• Journal of Korean Tunnelling and Underground Space Association
• /
• v.20 no.6
• /
• pp.1161-1175
• /
• 2018

An unexpected event could be easily followed by a large secondary accident due to the limitation in sight of drivers in road tunnels. Therefore, a series of automated incident detection systems have been under operation, which, however, appear in very low detection rates due to very low image qualities on CCTVs in tunnels. In order to overcome that limit, deep learning based tunnel incident detection system was developed, which already showed high detection rates in November of 2017. However, since the object detection process could deal with only still images, moving direction and speed of moving vehicles could not be identified. Furthermore it was hard to detect stopping and reverse the status of moving vehicles. Therefore, apart from the object detection, an object tracking method has been introduced and combined with the detection algorithm to track the moving vehicles. Also, stopping-reverse discrimination algorithm was proposed, thereby implementing into the combined incident detection processes. Each performance on detection of stopping, reverse driving and fire incident state were evaluated with showing 100% detection rate. But the detection for 'person' object appears relatively low success rate to 78.5%. Nevertheless, it is believed that the enlarged richness of image big-data could dramatically enhance the detection capacity of the automatic incident detection system.

• Journal of the Korean Society for Library and Information Science
• /
• v.53 no.3
• /
• pp.291-315
• /
• 2019

The aim of the present study was to compare the research trends on disinformation between Korean and abroad. To achieve this objective, a total of 283 author-assigned English keywords in 104 Korean papers and 3,551 author-assigned English keywords in 861 abroad papers were collected from the whole research fields and the publication periods. The collected data were analyzed using NetMiner V.4 to discover their 'degree centrality' and 'betweenness centrality'of the keyword network. The result are as follows. First, the major research topics of disinformation in Korea were drawn such as 'Freedom of Expression', 'Fact Check', 'Regulation', 'Media Literacy', and 'Information Literacy' in order; whereas, in abroad were shown like 'Social Media', 'Post Truth', 'Propaganda', 'Information Literacy', and 'Journalism' in order. Second, in terms of the influence of research topics related to disinformation, in Korea were identified such as 'Fact Check', 'Freedom of Expression', and 'Hoax' in order; whereas, in abroad were shown such as 'Social Media' and 'Detection' in order. Finally, in an aspect of intervention of research topics related to disinformation, in Korea were 'Fact Check', 'Polarization', 'Freedom of Expression', and 'Commercial'; whereas, in abroad were 'Social Media', 'Detection', and 'Machine Learning' in order.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.47 no.3
• /
• pp.49-59
• /
• 2019

This paper examines the background and content of Thomas Jefferson's botanical garden plan for the University of Virginia. When Jefferson promoted the establishment of a botanical garden, European botanical gardens were evolving from physic gardens, and American botanical gardens were in their infancy. Accordingly, this paper compares the Botanical Garden Plan for the University of Virginia with contemporary botanical gardens. This is examined by outlining the trends of botanical gardens in Europe and the United States around the nineteenth century, analyzing their function and spatial structure. Also, Jefferson's perspective on botany, his plan, and botanical gardens are reviewed. This study found that Jefferson's project had its background in the social recognition of the importance of botany as a practical science, advancing the national economy, which was a prominent goal in late eighteenth-century Europe, and in developing networks of exchanging plants and information concerning botany and botanical gardens. Based on the botanist Correia's opinion on the role of a public botanical garden, the Botanical Garden Plan for the University of Virginia was developed by Jefferson as an action plan, including its site creation, space organization, and supplying of plants. Compared to the other contemporary botanical gardens, the University of Virginia's Botanical Garden Plan has the following characteristics. First, like European gardens in the late eighteenth century, it evolved from being a physic garden to a botanical one. As such, it emphasized botanical research and education over medicine, creating a tree garden and a plant garden. Second, it differed from many European and American botanical gardens in that it rejected decorative elements, refused to install a greenhouse, and attempted to spread practical overseas plants suitable to the local climate. This study contributes to broadening the history of botanical gardens at the turn of the nineteenth century.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.12 no.3
• /
• pp.273-281
• /
• 2019

The energy consumed by buildings among the total national energy consumption is more than 10% of the total. For this reason, Korea has adopted the zero energy building policy since 2025, and research on the energy saving technology of buildings has been demanded. Analysis of buildings' energy consumption patterns shows that lighting, heating and cooling energy account for more than 60% of total energy consumption, which is directly related to solar power acquisition and window opening and closing operation. In this paper, we have developed a low - power IoT sensor module for window system to transfer acquired information to building energy management system. This module transmits the external environment and window opening / closing status information to the building energy management system in real time, and constructs the network to actively take energy saving measures. The power used in the module is designed as an independent power source using solar power among the harvest energy. The topology of the power supply is a Buck converter, which is charged at 4V to the lithium ion battery through MPPT control, and the efficiency is about 85.87%. Communication is configured to be able to transmit in real time by applying WiFi. In order to reduce the power consumption of the module, we analyzed the hardware and software aspects and implemented a low power IoT sensor module.

• Journal of the Korea Society for Simulation
• /
• v.28 no.2
• /
• pp.107-117
• /
• 2019

Because shipbuilding is single-product production with limited resources, production management technology is essential to manage the resources effectively and maximize the productivity of ship-process. Therefore, many shipbuilding companies are conducting research on ship production plan and process considering various constraints in the field by applying modeling and simulation. However, it is difficult to provide accurate production plan on sudden schedule and process changes, and to understand the interconnectivity between the processes that produce blocks in existing research. In addition, there are many differences between the production planning and field planning because detailed processes and quantity of blocks can not be considered. In this research, we propose the integrated process-based modeling method considering process-operation sequences, BOM(Bill of materials) and resource constraints of all the scheduled blocks in the indoor system. Through the integrated process-based model, it is easy for the user to grasp the assembly relationship, workspace and preliminary relationship of assembly process between the blocks in indoor system. Also, it is possible to obtain the overall production plan that maximizes resource efficiency without the separate simulation and resource modeling procedures because resource balancing that considers the amount of resource quantity shared in the indoor system is carried out.

• The Journal of the Korea Contents Association
• /
• v.19 no.9
• /
• pp.67-80
• /
• 2019

Augmented Reality (AR) is a crucial technology in the Fourth Industrial Revolution that can revolutionize the existing Information and Communication Technology (ICT) market and powerfully create a new market However, it is hard to find the clear answer for AD/PR strategies in the rapidly changing AR market. Thus this research explores the big picture of the AR industry as it pertains to Politics, Economy, Social, and Technology through in-depth interview with seven AR experts who are leading the domestic AR market. The research also analyzes the AR market's Strengths, Weaknesses, Opportunities, and Threats. Furthermore, it looks for strategies to vitalize the advertising and PR industry by analyzing the Contents, Platform, Network, and Devices of the AR ecosystem. The results of the research indicate a need for the government's strengthened policy of supporting the AR market, fostering of pace-setting killer contents, connecting services of several industries through AR platforms, strengthening the network of communication systems such as through 5G, and the commercialization and industrialization of domestic devices in order to vitalize the AR industry in its marketing and PR spheres. Therefore, this research suggests measures to revitalize the marketing and PR industries of the AR ecosystem, which has only recently gotten to its developing stage and provides an academic as well as practical foundation for future research in the field of AR.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.29 no.3
• /
• pp.491-501
• /
• 2019

In side-channel analysis, which exploit physical leakage from a cryptographic device, deep learning based attack has been significantly interested in recent years. However, most of the state-of-the-art methods have been focused on classifying side-channel information in a profiled scenario where attackers can obtain label of training data. In this paper, we propose a new method based on deep learning to improve non-profiling side-channel attack such as Differential Power Analysis and Correlation Power Analysis. The proposed method is a signal preprocessing technique that reduces the noise in a trace by modifying Auto-Encoder framework to the context of side-channel analysis. Previous work on Denoising Auto-Encoder was trained through randomly added noise by an attacker. In this paper, the proposed model trains Auto-Encoder through the noise from real data using the noise-reduced-label. Also, the proposed method permits to perform non-profiled attack by training only a single neural network. We validate the performance of the noise reduction of the proposed method on real traces collected from ChipWhisperer board. We demonstrate that the proposed method outperforms classic preprocessing methods such as Principal Component Analysis and Linear Discriminant Analysis.

• Journal of the Korean BIBLIA Society for library and Information Science
• /
• v.30 no.2
• /
• pp.189-209
• /
• 2019

Main Path Analysis (MPA) is one of the text mining techniques that extracts the core literature that contributes knowledge transfer based on citation information in the literature. This study applied various text mining techniques to abstract of the paper related with sense-of-place, which is published at Korea and abroad from 1990 to 2018 so that could discuss in a macro perspective. The main path analysis results showed that from 1990, overseas research on sense-of-place has been carried out in the order of personal identity, public land management, environmental education and urban development-related areas. Also, by using the network analysis, this study found that sense-of-place was discussed at various levels in Korea, including urban development, culture, literature, and history. On the other hand, it has been found that there are few topic changes in international studies, and that discussions on health, identity, landscape and urban development have been going on steadily since the 1990s. This study has implications that it presents a new perspective of grasping the overall flow of relevant research.

• The Journal of the Korea Contents Association
• /
• v.19 no.7
• /
• pp.360-375
• /
• 2019

This paper tries to study the ecosystem after constructing the network of the continuing transactions associated with distribution industry with the data of more than 50 thousands firms provided by the Korean enterprise data (KED) for 2015. After applying the clustering method, one of social network analysis tools, we find the firms in the network grouped into 732 clusters occupying about 80% of whole distribution industry sales in KED data. The firms in a cluster have most of their transactions with other firms in the cluster. But the clusters have smaller firm numbers in the cluster and sales portion of the biggest firms in the industry than the case of the manufacturing industry. The Input-output analysis for the biggest distribution firms show that the small and medium size enterprise(SME)s have very high sale dependency on a main firm in some clusters. This fact implies more efficient fair transaction policies within the clusters. And small number of big distribution firms have very high rear production linkage effects on SMEs or on the 10th or 31th group with high portion of SME employment. They should be considered important in the SME growth and employment policies.

• Journal of the Korea Computer Graphics Society
• /
• v.24 no.5
• /
• pp.31-39
• /
• 2018

In this paper, we propose an automated method for the ground-glass nodule(GGN) classification using GGN-Net based on intensity, texture, and shape-enhanced images in chest CT images. First, we propose the utilization of image that enhances the intensity, texture, and shape information so that the input image includes the presence and size information of the solid component in GGN. Second, we propose GGN-Net which integrates and trains feature maps obtained from various input images through multiple convolution modules on the internal network. To evaluate the classification accuracy of the proposed method, we used 90 pure GGNs, 38 part-solid GGNs less than 5mm with solid component, and 23 part-solid GGNs larger than 5mm with solid component. To evaluate the effect of input image, various input image set is composed and classification results were compared. The results showed that the proposed method using the composition of intensity, texture and shape-enhanced images showed the best result with 82.75% accuracy.