Read-only memory disk with AgOx and AgInSbTe superresolution mask layer

Two novel read-only memory (ROM) disks, one with an AgOx mask layer and the other with an AgInSbTe mask layer, are proposed and studied. The AgOx and the AgInSbTe films sputtered on the premastered substrates with pit depths of 50 nm and pit lengths (space) of 380 nm are studied by atomic force microscopy. Disk readout measurement is carried out using a dynamic setup with a laser wavelength of 632.8 nm and an object lens numerical aperture (NA) of 0.40. Results show that the superresolution effect happens only at a suitable oxygen flow ratio for the AgOx ROM disk. The best superresolution readout effect is achieved at an oxygen flow ratio of 0.5 with the smoothest film surface. Compared with the AgOx ROM disk, the AgInSbTe ROM disk has a much smoother film surface and better superresolution effect. A carrier-to-noise ratio (CNR) of above 40 dB can be obtained at an appropriate readout power and readout velocity. The readout CNR of both the AgOx and AgInSbTe ROM disks have a nonlinear dependence on the readout power. The superresolution readout mechanisms for these ROM disks are analyzed and compared as well. (c) 2005 Society of Photo-Optical Instrumentation Engineers.

Read-only memory disk with AgOx super-resolution mask layer

A novel read-only memory (ROM) disk with an AgOx mask layer was proposed and studied in this letter. The AgOx films sputtered on the premastered substrates, with pits depth of 50 nm and pits length of 380 nm, were studied by an atomic force microscopy. The transmittances of these AgOx films were also measured by a spectrophotometer. Disk measurement was carried out by a dynamic setup with a laser wavelength of 632.8 nm and a lens numerical aperture (NA) of 0.40. The readout resolution limit of this setup was λ/(4NA) (400 nm). Results showed that the super-resolution readout happened only when the oxygen flow ratios were at suitable values for these disks. The best super-resolution performance was achieved at the oxygen flow ratio of 0.5 with the smoothest film surface. The super-resolution readout mechanism of these ROM disks was analyzed as well.

Read-only memory disk with AgOx and AgInSbTe superresolution mask layer

Two novel read-only memory (ROM) disks, one with an AgOx mask layer and the other with an AgInSbTe mask layer, are proposed and studied. The AgOx and the AgInSbTe films sputtered on the premastered substrates with pit depths of 50 nm and pit lengths (space) of 380 nm are studied by atomic force microscopy. Disk readout measurement is carried out using a dynamic setup with a laser wavelength of 632.8 nm and an object lens numerical aperture (NA) of 0.40. Results show that the superresolution effect happens only at a suitable oxygen flow ratio for the AgOx ROM disk. The best superresolution readout effect is achieved at an oxygen flow ratio of 0.5 with the smoothest film surface. Compared with the AgOx ROM disk, the AgInSbTe ROM disk has a much smoother film surface and better superresolution effect. A carrier-to-noise ratio (CNR) of above 40 dB can be obtained at an appropriate readout power and readout velocity. The readout CNR of both the AgOx and AgInSbTe ROM disks have a nonlinear dependence on the readout power. The superresolution readout mechanisms for these ROM disks are analyzed and compared as well. (c) 2005 Society of Photo-Optical Instrumentation Engineers.

THE PHYLOGENETIC-RELATIONSHIPS AND CLASSIFICATION OF THE DOUCS AND SNUB-NOSED LANGURS OF CHINA AND VIETNAM

The taxonomy of the douc and snub-nosed langurs has changed several times during the 20th century. The controversy over the systematic position of these animals has been due in part to difficulties in studying them: both the doucs and the snub-nosed langurs are rare in the wild and are generally poorly represented in institutional collections. This review is based on a detailed examination of relatively large numbers of specimens of most of the species of langurs concerned. An attempt was made to draw upon as many types of information as were available in order to make an assessment of the phyletic relationships between the langur species under discussion. Toward this end, quantitative and qualitative features of the skeleton, specific features of visceral anatomy and characteristics of the pelage were utilized. The final data matrix comprised 178 characters. The matrix was analyzed using the program Hennig86. The results of the analysis support the following conclusions: (1) that the douc and snub-nosed langurs are generically distinct and should be referred to as species of Pygathrix and Rhinopithecus, respectively; (2) that the Tonkin snub-nosed langur be placed in its own subgenus as Rhinopithecus (Presbytiscus) avunculus and that the Chinese snub-nosed langur thus be placed in the subgenus Rhinopithecus (Rhinopithecus); (3) that four extant species of Rhinopithecus be recognized: R. (Rhinopithecus) roxellana Milne Edwards, 1870; R. (Rhinopithecus) bieti Milne Edwards, 1897; R. (Rhinopithecus) brelichi Thomas, 1903, and R. (Presbytiscus) avunculus Dollman, 1912; (4) that the Chinese snub-nosed langurs fall into northern and southern subgroups divided by the Yangtze river; (5) that R. lantianensis Hu and Qi, 1978, is a valid fossil species, and (6) the precise affinities and taxonomic status of the fossil species R. tingianus Matthew and Granger, 1923, are unclear because the type specimen is a subadult.

CLASSIFICATION AND EVOLUTION OF ASIAN COLOBINES

In order to study the differentiation of Asian colobines, 14 variables measured on 123 skulls, including Rhinopithecus, Presbytis, Presbytiscus (Rhinopithecus avunculus), Pygathrix and Nasalis were analyzed by one-way, cluster and discriminant function analyses. Information on paleoenvironmental changes in China and southeast Asia since the late Tertiary was used to examine the influences of migratory routes and range of distribution in Asian colobines. A cladogram for 6 genera of Asian colobines was constructed from the results of various analyses. Some new points or revisions were suggested: (1) Following one of two migratory routes, ancient species of Asian colobines perhaps passed through Xizang (Tibet) along the northern bank of the Tethys sea and through the Heng Duan Shan regions of Yunnan into Vietnam. An ancient landmass linking Yunnan and Xizang was already present on the east bank of the Tethys sea. Accordingly, Asian colobines would have two centers of evolutionary origin: Sundaland and the Heng Duan Shan regions of China. (2) Pygathrix shares more cranial features with Presbytiscus than with Rhinopithecus. This differs somewhat from the conclusion reached by Groves. (3) Nasalis (karyotype: 2n = 48) may be the most primitive genus among Asian colobines. Certain features shared with Rhinopithecus, e.g. large body size, terrestrial activity and limb proportions, can be interpreted as symple-siomorphic characters. (4) Rhinopithecus, with respect to craniofacial features, is a special case among Asian colobines. It combines a high degree of evolutionary specialization with retention of some primitive features thought to have been present in the ancestral Asian colobine.

An Automatic Classification Method of Metabolic Cycle Based on Biomimetic Pattern Recognition

Correct classification of different metabolic cycle stages to identification cell cycle is significant in both human development and clinical diagnostics. However, it has no perfect method has been reached in classification of metabolic cycle yet. This paper exploringly puts forward an automatic classification method of metabolic cycle based on Biomimetic pattern recognition (BPR). As to the three phases of yeast metabolic cycle, the correct classification rate reaches 90%, 100% and 100% respectively.

Method for improving classification performance of neural network based on fuzzy input and network inversion

In order to effectively improve the classification performance of neural network, first architecture of fuzzy neural network with fuzzy input was proposed. Next a cost function of fuzzy outputs and non-fuzzy targets was defined. Then a learning algorithm from the cost function for adjusting weights was derived. And then the fuzzy neural network was inversed and fuzzified inversion algorithm was proposed. Finally, computer simulations on real-world pattern classification problems examine the effectives of the proposed approach. The experiment results show that the proposed approach has the merits of high learning efficiency, high classification accuracy and high generalization capability.

Viruses' complete genomes classification based on geometrical learning

In this paper, we proposed a method of classification for viruses' complete genomes based on graph geometrical theory in order to viruses classification. Firstly, a model of triangular geometrical graph was put forward, and then constructed feature-space-samples-graphs for classes of viruses' complete genomes in feature space after feature extraction and normalization. Finally, we studied an algorithm for classification of viruses' complete genomes based on feature-space-samples-graphs. Compared with the BLAST algorithm, experiments prove its efficiency.

Ground target detection, classification and sensor fusion in distributed fiber seismic sensor network - art. no. 683015

This paper describes the ground target detection, classification and sensor fusion problems in distributed fiber seismic sensor network. Compared with conventional piezoelectric seismic sensor used in UGS, fiber optic sensor has advantages of high sensitivity and resistance to electromagnetic disturbance. We have developed a fiber seismic sensor network for target detection and classification. However, ground target recognition based on seismic sensor is a very challenging problem because of the non-stationary characteristic of seismic signal and complicated real life application environment. To solve these difficulties, we study robust feature extraction and classification algorithms adapted to fiber sensor network. An united multi-feature (UMF) method is used. An adaptive threshold detection algorithm is proposed to minimize the false alarm rate. Three kinds of targets comprise personnel, wheeled vehicle and tracked vehicle are concerned in the system. The classification simulation result shows that the SVM classifier outperforms the GMM and BPNN. The sensor fusion method based on D-S evidence theory is discussed to fully utilize information of fiber sensor array and improve overall performance of the system. A field experiment is organized to test the performance of fiber sensor network and gather real signal of targets for classification testing.