• Title/Summary/Keyword: expression mapping

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Implementation of Real-time VJing System for Live Projection Mapping Performance (라이브 프로젝션 매핑 공연을 위한 실시간 VJing 시스템 구현)

  • Noh, Seon;Lee, Jaejoong;Park, Jin Wan
    • The Journal of the Korea Contents Association
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    • v.13 no.6
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    • pp.55-66
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    • 2013
  • In these days, small devices like smartphones, TV, and projectors are popular, and they are being developed rapidly. The projector is being used in cinema and exhibition because it makes a big screen. This feature makes new expression named projection-mapping in art world. Projection-mapping is being utilized extensively in stages of performances, and it use variety of shape's screens. But projection-mapping has limitation in space. So in this paper, we propose new performance system for projection-mapping and it make possible to overcome many difficulties. Also, we discuss the result of using the system in actual performance. We hope to develop the utilization of projection-mapping in performance.

Prospects of Application of Linkage Disequilibrium Mapping for Crop Improvement in Wild Silkworm (Antheraea mylitta Drury)

  • Vijayan, Kunjupillai;Singh, Ravindra Nath;Saratchandra, Beera
    • International Journal of Industrial Entomology and Biomaterials
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    • v.20 no.2
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    • pp.37-43
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    • 2010
  • The wild silkworm, Antheraea mylitta Drury (Lepidoptera: Saturniidae) is a polyphagous silk producing insect that feeds on Terminalia arjuna, T. tomentosa and Shorea robusta and is distributed in the forest belts in different states of India. Phenotypically distinct populations of the A. mylitta are called "eco-race" or "ecotypes". Genetic improvement of this wild silkworm has not progressed much due to lack of adequate information on the factors that control the expression of most of the economically important traits. Considering the amazing technological advances taking place in molecular biology, it is envisaged that it is now possible to take greater control on these intractable traits if a combination of genetic, molecular and bioinformatics tools are used. Linkage disequilibrium (LD) mapping is one such approach that has extensively been used in both animal and plant system to identify quantitative trait loci (QTLs) for a number of economically important traits. LD mapping has a number of advantages over conventional biparental linkage mapping. Therefore, LD mapping is considered more efficient for gene discovery to meet the challenge of connecting sequence diversity with heritable phenotypic differences. However, care must be taken to avoid detection of spurious associations which may occur due to population structure and variety interrelationships. In this review, we discuss how LD mapping is suitable for the dissection of complex traits in wild silkworms (Antheraea mylitta).

Application of Hyperion Hyperspectral Remote Sensing Data for Wildfire Fuel Mapping

  • Yoon, Yeo-Sang;Kim, Yong-Seung
    • Korean Journal of Remote Sensing
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    • v.23 no.1
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    • pp.21-32
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    • 2007
  • Fire fuel map is one of the most critical factors for planning and managing the fire hazard and risk. However, fuel mapping is extremely difficult because fuel properties vary at spatial scales, change depending on the seasonal situations and are affected by the surrounding environment. Remote sensing has potential to reduce the uncertainty in mapping fuels and offers the best approach for improving our abilities. Especially, Hyperspectral sensor have a great potential for mapping vegetation properties because of their high spectral resolution. The objective of this paper is to evaluate the potential of mapping fuel properties using Hyperion hyperspectral remote sensing data acquired in April, 2002. Fuel properties are divided into four broad categories: 1) fuel moisture, 2) fuel green live biomass, 3) fuel condition and 4) fuel types. Fuel moisture and fuel green biomass were assessed using canopy moisture, derived from the expression of liquid water in the reflectance spectrum of plants. Fuel condition was assessed using endmember fractions from spectral mixture analysis (SMA). Fuel types were classified by fuel models based on the results of SMA. Although Hyperion imagery included a lot of sensor noise and poor performance in liquid water band, the overall results showed that Hyperion imagery have good potential for wildfire fuel mapping.

Functional characterization of a minimal sequence essential for the expression of human TLX2 gene

  • Borghini, Silvia;Bachetti, Tiziana;Fava, Monica;Duca, Marco Di;Ravazzolo, Roberto;Ceccherini, Isabella
    • BMB Reports
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    • v.42 no.12
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    • pp.788-793
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    • 2009
  • TLX2 is an orphan homeodomain transcription factor whose expression is mainly associated with tissues derived from neural crest cells. Recently, we have demonstrated that PHOX2A and PHOX2B are able to enhance the neural cell-type specific expression of human TLX2 by binding distally the 5' -flanking region. In the present work, to deepen into the TLX2 transcription regulation, we have focused on the proximal 5'-flanking region of the gene, mapping the transcription start site and identifying a minimal promoter necessary and sufficient for the basal transcription in cell lines from different origin. Site-directed mutagenesis has allowed to demonstrate that the integrity of this sequence is crucial for gene expression, while electrophoretic mobility shift assays and chromatin immunoprecipitation experiments have revealed that such an activity is dependent on the binding of a PBX factor. Consistent with these findings, such a basal promoter activity has resulted to be enhanced by the previously reported PHOX2-responding sequence.

Feature-Point Extraction by Dynamic Linking Model bas Wavelets and Fuzzy C-Means Clustering Algorithm (Gabor 웨이브렛과 FCM 군집화 알고리즘에 기반한 동적 연결모형에 의한 얼굴표정에서 특징점 추출)

  • 신영숙
    • Korean Journal of Cognitive Science
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    • v.14 no.1
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    • pp.11-16
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    • 2003
  • This Paper extracts the edge of main components of face with Gator wavelets transformation in facial expression images. FCM(Fuzzy C-Means) clustering algorithm then extracts the representative feature points of low dimensionality from the edge extracted in neutral face. The feature-points of the neutral face is used as a template to extract the feature-points of facial expression images. To match point to Point feature points on an expression face against each feature point on a neutral face, it consists of two steps using a dynamic linking model, which are called the coarse mapping and the fine mapping. This paper presents an automatic extraction of feature-points by dynamic linking model based on Gabor wavelets and fuzzy C-means(FCM) algorithm. The result of this study was applied to extract features automatically in facial expression recognition based on dimension[1].

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Genetic Mapping and Sequence Analysis of the Gene Encoding the Major Capsid Protein of Bacteriophage E3 (박테리오파지 E3의 Major Capsid Protein을 만드는 유전자의 Mapping 및 염기서열 분석)

  • Bae, Soo-Jin;Myung, Hee-Joon
    • Korean Journal of Microbiology
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    • v.35 no.4
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    • pp.266-269
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    • 1999
  • Bacteriophage E3 grows very rapidly and forms a large size plaque with a diameter of 1 cm. The promoter controlling the expression of the gene encoding the major capsid protein is thought to be most efficient. To find out this promoter, this gene was mapped in the genome according to the following procedure. The major capsid protein was purified from phage particle and the N-terminal amino acid sequence was revealed. Based on this sequence,a degernerate oligonucleotide probe was designed and used for screening of the genomic DNA fragments. From the DNA sequence of the selected clone, the gene encoding the major capsid protein was mapped at 70% of E3 genome. The expression of this gene was not sensitive to rifampicin which indicated the presence of E3's own RNA polymerase.

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Mapping of Gene Encoding Phospho-$\beta$-galactosidase from Lactobacillus casei and its Expression in Escherichea coli (Lactobacillus casei 의 Phospho-$\beta$-galactosidase 유전자의 지도작성과 Escherichia coli 내에서의 발현)

  • 박정희;문경희;민경희
    • Korean Journal of Microbiology
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    • v.30 no.6
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    • pp.539-545
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    • 1992
  • Recombinant plasmid pPLac15 determined both phosphoenolpyruvate-dependent phosphotransferase uptake of lactose and phospho-$\beta$-galactosidase (Moon et al., 1989). A restriction mapping of the pPLac15 was compiled with several restriction enzymes and a seriese of sub clones into pUC18 was constructed. From an analysis of the proteins produced by Escherichia coli cells of transformants containing each of the recombinant subclone plasmids, it was found that the gene for phospho-$\beta$-galactosidase in pUCI8 was expressed about 1.8-folds in E. coli.

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Large-scale Genotyping and Genetic Mapping in Plasmodium Parasites

  • Su, Xin-Zhuan;Jiang, Hongying;Yi, Ming;Mu, Jianbing;Stephens, Robert M.
    • Parasites, Hosts and Diseases
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    • v.47 no.2
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    • pp.83-91
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    • 2009
  • The completion of many malaria parasite genomes provides great opportunities for genomewide characterization of gene expression and high-throughput genotyping. Substantial progress in malaria genomics and genotyping has been made recently, particularly the development of various microarray platforms for large-scale characterization of the Plasmodium falciparum genome. Microarray has been used for gene expression analysis, detection of single nucleotide polymorphism (SNP) and copy number variation (CNV), characterization of chromatin modifications, and other applications. Here we discuss some recent advances in genetic mapping and genomic studies of malaria parasites, focusing on the use of high-throughput arrays for the detection of SNP and CNV in the P. falciparum genome. Strategies for genetic mapping of malaria traits are also discussed.

Patch based Semi-supervised Linear Regression for Face Recognition

  • Ding, Yuhua;Liu, Fan;Rui, Ting;Tang, Zhenmin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.8
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    • pp.3962-3980
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    • 2019
  • To deal with single sample face recognition, this paper presents a patch based semi-supervised linear regression (PSLR) algorithm, which draws facial variation information from unlabeled samples. Each facial image is divided into overlapped patches, and a regression model with mapping matrix will be constructed on each patch. Then, we adjust these matrices by mapping unlabeled patches to $[1,1,{\cdots},1]^T$. The solutions of all the mapping matrices are integrated into an overall objective function, which uses ${\ell}_{2,1}$-norm minimization constraints to improve discrimination ability of mapping matrices and reduce the impact of noise. After mapping matrices are computed, we adopt majority-voting strategy to classify the probe samples. To further learn the discrimination information between probe samples and obtain more robust mapping matrices, we also propose a multistage PSLR (MPSLR) algorithm, which iteratively updates the training dataset by adding those reliably labeled probe samples into it. The effectiveness of our approaches is evaluated using three public facial databases. Experimental results prove that our approaches are robust to illumination, expression and occlusion.