• Korean Journal of Construction Engineering and Management
• /
• v.23 no.6
• /
• pp.30-42
• /
• 2022

OSC is a type of supply chain and value chain that spans the entire process of construction production (planning, design, construction, maintenance, etc.). It is a method of producing the final object by manufacturing it in a factory, transporting it to the site, installing and construction. This research as is the construction cost was compared for each case A, which applied the PC method, and case B, which applied the RC method. In the case of applying the PC method (excluding the PC design cost), compared to the case where only the RC method was applied, the frame construction cost per unit quantity (m³) increased by about 70% (50% based on the total RC construction type). Of the total frame construction cost of PC method application, PC accounted for 90.2%, 'PC manufacturing cost' 54.8%, 'PC assembly cost' 28.5%, and 'transportation cost' accounted for 6.89%. Also a decision-making framework that can consider both costs and benefits was established. In the case of benefits, the construction period, defect repair, disaster occurrence, energy efficiency, noise/dust/waste, and greenhouse gas emission indicators reflecting OSC technical advantages were presented. It can contribute to providing a basis for helping decision-making on the introduction of PC apartment houses using OSC.

• Journal of the Korean Geosynthetics Society
• /
• v.21 no.2
• /
• pp.57-65
• /
• 2022

This study simulated the shock wave propagation through the tamping material between explosives and hole wall at blasting works and verified the effect of tamping materials. The Arbitrary Lagrangian-Eulerian(ALE) method was selected to model the mixture of solid (Lagrangian) and fluid (Eulerian). The time series analysis was carried out during blasting process time. Explosives and tamping materials (air or water) were modeled with finite element mesh and the hole wall was assumed as a rigid body that can determine the propagation velocity and shock force hitting the hole wall from starting point (explosives). The numerical simulation results show that the propagation velocity and shock force in case of water were larger than those in case of air. In addition, the real site at blasting work was modeled and simulated. The rock was treated as elasto-plastic material. The results demonstrate that the instantaneous shock force was larger and the demolished block size was smaller in water than in air. On the contrary, the impact in the back side of explosives hole was smaller in water, because considerable amount of shock energy was used to demolish the rock, but the propagation of compression through solid becomes smaller due to the damping effect by rock demolition. Therefore, It can be proven that the water as the tamping media was more profitable than air.

• Smart Media Journal
• /
• v.11 no.10
• /
• pp.65-75
• /
• 2022

Deep learning is used as a creative tool that could overcome the limitations of existing analysis models and generate various types of results such as text, image, and music. In this paper, we propose a method necessary to preprocess audio data using the Niko's MIDI Pack sound source file as a data set and to generate music using Bi-LSTM. Based on the generated root note, the hidden layers are composed of multi-layers to create a new note suitable for the musical composition, and an attention mechanism is applied to the output gate of the decoder to apply the weight of the factors that affect the data input from the encoder. Setting variables such as loss function and optimization method are applied as parameters for improving the LSTM model. The proposed model is a multi-channel Bi-LSTM with attention that applies notes pitch generated from separating treble clef and bass clef, length of notes, rests, length of rests, and chords to improve the efficiency and prediction of MIDI deep learning process. The results of the learning generate a sound that matches the development of music scale distinct from noise, and we are aiming to contribute to generating a harmonistic stable music.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.29 no.6D
• /
• pp.761-770
• /
• 2009

The energy efficiency and environment-friendly aspect of the railway system would be superior to other on-land ransportation systems. In a preliminary feasibility study stage and selection of optimal railway route, the energy efficiency and problems related to environment are usually considered. For the selection of optimal railway route, geographical features and facility of management are generally considered. Environment effect factors for the selection of environment-friendly railway router are focused and studied in this paper. In this study, various analysis of opinion of specialists (railway, environment, transport, urban planning, survey) and the guideline for construction of environment-friendly railway were accomplished. From these results of various analysis, 7 major categories (topography/geology, flora and fauna, Nature Property, air quality, water quality, noise/vibration, visual impact/cultural assets) were extracted. To select environment friendly railway route, many alternatives should be compared optimal route must be selected by a comprehensive assessment considering these 7 categories. To solve this problem, the selected method was AHP which simplifies the complex problems utilizing hierarchy, quantifying qualitative problems through 1:1 comparison, and extracting objective conclusions by maintaining consistency. As a result, a GUIbased program was developed which provides basic values of weighted parameters of each category defined by specialists, and a quantification of detailed assessment guidelines to ensures consistency.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.29 no.5B
• /
• pp.473-482
• /
• 2009

This study numerically discusses wave forces acting on a vertical wall such as breakwaters or revetments, subjected to incident undular or turbulent bores. Due to the complex hydrodynamics of bore, its wave forces have been predicted, mainly through laboratory experiments. Numerical simulations in this paper were carried out by CADMAS-SURF(CDIT, 2001), which is based on Navier-Stokes momentum equations and VOF method (Hirt and Nichols, 1981) for tracking free water surface. Its original source code was also partly revised to generate bore in the numerical water channel. Numerical raw data computed by CADMAS-SURF included great strong spike phenomena that show the abrupt jumps of wave loads. To resolve this undesired noise of raw data, the band-pass filter with the frequency of 5Hz was utilized. The filtered results showed reasonable agreements with the experimental results performed by Matsutomi (1991) and Ramsden (1996). It was confirmed that CADMASSURF can be applied to the design of coastal structures against tsunami bores. In addition, the transformation process and propagation speed of bores in the same 2-d water channel were discussed by the variations of water level for time and space. The numerical results indicated that the propagation speed of bore was changed due to the nonlinear interactions between negative and reflected waves.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.29 no.4
• /
• pp.389-394
• /
• 2023

In recent years, use of machine automation is rising in the industry. Ships also obtain machine condition information from sensor as digital information. However, on ships, crew members regularly surveil the engine room to check the condition of equipment and their information through analog gauges. This is a time-consuming and tedious process and poses safety risks to the crew while on surveillance. To address this, engine room surveillance using an autonomous mobile robot is being actively explored as a solution because it can reduce time, costs, and the safety risks for crew. Analog gauge reading using an autonomous mobile robot requires digitization for the robot to recognize the gauge value. In this study, image processing techniques were applied to achieve this. Analog gauge images were subjected to image preprocessing to remove noise and highlight their features. The center point, indicator point, minimum value and maximum value of the analog gauge were detected through image processing. Through the straight line connecting these points, the angle from the minimum value to the maximum value and the angle from the minimum value to indicator point were obtained. The obtained angle is digitized as the value currently indicated by the analog gauge through a formula. It was confirmed from the experiments that the digitization of the analog gauge using image processing was successful, indicating the equivalent current value shown by the gauge. When applied to surveillance robots, this algorithm can minimize safety risks and time and opportunity costs of crew members for engine room surveillance.

• Journal of the Korea Society of Computer and Information
• /
• v.28 no.10
• /
• pp.67-76
• /
• 2023

Although deep learning models are making innovative achievements in the field of computer vision, the problem of vulnerability to adversarial examples continues to be raised. Adversarial examples are attack methods that inject fine noise into images to induce misclassification, which can pose a serious threat to the application of deep learning models in the real world. In this paper, we propose a model that detects adversarial examples using differences in predictive values between edge-learned classification models and underlying classification models. The simple process of extracting the edges of the objects and reflecting them in learning can increase the robustness of the classification model, and economical and efficient detection is possible by detecting adversarial examples through differences in predictions between models. In our experiments, the general model showed accuracy of {49.9%, 29.84%, 18.46%, 4.95%, 3.36%} for adversarial examples (eps={0.02, 0.05, 0.1, 0.2, 0.3}), whereas the Canny edge model showed accuracy of {82.58%, 65.96%, 46.71%, 24.94%, 13.41%} and other edge models showed a similar level of accuracy also, indicating that the edge model was more robust against adversarial examples. In addition, adversarial example detection using differences in predictions between models revealed detection rates of {85.47%, 84.64%, 91.44%, 95.47%, and 87.61%} for each epsilon-specific adversarial example. It is expected that this study will contribute to improving the reliability of deep learning models in related research and application industries such as medical, autonomous driving, security, and national defense.

• KIPS Transactions on Software and Data Engineering
• /
• v.12 no.10
• /
• pp.455-460
• /
• 2023

Text augmentation is a methodology that creates new augmented texts by transforming or generating original texts for the purpose of improving the performance of NLP models. However existing text augmentation techniques have limitations such as lack of expressive diversity semantic distortion and limited number of augmented texts. Recently text augmentation using large language models and few-shot learning can overcome these limitations but there is also a risk of noise generation due to incorrect generation. In this paper, we propose a text augmentation method called TAGS that generates multiple candidate texts and selects the appropriate text as the augmented text. TAGS generates various expressions using few-shot learning while effectively selecting suitable data even with a small amount of original text by using contrastive learning and similarity comparison. We applied this method to task-oriented chatbot data and achieved more than sixty times quantitative improvement. We also analyzed the generated texts to confirm that they produced semantically and expressively diverse texts compared to the original texts. Moreover, we trained and evaluated a classification model using the augmented texts and showed that it improved the performance by more than 0.1915, confirming that it helps to improve the actual model performance.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.16 no.6
• /
• pp.454-464
• /
• 2023

This paper proposes a low-power 8-bit asynchronous SAR ADC with a sampling rate of 1 MS/s for sensor node applications. The ADC uses bootstrapped switches to improve linearity and applies a VCM-based CDAC switching technique to reduce the power consumption and area of the DAC. Conventional synchronous SAR ADCs that operate in synchronization with an external clock suffer from high power consumption due to the use of a clock faster than the sampling rate, which can be overcome by using an asynchronous SAR ADC structure that handles internal comparisons in an asynchronous manner. In addition, the SAR logic is designed using dynamic logic circuits to reduce the large digital power consumption that occurs in low resolution ADC designs. The proposed ADC was simulated in a 180-nm CMOS process, and at a 1.8 V supply voltage and a sampling rate of 1 MS/s, it consumed 46.06 𝜇W of power, achieved an SNDR of 49.76 dB and an ENOB of 7.9738 bits, and obtained a FoM of 183.2 fJ/conv-step. The simulated DNL and INL are +0.186/-0.157 LSB and +0.111/-0.169 LSB.

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