• Journal of the Korean Institute of Gas
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• v.26 no.6
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• pp.9-15
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• 2022

In order to verify the durability of the high-pressure hydrogen tank in the operating pressure range, a hydraulic rupture test should be performed. However, if the bubbles generated by the initial injection process of water are attached to the inner wall of the tank and remain, a sudden pressure change of the bubbles during the rupture of the pressurized tank may cause shock and noise. Therefore, in this study, the flow velocity required to remove the bubbles remaining on the inner wall of the tank was predicted through simplified formulas, and the shape of the injection nozzle to maintain the flow velocity was determined based on the shape of the hydrogen tank for the hydrogen bus. In addition, a numerical model was developed to predict the change in flow velocity according to the inlet pressure, and an experiment was performed through a model tank to prove the validity of the prediction result. As a result of the experiment, the flow velocity near the tank wall was similar to the predicted value of the analysis model, and when the inlet pressure was 1.5 to 5.5 bar, the minimum size of the removable bubble was predicted to be about 2.2 to 4.6 mm.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.3
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• pp.115-122
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• 2022

With the outbreak of COVID-19 a few years ago, video conferencing and electronic document work have increased, and for this reason, the proportion of computer work among modern people's daily routines is increasing. However, as more and more people work on computers in the wrong posture for a long time, the number of patients with poor eyesight and text neck is increasing. Until recently, many studies have been published to correct posture, but most of them have limitations that users may experience discomfort because they have to correct posture by wearing equipment. A posture correction sensor algorithm is proposed to prevent access to the minimum distance between a computer monitor and a person using an ultrasonic sensor device. At this time, an algorithm for minimizing false alarms among warning alarms that sound at the minimum distance is also proposed. Because the ultrasonic sensor device is used, posture correction can be performed without attaching a device to the body, and the user can relieve discomfort. In addition, experimental results showed that accuracy can be improved by reducing false alarms by removing more than half of the noise generated during distance measurement.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.5D
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• pp.635-644
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• 2009

Image processing technique in the outdoor environment is very sensitive, and it tends to lose a lot of accuracy when it rapidly changes by outdoor environment. Therefore, in order to calculate accurate traffic information using the traffic monitoring system, we must resolve removing shadow in transition time, Distortion by the vehicle headlights at night, noise of rain, snow, and fog, and occlusion. In the research, we developed a system to calibrate the amount of traffic, speed, and time occupancy by using image processing technique in a variety of outdoor environments change. This system were tested under outdoor environments at the Gonjiam test site, which is managed by Korea Institute of Construction Technology (www.kict.re.kr) for testing performance. We evaluated the performance of traffic information, volume counts, speed, and occupancy time, with 4 lanes (2 lanes are upstream and the rests are downstream) from the 16th to 18th December, 2008. The evaluation method performed as based on the standard data is a radar detection compared to calculated data using image processing technique. The System evaluation results showed that the amount of traffic, speed, and time occupancy in period (day, night, sunrise, sunset) are approximately 92-97% accuracy when these data compared to the standard data.

• Korea Trade Review
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• v.48 no.1
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• pp.215-241
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• 2023

As competition between ports intensifies, port efficiency has always been a hot topic in the port and shipping economy. Boosting regional and national economies by improving port efficiency and promoting sustainable development of ports is also a concern for port operators and local and national governments. In this situation, this study has the following objectives. First, using panel data from 2010 to 2017, the efficiency of 14 major inland ports along the Yangtze River was analyzed, and changes in port efficiency over time were examined. Second, 14 inland ports are divided into the middle, upper, and lower Yangtze River port groups to compare and review differences in efficiency levels of ports by basin. For the study, we applied a three-step DEA analysis method, which evaluated the pure relative efficiency of the port itself by removing the effects of environmental factors and statistical noise that could affect the efficiency evaluation and presented the results. As a result, it was confirmed that there was a clear difference in the efficiency value of the port between the first-stage and the third-stage efficiency evaluation result. In addition, the downstream ports showed relatively high efficiency compared to the middle and upstream ports.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.1
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• pp.32-38
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• 2024

In the case of apartment building, it is difficult to conduct non-destructive testing due to the actual presence of people and the dust and noise generated during the core test, so inspections are performed each time in the common area and underground parking lot, and the tests are conducted on the finishing material rather than on the concrete surface due to low-cost orders. As the process progresses, poor inspection is inevitable. In addition, the proposed formulas for strength estimation have large fluctuations depending on the differences in test conditions and environments, and even if they show the same measured value, the deviation between each proposed formula is large, making it difficult to accurately estimate strength, making it difficult to use. Accordingly, we would like to select finishing materials mainly used in apartment complexes and compare and evaluate the compressive strength of concrete according to the type of finishing material by using non-destructive testing methods directly on the finishing materials without removing the finishing materials. The reliability evaluation results of the estimated compressive strength of concrete using the ultrasonic velocity method according to the type of finishing material are as follows. The error rate between the estimated compressive strength and compressive strength derived through the ultrasonic velocity method shows a wide range of variation, ranging from 21.83% to 58.89%. The effect of the presence or absence of finishing materials on the estimated compressive strength was found to be insignificant. Accordingly, it is necessary to select more types of finishing materials and study ultrasonic velocity methods according to the presence or absence of finishing materials, and to study estimation techniques that can increase reliability.

• International Journal of Highway Engineering
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• v.9 no.4
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• pp.117-127
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• 2007

The exposed aggregate PCC(EAP) pavements have been successfully used in Europe and Japan as low-noise pavements. Coarse aggregate are exposed on the pavement surface texture of EAP by removing mortar of surface. The pavement surface texture should maintain not only low-noise characteristic but also adequate skid resistance level during the performance period. Skid resistance decreased with wearing and polishing of tire and pavement surface due to the repetition of tire-pavement contact. Since the tires mainly contact the exposed coarse aggregate, the shape and rock type of coarse aggregate significantly influence wearing and polishing of EAP pavements. The test for resistance to abrasion coarse aggregate by use of the Los Angeles machine(KS F 2508) and the method of test for resistance to abrasion coarse aggregate by use of the Accelerated Polishing Machine(ASTM D 3319-90) are generally used to evaluate polishing characteristics of aggregate. In this study, polishing of coarse aggregate of different five rock types were evaluated by KS F 2508(LA abrasion test) and ASTM D 3319-90(PSV method). The results of LA abrasion test and PSV method were contrary to each other. Since LA abrasion test is estimated the quantity of abrasion by the impact of aggregate, it may not be adequate to evaluate the polishing of aggregate by the repetition of tire. In the case of PSV method, the resistance of polishing is estimated the skid resistance variation of polished aggregate after repetition of tire. The PSV method is adequate for the evaluation on polishing of coarse aggregate. From the test results of PSV method, it was founded that rock type, specific gravity, coarse aggregate angularity, flat or elongated particles in coarse aggregate are significant to the resistance characteristic of coarse aggregate.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.99-112
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• 2010

Ensemble learning is a method for improving the performance of classification and prediction algorithms. It is a method for finding a highly accurateclassifier on the training set by constructing and combining an ensemble of weak classifiers, each of which needs only to be moderately accurate on the training set. Ensemble learning has received considerable attention from machine learning and artificial intelligence fields because of its remarkable performance improvement and flexible integration with the traditional learning algorithms such as decision tree (DT), neural networks (NN), and SVM, etc. In those researches, all of DT ensemble studies have demonstrated impressive improvements in the generalization behavior of DT, while NN and SVM ensemble studies have not shown remarkable performance as shown in DT ensembles. Recently, several works have reported that the performance of ensemble can be degraded where multiple classifiers of an ensemble are highly correlated with, and thereby result in multicollinearity problem, which leads to performance degradation of the ensemble. They have also proposed the differentiated learning strategies to cope with performance degradation problem. Hansen and Salamon (1990) insisted that it is necessary and sufficient for the performance enhancement of an ensemble that the ensemble should contain diverse classifiers. Breiman (1996) explored that ensemble learning can increase the performance of unstable learning algorithms, but does not show remarkable performance improvement on stable learning algorithms. Unstable learning algorithms such as decision tree learners are sensitive to the change of the training data, and thus small changes in the training data can yield large changes in the generated classifiers. Therefore, ensemble with unstable learning algorithms can guarantee some diversity among the classifiers. To the contrary, stable learning algorithms such as NN and SVM generate similar classifiers in spite of small changes of the training data, and thus the correlation among the resulting classifiers is very high. This high correlation results in multicollinearity problem, which leads to performance degradation of the ensemble. Kim,s work (2009) showedthe performance comparison in bankruptcy prediction on Korea firms using tradition prediction algorithms such as NN, DT, and SVM. It reports that stable learning algorithms such as NN and SVM have higher predictability than the unstable DT. Meanwhile, with respect to their ensemble learning, DT ensemble shows the more improved performance than NN and SVM ensemble. Further analysis with variance inflation factor (VIF) analysis empirically proves that performance degradation of ensemble is due to multicollinearity problem. It also proposes that optimization of ensemble is needed to cope with such a problem. This paper proposes a hybrid system for coverage optimization of NN ensemble (CO-NN) in order to improve the performance of NN ensemble. Coverage optimization is a technique of choosing a sub-ensemble from an original ensemble to guarantee the diversity of classifiers in coverage optimization process. CO-NN uses GA which has been widely used for various optimization problems to deal with the coverage optimization problem. The GA chromosomes for the coverage optimization are encoded into binary strings, each bit of which indicates individual classifier. The fitness function is defined as maximization of error reduction and a constraint of variance inflation factor (VIF), which is one of the generally used methods to measure multicollinearity, is added to insure the diversity of classifiers by removing high correlation among the classifiers. We use Microsoft Excel and the GAs software package called Evolver. Experiments on company failure prediction have shown that CO-NN is effectively applied in the stable performance enhancement of NNensembles through the choice of classifiers by considering the correlations of the ensemble. The classifiers which have the potential multicollinearity problem are removed by the coverage optimization process of CO-NN and thereby CO-NN has shown higher performance than a single NN classifier and NN ensemble at 1% significance level, and DT ensemble at 5% significance level. However, there remain further research issues. First, decision optimization process to find optimal combination function should be considered in further research. Secondly, various learning strategies to deal with data noise should be introduced in more advanced further researches in the future.