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A PageRank based Data Indexing Method for Designing Natural Language Interface to CRM Databases (분석 CRM 실무자의 자연어 질의 처리를 위한 기업 데이터베이스 구성요소 인덱싱 방법론)

  • Park, Sung-Hyuk;Hwang, Kyeong-Seo;Lee, Dong-Won
    • CRM연구
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    • v.2 no.2
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    • pp.53-70
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    • 2009
  • Understanding consumer behavior based on the analysis of the customer data is one essential part of analytic CRM. To do this, the analytic skills for data extraction and data processing are required to users. As a user has various kinds of questions for the consumer data analysis, the user should use database language such as SQL. However, for the firm's user, to generate SQL statements is not easy because the accuracy of the query result is hugely influenced by the knowledge of work-site operation and the firm's database. This paper proposes a natural language based database search framework finding relevant database elements. Specifically, we describe how our TableRank method can understand the user's natural query language and provide proper relations and attributes of data records to the user. Through several experiments, it is supported that the TableRank provides accurate database elements related to the user's natural query. We also show that the close distance among relations in the database represents the high data connectivity which guarantees matching with a search query from a user.

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A Cell Loss Constraint Method of Bandwidth Renegotiation for Prioritized MPEG Video Data Transmission in ATM Networks (ATM망에서 우선 순위가 주어진 MPEG 비디오 데이터 전송시 대역폭 재협상을 통한 셀 손실 방지 기법)

  • Yun, Byoung-An;Kim, Eun-Hwan;Jun, Moon-Seog
    • The Transactions of the Korea Information Processing Society
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    • v.4 no.7
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    • pp.1770-1780
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    • 1997
  • Our problem is improvement of image quality because it is inevitable cell loss of image data when traffic congestion occurs. If cells are discarded indiscriminately in transmission of MPEG video data, it occurs severe degradation in quality of service(QOS). In this paper, to solve this problem, we propose two method. The first, we analyze the traffic characteristics of an MPEG encoder and generate high priority and low priority data stream. During network congestion, only the least low priority cells are dropped, and this ensures that the high priority cells are successfully transmitted, which, in turn, guarantees satisfactory QoS. In this case, the prioritization scheme for the encoder assigns components of the data stream to each priority level based on the value of a parameter ${\beta}$. The second, Number of high priority cells are increased when value of ${\beta}$ is large. It occurs the loss of high priority cell in the congestion. To prevent it, this paper is regulated to data stream rate as buffer occupancy with UPC controller. Therefore, encoder's bandwidth can be calculated renegotiation of the encoder and networks. In this paper, the encoder's bandwidth requirements are characterized by a usage parameter control (UPC) set consisting of peak rate, burstness, and sustained rate. An adaptive encoder rate control algorithm at the Networks Interface Card(NIC) computes the necessary UPC parameter to maintain the user specified quality of service. Simulation results are given for a rate-controlled VBR video encoder operating through an ATM network interface which supports dynamic UPC. These results show that dynamic bandwidth renegotiation of prioritized data stream could provided bandwidth saving and significant quality gains which guarantee high priority data stream.

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An Efficient Technique for Processing Frequent Updates in the R-tree (R-트리에서 빈번한 변경 질의 처리를 위한 효율적인 기법)

  • 권동섭;이상준;이석호
    • Journal of KIISE:Databases
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    • v.31 no.3
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    • pp.261-273
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    • 2004
  • Advances in information and communication technologies have been creating new classes of applications in the area of databases. For example, in moving object databases, which track positions of a lot of objects, or stream databases, which process data streams from a lot of sensors, data Processed in such database systems are usually changed very rapidly and continuously. However, traditional database systems have a problem in processing these rapidly and continuously changing data because they suppose that a data item stored in the database remains constant until It is explicitly modified. The problem becomes more serious in the R-tree, which is a typical index structure for multidimensional data, because modifying data in the R-tree can generate cascading node splits or merges. To process frequent updates more efficiently, we propose a novel update technique for the R-tree, which we call the leaf-update technique. If a new value of a data item lies within the leaf MBR that the data item belongs, the leaf-update technique changes the leaf node only, not whole of the tree. Using this leaf-update manner and the leaf-access hash table for direct access to leaf nodes, the proposed technique can reduce update cost greatly. In addition, the leaf-update technique can be adopted in diverse variants of the R-tree and various applications that use the R-tree since it is based on the R-tree and it guarantees the correctness of the R-tree. In this paper, we prove the effectiveness of the leaf-update techniques theoretically and present experimental results that show that our technique outperforms traditional one.

Automatic Extraction of Initial Training Data Using National Land Cover Map and Unsupervised Classification and Updating Land Cover Map (국가토지피복도와 무감독분류를 이용한 초기 훈련자료 자동추출과 토지피복지도 갱신)

  • Soungki, Lee;Seok Keun, Choi;Sintaek, Noh;Noyeol, Lim;Juweon, Choi
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.33 no.4
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    • pp.267-275
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    • 2015
  • Those land cover maps have widely been used in various fields, such as environmental studies, military strategies as well as in decision-makings. This study proposes a method to extract training data, automatically and classify the cover using ingle satellite images and national land cover maps, provided by the Ministry of Environment. For this purpose, as the initial training data, those three were used; the unsupervised classification, the ISODATA, and the existing land cover maps. The class was classified and named automatically using the class information in the existing land cover maps to overcome the difficulty in selecting classification by each class and in naming class by the unsupervised classification; so as achieve difficulty in selecting the training data in supervised classification. The extracted initial training data were utilized as the training data of MLC for the land cover classification of target satellite images, which increase the accuracy of unsupervised classification. Finally, the land cover maps could be extracted from updated training data that has been applied by an iterative method. Also, in order to reduce salt and pepper occurring in the pixel classification method, the MRF was applied in each repeated phase to enhance the accuracy of classification. It was verified quantitatively and visually that the proposed method could effectively generate the land cover maps.

The Distribution of Total Ozone Amounts and Intercomparison of their characteristics Derived from the TOVS Observations over the Korean Peninsula (TOVS로 부터 도출한 한반도 부근의 전오존량 분포 및 그 특성 비교)

  • 정효상;주상원
    • Korean Journal of Remote Sensing
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    • v.11 no.3
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    • pp.23-31
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    • 1995
  • The International TOVS(TIROS Operational Vertical Sounders) Process Package(ITPP-VI), which has been installed at Korea Meteorological Administration(KMA), is only for a global usage to need a surface data to generate atmospheric soundings and total ozone amount. If the initial input process in the ITTP-VI is not modified, it takes climatic surface data for producing sounding data and total ozone amount in general. KMA is trying to improve the quality of TOVS total ozone amount using real-time synoptoc observation in various ways instead of climatological data because this retrieved data in the new scheme for total ozone presently used at the KMA may critically provide to analyze the long-term trend of ozone structure over the Korean peninsula. Two cases in this study show that TOVS retrieved total ozone amounts used by synoptic surface observations can delineate more detailed ozone structures rather than those used by climate surface data. The distribution of TOVS retrieved ozone amount fields with the synoptic surface analyzed data(TOVS-GPV) show more in detail relatively than those with the climate data(TOVS-CLIMAT) as expected. In addition, the collocated inter-comparisons of TOVS-GPV with TOVS-CLIMAT, TOMS observations and Dobsometer observations are performed statistically. TOVS-GPV fields with TOMS observations show smaller bias relatively than TOVS-CLIMAT and also reduce the differences.

Design and Evaluation of a High-performance Key-value Storage for Industrial IoT Environments (산업용 IoT 환경을 위한 고성능 키-값 저장소의 설계 및 평가)

  • Han, Hyuck
    • The Journal of the Korea Contents Association
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    • v.21 no.7
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    • pp.127-133
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    • 2021
  • In industrial IoT environments, sensors generate data for their detection targets and deliver the data to IoT gateways. Therefore, managing large amounts of real-time sensor data is an essential feature for IoT gateways, and key-value storage engines are widely used to manage these sensor data. However, key-value storage engines used in IoT gateways do not take into account the characteristics of sensor data generated in industrial IoT environments, and this limits the performance of key-value storage engines. In this paper, we optimize the key-value storage engine by utilizing the features of sensor data in industrial IoT environments. The proposed optimization technique is to analyze the key, which is the input of a key-value storage engine, for further indexing. This reduces excessive write amplification and improves performance. We implement our optimization scheme in LevelDB and use the workload of the TPCx-IoT benchmark to evaluate our proposed scheme. From experimental results we show that our proposed technique achieves up to 21 times better than the existing scheme, and this shows that the proposed technique can perform high-speed data ingestion in industrial IoT environments.

Unmanned AerialVehicles Images Based Tidal Flat Surface Sedimentary Facies Mapping Using Regression Kriging (회귀 크리깅을 이용한 무인기 영상 기반의 갯벌 표층 퇴적상 분포도 작성)

  • Geun-Ho Kwak;Keunyong Kim;Jingyo Lee;Joo-Hyung Ryu
    • Korean Journal of Remote Sensing
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    • v.39 no.5_1
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    • pp.537-549
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    • 2023
  • The distribution characteristics of tidal flat sediment components are used as an essential data for coastal environment analysis and environmental impact assessment. Therefore, a reliable classification map of surface sedimentary facies is essential. This study evaluated the applicability of regression kriging to generate a classification map of the sedimentary facies of tidal flats. For this aim, various factors such as the number of field survey data and remote sensing-based auxiliary data, the effect of regression models on regression kriging, and the comparison with other prediction methods (univariate kriging and regression analysis) on surface sedimentary facies classification were investigated. To evaluate the applicability of regression kriging, a case study using unmanned aerial vehicle (UAV) data was conducted on the Hwang-do tidal flat located at Anmyeon-do, Taean-gun, Korea. As a result of the case study, it was most important to secure an appropriate amount of field survey data and to use topographic elevation and channel density as auxiliary data to produce a reliable tidal flat surface sediment facies classification map. In addition, regression kriging, which can consider detailed characteristics of the sediment distributions using ultra-high resolution UAV data, had the best prediction performance compared to other prediction methods. It is expected that this result can be used as a guideline to produce the tidal flat surface sedimentary facies classification map.

A Development of Flood Mapping Accelerator Based on HEC-softwares (HEC 소프트웨어 기반 홍수범람지도 엑셀러레이터 개발)

  • Kim, JongChun;Hwang, Seokhwan;Jeong, Jongho
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.44 no.2
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    • pp.173-182
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    • 2024
  • In recent, there has been a trend toward primarily utilizing data-driven models employing artificial intelligence technologies, such as machine learning, for flood prediction. These data-driven models offer the advantage of utilizing pre-training results, significantly reducing the required simulation time. However, it remains that a considerable amount of flood data is necessary for the pre-training in data-driven models, while the available observed data for application is often insufficient. As an alternative, validated simulation results from physically-based models are being employed as pre-training data alongside observed data. In this context, we developed a flood mapping accelerator to generate flood maps for pre-training. The proposed accelerator automates the entire process of flood mapping, i.e., estimating flood discharge using HEC-1, calculating water surface levels using HEC-RAS, simulating channel overflow and generating flood maps using RAS Mapper. With the accelerator, users can easily prepare a database for pre-training of data-driven models from hundreds to tens of thousands of rainfall scenarios. It includes various convenient menus containing a Graphic User Interface(GUI), and its practical applicability has been validated across 26 test-beds.

Estimation of Structural Deterioration of Sewer using Markov Chain Model (마르코프 연쇄 모델을 이용한 하수관로의 구조적 노후도 추정)

  • Kang, Byong Jun;Yoo, Soon Yu;Zhang, Chuanli;Park, Kyoo Hong
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.43 no.4
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    • pp.421-431
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    • 2023
  • Sewer deterioration models can offer important information on prediction of future condition of the asset to decision makers in their implementing sewer pipe networks management program. In this study, Markov chain model was used to estimate sewer deterioration trend based on the historical structural condition assessment data obtained by CCTV inspection. The data used in this study were limited to Hume pipe with diameter of 450 mm and 600 mm in three sub-catchment areas in city A, which were collected by CCTV inspection projects performed in 1998-1999 and 2010-2011. As a result, it was found that sewers in sub-catchment area EM have deteriorated faster than those in other two sub-catchments. Various main defects were to generate in 29% of 450 mm sewers and 38% of 600 mm in 35 years after the installation, while serious failure in 62% of 450 mm sewers and 74% of 600 mm in 100 years after the installation in sub-catchment area EM. In sub-catchment area SN, main defects were to generate in 26% of 450 mm sewers and 35% of 600 mm in 35 years after the installation, while in sub-catchment area HK main defects were to generate in 27% of 450 mm sewers and 37% of 600 mm in 35 years after the installation. Larger sewer pipes of 600 mm were found to deteriorate faster than smaller sewer pipes of 450 mm by about 12 years. Assuming that the percentage of main defects generation could be set as 40% to estimate the life expectancy of the sewers, it was estimated as 60 years in sub-catchment area SN, 42 years in sub-catchment area EM, 59 years in sub-catchment area HK for 450 mm sewer pipes, respectively. For 600 mm sewer pipes, on the other hand, it was estimated as 43 years, 34 years, 39 years in sub-catchment areas SN, EM, and HK, respectively.

Mapping Inundation Areas Using SWMM (SWMM을 이용한 침수예상지도 작성 연구)

  • Don Gon, Choi;Jinmu, Choi
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.33 no.5
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    • pp.335-342
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    • 2015
  • In this study, data linking module called GeoSWMM was developed using a typical secondary flooding model SWMM in order to improve the accuracy of the input data of SWMM and to map hourly inundation estimation areas that were not represented in the conventional inundation map. GeoSWMM is a data linking module of GIS and SWMM, which can generate a SWMM project file directly from sewer network GIS data. Utilizing the GeoSWMM the project file of SWMM model was constructed in the study area, Seocho 2-dong, Seoul. The actual flooding has occurred September 21, 2010 and the actual rainfall data were used for flood simulation. As a result, the outflow started from 2 PM due to the lack of water flow capacity of the sewage system. Based on the results, hourly inundation estimation maps were produced and compared with flood train map in 2010. The comparison showed about 66% matching in the overlap of inundation areas. By utilizing GeoSWMM that was developed in this study, it is easy to build the sewer network data for SWMM. In addition, the creation of hourly inundation estimation map using SWMM will be much help to flood disaster prevention plan.