• Journal of Korean Society for Quality Management
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• v.38 no.3
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• pp.313-321
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• 2010

The coefficient of variation represents the ratio of the standard deviation to the mean, and it is a useful statistic for comparing the degree of variation from one data series to another, even if the means are drastically different from each other. Recently, the CV control chart is developed for monitoring processes in such situations. However, the CV control chart has low performance in detecting small shift. Due to the development of equipment and technique, currently, small shift of process occurs more frequently than large shift. In this paper, we proposes the CV-CUSUM control chart using CUSUM scheme which is cumulative sum of the deviations between each data point and a target value to detect a small shift in the process. We also found that the FIR(fast initial response) CUSUM control chart is especially valuable at start-up or after a CV-CUSUM control chart has signaled out-of-control.

• Bulletin of the Korean Chemical Society
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• v.33 no.8
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• pp.2539-2545
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• 2012

In the present study, we suggest a new way to reactivate performance of direct formic acid fuel cell (DFAFC) and explain its mechanism by employing electrochemical analyses like chronoamperometry (CA) and cyclic voltammogram (CV). For the evaluation of DFAFC performance, palladium (Pd) and platinum (Pt) are used as anode and cathode catalysts, respectively, and are applied to a Nafion membrane by catalyst-coated membrane spraying. After long DFAFC operation performed at 0.2 and 0.4 V and then CV test, DFAFC performance is better than its initial performance. It is attributed to dissolution of anode Pd into $Pd^{2+}$. By characterizations like TEM, Z-potential, CV and electrochemical impedance spectroscopy, it is evaluated that such dissolved $Pd^{2+}$ ions lead to (1) increase in the electrochemically active surface by reduction in Pd particle size and its improved redistribution and (2) increment in the total oxidation charge by fast reaction rate of the Pd dissolution reaction.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.364-368
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• 2018

In this paper, we use Faster R-CNN that is one of object detection algorithm and OpenCV that purposes computer vision, to implement the system that can detect danger when a vehicle attempts to change lanes into its own lane in videos of highway, national road, general road and etc. Also, the performance of implemented system is evaluated to prove that the performance is not bad.

• The Journal of Pediatrics of Korean Medicine
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• v.19 no.1
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• pp.103-115
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• 2005

Objectives : Nocturnal enuresis is common disorder in children and has important negative effects on the self-image and performance of children. Thus Successful treatment needed to increase self-esteem. Many studies of this symptoms were reported. But electro-acupuncture treatment not reported in Korea. Methods : We treated three cases enuretic children with different types. Their diagnosis were non-monosymptomatic primary, monosymptomatic primary, monosymptomatic secondary nocturnal enuresis. We used electro-acupuncture on Zhongji(CV3), Guanyuan(CV4) for 20 min. To investigate relapse. at least for 4 months after the end of the therapy we followed-up by telephone. Results : After treatment, diurnal urinary symptoms, such as increased frequency of urination, urgency, incontinence were dramatically improved. And the number of wet night decreased with nocturia and delayed wetting time. Compared to pre-treatment, findings, the number of wet nights decreased 80% or more. Conclusion : All of them tolerated electro-acupuncture well and kept reduction at least for 4 months follow-up. Further study is needed with more cases.

• Tribology and Lubricants
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• v.28 no.6
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• pp.328-332
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• 2012

Generated Axial Force (GAF) due to internal friction at Constant Velocity (CV) joints is one of the causes generating vibration problems such as shudder in vehicle. In this study, the GAF measuring tester is developed to precisely measure GAF caused by internal friction in CV joints. As the developed tester can control temperature at joint, driving torque, angle of rotation and joint angles, actual driving conditions such as sudden acceleration can be applied to the machine. GAFs are measured and compared by using different types of grease in tripod housing. Also GAFs are measured for both new and used CV joints to be compared and analyzed. The test result shows the repeatability and consistency of the tester in terms of the different test conditions. By using the developed CV joint tester, friction performance of the joint can be evaluated by proposing the best CV joints as well as greases generating the lowest GAF.

• 한국신재생에너지학회:학술대회논문집
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• 2007.06a
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• pp.157-160
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• 2007

The catalyst layer of a proton exchange membrane (PEM) fuel cell is a mixture of polymer, carbon, and platinum. The characteristics of the catalyst layer play critical role in determining the performance of the PEM fuel cell. This research investigates the role of catalyst layer composition using a Central Composite Design (CCD) experiment with two factors which are Nafion content and carbon loading while the platinum catalyst surface area is held constant. For each catalyst layer composition， polarization curves are measured to evaluate cell performance at common operating conditions, Electrochemical Impedance Spectroscopy (EIS), and Cyclic Voltammetry (CV) are then applied to investigate the cause of the observed variations in performance. The results show that both Nafion and carbon content significantly affect MEA performance. The ohmic resistance and active catalyst area of the cell do not correlate with catalyst layer composition, and observed variations in the cell resistance and active catalyst area produced changes in performance that were not significant relative to compositions of catalyst layers.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.116-122
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• 2016

Recently, the production cycle in manufacturing process has been getting shorter and different types of product have been produced in the same process line. In this case, the control chart using coefficient of variation would be applicable to the process. The theory that random variables are located in the three times distance of the deviation from mean value is applicable to the control chart that monitor the process in the manufacturing line, when the data of process are changed by the type of normal distribution. It is possible to apply to the control chart of coefficient of variation too. ${\bar{x}}$, s estimates that taken in the coefficient of variation have just used all of the data, but the upper control limit, center line and lower control limit have been settled by the effect of abnormal values, so this control chart could be in trouble of detection ability of the assignable value. The purpose of this study was to present the robust control chart than coefficient of variation control chart in the normal process. To perform this research, the location parameter, ${\bar{x_{\alpha}}}$, $s_{\alpha}$ were used. The robust control chart was named Tim-CV control chart. The result of simulation were summarized as follows; First, P values, the probability to get away from control limit, in Trim-CV control chart were larger than CV control chart in the normal process. Second, ARL values, average run length, in Trim-CV control chart were smaller than CV control chart in the normal process. Particularly, the difference of performance of two control charts was so sure when the change of the process was getting to bigger. Therefore, the Trim-CV control chart proposed in this paper would be more efficient tool than CV control chart in small quantity batch production.

• The Journal of Bigdata
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• v.9 no.1
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• pp.89-100
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• 2024

In the field of computer vision, models such as You Look Only Once (YOLO) and ResNet are widely used due to their real-time performance and high accuracy. However, to apply these models in real-world environments, factors such as runtime compatibility, memory usage, computing resources, and real-time conditions must be considered. This study compares the characteristics of three deep model runtimes: ONNX Runtime, TensorRT, and OpenCV DNN, and analyzes their performance on two models. The aim of this paper is to provide criteria for runtime selection for practical applications. The experiments compare runtimes based on the evaluation metrics of time, memory usage, and accuracy for vehicle license plate recognition and classification tasks. The experimental results show that ONNX Runtime excels in complex object detection performance, OpenCV DNN is suitable for environments with limited memory, and TensorRT offers superior execution speed for complex models.

• Journal of Animal Environmental Science
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• v.6 no.1
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• pp.37-44
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• 2000

A new hose slurry spreader with improved spreading uniformity is developed to distribute the slurrynear to the soil surface and to reduce odor problems. The precision of distributed slurry was investigated using 3 types of slurry and found to be dependent on the rotor speed. For the solid matter separated fluid containing 0.1% of dry matter rotor speed of 150 rpm showed best uniformity with CV of 10% In the case of slurry from dairy cattle which contains 8.2% of dry matter high rotor speed of 330 rpm showed best result with CV of 7.2% Also swine slurry which has a 13.6% of dry matter content showed the best result of 8.1% CV at the high rotor speed of 250rpm. A high rotor speed generates enough pressure in the central distributor and as a result uniform distribution of slurry can be achieved. In conclusion it is highly recommended rotor speed of 300 rpm to get the best performance.

• Journal of the Semiconductor & Display Technology
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• v.21 no.1
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• pp.75-78
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• 2022

Deep Neural Networks (DNN) has become an essential data processing architecture for the implementation of multiple computer vision tasks. Recently, DNN-based algorithms achieve much higher recognition accuracy than traditional algorithms based on shallow learning. However, training and inference DNNs require huge computational capabilities than daily usage purposes of computers. Moreover, with increased size and depth of DNNs, CPUs may be unsatisfactory since they use serial processing by default. GPUs are the solution that come up with greater speed compared to CPUs because of their Parallel Processing/Computation nature. In this paper, we analyze the inference time complexity of DNNs using well-known computer vision library, OpenCV. We measure and analyze inference time complexity for three cases, CPU, GPU-Float32, and GPU-Float16.