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Normalized Kernels as Similarity Indices [chapter]

Julien Ah-Pine
2010 Lecture Notes in Computer Science  
We show that the designed normalized kernels satisfy the basic axioms of a similarity index unlike most unnormalized kernels.  ...  We particularly focus on kernel normalization methods that aim at designing proximity measures that better fit the definition and the intuition of a similarity index.  ...  Properties of normalized kernels as similarity indices In this section, we want to better characterize the family of normalized kernels that we have introduced.  ... 
doi:10.1007/978-3-642-13672-6_36 fatcat:nhn6iulu3fegrpqasqx2h4cizi

Differences in Endosperm Proteins Between Yellow Berry and Normal Triticales

Jerold A. Bietz, Govind C. Sharma
1983 Crop science  
Results indicated that no1"'" mal triticales contain more residue protein (unreduced high molecular weight glutenin) than VB kernels.  ...  These interactions may lead to the differences in endosperm vitreosity and hardness between normal and VB kernels.  ...  Results for triticales 6TB 224, AM 2838, and AM 3425, however, as well as for Cando durum and Dannie bread wheat (not shown), indicated very similar gliadin compositions for YB and normal kernels within  ... 
doi:10.2135/cropsci1983.0011183x002300040024x fatcat:kfbq44cogbcqzo5hrgk34no4hu

Friendship of Stock Market Indices: A Cluster-Based Investigation of Stock Markets

László Nagy, Mihály Ormos
2018 Journal of Risk and Financial Management  
We cluster different stock indices and reconstruct the equity index graph from historical daily closing prices. We show that tail events have a minor effect on the equity index structure.  ...  Intuitively, indices with similar risk and return can be believed to be similar.  ...  Intuitively, indices with similar risk and return can be believed to be similar.  ... 
doi:10.3390/jrfm11040088 fatcat:j7hkk4kokfbhxjkvwpnotvhlqi

Spectral-Similarity-Based Kernel of SVM for Hyperspectral Image Classification

Ke Wang, Ligang Cheng, Bin Yong
2020 Remote Sensing  
Spectral similarity measures can be regarded as potential metrics for kernel functions, and can be used to generate spectral-similarity-based kernels.  ...  : Power spectral angle mapper RBF (Power-SAM-RBF) and normalized spectral information divergence-based RBF (Normalized-SID-RBF) kernels.  ...  This indicates that the Power-SAM-RBF kernel outperforms the RBF kernel when the similarity of class pairs is high or low.  ... 
doi:10.3390/rs12132154 fatcat:sc4filgm5zairfs553u7ftgxfi

Friendship Of Stock Indices

Laszlo Nagy, Mihaly Ormos
2016 ECMS 2016 Proceedings edited by Thorsten Claus, Frank Herrmann, Michael Manitz, Oliver Rose  
The aim of this study is to cluster different stock indices based on historical time series data. The current research shows that tail events have minor effect on the equity index structure.  ...  Intuitively, indices with similar risk and return can thought to be similar.  ...  Henceforth, Gaussian-kernel based normalized modularity matrix is used.  ... 
doi:10.7148/2016-0152 dblp:conf/ecms/NagyO16 fatcat:jvnihgph4ffjzeb2fjuuyutxfi

Some Physiological Effects of Viviparous Genes vp1 and vp5 on Developing Maize Kernels

G. F. Wilson, A. M. Rhodes, D. B. Dickinson
1973 Plant Physiology  
Increases in fresh weights indicated that viviparous began to grow more rapidly than normal embryos at that time.  ...  Differences between viviparous and normal embryos first appeared at 25 to 30 days after pollination.  ...  As early as 20 DAP, the amino acid content was higher in vp1 than in the normal embryo.  ... 
doi:10.1104/pp.52.4.350 pmid:16658561 pmcid:PMC366501 fatcat:l7payjpuufaxjixa4eboswm774

A Theoretical Investigation of Graph Degree as an Unsupervised Normality Measure [article]

Caglar Aytekin, Francesco Cricri, Lixin Fan, Emre Aksu
2018 arXiv   pre-print
For a graph representation of a dataset, a straightforward normality measure for a sample can be its graph degree.  ...  Considering a weighted graph, degree of a sample is the sum of the corresponding row's values in a similarity matrix.  ...  Then the average intra-similarity of the cluster for can be written as follows: x T W x x T x (4) In Eq. 4, W is a symmetric similarity (or affinity) matrix where w ij indicates the similarity between  ... 
arXiv:1801.07889v3 fatcat:ymedfo62ajaibh3tzw2gziea74

Expression profile of protein fractions in the developing kernel of normal, Opaque-2 and quality protein maize

Mehak Sethi, Alla Singh, Harmanjot Kaur, Ramesh Kumar Phagna, Sujay Rakshit, Dharam Paul Chaudhary
2021 Scientific Reports  
The present study was planned to analyze the expression dynamics of different protein fractions in the endospem of developing maize kernel in normal, opaque-2 and QPM in response to the introgression of  ...  It has also been noted that prolamin, glutelin, and glutelin-like fractions can be used as quick markers for quality assessment for differentiating QPM varieties, even at the immature stage of kernel development  ...  Similar findings have been reported earlier indicating that glutelin content increased from 17 to 44% in opaque-2 mutants as compared to its normal counterpart 32 .  ... 
doi:10.1038/s41598-021-81906-0 pmid:33510248 fatcat:wuhofjq5wbajjmercjz4fn6uea

Independent Regulatory Aspects and Posttranslational Modifications of Two -Amylases of Rye : Use of a Mutant Inbred Line

J. Daussant, J. Sadowski, T. Rorat, C. Mayer, C. Lauriere
1991 Plant Physiology  
This deficiency corresponds to a lack of accumulation of fl-amylase activity in the endosperm and does not affect the level of activity in the outer pericarp and green tissues as compared to the normal  ...  I and 11 display very similar electrophoretic polymorphism. In both lines, I appears to be ubiquitous, although it disappears from the outer pericarp during ripening.  ...  In the leaves of7-d-old seedlings (normal and mutant), the activity levels found were very low and similar to that found in mature mutant kernels.  ... 
doi:10.1104/pp.96.1.84 pmid:16668189 pmcid:PMC1080716 fatcat:7uctv7vobjgf5jz57pxfksnqau

Kernel Analysis for Estimating the Connectivity of a Network with Event Sequences

Taro Tezuka, Christophe Claramunt
2017 Journal of Artificial Intelligence and Soft Computing Research  
Specifically, a normalized positive definite kernel defined on spike trains was used.  ...  Real data recorded from the visual cortex of an anaesthetized cat was analyzed as well.  ...  The abscissa is pair ID ordered by increasing value of normalized kernel. The ordinate is the value of normalized kernel. Top 10 pairs with high normalized kernel values.  ... 
doi:10.1515/jaiscr-2017-0002 fatcat:wvrnj4hb6ng3vf322qjlflzmua

Compressive Strength of Wheat Endosperm: Comparison of Endosperm Bricks to the Single Kernel Characterization System

Craig F. Morris, Arthur D. Bettge, Marvin J. Pitts, G. E. King, Kameron Pecka, Patrick J. McCluskey
2008 Cereal Chemistry  
These results indicate that both the total variation as well as the robustness of the models were similar for brick material properties and SKCS HI.  ...  Again, normalization of the data indicated that the SKCS HI had a similar amount of inherent variation relative to the KS-brick compression results (Figs. 5-7) .  ... 
doi:10.1094/cchem-85-3-0359 fatcat:4xzn3kkyvbfsja3zw3ryjjd7xa

Evaluation of Local and Multinational Maize Hybrids for Tolerance Against High Temperature using Stress Tolerance Indices

Saleem Ur Rehman, Muhammad Irfan Yousaf, Mozammil Hussain, Khadim Hussain, Shahid Hussain, Muhammad Husnain Bhatti, Dilbar Hussain, Aamir Ghani, Abdul Razzaq, Muhammad Akram, Iqra Ibrar, Muhammad Shakeel Ahmed (+2 others)
2022 Pakistan Journal of Agricultural Research  
Correlation analysis indicated that some high temperature stress indices i.e., STI, MP, GMP and HARM had a strong positive correlation with kernel yield under normal (Yp) and high temperature stress conditions  ...  compared to normal sowing.  ...  High temperature stress indices were calculated from kernel yield of normal (Yp) and high temperature stress conditions (Ys) as used by Grzesiak et al. (2019) and Zhao et al. (2019).  ... 
doi:10.17582/journal.pjar/2022/ fatcat:cf7nfpavybcrtgm4pjmygkhanu

Adaptive Object Retrieval with Kernel Reconstructive Hashing

Haichuan Yang, Xiao Bai, Jun Zhou, Peng Ren, Zhihong Zhang, Jian Cheng
2014 2014 IEEE Conference on Computer Vision and Pattern Recognition  
Using low-rank approximation, our hashing framework is more effective than existing methods that preserve similarity over arbitrary kernel.  ...  In this paper, we firstly propose a new adaptive similarity measure which is consistent with k-NN search, and prove that it leads to a valid kernel.  ...  In this setting, Gaussian kernel and the Euclidean distance is equivalent. Figure 3 shows the results using Gaussian kernel and normalized Gaussian kernel as the similarity function.  ... 
doi:10.1109/cvpr.2014.251 dblp:conf/cvpr/Yang0ZRZC14 fatcat:bptrgyema5a7pgbfjsslmskdhm

Effects of long-term exposure to elevated temperature on Zea mays endosperm development during grain fill

Susan K. Boehlein, Peng Liu, Ashley Webster, Camila Ribeiro, Masaharu Suzuki, Shan Wu, Jiahn-Chou Guan, Jon D. Stewart, William F. Tracy, A. Mark Settles, Donald R. McCarty, Karen E. Koch (+3 others)
2019 The Plant Journal  
This study used controlled environments to isolate temperature as the sole environmental variable during Zea mays kernel-fill, from 12 days after pollination to maturity.  ...  Integrated analyses indicated that the normal developmental program of endosperm is fully executed under prolonged high-temperature conditions, but at a faster rate.  ...  (a) Whole kernel anthocyanin content calculated as cyanidin 3-glucoside equivalents. Values are normalized to wet weight.  ... 
doi:10.1111/tpj.14283 pmid:30746832 fatcat:hdmnfvzgjjcsbm5xlduixma6iu

An Iterative Locally Linear Embedding Algorithm [article]

Deguang Kong, Chris H.Q. Ding, Heng Huang (The University of Texas at Arlington), Feiping Nie
2012 arXiv   pre-print
Thirdly, we relax the kNN constraint of LLE and present a sparse similarity learning algorithm. The final Iterative LLE combines these three improvements.  ...  similarity W t , solve for Y t using Lemma 1. (3)Given embedding Y t , compute a new kernel K t+1 either as the final result of our algorithm (both embedding Y t and kernel K t+1 ) or as input to step  ...  Given Gaussian Kernel as the input, the iterative LLE algorithm ( §3) and sparse similarity learning algorithm ( §4) are run. The other parameters are set as mentioned before.  ... 
arXiv:1206.6463v1 fatcat:7win5nywjffffjhmw23trklbte
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