• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.3
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• pp.866-872
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• 2010

In this paper, we developed a digital soldering station based on PID controller, which supply stable power by controlling the current of heater of soldering iron. The proposed system designed PID controller to converge quickly to the set up temperature by user, and regain the lost of heat by external factors quickly. PID controller, designed by Ziegler-Nichols' tuning method, decides triac's trigger timing using setting temperature and present temperature to control the phase of AC 24V power that supply to the heater. Also, we give the function that shows present temperature and setting temperature of iron, and working time by graphic LCD. And during the rest time, we decided the power saving and extension of iron tip by dropping to the optimal temperature. Two experiments had implemented in $25^{\circ}C$ laboratory to confirm the performance of proposed method. The first experiment took 12sec, 13sec, 16sec, 18sec, reaching to $200^{\circ}C$, $300^{\circ}C$, $400^{\circ}C$, $480^{\circ}C$ respectively which result showed shorten of rising time than previous method. In the loading experiment of $300^{\circ}C$, $400^{\circ}C$, $480^{\circ}C$ steady state showed temperature drop of $3.8^{\circ}C$, $4.1^{\circ}C$, $4.5^{\circ}C$ which result showed the low temperature deviation than previous method.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.3
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• pp.99-108
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• 2021

There are unrestricted conditions on the driver's face inside the vehicle, such as changes in lighting, partial occlusion and various changes in the driver's condition. In this paper, we propose a face identification system in an unrestricted vehicle environment. The proposed method uses a near-infrared (NIR) camera to minimize the changes in facial images that occur according to the illumination changes inside and outside the vehicle. In order to process a face exposed to extreme light, the normal face image is changed to a simulated overexposed image using mean and variance for training. Thus, facial classifiers are simultaneously generated under both normal and extreme illumination conditions. Our method identifies a face by detecting facial landmarks and aggregating the confidence score of each landmark for the final decision. In particular, the performance improvement is the highest in the class where the driver wears glasses or sunglasses, owing to the robustness to partial occlusions by recognizing each landmark. We can recognize the driver by using the scores of remaining visible landmarks. We also propose a novel robust rejection and a new evaluation method, which considers the relations between registered and unregistered drivers. The experimental results on our dataset, PolyU and ORL datasets demonstrate the effectiveness of the proposed method.

• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.7
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• pp.922-930
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• 2020

Marine accidents involving fishing boats, caused by a loss of stability, have been increasing over the last decade. One of the main reasons for these accidents is a sudden wind attacks. In this regard, the wind loads acting on the ship hull need to be estimated accurately for safety assessments of the motion and maneuverability of the ship. Therefore, this study aims to develop a computational model for the inlet boundary condition and to numerically estimate the wind load acting on a fishing boat. In particular, wind loads acting on a fishing boat at the wind speed profile boundary condition were compared with the numerical results obtained under uniform wind speed. The wind loads were estimated at intervals of 15° over the range of 0° to 180°, and i.e., a total of 13 cases. Furthermore, a numerical mesh model was developed based on the results of the mesh dependency test. The numerical analysis was performed using the RANS-based commercial solver STAR-CCM+ (ver. 13.06) with the k-ω turbulent model in the steady state. The wind loads for surge, sway, and heave motions were reduced by 39.5 %, 41.6 %, and 46.1 % and roll, pitch, and yaw motions were 48.2 %, 50.6 %, and 36.5 %, respectively, as compared with the values under uniform wind speed. It was confirmed that the developed inlet boundary condition describing the wind speed gradient with respect to height features higher accuracy than the boundary condition of uniform wind speed. The insights obtained in this study can be useful for the development of a numerical computation method for ships.

• Korean Journal of Optics and Photonics
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• v.22 no.4
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• pp.184-190
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• 2011

A compact imaging spectrometer (COMIS) was developed for a microsatellite STSAT-3. The satellite is now rescheduled to be launched into a low sun-synchronous Earth orbit (~700 km) by the end of 2012. Its main operational goal is the imaging of the Earth's surface and atmosphere with ground sampling distance of 27 m and 2 - 15 nm spectral resolution over visible and near infrared spectrum (0.4 - 1.05 ${\mu}m$). A flight model of COMIS was developed following an engineering model that had successfully demonstrated hyperspectral imaging capability and structural rigidity. In this paper we report the environmental test results of the flight model. The mechanical stiffness of the model was confirmed by a small shift of the natural frequency i.e., < 1% over 10 gRMS random vibration test. Electrical functions of the model were also tested without showing any anomalies during and after vacuum thermal cycling test with < $10^{-5}$ torr and $-30^{\circ}C\;-\;35^{\circ}C$. The imaging capability of the model, represented by a modulation transfer function (MTF) value at the Nyquist frequency, was also kept unvaried after all those environmental tests.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.4
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• pp.579-586
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• 2018

Short-term prediction of travel speed has been widely studied using data-driven non-parametric techniques. There is, however, a lack of research on the prediction aimed at urban areas due to their complex dynamics stemming from traffic signals and intersections. The purpose of this study is to develop a hybrid approach combining ensemble empirical mode decomposition (EEMD) and artificial neural network (ANN) for predicting urban travel speed. The EEMD decomposes the time-series data of travel speed into intrinsic mode functions (IMFs) and residue. The decomposed IMFs represent local characteristics of time-scale components and they are predicted using an ANN, respectively. The IMFs can be predicted more accurately than their original travel speed since they mitigate the complexity of the original data such as non-linearity, non-stationarity, and oscillation. The predicted IMFs are summed up to represent the predicted travel speed. To evaluate the proposed method, the travel speed data from the dedicated short range communication (DSRC) in Daegu City are used. Performance evaluations are conducted targeting on the links that are particularly hard to predict. The results show the developed model has the mean absolute error rate of 10.41% in the normal condition and 25.35% in the break down for the 15-min-ahead prediction, respectively, and it outperforms the simple ANN model. The developed model contributes to the provision of the reliable traffic information in urban transportation management systems.

• Journal of the Korean Wood Science and Technology
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• v.41 no.6
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• pp.515-527
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• 2013

Building energy simulations which are mainly used in Korea have evaluated the building energy performance with the different thermal conductivity of construction materials. In order to evaluate the energy consumption accurately, the difference in thermal conductivity of the wood used in stud for wooden structure was confirmed from the each simulation. In addition, the thermal transmission of building members and the thermal bridge at the conjunction of building members according to thermal conductivity from each simulation programs were researched. The thermal conductivity of pine that has the largest variation among the energy simulations was applied to the thermal properties of studs in wooden structure. The maximum error between the maximum and minimum thermal transmission of roof, wall, and floor slab was $0.023W/m^2{\cdot}K$. Plus, that thermal bridge at Rafter junction on the roof, roof-wall joint, and floor slab-wall joint was $0.025W/m{\cdot}K$. The heat transfer image for changes in temperature and the heat exchange were analyzed by HEAT2 program. The distorted temperature lines were found around the insufficient insulated connection parts. It was predicted that the temperature at the distorted parts in the analyzed image was lower than that of the other portion of the other structures.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.5
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• pp.538-542
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• 2018

Echo generated in digital hearing aid vent give rise to user's discomfort. For cancelling feedback echo in vent, it is required to estimate vent impulse response exactly. The vent impulse response has time varying and sparse characteristics. The IPNLMS has been known a useful adaptive algorithm to estimate vent impulse response with these characteristics. In this paper, subband sparse adaptive filter which applying IPNLMS to subband hearing aid structure is proposed to cancel echo of vent by estimating sparse vent impulse response. In the propose method, the decomposition of input signal to subband can pre-whiten each subband signal, so adaptive filter convergence speed can be improved. And the poly phase component decomposition of adaptive filter increases sparsity of each components, and the better echo cancellation can be possible without additional computation. To derive coefficients update equation of the adaptive filter, by defining the cost function based weight NLMS is defined, and the coefficient update equation of each subband is derived. For verifying performances of the adaptive filter, convergence speed, and steady state error by white signal input, and echo cancelling results by real speech input are evaluated by comparing conventional adaptive filters.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.3
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• pp.242-250
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• 2019

In this paper, we propose a method to predict the failure of industrial robot using Seq2Seq (Sequence to Sequence) model, which is a model for transforming time series data among Artificial Neural Network models. The proposed method uses the data of the joint current and angular value, which can be measured by the robot itself, without additional sensor for fault diagnosis. After preprocessing the measured data for the model to learn, the Seq2Seq model was trained to convert the current to angle. Abnormal degree for fault diagnosis uses RMSE (Root Mean Squared Error) during unit time between predicted angle and actual angle. The performance evaluation of the proposed method was performed using the test data measured under different conditions of normal and defective condition of the robot. When the Abnormal degree exceed the threshold, it was classified as a fault, and the accuracy of the fault diagnosis was 96.67% from the experiment. The proposed method has the merit that it can perform fault prediction without additional sensor, and it has been confirmed from the experiment that high diagnostic performance and efficiency are available without requiring deep expert knowledge of the robot.

• Journal of Korean Society of Environmental Engineers
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• v.22 no.10
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• pp.1905-1919
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• 2000

The main motivation of this research is to develop an intelligent control strategy for Activated Sludge Process (ASP). ASP is a complex and nonlinear dynamic system because of the characteristic of wastewater, the change in influent flow rate, weather conditions, and etc. The mathematical model of ASP also includes uncertainties which are ignored or not considered by process engineer or controller designer. The ASP is generally controlled by a PID controller that consists of fixed proportional, integral, and derivative gain values. The PID gains are adjusted by the expert who has much experience in the ASP. The ASP model based on $Matlab^{(R)}5.3/Simulink^{(R)}3.0$ is developed in this paper. The performance of the model is tested by IWA(International Water Association) and COST(European Cooperation in the field of Scientific and Technical Research) data that include steady-state results during 14 days. The advantage of the developed model is that the user can easily modify or change the controller by the help of the graphical user interface. The ASP model as a typical nonlinear system can be used to simulate and test the proposed controller for an educational purpose. Various control methods are applied to the ASP model and the control results are compared to apply the proposed intelligent control strategy to a real ASP. Three control methods are designed and tested: conventional PID controller, fuzzy logic control approach to modify setpoints, and fuzzy-PID control method. The proposed setpoints changer based on the fuzzy logic shows a better performance and robustness under disturbances. The objective function can be defined and included in the proposed control strategy to improve the effluent water quality and to reduce the operating cost in a real ASP.

• Nuclear Medicine and Molecular Imaging
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• v.43 no.2
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• pp.120-128
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• 2009

Purpose: Early detection of recurrence is an important factor for long term survival of patients with colorectal cancer. Measurement of serum levels of CEA, CA 19-9, CT and PET/CT has been commonly used in the postoperative surveillance of colorectal cancer. The purpose of this study was to compare the diagnostic ability of PET/CT, tumor marker and CT for recurrence in colorectal cancer patients after treatment. Materials and Methods: F-18 FDG PET/CT imaging was performed in 189 colorectal cancer patients who underwent curative surgical resection and/or chemotherapy. Measurement of serum levels of CEA, CA 19-9 and CT imaging were performed within 2 months of PET/CT examination. Final diagnosis of recurrence was made by biopsy, radiologic studies or clinical follow-up for 6 months after each study. Results: Overall sensitivity, specificity of PET/CT was 94.7%, 91.1%, while those of serum CEA were 44.7% and 97.3%, respectively. Sensitivity and specificity were 94.2%, 90.4% for PET/CT and better than those of combined CEA and CA 19-9 measurement(52.1%, 88.5%) in 174 patients measured available both CEA and CA 19-9 data. In 115 patients with both tumor markers and CT images available, PET/CT showed similar sensitivity but higher specificity(92.9%, 91.3%) compared to combination of tumor markers and CT images(92.9%, 74.1%). Conclusion: PET/CT was superior for detection of recurred colorectal cancer patients compared with both CEA, CA 19-9, and even with combination of both tumor markers and CT. Therefore PET/CT could be used as a routine surveillance examination to detect recurrence or metastasis of colorectal cancer.