• Title/Summary/Keyword: Term Mapping

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Mapping Vegetation Volume in Urban Environments by Fusing LiDAR and Multispectral Data

  • Jung, Jinha;Pijanowski, Bryan
    • Korean Journal of Remote Sensing
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    • v.28 no.6
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    • pp.661-670
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    • 2012
  • Urban forests provide great ecosystem services to population in metropolitan areas even though they occupy little green space in a huge gray landscape. Unfortunately, urbanization inherently results in threatening the green infrastructure, and the recent urbanization trends drew great attention of scientists and policy makers on how to preserve or restore green infrastructure in metropolitan area. For this reason, mapping the spatial distribution of the green infrastructure is important in urban environments since the resulting map helps us identify hot green spots and set up long term plan on how to preserve or restore green infrastructure in urban environments. As a preliminary step for mapping green infrastructure utilizing multi-source remote sensing data in urban environments, the objective of this study is to map vegetation volume by fusing LiDAR and multispectral data in urban environments. Multispectral imageries are used to identify the two dimensional distribution of green infrastructure, while LiDAR data are utilized to characterize the vertical structure of the identified green structure. Vegetation volume was calculated over the metropolitan Chicago city area, and the vegetation volume was summarized over 16 NLCD classes. The experimental results indicated that vegetation volume varies greatly even in the same land cover class, and traditional land cover map based above ground biomass estimation approach may introduce bias in the estimation results.

Estimation of spatial parameters to be included in 3D mapping for long-term forest road management

  • Choi, Sung-Min;Kweon, Hyeongkeun;Lee, Joon-Woo
    • Korean Journal of Agricultural Science
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    • v.47 no.4
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    • pp.727-742
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    • 2020
  • Point cloud-based 3D maps can obtain many kinds of information for maintenance work on forest road networks. This study was conducted to compare the importance of each factor to select the factors required for the mapping of 3D forest road maps. This can be used as basic data for attribute information required to maintain forest road networks. The results of this study found that out of a total of 30 indexes extracted for mapping 3D forest roads, a total of 21 indexes related to stakeholder groups were significantly different. The importance of the index required by the civil service group was significantly higher than that of the other groups overall. In the case of the academic group, the index importance for cut slope, fill slope, and drainage facility was significantly higher. On the other hand, the index importance for the forestry cooperative and forest professional engineer group was mostly distributed between the civil servants' group and the academic group. In particular, the type of drainage system showed the highest value among the detailed indexes. Overall, drainage related factors in this survey had high coefficient values. The impact of water on forest roads was the most important part in road maintenance. In addition, the soil texture had a high value in relation to slope stability. This is thought to be because the texture of the soil affects the stability of the slope.

Term Mapping Methodology between Everyday Words and Legal Terms for Law Information Search System (법령정보 검색을 위한 생활용어와 법률용어 간의 대응관계 탐색 방법론)

  • Kim, Ji Hyun;Lee, Jong-Seo;Lee, Myungjin;Kim, Wooju;Hong, June Seok
    • Journal of Intelligence and Information Systems
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    • v.18 no.3
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    • pp.137-152
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    • 2012
  • In the generation of Web 2.0, as many users start to make lots of web contents called user created contents by themselves, the World Wide Web is overflowing by countless information. Therefore, it becomes the key to find out meaningful information among lots of resources. Nowadays, the information retrieval is the most important thing throughout the whole field and several types of search services are developed and widely used in various fields to retrieve information that user really wants. Especially, the legal information search is one of the indispensable services in order to provide people with their convenience through searching the law necessary to their present situation as a channel getting knowledge about it. The Office of Legislation in Korea provides the Korean Law Information portal service to search the law information such as legislation, administrative rule, and judicial precedent from 2009, so people can conveniently find information related to the law. However, this service has limitation because the recent technology for search engine basically returns documents depending on whether the query is included in it or not as a search result. Therefore, it is really difficult to retrieve information related the law for general users who are not familiar with legal terms in the search engine using simple matching of keywords in spite of those kinds of efforts of the Office of Legislation in Korea, because there is a huge divergence between everyday words and legal terms which are especially from Chinese words. Generally, people try to access the law information using everyday words, so they have a difficulty to get the result that they exactly want. In this paper, we propose a term mapping methodology between everyday words and legal terms for general users who don't have sufficient background about legal terms, and we develop a search service that can provide the search results of law information from everyday words. This will be able to search the law information accurately without the knowledge of legal terminology. In other words, our research goal is to make a law information search system that general users are able to retrieval the law information with everyday words. First, this paper takes advantage of tags of internet blogs using the concept for collective intelligence to find out the term mapping relationship between everyday words and legal terms. In order to achieve our goal, we collect tags related to an everyday word from web blog posts. Generally, people add a non-hierarchical keyword or term like a synonym, especially called tag, in order to describe, classify, and manage their posts when they make any post in the internet blog. Second, the collected tags are clustered through the cluster analysis method, K-means. Then, we find a mapping relationship between an everyday word and a legal term using our estimation measure to select the fittest one that can match with an everyday word. Selected legal terms are given the definite relationship, and the relations between everyday words and legal terms are described using SKOS that is an ontology to describe the knowledge related to thesauri, classification schemes, taxonomies, and subject-heading. Thus, based on proposed mapping and searching methodologies, our legal information search system finds out a legal term mapped with user query and retrieves law information using a matched legal term, if users try to retrieve law information using an everyday word. Therefore, from our research, users can get exact results even if they do not have the knowledge related to legal terms. As a result of our research, we expect that general users who don't have professional legal background can conveniently and efficiently retrieve the legal information using everyday words.

Improvement in Seasonal Prediction of Precipitation and Drought over the United States Based on Regional Climate Model Using Empirical Quantile Mapping (경험적 분위사상법을 이용한 지역기후모형 기반 미국 강수 및 가뭄의 계절 예측 성능 개선)

  • Song, Chan-Yeong;Kim, So-Hee;Ahn, Joong-Bae
    • Atmosphere
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    • v.31 no.5
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    • pp.637-656
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    • 2021
  • The United States has been known as the world's major producer of crops such as wheat, corn, and soybeans. Therefore, using meteorological long-term forecast data to project reliable crop yields in the United States is important for planning domestic food policies. The current study is part of an effort to improve the seasonal predictability of regional-scale precipitation across the United States for estimating crop production in the country. For the purpose, a dynamic downscaling method using Weather Research and Forecasting (WRF) model is utilized. The WRF simulation covers the crop-growing period (March to October) during 2000-2020. The initial and lateral boundary conditions of WRF are derived from the Pusan National University Coupled General Circulation Model (PNU CGCM), a participant model of Asia-Pacific Economic Cooperation Climate Center (APCC) Long-Term Multi-Model Ensemble Prediction System. For bias correction of downscaled daily precipitation, empirical quantile mapping (EQM) is applied. The downscaled data set without and with correction are called WRF_UC and WRF_C, respectively. In terms of mean precipitation, the EQM effectively reduces the wet biases over most of the United States and improves the spatial correlation coefficient with observation. The daily precipitation of WRF_C shows the better performance in terms of frequency and extreme precipitation intensity compared to WRF_UC. In addition, WRF_C shows a more reasonable performance in predicting drought frequency according to intensity than WRF_UC.

Exploratory Study of Person Centered Care Practice in Korean Long-term Care Facilities using DCM(Dementia Care Mapping) as a tool (DCM(Dementia Care Mapping)을 활용한 한국 요양시설에서의 사람중심케어 실천의 탐색적 연구)

  • Kim, Dongseon
    • 한국노년학
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    • v.41 no.2
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    • pp.197-215
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    • 2021
  • This study aims to evaluate Person Centered Care practice and characteristics of care services in Korean long-term care facilities using Dementia Care Mapping as a tool. DCM, systematic observational evaluation tool for measuring dementia patients' QOL, was transformed into self-report rating scale. The process of transforming DCM into a scale of 34 items involves operationalization of DCM concepts and it's adaptation into Korean long-term care practices. Review by research team of Bradford university was added to maintain DCM concept and meaning in this scale. The scale with Cronbach alpha of .88 was surveyed on 343 care workers. Survey result shows PCC value practiced by them is 3.77(of 5 likert scale) and values on each categories of PCC reveal the characteristics of care in Korean facilities; attachment(4.02), comfort(3.95), inclusion(3.89), identity(3.67) and occupation(3.41). Dementia care in Korean facilities focuses on recipients'safety, comfort but lacks individualistic care and the meaningful and fulfilling occupation for patients. Looking at the organizational and individual factors influencing DCM values, the small facilities showed higher PCC values and there are no significant difference in PCC values between public and private facilities. Managers and care workers with career of 1~2 years showed higher PCC values compared to other career ranks and lengthes. This study suggests care practice should be centered on personhood of patients in long-term care facilities, for which introduction of unit care and education of PCC for service providers including support personnel are needed. DCM and Korean DCM scale developed in this study are suggested for the PCC-based assessment on care quality.

Development of CPLD technology mapping control algorithm for Sequential Circuit under Time Constraint (시간제약 조건하에서 순차 회로를 위한 CPLD 기술 매핑 제어 알고리즘 개발)

  • Youn, Chung-Mo;Kim, Jae-Jin
    • Journal of the Korean Institute of Telematics and Electronics T
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    • v.36T no.4
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    • pp.71-81
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    • 1999
  • We propose a new CPLD(Complexity Programmable Logic Device) technology mapping algorithm improving run-time under time constraint. In our technology mapping algorithm, a given logic equation is constructed as the DAG(Directed Acyclic Graph) type, then the DAG is reconstructed by replicating the node that outdegree is more than or equal to 2. As a result, it makes delay time and the number of CLBs, run-time to be minimized. Also, after the number of multi-level is defined and cost of each nodes is calculated, the graph is partitioned in order to fit to k that is the number of OR term within CLB. The partitioned nodes are merged through collapsing and bin packing is performed in order to fit to the number of OR term within CLB(Configurable Logic Block). In the results of experiments to MCNC circuits for logic synthesis benchmark, we can shows that proposed technology mapping algorithm reduces run-time and the number of CLBs much more than the TEMPLA.

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Analysis on the Long-Term Shoreline Changes for Beaches Near Bangpo Port Using Aerial Imagery (항공사진을 이용한 방포항 인근 해빈의 장기간 해안선 변화 분석)

  • Kim, Baeck-Oon;Yun, Kong-Hyun;Lee, Chang-Kyung
    • Korean Journal of Remote Sensing
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    • v.29 no.5
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    • pp.477-486
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    • 2013
  • To analyze tendency of temporal and spatial change of shorelines and to estimate rate of shoreline changes using long-term shoreline change data is very important for the coastal environmental management. In this study, investigation was conducted to estimate the rate of shoreline changes using long-term shoreline change data from the year 1985 to 2009 aerial photographs. In this process aerial triangulation, GPS surveying and digital mapping was done for the estimation of changes. As the results, shorelines of Bangpo and Kkotji Beach retreated at a maximum rate of 0.2 m/yr and 0.8 m/yr, respectively. The shoreline could be changed by various factors. However, it was presumed that coastal erosion has been mainly affected by retaining wall constructed in the late 1990s.

A Train Ticket Reservation Aid System Using Automated Call Routing Technology Based on Speech Recognition (음성인식을 이용한 자동 호 분류 철도 예약 시스템)

  • Shim Yu-Jin;Kim Jae-In;Koo Myung-Wan
    • MALSORI
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    • no.52
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    • pp.161-169
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    • 2004
  • This paper describes the automated call routing for train ticket reservation aid system based on speech recognition. We focus on the task of automatically routing telephone calls based on user's fluently spoken response instead of touch tone menus in an interactive voice response system. Vector-based call routing algorithm is investigated and mapping table for key term is suggested. Korail database collected by KT is used for call routing experiment. We evaluate call-classification experiments for transcribed text from Korail database. In case of small training data, an average call routing error reduction rate of 14% is observed when mapping table is used.

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High-speed Fuzzy Inference System in Integrated GUI Environment

  • Lee, Sang-Gu
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.4 no.1
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    • pp.50-55
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    • 2004
  • We propose an intgrated Gill environment system having only integer fuzzy operations in the consequent part and the defuzzification stage. In this paper, we also propose an integrated Gill environment system with 4 parallel fuzzy processing units to be operated in parallel on the classification of the sensed image data. In this, we solve the problems of taking longer times as the fuzzy real computations of [0, 1] by using the integer pixel conversion algorithm to convert lines of each fuzzy linguistic term to the closest integer pixels. This procedure is performed automatically in the GUI application program. As a Gill environment, PCI transmission, image data pre-processing, integer pixel mapping and fuzzy membership tuning are considered. This system can be operated in parallel manner for MIMO or MISO systems.

MAPPING WETLANDS AND FLOODS IN THE TONLE SAP BASIN, CAMBODIA, USING AIRSAR DATA

  • Milne, A.K.;Tapley, I.J.
    • Proceedings of the KSRS Conference
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    • 2002.10a
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    • pp.441-441
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    • 2002
  • In order to ensure a balance between economic development and a healthy Mekong Basin environment supporting natural resources diversity and productivity critical to the livelihood of its 65 million inhabitants, the Mekong River Commission (MRC) has been investigating the use of radar to remotely characterize and monitor the diversity, complexity, size and connectivity of the Basin's aquatic habitats. The PACRIM AIRSAR Mission provided an opportunity to evaluate the usefulness of radar technology to derive information for assessing, forecasting and mitigating possible cumulative and long-term impacts of development on the natural environment and the people's livelihood. This paper presents the results of mapping wetland cover types using multi-polarimetric radar for an area of the north-western corner of the Tonle Sap basin with data acquired from the AIRSAR Mission in September 2000. The implementation of a newly developed segmentation classification routine used to derive the image classification is described and the results of a fieldwork campaign to check the classification is presented.

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