• Title/Summary/Keyword: Automatic Distribution System

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Recognition of the Center Position of Electric Line Using Modified Hough Transform (수정 하후변환을 이용한 전선의 중심위치의 인식)

  • 안경관
    • Journal of the Korean Society for Precision Engineering
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    • v.20 no.1
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    • pp.99-106
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    • 2003
  • Uninterrupted power supply has become indispensable during the maintenance task of active electric power lines as a result of today's highly information-oriented society and increasing demand of electric utilities. The maintenance task has the risk of electric shock and the danger of falling from high place. Therefore it is necessary to realize an autonomous robot system. In order to realize these tasks autonomously, the there dimensional position of target object such as electric line and the stand of insulator must be recognized accurately and rapidly. The insertion task of an electric line into a sleeve is selected as the typical task of the maintenance of active electric power distribution lines in this paper. A modified hough transform is applied to the recognition of the center of electric line and optimal target position calculation method is newly derived in order to recognize the center 3 dimensional position of the electric line. By the proposed method, it is proved that the center position of the electric line can be recognized without respect to the noise of image and the shape of electric lines and the insertion task of an electric tine is realized.

Characteristics of Wind Energy for Long-term Period (10 years) at Seoguang Site on Jeju Island (제주 서광지역에 대한 풍력에너지의 장기간 (10년) 특성)

  • Ko, Kyung-Nam;Kim, Kyoung-Bo;Huh, Jong-Chul
    • Journal of the Korean Solar Energy Society
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    • v.28 no.3
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    • pp.45-52
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    • 2008
  • In order to clarify characteristics of variation in wind energy over a long-term period, an investigation was carried out at Seoguang site on Jeju island. The wind data for 10 years from Automatic Weather System (AWS) were analyzed for each year. The variation in the annual energy production (AEP) for the 2 MW wind turbine was estimated through statistical work. The result shows that the range of the yearly average wind speed at 15 m above ground level for 10 years was from -22.6% to +13.7%, which is wider range than that in Japan. The coefficient of variation for the AEP was 22.7%, which is about twice of that for the yearly average wind speed. Therefore, for estimating the wind energy potential accurately at a given site, the wind data should be analyzed over a long-term period based on the data from the meteorological station.

A Study on RFID Application Method in Franchise Business (프랜차이즈산업에서의 RFID 적용 방법에 대한 연구)

  • Rim, Jae-Suk;Choi, Wean-Yang
    • Journal of the Korea Safety Management & Science
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    • v.10 no.4
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    • pp.189-198
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    • 2008
  • At present, companies write daily work record or use bar-code in order to collect distribution flow data in real time. However, it needs additional works to check the record or read the bar-code with a scanner. In this case, human error could decrease accuracy of data and it would cause problems in reliability. To solve this problem, RFID (Radio Frequency Identification) is introduced in many automatic recognition sector recently. RFID is a technology that identification data is inserted into micro-mini IC chip and recognize, trace, and manage object, animal, or person using wireless frequency. This is being emerged as the core technology in future ubiquitous environment. This study is intended to suggest RFID application method in franchise business. Traceability and visibility of individual product are supplied based on EPCglobal network. It includes DW system which supplies various assessment data about product in supply chain, financial transaction system which is based on product transaction and position information, and RFID middleware which refines and divides product data from RFID tag. With the suggested application methods, individual product's profile data are supplied in real time and it would boost reliability to customer and make effective cooperation with existing operation systems (SCM, CRM, and e-Business) possible.

Analyzing Online Customer Reviews for the Hotel Classification in Vietnam

  • NGUYEN, Ha Thi Thu;TRAN, Tuan Minh;NGUYEN, Giang Binh
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.8
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    • pp.443-451
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    • 2021
  • The classification standards for hotels in Vietnam are different from many other hotel classification standards in the world. This study aims to analyze customer reviews on the TripAdvisor website to develop a new algorithm for hotel rating that is independent of Vietnam's hotel classification standards. This method can be applied to individual hotels, or hotels of a region or the whole country, while online booking sites only rate individual hotels. Data was crawled from TripAdvisor with 22,287 reviews of 5 cities in Vietnam. This study used a statistical model to analyze the review dataset and build an algorithm to rate hotels according to aspects or hotel overall. The results have less rating deviation when compared to the TripAdvisor system. This study also supports hotel managers to regularly update the status of their hotels using data from customer reviews, from which, managers can strategize long-term solutions to improve the quality of the hotel in all aspects and attract more travelers to Vietnam. Moreover, this method can be developed into an automatic system to rate hotels and update the status of service quality more quickly, thus, saving time and costs.

Application of machine learning for merging multiple satellite precipitation products

  • Van, Giang Nguyen;Jung, Sungho;Lee, Giha
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.134-134
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    • 2021
  • Precipitation is a crucial component of water cycle and play a key role in hydrological processes. Traditionally, gauge-based precipitation is the main method to achieve high accuracy of rainfall estimation, but its distribution is sparsely in mountainous areas. Recently, satellite-based precipitation products (SPPs) provide grid-based precipitation with spatio-temporal variability, but SPPs contain a lot of uncertainty in estimated precipitation, and the spatial resolution quite coarse. To overcome these limitations, this study aims to generate new grid-based daily precipitation using Automatic weather system (AWS) in Korea and multiple SPPs(i.e. CHIRPSv2, CMORPH, GSMaP, TRMMv7) during the period of 2003-2017. And this study used a machine learning based Random Forest (RF) model for generating new merging precipitation. In addition, several statistical linear merging methods are used to compare with the results of the RF model. In order to investigate the efficiency of RF, observed data from 64 observed Automated Synoptic Observation System (ASOS) were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the random forest model showed higher accuracy than each satellite rainfall product and spatio-temporal variability was better reflected than other statistical merging methods. Therefore, a random forest-based ensemble satellite precipitation product can be efficiently used for hydrological simulations in ungauged basins such as the Mekong River.

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Integrated Korean Flora Database: A Versatile Web-based Database for Dissecting Flora Investigations

  • Yeon, Jihun;Kim, Yongsung;Kim, Hyejeong;Kim, Juhyun;Park, Jongsun
    • Proceedings of the Plant Resources Society of Korea Conference
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    • 2018.04a
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    • pp.16-16
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    • 2018
  • Flora investigations have been conducted by many researchers for a long time in Korea. Even though large amount of investigation data has been accumulated, there is no accurate statistics or database because most of data were published in a printed form. We developed a web-based database of flora investigation, named as the Integrated Korean Flora Database (http://www.floradb.net/) to understand distribution patterns and habitats of plants in Korea. Till now, 480 published paper, 356 thesis, 76 reports and books, and 8 unpublished papers written in between 1962 and 2017 were collected and their species lists from 280 papers were parsed into the database. From 124,105 records, 3,100 species belonging to 206 families and 965 genera were identified via comparing with two major Korean plant species lists. 55 endangered species, 159 endemic species, and 367 rare species were identified. The most frequently surveyed species were Commelina communis in herbaceous and Rosa multiflora in woody plants. Microclimate data provided by Korea Meteorological Administration were also integrated and analyzed to assign cold hardness zones for each species. By comparing minimum temperature (<2%) acquired from automated weather stations (AWS) near by plant species, 6a to 10b zones (7b is the most frequent zone) were identified. Integrated Korean Flora Database will be a fundamental platform of korea flora investigation as well as a new standard for classifying distribution of plants based on accurate microclimate data. Moreover, it can also provide evidences of investigated plant species, such as specimen and/or pictures with connecting to the InfoBoss Cyber Herbarium (http://herbarium.infoboss. co.kr/) and Biodiversity Observation Datbase (BODB; http://www.biodiversitydb.org/).

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A Scalable and Effective DDS Participant Discovery Mechanism (확장성과 효율성 고려한 DDS 참여자 디스커버리 기법)

  • Kwon, Ki-Jung;You, Yong-Duck;Choi, Hoon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.13 no.7
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    • pp.1344-1356
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    • 2009
  • The DDS (Data Distribution Service) is a data-centric communication technology that provides an efficient communication service that supports a dynamic plug & play through an automatic setting of participants' location information for each data (Topic) by using DDS discovery technique. This paper proposes the hierarchical-structured DDS discovery technique (SPDP-TBF) suitable for the large-scale distributed systems by comparing and analyzing the existing DDS discovery techniques in terms of performance and problem areas. The proposed SPDP-TBF performs the periodic discovery of the involved participants only by having separate hierarchical managers which take charge of the registration and search (of participants) so that a participant sends its information to the related participants only, and it enhances the effectiveness of the message transfer. Moreover, the proposed SPDP-TBF provides the improved scalability by performing the hierarchical discovery through hierarchical manager nodes so that it can be applied to the large-scale distributed system.

A Two-Phase Stock Trading System based on Pattern Matching and Automatic Rule Induction (패턴 매칭과 자동 규칙 생성에 기반한 2단계 주식 트레이딩 시스템)

  • Lee, Jong-Woo;Kim, Yu-Seop;Kim, Sung-Dong;Lee, Jae-Won;Chae, Jin-Seok
    • The KIPS Transactions:PartB
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    • v.10B no.3
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    • pp.257-264
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    • 2003
  • In the context of a dynamic trading environment, the ultimate goal of the financial forecasting system is to optimize a specific trading objective. This paper proposes a two-phase (extraction and filtering) stock trading system that aims at maximizing the rates of returns. Extraction of stocks is performed by searching specific time-series patterns described by a combination of values of technical indicators. In the filtering phase, several rules are applied to the extracted sets of stocks to select stocks to be actually traded. The filtering rules are automatically induced from past data. From a large database of daily stock prices, the values of technical indicators are calculated. They are used to make the extraction patterns, and the distributions of the discretization intervals of the values are calculated for both positive and negative data sets. We assumed that the values in the intervals of distinctive distribution may contribute to the prediction of future trend of stocks, so the rules for filtering stocks are automatically induced from the data in those intervals. We show the rates of returns when using our trading system outperform the market average. These results mean rule induction method using distributional differences is useful.

Development of an AVL System for Fire Fighting Services (소방용 AVL 시스템 개발)

  • Kim, Dong-Yong;Moon, Sang-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.4
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    • pp.886-892
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    • 2010
  • It is possible to use wireless communication any time in every place because of well-developed wireless networks and mobile devices. The AVL(Automatic Vehicle Location) system, therefore, has made practical use in situation control, distribution industry, home delivery service, and ITS(Intelligent Transportation System) area. In this paper, we design and implement an AVL system in order to use for fire fighting activities such as emergency rescue and relief. To do this, first, we investigate and analyze the existing researches and systems related to AVL system. In details, we develop an AVL server and clients to support stable communication each other using wireless networks. Using AVL system, calling cars find the position of accidents quickly and the fire defense headquarters control unforeseen accidents efficiently because the state of calling cars are confirmed in real time by their GPS data.

Rainfall analysis considering watershed characteristics and temporal-spatial characteristics of heavy rainfall (집중호우의 시·공간적 특성과 유역특성을 고려한 강우분석 연구)

  • Kim, Min-Seok;Choi, Ji-Hyeok;Moon, Young-Il
    • Journal of Korea Water Resources Association
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    • v.51 no.8
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    • pp.739-745
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    • 2018
  • Recently, the incidence of heavy rainfall is increasing. Therefore, a rainfall analysis should be performed considering increasing frequency. The current rainfall analysis for hydrologic design use the hourly rainfall data of ASOS with a density of 36 km on the Korean Peninsula. Therefore, medium and small scale watershed included Thiessen network at the same rainfall point are analyzed with the same design rainfall and time distribution. This causes problem that the watershed characteristics can not be considered. In addition, there is a problem that the temporal-spatial change of the heavy rainfall occurring in the range of 10~20 km can not be considered. In this study, Author estimated design rainfall considering heavy rainfall using minutely rainfall data of AWS, which are relatively dense than ASOS. Also, author analyzed the time distribution and runoff of each case to estimate the huff's method suitable for the watershed. The research result will contribute to the estimation of the design hydrologic data considering the heavy rainfall and watershed characteristics.