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Search Results: 1 - 10 of 353 matches for " SOM "
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A new projection method for biological semantic map generation  [PDF]
Hoan N. Nguyen, Nicolas Wicker, David Kieffer, Olivier Poch
Journal of Biomedical Science and Engineering (JBiSE) , 2010, DOI: 10.4236/jbise.2010.31002
Abstract: Low-dimensional representation is a convenient method of obtaining a synthetic view of complex datasets and has been used in various domains for a long time. When the representation is related to words in a document, this kind of representation is also called a semantic map. The two most popular methods are self-organizing maps and generative topographic mapping. The second approach is statistically well-founded but far less computationally efficient than the first. On the other hand, a drawback of self-organizing maps is that they do not project all points, but only map nodes. This paper presents a method of obtaining the projections for all data points complementary to the self-organizing map nodes. The idea is to project points so that their initial distances to some cluster centers are as conserved as possible. The method is tested on an oil flow dataset and then applied to a large protein sequence dataset described by keywords. It has been integrated into an interactive data browser for biological databases.
Application of SOM neural network in clustering  [PDF]
Soroor Behbahani, Ali Moti Nasrabadiv
Journal of Biomedical Science and Engineering (JBiSE) , 2009, DOI: 10.4236/jbise.2009.28093
Abstract: The Self-Organizing Map (SOM) is an unsupervised neural network algorithm that projects high-dimensional data onto a two-dimensional map. The projection preserves the topology of the data so that similar data items will be mapped to nearby locations on the map. One of the SOM neural network’s applications is clustering of animals due their features. In this paper we produce an experiment to analyze the SOM in clustering different species of animals.
A Load Balance Clustering Routing Algorism Based on SOM  [PDF]
Shan Zhong, Guihua Wang, Xiaohui Leng, Xiaona Wang, Lian Xue, Yue Gu
Journal of Software Engineering and Applications (JSEA) , 2012, DOI: 10.4236/jsea.2012.511101
Abstract: In order to solve the uneven node load in the tradition clustering routing protocols, a new clustering algorism based on SOM is proposed. Firstly, the network radio model and the energy consumption model are defined. A new algorism using SOM to form the cluster and select the cluster head is defined. In the clustering node remain energy and the Euclidean distance from cluster head to the cluster member are considered. The experiment shows our method has the longer life cycle and less total energy consumption. It is an effective clustering protocol.
Effect of Tillage and Nitrogen on Wheat Production, Economics, and Soil Fertility in Rice-Wheat Cropping System  [PDF]
Khalid Usman, Ejaz Ahmad Khan, Niamatullah Khan, Muhammad Anwar Khan, Said Ghulam, Sarfaraz Khan, Jalaluddin Baloch
American Journal of Plant Sciences (AJPS) , 2013, DOI: 10.4236/ajps.2013.41004
Abstract: Conservation tillage and nitrogen may improve soil fertility, yield and income on sustainable basis. The aim of this study was to evaluate the impact of three tillage systems viz. zero (ZT), reduced (RT), and conventional tillage (CT) and five N rates (0, 80, 120, 160, and 200 kg·N·ha-1) on yield and yield components, soil organic matter (SOM), total soil N (TSN), and income of wheat (Triticum aestivum L.) grown after rice (Oryza sativa L.). Nitrogen rates significantly affected yield and yield attributing characters with highest values recorded at200 kg·N·ha-1. Mean maximum grain yield (6390 -6845 kg·ha-1), net benefit (1359 - 1460 US$ ha-1), and benefit cost ratio (5.6 - 5.7) could be achieved at 160 to200 kg·N·ha-1. The tillage systems produced similar yield and yield components except spikes m-2. The SOM and TSN were highest in ZT compared to other tillage systems. Though tillage × N interactions were not significant for most of the parameters under study, the overall effect of ZT with200 kg·N·ha-1 appeared to be most favorable compared to RT and CT. Zero tillage resulted in highest number of spikes m-2 (304.4), SOM (9.6 g·kg-1) and TSN (0.5 g·kg-1) with200 kg·N·ha-1. The results suggest that ZT with200 kg·N·ha-1 was optimum and sustainable strategy to achieve higher yield and income and also to improve SOM and TSN on silty clay soil.
Cluster Analysis Based on Contextual Features Extraction for Conversational Corpus  [PDF]
Qi Chen, Yue Chen, Minghu Jiang
Journal of Computer and Communications (JCC) , 2015, DOI: 10.4236/jcc.2015.35004
Abstract:

Cluster analysis related to computational linguistics seldom concerned with Pragmatics level. Features of corpus on Pragmatics level related to specific situations, including backgrounds, titles and habits. To improve the accuracy of clustering for conversations collected from international students in Tsinghua University, it required contextual features. Here, we collected four-hundred conversations as a corpus and built it to Vector Space Model. With the Oxford-Duden Dictionary and other methods we modified the model and concluded into three groups. We testified our hypothesis through self-organizing map neural network. The result suggested that the modified model had a better outcome.

As vogais átonas finais e o português do Brasil
Pedro Caruso
Alfa : Revista de Linguística , 2001,
Abstract: A partir de duas tendências opostas quanto à interpreta o do valor fonético das vogais átonas finais do português antigo, este estudo prop e uma solu o intermediária, reinterpretando informa es e utilizando dados a respeito do português do Brasil.
O uso do ultra-som na remo o de retentores intra-radiculares com diferentes tipos de reten o
Menezes, Marcia Maciel et al.
Revista Odonto Ciência , 2009,
Abstract: Objetivo: O objetivo deste trabalho foi avaliar o uso do ultra-som na remo o de retentores intra-radiculares metálicos fundidos (RI). Metodologia: Foram utilizados 30 dentes humanos unirradiculados tratados endodonticamente e divididos em três grupos: grupo G1 - retentores intra-radiculares do tipo convencional, sem nenhum tipo de reten o mecanica adicional (tipo liso); grupo G2 - retentores intra-radiculares com sulcos longitudinais (tipo canaleta) e grupo G3 - retentores intra-radiculares com sulcos transversais (tipo anelado). Os retentores foram cimentados nos canais radiculares com cimento fosfato de zinco e os espécimes armazenados por 24 h em temperatura ambiente. Para a remo o dos retentores utilizou-se o ultra-som e a tra o manual com pin a hemostática. Foi medido o tempo necessário para remo o dos retentores; os dados foram analisados por ANOVA e teste de Tukey (5% de significancia). Resultados: Houve diferen a estatisticamente significante entre G1(3,7±1,5 min) e G2 (1,4±0,5 min) (P<0,001) e entre G1 e G3 (2,3±1,2 min) (P=0,041). N o houve diferen a significante entre G2 e G3 (P=0,207). Conclus o: Concluiu-se que os pinos metálicos fundidos lisos apresentaram maior dificuldade para remo o.
Introdu o à arqueologia da escuta: do som e da voz como objetos de enuncia o1
ivan Capeller
Ciberlegenda , 2011,
Abstract: A arqueologia da escuta rompe com os limites estreitos da história da música e abre a possibilidade de uma nova compreens o da historicidade dos regimes de escuta, n o mais entendidos apenas como o reflexo passivo de uma percep o dos sons determinada pela fisiologia da audi o, mas epistemologicamente re-configurados pelo conceito de objeto-som, de Pierre Schaeffer.
原空间中的核SOM分类器
潘志松,陈松灿,张道强
电子学报 , 2004,
Abstract: 自组织特征映射(SOM)是Kohonen提出的一种人工神经网络模型,其整个学习过程是在输入样本空间内进行,并以欧氏距离为度量.这将导致当输入样本分布结构呈高度非线性时,其分类能力下降.核方法通过核函数实现了一个从低维输入空间到高维特征空间的映射,从而使输入空间中复杂的样本结构在特征空间中变得简单.Donald等人通过核映射将低维输入空间中的非线性问题变换至高维特征空间中,从而使SOM聚类形成于映射后的高维特征空间中.但其缺点是失去了对原输入空间聚类中心及结果的直观刻画;本文采用核方法的目的是为原输入空间诱导出一类异于欧氏距离的新的距离度量,并使原SOM成为特例.而核的多样性进一步可诱导出原空间中不同的度量,导致各种对应SOM分类器的生成.最后,本文侧重通过几种经典的核函数在Benchmark上的试验,对该分类器的性能及可靠性进行了验证.
Estimating the number of data clusters via the contrast statistic  [PDF]
Yuriy Lyakh, Vitaliy Gurianov, Oleg Gorshkov, Yuriy Vihovanets
Journal of Biomedical Science and Engineering (JBiSE) , 2012, DOI: 10.4236/jbise.2012.52012
Abstract: A new method (the Contrast statistic) for estimating the number of clusters in a set of data is proposed. The technique uses the output of self-organising map clustering algorithm, comparing the change in dependency of “Contrast” value upon clusters number to that expected under a uniform distribution. A simulation study shows that the Contrast statistic can be used successfully either, when variables describing the object in a multi-dimensional space are independent (ideal objects) or dependent (real biological objects).
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