• Title/Summary/Keyword: merging techniques

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Logic Synthesis Algorithm for TLU-Type FPGA (TLU형 FPGA를 위한 기술 매핑 알고리즘)

  • Park, Jang-Hyeon;Kim, Bo-Gwan
    • The Transactions of the Korea Information Processing Society
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    • v.2 no.5
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    • pp.777-786
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    • 1995
  • This paper describes several algorithms for technology mapping of logic functions into interesting and popular FPGAs that use look-up table memories. In order to improve the technology mapping for FPGA, some existing multi-level logic synthesis, decomposition reduction and packing techniques are analyzed and compared. And then new algorithms such as node-pair decomposition, merging fanin, unified reduction and multiple output decomposition which are used for combinational logic design, are proposed. The cost function is used to minimize the number of CLBs and edges of the network. The cost is a linear combination of each weight that is given by user. Finally we compare our new algorithm with previous logic design technique[8]. In an experimental comparison our algorithm requires 10% fewer CLB and nets than SIS-pga.

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The Map Generalization Methodology for Korean Cadastral Map using Topographic Map (수치지형도를 이용한 연속지적도의 지도 일반화 기법 연구)

  • Park, Woo-Jin;Lee, Jae-Eun;Yu, Ki-Yun
    • Spatial Information Research
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    • v.19 no.1
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    • pp.73-82
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    • 2011
  • Recently, demand for the use of cadastral map is increasing in both public and private area. To use cadastral map in web or mobile environment, construction of the multi-representation database(MRDB) that is the compressed into multiple scale from the original map data is recommended. In this study, the map generalization methodology for the cadastral map by applying overlay with topographic map and polygon generalization technique is suggested. This process is composed of three steps, re-constructing the network data of topographic map, polygon merging of parcel lines according to network degree, and applying line simplification techniques. Proposed methodologies are applied to the cadastral map in Suwon area. The result map was generalized into 1:5,000, 1:20,000, 1:100,000 scale, and data compression ratio was shown in 15% 8% 1% level respectively.

A Study on the Interactive Ship Compartmentation Modelling Technique Using Graphical User Interface (그래픽 지원 대화식 구획배치 모델링에 관한 연구)

  • W.S. Kang;K.Y. Lee
    • Journal of the Society of Naval Architects of Korea
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    • v.31 no.4
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    • pp.23-31
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    • 1994
  • The compartmentation model is represented by the characteristics and geometric information of the spaces defined by the structural members which are used for the boundary planes of the compartment. For the efficient compartment modeling a program performing the compartmentation design by the chopping and merging method was presented by authors. In this research, the development of an interactive ship compartmentation modeller is introduced. It is natural that the value of the program lessens if the input process is complicated and uneasy, even though the internal techniques for the compartmentation modeling are superior. In this paper, a method for the convenient input is proposed and implemented with the help of a graphical user interface technique. The modeling method introduced in this paper performs an efficient compartmentation modeling fast and conveniently by the solid modeling concept and the graphical user interface.

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AN EFFICIENT IMAGE SEGMENTATION TECHNIQUE TO IDENTIFY TARGET AREAS FROM LARGE-SIZED MONOCHROME IMAGES

  • Yoon Young-Geun;Lee Seok-Lyong;park Ho-Hyun;Chung Chin-Wan
    • Proceedings of the KSRS Conference
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    • 2005.10a
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    • pp.571-574
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    • 2005
  • In this paper, we propose an efficient image segmentation technique for large-sized monochrome images using a hybrid approach which combines threshold and region-based techniques. First, an image is partitioned into fixed-size blocks and for each block the representative intensity is determined by averaging pixel intensities within the block. Next, the neighborhood blocks that have similar characteristics with respect to a specific threshold are merged in order to form candidate regions. Finally, those candidate regions are refined to get final target object regions by merging regions considering the spatial locality and certain criteria. We have performed experiments on images selected from various domains and showed that our technique was able to extract target object regions appropriately from most images.

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Logic synthesis for TLU-type FPGA (TLU형 FPGA를 위한 논리 설계 알고리즘)

  • 박장현;김보관
    • Journal of the Korean Institute of Telematics and Electronics A
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    • v.33A no.10
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    • pp.177-185
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    • 1996
  • This paper describes several algorithms for technolgoy mapping of logic functions into interesting and popular FPGAs that use look-up table memories. In order to improved the technology mapping for FPGA, some existing multi-level logic synthesis, decomposition reduction and packing techniques are analyzed and compared. And then new algorithms such as merging fanin, unified reduction and multiple disjoint decomposition which are used for combinational logic design, are proposed. The cost function is used to minimize the number of CLBs and edges of the network. The cost is a linear combination of each weight that is given by user. Finally we compare our new algorithm with previous logic design technique. In an experimental comparison our algorithm requires 10% fewer CLB and nets than SIS-pga.

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A Study on Feature Information Parsing System of Video Image for Multimedia Service (멀티미디어 서비스를 위한 동영상 이미지의 특징정보 분석 시스템에 관한 연구)

  • 이창수;지정규
    • Journal of Information Technology Applications and Management
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    • v.9 no.3
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    • pp.1-12
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    • 2002
  • Due to the fast development in computer and communication technologies, a video is now being more widely used than ever in many areas. The current information analyzing systems are originally built to process text-based data. Thus, it has little bits problems when it needs to correctly represent the ambiguity of a video, when it has to process a large amount of comments, or when it lacks the objectivity that the jobs require. We would like to purpose an algorithm that is capable of analyze a large amount of video efficiently. In a video, divided areas use a region growing and region merging techniques. To sample the color, we translate the color from RGB to HSI and use the information that matches with the representative colors. To sample the shape information, we use improved moment invariants(IMI) so that we can solve many problems of histogram intersection caused by current IMI and Jain. Sampled information on characteristics of the streaming media will be used to find similar frames.

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Toxicogenomic Assessment of Drugs-Induced Hepatotoxicity

  • Park, Joon-Suk;Hwang, Jae-Woong;Lee, Yong-Soon;Hwang, Seung-Yong;Jung, Jin-Wook;Kang, Jong-Soo;Lee, Gyoung-Jae;Lee, Wan-Seon;Jeon, Ki-Seon;Kang, Kyung-Sun
    • Proceedings of the Korean Society of Toxicology Conference
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    • 2003.05a
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    • pp.48-49
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    • 2003
  • Toxicogenomics is a term that represents the merging of toxicology with novel genomics techniques. Microarray, which provides a revolutionary basis to perform global gene expression analyses and to decode biological pathways, has begun to have a major impact on many different fields of drug discovery and development. (omitted)

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Application of Genetic and Local Optimization Algorithms for Object Clustering Problem with Similarity Coefficients (유사성 계수를 이용한 군집화 문제에서 유전자와 국부 최적화 알고리듬의 적용)

  • Yim, Dong-Soon;Oh, Hyun-Seung
    • Journal of Korean Institute of Industrial Engineers
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    • v.29 no.1
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    • pp.90-99
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    • 2003
  • Object clustering, which makes classification for a set of objects into a number of groups such that objects included in a group have similar characteristic and objects in different groups have dissimilar characteristic each other, has been exploited in diverse area such as information retrieval, data mining, group technology, etc. In this study, an object-clustering problem with similarity coefficients between objects is considered. At first, an evaluation function for the optimization problem is defined. Then, a genetic algorithm and local optimization technique based on heuristic method are proposed and used in order to obtain near optimal solutions. Solutions from the genetic algorithm are improved by local optimization techniques based on object relocation and cluster merging. Throughout extensive experiments, the validity and effectiveness of the proposed algorithms are tested.

MOSAICFUSION: MERGING MODALITIES WITH PARTIAL DIFFERENTIAL EQUATION AND DISCRETE COSINE TRANSFORMATION

  • GARGI TRIVEDI;RAJESH SANGHAVI
    • Journal of Applied and Pure Mathematics
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    • v.5 no.5_6
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    • pp.389-406
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    • 2023
  • In the pursuit of enhancing image fusion techniques, this research presents a novel approach for fusing multimodal images, specifically infrared (IR) and visible (VIS) images, utilizing a combination of partial differential equations (PDE) and discrete cosine transformation (DCT). The proposed method seeks to leverage the thermal and structural information provided by IR imaging and the fine-grained details offered by VIS imaging create composite images that are superior in quality and informativeness. Through a meticulous fusion process, which involves PDE-guided fusion, DCT component selection, and weighted combination, the methodology aims to strike a balance that optimally preserves essential features and minimizes artifacts. Rigorous evaluations, both objective and subjective, are conducted to validate the effectiveness of the approach. This research contributes to the ongoing advancement of multimodal image fusion, addressing applications in fields like medical imaging, surveillance, and remote sensing, where the marriage of IR and VIS data is of paramount importance.

Transformer-based reranking for improving Korean morphological analysis systems

  • Jihee Ryu;Soojong Lim;Oh-Woog Kwon;Seung-Hoon Na
    • ETRI Journal
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    • v.46 no.1
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    • pp.137-153
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    • 2024
  • This study introduces a new approach in Korean morphological analysis combining dictionary-based techniques with Transformer-based deep learning models. The key innovation is the use of a BERT-based reranking system, significantly enhancing the accuracy of traditional morphological analysis. The method generates multiple suboptimal paths, then employs BERT models for reranking, leveraging their advanced language comprehension. Results show remarkable performance improvements, with the first-stage reranking achieving over 20% improvement in error reduction rate compared with existing models. The second stage, using another BERT variant, further increases this improvement to over 30%. This indicates a significant leap in accuracy, validating the effectiveness of merging dictionary-based analysis with contemporary deep learning. The study suggests future exploration in refined integrations of dictionary and deep learning methods as well as using probabilistic models for enhanced morphological analysis. This hybrid approach sets a new benchmark in the field and offers insights for similar challenges in language processing applications.