• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.1742-1746
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• 2008

지금까지의 대부분의 2차원 수리해석 모형은 상류와 사류가 혼재된 불연속적인 천이류 흐름을 해석하기에 계산의 정확도 및 현실성에서 많은 문제를 보이고 있으며, 특히 계산과정에서 나타날 수 있는 마른하도의 처리에 있어서 많은 어려움을 겪고 있다. 본 연구의 목적은 유한체적기법을 사용하여 상류와 사류가 혼재하는 불연속적인 하천 천이류를 안정적으로 해석하기 위해 개발된 고정확도 수치모형의 자연하도 적용에 있으며, 또한 마른 하도로 전파되는 흐름 모의 및 계산과정에서 나타날 수 있는 마른하도 처리의 어려움을 해결함으로써 모형의 정확도와 안정성을 검증하여 실제 하천에서의 모형 적용성을 검토함에 있다. 이를 위해 본 연구에서는 흐름의 전파양상을 정확하게 반영할 수 있는 상류이송기법인 Godunov 기법과 관심격자의 좌우 격자 정보를 모두 사용하는 대표적 중앙차분기법인 Beam-Warming 기법의 장점을 모두 반영한 가중평균흐름률 (Weighted Average Flux) 기법을 사용하여 사각격자망의 구성을 통해 자연하도에 적용시킬 수 있는 2차원 유한체적모형을 개발하고자 하였고, 개발된 모형의 안정성, 정확도, 적용성을 검증하기 위해 직사각형 수로, 큰 사행비를 가진 만곡수로에 적용하고, 그 결과를 수리모형 실험결과와 비교, 분석하였다.

• Journal of the Korean Society for Heat Treatment
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• v.9 no.2
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• pp.147-158
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• 1996

Generally, analytical consideration on the behaviour of metallic structures during quenching process, and analysis on the thermal stress and deformation after heat treatment are very important in presumption of crack and distorsion of quenched material. In this study a set of constitute equations relevant to the analysis of thermo elasto-viscoplastic materials with strain hysteresis during quenching process way presented on the basis of contimuum thermo-dynamics mechanics. The thermal stresses were numerically calculated by finite element technique of weighted residual method and the principle of virtual work. In the calculation process, the temperature depandency of physical and mechaniclal properties of the material in consideration. On the distribution of elasto-viscoplastic thermal stresses according to radial direction, axial and tangential stress are tensile stress(50MPa, 1.5GPa and 300MPa) in surface and compressive stress(-1.2GPa, -1.14GPa and -750MPa) in the inner part on the other hand, radial stress is tensile stress(900MPa) in area of analysis. According to axial direction, tangential stress gradients are average 60MPa/mm on the whole. The reversion of stress takes place at 11.5 to 16.8mm from the center in area of analysing.

• JSTS:Journal of Semiconductor Technology and Science
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• v.16 no.6
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• pp.808-816
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• 2016

As the number of CPU/GPU cores and IPs in SOC increases and applications require explosive memory bandwidth, simultaneously achieving good throughput and fairness in the memory system among interfering applications is very challenging. Recent works proposed priority-based thread scheduling and channel partitioning to improve throughput and fairness. However, combining these different approaches leads to performance and fairness degradation. In this paper, we analyze the problems incurred when combining priority-based scheduling and channel partitioning and propose dynamic priority thread scheduling and adaptive channel partitioning method. In addition, we propose dynamic address mapping to further optimize the proposed scheme. Combining proposed methods could enhance weighted speedup and fairness for memory intensive applications by 4.2% and 10.2% over TCM or by 19.7% and 19.9% over FR-FCFS on average whereas the proposed scheme requires space less than TCM by 8%.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.7
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• pp.127-132
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• 2017

In this paper, we propose a controller gain based on model based design and implement the two-wheel inverted pendulum type robot using NXT Lego and RobotC language. Two-wheel inverted pendulum robot consists of NXT mindstorm, servo DC motor with encoder, gyro sensor, and accelerometer sensor. We measurement wheel angle using bulit-in encoder and calculate wheel angle speed using moving average method. Gyro measures body angular velocity and accelerometer measures body pitch angle. We calculate body angle with complementary filter using gyro and accelerometer sensor. The control gain is a weighted value for wheel angle, wheel angular velocity, body pitch angle, and body pich angular velocity, respectively. We experiment and observe the effect of two-wheel inverted pendulum with respect to change of control gains.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.7
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• pp.1104-1113
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• 2015

In this paper, we propose Two-Dimensional Robust Face Recognition System Realized with the Aid of Facial Symmetry with Illumination Variation. Preprocessing process is carried out to obtain mirror image which means new image rearranged by using difference between light and shade of right and left face based on a vertical axis of original face image. After image preprocessing, high dimensional image data is transformed to low-dimensional feature data through 2-directional and 2-dimensional Principal Component Analysis (2D)2PCA, which is one of dimensional reduction techniques. Polynomial-based Radial Basis Function Neural Network pattern classifier is used for face recognition. While FCM clustering is applied in the hidden layer, connection weights are defined as a linear polynomial function. In addition, the coefficients of linear function are learned through Weighted Least Square Estimation(WLSE). The Structural as well as parametric factors of the proposed classifier are optimized by using Particle Swarm Optimization(PSO). In the experiment, Yale B data is employed in order to confirm the advantage of the proposed methodology designed in the diverse illumination variation

• Journal of Information Technology Services
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• v.19 no.2
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• pp.93-107
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• 2020

Recently, artificial intelligence (AI) technologies has been widely used in various fields such as finance, and distribution. Accordingly, Korea has also announced its AI R&D strategy for the realization of i-Korea 4.0 in May 2018. However, Korea's AI technology is inferior to major competitors such as the US, Canada, and Japan Therefore, in order to cope with the 4th industrial revolution, it is necessary to allocate AI R&D budgets efficiently through selection and concentration so as to gain competitive advantage under a limited budget. In this study, the importance of each AI technology was evaluated in multi-dimensional way through the questionnaire of expert group using the evaluation index derived from the literature review From the results of this study, we draw the following implication. In order to successfully establish the AI technology development strategies, it is necessary to prioritize the cognitive computing technology that has great market growth potential, ripple effect of technology development, and the urgency of technology development according to the principle of selection and concentration. To this end, it is necessary to find creative ideas, manage assessments, converge multidisciplinary systems and strengthen core competencies. In addition, since AI technology has a large impact on socioeconomic development, it is necessary to comprehensively grasp and manage scientific and technological regulations in order to systematically promote AI technology development.

• Convergence Security Journal
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• v.11 no.3
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• pp.19-24
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• 2011

Software failure time presented in the literature exhibit either constant monotonic increasing or monotonic decreasing, For data analysis of software reliability model, data scale tools of trend analysis are developed. The methods of trend analysis are arithmetic mean test and Laplace trend test. Trend analysis only offer information of outline content. In this paper, we discuss forecasting failure time case of failure time censoring. In this study, time series analys is used in the simple moving average and weighted moving averages, exponential smoothing method for predict the future failure times, Empirical analysis used interval failure time for the prediction of this model. Model selection using the mean square error was presented for effective comparison.

• Journal of Digital Convergence
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• v.15 no.2
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• pp.165-172
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• 2017

In this paper, we analyze the research / technology trends of electric vehicles from 2001 to 2014, through keyword analysis using paper data published in SCIE or SSCI Journal on electric vehicles, time series analysis using patent data by IPC, and network analysis using nodeXL. also we predicted promising technologies of electric vehicles using one of the prediction methods, weighted moving average method. As a result of this study, battery technology among the electric vehicle component technologies appeared as a promising technology.

• Journal of Environmental Health Sciences
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• v.22 no.4
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• pp.62-68
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• 1996

Precipitation samples were collected by the wet-only event sampling method at Seoul from September 1991 to April 1995. Concentrations of samples for the ion components($NO_3^-, NO_2^-, SO_4^{2-}, Cl^-, F^-, Na^+, K^+, Ca^{2+}, Mg^{2+}$ and $NH_4^+$) were measured in addition to pH and electric conductivity. During the sampling period, 182 samples were collected, but only 163 samples were identified as valid. The pH, calculated from the volume-weighted $H^+$ concentration, was found to be 4.7, indicating a relatively intensive acidity compared with data from other regions of the world, where acid deposition was known to be a problem. Above all, the concentration of non-seasalt sulfate was $84 \mu eq/L$, which was the highest compared to that measured in other regions of the world. The major acidifying ions in the precipitation at Seoul were identified as sulfate and nitrate except for chloride, because the Cl/Na ratio in the precipitation was close to the ratio in seawater. If all of the non-seasalt sulfate and nitrate existed in the form of sulfuric and nitric acids, respectively, the average pH in the precipitation was calculated as 3.7, lower than the measured value. Consequently, the difference between the calculated and measured pH suggest that the acidity of precipitation was neutralized by alkaline species, not due to the low contribution of an anthropogenic air pollutants to the precipitation. The equivalent concentration ratio of sulfate to nitrate was 3.5, which indicated that the contributions of sulfuric and nitric acids to the precipitation acidity were 78% and 22%, respectively.

• Journal of Animal Science and Technology
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• v.65 no.3
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• pp.627-637
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• 2023

As the population and income levels rise, meat consumption steadily increases annually. However, the number of farms and farmers producing meat decrease during the same period, reducing meat sufficiency. Information and Communications Technology (ICT) has begun to be applied to reduce labor and production costs of livestock farms and improve productivity. This technology can be used for rapid pregnancy diagnosis of sows; the location and size of the gestation sacs of sows are directly related to the productivity of the farm. In this study, a system proposes to determine the number of gestation sacs of sows from ultrasound images. The system used the YOLOv7-E6E model, changing the activation function from sigmoid-weighted linear unit (SiLU) to a multi-activation function (SiLU + Mish). Also, the upsampling method was modified from nearest to bicubic to improve performance. The model trained with the original model using the original data achieved mean average precision of 86.3%. When the proposed multi-activation function, upsampling, and AutoAugment were applied, the performance improved by 0.3%, 0.9%, and 0.9%, respectively. When all three proposed methods were simultaneously applied, a significant performance improvement of 3.5% to 89.8% was achieved.