• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.60 no.3
• /
• pp.577-583
• /
• 2011

In AC-PDP, it is necessary to achieve high luminance efficiency, high luminance and high definition by adopting technologies such as high xenon concentration and long gap. However, it is very difficult to apply above technologies because they make many problems such as mis-discharge and high driving voltage. Especially, the reactive power of PDP must be reduced for satisfaction in international standard IEC62087. In this paper, we proposed CLHS driving method which is half sustain driver without energy recovery capacitor. In the experimental results, CLHS driving method reduced reactive power consumption about 10%. Also, CLHS driving method improved the luminance efficiency in all discharge loads. Therefor, the more the discharge load decreases, the more the luminance efficiency improves. When the discharge load is 20%, CLHS driving method improved 5.35%.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.48 no.8
• /
• pp.958-964
• /
• 1999

The distance in load parameter space to the closest saddle node bifurcation (CSNB) point provides the worst case power margin to voltage instability and the left eigenvector at CSNB identifies the most effective direction to steer the system to maximize voltage stability under contingency. This paper presents an improved direct method for computing CSNB: the order of nonlinear systems equations is reduced to about twice of the size of load flow equations in contrast to about three-times in Dobson's direct method; the initial guess for the direct method is computed efficiently and robustly by combined use of continuation power flow, a pair of multiple load flow solution with Lagrange interpolation. It is also shown that voltage stability may be enhanced significantly with shift of generations in the direction of the left eigenvector at CSNB.

• Journal of Information Processing Systems
• /
• v.16 no.4
• /
• pp.795-808
• /
• 2020

Due to the poor evaluation indexes such as detection accuracy and recall rate when Yolov3 network detects aircraft in remote sensing images, in this paper, we propose a remote sensing image aircraft detection method based on machine vision. In order to improve the target detection effect, the Inception module was introduced into the Yolov3 network structure, and then the data set was cluster analyzed using the k-means algorithm. In order to obtain the best aircraft detection model, on the basis of our proposed method, we adjusted the network parameters in the pre-training model and improved the resolution of the input image. Finally, our method adopted multi-scale training model. In this paper, we used remote sensing aircraft dataset of RSOD-Dataset to do experiments, and finally proved that our method improved some evaluation indicators. The experiment of this paper proves that our method also has good detection and recognition ability in other ground objects.

• Applied Biological Chemistry
• /
• v.8
• /
• pp.1-9
• /
• 1967

Korean soy-sauces were orepared by the ordinary and impreved method and its analyses on the organic acid. The results obtained is as following: 1. In analysing general components of prepared soy-sauce, total acid, volatile acid and non-volatile acid were found more in improved soy-sauce than in ordinary soy-sauce. 2. Volatile organic acid were analysed by gas-chromatography method. As a result, the followings was attained: a) In the ordinary soy-sauce, formic acid, acetic acid, propionic acid, and butyric acid were detected. Butyric acid was in the highest amount and then propionic acid, acetic acid and formic acid are followed in the order. b) In the improved soy-sauce, formic acid, acetic acid, propionic acid and butyric acid were detected. Acetic acid was in the highest amount and then propionic acid, butyric acid and formic acid are followed in the nrder. 3. Non-volatile organic acid were analysed by paper partition chromatography method. As a result, the followings were attained: a) Lactic, glutaric, fumaric, malonic, malic, glycolic, oxalic, tartaric, and succinic acid and two unknown spots were detected in ordinary soysauce. Lactic acid was in the highest amount and then succinic, glycolic, oxalic, tartaric, glutaric, malic, fumaric and malonic acid are followed in the order. b) Lactic, glutaric, malonic, malic, glycolic, tartaric, succinic and tgalacturonic acid and two unknown spots were detected in the improved soy-sauce. Lactic acid was in the highest amount and then succinic, glycolic, malic, glutaric, tartaric, galacturonic and malonic acid are followed in the order. 4. ${\alpha}-keto$ acid were analysed by paper partition chromatography. As a result, the followings were attained: Pyruvic acid and ${\alpha}-keto$ glutaric acid and an unknown spot were detected in the ordinary and improved soy-sauce. Pyruvic acid was in the highest amount and then ${\alpha}-keto$ glutaric acid are ollowed in the order. 5. Stale flavor in the ordinary soy-sauces seems to be partly affected by butyric acid and propionic acid. 6. Substances influencing taste, such as lactic acid and succinic acid, were found more in improved soy-sauce than ordinary soy-sauce.

• Computers and Concrete
• /
• v.15 no.1
• /
• pp.103-126
• /
• 2015

Thermal effects are significant loads for assessing concrete dam behaviour during operation. A new methodology to estimate thermal loads on concrete dams taking into account processes which were previously unconsidered, such as: the evaporative cooling, the night radiating cooling or the shades, has been recently reported. The application of this novel approach in combination with a three-dimensional finite element method to solve the heat diffusion equation led to a precise characterization of the thermal field inside the dam. However, that approach may be computationally expensive. This paper proposes the use of a new one-dimensional model based on an explicit finite difference scheme which is improved by means of the reported methodology for computing the heat fluxes through the dam faces. The improved model has been applied to a case study where observations from 21 concrete thermometers and data of climatic variables were available. The results are compared with those from: (a) the original one-dimensional finite difference model, (b) the Stucky-Derron classical one-dimensional analytical solution, and (c) a three-dimensional finite element method. The results of the improved model match well with the observed temperatures, in addition they are similar to those obtained with (c) except in the vicinity of the abutments, although this later is a considerably more complex methodology. The improved model have a better performance than the models (a) and (b), whose results present larger error and bias when compared with the recorded data.

• Smart Media Journal
• /
• v.9 no.4
• /
• pp.134-143
• /
• 2020

Vehicle License Plate Recognition is one of the approaches for transportation and traffic safety networks, such as traffic control, speed limit enforcement and runaway vehicle tracking. Although it has been studied for decades, it is attracting more and more attention due to the recent development of deep learning and improved performance. Also, it is largely divided into license plate detection and recognition. In this study, experiments were conducted to improve license plate detection performance by utilizing various object detection methods and WPOD-Net(Warped Planar Object Detection Network) model. The accuracy was improved by selecting the method of detecting the vehicle(s) and then detecting the license plate(s) instead of the conventional method of detecting the license plate using the object detection model. In particular, the final performance was improved through the process of removing noise existing in the image by using the Fast-SRGAN model, one of the Super-Resolution methods. As a result, this experiment showed the performance has improved an average of 4.34% from 92.38% to 96.72% compared to previous studies.

• Smart Structures and Systems
• /
• v.31 no.5
• /
• pp.469-483
• /
• 2023

The dynamic characteristics of wind turbine blades are usually monitored by contact sensors with the disadvantages of high cost, difficult installation, easy damage to the structure, and difficult signal transmission. In view of the above problems, based on computer vision technology and the improved YOLOv5 (You Only Look Once v5) deep learning model, a non-contact dynamic characteristic monitoring method for wind turbine blade is proposed. First, the original YOLOv5l model of the CSP (Cross Stage Partial) structure is improved by introducing the CSP2_2 structure, which reduce the number of residual components to better the network training speed. On this basis, combined with the Deep sort algorithm, the accuracy of structural displacement monitoring is mended. Secondly, for the disadvantage that the deep learning sample dataset is difficult to collect, the blender software is used to model the wind turbine structure with conditions, illuminations and other practical engineering similar environments changed. In addition, incorporated with the image expansion technology, a modeling-based dataset augmentation method is proposed. Finally, the feasibility of the proposed algorithm is verified by experiments followed by the analytical procedure about the influence of YOLOv5 models, lighting conditions and angles on the recognition results. The results show that the improved YOLOv5 deep learning model not only perform well compared with many other YOLOv5 models, but also has high accuracy in vibration monitoring in different environments. The method can accurately identify the dynamic characteristics of wind turbine blades, and therefore can provide a reference for evaluating the condition of wind turbine blades.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.10 no.4
• /
• pp.63-70
• /
• 2014

Method a target estimation in spatial are mobile wireless communication using network cell and GPS. It have much error that mobile wireless communication depend on cell size. GPS method can't find a target in shadow and inner area. In this paper, we estimate a target as direction of arrival method using adaptive array antenna system. Adaptive array antenna system can obtain desired signal to remove other signal This paper studied digital beamforming method in order to estimation a target. Proposed method is modified optimum weight and antenna error correction to estimation an optimal receive signal. Digital beamforming method decided a signal phase and amplitude from received signal on array antenna element. But if it is not to do error correction of received signal, system performance have decreased. Firstly, we proposed modified optimum weight in order to finding desired target. Secondly, we are error correction of antenna incident signals by optimal weight before digital beamforming method. Thirdly, throughly simulation, we showed that system performance of proposed method compare proposal method with general method. It have improved resolution of estimation target to good performance more proposed method than general method.

• Proceedings of the KIPE Conference
• /
• 2006.06a
• /
• pp.292-294
• /
• 2006

This paper presents a study on the use of improved space-vector modulation of VSI employing only four switches, four body diodes. Different switching sequence strategy for vector control for inverter fault mode are described. The influence of different switching patterns at same modulation index and improved PWM method is proposed. The proposed PWM is compared with conventional PWM. Simulation and experimental results are presented.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2017.10a
• /
• pp.721-722
• /
• 2017

This paper propose the method of an improved traffic light controller. the proposed improved traffic light controller are more systematic and decrement power consumption than earlier traffic light controller.