Pattern recognition using invariants defined from higher order spectra : 2-D image inputs

A new algorithm for extracting features from images for object recognition is described. The algorithm uses higher order spectra to provide desirable invariance properties, to provide noise immunity, and to incorporate nonlinearity into the feature extraction procedure thereby allowing the use of simple classifiers. An image can be reduced to a set of 1D functions via the Radon transform, or alternatively, the Fourier transform of each 1D projection can be obtained from a radial slice of the 2D Fourier transform of the image according to the Fourier slice theorem. A triple product of Fourier coefficients, referred to as the deterministic bispectrum, is computed for each 1D function and is integrated along radial lines in bifrequency space. Phases of the integrated bispectra are shown to be translation- and scale-invariant. Rotation invariance is achieved by a regrouping of these invariants at a constant radius followed by a second stage of invariant extraction. Rotation invariance is thus converted to translation invariance in the second step. Results using synthetic and actual images show that isolated, compact clusters are formed in feature space. These clusters are linearly separable, indicating that the nonlinearity required in the mapping from the input space to the classification space is incorporated well into the feature extraction stage. The use of higher order spectra results in good noise immunity, as verified with synthetic and real images. Classification of images using the higher order spectra-based algorithm compares favorably to classification using the method of moment invariants

Characterizing the signal pattern of a four-cylinder diesel engine using acoustic emission and vibration analysis

Condition monitoring of diesel engines can prevent unpredicted engine failures and the associated consequence. This paper presents an experimental study of the signal characteristics of a 4-cylinder diesel engine under various loading conditions. Acoustic emission, vibration and in-cylinder pressure signals were employed to study the effectiveness of these techniques for condition monitoring and identifying symptoms of incipient failures. An event driven synchronous averaging technique was employed to average the quasi-periodic diesel engine signal in the time domain to eliminate or minimize the effect of engine speed and amplitude variations on the analysis of condition monitoring signal. It was shown that acoustic emission (AE) is a better technique than vibration method for condition monitor of diesel engines due to its ability to produce high quality signals (i.e., excellent signal to noise ratio) in a noisy diesel engine environment. It was found that the peak amplitude of AE RMS signals correlating to the impact-like combustion related events decreases in general due to a more stable mechanical process of the engine as the loading increases. A small shift in the exhaust valve closing time was observed as the engine load increases which indicates a prolong combustion process in the cylinder (to produce more power). On the contrary, peak amplitudes of the AE RMS attributing to fuel injection increase as the loading increases. This can be explained by the increase fuel friction caused by the increase volume flow rate during the injection. Multiple AE pulses during the combustion process were identified in the study, which were generated by the piston rocking motion and the interaction between the piston and the cylinder wall. The piston rocking motion is caused by the non-uniform pressure distribution acting on the piston head as a result of the non-linear combustion process of the engine. The rocking motion ceased when the pressure in the cylinder chamber stabilized.

Pattern recognition using invariants defined from higher order spectra - one-dimensional inputs

A new approach to pattern recognition using invariant parameters based on higher order spectra is presented. In particular, invariant parameters derived from the bispectrum are used to classify one-dimensional shapes. The bispectrum, which is translation invariant, is integrated along straight lines passing through the origin in bifrequency space. The phase of the integrated bispectrum is shown to be scale and amplification invariant, as well. A minimal set of these invariants is selected as the feature vector for pattern classification, and a minimum distance classifier using a statistical distance measure is used to classify test patterns. The classification technique is shown to distinguish two similar, but different bolts given their one-dimensional profiles. Pattern recognition using higher order spectral invariants is fast, suited for parallel implementation, and has high immunity to additive Gaussian noise. Simulation results show very high classification accuracy, even for low signal-to-noise ratios.

BioPatML.NET – a bioinformatic pattern search engine

In the present paper, we introduce BioPatML.NET, an application library for the Microsoft Windows .NET framework [2] that implements the BioPatML pattern definition language and sequence search engine. BioPatML.NET is integrated with the Microsoft Biology Foundation (MBF) application library [3], unifying the parsers and annotation services supported or emerging through MBF with the language, search framework and pattern repository of BioPatML. End users who wish to exploit the BioPatML.NET engine and repository without engaging the services of a programmer may do so via the freely accessible web-based BioPatML Editor, which we describe below.

An evaluation of the pattern and structure mathematics awareness program in the early school years

This paper reports a 2-year longitudinal study on the effectiveness of the Pattern and Structure Mathematical Awareness Program (PASMAP) on students’ mathematical development. The study involved 316 Kindergarten students in 17 classes from four schools in Sydney and Brisbane. The development of the PASA assessment interview and scale are presented. The intervention program provided explicit instruction in mathematical pattern and structure that enhanced the development of students’ spatial structuring, multiplicative reasoning, and emergent generalisations. This paper presents the initial findings of the impact of the PASMAP and illustrates students’ structural development.

Developing the Pattern and Structure Assessment (PASA) interview to inform early mathematics learning

The Pattern and Structure Mathematical Awareness Program(PASMAP) stems from a 2-year longitudinal study on students’ early mathematical development. The paper outlines the interview assessment the Pattern and Structure Assessment(PASA) designed to describe students’ awareness of mathematical pattern and structure across a range of concepts. An overview of students’ performance across items and descriptions of their structural development are described.

Is anybody there? Bootstrapping attendance with engagement

The report card for the introductory programming unit at our university has historically been unremarkable in terms of attendance rates, student success rates and student retention in both the unit and the degree course. After a course restructure recently involving a fresh approach to introducing programming, we reported a high retention in the unit, with consistently high attendance and a very low failure rate. Following those encouraging results, we collected student attendance data for several semesters and compared attendance rates to student results. We have found that interesting workshop material which directly relates to course-relevant assessment items and therefore drives the learning, in an engaging collaborative learning environment has improved attendance to an extraordinary extent, with student failure rates plummeting to the lowest in recorded history at our university.

Ingroup and role identity influences on the initiation and maintenance of students' voluntary attendance at peer study sessions for statistics

Background: Although class attendance is linked to academic performance, questions remain about what determines students’ decisions to attend or miss class. Aims: In addition to the constructs of a common decision-making model, the theory of planned behaviour, the present study examined the influence of student role identity and university student (in-group) identification for predicting both the initiation and maintenance of students’ attendance at voluntary peer-assisted study sessions in a statistics subject. Sample: University students enrolled in a statistics subject were invited to complete a questionnaire at two time points across the academic semester. A total of 79 university students completed questionnaires at the first data collection point, with 46 students completing the questionnaire at the second data collection point. Method: Twice during the semester, students’ attitudes, subjective norm, perceived behavioural control, student role identity, in-group identification, and intention to attend study sessions were assessed via on-line questionnaires. Objective measures of class attendance records for each half-semester (or ‘term’) were obtained. Results: Across both terms, students’ attitudes predicted their attendance intentions, with intentions predicting class attendance. Earlier in the semester, in addition to perceived behavioural control, both student role identity and in-group identification predicted students’ attendance intentions, with only role identity influencing intentions later in the semester. Conclusions: These findings highlight the possible chronology that different identity influences have in determining students’ initial and maintained attendance at voluntary sessions designed to facilitate their learning.

Alternatives to youth imprisonment : evaluating the Victorian youth attendance order

On 22 June 1988 the then Minister for Community Services Victoria, Race Matthews, officially launched the Youth Attendance Order (YAO), a high tariff alternative for young offenders aged between 15 and 18 years who were facing a term of detention. Throughout the order's gestation, much debate occurred about the impact it would have on rates of juvenile incarceration as well as about the potential ‘net widening’ effect it could have on less serious offenders. In May 1994 the National Centre For Socio-Legal Studies at La Trobe University submitted its report evaluating the Victorian Youth Attendance Order. This article presents some of the major findings of that report and examines the future options for this high tariff order in juvenile justice

Expression Pattern of the Alpha-Kafirin Promoter Coupled with a Signal Peptide from Sorghum bicolor L. Moench

Regulatory sequences with endosperm specificity are essential for foreign gene expression in the desired tissue for both grain quality improvement and molecular pharming. In this study, promoters of seed storage α-kafirin genes coupled with signal sequence (ss) were isolated from Sorghum bicolor L. Moench genomic DNA by PCR. The α-kafirin promoter (α-kaf) contains endosperm specificity-determining motifs, prolamin-box, the O2-box 1, CATC, and TATA boxes required for α-kafirin gene expression in sorghum seeds. The constructs pMB-Ubi-gfp and pMB-kaf-gfp were microprojectile bombarded into various sorghum and sweet corn explants. GFP expression was detected on all explants using the Ubi promoter but only in seeds for the α-kaf promoter. This shows that the α-kaf promoter isolated was functional and demonstrated seed-specific GFP expression. The constructs pMB-Ubi-ss-gfp and pMB-kaf-ss-gfp were also bombarded into the same explants. Detection of GFP expression showed that the signal peptide (SP)::GFP fusion can assemble and fold properly, preserving the fluorescent properties of GFP.

Workflow resource pattern modelling and visualization

Workflow patterns have been recognized as the theoretical basis to modeling recurring problems in workflow systems. A form of workflow patterns, known as the resource patterns, characterise the behaviour of resources in workflow systems. Despite the fact that many resource patterns have been discovered, people still preclude them from many workflow system implementations. One of reasons could be obscurityin the behaviour of and interaction between resources and a workflow management system. Thus, we provide a modelling and visualization approach for the resource patterns, enabling a resource behaviour modeller to intuitively see the specific resource patterns involved in the lifecycle of a workitem. We believe this research can be extended to benefit not only workflow modelling, but also other applications, such as model validation, human resource behaviour modelling, and workflow model visualization.