Using multi-label classification for acoustic pattern detection and assisting bird species surveys

Acoustics is a rich source of environmental information that can reflect the ecological dynamics. To deal with the escalating acoustic data, a variety of automated classification techniques have been used for acoustic patterns or scene recognition, including urban soundscapes such as streets and restaurants; and natural soundscapes such as raining and thundering. It is common to classify acoustic patterns under the assumption that a single type of soundscapes present in an audio clip. This assumption is reasonable for some carefully selected audios. However, only few experiments have been focused on classifying simultaneous acoustic patterns in long-duration recordings. This paper proposes a binary relevance based multi-label classification approach to recognise simultaneous acoustic patterns in one-minute audio clips. By utilising acoustic indices as global features and multilayer perceptron as a base classifier, we achieve good classification performance on in-the-field data. Compared with single-label classification, multi-label classification approach provides more detailed information about the distributions of various acoustic patterns in long-duration recordings. These results will merit further biodiversity investigations, such as bird species surveys.

Unraveling the packing pattern leading to gelation using SS NMR and X-ray diffraction: direct observation of the evolution of self-assembled fibers

A detailed understanding of the mode of packing patterns that leads to the gelation of low molecular mass gelators derived from bile acid esters was carried out using solid state NMR along with complementary techniques such as powder X-ray diffraction (PXRD), differential scanning calorimetry (DSC), thermogravimetric analysis (TGA) and polarizing optical microscopy (POM). Solid state C-13{H-1} cross polarization (CP) magic angle spinning (MAS) NMR of the low molecularmass gel in its native state was recorded for the first time. A close resemblance in the packing patterns of the gel, xerogel and bulk solid states was revealed upon comparing their C-13{H-1} CPMAS NMR spectral pattern. A doublet resonance pattern of C-13 signals in C-13{H-1}CPMAS NMR spectra were observed for the gelator molecules, whereas the non-gelators showed simple singlet resonance or resulted inthe formation of inclusion complexes/solvates. PXRD patterns revealed a close isomorphous nature of the gelators indicating the similarity in the mode of the packing pattern in their solid state. Direct imaging of the evolution of nanofibers (sol-gel transition) was carried out using POM, which proved the presence of self-assembled fibrillar networks (SAFINs) in the gel. Finally powder X-ray structure determination revealed the presence of two non-equivalent molecules in an asymmetric unit which is responsible for the doublet resonance pattern in the solid state NMR spectra.

Novel composite coded pattern for small angle measurement using imaging method -art.no.62891D

A novel approach for measurement of small rotation angles using imaging method is proposed and demonstrated. A plane mirror placed on a precision rotating table is used for imaging the newly designed composite coded pattern. The imaged patterns are captured with the help of a CCD camera. The angular rotation of the plane mirror is determined from a pair of the images of the pattern, captured once before and once after affecting the tilt of the mirror. Both simulation and experimental results suggest that the proposed approach not only retains the advantages of the original imaging method but also contributes significantly to the enhancement of its measuring range (+/- 4.13 degrees with accuracy of the order of 1 arcsec).

Memory-based reasoning approach for pattern recognition of binary images

Template matching is concerned with measuring the similarity between patterns of two objects. This paper proposes a memory-based reasoning approach for pattern recognition of binary images with a large template set. It seems that memory-based reasoning intrinsically requires a large database. Moreover, some binary image recognition problems inherently need large template sets, such as the recognition of Chinese characters which needs thousands of templates. The proposed algorithm is based on the Connection Machine, which is the most massively parallel machine to date, using a multiresolution method to search for the matching template. The approach uses the pyramid data structure for the multiresolution representation of templates and the input image pattern. For a given binary image it scans the template pyramid searching the match. A binary image of N × N pixels can be matched in O(log N) time complexity by our algorithm and is independent of the number of templates. Implementation of the proposed scheme is described in detail.

New phase unwrapping strategy for rapid and dense 3D data acquisition in structured light approach

Sinusoidal structured light projection (SSLP) technique, specifically-phase stepping method, is in widespread use to obtain accurate, dense 3-D data. But, if the object under investigation possesses surface discontinuities, phase unwrapping (an intermediate step in SSLP) stage mandatorily require several additional images, of the object with projected fringes (of different spatial frequencies), as input to generate a reliable 3D shape. On the other hand, Color-coded structured light projection (CSLP) technique is known to require a single image as in put, but generates sparse 3D data. Thus we propose the use of CSLP in conjunction with SSLP to obtain dense 3D data with minimum number of images as input. This approach is shown to be significantly faster and reliable than temporal phase unwrapping procedure that uses a complete exponential sequence. For example, if a measurement with the accuracy obtained by interrogating the object with 32 fringes in the projected pattern is carried out with both the methods, new strategy proposed requires only 5 frames as compared to 24 frames required by the later method.

Multi-Pattern Viterbi Algorithm for joint decoding of multiple speech patterns

Joint decoding of multiple speech patterns so as to improve speech recognition performance is important, especially in the presence of noise. In this paper, we propose a Multi-Pattern Viterbi algorithm (MPVA) to jointly decode and recognize multiple speech patterns for automatic speech recognition (ASR). The MPVA is a generalization of the Viterbi Algorithm to jointly decode multiple patterns given a Hidden Markov Model (HMM). Unlike the previously proposed two stage Constrained Multi-Pattern Viterbi Algorithm (CMPVA),the MPVA is a single stage algorithm. MPVA has the advantage that it cart be extended to connected word recognition (CWR) and continuous speech recognition (CSR) problems. MPVA is shown to provide better speech recognition performance than the earlier techniques: using only two repetitions of noisy speech patterns (-5 dB SNR, 10% burst noise), the word error rate using MPVA decreased by 28.5%, when compared to using individual decoding. (C) 2010 Elsevier B.V. All rights reserved.

Nonlinear programming solutions for controlling the vibration pattern of stretched strings

The problem of controlling the vibration pattern of a driven string is considered. The basic question dealt with here is to find the control forces which reduce the energy of vibration of a driven string over a prescribed portion of its length while maintaining the energy outside that length above a desired value. The criterion of keeping the response outside the region of energy reduction as close to the original response as possible is introduced as an additional constraint. The slack unconstrained minimization technique (SLUMT) has been successfully applied to solve the above problem. The effect of varying the phase of the control forces (which results in a six-variable control problem) is then studied. The nonlinear programming techniques which have been effectively used to handle problems involving many variables and constraints therefore offer a powerful tool for the solution of vibration control problems.

Tyrphostin-A47 inhibitable tyrosine phosphorylation of flagellar proteins is associated with distinct alteration of motility pattern in hamster spermatozoa

To acquire fertilizing potential, mammalian spermatozoa must undergo capacitation and acrosome reaction. Our earlier work showed that pentoxifylline (0.45 mM), a sperm motility stimulant, induced an early onset of hamster sperm capacitation associated with tyrosine phosphorylation of 45-80 kDa proteins, localized to the mid-piece of the sperm tail. To assess the role of protein tyrosine phosphorylation in sperm capacitation, we used tyrphostin-A47 (TP-47), a specific protein tyrosine kinase inhibitor. The dose-dependent (0.1-0.5 mM) inhibition of tyrosine phosphorylation by TP-47 was associated with inhibition of hyperactivated motility and 0.5 mM TP-47-treated spermatozoa exhibited a distinct circular motility pattern. This was accompanied by hypo-tyrosine phosphorylation of 45-60 kDa proteins, localized to the principal piece of the intact-sperm and the outer dense fiber-like structures in detergent treated-sperm. Sperm kinematic analysis (by CASA) of spermatozoa, exhibiting circular motility (at 1st hr), showed lower values of straight line velocity, curvilinear velocity and average path velocity, compared to untreated controls. Other TP-47 analogues, tyrphostin-AG1478 and -AG1296, had no effect either on kinematic parameters or sperm protein tyrosine phosphorylation. These studies indicate that TP-47-induced circular motility of spermatozoa is compound-specific and that the tyrosine phosphorylation status of 45-60 kDa flagellum-localized proteins could be key regulators of sperm flagellar bending pattern, associated with the hyperactivation of hamster spermatozoa.

Helsingin metropolialueen maisemaekologiset muutokset vuosina 1955-2009

Landscape is shaped by natural environment and increasingly by human activity. In landscape ecology, the concept of landscape can be defined as a kilometre-scale mosaic formed by different land-use types. In Helsinki Metropolitan Region, the landscape change caused by urbanization has accelerated after the 1950s. Prior to that, the landscape of the region was mainly only shaped by agriculture. The goal of this study was in addition to describing the landscape change to discuss the factors impacting the landscape change and evaluate thelandscape ecological impacts of the change. Three study areas at different distances from Helsinki city centre were chosen in order to look at the landscape change. Study areas were Malmi, Espoo and Mäntsälä regions representing different parts of the urban-to-rural gradient in 1955, 1975, 1990 and 2009. Land-use of the maps was then digitized into five classes: agricultural lands, semi-natural grasslands, built areas, waters and others using GIS methods. First, landscape change was studied using landscape ecological indices. Indices used were PLAND i.e. the proportions of the different land-use types in the landscape; MPS, SHEI and SHDI which describe fragmentation and heterogeneity of the landscape; and MSI and ED which are measures of patch shape. Second, landscape change was studied statistically in relation to topography, soil and urban structure of the study areas. Indicators used concerning urban structure were number of residents, car ownership and travel-related zones of urban form which indicate the degree of urban sprawl within the study areas. For the statistical analyses, each of the 9.25 x 9.25 km sized study areas was further divided into grids with resolution of 0.25 x 0.25 kilometres. Third, the changes in the green structure of the study areas were evaluated. The landscape change reflected by the proportions of the land-use types was the most notable in Malmi area where a large amount of agricultural land was developed from 1955 to 2009. The proportion of semi-natural grasslands also showed an interesting pattern in relation to urbanization. When urbanization started, a great number of agricultural lands were abandoned and turned into semi-natural grasslands but as the urbanization accelerated, the number of semi-natural grasslands started to decline because of urban densification. Landscape fragmentation and heterogeneity were the most widespread in Espoo study area which is not only because of the great differences in relative heights within the region but also its location in the rural-urban fringe. According to the results, urbanization induced agricultural lands to be more regular in shape both spatially and temporally whereas for built areas and semi-natural grasslands the impact of urbanization was reverse. Changes in landscape were the most insignificant in the most rural study area Mäntsälä. In Mäntsälä, built area per resident showed the greatest values indicating a widespread urban sprawl. The values were the smallest in highly urbanized Malmi study area. Unlike other study areas, in Mäntsälä the proportion of developing land in the ecologically disadvantageous cardependent zone was on the increase. On the other hand, the green structure of the Mäntsälä study area was the most advantageous whereas Malmi study area showed the most ecologically disadvantageous structure. Considering all the landscape ecological criteria used, the landscape structure of Espoo study area proved to be the best not least because of the great heterogeneity of its landscape. Thus the study confirmed the previous results according to which landscape heterogeneity is the most significant in areas exposed to a moderate human impact.

A heuristic clustering algorithm using union of overlapping pattern-cells

Relative geometric arrangements of the sample points, with reference to the structure of the imbedding space, produce clusters. Hence, if each sample point is imagined to acquire a volume of a small M-cube (called pattern-cell), depending on the ranges of its (M) features and number (N) of samples; then overlapping pattern-cells would indicate naturally closer sample-points. A chain or blob of such overlapping cells would mean a cluster and separate clusters would not share a common pattern-cell between them. The conditions and an analytic method to find such an overlap are developed. A simple, intuitive, nonparametric clustering procedure, based on such overlapping pattern-cells is presented. It may be classified as an agglomerative, hierarchical, linkage-type clustering procedure. The algorithm is fast, requires low storage and can identify irregular clusters. Two extensions of the algorithm, to separate overlapping clusters and to estimate the nature of pattern distributions in the sample space, are also indicated.