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

Capturing affective experiences using the SMS experience sampling (SMS-ES) method

This paper reports the feasibility and methodological considerations of using the Short Message System Experience Sampling (SMS-ES) Method, which is an experience sampling research method developed to assist researchers to collect repeat measures of consumers’ affective experiences. The method combines SMS with web-based technology in a simple yet effective way. It is described using a practical implementation study that collected consumers’ emotions in response to using mobile phones in everyday situations. The method is further evaluated in terms of the quality of data collected in the study, as well as against the methodological considerations for experience sampling studies. These two evaluations suggest that the SMS-ES Method is both a valid and reliable approach for collecting consumers’ affective experiences. Moreover, the method can be applied across a range of for-profit and not-for-profit contexts where researchers want to capture repeated measures of consumers’ affective experiences occurring over a period of time. The benefits of the method are discussed to assist researchers who wish to apply the SMS-ES Method in their own research designs.

Leveraging Web 2.0 data for scalable semi-supervised learning of domain-specific sentiment lexicons

Since manually constructing domain-specific sentiment lexicons is extremely time consuming and it may not even be feasible for domains where linguistic expertise is not available. Research on the automatic construction of domain-specific sentiment lexicons has become a hot topic in recent years. The main contribution of this paper is the illustration of a novel semi-supervised learning method which exploits both term-to-term and document-to-term relations hidden in a corpus for the construction of domain specific sentiment lexicons. More specifically, the proposed two-pass pseudo labeling method combines shallow linguistic parsing and corpusbase statistical learning to make domain-specific sentiment extraction scalable with respect to the sheer volume of opinionated documents archived on the Internet these days. Another novelty of the proposed method is that it can utilize the readily available user-contributed labels of opinionated documents (e.g., the user ratings of product reviews) to bootstrap the performance of sentiment lexicon construction. Our experiments show that the proposed method can generate high quality domain-specific sentiment lexicons as directly assessed by human experts. Moreover, the system generated domain-specific sentiment lexicons can improve polarity prediction tasks at the document level by 2:18% when compared to other well-known baseline methods. Our research opens the door to the development of practical and scalable methods for domain-specific sentiment analysis.

An accessible method for teaching doctors about death certification

The World Health Organization recommends that data on mortality in its member countries are collected utilising the Medical Certificate of Cause of Death published in the instruction volume of the ICD-10. However, investment in health information processes necessary to promote the use of this certificate and improve mortality information is lacking in many countries. An appeal for support to make improvements has been launched through the Health Metrics Network’s MOVE-IT strategy (Monitoring of Vital Events – Information Technology) [World Health Organization, 2011]. Despite this international spotlight on the need for capture of mortality data and in the use of the ICD-10 to code the data reported on such certificates, there is little cohesion in the way that certifiers of deaths receive instruction in how to complete the death certificate, which is the main source document for mortality statistics. Complete and accurate documentation of the immediate, underlying and contributory causes of death of the decedent on the death certificate is a requirement to produce standardised statistical information and to the ability to produce cause-specific mortality statistics that can be compared between populations and across time. This paper reports on a research project conducted to determine the efficacy and accessibility of the certification module of the WHO’s newly-developed web based training tool for coders and certifiers of deaths. Involving a population of medical students from the Fiji School of Medicine and a pre and post research design, the study entailed completion of death certificates based on vignettes before and after access to the training tool. The ability of the participants to complete the death certificates and analysis of the completeness and specificity of the ICD-10 coding of the reported causes of death were used to measure the effect of the students’ learning from the training tool. The quality of death certificate completion was assessed using a Quality Index before and after the participants accessed the training tool. In addition, the views of the participants about accessibility and use of the training tool were elicited using a supplementary questionnaire. The results of the study demonstrated improvement in the ability of the participants to complete death certificates completely and accurately according to best practice. The training tool was viewed very positively and its implementation in the curriculum for medical students was encouraged. Participants also recommended that interactive discussions to examine the certification exercises would be an advantage.

A node-based smoothed conforming point interpolation method (NS-CPIM) for elasticity problems

This paper formulates a node-based smoothed conforming point interpolation method (NS-CPIM) for solid mechanics. In the proposed NS-CPIM, the higher order conforming PIM shape functions (CPIM) have been constructed to produce a continuous and piecewise quadratic displacement field over the whole problem domain, whereby the smoothed strain field was obtained through smoothing operation over each smoothing domain associated with domain nodes. The smoothed Galerkin weak form was then developed to create the discretized system equations. Numerical studies have demonstrated the following good properties: NS-CPIM (1) can pass both standard and quadratic patch test; (2) provides an upper bound of strain energy; (3) avoid the volumetric locking; (4) provides the higher accuracy than those in the node-based smoothed schemes of the original PIMs.

Raman spectroscopy of selected tsumcorite Pb(Zn,Fe3+)2(AsO4)2(OH,H2O) minerals –implications for arsenate accumulation

The presence of arsenic in the environment is a hazard. The accumulation of arsenate by a range of cations in the formation of minerals provides a mechanism for the accumulation of arsenate. The formation of the tsumcorite minerals is an example of a series of minerals which accumulate arsenate. There are about twelve examples in this mineral group. Raman spectroscopy offers a method for the analysis of these minerals. The structure of selected tsumcorite minerals with arsenate and sulphate anions were analysed by Raman spectroscopy. Isomorphic substitution of sulphate for arsenate is observed for gartrellite and thometzekite. A comparison is made with the sulphate bearing mineral natrochalcite. The position of the hydroxyl and water stretching vibrations are related to the strength of the hydrogen bond formed between the OH unit and the AsO43- anion. Characteristic Raman spectra of the minerals enable the assignment of the bands to specific vibrational modes.

Using the work system method with freshman information systems students

Recent surveys of information technology management professionals show that understanding business domains in terms of business productivity and cost reduction potential, knowledge of different vertical industry segments and their information requirements, understanding of business processes and client-facing skills are more critical for Information Systems personnel than ever before. In an attempt to restrucuture the information systems curriculum accordingly, our view it that information systems students need to develop an appreciation for organizational work systems in order to understand the operation and significance of information systems within such work systems.

A semi-local method for iterative depth-map refinement

We present an iterative hierarchical algorithm for multi-view stereo. The algorithm attempts to utilise as much contextual information as is available to compute highly accurate and robust depth maps. There are three novel aspects to the approach: 1) firstly we incrementally improve the depth fidelity as the algorithm progresses through the image pyramid; 2) secondly we show how to incorporate visual hull information (when available) to constrain depth searches; and 3) we show how to simultaneously enforce the consistency of the depth-map by continual comparison with neighbouring depth-maps. We show that this approach produces highly accurate depth-maps and, since it is essentially a local method, is both extremely fast and simple to implement.