• Journal of Biosystems Engineering
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• v.3 no.2
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• pp.34-34
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• 1978

To find out the power tiller's travel and tractive characteristics on the general slope land, the tractive p:nver transmitting system was divided into the internal an,~ external power transmission systems. The performance of power tiller's engine which is the initial unit of internal transmission system was tested. In addition, the mathematical model for the tractive force of driving wheel which is the initial unit of external transmission system, was derived by energy and force balance. An analytical solution of performed for tractive forces was determined by use of the model through the digital computer programme. To justify the reliability of the theoretical value, the draft force was measured by the strain gauge system on the general slope land and compared with theoretical values. The results of the analytical and experimental performance of power tiller on the field may be summarized as follows; (1) The mathematical equation of rolIing resistance was derived as $$Rh=\frac {W_z-AC \[1+ \frac{sl}{K} \(\varrho ^{-\frac{sl}{K}-1\)\] sin\theta_1}} {tan\phi \[1+ \frac{sl}{K} \(\varrho ^{-\frac{sl}{K}-1\)\]+\frac{tan\theta_1}{1}$$ and angle of rolling resistance as $$\theta _1 - tan^1\[ \frac {2T(AcrS_0 - T)+\sqrt (T-AcrS_0)^2(2T)^2-4(T^2-W_2^2r^2)\times (T-AcrS_0)^2 W_z^2r^2S_0^2tan^2\phi} {2(T^2-W_z^2r^2)S_0tan\phi}\] $$and the equation of frft force was derived as$$P=(AC+Rtan\phi)\[1+ \frac{sl}{K} \(\varrho ^{-\frac{sl}{K}-1\)\]cos\phi_1 ? \frac {W_z ?{AC\[ [1+ \frac{sl}{K} \(\varrho ^{-\frac{sl}{K}-1\)\]sin\phi_1 {tan\phi[1+ \frac{sl}{K} \(\varrho ^{-\frac{sl}{K}-1\]+ \frac {tan\phi_1} { 1} ? W_1sin\alpha $$The slip coefficient K in these equations was fitted to approximately 1. 5 on the level lands and 2 on the slope land. (2) The coefficient of rolling resistance Rn was increased with increasing slip percent 5 and did not influenced by the angle of slope land. The angle of rolling resistance Ol was increasing sinkage Z of driving wheel. The value of Ol was found to be within the limits of Ol =2? "'16?. (3) The vertical weight transfered to power tiller on general slope land can be estim ated by use of th~ derived equation: $$R_pz= \frac {\sum_{i=1}^{4}{W_i}} {l_T} { (l_T-l) cos\alpha cos\beta ? \bar(h) sin \alpha - W_1 cos\alpha cos\beta$$The vertical transfer weight $R_pz$ was decreased with increasing the angle of slope land. The ratio of weight difference of right and left driving wheel on slop eland,$\lambda= \frac { {W_L_Z} - {W_R_Z}} {W_Z} $, was increased from ,$\lambda$=0 to$\lambda$=0.4 with increasing the angle of side slope land ($\beta = 0^\circ~20^\circ) (4) In case of no draft resistance, the difference between the travelling velocities on the level and the slope land was very small to give 0.5m/sec, in which the travelling velocity on the general slope land was decreased in curvilinear trend as the draft load increased. The decreasing rate of travelling velocity by the increase of side slope angle was less than that by the increase of hill slope angle a, (5) Rate of side slip by the side slope angle was defined as $ S_r=\frac {S_s}{l_s} \times$ 100( %), and the rate of side slip of the low travelling velocity was larger than that of the high travelling velocity. (6) Draft forces of power tiller did not affect by the angular velocity of driving wheel, and maximum draft coefficient occurred at slip percent of S=60% and the maximum draft power efficiency occurred at slip percent of S=30%. The maximum draft coefficient occurred at slip percent of S=60% on the side slope land, and the draft coefficent was nearly constant regardless of the side slope angle on the hill slope land. The maximum draft coefficient occurred at slip perecent of S=65% and it was decreased with increasing hill slope angle $\alpha$. The maximum draft power efficiency occurred at S=30 % on the general slope land. Therefore, it would be reasonable to have the draft operation at slip percent of S=30% on the general slope land. (7) The portions of the power supplied by the engine of the power tiller which were used as the source of draft power were 46.7% on the concrete road, 26.7% on the level land, and 13~20%; on the general slope land ($\alpha = O~ 15^\circ ,\beta = 0 ~ 10^\circ$) , respectively. Therefore, it may be desirable to develope the new mechanism of the external pO'wer transmitting system for the general slope land to improved its performance.

• Journal of Biomedical Engineering Research
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• v.25 no.5
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• pp.403-414
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• 2004

In the accompanying paper, we proposed a real. time volumetric imaging method using a cross array based on receive dynamic focusing and synthetic aperture focusing along lateral and elevational directions, respetively. But synthetic aperture methods using spherical waves are subject to beam spreading with increasing depth due to the wave diffraction phenomenon. Moreover, since the proposed method uses only one element for each transmission, it has a limited transmit power. To overcome these limitations, we propose a new real. time volumetric imaging method using cross arrays based on synthetic aperture technique with linear wave fronts. In the proposed method, linear wave fronts having different angles on the horizontal plane is transmitted successively from all transmit array elements. On receive, by employing the conventional dynamic focusing and synthetic aperture methods along lateral and elevational directions, respectively, ultrasound waves can be focused effectively at all imaging points. Mathematical analysis and computer simulation results show that the proposed method can provide uniform elevational resolution over a large depth of field. Especially, since the new method can construct a volume image with a limited number of transmit receive events using a full transmit aperture, it is suitable for real-time 3D imaging with high transmit power and volume rate.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.4
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• pp.126-138
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• 2017

Recently, the national interest in environment is increasing and for dealing with water environment-related issues swiftly and accurately, the demand to facilitate the analysis of water environment data using a GIS is growing. To meet such growing demands, a spatial network data-based stream network analysis map(Korean Reach File; KRF) supporting spatial analysis of water environment data was developed and is being provided. However, there is a difficulty in delineating catchment areas, which are the basis of supplying spatial data including relevant information frequently required by the users such as establishing remediation measures against water pollution accidents. Therefore, in this study, the development of a computer program was made. The development process included steps such as designing a delineation method, and developing an algorithm and modules. DEM(Digital Elevation Model) and FDR(Flow Direction) were used as the major data to automatically delineate catchment areas. The algorithm for the delineation of catchment areas was developed through three stages; catchment area grid extraction, boundary point extraction, and boundary line division. Also, an add-in catchment area delineation module, based on ArcGIS from ESRI, was developed in the consideration of productivity and utility of the program. Using the developed program, the catchment areas were delineated and they were compared to the catchment areas currently used by the government. The results showed that the catchment areas were delineated efficiently using the digital elevation data. Especially, in the regions with clear topographical slopes, they were delineated accurately and swiftly. Although in some regions with flat fields of paddles and downtowns or well-organized drainage facilities, the catchment areas were not segmented accurately, the program definitely reduce the processing time to delineate existing catchment areas. In the future, more efforts should be made to enhance current algorithm to facilitate the use of the higher precision of digital elevation data, and furthermore reducing the calculation time for processing large data volume.

• The Journal of Korean Academy of Prosthodontics
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• v.50 no.4
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• pp.271-278
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• 2012

Purpose: Recently implant surgical guides were used for accurate and atraumatic operation. In this study, the accuracy of two different types of surgical guides, positioning device fabricated and stereolithography fabricated surgical guides, were evaluated in four different types of tooth loss models. Materials and methods: Surgical guides were fabricated with stereolithography and positioning device respectively. Implants were placed on 40 models using the two different types of surgical guides. The fitness of the surgical guides was evaluated by measuring the gap between the surgical guide and the model. The accuracy of surgical guide was evaluated on a pre- and post-surgical CT image fusion. Results: The gap between the surgical guide and the model was $1.4{\pm}0.3mm$ and $0.4{\pm}0.3mm$ for the stereolithography and positioning device surgical guide, respectively. The stereolithography showed mesiodistal angular deviation of $3.9{\pm}1.6^{\circ}$, buccolingual angular deviation of $2.7{\pm}1.5^{\circ}$ and vertical deviation of $1.9{\pm}0.9mm$, whereas the positioning device showed mesiodistal angular deviation of $0.7{\pm}0.3^{\circ}$, buccolingual angular deviation of $0.3{\pm}0.2^{\circ}$ and vertical deviation of $0.4{\pm}0.2mm$. The differences were statistically significant between the two groups (P<.05). Conclusion: The laboratory fabricated surgical guides using a positioning device allow implant placement more accurately than the stereolithography surgical guides in dental clinic.

• The Journal of Korean Academy of Prosthodontics
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• v.45 no.6
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• pp.753-759
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• 2007

Statement of problem. In distal extension removable partial denture, the preservation of health of abutment teeth is very important, but abutment teeth are subjected to unfavorable stress under unilateral loading specially. Purpose. The purpose of this study was to investigate the biomechanical effects of mandibular removable partial dentures with various prosthetic designs under unilateral loading, using strain gauge analysis. Material and methods. Artificial teeth of both canines were anchored bilaterally in a mandibular edentulous model made of resin. Bilateral distal extension removable partial dentures with splinted and unsplinted abutments were fabricated. Group 1: Clasp-retained mandibular removable partial denture with unsplinted abutments Group 2: Clasp-retained mandibular removable partial denture with splinted abutments by 6-unit bridge. Group 3: Bar-retained mandibular removable partial denture Strain gauges were bonded on the labial plate of the mandibular resin model, approximately 2 mm dose to the abutments. Two unilateral vertical experimental loadings (30N and 100N) were applied subsequently via miniature load cell that were placed at mandibular left first molar region. Strain measurements were performed and simultaneously monitored from a computer connected to data acquisition system. For within-group evaluations, t-test was used to compare the strain values and for between-group comparisons, a one-way analysis of variance (ANOVA) was used and Tukey test was used as post hoc comparisons. Results. The strain values of group 1 and 2 were tensile under loadings. In contrast, strain values of group 3 were compressive in nature. Strain values increased as the applied load in increased from 30N to 100N (p<.05) except for right side in group 1. Under 30N loading, in left side, group 1 showed higher strain values than groups 2 and 3 in absolute quantity (p<.05). And group 2 showed higher strain values than group 1 (p<.05). In right side, group 1 and 2 showed higher strain values than group 3 in absolute quantity (p<.05). Under 100N loading in left side, group 1 showed higher strain values than groups 2 and 3 in absolute quantity (p<.05). And group 2 showed higher strain values than group 1 (p<.05). In right side, group 1 and 2 showed higher strain values than group 3 in absolute quantity (p<.05). Under 30N loading, group 2 and 3 showed higher strain values in right side than in left side. Under 100N loading, right side strain values were higher than left side ones for all groups. Conclusion. Splinting of two isolated abutments by bridge reduced the peri-abutment strain in comparison with unsplinted abutments under unilateral loading. Bar-retained removable partial denture showed the lowest strain of three groups, and compressive nature.

• Korean Journal of Agricultural Science
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• v.22 no.1
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• pp.1-10
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• 1995

All agricultural crops and products should be cultured, harvested, handled and processed by the proper mechanical methods in the mechanized farming systems. Agricultural crops might be injured or deformed through various working stages due to static or dynamic forces of machines. Mechanical forces had to be applied with proper degrees to the agricultural crops in incoincidence with properties of crops without any damage of crops so as to increase the work efficiency qualitatively. Knowledges of mechanical properties of agricultural materials are essential to prevent of agricultural crops in relation with mechanical farming system. This study was carried out to examine and analyze the creep behavior of the rice stalk on growing and harvesting periods by mechanical model with computer measurement system in radial directional compressive force and bending force. The creep behavior of the rice stalk could be predicted precisely and its results approached closely to the measured values. The creep behaviors were increased greatly with increase of compressive force, namely, the steady state creep behavior occurred at the force less then 25N and the logarithmic creep behavior at the force bigger than 30N. The instantaneous elastic modulus $E_o$ and the retardation time ${\tau}_K$ were increased together with increase of applied forces, meanwhile the retarded elastic modulus $E_r$ and viscosity ${\eta}_v$ were decreased with increase of applied forces in mechanical model being expected the creep behavior in relation with the level of applied forces, which was well explained that the rice stalk might be visvo-elastic material. In the creep test along the stalk portion with compressive force and bending force, the intermediate portion showed greatest values and also the lower portion showed the least values, which implied that the intermediate portions of rice stalk were very weak. The steady state creep behavior occured at the intermediate portion and the upper portion in the rice stalk at the compressive force larger than 25.0N, which showed the possibility of injury due to external forces.

• 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.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.2
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• pp.1-22
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• 2022

The modification effects of street trees on outdoor thermal comfort in summertime according to tree planting types and road direction were analyzed using a computer simulation program, ENVI-met. With trees, the air temperature and wind speed decreased, and the relative humidity increased. In the case of mean radiant temperature (T_mrt) and human thermal sensation, physiological equivalent temperature (PET) and universal thermal climate index (UTCI), there was a decrease during the daytime. The greatest change among the meteorological factors by trees happened in Tmrt, and PET and UTCI showed similar patterns with T_mrt·The most effective tree planting type on thermal comfort modification was low tree height, wide tree crown, high leaf area index, and narrow planting interval (LWDN). T_mrt, PET and UTCI showed a large difference depending on shadow patterns of buildings and trees according to solar altitude and azimuth angles, and building locations. When the building shade areas increased, the thermal modification effect by trees decreased. In particular, results on the east and west sidewalks showed a large deviation over time. When applying the LWDN, the northwest, west and southwest sidewalks showed a significant reduction of 8.6-12.3℃ PET and 4.2-4.5℃ UTCI at 10:00, and the northeast, east and southeast sidewalks showed 8.1-11.8℃ PET and 4.4-5.0℃ UTCI at 16:00. On the other hand, when the least effective type (high tree height, narrow tree crown, low leaf area index, and wide planting interval) was applied, the maximum reduction was up to 1.8℃ PET and 0.9℃ UTCI on the eastern sidewalks, and up to 3.0℃ PET and 0.9℃ UTCI on the western ones. In addition, the difference in modification effects on T_mrt, PET and UTCI between the tree planting types was not significant when the tree effects were reduced by the effects of buildings. These results can be used as basic data to make the most appropriate street tree planting model for thermal comfort improvement in urban areas in summer.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.27 no.3
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• pp.127-143
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• 2022

Recently, many attempts to run numerical ocean models in cloud computing environments have been tried actively. A cloud computing environment can be an effective means to implement numerical ocean models requiring a large-scale resource or quickly preparing modeling environment for global or large-scale grids. Many commercial and private cloud computing systems provide technologies such as virtualization, high-performance CPUs and instances, ether-net based high-performance-networking, and remote direct memory access for High Performance Computing (HPC). These new features facilitate ocean modeling experimentation on commercial cloud computing systems. Many scientists and engineers expect cloud computing to become mainstream in the near future. Analysis of the performance and features of commercial cloud services for numerical modeling is essential in order to select appropriate systems as this can help to minimize execution time and the amount of resources utilized. The effect of cache memory is large in the processing structure of the ocean numerical model, which processes input/output of data in a multidimensional array structure, and the speed of the network is important due to the communication characteristics through which a large amount of data moves. In this study, the performance of the Regional Ocean Modeling System (ROMS), the High Performance Linpack (HPL) benchmarking software package, and STREAM, the memory benchmark were evaluated and compared on commercial cloud systems to provide information for the transition of other ocean models into cloud computing. Through analysis of actual performance data and configuration settings obtained from virtualization-based commercial clouds, we evaluated the efficiency of the computer resources for the various model grid sizes in the virtualization-based cloud systems. We found that cache hierarchy and capacity are crucial in the performance of ROMS using huge memory. The memory latency time is also important in the performance. Increasing the number of cores to reduce the running time for numerical modeling is more effective with large grid sizes than with small grid sizes. Our analysis results will be helpful as a reference for constructing the best computing system in the cloud to minimize time and cost for numerical ocean modeling.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.171-187
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• 2023

When a person's face is recognized through a recording device such as a low-pixel surveillance camera, it is difficult to capture the face due to low image quality. In situations where it is difficult to recognize a person's face, problems such as not being able to identify a criminal suspect or a missing person may occur. Existing studies on face recognition used refined datasets, so the performance could not be measured in various environments. Therefore, to solve the problem of poor face recognition performance in low-quality images, this paper proposes a method to generate high-quality images by performing image quality improvement on low-quality facial images considering various environments, and then improve the performance of facial feature point detection. To confirm the practical applicability of the proposed architecture, an experiment was conducted by selecting a data set in which people appear relatively small in the entire image. In addition, by choosing a facial image dataset considering the mask-wearing situation, the possibility of expanding to real problems was explored. As a result of measuring the performance of the feature point detection model by improving the image quality of the face image, it was confirmed that the face detection after improvement was enhanced by an average of 3.47 times in the case of images without a mask and 9.92 times in the case of wearing a mask. It was confirmed that the RMSE for facial feature points decreased by an average of 8.49 times when wearing a mask and by an average of 2.02 times when not wearing a mask. Therefore, it was possible to verify the applicability of the proposed method by increasing the recognition rate for facial images captured in low quality through image quality improvement.