• Title/Summary/Keyword: Human Similarity

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Protein Structure Alignment Based on Maximum of Residue Pair Distance and Similarity Graph (정렬된 잔기 사이의 최대거리와 유사도 그래프에 기반한 단백질 구조 정렬)

  • Kim, Woo-Cheol;Park, Sang-Hyun;Won, Jung-Im
    • Journal of KIISE:Databases
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    • v.34 no.5
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    • pp.396-408
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    • 2007
  • After the Human Genome Project finished the sequencing of a human DNA sequence, the concerns on protein functions are increasing. Since the structures of proteins are conserved in divergent evolution, their functions are determined by their structures rather than by their amino acid sequences. Therefore, if similarities between two protein structures are observed, we could expect them to have common biological functions. So far, a lot of researches on protein structure alignment have been performed. However, most of them use RMSD(Root Mean Square Deviation) as a similarity measure with which it is hard to judge the similarity level of two protein structures intuitively. In addition, they retrieve only one result having the highest alignment score with which it is hard to satisfy various users of different purpose. To overcome these limitations, we propose a novel protein structure alignment algorithm based on MRPD(Maximum of Residue Pair Distance) and SG (Similarity Graph). MRPD is more intuitive similarity measure by which fast tittering of unpromising pairs of protein pairs is possible, and SG is a compact representation method for multiple alignment results with which users can choose the most plausible one among various users' needs by providing multiple alignment results without compromising the time to align protein structures.

Development of a Batch-mode-based Comparison System for 3D Piping CAD Models of Offshore Plants (Aveva Marine과 SmartMarine 3D간의 해양 플랜트 3D 배관 CAD 모델의 배치모드 기반 비교 시스템 개발)

  • Lee, Jaesun;Kim, Byung Chul;Cheon, Sanguk;Cho, Mincheol;Lee, Gwang;Mun, Duhwan
    • Korean Journal of Computational Design and Engineering
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    • v.21 no.1
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    • pp.78-89
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    • 2016
  • When a plant owner requests plant 3D CAD models in the format that a shipbuilding company does not use, the shipyard manually re-models plant 3D CAD models according to the owner's requirement. Therefore, it is important to develop a technology to compare the re-modeled plant 3D CAD models with original ones and to quantitatively evaluate similarity between two models. In the previous study, we developed a graphic user interface (GUI)-based comparison system where a user evaluates similarity between original and re-modeled plant 3D CAD models for piping design at the level of unit. However, an offshore plant consists of thousands of units and thus a system which compares several plant 3D CAD models at unit-level without human intervention is necessary. For this, we developed a new batch model comparison system which automatically evaluates similarity of several unit-level plant 3D CAD models using an extensible markup language (XML) file storing file location and name data about a set of plant 3D CAD models. This paper suggests system configuration of a batch-mode-based comparison system and discusses its core functions. For the verification of the developed system, comparison experiments for offshore plant 3D piping CAD models using the system were performed. From the experiments, we confirmed that similarities for several plant 3D CAD models at unit-level were evaluated without human intervention.

Image Quality Assessment Considering both Computing Speed and Robustness to Distortions (계산 속도와 왜곡 강인성을 동시 고려한 이미지 품질 평가)

  • Kim, Suk-Won;Hong, Seongwoo;Jin, Jeong-Chan;Kim, Young-Jin
    • Journal of KIISE
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    • v.44 no.9
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    • pp.992-1004
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    • 2017
  • To assess image quality accurately, an image quality assessment (IQA) metric is required to reflect the human visual system (HVS) properly. In other words, the structure, color, and contrast ratio of the image should be evaluated in consideration of various factors. In addition, as mobile embedded devices such as smartphone become popular, a fast computing speed is important. In this paper, the proposed IQA metric combines color similarity, gradient similarity, and phase similarity synergistically to satisfy the HVS and is designed by using optimized pooling and quantization for fast computation. The proposed IQA metric is compared against existing 13 methods using 4 kinds of evaluation methods. The experimental results show that the proposed IQA metric ranks the first on 3 evaluation methods and the first on the remaining method, next to VSI which is the most remarkable IQA metric. Its computing speed is on average about 20% faster than VSI's. In addition, we find that the proposed IQA metric has a bigger amount of correlation with the HVS than existing IQA metrics.

Automatic Music Summarization Using Vector Quantization and Segment Similarity

  • Kim, Sang-Ho;Kim, Sung-Tak;Kim, Hoi-Rin
    • The Journal of the Acoustical Society of Korea
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    • v.27 no.2E
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    • pp.51-56
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    • 2008
  • In this paper, we propose an effective method for music summarization which automatically extracts a representative part of the music by using signal processing technology. Proposed method uses a vector quantization technique to extract several segments which can be regarded as the most important contents in the music. In general, there is a repetitive pattern in music, and human usually recognizes the most important or catchy tune from the repetitive pattern. Thus the repetition which is extracted using segment similarity is considered to express a music summary. The segments extracted are again combined to generate a complete music summary. Experiments show the proposed method captures the main theme of the music more effectively than conventional methods. The experimental results also show that the proposed method could be used for real-time application since the processing time in generating music summary is much faster than other methods.

Livestock Theft Detection System Using Skeleton Feature and Color Similarity (골격 특징 및 색상 유사도를 이용한 가축 도난 감지 시스템)

  • Kim, Jun Hyoung;Joo, Yung Hoon
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.67 no.4
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    • pp.586-594
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    • 2018
  • In this paper, we propose a livestock theft detection system through moving object classification and tracking method. To do this, first, we extract moving objects using GMM(Gaussian Mixture Model) and RGB background modeling method. Second, it utilizes a morphology technique to remove shadows and noise, and recognizes moving objects through labeling. Third, the recognized moving objects are classified into human and livestock using skeletal features and color similarity judgment. Fourth, for the classified moving objects, CAM (Continuously Adaptive Meanshift) Shift and Kalman Filter are used to perform tracking and overlapping judgment, and risk is judged to generate a notification. Finally, several experiments demonstrate the feasibility and applicability of the proposed method.

Incoming and Outgoing Human Matching Using Similarity Metrics for Occupancy Sensor (점유센서를 위한 유사성 메트릭 기반 입출입 사람 매칭)

  • Jung, Jaejune;Kim, Manbae
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2018.11a
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    • pp.33-35
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    • 2018
  • 기존의 사람간의 유사성 측정 시스템은 적외선 빔이나 열 감지 영상 장치를 통해 측정하였다. 하지만 이와 같은 방법으로 측정하면 2명 이상의 객체를 분류해내는 기술은 제공하지 않는다. 이에 본 논문은 고정된 카메라를 이용하여 각 사람의 피부색과 옷차림 등의 RGB 정보를 이용한 사람 유사성 측정 기법을 제안한다. RGB카메라 영상을 통하여 객체의 RGB 히스토그램을 얻은 후 각 객체에 대해 Bhattacharyya metric, Cosine similarity, Jensen difference, Euclidean distance로 histogram similarity를 계산하여 객체 추적 및 유사성 측정을 통해 객체를 분류한다. 제안된 시스템은 C/C++를 기반으로 구현하여, 유사성 측정 성능을 평가하였다.

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Baggage Recognition in Occluded Environment using Boosting Technique

  • Khanam, Tahmina;Deb, Kaushik
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.11
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    • pp.5436-5458
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    • 2017
  • Automatic Video Surveillance System (AVSS) has become important to computer vision researchers as crime has increased in the twenty-first century. As a new branch of AVSS, baggage detection has a wide area of security applications. Some of them are, detecting baggage in baggage restricted super shop, detecting unclaimed baggage in public space etc. However, in this paper, a detection & classification framework of baggage is proposed. Initially, background subtraction is performed instead of sliding window approach to speed up the system and HSI model is used to deal with different illumination conditions. Then, a model is introduced to overcome shadow effect. Then, occlusion of objects is detected using proposed mirroring algorithm to track individual objects. Extraction of rotational signal descriptor (SP-RSD-HOG) with support plane from Region of Interest (ROI) add rotation invariance nature in HOG. Finally, dynamic human body parameter setting approach enables the system to detect & classify single or multiple pieces of carried baggage even if some portions of human are absent. In baggage detection, a strong classifier is generated by boosting similarity measure based multi layer Support Vector Machine (SVM)s into HOG based SVM. This boosting technique has been used to deal with various texture patterns of baggage. Experimental results have discovered the system satisfactorily accurate and faster comparative to other alternatives.

Characterization of Binding Mode for Human Coagulation Factor XI (FXI) Inhibitors

  • Cho, Jae Eun;Kim, Jun Tae;Jung, Seo Hee;Kang, Nam Sook
    • Bulletin of the Korean Chemical Society
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    • v.34 no.4
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    • pp.1212-1220
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    • 2013
  • The human coagulation factor XI (FXI) is a serine protease that plays a significant role in blocking of the blood coagulation cascade as an attractive antithrombotic target. Selective inhibition of FXIa (an activated form of factor XI) disrupts the intrinsic coagulation pathway without affecting the extrinsic pathway or other coagulation factors such as FXa, FIIa, FVIIa. Furthermore, targeting the FXIa might significantly reduce the bleeding side effects and improve the safety index. This paper reports on a docking-based three dimensional quantitative structure activity relationship (3D-QSAR) study of the potent FXIa inhibitors, the chloro-phenyl tetrazole scaffold series, using comparative molecular field analysis (CoMFA) and comparative molecular similarity analysis (CoMSIA) methods. Due to the characterization of FXIa binding site, we classified the alignment of the known FXIa inhibitors into two groups according to the docked pose: S1-S2-S4 and S1-S1'-S2'. Consequently, highly predictive 3D-QSAR models of our result will provide insight for designing new potent FXIa inhibitors.

Mornitoring and Identification of Human Astrovirus from Groundwater in Korea Based on Highly Sensitive RT-nested PCR Primer Sets

  • Lee, Siwon;Bae, Kyung Seon;Park, Jihyun;Kim, Jin-Ho;Lee, Jin-Young;Choi, Jiwon;Park, Eung-Roh;You, Kyung-A
    • Biomedical Science Letters
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    • v.27 no.4
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    • pp.255-263
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    • 2021
  • Human Astrovirus (HuAstV) is an important gastrointestinal pathogen that is frequently reported worldwide. Monitoring of contaminated groundwater has been suggested since HuAstV is transmitted through the fecal-oral route. This study developed a test method based on conventional reverse transcription (RT)-nested polymerase chain reaction (PCR) that involves SL® non-specific reaction inhibitor for unknown non-specific amplification taking place in the groundwater environment. An optimal method for detecting HuAstV in groundwater sample through analysis and comparison against conventionally reported method was also suggested. The developed method enabled the production of nested PCR amplicon of 630 nt, which is a sufficient length for similarity analysis based on sequencing and genotyping. Amplicons suspected to be HuAstV were amplified in two out of the twenty groundwater samples collected in Korea, presenting 99.77% and 99.73% similarity against HuAstV 1 strain lhar/2011/kor (JN887820.1) in sequencing, respectively. These amplicons were identified as HuAstV 1.

Natural Color Recognition algorithm Based on Fuzzy Similarity Measure (퍼지 유사도 평가를 이용한 천연색상 인식 알고리듬)

  • Kim, Youn-Tae;Kim, Sung-Shin
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • v.9 no.2
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    • pp.1123-1127
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    • 2005
  • The Conventional methods of color separation in computer-based machine vision offer only weak performance because of environmental factors such as light source, camera sensitivity, and others. In this paper, we propose an improved color separation method using RGB, HLS, color coordination space, and fuzzy similarity measure. RGB consists of red, green and blue, the three primary colors of light. HLS includes hue, light and saturation, the human recognition elements of co]or. A fuzzy similarity measure was employed for evaluate the similarity among fuzzy colors with the six features of RGB and HLS.

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