• Title/Summary/Keyword: 입력처리 지도

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A Study on field-watershed integrated model for assessing water quality impact in agricultural small watershed (농업 소유역에서 수질영향 평가를 위한 포장-유역 연계모형의 기초연구)

  • Kim, Dong Hyeon;So, Hyun Chul;Jang, Taeil
    • Proceedings of the Korea Water Resources Association Conference
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    • 2018.05a
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    • pp.491-491
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    • 2018
  • 본 연구는 포장모형(APEX, Agricultural Policy Environmental eXtender)과 유역모형(SWAT, Soil and Water Assessment Tool)을 연계하여 새만금 유역의 미래 수문 수질영향과 용수생산성을 분석하기 위한 기초연구이다. APEX 모형을 연계하기에 앞서 SWAT 모형을 이용하여 만경강 유역의 유출량, T-N, T-P를 모의하고 그 적용성을 평가하였다. 모의 기간은 2004년부터 2017년까지 총 14년이며, 기상, 유출량 그리고 월단위 수질 자료를 모형의 입력자료 및 보정을 위해 사용하였다. 매개변수 보정은 객관적 보정이 가능한 SWAT-CUP을 이용하여 최적화 하였으며, 매개변수 보정의 목적함수는 NSE(Nash-Sutcliffe Efficiency)로 평가하였다. 모형의 적용성 평가 결과, 보정기간의 연평균 유출량은 실측치 835mm, 모의치 677mm로 나타났고, R2는 0.64, RMSE는 3.87mm/day, NSE는 0.61, RMAE는 0.99로 나타났다. 검정기간의 연평균 유출량은 실측치 884mm, 모의치 702mm로 나타났고, R2는 0.67, RMSE는 2.92mm/day, NSE는 0.7, RMAE는 0.94로 나타났다. 유출량의 결과를 살펴보면 검정기간이 보정기간보다 모의결과가 더 나은 것으로 나타나며, 이는 실측자료의 일관성 차이로 판단된다. T-N과 T-P의 경우 매개변수만으론 보정의 한계가 있으며, 실측치와 근접하게 모의하기 위해서 만경강 본류에 영향을 끼칠 수 있는 외부유입량을 고려할 필요가 있다. 따라서 본 연구에서는 만경강 상류의 경천댐, 대아댐 그리고 용담댐으로 부터 유입되는 외부유입량 자료를 수집하여 SWAT의 입력자료로 구축하였으며, 대상유역 내 익산, 완주, 전주, 김제에 위치하고 있는 하수처리장, 축산폐수처리장, 분뇨처리시설, 산업폐수처리시설 그리고 농공단지처리시설 등 총 12곳에 대한 점오염원 데이터를 입력자료로 구축하여 만경강 상류 농업소유역의 수질영향을 평가하였다. 본 연구결과는 향후 미래 수문 수질 모의에 대한 기초자료로 제공될 것이며, 외부유입량을 고려한 만경강 유역의 용수생산성 분석을 통해 미래 농업수자원 관리계획 수립에 활용할 수 있을 것이다.

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Design of a Variable-Mode Sync Generator for Implementing Digital Filters in Image Processing (이미지처리에서 디지털 필터를 구현하기 위한 가변모드 동기 발생기의 설계)

  • Semin Jung;Si-Yeon Han;Bongsoon Kang
    • Journal of IKEEE
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    • v.27 no.3
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    • pp.273-279
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    • 2023
  • The use of line memory is essential for image filtering in image processing hardware. After input data is stored in line memory, filtering is performed after synchronization to use the stored data. A sync generator is used for synchronization, and in the case of a conventional sync generator, the input sync signal is delayed by one row of the input image. If a signal delayed by two rows is required, it is necessary to connect two modules. This approach increases the size of the hardware and cannot be designed efficiently. In this paper, we propose a sync generator that generates multiple types of delayed signals by adding a finite state machine. The hardware design was coded in Verilog HDL, and performance is verified by applying it to image processing hardware using field programmable gate array board.

Data Stream Storing Techniques for Supporting Hybrid Query (하이브리드 질의를 위한 데이터 스트림 저장 기술)

  • Shin, Jae-Jyn;You, Byeong-Seob;Eo, Sang-Hun;Lee, Dong-Wook;Bae, Hae-Young
    • Journal of Korea Multimedia Society
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    • v.10 no.11
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    • pp.1384-1397
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    • 2007
  • This paper proposes fast storage techniques for hybrid query of data streams. DSMS(Data Stream Management System) have been researched for processing data streams that have busting income. To process hybrid query that retrieve both current incoming data streams and past data streams data streams have to be stored into disk. But due to fast input speed of data stream and memory and disk space limitation, the main research is not about querying to stored data streams but about querying to current incoming data streams. Proposed techniques of this paper use circular buffer for maximizing memory utility and for make non blocking insertion possible. Data in a disk is compressed to maximize the number of data in the disk. Through experiences, proposed technique show that bursting insertion is stored fast.

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Speaker-Adaptive Speech Synthesis based on Fuzzy Vector Quantizer Mapping and Neural Networks (퍼지 벡터 양자화기 사상화와 신경망에 의한 화자적응 음성합성)

  • Lee, Jin-Yi;Lee, Gwang-Hyeong
    • The Transactions of the Korea Information Processing Society
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    • v.4 no.1
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    • pp.149-160
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    • 1997
  • This paper is concerned with the problem of speaker-adaptive speech synthes is method using a mapped codebook designed by fuzzy mapping on FLVQ (Fuzzy Learning Vector Quantization). The FLVQ is used to design both input and reference speaker's codebook. This algorithm is incorporated fuzzy membership function into the LVQ(learning vector quantization) networks. Unlike the LVQ algorithm, this algorithm minimizes the network output errors which are the differences of clas s membership target and actual membership values, and results to minimize the distances between training patterns and competing neurons. Speaker Adaptation in speech synthesis is performed as follow;input speaker's codebook is mapped a reference speaker's codebook in fuzzy concepts. The Fuzzy VQ mapping replaces a codevector preserving its fuzzy membership function. The codevector correspondence histogram is obtained by accumulating the vector correspondence along the DTW optimal path. We use the Fuzzy VQ mapping to design a mapped codebook. The mapped codebook is defined as a linear combination of reference speaker's vectors using each fuzzy histogram as a weighting function with membership values. In adaptive-speech synthesis stage, input speech is fuzzy vector-quantized by the mapped codcbook, and then FCM arithmetic is used to synthesize speech adapted to input speaker. The speaker adaption experiments are carried out using speech of males in their thirties as input speaker's speech, and a female in her twenties as reference speaker's speech. Speeches used in experiments are sentences /anyoung hasim nika/ and /good morning/. As a results of experiments, we obtained a synthesized speech adapted to input speaker.

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Fine-tuning BERT-based NLP Models for Sentiment Analysis of Korean Reviews: Optimizing the sequence length (BERT 기반 자연어처리 모델의 미세 조정을 통한 한국어 리뷰 감성 분석: 입력 시퀀스 길이 최적화)

  • Sunga Hwang;Seyeon Park;Beakcheol Jang
    • Journal of Internet Computing and Services
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    • v.25 no.4
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    • pp.47-56
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    • 2024
  • This paper proposes a method for fine-tuning BERT-based natural language processing models to perform sentiment analysis on Korean review data. By varying the input sequence length during this process and comparing the performance, we aim to explore the optimal performance according to the input sequence length. For this purpose, text review data collected from the clothing shopping platform M was utilized. Through web scraping, review data was collected. During the data preprocessing stage, positive and negative satisfaction scores were recalibrated to improve the accuracy of the analysis. Specifically, the GPT-4 API was used to reset the labels to reflect the actual sentiment of the review texts, and data imbalance issues were addressed by adjusting the data to 6:4 ratio. The reviews on the clothing shopping platform averaged about 12 tokens in length, and to provide the optimal model suitable for this, five BERT-based pre-trained models were used in the modeling stage, focusing on input sequence length and memory usage for performance comparison. The experimental results indicated that an input sequence length of 64 generally exhibited the most appropriate performance and memory usage. In particular, the KcELECTRA model showed optimal performance and memory usage at an input sequence length of 64, achieving higher than 92% accuracy and reliability in sentiment analysis of Korean review data. Furthermore, by utilizing BERTopic, we provide a Korean review sentiment analysis process that classifies new incoming review data by category and extracts sentiment scores for each category using the final constructed model.

Dynamic Load Management Method for Spatial Data Stream Processing on MapReduce Online Frameworks (맵리듀스 온라인 프레임워크에서 공간 데이터 스트림 처리를 위한 동적 부하 관리 기법)

  • Jeong, Weonil
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.19 no.8
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    • pp.535-544
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    • 2018
  • As the spread of mobile devices equipped with various sensors and high-quality wireless network communications functionsexpands, the amount of spatio-temporal data generated from mobile devices in various service fields is rapidly increasing. In conventional research into processing a large amount of real-time spatio-temporal streams, it is very difficult to apply a Hadoop-based spatial big data system, designed to be a batch processing platform, to a real-time service for spatio-temporal data streams. This paper extends the MapReduce online framework to support real-time query processing for continuous-input, spatio-temporal data streams, and proposes a load management method to distribute overloads for efficient query processing. The proposed scheme shows a dynamic load balancing method for the nodes based on the inflow rate and the load factor of the input data based on the space partition. Experiments show that it is possible to support efficient query processing by distributing the spatial data stream in the corresponding area to the shared resources when load management in a specific area is required.

Image Enhancement Method Research for Face Detection (얼굴 검출을 위한 영상 향상 방법 연구)

  • Jun, In-Ja;Chung, Kyung-Yong
    • The Journal of the Korea Contents Association
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    • v.9 no.10
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    • pp.13-21
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    • 2009
  • This paper describes research of image enhancement for detection of face area. Typical face recognition algorithms used fixed parameter filtering algorithms to optimize face images for the recognition process. A fixed filtering scheme introduces errors when applied to face images captured in various different environmental conditions. For acquiring face image of good quality from the image including complex background and illumination, we propose a method for image enhancement using the categories based on the image intensity values. When an image is acquired average values of image from sub-window are computed and then compared to training values that were computed during preprocessing. The category is selected and the most suitable image filter method is applied to the image. We used histogram equalization, and gamma correction filters with two different parameters, and then used the most suitable filter among those three. An increase in enrollment of filtered images was observed compared to enrollment rates of the original images.

Effective Object Recognition based on Physical Theory in Medical Image Processing (의료 영상처리에서의 물리적 이론을 활용한 객체 유효 인식 방법)

  • Eun, Sung-Jong;WhangBo, Taeg-Keun
    • The Journal of the Korea Contents Association
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    • v.12 no.12
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    • pp.63-70
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    • 2012
  • In medical image processing field, object recognition is usually processed based on region segmentation algorithm. Region segmentation in the computing field is carried out by computerized processing of various input information such as brightness, shape, and pattern analysis. If the information mentioned does not make sense, however, many limitations could occur with region segmentation during computer processing. Therefore, this paper suggests effective region segmentation method based on R2-map information within the magnetic resonance (MR) theory. In this study, the experiment had been conducted using images including the liver region and by setting up feature points of R2-map as seed points for 2D region growing and final boundary correction to enable region segmentation even when the border line was not clear. As a result, an average area difference of 7.5%, which was higher than the accuracy of conventional exist region segmentation algorithm, was obtained.

Design and Implementation XML parser for Mobile GIS based on GVM (GVM 기반 모바일 GIS를 위한 XML 파서의 설계 및 구현)

  • Nam, Dong-Geun;Na, Seung-Won;Oh, Se-Man
    • Proceedings of the Korea Information Processing Society Conference
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    • 2002.11c
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    • pp.2277-2280
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    • 2002
  • 1995년 이후 NGIS(National Geographic Information System) 사업의 시작과 함께 활성화되기 시작한 GIS는 1990 년대 말 인터넷의 급속한 보급으로 인하여 비약적인 발전을 거듭하였다. 최근에는 무선 인터넷의 확산과 함께 모바일 GIS가 등장하였으며, OGC(Open GIS Consortium)에서는 효율적인 지리정보의 저장과 전달을 위해 GML(Geographic Markup Language)을 제안하였다. 본 논문에서는 GVM(General Virtual Machine)기반의 모바일 디바이스에서 GML 문서를 처리하기 위한 XML 파서와 맵매니저(MapManager)를 설계하고 구현하였다. XML 파서는 서버로부터 GML문서를 다운로드 받아서 파싱과정을 거쳐서 DOM(Document Object Model)형태의 자료구조를 생성한다. 맵매니저는 DOM 구조를 입력으로 받아서 모바일 디바이스의 화면에 지도를 표시하고, 사용자 상호작용을 처리한다.

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Semantic schema data processing using cache mechanism (캐쉬메카니즘을 이용한 시맨틱 스키마 데이터 처리)

  • Kim, Byung-Gon;Oh, Sung-Kyun
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.3
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    • pp.89-97
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    • 2011
  • In semantic web information system like ontology that access distributed information from network, efficient query processing requires an advanced caching mechanism to reduce the query response time. P2P network system have become an important infra structure in web environment. In P2P network system, when the query is initiated, reducing the demand of data transformation to source peer is important aspect of efficient query processing. Caching of query and query result takes a particular advantage by adding or removing a query term. Many of the answers may already be cached and can be delivered to the user right away. In web environment, semantic caching method has been proposed which manages the cache as a collection of semantic regions. In this paper, we propose the semantic caching technique in cluster environment of peers. Especially, using schema data filtering technique and schema similarity cache replacement method, we enhanced the query processing efficiency.