• Title/Summary/Keyword: Location Potential

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Potential Mapping of Mountainous Wetlands using Weights of Evidence Model in Yeongnam Area, Korea (Weight of Evidence 기법을 이용한 영남지역의 산지습지 가능지역 추출)

  • Baek, Seung-Gyun;Jang, Dong-Ho
    • Journal of The Geomorphological Association of Korea
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    • v.20 no.1
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    • pp.21-33
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    • 2013
  • Weight of evidence model was applied for potential mapping of mountainous wetland to reduce the range of the field survey and to increase the efficiency of operations because the surveys of mountainous wetland need a lot of time and money owing to inaccessibility and extensiveness. The relationship between mountainous wetland location and related factors is expressed as a probability by Weight of evidence model. For this, the spatial database consist of slope map, curvature map, vegetation index map, wetness index map, soil drainage rating map was constructed in Yeongnam area, Korea, and weights of evidence based on the relationship between mountainous wetland location and each factor rating were calculated. As a result of correlation analysis between mountainous wetland location and each factors rating using likelihood ratio values, the probability of mountainous wetlands were increased at condition of lower slope, lower curvature, lower vegetation index value, lower wetness value, moderate soil drainage rating. Mountainous Wetland Potential Index(MWPI) was calculated by summation of the likelihood ratio and mountainous wetland potential map was constucted from GIS integration. The mountain wetland potential map was verified by comparison with the known mountainous wetland locations. The result showed the 75.48% in prediction accuracy.

Nano-delamination monitoring of BFRP nano-pipes of electrical potential change with ANNs

  • Altabey, Wael A.;Noori, Mohammad;Alarjani, Ali;Zhao, Ying
    • Advances in nano research
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    • v.9 no.1
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    • pp.1-13
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    • 2020
  • In this work, the electrical potential (EP) technique with an artificial neural networks (ANNs) for monitoring of nanostructures are used for the first time. This study employs an expert system to identify size and localize hidden nano-delamination (N.Del) inside layers of nano-pipe (N.P) manufactured from Basalt Fiber Reinforced Polymer (BFRP) laminate composite by using low-cost monitoring method of electrical potential (EP) technique with an artificial neural networks (ANNs), which are combined to decrease detection effort to discern N.Del location/size inside the N.P layers, with high accuracy, simple and low-cost. The dielectric properties of the N.P material are measured before and after N.Del introduced using arrays of electrical contacts and the variation in capacitance values, capacitance change and node potential distribution are analyzed. Using these changes in electrical potential due to N.Del, a finite element (FE) simulation model for N.Del location/size detection is generated by ANSYS and MATLAB, which are combined to simulate sensor characteristic, therefore, FE analyses are employed to make sets of data for the learning of the ANNs. The method is applied for the N.Del monitoring, to minimize the number of FE analysis in order to keep the cost and save the time of the assessment to a minimum. The FE results are in excellent agreement with an ANN and the experimental results available in the literature, thus validating the accuracy and reliability of the proposed technique.

Development of an Efficient Method to Evaluate the Optimal Location of Groundwater Dam (최적의 지하댐 입지 선정을 위한 효율적 평가 방법 개발)

  • Jeong, Jina;Park, Eungyu
    • Economic and Environmental Geology
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    • v.53 no.3
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    • pp.245-258
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    • 2020
  • In this study, a data-driven response surface method using the results acquired from the numerical simulation is developed to evaluate the potential storage capacity of groundwater due to the construction of a groundwater dam. The hydraulic conductivities of alluvium and basement rock, depth and slope of the channel are considered as the natural conditions of the location for groundwater dam construction. In particular, the probability models of the hydraulic conductivities and the various types of geometry of the channel are considered to ensure the reliability of the numerical simulation and the generality of the developed estimation model. As the results of multiple simulations, it can be seen that the hydraulic conductivity of basement rock and the depth of the channel greatly influence to the groundwater storage capacity. In contrast, the slope of the channel along the groundwater flow direction shows a relatively lower impact on the storage capacity. Based on the considered natural conditions and the corresponding numerical simulation results, the storage capacity estimation model is developed applying an artificial neural network as the nonlinear regression model for training. The developed estimation model shows a high correlation coefficient (>0.9) between the simulated and the estimated storage amount. This result indicates the superiority of the developed model in evaluating the storage capacity of the potential location for groundwater dam construction without the numerical simulation. Therefore, a more objective and efficient comparison for the storage capacity between the different potential locations can be possibly made based on the developed estimation model. In line with this, the proposed method can be an effective tool to assess the optimal location of groundwater dam construction across Korea.

Location and Spatial Variations of Ceramic Industry in Miryang City, Kyongnam Province, Korea (밀양시 요업의 입지와 공간변화)

  • Lim, Yeong-Dae
    • Journal of the Korean association of regional geographers
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    • v.8 no.1
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    • pp.40-64
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    • 2002
  • The locational characteristics of ceramic industry in Miryang city, Kyongnam province, were clarified by means of examining the process of its formation, spatial variation, locations and their changes. The government policy on industry and the business fluctuation are important in the quantitative changes of the industry. The spatial variation of industry toward the outer part of area are the results of equilibrium between the decrease of firms in inner city and the increase of firms in outer part. The births and deaths of firms played important role in the processes of spatial variations. The industry location has lasted by the accumulation of location decision of 'potential entrepreneurs' who learned knowledges on the industry and had personal contacts with the business-related persons for long time. The main factors on the locational decision of firms are personal factor, raw materials, land, water and market. The locational problems have mainly related with plant expansion, land, marketing, labour and capital. They caused investment changes and caused relocations of firms. Such disadvantages as raw material exhaustion, shortage of land and congestion within the agglomeration area, development of road transportation and local government policy on industry location, induced recent decentralization of industry to outer part.

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Development of Time-location Weighted Spatial Measures Using Global Positioning System Data

  • Han, Daikwon;Lee, Kiyoung;Kim, Jongyun;Bennett, Deborah H.;Cassady, Diana;Hertz-Picciotto, Irva
    • Environmental Analysis Health and Toxicology
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    • v.28
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    • pp.5.1-5.7
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    • 2013
  • Objectives Despite increasing availability of global positioning system (GPS), no research has been conducted to analyze GPS data for exposure opportunities associated with time at indoor and outdoor microenvironments. We developed location-based and time-weighted spatial measures that incorporate indoor and outdoor time-location data collected by GPS. Methods Time-location data were drawn from 38 female subjects in California who wore a GPS device for seven days. Ambient standard deviational ellipse was determined based on outdoor locations and time duration, while indoor time weighted standard deviational ellipse (SDE) was developed to incorporate indoor and outdoor times and locations data into the ellipse measure. Results Our findings indicated that there was considerable difference in the sizes of exposure potential measures when indoor time was taken into consideration, and that they were associated with day type (weekday/weekend) and employment status. Conclusions This study provides evidence that time-location weighted measure may provide better accuracy in assessing exposure opportunities at different microenvironments. The use of GPS likely improves the geographical details and accuracy of time-location data, and further development of such location-time weighted spatial measure is encouraged.

An Automatic Diagnosis Methods for Impact Location Estimation

  • Kim, Jung-Soo;Lyu, Joon
    • Journal of IKEEE
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    • v.3 no.1 s.4
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    • pp.101-108
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    • 1999
  • In this paper, a real time diagnostic algorithm for estimating the impact location by loose parts is proposed. It is composed of two modules such as the alarm discrimination module (ADM) and the impact-location estimation module(IEM). First, ADM decides whether the detected signal that triggers the alarm is the impact signal by loose parts or the noise signal. Second, IEM by use of the arrival time method estimates the impact location of loose parts. In order to validate the application of this method, the test experiment with a mock-up (flat board and reactor) system is performed. The experimental results show the efficiency of this algorithm even under high level noise and potential application to Loose Part Monitoring System (LPMS) for improving diagnosis capability in nuclear power plants.

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Implementation of Indoor Location-Aware System based on Probability Distribution of RSSI (RSSI 확률분포를 사용한 실내 위치 인식 시스템의 구현)

  • Kim, Myung Gwan;Kim, Jin Woo
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.8 no.4
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    • pp.9-14
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    • 2008
  • Ubiquitous implementation of indoor location-based technology is recognized that one of the important elements of the technology. Specifically, the hospital management of patients, the silver-town management, the implementation of the smart home for the indoors rather than outdoors in a range of broadband users for location-aware technology is needed. This paper in wireless devices with an indoor location awareness shows about the system's technical design and implementation. Location-based technology for wireless LAN users aware of the strength of radio signals (Received Signal Strength Indication, RSSI) using trilateration. Topographic mapping system will be implemented wireless devices and servers, Access Point (AP), which is the system's development and testing throughout the physical environment to determine the potential for real-life applications.

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An Examination of Location Choice for Free Trade Zone in Busan: the Preference Discrimination Score Approach (부산자유무역지역 입지선정 검증 -선호판별점수접근-)

  • Park, Ro-Kyung;Park, Gil-Young
    • Journal of Korea Port Economic Association
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    • v.21 no.3
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    • pp.19-34
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    • 2005
  • The purpose of this paper is to introduce the new way of location choice for free trade zone in Busan area by using Obata and Ishii(2003) model of preference discrimination score. And also, this paper investigates the result of Choi, Bong-ho(200l) that deals with the choice of tariff free area in Busan area. Empirical main results are as follows: First, the North Port(Sinsundae)and the New Busan Port are efficient. Final winer of location choice for free trade zone is the North Port(Sinsundae). Second, the ranking result of this paper for 10 potential sites of free trade zone shows the almost similar to that of Choi, Bong-ho(200l). Policy planner for location choice of free trade zone should introduce the preference discrimination score method by Obata and Ishii(2003), because this method shows the very positive empirical results like questionaire method by expert groups and common people in Busan which should cause the much time and much money.

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An Automatic Diagnosis Method for Impact Location Estimation

  • Kim, Jung-Soo;Joon Lyou
    • 제어로봇시스템학회:학술대회논문집
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    • 1998.10a
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    • pp.295-300
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    • 1998
  • In this paper, a real time diagnostic algorithm fur estimating the impact location by loose parts is proposed. It is composed of two modules such as the alarm discrimination module (ADM) and the impact-location estimation module(IEM). ADM decides whether the detected signal that triggers the alarm is the impact signal by loose parts or the noise signal. When the decision from ADM is concluded as the impact signal, the beginning time of burst-type signal, which the impact signal has usually such a form in time domain, provides the necessary data fur IEM. IEM by use of the arrival time method estimates the impact location of loose parts. The overall results of the estimated impact location are displayed on a computer monitor by the graphical mode and numerical data composed of the impact point, and thereby a plant operator can recognize easily the status of the impact event. This algorithm can perform the diagnosis process automatically and hence the operator's burden and the possible operator's error due to lack of expert knowledge of impact signals can be reduced remarkably. In order to validate the application of this method, the test experiment with a mock-up (flat board and reactor) system is performed. The experimental results show the efficiency of this algorithm even under high level noise and potential application to Loose Part Monitoring System (LPMS) for improving diagnosis capability in nuclear power plants.

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A Human Movement Stream Processing System for Estimating Worker Locations in Shipyards

  • Duong, Dat Van Anh;Yoon, Seokhoon
    • International Journal of Internet, Broadcasting and Communication
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    • v.13 no.4
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    • pp.135-142
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    • 2021
  • Estimating the locations of workers in a shipyard is beneficial for a variety of applications such as selecting potential forwarders for transferring data in IoT services and quickly rescuing workers in the event of industrial disasters or accidents. In this work, we propose a human movement stream processing system for estimating worker locations in shipyards based on Apache Spark and TensorFlow serving. First, we use Apache Spark to process location data streams. Then, we design a worker location prediction model to estimate the locations of workers. TensorFlow serving manages and executes the worker location prediction model. When there are requirements from clients, Apache Spark extracts input data from the processed data for the prediction model and then sends it to TensorFlow serving for estimating workers' locations. The worker movement data is needed to evaluate the proposed system but there are no available worker movement traces in shipyards. Therefore, we also develop a mobility model for generating the workers' movements in shipyards. Based on synthetic data, the proposed system is evaluated. It obtains a high performance and could be used for a variety of tasksin shipyards.