Enhancing acoustic emission signals from multi-cylinder diesel engine

This paper presents techniques which can be viewed as pre-processing step towards diagnosis of faults in a small size multi-cylinder diesel engine. Preliminary analysis of the acoustic emission (AE) signals is outlined, including time-frequency analysis, selection of optimum frequency band. Some results of applying mean field independent component analysis (MFICA) to separate the AE root mean square (RMS) signals are also outlined. The results on separation of RMS signals show this technique has the potential of increasing the probability to successfully identify the AE events associated with the various mechanical events.

User-web interactions : how wholistic/analytic web users search the web?

User-Web interactions have emerged as an important research in the field of information science. In this study, we examine extensively the Web searching performed by general users. Our goal is to investigate the effects of users’ cognitive styles on their Web search behavior in relation to two broad components: Information Searching and Information Processing Approaches. We use questionnaires, a measure of cognitive style, Web session logs and think-aloud as the data collection instruments. Our study findings show wholistic Web users tend to adopt a top-down approach to Web searching, where the users searched for a generic topic, and then reformulate their queries to search for specific information. They tend to prefer reading to process information. Analytic users tend to prefer a bottom-up approach to information searching and they process information by scanning search result pages.

Betting on the underdog : bricolage as an engine of resource advantage

Resource-based theory posits that firms achieve high performance by controlling resources that are rare, valuable and costly for others to duplicate or work around. Yet scholars have been less successful understanding processes and behaviours by which firms develop such resources. We draw on the behavioral theory of bricolage from the entrepreneurship literature to suggest one such mechanism by which firms may develop such resource-based advantages. The core of our argument is that idiosyncratic bundling processes synonymous with bricolage behavior may create advantageous resource positions by (i) allowing resource constrained firms to allocate more of their limited resources to activities that they view as more strategically important, and (ii) increasing the difficulties other firms face in trying to imitate these advantages. Based on this reasoning we develop several hypotheses which we test in the context of several samples from a large, longitudinal, Australian study of new firm development. The results support our arguments that bricolage will improve a firms’ overall resource positions while generating more areas of strong resource advantage and fewer areas of strong resource disadvantage. We find little support, however, for our arguments that bricolage will make a firms’ key resource advantages more difficult for other firms to imitate. We find some support for our argument that the role of bricolage in creating resource advantages will be enhanced by the quality of the opportunity with which a firm is engaged.

Modelling web search behaviour : a user’s cognitive style perspective [Unpublished]

Many researchers have investigated and modelled aspects of Web searching. A number of studies have explored the relationships between individual differences and Web searching. However, limited studies have explored the role of users’ cognitive styles in determining Web searching behaviour. Current models of Web searching have limited consideration of users’ cognitive styles. The impact of users’ cognitive style on Web searching and their relationships are little understood or represented. Individuals differ in their information processing approaches and the way they represent information, thus affecting their performance. To create better models of Web searching we need to understand more about user’s cognitive style and their Web search behaviour, and the relationship between them. More rigorous research is needed in using more complex and meaningful measures of relevance; across a range of different types of search tasks and different populations of Internet users. The project further explores the relationships between the users’ cognitive style and their Web searching. The project will develop a model depicting the relationships between a user’s cognitive style and their Web searching. The related literature, aims and objectives and research design are discussed.

Micro-family-owned businesses in hostile environment : future engine for growth?

Using panel data from the four waves of the Indonesia Family Life Survey in 1993, 1997, 2000 and 2007 we investigate the prerequisite for and contribution of micro-family-businesses to economic development. We find that family-owned firms are on average fairly profitable compared with the industrial sector profit standard. Failure rates between 1997 and 2000 are very low (about 10%), while the industrial sector experimented a massive shakeout of about 33% in the wake of the 1997 crisis (Ter Wengel & Rodriguez, 2006), with an increase in the number of family-businesses between the two years of observation. This paper contributes to the economics of entrepreneurship studies by continuing the discussion of entrepreneurship in hostile business environments (Baumol, 1990; Sobel, 2008).

The international search for ethics norms : which consumer behaviors do consumers consider (un)acceptable?

Purpose: Businesses cannot rely on their customers to always do the right thing. To help researchers and service providers better understand the dark (and light) side of customer behavior, this study aims to aggregate and investigate perceptions of consumer ethics from young consumers on five continents. The study seeks to present a profile of consumer behavioral norms, how ethical inclinations have evolved over time, and country differences. ---------- Design/methodology/approach: Data were collected from ten countries across five continents between 1997 and 2007. A self-administered questionnaire containing 14 consumer scenarios asked respondents to rate acceptability of questionable consumer actions. ---------- Findings: Overall, consumers found four of the 14 questionable consumer actions acceptable. Illegal activities were mostly viewed as unethical, while some legal actions that were against company policy were viewed less harshly. Differences across continents emerged, with Europeans being the least critical, while Asians and Africans shared duties as most critical of consumer actions. Over time, consumers have become less tolerant of questionable behaviors. ---------- Practical implications: Service providers should use the findings of this study to better understand the service customer. Knowing what customers in general believe is ethical or unethical can help service designers focus on the aspects of the technology or design most vulnerable to customer deviance. ---------- Multinationals already know they must adapt their business practices to the market in which they are operating, but they must also adapt their expectations as to the behavior of the corresponding consumer base. Originality/value: This investigation into consumer ethics helps businesses understand what their customer base believes is the right thing in their role as customer. This is a large-scale study of consumer ethics including 3,739 respondents on five continents offering an evolving view of the ethical inclinations of young consumers.

Improving the performance of model-order selection criteria by partial-model selection search

The traditional searching method for model-order selection in linear regression is a nested full-parameters-set searching procedure over the desired orders, which we call full-model order selection. On the other hand, a method for model-selection searches for the best sub-model within each order. In this paper, we propose using the model-selection searching method for model-order selection, which we call partial-model order selection. We show by simulations that the proposed searching method gives better accuracies than the traditional one, especially for low signal-to-noise ratios over a wide range of model-order selection criteria (both information theoretic based and bootstrap-based). Also, we show that for some models the performance of the bootstrap-based criterion improves significantly by using the proposed partial-model selection searching method. Index Terms— Model order estimation, model selection, information theoretic criteria, bootstrap 1. INTRODUCTION Several model-order selection criteria can be applied to find the optimal order. Some of the more commonly used information theoretic-based procedures include Akaike’s information criterion (AIC) [1], corrected Akaike (AICc) [2], minimum description length (MDL) [3], normalized maximum likelihood (NML) [4], Hannan-Quinn criterion (HQC) [5], conditional model-order estimation (CME) [6], and the efficient detection criterion (EDC) [7]. From a practical point of view, it is difficult to decide which model order selection criterion to use. Many of them perform reasonably well when the signal-to-noise ratio (SNR) is high. The discrepancies in their performance, however, become more evident when the SNR is low. In those situations, the performance of the given technique is not only determined by the model structure (say a polynomial trend versus a Fourier series) but, more importantly, by the relative values of the parameters within the model. This makes the comparison between the model-order selection algorithms difficult as within the same model with a given order one could find an example for which one of the methods performs favourably well or fails [6, 8]. Our aim is to improve the performance of the model order selection criteria in cases where the SNR is low by considering a model-selection searching procedure that takes into account not only the full-model order search but also a partial model order search within the given model order. Understandably, the improvement in the performance of the model order estimation is at the expense of additional computational complexity.

Review of Engine

Review of Engine by NORPA in Lowdown Spetember 2010

Using text-spotting to query the world

The world we live in is well labeled for the benefit of humans but to date robots have made little use of this resource. In this paper we describe a system that allows robots to read and interpret visible text and use it to understand the content of the scene. We use a generative probabilistic model that explains spotted text in terms of arbitrary search terms. This allows the robot to understand the underlying function of the scene it is looking at, such as whether it is a bank or a restaurant. We describe the text spotting engine at the heart of our system that is able to detect and parse wild text in images, and the generative model, and present results from images obtained with a robot in a busy city setting.

Diesel engine condition monitoring and simulated diesel knock

This paper discusses diesel engine condition monitoring (CM) using acoustic emissions (AE)as well as some of the commonly encountered diesel engine problems. Also discussed are some of the underlying combustion related faults and the methods used in past studies to simulate diesel engine faults. The initial test involved an experimental simulation of two common combustion related diesel engine faults, namely diesel knock and misfire. These simulated faults represent the first step towards a comprehensive investigation and analysis into the characteristics of acoustic emission signals arising from combustion related diesel engine faults. Data corresponding to different engine running conditions was captured using in-cylinder pressure, vibration and acoustic emission transducers along with both crank angle encoder and top-dead centre (TDC) signals. Using these signals, it was possible to characterise the effect of different combustion conditions and hence, various diesel engine in-cylinder pressure profiles.

HyperCard test engine using Rasch Analysis

This paper will focus on the development of an interactive test engine using Rasch analysis of item responses for question selection and reporting of results. The Rasch analysis is used to determine student ability and question difficulty. This model is widely used in the preparation of paper-based tests and has been the subject of particular use and development at the Australian Council for Education Research (ACER). This paper presents an overview of an interactive implementation of the Rasch analysis model in HyperCard, where student ability estimates are generated 'on the fly' and question difficulty values updated from time to time. The student ability estimates are used to determine question selection and are the basis of scoring and reporting schemes.

Critical gap estimation by numerical and statistical highest likelihood search

Many traffic situations require drivers to cross or merge into a stream having higher priority. Gap acceptance theory enables us to model such processes to analyse traffic operation. This discussion demonstrated that numerical search fine tuned by statistical analysis can be used to determine the most likely critical gap for a sample of drivers, based on their largest rejected gap and accepted gap. This method shares some common features with the Maximum Likelihood Estimation technique (Troutbeck 1992) but lends itself well to contemporary analysis tools such as spreadsheet and is particularly analytically transparent. This method is considered not to bias estimation of critical gap due to very small rejected gaps or very large rejected gaps. However, it requires a sufficiently large sample that there is reasonable representation of largest rejected gap/accepted gap pairs within a fairly narrow highest likelihood search band.