• KIPS Transactions on Computer and Communication Systems
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• v.8 no.9
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• pp.217-224
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• 2019

Recently, sensor networks are built and used on many kinds of fields such as home, traffic, medical treatment and power grid. Sensing data manipulation on these fields could be a serious threat on property and safety. Thus, a proper way to block sensing data manipulation is necessary. In this paper, we propose IoT(Internet of Things) sensing data validation mechanism based on data obfuscation and variance analysis to remove manipulated sensing data effectively. IoT sensor device modulates sensing data with obfuscation function and sends it to a user. The user demodulates received data to use it. Fake data which are not modulated with proper obfuscation function show different variance aspect with valid data. Our proposed mechanism thus can detect fake data by analyzing data variance. Finally, we measured data validation time for performance analysis. As a result, block rate for false data was improved by up to 1.45 times compared with the existing technique and false alarm rate was 0.1~2.0%. In addition, the validation time on the low-power, low-performance IoT sensor device was measured. Compared to the RSA encryption method, which increased to 2.5969 seconds according to the increase of the data amount, the proposed method showed high validation efficiency as 0.0003 seconds.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.12 no.3
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• pp.170-177
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• 2007

In this study, the long-term predictability of El Nino and La Nina events of Pusan National University Coupled General Circulation Model(PNU/CME CGCM) developed from a Research and Development Grant funded by Korea Meteorology Administration(KMA) was examined in terms of the correlation coefficients of the sea surface temperature between the model and observation and skill scores at the tropical Pacific. For the purpose, long-term global climate was hindcasted using PNU/CME CGCM for 12 months starting from April, July, October and January(APR RUN, JUL RUN, OCT RUN and JAN RUN, respectively) of each and every years between 1979 and 2004. Each 12-month hindcast consisted of 5 ensemble members. Relatively high correlation was maintained throughout the 12-month lead hindcasts at the equatorial Pacific for the four RUNs starting at different months. It is found that the predictability of our CGCM in forecasting equatorial SST anomalies is more pronounced within 6-month of lead time, in particular. For the assessment of model capability in predicting El Nino and La Nina, various skill scores such as Hit rates and False Alarm rate are calculated. According to the results, PNU/CME CGCM has a good predictability in forecasting warm and cold events, in spite of relatively poor capability in predicting normal state of equatorial Pacific. The predictability of our CGCM was also compared with those of other CGCMs participating DEMETER project. The comparative analysis also illustrated that our CGCM has reasonable long-term predictability comparable to the DEMETER participating CGCMs. As a conclusion, PNU/CME CGCM can predict El Nino and La Nina events at least 12 months ahead in terms of NIino 3.4 SST anomaly, showing much better predictability within 6-month of leading time.

• Journal of Korean Society of Environmental Engineers
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• v.22 no.12
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• pp.2175-2185
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• 2000

Respiration rate should be a reasonable state variable for the activated sludge and could be used to simulate the performance of the activated sludge process. Toxic materials are classified into three groups, competitive, noncompetitive and uncompetitive. They increase/decrease the half saturation coefficient or specific growth rate. that means decreasing of the substrate removal capacity. In this research, a pilot-scale activated sludge process was operated under extended aeration method, and a representative noncompetitive inhibitor, acidic wastewater was applied to establish a respirometry-based toxicity model. Using this model. the correlation coefficient between measured and calculated respiration rate was 0.96 when acidic wastewater(pH 3.9~5.5) was introduced continuously to the aeration tank. Even though respiration rate was decreased by toxic effect of acidic wastewater, effluent substrate concentration represented to COD was deteriorated just a little bit. It might be caused by the low ratio of readily biodegradable substrate in the input substrate. Reduction of respiration rate by decreasing of input substrate concentration was much lower than that by acidic wastewater, and hence it was estimated that the possibility of false toxic alarm caused by decreasing of substrate concentration should be low.

• Korean Journal of Remote Sensing
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• v.33 no.6_2
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• pp.1075-1087
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• 2017

In this study, we tried to utilize results of the change detection analysis for satellite images as the basis for updating the land cover map. The Sequential Spectral Change Vector Analysis ($S^2CVA$) was applied to multi-temporal multispectral satellite imagery in order to extract changed areas, efficiently. Especially, we minimized the false alarm rate of unsupervised change detection due to the seasonal variation using the direction information in $S^2CVA$. The binary image, which is the result of unsupervised change detection, was integrated with the existing land cover map using the zonal statistics. And then, object-based analysis was performed to determine the changed area. In the experiment using PlanetScope data and the land cover map of the Ministry of Environment, the change areas within the existing land cover map could be detected efficiently.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.5
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• pp.1235-1242
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• 2015

In global shipping logistics, it is important for users to keep track of the location of their continuously moving cargos. Analyzing the GPS data stream coming from the tag which is attached to the cargo, we are able to keep track of the cargo location in terms of going into or out of a certain logistics area using the information of the spatial relationship change between the tag and the logistics area. In this paper, we propose a simulation system for measuring the precision and false alarm rate of the cargo location tracking algorithm which generates spatial events over the global logistics areas. Due to the difficulty of experiment with a real tag, we developed a tag emulator to create a virtual tag which operates exactly like a real tag. We show the cargo location tracking system works correctly with the tag emulator which communicates with it using the same protocol as the real tag.

• The Journal of the Acoustical Society of Korea
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• v.34 no.6
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• pp.487-492
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• 2015

A short-range underwater target detection and identification techniques using mid- and high-frequency bands have been highly developed. However, nowadays the long-range detection using the low-frequency band is requested and one of the most challengeable issues. The waveform inversion technique is widely used and the hottest technology in both academia and industry of the seismic exploration. It is based on the numerical analysis tool, and could construct more than a few kilometers of the subsurface structures and model-parameters such as P-wave velocity using a low-frequency band. By applying this technique to the underwater acoustic circumstance, firstly application of underwater target detection is verified. Furthermore, subsurface structures and it's parameters of the war-field are well reconstructed. We can confirm that this technique greatly reduces the false-alarm rate for the underwater targets because it could accurately reproduce both the shape and the model-parameters at the same time.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.1
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• pp.47-58
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• 2011

MTI filter is used to separate target signal from clutter in many radar signal processing. By suppressing clutter before CFAR detection, the detection performance can be improved. As a radar system designed, a design engineer generally takes averaged SNR and CNR into account and does not include the effect of MTI filter's frequency response. In practice, when the signals including clutter are pass through the filter, SNR is widely varying according to target velocity and CNR is also varying according to clutter center frequency and spectrum spreading. In this paper, we have derived the relationship between the MTI filter's frequency response and a target's velocity and a clutter's spectrum characteristics. With the variation of SNR and CNR at the filter output, the detection performance of CFAR has been analyzed by the simulation and has made certain of their influences on the performance.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.1
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• pp.28-42
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• 2013

Personal Rapid Transit(PRT) is a new unmanned transportation system using electricity. The purpose of the PRT is relieving the congestion of city traffic and connecting between inner city and airport, high-speed railroad. PRT requires to develop devices for the guarantee of safety and reliability. PRT as the mean of rail transportation must be equipped with control system for front rail sensing. Ultra Wide Band(UWB) radar system is suitable for PRT's detection because it has the advantage of low power consumption, low interference and high resolution. In this paper, an improved adaptive Constant False Alarm Rate(CFAR) algorithm is proposed and studied in various noise environments. The proposed algorithm improves performance in various noise environments compared to the Mean Level CFAR algorithms and other adaptive CFAR algorithms.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.7
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• pp.45-50
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• 2010

In this paper, we analysis the performance of cooperative spectrum sensing with distance based weight for cognitive radio (CR) systems and CR systems sense the spectrum of the licensed user by using a energy detection method. Threshold is determined in accordance with the constant false alarm rate (CFAR) algorithm for energy detection. The signal of licensed user is OFDM signal and the wireless channel between a licensed user and CR systems is modeled as Gaussian channel. From the simulation results, the cooperative spectrum sensing with distance based weight combining (DWC) and equal gain combing (EGC) methods shows higher spectrum sensing performance than single spectrum sensing does. And the detection probability performance with the DWC is higher than that with the EGC.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.2 no.1 s.2
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• pp.75-84
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• 2003

Current techniques for road-traffic monitoring rely on sensors which have limited capabilities, are costly and disruptive to install. The use of video cameras coupled with computer vision techniques offers an attractive alternative to current sensors. Video based traffic monitoring systems are now being considered key points of advanced traffic management systems. In this paper, we propose the new method which extract the traffic information using video camera. The proposed method uses an adaptive updating scheme for background in order to reduce the false alarm rate due to various noises in images. also, the proposed extraction method of traffic information calculates the traffic volume ratio of vehicles passing through predefined detection area, which is defined by the length of profile occupied by cars over that of overall detection area. Then the ratio is used to define 8 different states of traffic and to interpret the state of vehicle flows. The proposed method is verified by an experiment using CCTV traffic data from urban area.