• Transactions of the Korean hydrogen and new energy society
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• v.25 no.5
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• pp.525-532
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• 2014

The sensing of a stack coolant deficiency is very important in that cooling performance of a fuel cell, overheating prevention of a stack or coolant heater. This paper explains the performance comparison between the coolant contact/noncontact level sensors and coolant deficiency sensing logic using the pressure sensor in a stagnant or circulating flow. Throughout the comparison, the pressure sensor is more suitable than the other sensors in terms of the precision, fast response, sensing frequency. After the experiment, the pressure sensor is equipped to an FCEV(Fuel Cell Electric Vehicle) to verify sensing definitely. There was no miss-sensing using pressure sensor while FCEV runs in the conditions of the paved road and cross country road.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.5
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• pp.1131-1145
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• 2013

Energy detection is a widely used method for spectrum sensing in cognitive radios due to its simplicity and accuracy. However, it is severely affected by the noise uncertainty. To solve this problem, a blind multiband spectrum sensing scheme which is robust to noise uncertainty is proposed in this paper. The proposed scheme performs spectrum sensing over the total frequency channels simultaneously rather than a single channel each time. To improve the detection performance, the proposal jointly utilizes the likelihood function combined with Gerschgorin radii of unitary transformed covariance matrix. Unlike the conventional sensing methods, our scheme does not need any prior knowledge of noise power or PU signals, and thus is suitable for blind spectrum sensing. In addition, no subjective decision threshold setting is required in our scheme, making it robust to noise uncertainty. Finally, numerical results based on the probability of detection and false alarm versus SNR or the number of samples are presented to validate the performance of the proposed scheme.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.175-182
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• 2002

The paper introduces the application of flood monitoring and assessment by remote sensing and GIS in china and describes the frame of operational system for practical performance of flood disaster mitigation. In addition, The operational system for flood monitoring and assessment in RSTAC/ MWR and its application in the floods of 1998,1999 in china are introduced.

• Information Display
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• v.18 no.3
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• pp.3-12
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• 2017

In the recent years, significant advances have been made in the development of small form-factor, low power, and low cost 3D-sensing devices based on depth-imaging technologies with real-time performance. This has led to the advent of devices and machines that are able to sense and understand the world, navigate in the environment, and interact naturally with their human users. Human-computer interactions based on touch sensing and speech recognition have already become mainstream, and the rapid developments in 3D sensing is paving the path towards the next level of machine intelligence and interactions. This paper discusses the recent developments in real-time 3D sensing technologies and their emerging system application.

• International Journal of Advanced Culture Technology
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• v.1 no.2
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• pp.18-23
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• 2013

In this paper, we consider the problem of designing optimal sensing time and the minimization of energy consumption in the Cognitive radio Network. Trade-off between throughput and the sensing time are observed, and the equations are derived for the optimal choice of design variables. In this paper, we also look at the optimization problem involving all the design parameters together. The advantages of the proposed scheme for the spectrum sensing and access process are shown through simulation.

• Journal of Satellite, Information and Communications
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• v.9 no.1
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• pp.22-27
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• 2014

In this paper, we analyzed performance of FFT based on pilot sensing scheme for DTV signal in fading environments. In order to detect the present and absent for advanced television system committee digital television (ATSC DTV), a pilot detection scheme based on FFT is employed. Also, these signals are applied to each fading environment. For evaluating the spectrum sensing performance, detection probability is derived. When threshold is decided, we refer to constant false alarm rate (CFAR) scheme. From simulation results, it is confirmed that the spectrum sensing performance is improved as increase of the false alarm rate. The result of this paper can be applied to implement the spectrum sensing part of cognitive radio (CR) systems.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.6
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• pp.87-92
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• 2013

This paper focuses on analyzing the effects of primary user (PU) signal arrival on the local spectrum sensing performance. The probability for signal arrival at a sample in the sensing time is uniformly distributed in the sensing time. We first analyze the main factor that causes the degradation in the detection results in the conventional energy detection (CED) under the uniformly random arrival of the PU-signal. Thus we propose an approach in order to enhance the detection performance, in which an estimator which detects the arrival of the PU signal cooperates with a composite energy detection. The mathematical analysis and numerical simulation has validated the outperformance of the proposed approach compared to the CED.

• Journal of Information Technology Services
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• v.15 no.1
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• pp.167-178
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• 2016

Spectrum sensing in cognitive radio (CR) has a great role in order to utilize idle spectrum opportunistically, since it is responsible for making available dynamic spectrum access efficiently. In this research area, collaboration among multiple cognitive radio users has been proposed for the betterment of detection reliability. Even though cooperation among them improves the spectrum sensing performance, some falsely reporting malicious users may degrade the performance rigorously. In this article, we have studied the detection and nullifying the harmful effects of such malicious users by applying some well known outlier detection methods based on Grubb's test, Boxplot method and Dixon's test in cooperative spectrum sensing. Initially, the performance of each technique is compared and found that Boxplot method outperforms both Grubb's and Dixon's test for the case where multiple malicious users are present. Secondly, a new algorithm based on reputation and weight is developed to identify malicious users and cancel out their negative impact in final decision making. Simulation results demonstrate that the proposed scheme effectively identifies the malicious users and suppress their harmful effects at the fusion center to decide whether the spectrum is idle.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.39-46
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• 2013

Cooperative spectrum sensing can improve sensing reliability, compared with single node spectrum sensing. In addition, Eigenvalue-based spectrum sensing has also drawn a great attention due to its performance improvement over the energy detection method in which the more smoothing factor, the better performance is achieved. However, the more smoothing factor in Eignevalue-based spectrum sensing requires the more sensing time. Furthermore, more reporting time in cooperative sensing will be required as the number of nodes increases. Subsequently, we in this paper propose an Eigenvalue and superposition-based spectrum sensing where the reporting time is utilized so as to increase the number of smoothing factors for autocorrelation calculation. Simulation result demonstrates that the proposed scheme has better detection probability in both local as well as global detection while requiring less sensing time as compared with conventional Eigenvalue-based detection scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.20-33
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• 2015

Spectrum sensing is a key component of cognitive radio. The prediction of the primary user status in a low signal-to-noise ratio is an important factor in spectrum sensing. However, because of noise uncertainty, secondary users have difficulty distinguishing between the primary signal and an unauthorized signal when an unauthorized user exists in a cognitive radio network. To resolve the sensitivity to the noise uncertainty problem, we propose an entropy-based spectrum sensing scheme to detect the primary signal accurately in the presence of an unauthorized signal. The proposed spectrum sensing uses the conditional entropy between the primary signal and the unauthorized signal. The ability to detect the primary signal is thus robust against noise uncertainty, which leads to superior sensing performance in a low signal-to-noise ratio. Simulation results show that the proposed spectrum sensing scheme outperforms the conventional entropy-based spectrum sensing schemes in terms of the primary user detection probability.