• Wind and Structures
• /
• v.31 no.2
• /
• pp.165-183
• /
• 2020

The first step of performance-based design for transmission lines is the determination of wind fields as well as wind loads, which are largely depending on local wind climate and the surrounding terrain. Wind fields in a mountainous area are very different with that in a flat terrain. This paper firstly investigated both mean and fluctuating wind characteristics of a typical mountainous wind field by wind tunnel tests and computational fluid dynamics (CFD). The speedup effects of mean wind and specific turbulence properties, i.e., turbulence intensity, power spectral density (PSD) and coherence function, are highlighted. Then a hybrid simulation framework for generating three dimensional (3D) wind velocity field in the mountainous area was proposed by combining the CFD and proper orthogonal decomposition (POD) method given the properties of the target turbulence field. Finally, a practical 220 kV transmission line was employed to demonstrate the effectiveness of the proposed wind field generation framework and its role in the performance-based design. It was found that the terrain-induce turbulence effects dominate the performance-based structural design of transmission lines running through the mountainous area.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.6 no.3
• /
• pp.249-254
• /
• 2005

In this paper, we analysis the recognition performance of PCA/LDA by distance measures. We are adapt to ORL face database with the fourteen distance measures. In case of PCA, it has high performance for the manhattan distance and the weighted SSE distance to face recognition, In case of PCA/LDA, it has high performance for the angle-based distance and the modified SSE distance. Also, PCA/LDA is better than PCA for reduction of dimension. Therefore, the PCA/LDA method and the angle-based distance have the most performance and a few dimension for face recognition with ORL face database.

• Journal of Labour Economics
• /
• v.34 no.2
• /
• pp.29-52
• /
• 2011

Using occupational wage structure survey(1996-2006) by Korean ministry of employment and labor, we explored the effect of performance based pay on the pay dispersion within firm. Pay dispersion is defined as the within-firm variance of wage residuals after controlling the individual characteristics in the labor market. The results show that introduction of performance-based pay system increases the level of pay dispersion significantly. However, The relationship of employees' ratio who receive performance-based pay and the level of pay dispersion is an inverted U-shaped($\bigcap$).

• Journal of IKEEE
• /
• v.20 no.1
• /
• pp.75-81
• /
• 2016

This paper proposes a design of the tile based on graphic pipeline to improve the graphic application performance in SIMT based GP-GPU. The proposed Tile based on graphics pipeline avoids unnecessary graphic processing operation, and processes the rasterization step in parallel. The massive data processing in parallel through SIMT architecture improve the computational performance, thereby improving the 3D graphic pipeline performance. The more vertex data of 3D model, the higher performance. The proposed structure was confirmed to improve processing performance of up to 3 times from about 1.18 times as compared to 'RAMP' and previous studies.

• MALSORI
• /
• no.54
• /
• pp.27-43
• /
• 2005

Existing standard speech coders can provide speech communication of high quality while they degrade the performance of speech recognition systems that use the reconstructed speech by the coders. The main cause of the degradation is that the spectral envelope parameters in speech coding are optimized to speech quality rather than to the performance of speech recognition. For example, mel-frequency cepstral coefficient (MFCC) is generally known to provide better speech recognition performance than linear prediction coefficient (LPC) that is a typical parameter set in speech coding. In this paper, we propose a speech coder using MFCC instead of LPC to improve the performance of a server-based speech recognition system in network environments. However, the main drawback of using MFCC is to develop the efficient MFCC quantization with a low-bit rate. First, we explore the interframe correlation of MFCCs, which results in the predictive quantization of MFCC. Second, a safety-net scheme is proposed to make the MFCC-based speech coder robust to channel error. As a result, we propose a 8.7 kbps MFCC-based CELP coder. It is shown from a PESQ test that the proposed speech coder has a comparable speech quality to 8 kbps G.729 while it is shown that the performance of speech recognition using the proposed speech coder is better than that using G.729.

• Journal of Auto-vehicle Safety Association
• /
• v.13 no.4
• /
• pp.129-143
• /
• 2021

This paper proposes actuator fault detection and adaptive fault-tolerant control algorithms using performance index and human-like learning for longitudinal autonomous vehicles. Conventional longitudinal controller for autonomous driving consists of supervisory, upper level and lower level controllers. In this paper, feedback control law and PID control algorithm have been used for upper level and lower level controllers, respectively. For actuator fault-tolerant control, adaptive rule has been designed using the gradient descent method with estimated coefficients. In order to adjust the control parameter used for determination of adaptation gain, human-like learning algorithm has been designed based on perceptron learning method using control errors and control parameter. It is designed that the learning algorithm determines current control parameter by saving it in memory and updating based on the cost function-based gradient descent method. Based on the updated control parameter, the longitudinal acceleration has been computed adaptively using feedback law for actuator fault-tolerant control. The finite window-based performance index has been designed for detection and evaluation of actuator performance degradation using control error.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.19 no.2
• /
• pp.53-58
• /
• 2019

In this paper, we propose a new definition for the Private interface communication protocol structures order to improve the performance of LDAP-based Ud interface. Performance tests were separated by LDAP-based interface method and Private based interface method and analyzed the results of the performance test. As a result, it was confirmed the amount of processing of the received message and the response message to the result of the performance test that the Private based Ud interface method is 1.7 times(avg.) higher than the LDAP based Ud interface method.

• Transactions of Materials Processing
• /
• v.31 no.4
• /
• pp.229-239
• /
• 2022

Convolution Neural Network(CNN) is a class of deep learning algorithms and can be used for image analysis. In particular, it has excellent performance in finding the pattern of images. Therefore, CNN is commonly applied for recognizing, learning and classifying images. In this study, the surface defect classification performance of Al 6061 extruded material using CNN-based algorithms were compared and evaluated. First, the data collection criteria were suggested and a total of 2,024 datasets were prepared. And they were randomly classified into 1,417 learning data and 607 evaluation data. After that, the size and quality of the training data set were improved using data augmentation techniques to increase the performance of deep learning. The CNN-based algorithms used in this study were VGGNet-16, VGGNet-19, ResNet-50 and DenseNet-121. The evaluation of the defect classification performance was made by comparing the accuracy, loss, and learning speed using verification data. The DenseNet-121 algorithm showed better performance than other algorithms with an accuracy of 99.13% and a loss value of 0.037. This was due to the structural characteristics of the DenseNet model, and the information loss was reduced by acquiring information from all previous layers for image identification in this algorithm. Based on the above results, the possibility of machine vision application of CNN-based model for the surface defect classification of Al extruded materials was also discussed.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2022.05a
• /
• pp.139-139
• /
• 2022

Nature-based solutions (NBS) involved conservation or rehabilitation of natural ecosystems or the creation of natural processes in modified or artificial ecosystems to mimic natural processes for the improved management of water (UN-Water, 2018). This study investigated the relationship between microbial presence and survival to the pollutant treatment performance of seven different stormwater NBS managing urban stormwater runoff. In this study, seven different stormwater nature-based solution (NBS) was investigated to identify the relationship of microbial community to the pollutant removal performance of stormwater NBS. Based on this study, Proteobacteria was found to be the most dominant microorganism for all stormwater NBS and IS followed by Acidobacteria and Actinobacteria. Acidobacteria, Actinobacteria, Chloroflexi, Gemmatimonadetes, WS3, and AF234118_p were found to have high positive correlation to most pollutant removal efficiency of different stormwater NBS (r-value: 0.62 to 0.68). Using Proteobacteria and Acidobacteria count in stormwater NBS, equations predicting pollutant removal performance were also developed and may be used in minimizing the cost for stormevent monitoring to identify the pollutant removal performance of stormwater NBS.

• Transactions of the Korean hydrogen and new energy society
• /
• v.31 no.6
• /
• pp.622-629
• /
• 2020

The performance and cost of electric vehicles (EVs) are much influenced by the performance and service life of the Li-ion battery system. In particular, the cell performance and reliability of Li-ion battery packs are highly dependent on their operating temperature. Therefore, a novel battery thermal management is crucial for Li-ion batteries owing to heat dissipation effects on their performance. Among various types of battery thermal management systems (BTMS'), the phase change material (PCM) based BTMS is considered to be a promising cooling system in terms of guaranteeing the performance and reliability of Li-ion batteries. This work is mainly concerned with the basic research on PCM based BTMS. In this paper, a basic experimental study on PCM based battery cooling system was performed. The main purpose of the present study is to present a comparison of two PCM-based cooling systems (n-Eicosane and n-Docosane) of the unit 18650 battery module. To this end, the simplified PCM-based Li-ion battery module with two 18650 batteries was designed and fabricated. The thermal behavior (such as temperature rise of the battery pack) with various discharge rates (c-rate) was mainly investigated and compared for two types of battery systems employing PCM-based cooling. It is considered that the results obtained from this study provide good fundamental data on screening the appropriate PCMs for future research on PCM based BTMS for EV applications.