Discriminative Orthogonal Neighborhood-Preserving Projections for Classification

Orthogonal neighborhood-preserving projection (ONPP) is a recently developed orthogonal linear algorithm for overcoming the out-of-sample problem existing in the well-known manifold learning algorithm, i.e., locally linear embedding. It has been shown that ONPP is a strong analyzer of high-dimensional data. However, when applied to classification problems in a supervised setting, ONPP only focuses on the intraclass geometrical information while ignores the interaction of samples from different classes. To enhance the performance of ONPP in classification, a new algorithm termed discriminative ONPP (DONPP) is proposed in this paper. DONPP 1) takes into account both intraclass and interclass geometries; 2) considers the neighborhood information of interclass relationships; and 3) follows the orthogonality property of ONPP. Furthermore, DONPP is extended to the semisupervised case, i.e., semisupervised DONPP (SDONPP). This uses unlabeled samples to improve the classification accuracy of the original DONPP. Empirical studies demonstrate the effectiveness of both DONPP and SDONPP.

Biologically Inspired Features for Scene Classification in Video Surveillance

Inspired by human visual cognition mechanism, this paper first presents a scene classification method based on an improved standard model feature. Compared with state-of-the-art efforts in scene classification, the newly proposed method is more robust, more selective, and of lower complexity. These advantages are demonstrated by two sets of experiments on both our own database and standard public ones. Furthermore, occlusion and disorder problems in scene classification in video surveillance are also first studied in this paper.

Classification of valence changes of trivalent rare earth ions in alkaline earth borates using artificial neural networks

The investigations of classification on the valence changes from RE3+ to RE2+ (RE = Eu, Sm, Yb, Tm) in host compounds of alkaline earth berate were performed using artificial neural networks (ANNs). For comparison, the common methods of pattern recognition, such as SIMCA, KNN, Fisher discriminant analysis and stepwise discriminant analysis were adopted. A learning set consisting of 24 host compounds and a test set consisting of 12 host compounds were characterized by eight crystal structure parameters. These parameters were reduced from 8 to 4 by leaps and bounds algorithm. The recognition rates from 87.5 to 95.8% and prediction capabilities from 75.0 to 91.7% were obtained. The results provided by ANN method were better than that achieved by the other four methods. (C) 1999 Elsevier Science B.V. All rights reserved.

MULTIVARIATE CLASSIFICATION BASED ON METAL CONTENTS IN HUMAN SENILE CATARACT LENSES

Multivariate classification methods were used to evaluate data on the concentrations of eight metals in human senile lenses measured by atomic absorption spectrometry. Principal components analysis and hierarchical clustering separated senile cataract lenses, nuclei from cataract lenses, and normal lenses into three classes on the basis of the eight elements. Stepwise discriminant analysis was applied to give discriminant functions with five selected variables. Results provided by the linear learning machine method were also satisfactory; the k-nearest neighbour method was less useful.

PenBase, the shrimp antimicrobial peptide penaeidin database: Sequence-based classification and recommended nomenclature

Antimicrobial peptides play a major role in innate immunity. The penaeidins, initially characterized from the shrimp Litopenaeus vannamei, are a family of antimicrobial peptides that appear to be expressed in all penaeid shrimps. As of recent, a large number of penaeid nucleotide sequences have been identified from a variety of penaeid shrimp species and these sequences currently reside in several databases under unique identifiers with no nomenclatural continuity. To facilitate research in this field and avoid potential confusion due to a diverse number of nomenclatural designations, we have made a systematic effort to collect, analyse, and classify all the penaeidin sequences available in every database. We have identified a common penaeidin signature and subsequently established a classification based on amino acid sequences. In order to clarify the naming process, we have introduced a 'penaeidin nomenclature' that can be applied to all extant and future penaeidins. A specialized database, PenBase, which is freely available at http://www.penbase.immunaqua.com, has been developed for the penaeidin family of antimicrobial peptides, to provide comprehensive information about their properties, diversity and nomenclature. (c) 2005 Elsevier Ltd. All rights reserved.

Evaluation of a combined wavelet and a combined principal component analysis classification system for BCG diagnostic problem

Heart disease is one of the main factor causing death in the developed countries. Over several decades, variety of electronic and computer technology have been developed to assist clinical practices for cardiac performance monitoring and heart disease diagnosis. Among these methods, Ballistocardiography (BCG) has an interesting feature that no electrodes are needed to be attached to the body during the measurement. Thus, it is provides a potential application to asses the patients heart condition in the home. In this paper, a comparison is made for two neural networks based BCG signal classification models. One system uses a principal component analysis (PCA) method, and the other a discrete wavelet transform, to reduce the input dimensionality. It is indicated that the combined wavelet transform and neural network has a more reliable performance than the combined PCA and neural network system. Moreover, the wavelet transform requires no prior knowledge of the statistical distribution of data samples and the computation complexity and training time are reduced.

Classification of jinjiang oysters Crassostrea rivularis (Gould, 1861) from China, based on morphology and phylogenetic analysis

The jinjiang oyster Crassostrea rivularis [Gould, 1861. Descriptions of Shells collected in the North Pacific Exploring Expedition under Captains Ringgold and Rodgers. Proc. Boston Soc. Nat. Hist. 8 (April) 33-40] is one of the most important and best-known oysters in China. Based on the color of its flesh, two forms of C rivularis are recognized and referred to as the "white meat" and 11 red meat" oysters. The classification of white and red forms of this species has been a subject of confusion and debate in China. To clarify the taxonomic status of the two forms of C. rivularis, we collected and analyzed oysters from five locations along China's coast using both morphological characters and DNA sequences from mitochondrial 16S rRNA and cytochrome oxidase 1, and the nuclear 28S rRNA genes. Oysters were classified as white or red forms according to their morphological characteristics and then subjected to DNA sequencing. Both morphological and DNA sequence data suggest that the red and white oysters are two separate species. Phylogenetic analysis of DNA sequences obtained in this study and existing sequences of reference species show that the red oyster is the same species as C. ariakensis Wakiya [1929. Japanese food oysters. Jpn. J. Zool. 2, 359-367.], albeit the red oysters from north and south China are genetically distinctive. The white oyster is the same species as a newly described species from Hong Kong, C. hongkongensis Lam and Morton [2003. Mitochondrial DNA and identification of a new species of Crassostrea (Bivalvia: Ostreidae) cultured for centuries in the Pearl River Delta, Hong Kong, China. Aqua. 228, 1-13]. Although the name C. rivularis has seniority over C. ariakensis and C. hongkongensis, the original description of Ostrea rivularis by Gould [1861] does not fit shell characteristics of either the red or the white oysters. We propose that the name of C. rivularis Gould [1861] should be suspended, the red oyster should take the name C. ariakensis, and the white oyster should take the name C. hongkongensis. (C) 2004 Elsevier B.V. All rights reserved.

Classification of common oysters from North China

Oysters are commonly found on rocky shores along China's northern coast, although there is considerable confusion as to what species they are. To determine the taxonomic status of these oysters, we collected specimens from nine locations north of the Yangtze River and conducted genetic identification using DNA sequences. Fragments from three genes, mitochondrial 165 rRNA, mitochondria! cytochrome oxidase I (COI), and nuclear 285 rRNA, were sequenced in six oysters from each of the nine sites. Phylogenetic analysis of all three gene fragments clearly demonstrated that the small oysters commonly found on intertidal rocks in north China are Crassostrea gigas (Thunberg, 1793), not C. plicatula (the zhe oyster) as widely assumed. Their small size and irregular shell characteristics are reflections of the stressful intertidal environment they live in and not reliable characters for classification. Our study confirms that the oysters from Weifang, referred to as Jinjiang oysters or C. rivularis (Gould, 1861), are C. ariakensis (Wakiya, 1929). We found no evidence for the existence of C. talienwhanensis (Crosse, 1862) and other Crassostrea species in north China. Our study highlights the need for reclassifying oysters of China with molecular data.

Molecular phylogeny and biogeography of the Qinghai-Tibet Plateau endemic Nannoglottis (Asteraceae)

All taxa endemic to the Qinghai-Tibet Plateau are hypothesized to have originated in situ or from immediately adjacent areas because of the relatively recent formation of the plateau since the Pliocene, followed by the large-scaled biota extinction and recession caused by the Quaternary ice sheet. However, identification of specific progenitors remains difficult for some endemics, especially some endemic genera. Nannoglottis, with about eight species endemic to this region, is one such genus. Past taxonomic treatments have suggested its relationships with four different tribes of Asteraceae. We intend to identify the closest relatives of Nannoglottis by evaluating the level of monophyly, tribal delimitation, and systematic position of the genus by using molecular data from ndhF gene, trnL-F, and ITS region sequences. We find that all sampled species of Nannoglottis are a well-defined monophyly. This supports all recent taxonomic treatments of Nannoglottis, in which all sampled species were placed in one broadly re-circumscribed genus. Nannoglottis is most closely related to the Astereae, but stands as an isolated genus as the first diverging lineage of the tribe, without close relatives. A tentative relationship was suggested for Nannoglottis and the next lineage of the tribe was based on the ITS topology, the "basal group," which consists of seven genera from the Southern Hemisphere. Such a relationship is supported by some commonly shared plesiomorphic morphological characters. Despite the very early divergence of Nannoglottis in the Astereae, the tribe must be regarded to have its origin in Southern Hemisphere rather than in Asia, because based on all morphological, molecular, biogeographical, and fossil data, the Asteraceae and its major lineages (tribes) are supposed to have originated in the former area. Long-distance dispersal using Southeast Asia as a steppingstone from Southern Hemisphere to the Qinghai-Tibet Plateau is the most likely explanation for this unusual biogeographic link of Nannoglottis. The 23-32-million-year divergence time between Nannoglottis and the other Astereae estimated by DNA sequences predated the formation of the plateau. This estimation is further favored by the fossil record of the Asteraceae and the possible time of origin of the Astereae. Nannoglottis seems to have reached the Qinghai-Tibet area in the Oligocene-Eocene and then re-diversified with the uplift of the plateau. The molecular infragenetic phylogeny of the genus identifies two distinct clades, which reject the earlier infrageneric classification based on the arrangement of the involucral bracts and the length of the ligules, but agree well with the habits and ecological preferences of its current species. The "alpine shrub" vs. "coniferous forest" divergence within Nannoglottis was estimated at about 3.4 million years ago when the plateau began its first large-scale uplifting and the coniferous vegetation began to appear. Most of the current species at the "coniferous forest" clade of the genus are estimated to have originated from 1.02 to 1.94 million years ago, when the second and third uprisings of the plateau occurred, the climate oscillated and the habitats were strongly changed. The assumed evolution, speciation diversity, and radiation of Nannoglottis based on molecular phylogeny and divergence times agree well with the known geological and paleobotanical histories of the Qinghai-Tibet Plateau. (C) 2002 Elsevier Science (USA). All rights reserved.