• Korean Journal of Artificial Intelligence
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• v.6 no.1
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• pp.1-10
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• 2018

Compressed Air is an important energy source used in most factories nowadays. The automation trend using air compressor has been gradually increasing with the interest of the 4th industry in recent years. With the air compressor system, it is possible to construct the device at low cost and easily achieve automation and energy saving. In addition, With trend of FA, miniaturation and light weight manufacturing trend expand their use in the electronics, medical, and food sectors. Research method is to design the technology for the remote control of the following information as USN base. Development of flexible sensing module from real time observation module for fusion of IT technology in compressed air systems, design and manufacture of flexible sensing module, and realiability assessment. Design of real-time integrated management system for observation data of compressed air system - Ability to process observation data measured in real time into pre-processing and analysis data. This study expects unconventionally decreasing effect of energy cost that takes up 60~70% of air compressor layout and operation and maintenance management cost through USN(Ubiquitous Sensor Network) technology by using optimum operational condition from real time observation module. In addition, by preventing maintenance cost from malfunction of air compressor beforehand, maintenance cost is anticipated to cut back.

• Journal of Korean Society of Rural Planning
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• v.20 no.2
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• pp.1-10
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• 2014

Smartphones change the picture of data and information sharing and make it possible to share various real-time flooding data and information. The vulnerability indicators of farmland inundation is needed to calculate the risk of farmland flood based on changeable hydro-meteorological data over time with morphologic characteristics of flood-damaged areas. To find related variables show the vulnerability of farmland inundation using the binary-logit model and correlation analysis and to provide vulnerability indicators were estimated by fuzzy set method. The outputs of vulnerability indicators were compared with the results of Monte Carlo simulation (MCS) for verification. From the result vulnerability indicators are applicable to mobile_based information system of farmland inundation.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.375-381
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• 2022

Safety accidents are of concern during construction projects, even given the recent innovations in digital technologies. These projects remain focused on overcoming specific and limited applications on construction sites. For this reason, the development of an inclusive safety management system has become crucial. This study aims to build a Big Data platform to inform decisions on how to proactively eliminate worker hazards on construction sites. The platform consists of about 100,000 real records and a real-time monitored database featuring various safety indices, such as workers' altitudes, heart rates, and fatigability during construction, which are determined through various wearable devices. The data types are customized and integrated by a research team in accordance with the characteristics of a specific project using hypertext transfer protocol (HTTP). The results can be helpful as efficient tools to ensure successful safety management in complex construction situations. This study is expected to provide three significant contributions to the field, including real-time fatigability analysis and tracking of workers on-site; providing early GPS-based warnings to workers who might be accessing dangerous spaces or places; and monitoring the workers' health indices, based on details from 100,000 cases.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.464-469
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• 2023

As modern society develops, the number of diseases caused by bad smells is increasing. As it can harm people's health, it is important to predict in advance the extent to which bad smells may occur, inform the public about this, and take preventive measures. In this paper, we propose a hybrid neural network structure of CNN and LSTM that can be used to detect or predict the occurrence of odors, which are most required in manufacturing or real life, using odor complex sensors. In addition, the proposed learning model uses a complex odor sensor to receive four types of data, including hydrogen sulfide, ammonia, benzene, and toluene, in real time, and applies this data to the inference model to detect and predict the odor state. The proposed model evaluated the prediction accuracy of the training model through performance indicators based on accuracy, and the evaluation results showed an average performance of more than 94%.

• Journal of Environmental Impact Assessment
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• v.20 no.4
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• pp.575-583
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• 2011

In this study, the plausible grid size was estimated to increase for efficiency of reservoir management using 3 dimensional water quality model. To validate utilization of a real time water quality management tool, ELCOM-CAEDYM model was applied to Soyang reservoir in korea. 100m grid size can represent the real topography and take out exact analysis results. $400{\times}400m$ grid can be easily used to analysis because of data capacity. Consequently, the grid size of 200m or 300m was recommended to establish 3D model considering the required simulation time and the irrelevance between horizontal grid size and vertical distribution for temperature and turbidity analysis.

• Journal of Technology Innovation
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• v.7 no.1
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• pp.176-186
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• 1999

This paper starts out by reviewing the literature that in different ways utilizes patent data as an output of Research ＆ Development (R&D) investment. The main focus, however, is an analysis of time-lag between industrial R&D input and its output. To achieve this research's purpose, the basic data associated with the industrial R&D input (expenditure, researchers) and output (applied patent and utilities) for the past 15 years, from 1980 to 1994, in the areas of electrical-electronic, mechanical and chemical industries have been collected. And the raw input data were altered into real flow data (but stock data) using Laspeyres approach and analyzed using multiple regression analysis, especially stepwise regression analysis. The result of this study can be summarized as follows: a) The time-lag; between industrial R&D input and its output is within 1 to 3 years. b) The time-lag: of patents was longer than that of utility models. c) The time-lag: in electrical-electronic, chemical industry was longer than that of the mechanical industry.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.194-197
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• 1999

In AVL, GIS analyze the information from the vehicles to provide commercial or other value far user. As spatial analysis functions in GIS make a new valuable information using the vehicle's position and geographic object's location, they perform an important roles to improve the management efficiency of vehicles. Most GIS however are used static data for the spatial analysis, so the research area on AVL used dynamic vehicle location has generated unsuitable result. In this study, we use GPS real time tracking data to perform spatial analysis between moving vehicle and static geographic object. The method proposed in this paper considers the driving direction of vehicle and creates the result which is located in forward of vehicle. In this paper, two spatial analysis functions, near and connectivity, are developed.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.03a
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• pp.704-715
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• 2008

The Aim of this development is the management of a forecasting analysis program based on a real-time remote sensing data. Using this program it is possible to predict a failure of levee facilities in advance. therefor, it is necessary for making plans of a safety countermove. In this development we have researched the analysis method which could operate effectively the levee facilities using real-time monitoring data from a remote sensing system and the safety managerial program using the algorism from the analysis method developed.

• International Journal of Highway Engineering
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• v.10 no.1
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• pp.155-164
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• 2008

It is critical to develop a core ITS technology such as real-time travel time estimation in order that the efficient use of the ITS implementation can be achieved as the ITS infrastructure and relevant facilities are broadly installed in recent years. The provision of travel time information in real-time allows travellers to make informed decisions and hence not only the traveller's travel utilities but also the road utilization can be maximized. In this paper, a hybrid model is proposed to combine VDS and AVI which have different characteristics in terms of space and time dimensions. The proposed model can incorporate the immediacy of VDS data and the reality of AVI data into one single framework simultaneously. In addition, the solution algorithm is made to have no significant computational burden so that the model can be deployable in real world. A set of real field data is used to analyze the reliability and applicability of the proposed model. The analysis results suggest that the proposed model is very efficient computationally and improves the accuracy of the information provided, which demonstrates the real-time applicability of the proposed model. In particular, the data fusion methodology developed in this paper is expected to be used more widely when a new type of traffic data becomes available.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.411-418
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• 2007

To analyze dynamic and long-term behavior of high speed rail system, and seismic measurements been installed at the various locations in the high speed rail system. Among these, 76 measurements were installed Chunan and Deajeon, and 80 measurements between Kwangmyung and Chunan. From these 156 measurements, real time data are continuously corrected and be sent to the main monitoring system to be used further analysis. These two systems were installed by different institution, and so there are not only basic differences in the system itself, but system running methods and data collecting/transferring methodology. There has been systematic difficulties due to these differences. This study shows the whole steps of high speed rail data monitoring systems include measurement equipment itself and data collecting/transferring system. study will proposed a more effective methods for collecting. This study also discuss the real time analysis method which can be used for future high speed rail monitoring system.