• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.19 no.2
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• pp.183-188
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• 2001

Topographic map is important for the additional detailed construction planning followed by slope sliding. It is a base map that is used to compute the volume of soil, the cost of construction, and check the stability in the area of slope sliding. In this study, 3D topographic data were acquired appling softcopy photogrammetry to the dangerous slope, and the method which can transform these data to the same coordinates system as early TM coordinates was designed. There was a problem when the one meter contour line was made by analysing the image taken from the distance three hundred meters. By solving this problem, this could be used as important data for the planning of road expansion construction. It is expected to be useful for the measurement of various dangerous area in civil engineering works.

• Tribology and Lubricants
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• v.36 no.3
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• pp.133-138
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• 2020

In this paper, we present an experimental investigation of the friction coefficient and wear area change of carbon/epoxy and E-glass/epoxy composites depending on the fiber direction (0°/90°). We compared the results of the case where the sliding direction is parallel to the fiber direction (0°) with that of the case where it is perpendicular to the fiber direction (90°). The ball-on-plate wear test equipment was used to cause wear in both directions. Two types of specimens were prepared with thicknesses of 3 mm-one made of carbon fiber reinforced plastic composite (CFRP) and the other of glass fiber reinforced plastic composite (GFRP). A normal force of 20 N was applied to the specimen and the sliding speed was 10 mm/s and the sliding distance was set to 20 m to perform the wear test. The CFRP demonstrates superior tribological characteristics compared to the GFRP. This outcome is attributed to graphitization of carbon, which serves as solid lubricating particles. In addition, both CFRP and GFRP are worn more in the 90° direction than in the 0° direction. This is due to the greater occurrence of fiber breakage and separation in the 90° direction than in the 0° direction. This study is expected to be utilized as basic data for understanding the friction and wear characteristics of CFRP and GFRP composites along the fiber direction and to apply the appropriate material.

• Journal of Korean Society of Steel Construction
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• v.16 no.4 s.71
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• pp.407-414
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• 2004

Bridges in common use are expected to have more varieties of load in their connected members and bolts than in construction. Faults in connection members or bolts occur so often according to the time flow. One of the purposes of this study is to find out the behavior and structural features of high-tension bolted joints with faults that are very difficult and cost much to find out through experimentation with finite element analysis. Another purpose of this study is to provide sufficient data, estimated experimental results, and the scheme of the test plate for an economical experimental study in the future. Surveys of bridges with a variety of faults and statistical classifications of their faults were performed, as was a finite element analysis of the internal stress and the sliding behavior of standard and defective bridge models. The finite element analysis of the internal stress was performed according to the interval of the bolt, the thickness of the plate, the distance of the edge, the diameter of the bolt, and the expansion of the construction. Furthermore, the analysis explained the sliding behavior of high-tension bolt joints and showed the geometric non-linear against the large deformation, and the boundary non-linear against the non-linear in the contact surface, including the material non-linear, to best explain the exceeding of the yield stress by sliding. A normally bolted high-tension bolt joint and deduction of bolt tension were also analyzed with the finite element analysis of bridge-sliding behavior.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.23 no.3
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• pp.215-225
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• 2011

During the past decade, the performance-based design method of caisson breakwaters has been developed, which allows a certain damage while maintaining the function of the structure. However, the existing method does not consider the changing coastal environment due to climate change impacts so that the stability of the structure is not guaranteed over the lifetime of the structure. In this paper, a time-dependent performance-based design method is developed, which is able to estimate the expected sliding distance and the probability of failure of a caisson breakwater considering the influence of sea level rise and wave height increase due to climate change. Especially, time-dependent probability of failure is calculated by considering the sea level rise and wave height increase as a function of time. The developed method was applied to the East Breakwater of the Hitachinaka Port which is located on the east coast of Japan. It was shown that the influence of wave height increase is much greater than that of sea level rise, because the magnitude of sea level rise is negligibly small compared with the water depth at the breakwater site. Moreover, investigation was made for the change of caisson width due to climate change impacts, which is the main concern of harbor engineers. The longer the structure lifetime, the greater was the increase of caisson width. The required increase of caisson width of the Hitachinaka breakwater whose width is 22 m at present was about 0.5 m and 1.5 m respectively for parabolic and linear wave height increase due to climate change.

• Structural Engineering and Mechanics
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• v.61 no.4
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• pp.527-538
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• 2017

The evaluation of the loss-of-support conditions of frictional beam-to-column connections using simplified numerical models describing the transverse response of a portal-like structure is presented in this paper considering the effects of the seismic-hazard disaggregation. Real earthquake time histories selected from European Strong-motion Database (ESD) are used to show the effects of the seismic-hazard disaggregation on the beam loss-of-support conditions. Seismic events are classified according to different values of magnitudes, epicentral distances and soil conditions (stiff or soft soil) highlighting the importance of considering the characteristics of the seismic input in the assessment of the loss-of-support conditions of frictional beam-to-column connections. A rigid and an elastic model of a frame of a precast industrial building (2-DoF portal-like model) are presented and adopted to find the minimum required friction coefficient to avoid sliding. Then, the mean value of the minimum required friction coefficient with an epicentral distance bin of 10 km is calculated and fitted with a linear function depending on the logarithm of the epicentral distance. A complete parametric analysis varying the horizontal and vertical period of vibration of the structure is performed. Results show that the loss-of-support condition is strongly influenced by magnitude, epicentral distance and soil conditions determining the frequency content of the earthquake time histories and the correlation between the maxima of the horizontal and vertical components. Moreover, as expected, dynamic characteristics of the structure have also a strong influence. Finally, the effect of the column nonlinear behavior (i.e. formation of plastic hinges at the base) is analyzed showing that the connection and the column are a series system where the maximum force is limited by the element having the minimum strength. Two different longitudinal reinforcement ratios are analyzed demonstrating that the column strength variation changes the system response.

• The Journal of Korean Society for Radiation Therapy
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• v.18 no.1
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• pp.1-5
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• 2006

Purpose: IMRT quality assurance(Q.A) is consist of the absolute dosimetry using ionization chamber and relative dosimetry using the film. We have in general used 0.015 cc ionization chamber, because small size and measure the point dose. But this ionization chamber is too small to give an accurate measurement value. In this study, we have examined the degree of calculated to measured dose difference in intensity modulated radiotherapy(IMRT) based on the observed/expected ratio using various kinds of ion chambers, which were used for absolute dosimetry. Materials and Methods: we peformed the 6 cases of IMRT sliding-window method for head and neck cases. Radiation was delivered by using a Clinac 21EX unit(Varian, USA) generating a 6 MV x-ray beam, which is equipped with an integrated multileaf collimator. The dose rate for IMRT treatment is set to 300 MU/min. The ion chamber was located 5cm below the surface of phantom giving 100cm as a source-axis distance(SAD). The various types of ion chambers were used including 0.015cc(pin point type 31014, PTW. Germany), 0.125 cc(micro type 31002, PTW, Germany) and 0.6 cc(famer type 30002, PTW, Germany). The measurement point was carefully chosen to be located at low-gradient area. Results: The experimental results show that the average differences between plan value and measured value are ${\pm}0.91%$ for 0.015 cc pin point chamber, ${\pm}0.52%$ for 0.125 cc micro type chamber and ${\pm}0.76%$ for farmer type 0.6cc chamber. The 0.125 cc micro type chamber is appropriate size for dose measure in IMRT. Conclusion: IMRT Q.A is the important procedure. Based on the various types of ion chamber measurements, we have demonstrated that the dose discrepancy between calculated dose distribution and measured dose distribution for IMRT plans is dependent on the size of ion chambers. The reason is small size ionization chamber have the high signal-to-noise ratio and big size ionization chamber is not located accurate measurement point. Therefore our results suggest the 0.125 cc farmer type chamber is appropriate size for dose measure in IMRT.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.1
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• pp.21-30
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• 2017

The surface temperature of disc brakes varies during braking, which can affect the friction and wear behavior of braking systems. In order to develop an efficient braking system, the friction and wear behaviors of brake materials need to be clearly understood. In this work, the friction and wear behavior of the C/C-SiC-Cu composite and the Al/SiC composite, which are used in disc braking systems, were investigated. Both the surface temperature and contact pressure were studied. A pin-on-reciprocating tribotester was used for this purpose, in order to control temperature and load. Results showed that the friction varied significantly with temperature and sliding distance. It was found that a transfer layer of compacted wear debris formed on the wear track of the two materials. These layers caused the surface roughness of the wear track to increase. The outcome of this work is expected to serve as a basis for the development of braking systems under various operating conditions.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.