Juveniles’ contact with the criminal justice system in Australia

This report presents the first collection of data on juveniles’ contact with the criminal justice system as both alleged/convicted offenders and complainants/victims in New South Wales, the Australian Capital Territory, Victoria, Queensland, Western Australia, South Australia and the Northern Territory. Its primary objectives are to outline data from each of these jurisdictions on juveniles’ contact with the policing, courts and correctional systems and to determine what we do and do not know about juveniles’ contact with the criminal justice system.

The correlation between electric field emission phenomenon and Schottky contact reverse bias characteristics in nanostructured systems

Two different morphologies of nanotextured molybdenum oxide were deposited by thermal evaporation. By measuring their field emission (FE) properties, an enhancement factor was extracted. Subsequently, these films were coated with a thin layer of Pt to form Schottky contacts. The current-voltage (I-V) characteristics showed low magnitude reverse breakdown voltages, which we attributed to the localized electric field enhancement. An enhancement factor was obtained from the I-V curves. We will show that the enhancement factor extracted from the I-V curves is in good agreement with the enhancement factor extracted from the FE measurements.

Integrating collaborative filtering and matching-based search for product recommendation

Currently, recommender systems (RS) have been widely applied in many commercial e-commerce sites to help users deal with the information overload problem. Recommender systems provide personalized recommendations to users and thus help them in making good decisions about which product to buy from the vast number of product choices available to them. Many of the current recommender systems are developed for simple and frequently purchased products like books and videos, by using collaborative-filtering and content-based recommender system approaches. These approaches are not suitable for recommending luxurious and infrequently purchased products as they rely on a large amount of ratings data that is not usually available for such products. This research aims to explore novel approaches for recommending infrequently purchased products by exploiting user generated content such as user reviews and product click streams data. From reviews on products given by the previous users, association rules between product attributes are extracted using an association rule mining technique. Furthermore, from product click streams data, user profiles are generated using the proposed user profiling approach. Two recommendation approaches are proposed based on the knowledge extracted from these resources. The first approach is developed by formulating a new query from the initial query given by the target user, by expanding the query with the suitable association rules. In the second approach, a collaborative-filtering recommender system and search-based approaches are integrated within a hybrid system. In this hybrid system, user profiles are used to find the target user’s neighbour and the subsequent products viewed by them are then used to search for other relevant products. Experiments have been conducted on a real world dataset collected from one of the online car sale companies in Australia to evaluate the effectiveness of the proposed recommendation approaches. The experiment results show that user profiles generated from user click stream data and association rules generated from user reviews can improve recommendation accuracy. In addition, the experiment results also prove that the proposed query expansion and the hybrid collaborative filtering and search-based approaches perform better than the baseline approaches. Integrating the collaborative-filtering and search-based approaches has been challenging as this strategy has not been widely explored so far especially for recommending infrequently purchased products. Therefore, this research will provide a theoretical contribution to the recommender system field as a new technique of combining collaborative-filtering and search-based approaches will be developed. This research also contributes to a development of a new query expansion technique for infrequently purchased products recommendation. This research will also provide a practical contribution to the development of a prototype system for recommending cars.

Reverse biased Schottky contact hydrogen sensors based on Pt∕nanostructured ZnO∕SiC

Pt/nanostructured ZnO/SiC Schottky contact devices were fabricated and characterized for hydrogen gas sensing. These devices were investigated in reverse bias due to greater sensitivity, which attributes to the application of nanostructured ZnO. The current-voltage (I-V) characteristics of these devices were measured in different hydrogen concentrations. Effective change in the barrier height for 1% hydrogen was calculated as 27.06 meV at 620°C. The dynamic response of the sensors was also investigated and a voltage shift of 325 mV was recorded at 620°C during exposure to 1% hydrogen in synthetic air.

Developing a method for assessing product inclusivity

In order to develop more inclusive products and services, designers need a means of assessing the inclusivity of existing products and new concepts. Following previous research on the development of scales for inclusive design at University of Cambridge, Engineering Design Centre (EDC) [1], this paper presents the latest version of the exclusion audit method. For a specific product interaction, this estimates the proportion of the Great British population who would be excluded from using a product or service, due to the demands the product places on key user capabilities. A critical part of the method involves rating of the level of demand placed by a task on a range of key user capabilities, so the procedure to perform this assessment was operationalised and then its reliability was tested with 31 participants. There was no evidence that participants rated the same demands consistently. The qualitative results from the experiment suggest that the consistency of participants’ demand level ratings could be significantly improved if the audit materials and their instructions better guided the participant through the judgement process.

Towards a capabilities database to inform inclusive design : Experimental investigation of effective survey-based predictors of human-product interaction

A key issue in the field of inclusive design is the ability to provide designers with an understanding of people's range of capabilities. Since it is not feasible to assess product interactions with a large sample, this paper assesses a range of proxy measures of design-relevant capabilities. It describes a study that was conducted to identify which measures provide the best prediction of people's abilities to use a range of products. A detailed investigation with 100 respondents aged 50-80 years was undertaken to examine how they manage typical household products. Predictor variables included self-report and performance measures across a variety of capabilities (vision, hearing, dexterity and cognitive function), component activities used in product interactions (e.g. using a remote control, touch screen) and psychological characteristics (e.g. self-efficacy, confidence with using electronic devices). Results showed, as expected, a higher prevalence of visual, hearing, dexterity, cognitive and product interaction difficulties in the 65-80 age group. Regression analyses showed that, in addition to age, performance measures of vision (acuity, contrast sensitivity) and hearing (hearing threshold) and self-report and performance measures of component activities are strong predictors of successful product interactions. These findings will guide the choice of measures to be used in a subsequent national survey of design-relevant capabilities, which will lead to the creation of a capability database. This will be converted into a tool for designers to understand the implications of their design decisions, so that they can design products in a more inclusive way.

Non-contact ACL injuries : association with clegg soil impact test values for sports fields, soil moisture and prevailing weather

Introduction: There is a recognised relationship between dry weather conditions and increased risk of anterior cruciate ligament (ACL) injury. Previous studies have identified 28 day evaporation as an important weather-based predictor of non-contact ACL injuries in professional Australian Football League matches. The mechanism of non-contact injury to the ACL is believed to increased traction and impact forces between footwear and playing surface. Ground hardness and the amount and quality of grass are factors that would most likely influence this and are inturn, related to the soil moisture content and prevailing weather conditions. This paper explores the relationship between soil moisture content, preceding weather conditions and the Clegg Soil Impact Test (CSIT) which is an internationally recognised standard measure of ground hardness for sports fields. Methodology: The 2.25 kg Clegg Soil Impact Test and a pair of 12 cm soil moisture probes were used to measure ground hardness and percentage moisture content. Five football fields were surveyed at 13 prescribed sites just before seven football matches from October 2008 to January 2009 (an FC Women’s WLeague team). Weather conditions recorded at the nearest weather station were obtained from the Bureau of Meteorology website and total rainfall less evaporation was calculated for 7 and 28 days prior to each match. All non-contact injuries occurring during match play and their location on the field were recorded. Results/conclusions: Ground hardness varied between CSIT 5 and 17 (x10G) (8 is considered a good value for sports fields). Variations within fields were typically greatest in the centre and goal areas. Soil moisture ranged from 3 to 40% with some fields requiring twice the moisture content of others to maintain similar CSIT values. There was a non-linear, negative relationship for ground hardness versus moisture content and a linear relationship with weather (R2, of 0.30 and 0.34, respectively). Three non-contact ACL injuries occurred during the season. Two of these were associated with hard and variable ground conditions.

Molecular dynamics study of ‘contact epitaxy’ in Ag clusters supported on a copper (001) surface

In this paper, the formation of heteroepitaxial interfacial layers was investigated by molecular dynamics simulation of soft silver particles landing on the (001) surface of single-crystal copper. In our simulations, the clusters Ag13, Ag55, Ag147 and Ag688 were chosen as projectiles. A small cluster will rearrange into an f.c.c. structure when it is supported on the substrate, due to the large value of its surface/volume ratio. Contact epitaxy appeared in large clusters. The characteristic structure of an epitaxial layer in large silver cluster shows the 〈111〉 direction to be the preferential orientation of heteroepitaxial layers on the surface because of the lattice mismatch between the cluster and the substrate. This was confirmed by studying soft landing events in other systems (Au/Cu and Al/Ni).

Connected learning in the library as a product of hacking, making, social diversity and messiness

Learning is most effective when intrinsically motivated through personal interest, and situated in a supportive socio-cultural context. This paper reports on findings from a study that explored implications for design of interactive learning environments through 18 months of ethnographic observations of people’s interactions at “Hack The Evening” (HTE). HTE is a meetup group initiated at the State Library of Queensland in Brisbane, Australia, and dedicated to provide visitors with opportunities for connected learning in relation to hacking, making and do-it-yourself technology. The results provide insights into factors that contributed to HTE as a social, interactive and participatory environment for learning – knowledge is created and co-created through uncoordinated interactions among participants that come from a diversity of backgrounds, skills and areas of expertise. The insights also reveal challenges and barriers that the HTE group faced in regards to connected learning. Four dimensions of design opportunities are presented to overcome those challenges and barriers towards improving connected learning in library buildings and other free-choice learning environments that seek to embody a more interactive and participatory culture among their users. The insights are relevant for librarians as well as designers, managers and decision makers of other interactive and free-choice learning environments.

International tax and the Australian wine industry: Is your client’s product destined to sail the seven seas?

The export market for Australian wine continues to grow at a rapid rate, with imported wines also playing a role in market share in sales in Australia. It is estimated that over 60 per cent of all Australian wine is exported, while 12 per cent of wine consumed in Australia has overseas origins. In addition to understanding the size and direction (import or export) of wines, the foreign locales also play an important role in any tax considerations. While the export market for Australian produced alcohol continues to grow, it is into the Asian market that the most significant inroads are occurring. Sales into China of bottled wine over $7.50 per litre recently overtook the volume sold our traditional partners of the United States and Canada. It is becoming easier for even small to medium sized businesses to export their services or products overseas. However, it is vital for those businesses to understand the tax rules applying to any international transactions. Specifically, one of the first tax regimes that importers and exporters need to understand once they decide to establish a presence overseas is transfer pricing. These are the rules that govern the cross-border prices of goods, services and other transactions entered into between related parties. This paper is Part 2 of the seminar presented on transfer pricing and international tax issues which are particularly relevant to the wine industry. The predominant focus of Part 2 is to discuss four key areas likely to affect international expansion. First, the use of the available transfer pricing methodologies for international related party transactions is discussed. Second, the affects that double tax agreements will have on taking a business offshore are considered. Third, the risks associated with aggressive tax planning through tax information exchange agreements is reviewed. Finally, the paper predicts future ‘trip-wires’ and areas to ‘watch out for’ for practitioners dealing with clients operating in the international arena.

Sampling stored-product insect pests : a comparison of four statistical sampling models for probability of pest detection

Background: Developing sampling strategies to target biological pests such as insects in stored grain is inherently difficult owing to species biology and behavioural characteristics. The design of robust sampling programmes should be based on an underlying statistical distribution that is sufficiently flexible to capture variations in the spatial distribution of the target species. Results: Comparisons are made of the accuracy of four probability-of-detection sampling models - the negative binomial model,1 the Poisson model,1 the double logarithmic model2 and the compound model3 - for detection of insects over a broad range of insect densities. Although the double log and negative binomial models performed well under specific conditions, it is shown that, of the four models examined, the compound model performed the best over a broad range of insect spatial distributions and densities. In particular, this model predicted well the number of samples required when insect density was high and clumped within experimental storages. Conclusions: This paper reinforces the need for effective sampling programs designed to detect insects over a broad range of spatial distributions. The compound model is robust over a broad range of insect densities and leads to substantial improvement in detection probabilities within highly variable systems such as grain storage.

Integrating collaborative filtering and matching-based search for product recommendations

Currently, recommender systems (RS) have been widely applied in many commercial e-commerce sites to help users deal with the information overload problem. Recommender systems provide personalized recommendations to users and, thus, help in making good decisions about which product to buy from the vast amount of product choices. Many of the current recommender systems are developed for simple and frequently purchased products like books and videos, by using collaborative-filtering and content-based approaches. These approaches are not directly applicable for recommending infrequently purchased products such as cars and houses as it is difficult to collect a large number of ratings data from users for such products. Many of the ecommerce sites for infrequently purchased products are still using basic search-based techniques whereby the products that match with the attributes given in the target user’s query are retrieved and recommended. However, search-based recommenders cannot provide personalized recommendations. For different users, the recommendations will be the same if they provide the same query regardless of any difference in their interest. In this article, a simple user profiling approach is proposed to generate user’s preferences to product attributes (i.e., user profiles) based on user product click stream data. The user profiles can be used to find similarminded users (i.e., neighbours) accurately. Two recommendation approaches are proposed, namely Round- Robin fusion algorithm (CFRRobin) and Collaborative Filtering-based Aggregated Query algorithm (CFAgQuery), to generate personalized recommendations based on the user profiles. Instead of using the target user’s query to search for products as normal search based systems do, the CFRRobin technique uses the attributes of the products in which the target user’s neighbours have shown interest as queries to retrieve relevant products, and then recommends to the target user a list of products by merging and ranking the returned products using the Round Robin method. The CFAgQuery technique uses the attributes of the products that the user’s neighbours have shown interest in to derive an aggregated query, which is then used to retrieve products to recommend to the target user. Experiments conducted on a real e-commerce dataset show that both the proposed techniques CFRRobin and CFAgQuery perform better than the standard Collaborative Filtering and the Basic Search approaches, which are widely applied by the current e-commerce applications.