oalib

Publish in OALib Journal

ISSN: 2333-9721

APC: Only $99

Submit

Any time

2018 ( 1 )

2016 ( 1 )

2015 ( 25 )

2014 ( 33 )

Custom range...

Search Results: 1 - 10 of 488 matches for " Eunseog Youn "
All listed articles are free for downloading (OA Articles)
Page 1 /488
Display every page Item
基于蒙特卡罗特征降维算法的小样本高光谱图像分类
赵春晖,齐滨,Eunseog,Youn
红外与毫米波学报 , 2013,
Abstract: 高光谱图像分类是高光谱数据分析的重要研究内容.相关向量机由于不受梅西定理的限制、不需要设置惩罚因子等优势受到广泛关注.由于高光谱数据具有较高的维数,当训练样本较少时,高光谱数据的分类精度受到严重的影响.通常解决这种现象的办法是对原数据进行特征降维处理,然而多数基于filter模型的特征选择算法无法直接给出最优特征选择个数.为此提出利用蒙特卡罗随机实验可以对特征参量进行统计估计的特性,计算高光谱图像的最优降维特征数,并与相关向量机结合,对降维后的数据进行分类.实验结果表明了使用蒙特卡罗算法求解降维波段数的可靠性.相比较原始未降维数据,降维后的高光谱图像分类精度有较大幅度的提高.
Hyperspectral image classification based on Monte Carlo feature reduction method
基于蒙特卡罗特征降维算法的小样本高光谱图像分类

ZHAO Chun-Hui,QI Bin,Eunseog Youn,
赵春晖
,齐滨,Eunseog Youn

红外与毫米波学报 , 2013,
Abstract: Hyperspectral image classification is an important research aspect of hyperspectral data analysis. Relevance vector machine (RVM) is widely utilized since it is not restricted to Mercer condition and does not have to set the penalty factor. Due to the high dimension of hyperspectral data, the classification accuracy is severely affected when there are few training samples. Feature reduction is a common method to deal with this phenomenon. However, most of the filter model based feature selection methods can not provide optimal feature selection number. This paper proposes to utilize the statistic estimation characteristic of Monte Carlo random experiments to calculate optimal feature reduction number and conduct hyperspectral image classification with relevance vector machine. Experimental results show the reliability of the feature reduction number calculated by Monte Carlo method. Compared with the classification of original data, there is a significant improvement in the classification accuracy with the feature reduction data.
Double feature selection and cluster analyses in mining of microarray data from cotton
Magdy S Alabady, Eunseog Youn, Thea A Wilkins
BMC Genomics , 2008, DOI: 10.1186/1471-2164-9-295
Abstract: Mining of independent microarray studies from Pima and Upland (TM1) cotton using double feature selection and cluster analyses identified species-specific and stage-specific gene transcripts that argue in favor of discrete genetic mechanisms that govern developmental programming of cotton fiber morphogenesis in these two cultivated species. Double feature selection analysis identified the highest number of differentially expressed genes that distinguish the fiber transcriptomes of developing Pima and TM1 fibers. These results were based on the finding that differences in fibers harvested between 17 and 24 day post-anthesis (dpa) represent the greatest expressional distance between the two species. This powerful selection method identified a subset of genes expressed during primary (PCW) and secondary (SCW) cell wall biogenesis in Pima fibers that exhibits an expression pattern that is generally reversed in TM1 at the same developmental stage. Cluster and functional analyses revealed that this subset of genes are primarily regulated during the transition stage that overlaps the termination of PCW and onset of SCW biogenesis, suggesting that these particular genes play a major role in the genetic mechanism that underlies the phenotypic differences in fiber traits between Pima and TM1.The novel application of double feature selection analysis led to the discovery of species- and stage-specific genetic expression patterns, which are biologically relevant to the genetic programs that underlie the differences in the fiber phenotypes in Pima and TM1. These results promise to have profound impacts on the ongoing efforts to improve cotton fiber traits.Microarray technology provides data in high-dimensional space defined by the size of the genome under investigation. With such high-dimensional data, feature selection methods are essentially classification tools used to identify gene clusters that reveal biologically meaningful relationships [1]. A classical use of feature sel
An Improved Systematic Approach to Predicting Transcription Factor Target Genes Using Support Vector Machine
Song Cui, Eunseog Youn, Joohyun Lee, Stephan J. Maas
PLOS ONE , 2014, DOI: 10.1371/journal.pone.0094519
Abstract: Biological prediction of transcription factor binding sites and their corresponding transcription factor target genes (TFTGs) makes great contribution to understanding the gene regulatory networks. However, these approaches are based on laborious and time-consuming biological experiments. Numerous computational approaches have shown great potential to circumvent laborious biological methods. However, the majority of these algorithms provide limited performances and fail to consider the structural property of the datasets. We proposed a refined systematic computational approach for predicting TFTGs. Based on previous work done on identifying auxin response factor target genes from Arabidopsis thaliana co-expression data, we adopted a novel reverse-complementary distance-sensitive n-gram profile algorithm. This algorithm converts each upstream sub-sequence into a high-dimensional vector data point and transforms the prediction task into a classification problem using support vector machine-based classifier. Our approach showed significant improvement compared to other computational methods based on the area under curve value of the receiver operating characteristic curve using 10-fold cross validation. In addition, in the light of the highly skewed structure of the dataset, we also evaluated other metrics and their associated curves, such as precision-recall curves and cost curves, which provided highly satisfactory results.
Transgene Silencing and Transgene-Derived siRNA Production in Tobacco Plants Homozygous for an Introduced AtMYB90 Construct
Jeff Velten, Cahid Cakir, Eunseog Youn, Junping Chen, Christopher I. Cazzonelli
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0030141
Abstract: Transgenic tobacco (Nicotiana tabacum) lines were engineered to ectopically over-express AtMYB90 (PAP2), an R2–R3 Myb gene associated with regulation of anthocyanin production in Arabidopsis thaliana. Independently transformed transgenic lines, Myb27 and Myb237, accumulated large quantities of anthocyanin, generating a dark purple phenotype in nearly all tissues. After self-fertilization, some progeny of the Myb27 line displayed an unexpected pigmentation pattern, with most leaves displaying large sectors of dramatically reduced anthocyanin production. The green-sectored 27Hmo plants were all found to be homozygous for the transgene and, despite a doubled transgene dosage, to have reduced levels of AtMYB90 mRNA. The observed reduction in anthocyanin pigmentation and AtMYB90 mRNA was phenotypically identical to the patterns seen in leaves systemically silenced for the AtMYB90 transgene, and was associated with the presence of AtMYB90-derived siRNA homologous to both strands of a portion of the AtMYB90 transcribed region. Activation of transgene silencing in the Myb27 line was triggered when the 35S::AtMYB90 transgene dosage was doubled, in both Myb27 homozygotes, and in plants containing one copy of each of the independently segregating Myb27 and Myb237 transgene loci. Mapping of sequenced siRNA molecules to the Myb27 TDNA (including flanking tobacco sequences) indicated that the 3′ half of the AtMYB90 transcript is the primary target for siRNA associated silencing in both homozygous Myb27 plants and in systemically silenced tissues. The transgene within the Myb27 line was found to consist of a single, fully intact, copy of the AtMYB90 construct. Silencing appears to initiate in response to elevated levels of transgene mRNA (or an aberrant product thereof) present within a subset of leaf cells, followed by spread of the resulting small RNA to adjacent leaf tissues and subsequent amplification of siRNA production.
Identification of similar regions of protein structures using integrated sequence and structure analysis tools
Brandon Peters, Charles Moad, Eunseog Youn, Kris Buffington, Randy Heiland, Sean Mooney
BMC Structural Biology , 2006, DOI: 10.1186/1472-6807-6-4
Abstract: Users are able to submit their own queries or use a structure already in the PDB. Currently the databases that a user can query include the popular structural datasets ASTRAL 40 v1.69, ASTRAL 95 v1.69, CLUSTER50, CLUSTER70 and CLUSTER90 and PDBSELECT25. The results can be downloaded directly from the site and include function prediction, analysis of the most conserved environments and automated annotation of query proteins. These results reflect both the hits found with PSI-BLAST, HMMer and with S-BLEST. We have evaluated how well annotation transfer can be performed on SCOP ID's, Gene Ontology (GO) ID's and EC Numbers. The method is very efficient and totally automated, generally taking around fifteen minutes for a 400 residue protein.With structural genomics initiatives determining structures with little, if any, functional characterization, development of protein structure and function analysis tools are a necessary endeavor. We have developed a useful application towards a solution to this problem using common structural and sequence based analysis tools. These approaches are able to find statistically significant environments in a database of protein structure, and the method is able to quantify how closely associated each environment is to a predicted functional annotation.Automated functional annotation of proteins based on their sequence and structure is a challenging and important problem [1]. One area of interest to us is the identification of regions in protein structures that are statistically associated with a given structural or functional annotation. To provide a useful resource addressing this problem, we have developed web tools for identification of sequence conserved residues and environments structurally associated with specific functional and structural annotations.Projects such as Structural Classification of Proteins (SCOP) [2] or CATH [3] annotate the known protein structure universe heirarchically. For example, SCOP classifies protein by cla
Analysis of Antisense Expression by Whole Genome Tiling Microarrays and siRNAs Suggests Mis-Annotation of Arabidopsis Orphan Protein-Coding Genes
Casey R. Richardson,Qing-Jun Luo,Viktoria Gontcharova,Ying-Wen Jiang,Manoj Samanta,Eunseog Youn,Christopher D. Rock
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0010710
Abstract: MicroRNAs (miRNAs) and trans-acting small-interfering RNAs (tasi-RNAs) are small (20–22 nt long) RNAs (smRNAs) generated from hairpin secondary structures or antisense transcripts, respectively, that regulate gene expression by Watson-Crick pairing to a target mRNA and altering expression by mechanisms related to RNA interference. The high sequence homology of plant miRNAs to their targets has been the mainstay of miRNA prediction algorithms, which are limited in their predictive power for other kingdoms because miRNA complementarity is less conserved yet transitive processes (production of antisense smRNAs) are active in eukaryotes. We hypothesize that antisense transcription and associated smRNAs are biomarkers which can be computationally modeled for gene discovery.
A Dynamic Cournot Model with Brownian Motion  [PDF]
Hyungho Youn, Victor J. Tremblay
Theoretical Economics Letters (TEL) , 2015, DOI: 10.4236/tel.2015.51009
Abstract: In this paper we develop a stochastic version of a dynamic Cournot model. The model is dynamic because firms are slow to adjust output in response to changes in their economic environment. The model is stochastic because management may make errors in identifying the best course of action in a dynamic setting. We capture these behavioral errors with Brownian motion. The model demonstrates that the limiting output level of the game is a random variable, rather than a constant that is found in the non-stochastic case. In addition, the limiting variance in firm output is smaller with more firms. Finally, the model predicts that firm failure is more likely in smaller markets and for firms that are smaller and less efficient at managing errors.
A Comparison of Clock Synchronization in Wireless Sensor Networks
Seongwook Youn
International Journal of Distributed Sensor Networks , 2013, DOI: 10.1155/2013/532986
Abstract: The recent advances in microelectro devices have led the researchers to an area of developing a large distributed system that consist of small, wireless sensor nodes. These sensor nodes are usually equipped with sensors to perceive the environment. Synchronization is an important component of almost all distributed systems and has been studied by many researchers. There are many solutions for the classical networks, but the traditional synchronization techniques are not suitable for sensor networks because they do not consider the partitioning of the network and message delay. Additionally, limited power, computational capacity, and memory of the sensor nodes make the problem more challenging for wireless sensor networks. This paper examines the clock synchronization issues in wireless sensor networks. Energy efficiency, cost, scalability, lifetime, robustness, and precision are the main problems to be considered in design of a synchronization algorithm. There is no one single system that satisfies all these together. A comparison of different clock synchronization algorithms in wireless sensor networks with a main focus on energy efficiency, scalability, and precision properties of them will be provided here. 1. Introduction Wireless sensor networks are the networks that consist of mobile wireless computing devices, in which these devices are usually equipped with sensors to perceive the environment. Along with the recent advances in technology and the increasing demand, sensor networks are now being widely used in many applications. Wireless sensor networks have many applications including environmental monitoring, health monitoring, inventory location monitoring, and objects tracking. Features of a sensor network, such as size (number of nodes), density, and connectivity, vary depending on the application. Sensor nodes in the network are mostly mobile devices equipped with limited power and computation capabilities. Hence, a reasonable ordering of events in such environments is a challenging task. This paper examines the clock synchronization issues in ad hoc and sensor networks [1]. Clocks can be out of synchronization in two ways: shifting (clock offset or phase offset) or drifting (clock skew-oscillator’s frequency offset). In the case of shifting, they run at the same frequency, but their clock readings differ by a constant value—the offset between the clocks. In the case of drifting, they run at different frequencies. Synchronizing drifting clocks is much more costly and difficult than synchronizing two shifting clocks. Clocks of nodes may run
Undergraduate Students’Evaluation Criteria When Using Web Resources for Class Papers
Tsai-Youn Hung
Journal of Educational Media & Library Sciences , 2004,
Abstract: The growth in popularity of the World Wide Web has dramatically changed the way undergraduate students conduct information searches. The purpose of this study is to investigate what core quality criteria undergraduate students use to evaluate Web resources for their class papers and to what extent they evaluate the Web resources. This study reports on five Web page evaluations and a questionnaire survey of thirty five undergraduate students in the Information Technology and Informatics Program at Rutgers University. Results show that undergraduate students have become increasingly sophisticated about using Web resources, but not yet sophisticated about searching them. Undergraduate students only used one or two surface quality criteria to evaluate Web resources. They made immediate judgments about the surface features of Web pages and ignored the content of the documents themselves. This research suggests that undergraduate instructors should take the responsibility for instructing students on basic Web use knowledge or work with librarians to develop undergraduate students information literacy skills.
Page 1 /488
Display every page Item


Home
Copyright © 2008-2017 Open Access Library. All rights reserved.