What will affect software reuse: a causal model analysis

Software reuse is an important topic due to its potential benefits in increasing product quality and decreasing cost. Although more and more people are aware that not only technical issues, but also nontechnical issues are important to the success of software reuse, people are still not certain which factors will have direct effect on the success of reuse. In this paper, we applied a causal discovery algorithm to the software reuse survey data [2]. Ensemble strategy is incorporated to locate a probable causal model structure for software reuse, and find all those factors which have direct effect on the success of reuse. Our discovery results reinforced some conclusions of Morisio et al. and found some new conclusions which might significantly improve the odds of a reuse project succeeding.

Store names information signalling : a credibility perspective

This study is about store names as brand signals. Using the framework of Erdem and Swait (1998), hypotheses are developed regarding the effects of store names on consumers' expected product utility. It is relevant to study store names as brand signals because store names can act as additional signals in the consumer purchase decision process. The study focuses in particular on the effects of store name credibility on perceived risk, information costs and perceived product quality. The hypotheses will be tested on data that are currently being collected in a survey among two hundred students.

Depth estimation using multi-wavelet analysis based stereo vision approach

The problem of dimensional defects in aluminum die- casting is widespread throughout the foundry industry and their detection is of paramount importance in maintaining product quality. Due to the unpredictable factory environment and metallic, with highly reflective, nature of aluminum die-castings, it is extremely hard to estimate true dimensionality of the die-casting, autonomously. In this work, we propose a novel robust 3D reconstruction algorithm capable of reconstructing dimensionally accurate 3D depth models of the aluminum die-castings. The developed system is very simple and cost effective as it consists of only a stereo cameras pair and a simple fluorescent light. The developed system is capable of estimating surface depths within the tolerance of 1.5 mm. Moreover, the system is invariant to illuminative variations and orientation of the objects in the input image space, which makes the developed system highly robust. Due to its hardware simplicity and robustness, it can be implemented in different factory environments without a significant change in the setup.

Integrated model for thermo-mechanical controlled process in rod (or bar) rolling

This study presents an integrated model for computing the thermo-mechanical parameters (cross-sectional shape of workpiece, the pass-by-pass strain and strain rate and the temperature variation during rolling and cooling between inter-stands) and metallurgical parameters (recrystallisation behaviour and austenite grain size—AGS), to assess the potential for developing “Thermo-Mechanical Controlled Process” technology in rod (or bar) rolling, which has been a well-known technical terminology in strip (or plate) rolling since 1970s.

The advantage of this model is that metallurgical and mechanical parameters are obtained simultaneously in a short computation time compared with other models. The model has been applied to a rod mill to predict the exit cross-sectional shape, area and AGS per pass by incorporating the equations for AGS evolution being used in strip rolling. At the finishing train of rod mills, the strain rates reach as high as 1000–3000 s−1 and the inter-pass times are around 10–60 ms.

The results show that the proposed model is an efficient tool for evaluating the effects of process-related parameters on product quality and dimensional tolerance of the products in rod (or bar) rolling. The results of the simulation demonstrated that the equation for AGS evolution being used in strip rolling might have limitations when applied directly to rod rolling at a high strain rate.

Consumer loyalty versus propensity to switch between providers in mature IT markets (the case of mobile phone market)

The example of the youth mobile phone market is used for pilot empirical testing of a model of consumers’ decision making, based on common features of consumer behaviour in mature markets of information and high technology products. Firstly, we discuss the key properties of mature high technology markets which affect market behaviour and strategies. These properties include: established customer and provider bases; the elements of both oligopolistic and monopolistic competition; very short product life cycle; considerable product differentiation; and using product quality, versioning and price discrimination as planning and marketing tools. Secondly, a model of consumers’ decision making in such markets is suggested on the assumption that a choice is to be made between the following options: to continue using the existing version of the product, to upgrade it with the current provider or to switch to another provider. Product price, quality characteristics, switching costs and network effects are demonstrated to be the variables affecting consumers’ decisions and therefore, these variables should be considered by competing providers when they choose production and marketing strategies. In conclusion, the results of the empirical study are discussed in the context of their possible application to other information and high technology markets.

Biometric, nutritional and organoleptic changes in intensively farmed Murray Cod (Maccullochella peelii peelii) purged for different time periods

A period of purging before harvesting is common practice in intensive aquaculture to eliminate any possible off flavours from the fish. The present study was conducted to evaluate the biometrical, nutritional and sensory changes in intensively farmed Murray cod (Maccullochella peelii peelii) after 0, 2 and 4 weeks of purging. After the main biometric parameters were recorded, fish were analysed for proximate, fatty acid composition and flavour volatile compounds. A consumer preference test (triangle test) was also conducted to identify sensorial differences that may affect the consumer acceptability of the product.

Fish purged for 2 and 4 weeks had a significant weight loss of 4.1% and 9.1%, respectively, compared to unpurged fish, whilst perivisceral fat content did not change. The concentration of saturated (SFA), monounsaturated (MUFA) and highly unsaturated (HUFA) fatty acids were not significantly affected by purging time, while polyunsaturated fatty acids (PUFA), n − 3 and n − 3 HUFA were significantly higher (P < 0.05) in purged fish compared to unpurged fish. Consumers were able to detect differences between the purged and unpurged fish (P < 0.05) preferring the taste of the purged fish. However, consumers were unable to distinguish between fish purged for 2 and 4 weeks.

This study showed that a 2 weeks purging period was necessary and sufficient to ameliorate the final organoleptic quality of farmed Murray cod. With such a strategy the nutritional qualities of edible flesh are improved while the unavoidable body weight loss is limited.

Biometric, nutritional and sensory changes in intensively farmed Murray cod (Maccullochella peelii peelii, Mitchell) following different purging times

A period of purging before harvesting is common practice in intensive aquaculture to eliminate any possible off flavours from the fish. The present study was conducted to evaluate the biometrical, nutritional and sensory changes in intensively farmed Murray cod (Maccullochella peelii peelii) after 0, 2 and 4 weeks of purging. After the main biometric parameters were recorded, fish were analysed for proximate, fatty acid composition and flavour volatile compounds. A consumer preference test (triangle test) was also conducted to identify sensorial differences that may affect the consumer acceptability of the product.

Fish purged for 2 and 4 weeks had a significant weight loss of 4.1% and 9.1%, respectively, compared to unpurged fish, whilst perivisceral fat content did not change. The concentration of saturated (SFA), monounsaturated (MUFA) and highly unsaturated (HUFA) fatty acids were not significantly affected by purging time, while polyunsaturated fatty acids (PUFA), n − 3 and n − 3 HUFA were significantly higher (P < 0.05) in purged fish compared to unpurged fish. Consumers were able to detect differences between the purged and unpurged fish (P < 0.05) preferring the taste of the purged fish. However, consumers were unable to distinguish between fish purged for 2 and 4 weeks.

This study showed that a 2 weeks purging period was necessary and sufficient to ameliorate the final organoleptic quality of farmed Murray cod. With such a strategy the nutritional qualities of edible flesh are improved while the unavoidable body weight loss is limited.

Competition in mature software markets

A theoretical framework is built for capturing properties of competition in mature monopolistic digital product markets. Based on an empirical study of the market of accounting software for small and medium enterprises, a consumer choice model is suggested, where a rational consumer is already using a particular version of a software package and is considering to chose from the following three options: either to continue using it, or to upgrade to a newer version of the product, or to switch to a competitive product. Consumer decision is justified by software quality, and network effects, under the price and switching costs constrains. A modified consumer demand function is used for the model, and theoretical conditions are analysed for choosing from one of the three above-mentioned options. The results are applicable to a wide range of digital products.

Depth estimation of metallic objects using multiwavelets scale-space representation

The problem of dimensional defects in aluminum die-castings is widespread throughout the foundry industry and their detection is of paramount importance in maintaining product quality. Due to the unpredictable factory environment and metallic with highly reflective nature, it is extremely hard to estimate true dimensionality of these metallic parts, autonomously. Some existing vision systems are capable of estimating depth to high accuracy, however are very much hardware dependent, involving the use of light and laser pattern projectors, integrated into vision systems or laser scanners. However, due to the reflective nature of these metallic parts and variable factory environments, the aforementioned vision systems tend to exhibit unpromising performance. Moreover, hardware dependency makes these systems cumbersome and costly. In this work, we propose a novel robust 3D reconstruction algorithm capable of reconstructing dimensionally accurate 3D depth models of the aluminum die-castings. The developed system is very simple and cost effective as it consists of only a pair of stereo cameras and a defused fluorescent light. The proposed vision system is capable of estimating surface depths within the accuracy of 0.5mm. In addition, the system is invariant to illuminative variations as well as orientation and location of the objects on the input image space, making the developed system highly robust. Due to its hardware simplicity and robustness, it can be implemented in different factory environments without a significant change in the setup. The proposed system is a major part of quality inspection system for the automotive manufacturing industry.

Depth estimation using multiwavelet analysis based stereo vision approach

The problem of dimensional defects in aluminum die-casting is widespread throughout the foundry industry and their detection is of paramount importance in maintaining product quality. Due to the unpredictable factory environment and metallic, with highly reflective, nature of aluminum die-castings, it is extremely hard to estimate true dimensionality of the die-casting, autonomously. In this work, we propose a novel robust 3D reconstruction algorithm capable of reconstructing dimensionally accurate 3D depth models of the aluminum die-castings. The developed system is very simple and cost effective as it consists of only a stereo camera pair and a simple fluorescent light. The developed system is capable of estimating surface depths within the tolerance of 1.5 mm. Moreover, the system is invariant to illuminative variations and orientation of the objects in the input image space, which makes the developed system highly robust. Due to its hardware simplicity and robustness, it can be implemented in different factory environments without a significant change in the setup.

Competition in the mature markets of professional versus final consumer information products

Factors are explored of decision making in regard to buying and/or upgrading information products. Mature information product markets are considered. Comparing two cases - professional and final consumer information products - the decision making process is considered on the choice of product variant. We distinguish three groups of users according to their ultimate decisions to either not to upgrade the existing system, or to upgrade it with the existing provider, or to switch to another provider. Consumer decision is based on multiple characteristics of information product quality, network effects, price and switching costs, whereas producers have to compete not only with their competitors, but also with the previous versions of the own products. Based on the considered cases, differences in consumer priorities are discussed in the markets of professional versus final consumer information products.

Impact of electronic data interchange in the Australian automotive industry

Information technology continues to play an increasingly significant role in the development of firms competing in the vast array of markets from those classified as global markets, such as the automotive industry, to the smaller nationally-based markets such as retailing. An objective of electronic commerce is to assist organisations to remain competitive and gain entry to markets which were previously unattainable. This study focuses on the organisational impact of one form of electronic commerce (electronic data interchange) on the component sector of the Australian automotive industry and examines the extent to which trading partner relationships have been affected. The research investigates the extent to which the integration of electronic data interchange (EDI) with an organisation’s internal application system may facilitate specific net benefits. The automotive industry became the first Australian industry to cooperatively adopt EDI. Research to date has not adequately examined the organisational impact of the nature and extent of net benefits gained from EDI adoption. To achieve the objective of assessing EDI net benefits, a conceptual model was developed. The model proposed that the level of EDI net benefits expected is influenced by the size of the organisation and the concentration of trade achieved within the industry via intervening links through (a) the level of senior management commitment and (b) the extent of system integration. Nine empirically testable research propositions are derived from the model, each testing the relationship between model constructs. Data was collected from 114 component suppliers to Ford Australia in 1992 and 1994 using a repeated cross-sectional longitudinal design. Structural equation modelling using partial least squares was adopted in the analysis of the data. A pure longitudinal model together with 12 case studies of selected component manufacturers supplemented the research design. The results of the research showed that the proposed conceptual model is a good description of the data. In particular, net benefits obtained from EDI adoption are directly determined by the size of the organisation, and the extent to which firms integrate EDI into their internal application systems. The level of net benefits is only indirectly influenced by the level of senior management commitment to the EDI project through (a) management commitment’s direct effect on integration, and (b) the direct effect the volume of trade a supplier achieves with the automotive industry on senior management commitment and system integration. The major benefits organisations experienced from EDI were enhanced productivity, clerical staff savings, improved data accuracy, enhanced customer service and reduced administration costs. The research showed that few suppliers gained inventory savings from EDI, a frequently claimed benefit from EDI adoption. Evidence of small improvements in product quality emerged from the results. In summary, this research attempts to make two primary contributions to knowledge, first in providing a method by which net benefits from electronic commerce can be measured within an industry adopting electronic trading, and second, by providing organisations with the knowledge of the specific net benefits organisations could expect from EDI adoption, together with the four major factors affecting these benefits. The research concludes with possible directions for future research, in particular an assessment of the impact of incorporating financial EDI into electronic trading.

A study on within-fibre diameter variation of wool

This work established and experimentally validated several models for accurately predicting wool fibre and yarn properties. The results will be useful in fibre selection, and will help predict fibre processing performance and end-product quality.

Modeling and control of flatness in cold rolling mill using fuzzy petri nets

Today, having a good flatness control in steel industry is essential to ensure an overall product quality, productivity and successful processing. Flatness error, given as difference between measured strip flatness and target curve, can be minimized by modifying roll gap with various control functions. In most practical systems, knowing the definition of the model in order to have an acceptable control is essential. In this paper, a fuzzy Petri net method for modeling and control of flatness in cold rolling mill is developed. The method combines the concepts of Petri net and fuzzy control theories. It focuses on the fuzzy decision making problems of the fuzzy rule tree structures. The method is able to detect and recover possible errors that can occur in the fuzzy rule of the knowledge-based system. The method is implemented and simulated. The results show that its error is less than that of a PI conventional controller.

Predicting amount of saleable products using neural network metamodels of casthouses

This study aims at developing abstract metamodels for approximating highly nonlinear relationships within a metal casting plant. Metal casting product quality nonlinearly depends on many controllable and uncontrollable factors. For improving the productivity of the system, it is vital for operation planners to predict in advance the amount of high quality products. Neural networks metamodels are developed and applied in this study for predicting the amount of saleable products. Training of metamodels is done using the Levenberg-Marquardt and Bayesian learning methods. Statistical measures are calculated for the developed metamodels over a grid of neural network structures. Demonstrated results indicate that Bayesian-based neural network metamodels outperform the Levenberg-Marquardt-based metamodels in terms of both prediction accuracy and robustness to the metamodel complexity. In contrast, the latter metamodels are computationally less expensive and generate the results more quickly.