• Journal of Service Research and Studies
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• v.12 no.3
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• pp.158-175
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• 2022

This study discusses mass unemployment and job insecurity due to the 4th industrial revolution and technological progress. In particular, the construction automation service method can contribute to increasing work productivity, preventing on-site safety accidents, and enhancing the competitiveness of the construction industry according to rapid development and convergence between technologies. However, there is great concern that the position of workers will decrease and the income distribution will deteriorate. Therefore, this study is necessary to alleviate the anxiety of the labor market and to find a direction for the government and all walks of life to ponder. To carry out this study, in-depth interviews were conducted with two experts currently engaged in the construction field, and through analysis, we intend to derive meaning and identify current trends, identify necessary improvement measures and institutional areas and suggest research directions. As a result of the analysis, it is possible to suggest a response strategy in a total of three themes: purpose, implication, and strategy. Based on this, there are response strategies in four areas: (1) industrial site response, (2) worker response, (3) education, and (4) training response, and government and corporate response. Through this study, it is necessary to revitalize economic and sociological discussions in the future so that the improvement in productivity and efficiency of society as a whole due to technological innovation of construction automation services does not lead to social problems such as an increase in the unemployment rate and a decrease in jobs in the labor market.

• Journal of the Korean Geotechnical Society
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• v.22 no.11
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• pp.89-99
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• 2006

The PCRW (Precast Concrete Retaining Wall) has many advantages compared with cast in place concrete retaining wall : shorter construction period, excellency of quality and minimum interference with the adjacent structure and traffics. However, shallow foundation type of PCRW, which has comparatively better ground condition, has some disadvantages such as difficulty in transportation and higher cost due to the size of PCRW being expanded by resisting only with self-weight if there is no other supplementary reinforcement. The presented study, in order to complement such disadvantages of PCRW, have applied the micropile method. The micropile method has advantages like low-cost and high-efficiency and does not require huge space, because it can be executed with small size equipment. However, the mechanical behavior characteristics of the PCRW reinforced by micropile, which is installed to improve the reinforcement effect, is not yet clearly identified and there is no suggested standard as to the length, diameter, install angle and install position of micropiles. Hence, this method is yet being designed depend on engineer's experience. In this study, various laboratory model tests as to sliding and overturning were performed in order to identify and present the optimum type of reinforcement and reinforcement effect of the PCRW reinforced by micropiles. In addition, it also executed numerical analysis for the purpose of verifying the optimum type of reinforcement for micropiles based on the results of laboratory model tests. The optimum reinforcement type of micropiles was estimated by model test and numerical analysis. The length of micropiles is 0.4 times wall height and the diameter is 0.04 times wall length.

• Journal of the Korean Recycled Construction Resources Institute
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• v.11 no.2
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• pp.130-137
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• 2023

This study analyzed the effect of mixing order on the flowability, compressive strength, and flexural strength of cement composites reinforced with polyvinyl alcohol(PVA) fibers and multi-walled carbon nanotubes(MWCNTs). The experimental results showed that the addition of CNTs significantly reduced the flowability, and the flowability was considerably affected by the mixing order when CNTs were added. The compressive strength was most effectively improved when water and CNTs solution were mixed first before adding PVA fibers, and the flexural strength was highest when water and CNTs solution were mixed with PVA fibers after dry mixing. However, there was no clear correlation between the flexural toughness and the mixing order. In addition, scanning electron microscopy(SEM) image analysis was conducted to analyze the microstructure. The SEM images showed that CNTs were randomly dispersed through the specimens and contributed to the strength improvement, but the effect of the mixing order was not clearly observed. The main results of this study are expected to be useful for evaluations of workability and material performance of PVA fiber-reinforced cement composites with CNTs.

• Korean Journal of Heritage: History & Science
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• v.56 no.1
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• pp.6-19
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• 2023

As data management and intelligence capability become proxy indicators of national power, the risk provoked by high depending on digital technology ironically increases. The quicker the changes come to be, the more important digitizing existing data and management of digital data are. The management of archaeological data could not be exceptional. It has to be performed in a more comprehensive, systematic and rapid manner. In order to perform the task, the nature of archaeological data contained in the digital archive should be properly recognized in advance: the primary data are generated by excavation as a process destroying their sources, the data are enormous in type and quantity, including long-term and various human experience, and the natural extinction of primary data in handwritten form is likely to be more crucial than in any other discipline. These characteristics of archaeological data unimaginably devastated the possibility of recovering archives, when we face a digital dark age. Considering both recent trend and the nature of archaeological data mentioned above, we can derive strategies for building a sustainable archaeological digital archive. As an archaeology-major consumer of the digital data, I propose four strategic considerations: ① establishing a system of digital data literacy; ② enhancing evaluation and capability of data reuse; ③ building an international data sharing system; ④ developing it into the platform for digital archaeology.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3B
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• pp.305-313
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• 2010

River restoration or rehabilitation should be conducted in a way to maximize the channel stability with natural river configuration close to the equilibrium condition considering divers aspects of fluvial hydraulics, erosion and sedimentation, fluvial geomorphology, and ecological environment and to minimize the maintenance work. Therefore, the channel stability evaluation for present condition based on the equilibrium channel concept should be preceded for the river restoration project. Methods for equilibrium channel theory have generally been developed following either analytical regime theory or empirical regime theory. The main purpose of this paper is to evaluate the stability of present channel condition for the section of abandoned channel restoration in Cheongmi Stream using the Stable channel Analytical Model (SAM) and equilibrium hydraulic geometry equations. The results of analytical and empirical regime theories should provide fundamental and essential information to design the stable channel geometry. As a calculation result of Copeland's method for the study reach, the equilibrium channel has a narrower channel width, deeper water depth, and more gentle slope than the present channel geometry. As results of equilibrium hydraulic geometry equations, predicted equilibrium widths are less than the channel width in the field. It is represented that the current bed slope must be gentle to reach the equilibrium condition according to the results of Julien and Wargadalam method.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5C
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• pp.293-301
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• 2008

Soil profiling is one of the most important work among geotehnical engineering practice. Generally, soil profile is estimated from the observation of soil samples during subsurface exploration but such estimation also includes some experiencing aspects such as flushed water from the borehole, slime colour, boring speed and so on. In addition, since the capacity of hydraulic drill rig is significantly increased, thin layers might be easily missed. So, continuous soil profile is almost impossible over all depth to be bored from conventional subsurface exploration. While CPT or CPTu can serve continuous soil profile information over all depth generally in 5cm interval. Many charts or methods for soil profile from CPT result have been proposed during last several decades over the world. However they have not been verified in local ground condition in Korea. In this research, CPT results and soil classification results based on USCS were compiled from 17 sites over the Korea. Soil classification results by using 7 CPT soil classification charts were compared with those of USCS for the compiled database. Most proper CPT soil classification chart for Korean soil characteristics was evaluated and effective parameters for the soil classification from CPT were discussed. Finally interrelationship between CPT soil classification chart and USCS soil classification was evaluated.

• Journal of the Korea Computer Graphics Society
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• v.29 no.3
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• pp.69-77
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• 2023

This study proposes a rigid-body tracking based virtual avatar application method to increase the social presence and provide various experiences of virtual reality(VR) users in an immersive virtual environment. The proposed method estimates the motion of a virtual avatar through inverse kinematics based on real-time rigid-body tracking based on motion capture using markers. Through this, it aims to design a highly immersive virtual environment with simple object manipulation in the real world. Science experiment educational contents are produced to experiment and analyze applications related to immersive virtual environments through virtual avatars. In addition, audiovisual education, full-body tracking, and the proposed rigid-body tracking method were compared and analyzed through survey. In the proposed virtual environment, participants wore VR HMDs and conducted a survey to confirm immersion and educational effects from virtual avatars performing experimental educational actions from estimated motions. As a result, through the method of utilizing virtual avatars based on rigid-body tracking, it was possible to induce higher immersion and educational effects than traditional audiovisual education. In addition, it was confirmed that a sufficiently positive experience can be provided without much work for full-body tracking.

• The Journal of Bigdata
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• v.7 no.1
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• pp.15-27
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• 2022

In the past five years, the fatality rate of single-vehicle accidents has been 4.7 times higher than that of all accidents, so it is necessary to establish a system that can detect and respond to single-vehicle accidents immediately. The IoT(Internet of Thing)-based real-time traffic accident recognition system proposed in this study is as following. By attaching an IoT sensor which detects the impact and vehicle ingress to the guardrail, when an impact occurs to the guardrail, the image of the accident site is analyzed through artificial intelligence technology and transmitted to a rescue organization to perform quick rescue operations to damage minimization. An IoT sensor module that recognizes vehicles entering the monitoring area and detects the impact of a guardrail and an AI-based object detection module based on vehicle image data learning were implemented. In addition, a monitoring and operation module that imanages sensor information and image data in integrate was also implemented. For the validation of the system, it was confirmed that the target values were all met by measuring the shock detection transmission speed, the object detection accuracy of vehicles and people, and the sensor failure detection accuracy. In the future, we plan to apply it to actual roads to verify the validity using real data and to commercialize it. This system will contribute to improving road safety.

• Convergence Security Journal
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• v.22 no.3
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• pp.25-32
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• 2022

Recently, the image processing industry has been activated as deep learning-based technology is introduced in the image recognition and detection field. With the development of deep learning technology, learning model vulnerabilities for adversarial attacks continue to be reported. However, studies on countermeasures against poisoning attacks that inject malicious data during learning are insufficient. The conventional countermeasure against poisoning attacks has a limitation in that it is necessary to perform a separate detection and removal operation by examining the training data each time. Therefore, in this paper, we propose a technique for reducing the attack success rate by applying modifications to the training data and inference data without a separate detection and removal process for the poison data. The One-shot kill poison attack, a clean label poison attack proposed in previous studies, was used as an attack model. The attack performance was confirmed by dividing it into a general attacker and an intelligent attacker according to the attacker's attack strategy. According to the experimental results, when the proposed defense mechanism is applied, the attack success rate can be reduced by up to 65% compared to the conventional method.

• The Journal of Bigdata
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• v.8 no.1
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• pp.99-109
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• 2023

Recently, not only in Korea but also around the world, we have been experiencing constant disasters such as typhoons, wildfires, and heavy rains. The property damage caused by typhoons and heavy rain in South Korea alone has exceeded 1 trillion won. These disasters have resulted in significant loss of life and property damage, and the recovery process will also take a considerable amount of time. In addition, the government's contingency funds are insufficient for the current situation. To prevent and effectively respond to these issues, it is necessary to collect and analyze accurate data in real-time. However, delays and data loss can occur depending on the environment where the sensors are located, the status of the communication network, and the receiving servers. In this paper, we propose a two-stage hybrid situation analysis and prediction algorithm that can accurately analyze even in such communication network conditions. In the first step, data on river and stream levels are collected, filtered, and refined from diverse sensors of different types and stored in a bigdata. An AI rule-based inference algorithm is applied to analyze the crisis alert levels. If the rainfall exceeds a certain threshold, but it remains below the desired level of interest, the second step of deep learning image analysis is performed to determine the final crisis alert level.