• Journal of Korean Society of Coastal and Ocean Engineers
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• v.35 no.4
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• pp.75-83
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• 2023

Apart from implementing hardware solutions like raising the crest freeboard of coastal structures to efficiently counter wave-overtopping, there is a simultaneous requirement for software-driven disaster mitigation strategies. These tactics involve the swift and accurate dissemination of wave-overtopping information to the inland regions of coastal zones, enabling the regulation of evacuation procedures and movement. In this study, a method was proposed to estimate wave-overtopping by utilizing the temporal variation of wave heights exceeding the structure's crown level, with the aim of developing an on-site wave measurement system for providing wave-overtopping information in the field. Laboratory model experiments were conducted on vertical seawall structures to measure wave-overtopping volumes and wave runup heights under different wave conditions and structural freeboard variations. By assuming that the velocity of water inundation on the top of the structure during wave-overtopping events is equivalent to the long-wave velocity, an overtopping discharge coefficient was introduced. This coefficient was utilized to estimate the rate of wave-overtopping based on the temporal changes in wave runup heights measured at the top of the structure. Upon reasonably calculating the overtopping discharge coefficient, it was verified that the estimation of wave-overtopping could be achieved solely based on the wave runup heights.

• Korean Journal of Construction Engineering and Management
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• v.24 no.5
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• pp.52-62
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• 2023

The objective of this study is to propose an automated algorithm for precise cutting length of slab rebar complying with regulations such as anchorage length, standard hooks, and lapping length. This algorithm aims to improve the traditional manual quantity take-off process typically outsourced by external contractors. By providing accurate rebar quantity data at BBS(Bar Bending Schedule) level from the bidding phase, uncertainty in quantity take-off can be eliminated and reliance on out-sourcing reduced. In addition, the algorithm allows for early determination of precise quantities, enabling construction firms to preapre competitive and optimized bids, leading to increased profit margins during contract negotiations. The proposed algorithm not only streamlines redundant tasks across various processes, including estimating, budgeting, and BBS generation but also offers flexibility in handling post-contract structural drawing changes. In particular, the proposed algorithm, when combined with BIM, can solve the technical problems of using BIM in the early phases of construction, and the algorithm's formulas and shape codes that built as REVIT-based family files, can help saving time and manpower.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1243-1244
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• 2022

In recent years, the growing interest in off-site construction has led to factories scaling up their manufacturing and production processes in the construction sector. Consequently, continuous large-scale site monitoring in low-variability environments, such as prefabricated components production plants (precast concrete production), has gained increasing importance. Although many studies on computer vision-based site monitoring have been conducted, challenges for deploying this technology for large-scale field applications still remain. One of the issues is collecting and transmitting vast amounts of video data. Continuous site monitoring systems are based on real-time video data collection and analysis, which requires excessive computational resources and network traffic. In addition, it is difficult to integrate various object information with different sizes and scales into a single scene. Various sizes and types of objects (e.g., workers, heavy equipment, and materials) exist in a plant production environment, and these objects should be detected simultaneously for effective site monitoring. However, with the existing object detection algorithms, it is difficult to simultaneously detect objects with significant differences in size because collecting and training massive amounts of object image data with various scales is necessary. This study thus developed a large-scale site monitoring system using edge computing and a small-object detection system to solve these problems. Edge computing is a distributed information technology architecture wherein the image or video data is processed near the originating source, not on a centralized server or cloud. By inferring information from the AI computing module equipped with CCTVs and communicating only the processed information with the server, it is possible to reduce excessive network traffic. Small-object detection is an innovative method to detect different-sized objects by cropping the raw image and setting the appropriate number of rows and columns for image splitting based on the target object size. This enables the detection of small objects from cropped and magnified images. The detected small objects can then be expressed in the original image. In the inference process, this study used the YOLO-v5 algorithm, known for its fast processing speed and widely used for real-time object detection. This method could effectively detect large and even small objects that were difficult to detect with the existing object detection algorithms. When the large-scale site monitoring system was tested, it performed well in detecting small objects, such as workers in a large-scale view of construction sites, which were inaccurately detected by the existing algorithms. Our next goal is to incorporate various safety monitoring and risk analysis algorithms into this system, such as collision risk estimation, based on the time-to-collision concept, enabling the optimization of safety routes by accumulating workers' paths and inferring the risky areas based on workers' trajectory patterns. Through such developments, this continuous large-scale site monitoring system can guide a construction plant's safety management system more effectively.

• Journal of the Daesoon Academy of Sciences
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• v.33
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• pp.147-177
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• 2019

This article attempts to examine the fundamental perceptions and attitudes of human beings towards others utilizing the concept of 'precariat,' a new word recently created to designate people affected by the inequality and instability brought about by neoliberal globalization. Especially, the precariats within South Korean society noted in this article will be North Korean migrants. When leaving North Korea, they have entered into South Korean society with hurting bodies and minds as they made their way through China or third party countries. After arriving in South Korea, they face difficulties such as inadequate jobs and low-level welfare benefits. Also, considering the social discrimination, exclusion, and indifference towards North Korean migrants which are commonplace, they come to live their lives as precariats. Given their situation, I would like to seek wisdom for North Korean migrants to apply as they escape from insecure lives, and perhaps Sangsaeng (mutual beneficence) would allow them to do that within South Korean society. In this light, I think that the concept of hospitality and Haewon Sangsaeng (the resolution of grievances for mutual beneficence), a code of practical ethics within the Daesoon Thought, as a basis for discussion with other philosophies that are practical in enabling North Korean migrants and South Korean citizens to coexist within modern day South Korean society. This can be achieved because 'Haewon (grievance-resolution)' lowers the boundary between self and others through sharing, and consequently, daily mutual interactions can unfold as 'Sangsaeng', which stands as a new ethical and practical system of values available to all modern individuals. In fact, contrary to the religious implications of Daesoon Thought, the philosophical and existential significance of Daesoon Thought has not received much attention. However, if we pay attention to the question of why human subjects should be hospitable to others, we can grasp how Daesoon Thought presents values that are existential in nature and also consider the specific context that accompanies the religious aspects of this system of thought.

• Journal of Arbitration Studies
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• v.32 no.4
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• pp.53-85
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• 2022

Small and medium-sized enterprises ("SMEs") are vulnerable to trade secret misappropriation. Korea's legislation for the protection of SMEs' trade secrets and provision of civil, criminal, and administrative remedies includes the SME Technology Protection Act, the Unfair Competition Prevention Act, the Industrial Technology Protection Act, the Mutually Beneficial Cooperation Act, and the Subcontracting Act. Among these acts, the revised SME Technology Protection Act of 2018 introduced the "administrative technology misappropriation investigation system" to facilitate a rapid resolution of SMEs' technology misappropriation disputes. On September 27, 2021, Korea's Ministry of SMEs announced that it had reached an agreement to resolve the dispute between Hyundai Heavy Industries and Samyeong Machinery through the administrative technology misappropriation investigation system. However, not until 3 years and a few months passed since the introduction of the system could it be used to resolve an SME's technology misappropriation dispute with a large corporation. So there arose a question on the usefulness of the system. Therefore, we conducted a comparative legal analysis of Korea's laws enacted to protect trade secrets of SMEs and to address technology misappropriation, focusing on their legislative purpose, protected subject matter, types of misappropriation, and legal remedies. Then we analyzed the administrative technology misappropriation investigation system and the cases where this system was applied. We developed a proposal to enhance the usefulness of the system. The expert interviews of 4 attorneys who are experienced in the management of the system to check the practical value of the proposal. Our analysis shows that the lack of compulsory investigation and criminal sanctions is the fundamental limitation of the system. We propose revising the SME Technology Protection Act to provide correction orders, criminal sanctions, and compulsory investigation. We also propose training professional workforces to conduct digital forensics, enabling terminated SMEs to utilize the system, and assuring independence and fairness of the mediation and arbitration of the technology misappropriation disputes.

• Membrane Journal
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• v.33 no.2
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• pp.77-86
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• 2023

In this study, pore-filled ion exchange membranes with low membrane resistance and high hydroxide ion conductivity was developed. To improve alkali durability, a porous substrate made of polytetrafluoroethylene was used, and a copolymer was prepared using monomers 2-(dimethyl amino) ethyl methacrylate (DMAEMA) and vinyl benzyl chloride (VBC) for pores. divinyl benzene (DVB) was used as the cross-linker, and ion exchange membranes were prepared for each cross-linking agent content to study the effect of the cross-linker content on DMAEMA-DVB and VBC-DMAEMA-DVB copolymers. As a result, chemical stability is improved by using a PTFE material substrate, and productivity can be increased by enabling fast photo polymerization at a low temperature by using a low-pressure UV lamp. To confirm the physical and chemical stability of the ion exchange membrane required for an anion exchange membrane fuel cell, tensile strength, and alkali resistance tests were conducted. As a result, as the cross-linking degree increased, the tensile strength increased by approximately 40 MPa, and finally, through the silver conductivity and alkali resistance tests, it was confirmed that the alkaline stability increased as the cross-linking agent increased.

• Therapeutic Science for Rehabilitation
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• v.11 no.1
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• pp.87-99
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• 2022

Objective : Through the application of the Anderson model, this study provides an empirical analysis of the decision-making factors for participation in cognitive improvement programs for the elderly living in the community. Methods : This study was conducted through an online survey. The participants were elderly people aged 65 years or older living in the community. The survey had 154 participants and was conducted over a two-month period from August to September 2020. Results : The main results of this study were as follow: first, there was no correlation between the predisposing factors and cognitive improvement program; second, among the enabling factors, diversity, interest, and effectiveness of the program were correlated with the cognitive improvement program; and third, there was no correlation between participation in the cognitive improvement program and need factors. Conclusion : This study shows that the results of basic information and evidence will be identified through analysis of the results of the study and that the implications for the development of cognitive improvement programs will be obtained in the future.

• Geophysics and Geophysical Exploration
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• v.25 no.4
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• pp.227-241
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• 2022

Full waveform inversion (FWI) in the field of seismic data processing is an inversion technique that is used to estimate the velocity model of the subsurface for oil and gas exploration. Recently, deep learning (DL) technology has been increasingly used for seismic data processing, and its combination with FWI has attracted remarkable research efforts. For example, DL-based data processing techniques have been utilized for preprocessing input data for FWI, enabling the direct implementation of FWI through DL technology. DL-based FWI can be divided into the following methods: pure data-based, physics-based neural network, encoder-decoder, reparameterized FWI, and physics-informed neural network. In this review, we describe the theory and characteristics of the methods by systematizing them in the order of advancements. In the early days of DL-based FWI, the DL model predicted the velocity model by preparing a large training data set to adopt faithfully the basic principles of data science and apply a pure data-based prediction model. The current research trend is to supplement the shortcomings of the pure data-based approach using the loss function consisting of seismic data or physical information from the wave equation itself in deep neural networks. Based on these developments, DL-based FWI has evolved to not require a large amount of learning data, alleviating the cycle-skipping problem, which is an intrinsic limitation of FWI, and reducing computation times dramatically. The value of DL-based FWI is expected to increase continually in the processing of seismic data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.2
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• pp.281-290
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• 2022

In Korea, the number of national facilities for which a safety inspection is mandatory is increasing, and a safer safety inspection method is needed. This study aimed to increase the efficiency of the bridge safety inspection by enabling rapid exterior inspection while securing the safety of inspectors by using drones to perform the safety inspections of bridges, which had mainly relied on visual inspections. For the research, the Youngjong Grand Bridge in Incheon was selected as a test bed and was divided into four parts: the warren truss, suspension bridge main cable, main tower, and pier. It was possible to establish a five-step standard procedure for drone safety inspections. The step-by-step contents of the standard procedure obtained as a result of this research are: Step 1, facility information collection and analysis, Step 2, analysis of vulnerable parts and drone flight planning, Step 3, drone photography and data processing, Step 4, condition evaluation by external inspection, Step 5, building of external inspection diagram and database. Therefore, if the safety inspections of civil engineering facilities including bridges are performed according to this standard procedure, it is expected that these inspection can be carried out more systematically and efficiently.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.2
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• pp.255-264
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• 2022

The conventional spot-type UV curing machine configures a collimator optical system using a plurality of lenses so that the light beam is incident through an optical cable. In order to increase the transmission light efficiency, a collimator optical system composed of three or more lenses is required, and accordingly, it is difficult to align the optical system, and it is difficult to implement the system compactly. In this study, a single TIR lens collimator that can realize the same level of spot diameter and light efficiency as the conventional collimator optical system composed of three lenses was designed. Through this, the light efficiency at the curing area with the minimum illuminance deviation was 33.2 %, which was similar to the performance of the reference collimator optical system, and the illuminance deviation on the curing area was 18.8 %, ensuring acceptable performance. In addition, by arranging a fly-eye lens with field flattening function at the front end of the condensing lens, the effective curing area diameter was reduced from 5.0 mm to 3.0 mm, enabling higher curing energy density to be realized. In addition, it was confirmed that the illuminance deviation can be greatly improved to a level of 14.4%.