• Journal of the Korean Society of Safety
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• v.38 no.1
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• pp.1-8
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• 2023

It is extremely important to design safety-guaranteed industrial processes because such process determine the ultimate outcomes of industrial activities, including worker safety. Application of artificial intelligence (AI) in industrial safety involves modeling industrial safety systems by using vast amounts of safety-related data, accident prediction, and accident prevention based on predictions. As a preliminary step toward realizing AI-based industrial safety in Korea, this study discusses neural network-based modeling of industrial safety systems. The input variables that are the most discriminatory relative to the output variables of industrial safety processes are selected using two information-theoretic measures, namely entropy and cross entropy. Normalized frequency and severity of industrial accidents are selected as the output variables. Our simulation results confirm the effectiveness of the proposed neural network model and, therefore, the feasibility of extending the model to include more input and output variables.

• The Journal of Korea Robotics Society
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• v.19 no.3
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• pp.266-273
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• 2024

With the rising interaction between robots and humans, detecting collisions has become increasingly vital for ensuring safety. In this paper, we propose a novel approach for detecting collisions without using force torque sensors or tactile sensors, utilizing a Transformer-based neural network architecture. The proposed collision detection approach comprises a torque estimator network that predicts the joint torque in a free-motion state using Synchronous time-step encoding, and a collision discriminator network that predicts collisions by leveraging the difference between estimated and actual torques. The collision discriminator finally creates a binary tensor that predicts collisions frame by frame. In simulations, the proposed network exhibited enhanced collision detection performance relative to the other kinds of networks both in terms of prediction speed and accuracy. This underscores the benefits of using Transformer networks for collision detection tasks, where rapid decision-making is essential.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.471-474
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• 2012

The administration of government agencies and Law enforcement agencies is utilize. that network separation and Establish CERT for network security. However, the legislature has a basic security system. so a lot of relative vulnerability. In this paper, study for security National Assembly and the National Assembly Secretariat, at Library of National Assembly on legislative National Assembly for information security and network configuration, network and external Internet networks is to divide the internal affairs. Network separation in accordance with the movement of materials to use secure USB memory, the user has the uncomfortable issues. Problem analysis and security vulnerabilities on the use of USB memory is study the problem. User efficiency and enhance security.

• Proceedings of the Technology Innovation Conference
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• 1997.12a
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• pp.133-158
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• 1997

This paper analyzes the characteristics of technological knowledge flow-structure of Korean manufacturing in dynamic perspective. In doing that, the concept of the knowledge network is introduced which is defined as a set of industries and their interaction(knowledge flow) or linkage. The analysis of the inter-industrial knowledge flows is based on the technological similarity by using R&D researchers'academic background in the year of 1984, 1987, 1990. The analysis is carried out by such methodology as network analysis, indicator analysis and simple statistical analysis. And the final results are drawn both in absolute terms(dimension effect) and in relative terms (proportion effect) respectively. The main findings are as follow. First, the Korean manufacturing knowledge network appears to strengthen existing inter-industrial knowledge linkages rather than to construct new linkages. Second, the network seems to form a dualistic structure in that some high-technology sectors (knowledge production sectors) emerge along with traditional sectors (knowledge absorbing sectors). Third, since the mid-1980s, an inter-industrial fusion is witnessed among technologically intensive sectors, indicating that some sophisticated innovation modes are emerging in Korean manufacturing system.

• Journal of the Korean Institute of Landscape Architecture
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• v.27 no.4
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• pp.29-38
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• 1999

Present green space planning of Korea pay little attention to biodiversity conservation in urban areas. The quality of urban wildlife habitat has been deteriorated severely due to fragmentation and isolation of urban open spaces. The application of ecological corridors to urban green space planning and management can greatly enhance the bird habitat of Seoul. The objectives of this study were to evaluate bird habitat potential of existing urban parks of Seoul, and to investigate methods to develop ecological corridors for wild birds. This study consists of three parts. The first part is to construct bird species/habitat relationship model. The second part is to evaluate 207 urban parks of Seoul with the model. Based on the relative potential for bird habitat, urban parks of Seoul can be classified into cores, nodes, and points of the network. Outcomes of this part can also be used to enhance the quality of bird habitats by identifying limits or weakness of existing green spaces for bird habitat. The final part is to develop three green network plans; north-south network, the Han river network, and a district network for Kangnam-Gu.

• Korean Journal of Environment and Ecology
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• v.25 no.3
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• pp.412-420
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• 2011

This study was conducted to quantitatively analyze the temporal change of green space network at multi-scales from 1975 to 2006 with the application of graph theory in Seoul, Korea. Remarkable change of connectivity was detected in green space networks at the scale ranging from 1,000 ~ 1,600 m during 30 years. Green spaces and their networks have been restoring after 1990 since forest areas had been fragmented in 1975. In 2006, we identified the important core habitat areas that can sustain diverse wildlife species and stepping stones composed of small patches that can link these core habitat areas. Green spaces showed high correlation with the relative importance value of green space connectivity. So, this study could graphically represent green space networks of Seoul City. Green spaces of core areas distributed at the northern and southern boundary, and those of stepping stones possessing the high value of betweenness centrality consisted at the middle, eastern and western boundary. These results indicate that green space network can be graphically and quantitatively explained by degree centrality, betweenness centrality and relative importance value of connectivity with the application of graph theory.

• KIEAE Journal
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• v.12 no.4
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• pp.21-30
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• 2012

This study aims to set up Energy self-sufficiency urban planning system responding climate change by reducing fossil energy consumption and carbon emission, and to suggest effective application method. This study has 3 levels. First, it defines energy self-sufficient city responding climate change theoretically. Second, it set up planning system of Energy Self-sufficient city responding climate change. Third, ANP method was applied to introduce priority of application according to relative importance of planning section. As ANP method has to construct network to show interrelation among elements, 1st questionnaire survey was carried out to figure out interrelation. 2nd questionnaire survey introduced to judge relative importance of planning aspects and sections. In conclusion, this study shows interrelation among planning sections. By considering the relative importance, Energy environment and Energy consumption was derived as important planning aspects, and Architecture, Landuse, and Production of renewable energy was estimated as s important planning elements.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.3
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• pp.237-247
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• 2011

As of 2011, 72 Permanent GPS Stations are installed to control DGPS reference points by the National Geographic Information Institute in South Korea. As the center of the Earth's mass continues to move, the coordinates of the permanent GPS stations become inconsistent over time. Thus, a reference frame using a set of coordinates and their velocities of a global network of stations at a specific period has been used to solve the inconsistency. However, the relative movement of the permanent GPS stations can lower the accuracy of GPS relative positioning. In this research, we first analyzed the data collected daily during the past 30 months at the 40 permanent GPS stations within South Korea and the 5 IGS permanent GPS stations around the Korean Peninsula using a global network adjustment. We then calculated the absolute and relative amount of movement of the GPS permanent stations. We also identified the optimum renewal period of the permanent GPS stations considering the accuracy of relative GPS surveying. Finally, we developed a Korean a Korean crustal movement model that can be used to improvement of accuracy.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.202-205
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• 2005

Cell phenotypes are determined by the concerted activity of thousands of genes and their products. This activity is coordinated by a complex network that regulates the expression of genes. Understanding this organization is crucial to elucidate cellular activities, and many researches have tried to construct gene regulatory networks from mRNA expression data which are nowadays the most available and have a lot of information for cellular processes. Several computational tools, such as Boolean network, Qualitative network, Bayesian network, and so on, have been applied to infer these networks. Among them, Bayesian networks that we chose as the inference tool have been often used in this field recently due to their well-established theoretical foundation and statistical robustness. However, the relative insufficiency of experiments with respect to the number of genes leads to many false positive inferences. To alleviate this problem, we had developed the algorithm of MONET(MOdularized NETwork learning), which is a new method for inferring modularized gene networks by utilizing two complementary sources of information: biological annotations and gene expression. Afterward, we have packaged and improved MONET by combining dispersed functional blocks, extending species which can be inputted in this system, reducing the time complexities by improving algorithms, and simplifying input/output formats and parameters so that it can be utilized in actual fields. In this paper, we present the architecture of MONET system that we have improved.

• Asian Journal of Atmospheric Environment
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• v.9 no.1
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• pp.12-21
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• 2015

Air pollution is a challenging issue in some of the large cities in developing countries. In this regard, data interpretation is one of the most important parts of air quality management. Several methods exist to analyze air quality; among these, we applied the Multilayer Perceptron (MLP) and Radial Basis Function (RBF) methods to predict the hourly air concentration of benzene in 14 districts in the municipality of Tehran. Input data were hourly temperature, wind speed and relative humidity. Both methods determined reliable results. However, the RBF neural network performance was much closer to observed benzene data than the MLP neural network. The correlation determination resulted in 0.868 for MLP and 0.907 for RBF, while the Index of Agreement (IA) was 0.889 for MLP and 0.937 for RBF. The sensitivity analysis related to the MLP neural network indicated that the temperature had the greatest effect on prediction of benzene in comparison with the wind speed and humidity in the study area. The temperature was the most significant factor in benzene production because benzene is a volatile liquid.