• Journal of Radiation Protection and Research
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• v.24 no.3
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• pp.171-184
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• 1999

In this paper, using statistical theory the basic concepts and the formulars of lower limit of detection were deasribed. Assuming that risks of 5% are acceptable (95% confidence level), lower limits of detection were calculated on the measuring apparatus for alpha, beta and gamma nuclides. Also, on the basis concepts of lower limit of detection, the MDA values were calculated for the radionuclides detected easily in the environment. These results make it possible to evaluate confidence limits on the radioanalytical results in the environmental sample.

• Nuclear Engineering and Technology
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• v.55 no.11
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• pp.3925-3934
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• 2023

The importance of fast neutron detection for nuclear safeguards purposes has increased due to its potential advantages such as reasonable cost and higher precision for larger sample masses of nuclear materials. Pulse-shape discrimination (PSD) is inevitably used to discriminate neutron- and gamma-ray- induced signals from organic scintillators of very high gamma sensitivity. The light output (LO) threshold corresponding to several MeV of recoiled proton energy could be necessary to achieve fine PSD performance. However, this leads to neutron count losses and possible distortion of results obtained by neutron multiplicity counting (NMC)-based nuclear material accountancy (NMA). Moreover, conventional PSD techniques are not effective for counting of neutrons in a high-gamma-ray environment, even under a sufficiently high LO threshold. In the present work, PSD performance (figure-of-merit, FOM) according to LO bands was confirmed using a conventional charge comparison method (CCM) and compared with results obtained by convolution neural network (CNN)-based PSD algorithms. Also, it was attempted, for the first time ever, to reject fake neutron signals from distorted PSD regions where neutron-induced signals are normally detected. The overall results indicated that higher neutron detection efficiency with better accuracy could be achieved via CNN-based PSD algorithms.

• Proceedings of the Acoustical Society of Korea Conference
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• 1984.12a
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• pp.66-69
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• 1984

This paper is a study on the Endpoint Detection for Korean Speech Recognition. In speech signal process, analysis parameter was classification from Zero Crossing Rate(Z.C.R), Log Energy(L.E), Energy in the predictive error(Ep) and fundamental Korean Speech digits, /영/-/구/ are selected as date for the Recognition of Speech. The main goal of this paper is to develop techniques and system for Speech input ot machine. In order to detect the Endpoint, this paper makes choice of Log Energy(L.E) from various parameters analysis, and the Log Energy is very effective parameter in classifying speech and nonspeech segments. The error rate of 1.43% result from the analysis.

• Journal of Communications and Networks
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• v.16 no.5
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• pp.493-501
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• 2014

Coverage completeness is an important indicator for quality of service in wireless sensor networks (WSN). Due to limited energy and diverse working conditions, the sensor nodes have different lifetimes which often cause network holes. Most of the existing methods expose large limitation and one-sidedness because they generally consider only one aspect, either coverage rate or energy issue. This paper presents a novel method for coverage hole detection with residual energy in randomly deployed wireless sensor networks. By calculating the life expectancy of working nodes through residual energy, we make a trade-off between network repair cost and energy waste. The working nodes with short lifetime are screened out according to a proper ratio. After that, the locations of coverage holes can be determined by calculating the joint coverage probability and the evaluation criteria. Simulation result shows that compared to those traditional algorithms without consideration of energy problem, our method can effectively maintain the coverage quality of repaired WSN while enhancing the life span of WSN at the same time.

• Journal of Communications and Networks
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• v.16 no.2
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• pp.172-182
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• 2014

In this paper, we investigate the fundamental performance limits of the cooperative sensing using energy detection by considering the unlimited number of sensing nodes. Although a lot of cognitive radio research so far proposed various uses of energy detection because of its simplicity, the performance limits of energy detection have not been studied when a large number of sensing nodes exist. First, we show that when the sensing nodes see the independent and identically distributed channel conditions, then as the number of sensing nodes N goes to infinity, the OR rule of hard decision achieves zero of false alarm Pf for any given target probability of detection $\bar{P_d}$ irrespective of the non-zero received primary user signal to noise ratio ${\gamma}$. Second, we show that under the same condition, when the AND rule of hard decision is used, there exists a lower bound of $P_f$. Interestingly, however, for given $\bar{P_d}$, $P_f$ goes to 1 as N goes to infinity. Third, we show that when the soft decision is used, there exists a way of achieving 100% utilization of secondary user, i.e., the sensing time overhead ratio goes to zero so does $P_f$.We verify our analyses by performing extensive simulations of the proposed unlimited cooperative sensing. Finally, we suggest a way of incorporating the unlimited cooperative sensing into a practical cellular system such as long term evolutionadvanced by exploiting the existing frame structure of absolute blank subframe to implement the in-band sensing.

• The Journal of the Korea Contents Association
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• v.10 no.12
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• pp.101-108
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• 2010

Many works on energy-efficient cluster event detection schemes have been done considering the energy restriction of sensor networks. The existing cluster event detection schemes transmit only the boundary information of detected cluster event nodes to the base station. However, If the range of the cluster event is widened and the distribution density of sensor nodes is high, the existing cluster event detection schemes need high transmission costs due to the increase of sensor nodes located in the event boundary. In this paper, we propose an energy-efficient cluster event detection scheme using the minimum boundary polygons (MBP) that can compress and summarize the information of event boundary nodes. The proposed scheme represents the boundary information of cluster events using the MBP creation technique in the large scale of sensor network environments. In order to show the superiority of the proposed scheme, we compare it with the existing scheme through the performance evaluation. Simulation results show that our scheme maintains about 92% accuracy and decreases about 80% in energy consumption to detect the cluster event over the existing schemes on average.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.2
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• pp.147-154
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• 2015

In this paper, we propose human detection and fuzzy temperature control system for energy reduction of cooling device in elevator. In order to improve problems of existing cooling device using the refrigerant, energy reduction and efficient management are continuously achieved because of operation of thermoelectric cooling device using the human detection and fuzzy temperature control system. The proposed system confirms the number of passengers in elevator and temperature is then controlled by those numbers and an average temperature for the season in fuzzy system. The human detection method scans the number of passengers using a head part as a feature based on bird's-eye view camera in elevator. The fuzzy system determines elevator internal temperature considering atmospheric temperature and the scanned passenger numbers as a look-up table. The proposed system reduces energy of the cooling device through the human detection and temperature control. In experiment, energy reduction is confirmed and the performance of the proposed system is verified.

• Journal of Satellite, Information and Communications
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• v.9 no.1
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• pp.28-32
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• 2014

In this paper, we analyzed performance of signal detection for terrestrial digital multimedia broadcasting (T-DMB) system in various channel environments that applied gaussian, Rayleigh and COST 207 environments that estimate response of real channel state. In order to detect the signal, a signal detection scheme based on energy detection is employed. We generated T-DMB signals so that estimate properly simulation result. For evaluating the signal detection performance, detection probability is derived. We consider two kinds of detection segment, which are three segments and five segments. And we compare the system performances in accordance with the detection segment. From simulation results, it is confirmed that the performance of signal detection is raised as increase the number of segments. The result of this paper can be applied to implement signal detection of broadcasting system.

• Journal of the Korean Solar Energy Society
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• v.33 no.4
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• pp.89-93
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• 2013

In recent years, many investigations about photovoltaic power systems have been significantly carried out in the fields of renewable power energy. Such research area generally includes developments of highly efficient solar cells, advanced power conversion systems, and smart monitoring systems. A generic objective of fault detection and diagnosis techniques is to timely recognize unexpected faulty of dynamic systems so that economic demage occurred by such faulty is decreased by means of engineering techniques. This paper presents a novel fault detection approach for photovoltaic power arrays which are electrically connected in series and parallels. In the proposed fault detection scheme, we first measure all of photovoltaic modules located in each array by using electronic sense systems and then compare each measurement in turn to detect location of fault module through statistic computation algorithm. We accomplish real-time experiments to demonstrate our proposed fault detection methodology by using a test-bed system including two 20 watt photovoltaic modules.

• ETRI Journal
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• v.35 no.1
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• pp.80-88
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• 2013

A passive infrared or pyroelectric infrared (PIR) sensor is mainly used to sense the existence of moving objects in an indoor environment. However, in an outdoor environment, there are often outbreaks of false alarms from environmental changes and other sources. Therefore, it is difficult to provide reliable detection outdoors. In this paper, two algorithms are proposed to reduce false alarms and provide trustworthy quality to surveillance systems. We gather PIR signals outdoors, analyze the collected data, and extract the target features defined as window energy and alarm duration. Using these features, we model target and false alarms, from which we propose two target decision algorithms: window energy detection and alarm duration detection. Simulation results using real PIR signals show the performance of the proposed algorithms.