Predicting mothers’ decisions to introduce complementary feeding at 6 months : an investigation using an extended theory of planned behaviour

In Australia and other developed countries there is poor adherence to guidelines recommending the introduction of complementary feeding to infants at 6 months of age. We aimed to investigate, via adopting a theory of planned behaviour framework and incorporating additional normative and demographic influences, mothers’ complementary feeding intentions and behaviour. Participants were 375 primiparas who completed an initial questionnaire (infant age 13±3weeks) that assessed the theory of planned behaviour constructs of attitude, subjective norm, and perceived behavioural control, as well as group norm and additional maternal and infant variables of mothers’ age, education level, weight status perception, current maternal feeding practices, and infant birth weight. Approximately, 3 months after completion of the main questionnaire, mothers completed a follow-up questionnaire that assessed the age in months at which the infant was first introduced to solids. The theory of planned behaviour variables of attitude and subjective norm, along with group norm, predicted intentions, with intention, mothers’ age (older more likely), and weight status perception (overweight less likely) predicting behaviour. Overall, the results highlight the importance of attitudes, normative influences, and individual characteristics in complementary feeding decision-making which should be considered when designing interventions aimed at improving adherence to current maternal feeding guidelines.

Can the contra-lateral limb be used as a control with respect to analyses of bone remodelling?

Bone loss may result from remodelling initiated by implant stress protection. Quantifying remodelling requires bone density distributions which can be obtained from computed tomography scans. Pre-operative scans of large animals however are rarely possible. This study aimed to determine if the contra-lateral bone is a suitable control for the purpose of quantifying bone remodelling. CT scans of 8 pairs of ovine tibia were used to determine the likeness of left and right bones. The deviation between the outer surfaces of the bone pairs was used to quantify geometric similarity. The density differences were determined by dividing the bones into discrete volumes along the shaft of the tibia. Density differences were also determined for fractured and contra-lateral bone pairs to determine the magnitude of implant related remodelling. Left and right ovine tibiae were found to have a high degree of similarity with differences of less than 1.0 mm in the outer surface deviation and density difference of less than 5% in over 90% of the shaft region. The density differences (10–40%) as a result of implant related bone remodelling were greater than left-right differences. Therefore, for the purpose of quantifying bone remodelling in sheep, the contra-lateral tibia may be considered an alternative to a pre-operative control.

Developing trust networks based on user tagging information for recommendation making

Recommender systems are one of the recent inventions to deal with ever growing information overload. Collaborative filtering seems to be the most popular technique in recommender systems. With sufficient background information of item ratings, its performance is promising enough. But research shows that it performs very poor in a cold start situation where previous rating data is sparse. As an alternative, trust can be used for neighbor formation to generate automated recommendation. User assigned explicit trust rating such as how much they trust each other is used for this purpose. However, reliable explicit trust data is not always available. In this paper we propose a new method of developing trust networks based on user’s interest similarity in the absence of explicit trust data. To identify the interest similarity, we have used user’s personalized tagging information. This trust network can be used to find the neighbors to make automated recommendations. Our experiment result shows that the proposed trust based method outperforms the traditional collaborative filtering approach which uses users rating data. Its performance improves even further when we utilize trust propagation techniques to broaden the range of neighborhood.

SimTrust : a new method of trust network generation

Trust can be used for neighbor formation to generate automated recommendations. User assigned explicit rating data can be used for this purpose. However, the explicit rating data is not always available. In this paper we present a new method of generating trust network based on user’s interest similarity. To identify the interest similarity, we use user’s personalized tag information. This trust network can be used to find the neighbors to make automated recommendation. Our experiment result shows that the precision of the proposed method outperforms the traditional collaborative filtering approach.

Managing Trust in Online Social Networks

In recent years, there is a dramatic growth in number and popularity of online social networks. There are many networks available with more than 100 million registered users such as Facebook, MySpace, QZone, Windows Live Spaces etc. People may connect, discover and share by using these online social networks. The exponential growth of online communities in the area of social networks attracts the attention of the researchers about the importance of managing trust in online environment. Users of the online social networks may share their experiences and opinions within the networks about an item which may be a product or service. The user faces the problem of evaluating trust in a service or service provider before making a choice. Recommendations may be received through a chain of friends network, so the problem for the user is to be able to evaluate various types of trust opinions and recommendations. This opinion or recommendation has a great influence to choose to use or enjoy the item by the other user of the community. Collaborative filtering system is the most popular method in recommender system. The task in collaborative filtering is to predict the utility of items to a particular user based on a database of user rates from a sample or population of other users. Because of the different taste of different people, they rate differently according to their subjective taste. If two people rate a set of items similarly, they share similar tastes. In the recommender system, this information is used to recommend items that one participant likes, to other persons in the same cluster. But the collaborative filtering system performs poor when there is insufficient previous common rating available between users; commonly known as cost start problem. To overcome the cold start problem and with the dramatic growth of online social networks, trust based approach to recommendation has emerged. This approach assumes a trust network among users and makes recommendations based on the ratings of the users that are directly or indirectly trusted by the target user.

Trust and reputation management in web-based social network

know personally. They also communicate with other members of the network who are the friends of their friends and may be friends of their friend’s network. They share their experiences and opinions within the social network about an item which may be a product or service. The user faces the problem of evaluating trust in a service or service provider before making a choice. Opinions, reputations and ecommendations will influence users' choice and usage of online resources. Recommendations may be received through a chain of friends of friends, so the problem for the user is to be able to evaluate various types of trust recommendations and reputations. This opinion or ecommendation has a great influence to choose to use or enjoy the item by the other user of the community. Users share information on the level of trust they explicitly assign to other users. This trust can be used to determine while taking decision based on any recommendation. In case of the absence of direct connection of the recommender user, propagated trust could be useful.

Preclinical animal models for segmental bone defect research and tissue engineering

Currently, well-established clinical therapeutic approaches for bone reconstruction are restricted to the transplantation of autografts and allografts, and the implantation of metal devices or ceramic-based implants to assist bone regeneration. Bone grafts possess osteoconductive and osteoinductive properties, however they are limited in access and availability and associated with donor site morbidity, haemorrhage, risk of infection, insufficient transplant integration, graft devitalisation, and subsequent resorption resulting in decreased mechanical stability. As a result, recent research focuses on the development of alternative therapeutic concepts. Analysing the tissue engineering literature it can be concluded that bone regeneration has become a focus area in the field. Hence, a considerable number of research groups and commercial entities work on the development of tissue engineered constructs for bone regeneration. However, bench to bedside translations are still infrequent as the process towards approval by regulatory bodies is protracted and costly, requiring both comprehensive in vitro and in vivo studies. In translational orthopaedic research, the utilisation of large preclinical animal models is a conditio sine qua non. Consequently, to allow comparison between different studies and their outcomes, it is essential that animal models, fixation devices, surgical procedures and methods of taking measurements are well standardized to produce reliable data pools as a base for further research directions. The following chapter reviews animal models of the weight-bearing lower extremity utilized in the field which include representations of fracture-healing, segmental bone defects, and fracture non-unions.

Strategic technology management : case study development in innovative building products

National and international competition demands that Australian organisations become more competent at making the strategic technological decisions that impact their future in the international business economy. A new subject unit, Management of Technology is now offered in the popular Master of Project Management and Master of Business Administration programs at the Queensland University of Technology. This cross-disciplinary subject provides students with a theoretical foundation and practical tools to improve the efficiency and competitiveness of technically-oriented organisations. Applied case studies—shown to be the most appropriate mode of learning for mature-age students—form an integral component of the teaching program. In the first offerings of this subject during 1995 and 1996, American case studies were used. QUT has now supported the development of Australian case study packages for technology management through its Teaching and Learning Grants Scheme. The first case developed—Inland Oil Refiners’ Microstill Project—was completed in early 1996. A newly developed case—Automated Door Opening System for Wheelchair Access—is currently being completed. This case (comprising case study documentation and video presentation) tracks a cross-disciplinary product development driven by legislative and community pressures. It also reinforces the importance of personal relationships in the technology and business development that has taken this young Brisbane-based company from its embryonic beginnings on the Queensland Cultural Centre in 1994 to a national and export-focussed organisation in 1997. This paper reviews the need to develop Australian case material in Management of Technology, discusses the case study documentation and supporting video developed, and application of the case study approach in this teaching initiative in QUT’s Master of Project Management and Master of Business Administration programs.

A solid state Marx generator with a novel configuration

The new configuration proposed in this paper for Marx Generator (MG) aims to generate high voltage for pulsed power applications through reduced number of semiconductor components with a more efficient load supplying process. The main idea is to charge two groups of capacitors in parallel through an inductor and take advantage of resonant phenomenon in charging each capacitor up to a double input voltage level. In each resonant half a cycle, one of those capacitor groups are charged, and eventually the charged capacitors will be connected in series and the summation of the capacitor voltages can be appeared at the output of the topology. This topology can be considered as a modified Marx generator which works based on the resonant concept. Simulated models of this converter have been investigated in Matlab/SIMULINK platform and a prototype set up has been implemented in laboratory. The acquired results of either fully satisfy the anticipations in proper operation of the converter.

A new family of Marx generators based on commutation circuits

This paper presents a novel topology for the generation of high voltage pulses that uses both slow and fast solid-state power switches. This topology includes diode-capacitor units in parallel with commutation circuits connected to a positive buck-boost converter. This enables the generation of a range of high output voltages with a given number of capacitors. The advantages of this topology are the use of slow switches and a reduced number of diodes in comparison with conventional Marx generator. Simulations performed for single and repetitive pulse generation and experimental tests of a prototype hardware verify the proposed topology.

Textures of optical flow for real-time anomaly detection in crowds

Automated visual surveillance of crowds is a rapidly growing area of research. In this paper we focus on motion representation for the purpose of abnormality detection in crowded scenes. We propose a novel visual representation called textures of optical flow. The proposed representation measures the uniformity of a flow field in order to detect anomalous objects such as bicycles, vehicles and skateboarders; and can be combined with spatial information to detect other forms of abnormality. We demonstrate that the proposed approach outperforms state-of-the-art anomaly detection algorithms on a large, publicly-available dataset.

A hierarchical security assessment model for object-oriented programs

We present a hierarchical model for assessing an object-oriented program's security. Security is quantified using structural properties of the program code to identify the ways in which `classified' data values may be transferred between objects. The model begins with a set of low-level security metrics based on traditional design characteristics of object-oriented classes, such as data encapsulation, cohesion and coupling. These metrics are then used to characterise higher-level properties concerning the overall readability and writability of classified data throughout the program. In turn, these metrics are then mapped to well-known security design principles such as `assigning the least privilege' and `reducing the size of the attack surface'. Finally, the entire program's security is summarised as a single security index value. These metrics allow different versions of the same program, or different programs intended to perform the same task, to be compared for their relative security at a number of different abstraction levels. The model is validated via an experiment involving five open source Java programs, using a static analysis tool we have developed to automatically extract the security metrics from compiled Java bytecode.

Regulating for Sustainability : Property Issues

All Australian governments recognize the need to ensure that land and natural resources are used sustainably. In this context, ‘resources’ includes natural resources found on land such as trees and other vegetation, fauna, soil and minerals, and cultural resources found on land such as archaeological sites and artefacts. Regulators use a wide range of techniques to promote sustainability. To achieve their objectives, they may, for example, create economic incentives through bounties, grants and subsidies, encourage the development of self-regulatory codes, or enter into agreements with landowners specifying how the land is to be managed. A common way of regulating is by making administrative orders, determinations or decisions under powers given to regulators by Acts of Parliament (statutes) or by regulations (delegated legislation). Generally the legislation provides for specified rights or duties, and authorises a regulator to make an order or decision to apply the legislative provisions to particular land or cases. For example, legislation might empower a regulator to make an order that requires the owner of a contaminated site to remediate it. When the regulator exercises the power by making an order in relation to particular land, the owner is placed under a statutory duty to remediate. When regulators exercise their statutory powers to manage the use of private land or natural or cultural resources on private land, property law issues can arise. The owner of land has a private property right that the law will enforce against anybody else who interferes with the enjoyment of the right, without legal authority to do so. The law dealing with the enforcement of private property rights forms part of private law. This report focuses on the relationship between the law of private property and the regulation of land and resources by legislation and by administrative decisions made under powers given by legislation (statutory powers).