• Journal of Drive and Control
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• v.21 no.1
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• pp.22-30
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• 2024

Gearboxes designed for reciprocating motion operating mechanisms operate under conditions where both the load and speed undergo continuous variations. When conducting durability tests on gearboxes designed for such applications, operating the target gearbox under conditions similar to the intended usage is essential. The gearbox must be operated for the required number of cycles to validate its durability under conditions mirroring its intended usage. This study devised an accelerated test method for gearboxes, which reduces operating angles and operational strokes. The reliability of the accelerated test was verified by comparing the stresses imposed on the gears under general and acceleration conditions through multi-body dynamic simulations. The results confirmed that the maximum contact stress levels under normal and accelerated conditions were within a 0.1% error range, indicating a minimal difference in the gear damage rates. However, a difference in the maximum contact stress results between the normal and accelerated conditions was observed when inertial forces acted on the output shaft due to the operational acceleration of the gearbox. Therefore, when conducting this acceleration test, caution should be exercised to ensure that the operational load on the gearbox, which affects inertia, does not significantly deviate from the conditions observed under normal operating conditions.

• Archives of Plastic Surgery
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• v.50 no.6
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• pp.627-634
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• 2023

In recent decades, a number of simulation models for microsurgical training have been published. The human placenta has received extensive validation in microneurosurgery and is a useful instrument to facilitate learning in microvascular repair techniques as an alternative to using live animals. This study uses a straightforward, step-by-step procedure for instructing the creation of simulators with dynamic flow to characterize the placental vascular tree and assess its relevance for plastic surgery departments. Measurements of the placental vasculature and morphological characterization of 18 placentas were made. After the model was used in a basic microsurgery training laboratory session, a survey was given to nine plastic surgery residents, two microsurgeons, and one hand surgeon. In all divisions, venous diameters were larger than arterial diameters, with minimum diameters of 0.8 and 0.6 mm, respectively. The majority of the participants considered that the model faithfully reproduces a real microsurgical scenario; the consistency of the vessels and their dissection are similar in in vivo tissue. Furthermore, all the participants considered that this model could improve their surgical technique and would propose it for microsurgical training. As some of the model's disadvantages, an abundantly thick adventitia, a thin tunica media, and higher adherence to the underlying tissue were identified. The color-perfused placenta is an excellent tool for microsurgical training in plastic surgery. It can faithfully reproduce a microsurgical scenario, offering an abundance of vasculature with varying sizes similar to tissue in vivo, enhancing technical proficiency, and lowering patient error.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.5
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• pp.1082-1090
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• 2009

Peak expiratory flow rate(PEF) is a very important diagnostic parameter obtained from the forced vital capacity(FVC) test. The expiratory flow rate increases during the short initial time period and may cause measurement error in PEF particularly due to non-ideal dynamic characteristic of the transducer. The present study evaluated the initial rise slope($S_r$) on the flow rate signal to compensate the transducer output data. The 26 standard signals recommended by the American Thoracic Society(ATS) were generated and flown through the velocity-type respiratory air flow transducer with simultaneously acquiring the transducer output signal. Most PEF and the corresponding output($N_{PEF}$) were well fitted into a quadratic equation with a high enough correlation coefficient of 0.9997. But only two(ATS#2 and 26) signals resulted significant deviation of $N_{PEF}$ with relative errors>10%. The relationship between the relative error in $N_{PEF}$ and $S_r$ was found to be linear, based on which $N_{PEF}$ data were compensated. As a result, the 99% confidence interval of PEF error was turned out to be approximately 2.5%, which was less than a quarter of the upper limit of 10% recommended by ATS. Therefore, the present compensation technique was proved to be very accurate, complying the international standards of ATS, which would be useful to calibrate respiratory air flow transducers.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.127-142
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• 2016

Deep learning model is a kind of neural networks that allows multiple hidden layers. There are various deep learning architectures such as convolutional neural networks, deep belief networks and recurrent neural networks. Those have been applied to fields like computer vision, automatic speech recognition, natural language processing, audio recognition and bioinformatics where they have been shown to produce state-of-the-art results on various tasks. Among those architectures, convolutional neural networks and recurrent neural networks are classified as the supervised learning model. And in recent years, those supervised learning models have gained more popularity than unsupervised learning models such as deep belief networks, because supervised learning models have shown fashionable applications in such fields mentioned above. Deep learning models can be trained with backpropagation algorithm. Backpropagation is an abbreviation for "backward propagation of errors" and a common method of training artificial neural networks used in conjunction with an optimization method such as gradient descent. The method calculates the gradient of an error function with respect to all the weights in the network. The gradient is fed to the optimization method which in turn uses it to update the weights, in an attempt to minimize the error function. Convolutional neural networks use a special architecture which is particularly well-adapted to classify images. Using this architecture makes convolutional networks fast to train. This, in turn, helps us train deep, muti-layer networks, which are very good at classifying images. These days, deep convolutional networks are used in most neural networks for image recognition. Convolutional neural networks use three basic ideas: local receptive fields, shared weights, and pooling. By local receptive fields, we mean that each neuron in the first(or any) hidden layer will be connected to a small region of the input(or previous layer's) neurons. Shared weights mean that we're going to use the same weights and bias for each of the local receptive field. This means that all the neurons in the hidden layer detect exactly the same feature, just at different locations in the input image. In addition to the convolutional layers just described, convolutional neural networks also contain pooling layers. Pooling layers are usually used immediately after convolutional layers. What the pooling layers do is to simplify the information in the output from the convolutional layer. Recent convolutional network architectures have 10 to 20 hidden layers and billions of connections between units. Training deep learning networks has taken weeks several years ago, but thanks to progress in GPU and algorithm enhancement, training time has reduced to several hours. Neural networks with time-varying behavior are known as recurrent neural networks or RNNs. A recurrent neural network is a class of artificial neural network where connections between units form a directed cycle. This creates an internal state of the network which allows it to exhibit dynamic temporal behavior. Unlike feedforward neural networks, RNNs can use their internal memory to process arbitrary sequences of inputs. Early RNN models turned out to be very difficult to train, harder even than deep feedforward networks. The reason is the unstable gradient problem such as vanishing gradient and exploding gradient. The gradient can get smaller and smaller as it is propagated back through layers. This makes learning in early layers extremely slow. The problem actually gets worse in RNNs, since gradients aren't just propagated backward through layers, they're propagated backward through time. If the network runs for a long time, that can make the gradient extremely unstable and hard to learn from. It has been possible to incorporate an idea known as long short-term memory units (LSTMs) into RNNs. LSTMs make it much easier to get good results when training RNNs, and many recent papers make use of LSTMs or related ideas.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.307-319
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• 2016

A Land-Atmosphere Modeling Package (LAMP) for supporting agricultural and forest management was developed at the National Center for AgroMeteorology (NCAM). The package is comprised of two components; one is the Weather Research and Forecasting modeling system (WRF) coupled with Noah-Multiparameterization options (Noah-MP) Land Surface Model (LSM) and the other is an offline one-dimensional LSM. The objective of this paper is to briefly describe the two components of the NCAM-LAMP and to evaluate their initial performance. The coupled WRF/Noah-MP system is configured with a parent domain over East Asia and three nested domains with a finest horizontal grid size of 810 m. The innermost domain covers two Gwangneung deciduous and coniferous KoFlux sites (GDK and GCK). The model is integrated for about 8 days with the initial and boundary conditions taken from the National Centers for Environmental Prediction (NCEP) Final Analysis (FNL) data. The verification variables are 2-m air temperature, 10-m wind, 2-m humidity, and surface precipitation for the WRF/Noah-MP coupled system. Skill scores are calculated for each domain and two dynamic vegetation options using the difference between the observed data from the Korea Meteorological Administration (KMA) and the simulated data from the WRF/Noah-MP coupled system. The accuracy of precipitation simulation is examined using a contingency table that is made up of the Probability of Detection (POD) and the Equitable Threat Score (ETS). The standalone LSM simulation is conducted for one year with the original settings and is compared with the KoFlux site observation for net radiation, sensible heat flux, latent heat flux, and soil moisture variables. According to results, the innermost domain (810 m resolution) among all domains showed the minimum root mean square error for 2-m air temperature, 10-m wind, and 2-m humidity. Turning on the dynamic vegetation had a tendency of reducing 10-m wind simulation errors in all domains. The first nested domain (7,290 m resolution) showed the highest precipitation score, but showed little advantage compared with using the dynamic vegetation. On the other hand, the offline one-dimensional Noah-MP LSM simulation captured the site observed pattern and magnitude of radiative fluxes and soil moisture, and it left room for further improvement through supplementing the model input of leaf area index and finding a proper combination of model physics.

• Environmental and Resource Economics Review
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• v.22 no.4
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• pp.613-641
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• 2013

This paper uses the error correction model to analyse dynamic gasoline price adjustments of the four refiners. Unlike the existing studies, this model allows a refiner's asymmetric adjustment to changes in the other refiners' prices as well as in its own price and costs. With the estimation results, we can obtain the following findings. First, there are the asymmetric price adjustments to changes in exchange rate and international gasoline price, but showing opposing directions. Second, for most of the refiners, the prices respond immediately to the lagged deviation from the long run equilibrium price, but asymmetrically respond for a few refiners. Third, there are some refiners that adjust their price to the other refiners' price deviation from the long run equilibrium. For some refiners, there are competitive price adjustments to the others' price deviations. These findings imply that a refiner faces inelastic demand, intends to maintain implicitly a relative level of its own price to others, and tends to respond competitively to the others' price deviation from the equilibrium.

• Journal of Korean Ophthalmic Optics Society
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• v.14 no.2
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• pp.9-14
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• 2009

Purpose: The purpose of this study was to examine the relationship between the accommodative facility, blink rate and accommodative lag according to the change of angles of main viewpoint of near distance worker and study an appropriate viewing angle that mitigates asthenopia, such as headaches or eye fatigue accompanied when reading and staring at the computer or TV for a long time. Methods: Total of 27 people including 12 male university students and 15 female university students in the age of 20 to 36 with frequent near distance works, such as computers, were selected to study the accommodative facility, the blink rate and the accommodative lag in accordance with the change of viewing angles of the near distance workers. The refraction error was corrected completely and the phoropter was shifted to near distance mode to locate the near distance indication at 40 cm. The accommodative facility and the blink rate were measured for one minute at each viewing direction of $40^{\circ}$ downward, $20^{\circ}$ downward, horizontal, and $20^{\circ}$ upward directions based on the horizontal line and the accommodative lag was measured in dynamic retinoscopy using retinoscope. Results: As a result, when the main viewpoint was moved on upper direction from the $40^{\circ}$ below, the accommodative facility was reduced and the blink rate and the accommodative lag were increased so their eyes became dry and the accommodation response was reduced. Conclusions: In near distance works, the eye fatigue level can be minimized by locating a book or a computer screen $40^{\circ}$ below than the horizontal direction.

• Clean Technology
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• v.26 no.3
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• pp.186-195
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• 2020

The isothermal adsorption, dynamic, and thermodynamic parameters of Acid black (AB) and Quinoline yellow (QY) adsorption by activated carbon were investigated using the initial concentration, contact time, temperature, and pH of the dyes as adsorption parameters. The adsorption equilibrium data fits the Freundlich isothermal adsorption model, and the calculated Freundlich separation factor values found that activated carbon can effectively remove AB and QY. Comparing the kinetic data showed that the pseudo second order model was within 10% error in the adsorption process. The intraparticle diffusion equation results were divided into two straight lines. Since the slope of the intraparticle diffusion line was smaller than the slope of the boundary layer diffusion line, it was confirmed that intraparticle diffusion was the rate-controlling step. The thermodynamic experiments indicated that the activation energies of AB and QY were 19.87 kJ mol^-1 and 14.17 kJ mol^-1, which corresponded with the physical adsorption process (5 ~ 40 kJ mol^-1). The adsorption reaction was spontaneous because the free energy change in the adsorption of AB and QY by activated carbon was negative from 298 to 318 K. As the temperature increased, the free energy value decreased resulting in higher spontaneity. Adsorption of AB and QY by activated carbon showed the highest adsorption removal rate at pH 3 due to the effect of anions generated by dissociation. The adsorption mechanism was electrostatic attraction.

• Journal of the Earthquake Engineering Society of Korea
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• v.22 no.3
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• pp.175-184
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• 2018

In this paper, comparative analysis of the 9.12 Gyeongju and 11.15 Pohang earthquakes was conducted in order to provide probable explanations and reasons for the damage observed in the 11.15 Pohang earthquake from both earthquake and structural engineering perspectives. The damage potentials like Arias intensity, effective peak ground acceleration, etc observed in the 11.15 Pohang earthquake were generally weaker than those of the 9.12 Gyeongju earthquake. However, in contrast to the high-frequency dominant nature of the 9.12 Gyeongju earthquake records, the spectral power of PHA2 record observed in the soft soil site was highly concentrated around 2Hz. The base shear around 2 Hz frequency was as high as 40% building weight. This frequency band is very close to the fundamental frequency of the piloti-type buildings severely damaged in the northern part of Pohang. Unfortunately, in addition to inherent vertical irregularity, most of the damaged piloti-type buildings had plan irregularity as well and were non-seismic. All these contributed to the fatal damage. Inelastic dynamic analysis indicated that PHA2 record demands system ductility capacity of 3.5 for a structure with a fundamental period of 0.5 sec and yield base shear strength of 10% building weight. The system ductility level of 3.5 seems very difficult to be achievable in non-seismic brittle piloti-type buildings. The soil profile of the PHA2 site was inversely estimated based on deconvolution technique and trial-error procedure with utilizing available records measured at several rock sites during the 11.15 Pohang earthquake. The soil profile estimated was very typical of soil class D, implying significant soil amplification in the 11.15 Pohang earthquake. The 11.15 Pohang earthquake gave us the expensive lesson that near-collapse damage to irregular and brittle buildings is highly possible when soil is soft and epicenter is close, although the earthquake magnitude is just minor to moderate (M 5+).

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.3
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• pp.120-126
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• 2016

This study was carried out to examine the relationships between seasonal variations of soil $CO_2$ efflux rates and soil environmental factors in matured Pinus densiflora and Quercus variabilis stands in the Wola national experimental forests, southern Korea. Soil $CO_2$ efflux rates were measured monthly from March 2015 to February 2016. Mean soil $CO_2$ efflux rates during the study period were significantly higher in the Q. variabilis ($mean{\pm}standard$ error; $2.27{\pm}0.22{\mu}mol\;m^{-2}s^{-1}$) than in the P. densiflora ($1.63{\pm}0.12{\mu}mol\;m^{-2}s^{-1}$) stands. Mean soil water content and pH were also significantly higher in the Q. variabilis ($26.96{\pm}0.93%$, pH 5.19) than in the P. densiflora ($21.32{\pm}0.89%$, pH 4.87) stands, while soil temperature was not significantly different between the P. densiflora ($13.92{\pm}0.67^{\circ}C$) and in the Q. variabilis ($13.52{\pm}0.70^{\circ}C$) stands. $Q_{10}$ values were higher in the Q. variabilis (3.35) than in the P. densiflora (2.72) stands. The results indicate that soil $CO_2$ efflux rates in Q. variabilis stand could be more sensitive by the change of soil temperature compared with P. densiflora stand under a similar site environmental condition.