• Nuclear Engineering and Technology
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• v.38 no.1
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• pp.81-92
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• 2006

In this study, the core dynamics of a PWR reactor is identified online by a recursive least-squares method. Based on the identified reactor model consisting of the control rod position and the core average coolant temperature, the future average coolant temperature is predicted. A model predictive control method is applied to designing an automatic controller for the thermal power control of PWR reactors. The basic concept of the model predictive control is to solve an optimization problem for a finite future at current time and to implement as the current control input only the first optimal control input among the solutions of the finite time steps. At the next time step, this procedure for solving the optimization problem is repeated. The objectives of the proposed model predictive controller are to minimize both the difference between the predicted core coolant temperature and the desired temperature, as well as minimizing the variation of the control rod positions. In addition, the objectives are subject to the maximum and minimum control rod positions as well as the maximum control rod speed. Therefore, a genetic algorithm that is appropriate for the accomplishment of multiple objectives is utilized in order to optimize the model predictive controller. A three-dimensional nuclear reactor analysis code, MASTER that was developed by the Korea Atomic Energy Research Institute (KAERI) , is used to verify the proposed controller for a nuclear reactor. From the results of a numerical simulation that was carried out in order to verify the performance of the proposed controller with a $5\%/min$ ramp increase or decrease of a desired load and a $10\%$ step increase or decrease (which were design requirements), it was found that the nuclear power level controlled by the proposed controller could track the desired power level very well.

• The KIPS Transactions:PartB
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• v.17B no.5
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• pp.355-362
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• 2010

Face tracking is to estimate the motion of a non-rigid face together with a rigid head in 3D, and plays important roles in higher levels such as face/facial expression/emotion recognition. In this paper, we propose an AAM-based face tracking algorithm. AAM has been widely used to segment and track deformable objects, but there are still many difficulties. Particularly, it often tends to diverge or converge into local minima when a target object is self-occluded, partially or completely occluded. To address this problem, we utilize the scale invariant feature transform (SIFT). SIFT is an effective method for self and partial occlusion because it is able to find correspondence between feature points under partial loss. And it enables an AAM to continue to track without re-initialization in complete occlusions thanks to the good performance of global matching. We also register and use the SIFT features extracted from multi-view face images during tracking to effectively track a face across large pose changes. Our proposed algorithm is validated by comparing other algorithms under the above 3 kinds of occlusions.

• The Journal of the Korea Contents Association
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• v.18 no.8
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• pp.434-445
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• 2018

This study examined whether mobile OTT video service substitutes home TV by using 3 screen data of Nielson-KoreanClick. According to the 2SLS estimation results, when the time spent on mobile OTT video service increased by 1% p, the time spent watching home TV decreased by 12.4%. The results also showed that 1%p increase in the time spent using YouTube app and the mobile OTT video services provided by telecommunication company(Oksusu, Alleh TV, VideoPortal) reduced the time spent on watching terrestrial channels on TV by 16.2% and 23.9%, respectively. The displacement of mobile OTT video service on home TV will be accelerated in the near future. In order to resolve the issue of regulatory unfairness with pay TV services and to safeguard viewer's interests, discussions to establish regulation for OTT video services should be taken place more quickly.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.104-106
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• 2005

In this work, a PWR reactor core dynamics is identified online by a recursive least squares method. Based on this identified reactor model consisting of the control rod position and the core average coolant temperature, the future average coolant temperature is predicted. A model predictive control method is applied to design an automatic controller for thermal power control in PWRs. The basic concept of the model predictive control is to solve an optimization problem for a finite future at current time and to implement as the current control input only the first optimal control input among the solutions of the finite time steps. At the next time step, the procedure to solve the optimization problem is then repeated. The objectives of the proposed model predictive controller are to minimize both the difference between the predicted core coolant temperature and the desired one, and the variation of the control rod positions. Also, the objectives are subject to maximum and minimum control rod positions and maximum control rod speed. Therefore, the genetic algorithm that is appropriate to accomplish multiple objectives is used to optimize the model predictive controller. A 3-dimensional nuclear reactor analysis code, MASTER that was developed by Korea Atomic Energy Research Institute (KAERI), is used to verify the proposed controller for a nuclear reactor. From results of numerical simulation to check the performance of the proposed controller at the 5%/min ramp increase or decrease of a desired load and its 10% step increase or decrease which are design requirements, it was found that the nuclear power level controlled by the proposed controller could track the desired power level very well.

• Smart Structures and Systems
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• v.25 no.5
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• pp.569-580
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• 2020

The identification of delays and delay compensation are critical problems in real-time hybrid simulations (RTHS). Conventional delay compensation methods are mostly based on the assumption of a constant delay. However, the system delay may vary during tests owing to the nonlinearity of the loading system and/or the behavioral variations of the specimen. To address this issue, this study presents an adaptive delay compensation method based on a discrete model of the loading system. In particular, the parameters of this discrete model are identified and updated online with the least-squares method to represent a servo hydraulic loading system. Furthermore, based on this model, the system delays are compensated for by generating system commands using the desired displacements, achieved displacements, and previous displacement commands. This method is more general than the existing compensation methods because it can predict commands based on multiple displacement categories. Moreover, this method is straightforward and suitable for implementation on digital signal processing boards because it relies solely on the displacements rather than on velocity and/or acceleration data. The virtual and real RTHS results show that the studied method exhibits satisfactory estimation smoothness and compensation accuracy. Furthermore, considering the measurement noise, the low-order parameter models of this method are more favorable than that the high-order parameter models.

• Journal of the Korea Society of Computer and Information
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• v.24 no.12
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• pp.93-100
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• 2019

Similarity computation is very crucial to performance of memory-based collaborative filtering systems. These systems make use of user ratings to recommend products to customers in online commercial sites. For better recommendation, most similar users to the active user need to be selected for their references. There have been numerous similarity measures developed in literature, most of which suffer from data sparsity or cold start problems. This paper intends to extract preference information as much as possible from user ratings to compute more reliable similarity even in a sparse data condition, as compared to previous similarity measures. We propose a new similarity measure which relies not only on user ratings but also on movie genre information provided by the dataset. Performance experiments of the proposed measure and previous relevant measures are conducted to investigate their performance. As a result, it is found that the proposed measure yields better or comparable achievements in terms of major performance metrics.

• Nuclear Engineering and Technology
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• v.52 no.2
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• pp.296-307
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• 2020

Permanent magnet sodium flowmeter (PMSF) have been used to measure the sodium flow in fast breeder reactors. Due to the effects of irradiation, thermal cycling, time lapse, etc., the magnetic flux density of the PMSF will decrease after being used in the reactor for a period of time. Therefore, it must be calibrated regularly. But some flowmeters that immersed in sodium cannot be removed for an off-line calibration, so the on-line calibration is required. However, the best online calibration accuracy of PMSF using cross-correlation analysis method was 2.0-level without considering the repeatability. In order to further improve this work, the operational principle of the transducer in PMSF is analyzed and the design principle of the transducer is proposed. The transducers were tested on the sodium flow loop to collect the experimental data. The signal characteristics are analyzed from the time and frequency domains, respectively. The cross-correlation analysis method based on biased estimation is adopted to obtain the flow rate. The verification experimental results showed that the measurement accuracy is 1.0-level when the flow velocity is above 0.5 m/s, and the measurement accuracy is 3.0-level when the flow velocity is in the range of 0.2 m/s to 0.5 m/s.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.3
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• pp.869-874
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• 2015

Background: The prognostic value of microvessel density (MVD), reflecting angiogenesis, detected in ovarian cancer is currently controversial. Here we performed a meta-analysis of all relevant eligible studies. Materials and Methods: A comprehensive search of online PubMed, Medline, EMBASE and Sciencedirect was performed to identify all related articles. The search strategy was designed as 'microvessel density', 'ovarian cancer', 'ovarian neoplasm', 'CD34' and 'angiogenesis'. Results: The studies were categorized by author/year, number of patients, FIGO stage, histology, cutoff value for microvessel density, types of survival analysis, methods of hazard rations (HR) estimation, HR and its 95% confidence interval (CI). Combined hazard ratios suggested that high MVD was associated with poor overall survival (OS) and progression-free survival (PFS), with HR and 95% CIs of 1.84 (1.33-2.35) and 1.36 (1.06-1.66), respectively. Subgroup analysis showed that high MVD detected by CD34 was relevant for OS [HR=1.67 (1.36-2.35)], but not MVD detected with other antibodies [HR=2.11 (0.90-3.31)]. Another subgroup analysis indicated that high MVD in patients without pre-chemotherapy, but not with pre-chemotherapy, was associated with OS [HR=1.88(1.59-2.18 and HR=1.70 (-0.18-3.59)]. Conclusions: The OS and PFS with high MVD were significant poorer than with low MVD in ovarian cancer patients. However, high MVD detected by CD34 seems to be more associated with survival for patients without pre-chemotherapy.

• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.6
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• pp.101-112
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• 2013

Shuttle Radar Topography Mission Digital Elevation Model (SRTM DEM) offers opportunities to make advances in many research areas including hydrology by providing near-global scale elevation measurements at a uniform resolution. Its wide coverage and complimentary online access especially benefits researchers requiring topographic information of hard-to-access areas. However, SRTM DEM also contains inherent errors, which are subject to propagation with its manipulation into analysis outputs. Sensitivity of hydrologic analysis to the errors has not been fully understood yet. This study investigated their impact on estimation of hydrologic derivatives such as slope, stream network, and watershed boundary using Monte Carlo simulation and spatial moving average techniques. Different amount of the errors and their spatial auto-correlation structure were considered in the study. Two sub-watersheds of Geum and Deadong River areas located in South and North Korea, respectively, were selected as the study areas. The results demonstrated that the spatial presentations of stream networks and watershed boundaries and their length and area estimations could be greatly affected by the SRTM DEM errors, in particular relatively flat areas. In the Deadong River area, artifacts of the SRTM DEM created sinks even after the filling process and then closed drainage basin and short stream lines, which are not the case in the reality. These findings provided an evidence that SRTM DEM alone may not enough to accurately figure out the hydrologic feature of a watershed, suggesting need of local knowledge and complementary data.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.6
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• pp.29-38
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• 2018

In this paper, we developed a virtual cloth try-on (VTON) technology that segement the cloth image worn on the mannequin and applies it to the user 's photograph. The two-dimensional image-based virtual wear study which does not require three-dimensional information of cloth and model is of practical value, but the research result shows that there are limitations of of the current technology for the problem of occlusion or distortion. In this study, we proposed an algorithm to apply the results obtained from the DNN- based segmentation and posture estimation to the user 's photograph, assuming that the mannequin cloth reduces the difficulties in this part. In order to improve the performance compared with the existing one, we used the validity check of the pre-attitude information, the improvement of the deformation using the outline, and the improvement of the divided area. As a result, a significantly improved result image of more than 50% was obtained.