• Journal of the Institute of Convergence Signal Processing
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• v.23 no.3
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• pp.166-172
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• 2022

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• Journal of Korean Elementary Science Education
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• v.42 no.1
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• pp.17-33
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• 2023

This study examined inservice elementary teachers' thoughts on the development of educational apps by preservice elementary teachers and implications for TPACK education for preservice elementary teachers. A case study was conducted in which preservice elementary teachers developed a science education app, and the three teachers were surveyed for their thoughts regarding this. The results regarding the characteristics of the developed app by preservice teachers were as follows. First, "inquiry" had the highest value among educational goals intended by the preservice teachers. In addition, the scores for tool-type apps and apps in which interaction between learners and instructors occurs were relatively high. Second, most of the preservice teachers developed apps to meet curriculum goals, but their apps showed low-level characteristics in terms of the constructive and cooperative dimensions. The results of the analysis of the thinking of elementary school teachers regarding the education development apps are as follows. First, elementary school teachers assigned the lowest scores to the effectiveness of the apps, and to this problem, the achievement standard with respect to the curriculum and the evaluation and modification activities fir the apps were proposed. Second, the teachers indicated that it would be appropriate to provide the experience of making apps to directly improve the TPACK of preservice teachers. Third, the respondents thought that preservice teachers should develop block coding literacy to create apps using App Inventor. Fourth, the teachers considered it necessary to emphasize simulated instructions, as well as the experience of collecting and handling data through apps to improve preservice teachers' TPACK app development for educational use.

• Journal of the Korean Geotechnical Society
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• v.24 no.6
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• pp.77-84
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• 2008

The existing equations for radial consolidation cannot account for the changes of well resistance with time and cannot predict the appropriate in-situ consolidation curve. In this study, small cylinder cell tests are performed to evaluate the discharge capacity of PVD. Also, a block sample of 1.2 m in diameter and 2.0 m in height was consolidated to observe the change in the drainage capacity with time for three types of PVD. From the test results on a block sample, the drainage curves normalized with initial drainage of each PVD are similar, regardless of the PVD type and the consolidation curve, which is predicted using solutions of radial consolidation based on the discharge capacity measured in a small cylinder cell tests, significantly overestimates the degree of consolidation. The term of well resistance in the radial consolidation solution was back-calculated to fit the consolidation curve of a large block sample and it is defined as the time dependent well resistance factor, L(t). The L(t) was found to be linearly proportional to the dimensionless time factor, Th. It was also shown that the consolidation curve evaluated by using L(t) provides more accurate prediction than the existing solution.

• Journal of the Korean Geotechnical Society
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• v.25 no.12
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• pp.5-12
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• 2009

As rock bolts become one of the main support systems in tunnels and underground structures, the integrity of the rock bolts affects the safety of these structures. The purpose of this study is the evaluation of rock bolt integrity using wavelet transforms of the guided ultrasonic waves by using transmission test in the field. After several rock bolts with various defect ratios are embedded into a large scale concrete block and rock mass, guided waves are generated by a piezo disk element and measured by an acoustic emission (AE) sensor. The captured signals are analyzed in the time-frequency domain using the wavelet transform based on a Gabor wavelet. Peak values in the time-frequency domain represent the interval of travel time of each echo. The energy velocities of the guided waves increase with an increase in the defect ratio. The suitable curing time for the evergy velocity analysis is proposed by the laboratory test, and in-situ tests are performed in two tunnelling sites to verify the applicability of rock bolt integrity tests performed after proposed curing time. This study proves that time-frequency domain analysis is an effective tool for the evaluation of the rock bolt integrity.

• Journal of the Korean Geotechnical Society
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• v.24 no.5
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• pp.65-78
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• 2008

In case of cut-slopes or shallow-depth tunnels, sliding along with discontinuities or rotation could play a critical role in judging stability. Although numerical analysis is widely used to check the stability of these cut-slopes and shallow-depth tunnels in early design process, common analysis programs are based on continuum model. Performing continuum model analysis regarding discontinuities is possible by reducing overall strength of jointed rock mass. It is also possible by applying ubiquitous joint model to Mohr-Coulomb failure criteria. In numerical analysis of cut-slope, main geotechnical properties such as cohesion, friction angle and elastic modulus can be evaluated by empirical equations. This study tried to compare two main systems, RMR and GSI system by applying them to in-situ hazardous cut-slopes. In addition, this study applied ubiquitous joint model to simulation model with inputs derived by RMR and GSI system to compare with displacements obtained by in-situ monitoring. To sum up, numerical analysis mixed with GSI inputs and ubiquitous joint model proved to provide most reliable results which were similar to actual displacements and their patterns.

• Industry Promotion Research
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• v.8 no.2
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• pp.21-27
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• 2023

This study studies the policies and use cases of the government and the financial sector for artificial intelligence, and the future policy tasks of the financial sector. want to derive According to Gartner, noteworthy technologies leading the financial industry in 2022 include 'generative AI', 'autonomous system', 'Privacy Enhanced Computation (PEC) was selected. The financial sector is developing new technologies such as artificial intelligence, big data, and blockchain. Developments are spurring innovation in the financial sector. Data loss due to the spread of telecommuting after the corona pandemic As interests in sharing and personal information protection increase, companies are expected to change in new digital technologies. Global financial companies also utilize new digital technology to develop products or manage and operate existing businesses. I n order to promote process innovation, I T expenses are being expanded. The financial sector utilizes new digital technology to prevent money laundering, improve work efficiency, and strengthen personal information protection. are applying In the era of Big Blur, where the boundaries between industries are disappearing, the competitive edge in the challenge of new entrants In order to preoccupy the market, financial institutions must actively utilize new technologies in their work.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.41 no.1
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• pp.21-34
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• 2023

This study identified the materials and construction methods of 'Old Wall' in 13 villages which were designated as National Registered Cultural Heritage at the time of designation and examined the their structural changes based on field survey. The results are as follows: First, the 'Old Wall' consisted of 10 Soil-Stone Wall and 5 Stone Wall. At the time of designation, Stone Wall, which was built irregularly by dry-construction of natural stones, is similar in shape, but Soil-Stone Wall showed difference by the construction method of making used stones, joints, and faces. Second, the study extracted the changes of 'Old Wall' by repair and examined the changes of construction methods as well as the substitution and addition of materials of structure. The wall-roof was built with cement roof-tile and asbestos slate which have the advantage improve durability and cost-effectiveness. In addition, tile-mouth soil was added to korean traditional roof-tile to prevent rainwater from flowing in. Besides, to improve constructional convenience, the natural stone of the wall-body was replaced with blast stone, float stone and cut stone. Cement block, cement brick and cement mortar were frequently used to repair as well. As Soil-Stone Wall was transformed from irregular pattern-construction to comb pattern-construction and wet-construction was changed to dry-construction, it caused landscape and structural problems. Also, the layer of cement mortar applied to wall-foundation blocked the flow of rainwater that was induced by dry-construction of natural stones. Third, the study regarded that the problem with the repair of 'Old Wall' may occur as it is located in living space, because the owner of the wall could repair for the minor damages without technical knowledge. In addition, it is difficult for repair companies in charge of maintenance of Cultural Heritage to supply local materials, and it is differential construction specifications are not applied.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.3
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• pp.38-46
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• 2023

In this study, a bearing test was performed and analytically evaluated to evaluate the bearing performance according to the application of the aluminum stiffener in round-end concrete. In the bearing strength test, the change in bearing performance due to the aluminum stiffener using the aluminum form for manufacturing concrete with round-end, and the steel anchor bolts for member movement and assembly was confirmed. The FE analysis model was identically configured to the experimental conditions, and the result was compared with the experiment. Also, the crack patterns and stress behavior were confirmed. In addition, the effect of strength change of the aluminum stiffener on the round-end concrete was also evaluated analytically. The bearing strength of the round-end concrete increased by about 20% due to the aluminum stiffener, and it was confirmed that the steel anchor bolt did not affect the bearing strength. The maximum load and crack patterns shown as a result of FE analysis were similar to those of the experiment. As a result of FE analysis according to the strength change of the aluminum stiffener, the maximum load change according to the increase and decrease of the strength of the aluminum stiffener by 10% and 20% was evaluated to have no significant effect at a maximum of about 4% compared to before the strength change.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.343-348
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• 2022

Recently, With the recent rapid development of technology, the amount of data generated by various systems is increasing, and enterprise servers and data centers that have to handle large amounts of big data need to apply high-stability and high-performance storage devices even if costs increase. In such systems, SSD(solid state disk) that provide high performance of read/write are often used as storage devices. However, due to the characteristics of reading and writing on a page-by-page basis, erasing operations on a block basis, and erassing-before-writing, there is a problem that performance is degraded when duplicate writes occur. Therefore, in order to delay this performance degradation problem, over-provision technology of SSD has been applied internally. However, since over-provided technologies have the disadvantage of consuming a lot of storage space instead of performance, the application of inefficient technologies above the right performance has a problem of over-costing. In this paper, we proposed a method of measuring the performance and cost incurred when various over-provisions are applied in an SSD and predicting the system-optimized over-provided ratio based on this. Through this research, we expect to find a trade-off with costs to meet the performance requirements in systems that process big data.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.129-148
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• 2023

Bitcoin is a blockchain technology-based digital currency that has been recognized as a representative cryptocurrency and a financial investment asset. Due to its highly volatile nature, Bitcoin has gained a lot of attention from investors and the public. Based on this popularity, numerous studies have been conducted on price and trend prediction using machine learning and deep learning. This study employed LSTM (Long Short Term Memory) and CNN (Convolutional Neural Networks), which have shown potential for predictive performance in the finance domain, to enhance the classification accuracy in Bitcoin price trend prediction. XAI(eXplainable Artificial Intelligence) techniques were applied to the predictive model to enhance its explainability and interpretability by providing a comprehensive explanation of the model. In the empirical experiment, CNN was applied to technical indicators and Google trend data to build a Bitcoin price trend prediction model, and the CNN model using both technical indicators and Google trend data clearly outperformed the other models using neural networks, SVM, and LSTM. Then SHAP(Shapley Additive exPlanations) was applied to the predictive model to obtain explanations about the output values. Important prediction drivers in input variables were extracted through global interpretation, and the interpretation of the predictive model's decision process for each instance was suggested through local interpretation. The results show that our proposed research framework demonstrates both improved classification accuracy and explainability by using CNN, Google trend data, and SHAP.