Transitional experiences of international postgraduate students utilising a peer mentor programme

Background: Mentoring provides a range of benefits and one of them is social support. The number of students in transnational education has been increasing, and their transition into university is often fraught with difficulties. Universities can support transition through the use of a peer mentor programme (PMP).

Purpose: The purpose of the study is to investigate the transitional issues that international postgraduate students (IPSs) face in their transition to an Australian University. The study also investigated the role played by a mentoring programme, and how this assists students with their transition.

Sample: The sample included 31 IPSs, who had come from Asian European, Middle Eastern, African and South American countries, 15 being male, and 16 being female, with an average age of 24; most had been studying at the Australian University for more than 12 months.

Design and methods: The study utilised a qualitative research method to examine the experiences of IPSs undergoing transition from their home universities to an Australian university. Semi-structured interviews were conducted with students, who were asked about their transition experiences and the assistance of the mentor programme. Thematic analysis was then conducted to determine themes from the research.

Results: IPSs reported mixed experiences with their transition. Those with difficulties referred to loneliness, different studying practices, finding accommodation and making friends. IPSs reported that the PMP helped, as mentors provided the necessary social support, friendship, information and confidence to overcome those difficulties. Those students who did not have problems with their transition had reported that they had friends or family that assisted them with their transition. As a result, these students did not need the support of mentors to the same degree as those students having problems.

Conclusions: It is concluded that mentor programmes were important for transitioning IPSs who had difficulties. Therefore, this study identified a role for a PMP in universities where there are a high proportion of IPSs who are going through transitional problems.

Secure object tracking protocol for networked RFID systems

Networked systems have adapted Radio Frequency identification technology (RFID) to automate their business process. The Networked RFID Systems (NRS) has some unique characteristics which raise new privacy and security concerns for organizations and their NRS systems. The businesses are always having new realization of business needs using NRS. One of the most recent business realization of NRS implementation on large scale distributed systems (such as Internet of Things (IoT), supply chain) is to ensure visibility and traceability of the object throughout the chain. However, this requires assurance of security and privacy to ensure lawful business operation. In this paper, we are proposing a secure tracker protocol that will ensure not only visibility and traceability of the object but also genuineness of the object and its travel path on-site. The proposed protocol is using Physically Unclonable Function (PUF), Diffie-Hellman algorithm and simple cryptographic primitives to protect privacy of the partners, injection of fake objects, non-repudiation, and unclonability. The tag only performs a simple mathematical computation (such as combination, PUF and division) that makes the proposed protocol suitable to passive tags. To verify our security claims, we performed experiment on Security Protocol Description Language (SPDL) model of the proposed protocol using automated claim verification tool Scyther. Our experiment not only verified our claims but also helped us to eliminate possible attacks identified by Scyther.

Oxytocin enhances the appropriate use of human social cues by the domestic dog (Canis familiaris) in an object choice task

It has been postulated that the neuropeptide, oxytocin, is involved in human-dog bonding. This may explain why dogs, compared to wolves, are such good performers on object choice tasks, which test their ability to attend to, and use, human social cues in order to find hidden food treats. The objective of this study was to investigate the effect of intranasal oxytocin administration, which is known to increase social cognition in humans, on domestic dogs' ability to perform such a task. We hypothesised that dogs would perform better on the task after an intranasal treatment of oxytocin. Sixty-two (31 males and 31 females) pet dogs completed the experiment over two different testing sessions, 5-15 days apart. Intranasal oxytocin or a saline control was administered 45 min before each session. All dogs received both treatments in a pseudo-randomised, counterbalanced order. Data were collected as scores out of ten for each of the four blocks of trials in each session. Two blocks of trials were conducted using a momentary distal pointing cue and two using a gazing cue, given by the experimenter. Oxytocin enhanced performance using momentary distal pointing cues, and this enhanced level of performance was maintained over 5-15 days time in the absence of oxytocin. Oxytocin also decreased aversion to gazing cues, in that performance was below chance levels after saline administration but at chance levels after oxytocin administration.

First report of a phytogeographically mixed (transitional) Middle-Late Permian fossil wood assemblage from the Hami area, northwest China, and implications for Permian phytogeographical, paleogeographical and paleoclimatic evolution in central Asia

A diverse and well-preserved fossil wood assemblage is described, for the first time, from the Middle Permian Taerlang Formation and the Upper Permian Quanzijie Formation in the vicinity of the Tianshan Town, Hami City of northwestern China. On the basis of wood microstructure, the fossil woods are classified into three genera and five species, including one new genus: Prototianshanoxylon gen. nov. and two new species: Prototianshanoxylon erdaogouense sp. nov., Prototianshanoxylon hamiense sp. nov. The new genus is characterized by window-like cross-field pitting and mixed tracheid radial wall pitting that suggest a transitional type between araucarioid-type and protopinoid-type pittings.Phytogeographically, the fossil wood assemblage is characterized by an admixture of elements of both temperate Angaran (represented by wood specimens with moderately to well defined growth rings in their secondary xylem) and tropical-subtropical north subregion of the Cathaysian floras (with wood specimens lacking well-defined growth rings). Such a phytogeographically mixed fossil wood assemblage is interpreted to represent a transitional and complex climate condition between a cool temperate and tropical to subtropical zones, showing both seasonal variation and unstable climate conditions. Previously, similarly mixed floras have already been found to exist widely in northern China ranging in age from Early to Late Permian, but the mechanisms thought to be responsible for their formation were varied and remain controversial. In this study, the formation of these mixed Permian floras of North China is linked to the closure of the Tianshan-Hingan seaway coupled with the collision and amalgamation of Siberia with North China and the Tarim block, in a manner much like closing a pair of scissors with the closure of the seaway proceeding gradually and progressively from west to the east.

Performance analysis for object-oriented software: a systematic mapping

Performance is a crucial attribute for most software, making performance analysis an important software engineering task. The difficulty is that modern applications are challenging to analyse for performance. Many profiling techniques used in real-world software development struggle to provide useful results when applied to large-scale object-oriented applications. There is a substantial body of research into software performance generally but currently there exists no survey of this research that would help identify approaches useful for object-oriented software. To provide such a review we performed a systematic mapping study of empirical performance analysis approaches that are applicable to object-oriented software. Using keyword searches against leading software engineering research databases and manual searches of relevant venues we identified over 5,000 related articles published since January 2000. From these we systematically selected 253 applicable articles and categorised them according to ten facets that capture the intent, implementation and evaluation of the approaches. Our mapping study results allow us to highlight the main contributions of the existing literature and identify areas where there are interesting opportunities. We also find that, despite the research including approaches specifically aimed at object-oriented software, there are significant challenges in providing actionable feedback on the performance of large-scale object-oriented applications.

Subsuming methods: finding new optimisation opportunities in object-oriented software

The majority of existing application profiling techniques ag- gregate and report performance costs by method or call- ing context. Modern large-scale object-oriented applications consist of thousands of methods with complex calling pat- terns. Consequently, when profiled, their performance costs tend to be thinly distributed across many thousands of loca- tions with few easily identifiable optimisation opportunities. However experienced performance engineers know that there are repeated patterns of method calls in the execution of an application that are induced by the libraries, design patterns and coding idioms used in the software. Automati- cally identifying and aggregating costs over these patterns of method calls allows us to identify opportunities to improve performance based on optimising these patterns. We have developed an analysis technique that is able to identify the entry point methods, which we call subsuming methods, of such patterns. Our ofiine analysis runs over previously collected runtime performance data structured in a calling context tree, such as produced by a large number of existing commercial and open source profilers. We have evaluated our approach on the DaCapo bench- mark suite, showing that our analysis significantly reduces the size and complexity of the runtime performance data set, facilitating its comprehension and interpretation. We also demonstrate, with a collection of case studies, that our analysis identifies new optimisation opportunities that can lead to significant performance improvements (from 20% to over 50% improvement in our case studies).

Visual object clustering via mixed-norm regularization

Many vision problems deal with high-dimensional data, such as motion segmentation and face clustering. However, these high-dimensional data usually lie in a low-dimensional structure. Sparse representation is a powerful principle for solving a number of clustering problems with high-dimensional data. This principle is motivated from an ideal modeling of data points according to linear algebra theory. However, real data in computer vision are unlikely to follow the ideal model perfectly. In this paper, we exploit the mixed norm regularization for sparse subspace clustering. This regularization term is a convex combination of the l1norm, which promotes sparsity at the individual level and the block norm l2/1 which promotes group sparsity. Combining these powerful regularization terms will provide a more accurate modeling, subsequently leading to a better solution for the affinity matrix used in sparse subspace clustering. This could help us achieve better performance on motion segmentation and face clustering problems. This formulation also caters for different types of data corruptions. We derive a provably convergent algorithm based on the alternating direction method of multipliers (ADMM) framework, which is computationally efficient, to solve the formulation. We demonstrate that this formulation outperforms other state-of-arts on both motion segmentation and face clustering.

Understanding a transitional teacher education in globalized and neoliberal contexts

Many early career teachers commence their transition into the teaching profession in rural and remote schools. Separated from existing interpersonal/professional networks of support, early career teachers rely on new colleagues and school leaders in more complex ways than their peers teaching closer to home. Crucially, their emerging identities, resilience and motivations are therefore influenced and reinforced
through professional interactions. This paper explores the critical turning points and narratives of two early career rural teachers. The narratives were collected through reflect.goingok.com, a digital tool created by one of the authors; that enabled the teachers to engage in regular reflections about their transition from university to the classroom. In conclusion some of the implications of the co-narration of teacher identity, and how this informs a systemic approach that supports early career teachers in rural teaching practice is discussed.

Marine object detection using background modelling and blob analysis

Monitoring marine object is important for understanding the marine ecosystem and evaluating impacts on different environmental changes. One prerequisite of monitoring is to identify targets of interest. Traditionally, the target objects are recognized by trained scientists through towed nets and human observation, which cause much cost and risk to operators and creatures. In comparison, a noninvasive way via setting up a camera and seeking objects in images is more promising. In this paper, a novel technique of object detection in images is presented, which is applicable to generic objects. A robust background modelling algorithm is proposed to extract foregrounds and then blob features are introduced to classify foregrounds. Particular marine objects, box jellyfish and sea snake, are successfully detected in our work. Experiments conducted on image datasets collected by the Australian Institute of Marine Science (AIMS) demonstrate the effectiveness of the proposed technique.

The status and function of Inanimate 'object-actors' in cyborg theatre

 This practice-led research investigates the relationships between human and technological actors in theatre with specific reference to theatrical presence.The research proposes to advance knowledge in the fields of directing and theatre making by putting forward new strategies for directing actors who perform with computer-based technologies.

Secure object tracking protocol for the internet of things

In this paper, we propose a secure object tracking protocol to ensure the visibility and traceability of an object along the travel path to support the Internet of Things (IoT). The proposed protocol is based on radio frequency identification system for global unique identification of IoT objects. For ensuring secure object tracking, lightweight cryptographic primitives and physically unclonable function are used by the proposed protocol in tags. We evaluated the proposed protocol both quantitatively and qualitatively. In our experiment, we modeled the protocol using security protocol description language (SPDL) and simulated SPDL model using automated claim verification tool Scyther. The results show that the proposed protocol is more secure and requires less computation compared to existing similar protocols.