Similar Video Retrieval via Order-Aware Exemplars and Alignment

In this paper, we present machine learning algorithms and systems for similar video retrieval. Here, the query is itself a video. For the similarity measurement, exemplars, or representative frames in each video, are extracted by unsupervised learning. For this learning, we chose the order-aware competitive learning. After obtaining a set of exemplars for each video, the similarity is computed. Because the numbers and positions of the exemplars are different in each video, we use a similarity computing method called M-distance, which generalizes existing global and local alignment methods using followers to the exemplars. To represent each frame in the video, this paper emphasizes the Frame Signature of the ISO/IEC standard so that the total system, along with its graphical user interface, becomes practical. Experiments on the detection of inserted plagiaristic scenes showed excellent precision-recall curves, with precision values very close to 1. Thus, the proposed system can work as a plagiarism detector for videos. In addition, this method can be regarded as the structuring of unstructured data via numerical labeling by exemplars. Finally, further sophistication of this labeling is discussed.

Automatic Aggregation Enhanced Affinity Propagation Clustering Based on Mutually Exclusive Exemplar Processing

Affinity propagation(AP)is a widely used exemplar-based clustering approach with superior efficiency and clustering quality.Nevertheless,a common issue with AP clustering is the presence of excessive exemplars,which limits its ability to perform effective aggregation.This research aims to enable AP to automatically aggregate to produce fewer and more compact clusters,without changing the similarity matrix or customizing preference parameters,as done in existing enhanced approaches.An automatic aggregation enhanced affinity propagation(AAEAP)clustering algorithm is proposed,which combines a dependable partitioning clustering approach with AP to achieve this purpose.The partitioning clustering approach generates an additional set of findings with an equivalent number of clusters whenever the clustering stabilizes and the exemplars emerge.Based on these findings,mutually exclusive exemplar detection was conducted on the current AP exemplars,and a pair of unsuitable exemplars for coexistence is recommended.The recommendation is then mapped as a novel constraint,designated mutual exclusion and aggregation.To address this limitation,a modified AP clustering model is derived and the clustering is restarted,which can result in exemplar number reduction,exemplar selection adjustment,and other data point redistribution.The clustering is ultimately completed and a smaller number of clusters are obtained by repeatedly performing automatic detection and clustering until no mutually exclusive exemplars are detected.Some standard classification data sets are adopted for experiments on AAEAP and other clustering algorithms for comparison,and many internal and external clustering evaluation indexes are used to measure the clustering performance.The findings demonstrate that the AAEAP clustering algorithm demonstrates a substantial automatic aggregation impact while maintaining good clustering quality.

New mutational trends in the HA protein of 2009 H1N1 pandemic influenza virus from May 2010 to February 2011

As we enter the year of 2011, the 2009 H1N1 pandemic influenza virus is in the news again. At least 20 people have died of this virus in China since the beginning of 2011 and it is now the predominant flu strain in the country. Although this novel virus was quite stable during its run in the flu season of 2009-2010, a genetic variant of this virus was found in Singapore in early 2010, and then in Australia and New Zealand during their 2010 winter influenza season. Several critical mutations in the HA protein of this variant were uncovered in the strains collected from January 2010 to April 2010. Moreover, a structural homology model of HA from the A/Brisbane/10/2010(H1N1) strain was made based on the structure of A/California/04/2009 (H1N1). The purpose of this study was to investigate mutations in the HA protein of 2009 H1N1 from sequence data collected worldwide from May 2010 to February 2011. A fundamental problem in bioinformatics and biology is to find the similar gene sequences for a given gene sequence of interest. Here we proposed the inverse problem, i.e., finding the exemplars from a group of related gene sequences. With a clustering algorithm affinity propagation, six exemplars of the HA sequences were identified to represent six clusters. One of the clusters contained strain A/Brisbane/12/2010(H1N1) that only differed from A/Brisbane/10/2010 in the HA sequence at position 449. Based on the sequence identity of the six exemplars, nine mutations in HA were located that could be used to distinguish these six clusters. Finally, we discovered the change of correlation patterns for the HA and NA of 2009 H1N1 as a result of the HA receptor binding specificity switch, revealing the balanced interplay between these two surface proteins of the virus.

A High-accuracy Approach to Pronunciation Prediction for Out-of-vocabulary English Word

Letter-to-Sound conversion is one of the fundamental issues in text-to-speech synthesis. In this paper, we address an approach to automatic prediction of word pronunciation. This approach combines example-based learning and dynamic-programming searching to predict sub-word pronunciation. Word pronunciation is formed by concatenating sub-word pronunciations. We conducted comparative experiments over a large-scale English dictionary. Experimental results show that this approach can achieve accuracy of 70.1%, which outperforms those published results.

Top Down FPGA设计的黄金组合

电子技术的日新月异,不断地改变着人们的生活方式.而世界电子技术及设计方法的发展,正在给中国的电子设计工程师们以新的挑战和压力.不能否认,目前中国电子设计技术仍远远落后于发达国家水平,尤其是在电子技术的基础产业,即IC/ASIC方面.当国人以国产计算机,电视,VCD,影碟机等产业欣欣向荣,飞速发展而沾沾自喜的时候,却不能不看到,几乎所有的核心技术和几乎所有的内部关键集成电路,仍然印着国外半导体厂家的商标.单从时间上看,国内技术可能只落后一、二十年,但是我们更应该看到:一方面,这一产业的发展是以非线性速度向前推进的,另一方面,当发达国家"全民皆兵",整体发展水平平均较高时,国内仍局限在为数不多的几个国家重点投资企业或合资/独资企业里.

A Cognitive Study on the Category Fruit——Taking under 35-year-old Women's Cognitions as Informants

This paper probes into the category fruit, aiming at revealing the categorization of fruit to find them prototype in under 35-year-old women's cognitions at present. And author uses related category theories, such as prototype category to analyze the outcome of the research. In addition, author also locates women who under 35 years old as this research's informants to find whether the prototype changed in their cognition or not. The method of research is questionnaires, and hands out the questionnaires by the Internet. And this research also uses SSPS to analyze the effective data.

China: An Exemplar in Respecting and Protecting Human Rights

China has developed its own views on human rights and pursued its own path of human rights development in light of the UN Charter principles,its national conditions,and its experience over many years.Human rights in China have scored remarkable achievements.The Chinese perspective on human rights and the Chinese path of human rights development has become a shining example for the whole world.

Automatic texture exemplar extraction based on global and local textureness measures

Texture synthesis is widely used for modeling the appearance of virtual objects. However, traditional texture synthesis techniques eInphasize creation of optimal target textures, and pay insufficient attention to choice of suitable input texture exemplars. Currently, of taining texture exemplars from natural images is a labor intensive task for the artists, requiring careful photography and significant post- processing. In this paper, we present an automatic texture exemplar extraction method based on global and local textureness measures. To improve the efficiency of dominant texture identification, we first perform Poisson disk sampling to randomly and uniformly erop patches from a natural image. For global textureness assessment, we use a GIST descriptor to distinguish textured t）atches from non-textured patches, in conjunction with SVM prediction. To identify real texture, exemplars consisting solely of the dominant texture, we further measure the local textureness of a patch by extracting and matching the local structure （using t）inary Gabor pattern （BGP）） and dominant color features （using color histograms） between a patch and its sub-regions. Finally, we obtain optimal texture exemplars by scoring and ranking extracted patches using these global and local textureness measures We evaluate our method on a variety of images with different kinds of textures. A convincing visual comparison with textures mauually selected by an artist and a statistical study demonstrate its effectiveness.

Differential Evolution with Level-Based Learning Mechanism

To address complex single objective global optimization problems,a new Level-Based Learning Differential Evolution(LBLDE)is developed in this study.In this approach,the whole population is sorted from the best to the worst at the beginning of each generation.Then,the population is partitioned into multiple levels,and different levels are used to exert different functions.In each level,a control parameter is used to select excellent exemplars from upper levels for learning.In this case,the poorer individuals can choose more learning exemplars to improve their exploration ability,and excellent individuals can directly learn from the several best individuals to improve the quality of solutions.To accelerate the convergence speed,a difference vector selection method based on the level is developed.Furthermore,specific crossover rates are assigned to individuals at the lowest level to guarantee that the population can continue to update during the later evolutionary process.A comprehensive experiment is organized and conducted to obtain a deep insight into LBLDE and demonstrates the superiority of LBLDE in comparison with seven peer DE variants.