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• 2000.05a
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• pp.93-98
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• 2000

본 연구에서는 멀티미디어 환경에서 인지부하 정도에 따라 학습 수행에 어떤 차이를 보이는지를 알아보고자 하였다. 본 연구에서는 멀티미디어 환경 학습을 함에 있어서 학습 제시 유형이 학습 수행에 영향을 미칠 것으로 보아, 같은 내용을 텍스트로 제시하는 조건, 텍스트와 나레이션으로 제시하는 조건, 애니메이션과 텍스트로 제시하는 조건에서 학습하도록 한 후 학습 수행 정도를 비교하였다. 학습 수행 정도는 학습이 끝난 후 즉시 시행하는 검사와 일 주일 후에 실시한 지연검사로 평가되었다. 그 결과 텍스트로만 제시한 조건의 학습자들이 다른 조건에 비해 즉시 검사와 지연검사 모두 더 높은 수행을 보인 것으로 나타났다. 이 결과는 멀티미디어 환경에서 인지부하를 주는 자극 제시 유형은 학습에 방해를 준다는 것을 보여주며, 이는 멀티미디어로 학습정보를 제시하는 것이 어떠한 경우에서나 늘 좋은 것이 아니라, 학습자 상황과 학습 내용을 충분히 고려해야 하는 것을 시사한다.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2008.10b
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• pp.634-642
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• 2008

Radio wave is the valuable resources in $21^{st}$ century. It will be widely used in various applications such as DMB, USN, telematics, and home network as well as mobile and wireless communications. Cognitive Radio technology is devised to maximize the utilization of radio resources by sensing near-by spectrum and dynamic and allocating free resources dynamically and adaptively. Wireless links for the secondary user need to be frequently switched to idle frequencies during the transmission of multimedia data in the cognitive radio based system. This may cause delay and information loss, and QoS degradations occur inevitably. The efficient frequency allocation scheme is necessary to support the seamless multimedia service to the secondary user while maintaining QoS of the primary user. This paper suggests a frequency selection scheme which considers other parameters such as cell load, data rate, and available bandwidth than just received signal strength during the frequency selection process. The performance of our proposed scheme is analyzed by simulation.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.17 no.30
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• pp.25-34
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• 1994

Mental workload has a improtant place in modern work environment such as human-computer interaction. Designing man-machine system requires knowledge and evaluation of the human cognitive process which controls information flow during our works. Many studies estimate reaction time as a index of menatal workload. This paper investigates what reflacts the workload of human information handling when the informations grow its degree. Experiment result introuce the memory time that explain the information-load more sensitive than react time. And react time shows learning effect but memory time does'nt show that effect So it can be concluded that cognitive learning or work schema needs more time to achieve dexterity than motor skill.

• The Journal of Korea Robotics Society
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• v.13 no.2
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• pp.113-120
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• 2018

To fly a drone or unmanned aerial vechicle(UAV) safely, its pilot needs to maintain high situation awareness of its flight space. One of the important ways to improve the flight space awareness is to integrate both the global and the local navigation map a drone provides. However, the drone pilot often has to use the inconsistent reference frames or perspectives between the two maps. In specific, the global navigation map tends to display space information in the third-person perspective, whereas the local map tends to use the first-person perspective through the drone camera. This inconsistent perspective problem makes the pilot use mental rotation to align the different perspectives. In addition, integrating different dimensionalities (2D vs. 3D) of the two maps may aggravate the pilot's cognitive load of mental rotation. Therefore, this study aims to investigate the relation between perspective difference ($0^{\circ}$, $90^{\circ}$, $180^{\circ}$, $270^{\circ}$) and the map dimensionality matches (3D-3D vs. 3D-2D) to improve the way of integrating the two maps. The results show that the pilot's flight space awareness improves when the perspective differences are smaller and also when the dimensionalities between the two maps are matched.

• Journal of Biomedical Engineering Research
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• v.28 no.1
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• pp.55-65
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• 2007

This paper sought to investigate pupil size variability, pupil size parameters in terms of time domain and frequency domain, the autonomic activity change induced by posture change, degree of sleepiness and cognitive task (math task). With a specially designed pupil image acquisition system in the dark room, these three kinds of experiments were performed to induce a dominant state of sympathetic or parasympathetic activation. Electrocardiogram and pupil size were measured in all the experiments. Based on three experiments, we calculated heart rate variability. In the pupil size analysis, we calculated the mean and standard deviation of pupil size (in time domain), and proposed several frequency bands that exhibit different autonomic activation between different sessions. The results indicate that in terms of heart rate variability, posture change exhibited significant differences but not between sleepiness level, or between cognitive task. Pupil sizes differed only during the postures. And we found some frequency bands that correlated with autonomic activation in each experiment. While heart rate variability reflects posture change that need cardiac control, pupil size variability reflects not only posture induced autonomic activation but sleepiness and cognitive load, which is processed in the brain, in time and frequency domain parameter.

• Journal of Information Technology Services
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• v.14 no.1
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• pp.129-143
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• 2015

This study has two goals. The first goal is to investigate whether worked examples are effective in the ill-defined domain with on-line learning and the second goal is to find out which components (conceptual or procedural knowledge) of worked examples are effective factor at the given learning environment. We carried out three experiments in which Korean undergraduate or graduate students were working in three or four conditions of worked examples (CWE, PWE, CPWE, or the control group). While experiment 1 conducted in on-line learning environment did not find any effect and difference among groups and also any logical reason for those results, experiment 2 conducted in completely controlled laboratory setting with less knowledgeable students showed the clear difference among groups by the order CPWE, PWE, and CWE. Experiment 3 in which highly knowledgeable and motivated students were presented the same materials in more controlled on-line learning environment indicated the difference among groups by the order CWE, CPWE, and PWE. The results were discussed within the framework of cognitive load theory.

• Journal of Korean Library and Information Science Society
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• v.48 no.3
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• pp.281-302
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• 2017

This study examined the differences in a searcher's mental states of a complex information search and retrieval task during information search process between the two groups: participants who were exposed to mental demand manipulation and those not exposed. Data from the experiments and questionnaires were analyzed. Based on qualitative approach and quantitative analyses, the results indicated that the participants exposed to mental demand required more thoughts; addressed negative emotions more often; reduced a searcher's efforts; and interrupted search performance than those not exposed. These results suggest that mental demand contributed to a searcher's perceived thought, emotion, effort, and performance, although these mental states differed in relative contribution of information search process. Significant differences were found between the two groups with respect to the component of mental demand, performance, and frustration of the NASA-TLX subjective cognitive load. These results have implications for search user interface design and information search systems among others.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.7
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• pp.805-812
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• 2005

Smart home is one of the ubiquitous environment platforms with various complex sensor-and-control network. In this paper, a now learning methodology for learning user's behavior preference pattern is proposed in the sense of reductive user's cognitive load to access complex interfaces and providing personalized services. We propose a fuzzy inductive learning methodology based on life-long learning paradigm for knowledge discovery, which tries to construct efficient fuzzy partition for each input space and to extract fuzzy association rules from the numerical data pattern.