• Computers and Concrete
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• v.24 no.2
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• pp.103-115
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• 2019

In this study, the strength and stiffness (EI) of wood-concrete composite beams for bridges with T-shaped cross section were evaluated. Two types of connectors were used: connectors bonded with epoxy adhesive and connectors attached to the wood just by pre-drilling (without adhesive). The connectors consisted of common steel bars with a diameter of 12.5 mm. Initially, the strength and stiffness (EI) of the beams were analyzed by bending tests with the load applied at the third point of the beam. Subsequently, the composite beams were evaluated by numerical simulation using ANSYS software with focus on the connection system. To make the composite beams, Eucalyptus citriodora wood and medium strength concrete were used. The slip modulus K and the ultimate strength values of each type of connector were obtained by direct shear tests performed on composite specimens. The results showed that the connector glued with epoxy adhesive resulted in better strength and stiffness (EI) for the composite beams when compared to the connector fixed by pre-drilling. The differences observed were up to 10%. The strength and stiffness (EI) values obtained analytically by $M{\ddot{o}}hler^{\prime}$ model were lower than the values obtained experimentally from the bending tests, and the differences were up to 25%. The numerical simulations allowed, with reasonable approximation, the evaluation of stress distributions in the composite beams tested experimentally.

• The Korean Journal of Archival Studies
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• no.54
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• pp.211-248
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• 2017

This study examined ways to improve records management by using the new technology of the Fourth Industrial Revolution. To do this, we selected four technologies that have a huge impact on the production and management of records such as cloud, big data, artificial intelligence, and the Internet of Things. We tested these technologies and summarized their concepts, characteristics, and applications. The characteristics of the changed production records were analyzed by each technology. Because of new technology, the production of records has rapidly increased and the types of records have become diverse. With this, there is also a need for solutions to explain the quality of data and the context of production. To effectively introduce each technology into records management, a roadmap should be designed by classifying which technology should be applied immediately and which should be applied later depending on the maturity of the technology. To cope with changes in the characteristics of production records, a flexible data structure must be produced in a standardized format. Public authorities should also be able to procure Software as a Service (SaaS) products and use digital technology to improve the quality of public services.

• Advances in robotics research
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• v.2 no.3
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• pp.201-217
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• 2018

Agriculture production is a critical human intensive task, which takes place in all regions of the world. The process to grow and harvest crops is labor intensive in many countries due to the lack of automation and advanced technology. Much of the difficult, dangerous and dirty labor of crop production can be automated with intelligent and robotic platforms. We propose an intelligent, agent-oriented robotic team, which can enable the process of harvesting, gathering and collecting crops and fruits, of many types, from agricultural fields. This paper describes a novel robotic organization enabling humans, robots and agents to work together for automation of gathering and collection functions. The focus of the research is a model, called HARMS, which can enable Humans, software Agents, Robots, Machines and Sensors to work together indistinguishably. With this model, any capability-based human-like organization can be conceived and modeled, such as in manufacturing or agriculture. In this research, we model, design and implement a technology application of knowledge-based robot-to-robot and human-to-robot collaboration for an agricultural gathering and collection function. The gathering and collection functions were chosen as they are some of the most labor intensive and least automated processes in the process acquisition of agricultural products. The use of robotic organizations can reduce human labor and increase efficiency allowing people to focus on higher level tasks and minimizing the backbreaking tasks of agricultural production in the future. In this work, the HARMS model was applied to three different robotic instances and an integrated test was completed with satisfactory results that show the basic promise of this research.

• Structural Engineering and Mechanics
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• v.69 no.2
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• pp.221-230
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• 2019

In this paper, shear behavior of non-persistent joint surrounded in concrete and gypsum layers has been investigated using experimental test and numerical simulation. Two types of mixture were prepared for this study. The first type consists of water and gypsum that were mixed with a ratio of water/gypsum of 0.6. The second type of mixture, water, sand and cement were mixed with a ratio of 27%, 33% and 40% by weight. Shear behavior of a non-persistent joint embedded in these specimens is studied. Physical models consisting of two edge concrete layers with dimensions of 160 mm by 130 mm by 60 mm and one internal gypsum layer with the dimension of 16 mm by 13 mm by 6 mm were made. Two horizontal edge joints were embedded in concrete beams and one angled joint was created in gypsum layer. Several analyses with joints with angles of $0^{\circ}$, $30^{\circ}$, and $60^{\circ}$ degree were conducted. The central fault places in 3 different positions. Along the edge joints, 1.5 cm vertically far from the edge joint face and 3 cm vertically far from the edge joint face. All samples were tested in compression using a universal loading machine and the shear load was induced because of the specimen geometry. Concurrent with the experiments, the extended finite element method (XFEM) was employed to analyze the fracture processes occurring in a non-persistent joint embedded in concrete and gypsum layers using Abaqus, a finite element software platform. The failure pattern of non-persistent cracks (faults) was found to be affected mostly by the central crack and its configuration and the shear strength was found to be related to the failure pattern. Comparison between experimental and corresponding numerical results showed a great agreement. XFEM was found as a capable tool for investigating the fracturing mechanism of rock specimens with non-persistent joint.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.1
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• pp.106-112
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• 2019

The Korea Copyright Commission has pursued copyright technology R&D projects to prevent illegal copying of comics and Webtoons. We developed a feature-based scanned comic filtering technology in order to apply technical measures to specific types of online service providers. We also developed technologies in order to monitor and identify illegally distributed comics on webhard sites and to monitor and identify illegally distributed webtoons. Even though all comic books posted on webhard sites are illegal, it is no trouble to download and access popular comics by accessing websites in foreign countries. Even under these circumstances, the comic and webtoon copyright protection technologies developed over the past six years have been used at all. In this paper, we examine what the problems are and find solutions to propose a copyright protection method for webtoons.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.5
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• pp.205-212
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• 2019

Scene graph is a kind of knowledge graph that represents both objects and their relationships found in a image. This paper proposes a 3D scene graph generation model for three-dimensional indoor environments. An 3D scene graph includes not only object types, their positions and attributes, but also three-dimensional spatial relationships between them, An 3D scene graph can be viewed as a prior knowledge base describing the given environment within that the agent will be deployed later. Therefore, 3D scene graphs can be used in many useful applications, such as visual question answering (VQA) and service robots. This proposed 3D scene graph generation model consists of four sub-networks: object detection network (ObjNet), attribute prediction network (AttNet), transfer network (TransNet), relationship prediction network (RelNet). Conducting several experiments with 3D simulated indoor environments provided by AI2-THOR, we confirmed that the proposed model shows high performance.

• Journal of Acupuncture Research
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• v.38 no.2
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• pp.110-121
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• 2021

The objective of this study was to conduct a systematic review and network meta-analysis to evaluate and compare the effectiveness of various types of acupuncture for menopausal hot flashes (HF). Randomized controlled trials (RCTs) were retrieved from 8 electronic databases, and the risk of bias was evaluated for the included studies. Pairwise meta-analysis and network meta-analysis were performed using Review Manager and R software for indirect comparison and ranking, respectively. In total, 23 RCTs (2,302 patients) were eligible for systematic review, of which 10 were included in network meta-analysis. Network meta-analysis showed manual acupuncture (MA) had the highest probability of reducing HF frequency and severity, followed by sham acupuncture (SA), electroacupuncture, usual care, or no treatment; furthermore, warm acupuncture significantly improved menopause-specific quality of life compared with MA or electroacupuncture. Compared with hormone replacement therapy, acupuncture had less efficacy in reducing HF frequency but enhanced menopause-specific quality of life. There was no significant difference between MA and SA in mitigating HF. The existing evidence showed that MA could be used for alleviating menopausal HF. However, it is recommended that more high-quality RCTs should be performed.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.5
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• pp.807-816
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• 2021

With the technology of the 4th industrial revolution, network traffic is increasing due to an increase in supply, an increase in demand, and an increase in the complexity of traffic patterns. SDN, a concept in which H/W and S/W are separated in order to efficiently manage such massive traffic, is attracting attention as a next-generation network. A lot of research is being conducted on the merits of applying flexible policies by avoiding the problem of rigid vendor dependency by using the SDN controller implemented with S/W Opensource. Therefore, in this paper, we propose an efficient load balancing technique by grouping through the packet structure of the network layer using the control layer and infrastructure layer of SDN and analyzing the packet delay and reception rate.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.508-514
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• 2021

In this paper, to propose a classifier based on supervised learning, three types of fuzzy membership functions that determine the membership of each feature of classification data are proposed. In addition, the possibility of improving the classifier performance was suggested by using the average value calculation method used in the process of deriving the classification result using the average value of the membership degrees for each feature, not by using a simple arithmetic average, but by using a weighted average using various weights. To experiment with the proposed methods, three standard data sets were used: Iris, Ecoli, and Yeast. As a result of the experiment, it was confirmed that evenly excellent classification performance can be obtained for data sets of different characteristics. It was confirmed that better classification performance is possible through improvement of fuzzy membership functions and the weighted average methods.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.3
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• pp.223-230
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• 2021

Currently, self-driving vehicles are on the verge of commercialization after testing. However, even though autonomous vehicles have not been fully commercialized, 81 accidents have occurred, and the driving method of vehicles to avoid accidents relies heavily on LiDAR. In order for the currently commercialized 3-level autonomous vehicle to develop into a 4-level autonomous vehicle, more information must be collected than previously collected information. Therefore, this paper proposes a Driving Situation Judgment System (DSJS) that accurately calculates the crisis situation the vehicle is in by useing the roughness of the road and the state of the passengers of surrounding vehicles including road information and weather information collected from existing autonomous vehicles. As a result of DSJS's PDM experiment, PDM was able to classify passengers 15.52% more accurately on average than the existing vehicle's passenger recognition system. This study can be a basic research to achieve the 4th level autonomous vehicle by collecting more various types than the data collected by the existing 3rd level autonomous vehicle.