• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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• pp.1301-1312
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• 2020

Using decode-and-forward relaying in the cognitive radio networks, the spectrum efficiency can improve furthermore. The optimization algorithm of the spectrum sensing estimation time is presented for the cognitive relay networks in this paper. The longer sensing time will bring two aspects of the consequences. On the one hand, the channel parameters are estimated more accurate so as to reduce the interferences to the authorized users and to improve the throughput of the cognitive users. On the other hand, it shortens the transmission time so as to decease the system throughput. In this time, it exists an optimal sensing time to maximize the throughput. The channel state information of the sub-bands is considered as the exponentially distributed, so a stochastic programming method is proposed to optimize the sensing time for the cognitive relay networks. The computer simulation results using the Matlab software show that the algorithm is effective, which has a certain engineering application value.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.3
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• pp.27-33
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• 2008

In this paper, we propose a cognitive beamforming scheme for coexistence of CR (Cognitive Radio) and IR (Incumbent Radio) systems. In order to maintain the priority of the IR in spectrum utilization the proposed cognitive beamforming scheme needs to have the CR not cause any interference to the IR systems occupying the same frequency band at the same time. In addition the proposed scheme has to provide maximum channel gain to the CRU (CR User) in a boundary of satisfying the former criterion. For this purpose, the proposed scheme does not cause any interference to the IRU (IR User), while the CRU is served without additional radio resource consumption. From simulation, we confirmed that when using the proposed scheme the CRU does not interfere with the IRU and there is little bit error rate performance degradation of the CRU as compared to that of the ideal beamforming system, which does not consider the IR priority.

• Journal of Korean Society for Quality Management
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• v.23 no.3
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• pp.69-83
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• 1995

In a large number of literature on of inspection tasks, one of the most consistent findings is the existence of large and consistent differences among inspectors. It is possible that the individual difference is described by the difference of cognitive skills, because cognitive skills are required more than manual skills in inspection tasks. Therefore, a set of cognitive factors in human information processing may underly human performance in inspection tasks. In this study, a cognitive skill was described as the relative importance of the cognitive factors involved. A hierarchical task analysis and a fuzzy hierarchical analysis were used to represent how the importance of cognitive factors contribute to inspection performance. An experiment was conducted using the computer simulations of PCB inspection tasks. The results revealed that the subject group with better performance showed the importance weights of cognitive factors in the following rank; (attention, perception, judgement, classification, recognition)<(detection)$\ll$(memory). The results of the experiment can serve as a selection criterion for efficient inspection performance and the information of skilled learning for an inspection training program. The usefullness of a hierarchical task analysis and a fuzzy hierarchical task analysis for the analysis of cognitive tasks are also confirmed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.3
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• pp.289-304
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• 2010

This paper proposes a novel scheme for cooperative spectrum sensing on distributed cognitive radio networks. A fuzzy logic rule - based inference system is proposed to estimate the presence possibility of the licensed user's signal based on the observed energy at each cognitive radio terminal. The estimated results are aggregated to make the final sensing decision at the fusion center. Simulation results show that significant improvement of the spectrum sensing accuracy is achieved by our schemes.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.1403-1404
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• 2010

• Journal of Biomedical Engineering Research
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• v.43 no.4
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• pp.185-192
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• 2022

Early detection of mild cognitive impairment can help prevent the progression of dementia. The purpose of this study was to design and validate a machine learning model that automatically differential diagnosed patients with mild cognitive impairment and identified cognitive decline characteristics compared to a control group with normal cognition using resting-state quantitative electroencephalogram (qEEG) with eyes closed. In the first step, a rectified signal was obtained through a preprocessing process that receives a quantitative EEG signal as an input and removes noise through a filter and independent component analysis (ICA). Frequency analysis and non-linear features were extracted from the rectified signal, and the 3067 extracted features were used as input of a linear support vector machine (SVM), a representative algorithm among machine learning algorithms, and classified into mild cognitive impairment patients and normal cognitive adults. As a result of classification analysis of 58 normal cognitive group and 80 patients in mild cognitive impairment, the accuracy of SVM was 86.2%. In patients with mild cognitive impairment, alpha band power was decreased in the frontal lobe, and high beta band power was increased in the frontal lobe compared to the normal cognitive group. Also, the gamma band power of the occipital-parietal lobe was decreased in mild cognitive impairment. These results represented that quantitative EEG can be used as a meaningful biomarker to discriminate cognitive decline.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.911-923
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• 2014

Ad hoc cognitive radio wireless sensor networks allow secondary wireless sensor nodes to recognize spectrum opportunities and transmit data. Most existing protocols proposed for ad hoc cognitive radio wireless sensor networks require a dedicated common control channel. Allocating one channel just for control packet exchange is a waste of resources for channel-constrained networks. There are very few protocols that do not rely on a common control channel and that exchange channel-negotiation control packets during a pre-allocated time on the data channels. This, however, can require a substantial amount of time to access the channel when an incumbent is present on the channel, where the nodes are intended to negotiate for the data channel. This study examined channel access delay on cognitive radio wireless sensor networks that have no dedicated common control channel.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.2
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• pp.371-388
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• 2014

Cognitive Radio (CR) has been recently proposed as a promising technology to remedy the problems of spectrum scarcity and spectrum underutilization by enabling unlicensed users to opportunistically utilize temporally unused licensed spectrums in a cautious manner. In Cognitive Radio Ad Hoc Networks (CRAHNs), data routing is one of the most challenging tasks since the channel availability and node mobility are unpredictable. Moreover, the network performance is severely degraded due to large numbers of path failures. In this paper, we propose the Fault-Tolerant Cognitive Ad-hoc Routing Protocol (FTCARP) to provide fast and efficient route recovery in presence of path failures during data delivery in CRAHNs. The protocol exploits the joint path and spectrum diversity to offer reliable communication and efficient spectrum usage over the networks. In the proposed protocol, a backup path is utilized in case a failure occurs over a primary transmission route. Different cause of a path failure will be handled by different route recovery mechanism. The protocol performance is compared with that of the Dual Diversity Cognitive Ad-hoc Routing Protocol (D2CARP). The simulation results obviously prove that FTCARP outperforms D2CARP in terms of throughput, packet loss, end-to-end delay and jitter in the high path-failure rate CRAHNs.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.10a
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• pp.219-220
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• 2009

• Journal of Engineering Education Research
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• v.18 no.5
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• pp.59-66
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• 2015

In the on-line pre-learning which is applied in this study, on line pre-learning, in-class, post-learning are circulated together in the same experiments. The on-line pre-learning has been tried to 136 students in A junior college in Seoul for 3 years. The effects of their self-regulated learning are as follows. First, the self-regulated learning ability has increased by 0.42 point. The point after the self-regulated learning and before it is 3.24 and 3.66 respectively. Second, cognitive regulation, motivational regulation and behavioral regulation have also increased. Out of them, cognitive control has increased the most. Metacognitive strategy is higher than cognitive strategy. In conclusion, the result shows that the on-line pre-learning is helpful to develop the self-regulated learning ability and it is also suitable to teaching-learning method for junior college.