• Title/Summary/Keyword: measure of structural similarity

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Global Sequence Homology Detection Using Word Conservation Probability

  • Yang, Jae-Seong;Kim, Dae-Kyum;Kim, Jin-Ho;Kim, Sang-Uk
    • Interdisciplinary Bio Central
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    • v.3 no.4
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    • pp.14.1-14.9
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    • 2011
  • Protein homology detection is an important issue in comparative genomics. Because of the exponential growth of sequence databases, fast and efficient homology detection tools are urgently needed. Currently, for homology detection, sequence comparison methods using local alignment such as BLAST are generally used as they give a reasonable measure for sequence similarity. However, these methods have drawbacks in offering overall sequence similarity, especially in dealing with eukaryotic genomes that often contain many insertions and duplications on sequences. Also these methods do not provide the explicit models for speciation, thus it is difficult to interpret their similarity measure into homology detection. Here, we present a novel method based on Word Conservation Score (WCS) to address the current limitations of homology detection. Instead of counting each amino acid, we adopted the concept of 'Word' to compare sequences. WCS measures overall sequence similarity by comparing word contents, which is much faster than BLAST comparisons. Furthermore, evolutionary distance between homologous sequences could be measured by WCS. Therefore, we expect that sequence comparison with WCS is useful for the multiple-species-comparisons of large genomes. In the performance comparisons on protein structural classifications, our method showed a considerable improvement over BLAST. Our method found bigger micro-syntenic blocks which consist of orthologs with conserved gene order. By testing on various datasets, we showed that WCS gives faster and better overall similarity measure compared to BLAST.

A Tracking Method of Same Drug Sales Accounts through Similarity Analysis of Instagram Profiles and Posts

  • Eun-Young Park;Jiyeon Kim;Chang-Hoon Kim
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.2
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    • pp.109-118
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    • 2024
  • With the increasing number of social media users worldwide, cases of social media being abused to perpetrate various crimes are increasing. Specifically, drug distribution through social media is emerging as a serious social problem. Using social media channels, the curiosity of teenagers regarding drugs is stimulated through clever marketing. Further, social media easily facilitates drug purchases due to the high accessibility of drug sellers and consumers. Among various social media platforms, we focused on Instagram, which is the most used social media platform by young adults aged 19 to 24 years in South Korea. We collected four types of information, including profile photos, introductions, posts in the form of images, and posts in the form of texts on Instagram; then, we analyzed the similarity among each type of collected information. The profile photos and posts in the form of image were analyzed for similarity based on the SSIM(Structural Simplicity Index Measure), while introductions and posts in the form of text were analyzed for similarity using Jaccard and Cosine similarity techniques. Through the similarity analysis, the similarity among various accounts for each collected information type was measured, and accounts with similarity above the significance level were determined as the same drug sales account. By performing logistic regression analysis on the aforementioned information types, we confirmed that except posts in image form, profile photos, introductions, and posts in the text form were valid information for tracking the same drug sales account.

Synthetic Infra-Red Image Dataset Generation by CycleGAN based on SSIM Loss Function (SSIM 목적 함수와 CycleGAN을 이용한 적외선 이미지 데이터셋 생성 기법 연구)

  • Lee, Sky;Leeghim, Henzeh
    • Journal of the Korea Institute of Military Science and Technology
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    • v.25 no.5
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    • pp.476-486
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    • 2022
  • Synthetic dynamic infrared image generation from the given virtual environment is being the primary goal to simulate the output of the infra-red(IR) camera installed on a vehicle to evaluate the control algorithm for various search & reconnaissance missions. Due to the difficulty to obtain actual IR data in complex environments, Artificial intelligence(AI) has been used recently in the field of image data generation. In this paper, CycleGAN technique is applied to obtain a more realistic synthetic IR image. We added the Structural Similarity Index Measure(SSIM) loss function to the L1 loss function to generate a more realistic synthetic IR image when the CycleGAN image is generated. From the simulation, it is applicable to the guided-missile flight simulation tests by using the synthetic infrared image generated by the proposed technique.

Designing a Hydro-Structural Ship Model to Experimentally Measure its Vertical Bending and Torsional Vibrations

  • Houtani, Hidetaka;Komoriyama, Yusuke;Matsui, Sadaoki;Oka, Masayoshi;Sawada, Hiroshi;Tanaka, Yoshiteru;Tanizawa, Katsuji
    • Journal of Advanced Research in Ocean Engineering
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    • v.4 no.4
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    • pp.174-184
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    • 2018
  • We herein propose a new design procedure of a flexible container ship model where the vertical bending and torsional vibration modes are similar to its prototype. To achieve similarity in torsional vibration mode shapes, the height of the shear center of the model must be located below the bottom hull, similar to an actual container ship with large opening decks. Therefore, we designed a ship model by imparting appropriate stiffness to the hull, using urethane foam without a backbone. We built a container ship model according to this design strategy and validated its dynamic elastic properties using a decay test. We measured wave-induced structural vibrations and present the results of tank experiments in regular and freak waves.

Image compression using K-mean clustering algorithm

  • Munshi, Amani;Alshehri, Asma;Alharbi, Bayan;AlGhamdi, Eman;Banajjar, Esraa;Albogami, Meznah;Alshanbari, Hanan S.
    • International Journal of Computer Science & Network Security
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    • v.21 no.9
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    • pp.275-280
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    • 2021
  • With the development of communication networks, the processes of exchanging and transmitting information rapidly developed. As millions of images are sent via social media every day, also wireless sensor networks are now used in all applications to capture images such as those used in traffic lights, roads and malls. Therefore, there is a need to reduce the size of these images while maintaining an acceptable degree of quality. In this paper, we use Python software to apply K-mean Clustering algorithm to compress RGB images. The PSNR, MSE, and SSIM are utilized to measure the image quality after image compression. The results of compression reduced the image size to nearly half the size of the original images using k = 64. In the SSIM measure, the higher the K, the greater the similarity between the two images which is a good indicator to a significant reduction in image size. Our proposed compression technique powered by the K-Mean clustering algorithm is useful for compressing images and reducing the size of images.

A Clustering Algorithm Considering Structural Relationships of Web Contents

  • Kang Hyuncheol;Han Sang-Tae;Sun Young-Su
    • Communications for Statistical Applications and Methods
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    • v.12 no.1
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    • pp.191-197
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    • 2005
  • Application of data mining techniques to the world wide web, referred to as web mining, has been the focus of several recent researches. With the explosive growth of information sources available on the world wide web, it has become increasingly necessary to track and analyze their usage patterns. In this study, we introduce a process of pre-processing and cluster analysis on web log data and suggest a distance measure considering the structural relationships between web contents. Also, we illustrate some real examples of cluster analysis for web log data and look into practical application of web usage mining for eCRM.

Tension Measurement of Stay Cables in Consideration with Image Including Vehicle (차량이 포함된 이미지를 고려한 사장재 케이블의 장력 측정 )

  • Sung-Wan Kim;Dong-Uk Park;Jin-Soo Kim;Seung-Su Park;Jae-Bong Park
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.27 no.2
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    • pp.58-66
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    • 2023
  • In this study, cable tension was measured using the vibration method, and a vision-based system was applied as a sensor to measure the displacement response of a cable in a non-contact method. In the vision-based system, the camera is installed in a location that considers the target structure and the field of view of the camera. However, it can be difficult to recognize the control points required to measure the displacement response of a structure as the target structure and other structures such as vehicles may be included in the image at the intended installation location. In this study, a distorted image including a vehicle shows inaccurate results in image analysis due to the installation position of the vision-based system. Accordingly, the image including the vehicle was eliminated by calculating the similarity between the two images. To verify the validity of the method of estimating the cable tension of cable-stayed bridges using the proposed method, the vibration method was applied to cable-stayed bridges in service to measure the tension.

Similarity Measure and Clustering Technique for XML Documents by a Parent-Child Matrix (부모-자식 행렬을 사용한 XML 문서 유사도 측정과 군집 기법)

  • Lee, Yun-Gu;Kim, Woosaeng
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.7
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    • pp.1599-1607
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    • 2015
  • Recently, researches have been developing efficient techniques for accessing, querying, and managing XML documents which are frequently used in the Internet. In this paper, we propose a parent-child matrix to cluster XML documents efficiently. A parent-child matrix analyzes both the content and structural features of an XML document. Each cell of a parent-child matrix has either the value of a node in an XML tree or the value of a child node, where a parent-child relationship exists in the XML tree. Then, the similarity between two XML documents can be measured by the similarity between two corresponding parent-child matrices. The experiment shows that our proposed method has good performance.

Applying the Schema Matching Method to XML Semantic Model of Steelbox-bridge's Structural Calculation Reports (강박스교 구조계산서 XML 시맨틱 모델의 스키마 매칭 기법 적용)

  • Yang Yeong-Ae;Kim Bong-Geun;Lee Sang-Ho
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2005.04a
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    • pp.680-687
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    • 2005
  • This study presents a schema matching technique which can be applied to XML semantic model of structural calculation reports of steel-box bridges. The semantic model of structural calculation documents was developed by extracting the optimized common elements from the analyses of various existing structural calculation documents, and the standardized semantic model was schematized by using XML Schema. In addition, the similarity measure technique and the relaxation labeling technique were employed to develop the schema matching algorithm. The former takes into account the element categories and their features, and the latter considers the structural constraints in the semantic model. The standardized XML semantic model of steel-box bridge's structural calculation documents called target schema was compared with existing nonstandardized structural calculation documents called primitive schema by the developed schema matching algorithm Some application examples show the importance of the development of standardized target schema for structural calculation documents and the effectiveness and efficiency of schema matching technique in the examination of the degree of document standardization in structural calculation reports.

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Multi-level Mapping of Ontologies Based on Lexical and Structural Information (어휘와 구조 정보에 기반한 온톨로지의 다단계 매핑)

  • Hwang, Se-Chan;Kang, Sin-Jae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.22 no.1
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    • pp.42-48
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    • 2012
  • Since the Semantic Web emerged, ontology has been widely used in web environment. Even ontologies belong to the same domain, they may contain same meaning different words, or different meaning same words according to their development background and the type of utilization. In order to share and reuse the ontologies, ontology mapping is required. This paper presents a ontology mapping method that consists of the initial process of multi-level mapping based on lexical information, and the second mapping process using the lexical results and structural similarity. Mapping performance was improved by additionally expanding structural information of blank nodes, which have no lexical information. Through experiments, our method achieved 86.38% in F1-measure.