Understanding the fabric of social interactions for ridesharing through mining social networking sites

The design of applications for dynamic ridesharing or carpooling is often formulated as a matching problem of connecting people with an aligned set of transport needs within a reasonable interval of time and space. This problem formulation relegates social connections to being secondary factors. Technology assisted ridesharing applications that put the matching problem first have revealed that they suffer from being unable to address the factor of social comfort, even after adding friend features or piggybacking on social networking sites. This research aims to understand the fabric of social interactions through which ridesharing happens. We take an online observation approach in order to understand the fabric of social interactions for ridesharing that is happening in highly subscribed online groups of local residents. This understanding will help researchers to identify design challenges and opportunities to support ridesharing in local communities. This paper contributes a fundamental understanding of how social interactions and social comfort precede rideshare requests in local communities.

Semi-binary based video features for activity representation

Efficient and effective feature detection and representation is an important consideration when processing videos, and a large number of applications such as motion analysis, 3D scene understanding, tracking etc. depend on this. Amongst several feature description methods, local features are becoming increasingly popular for representing videos because of their simplicity and efficiency. While they achieve state-of-the-art performance with low computational complexity, their performance is still too limited for real world applications. Furthermore, rapid increases in the uptake of mobile devices has increased the demand for algorithms that can run with reduced memory and computational requirements. In this paper we propose a semi binary based feature detectordescriptor based on the BRISK detector, which can detect and represent videos with significantly reduced computational requirements, while achieving comparable performance to the state of the art spatio-temporal feature descriptors. First, the BRISK feature detector is applied on a frame by frame basis to detect interest points, then the detected key points are compared against consecutive frames for significant motion. Key points with significant motion are encoded with the BRISK descriptor in the spatial domain and Motion Boundary Histogram in the temporal domain. This descriptor is not only lightweight but also has lower memory requirements because of the binary nature of the BRISK descriptor, allowing the possibility of applications using hand held devices.We evaluate the combination of detectordescriptor performance in the context of action classification with a standard, popular bag-of-features with SVM framework. Experiments are carried out on two popular datasets with varying complexity and we demonstrate comparable performance with other descriptors with reduced computational complexity.

Real-time mobile 3D temperature mapping

The ability to measure surface temperature and represent it on a metrically accurate 3D model has proven applications in many areas such as medical imaging, building energy auditing, and search and rescue. A system is proposed that enables this task to be performed with a handheld sensor, and for the first time with results able to be visualized and analyzed in real-time. A device comprising a thermal-infrared camera and range sensor is calibrated geometrically and used for data capture. The device is localized using a combination of ICP and video-based pose estimation from the thermal-infrared video footage which is shown to reduce the occurrence of failure modes. Furthermore, the problem of misregistration which can introduce severe distortions in assigned surface temperatures is avoided through the use of a risk-averse neighborhood weighting mechanism. Results demonstrate that the system is more stable and accurate than previous approaches, and can be used to accurately model complex objects and environments for practical tasks.

Process mining for clinical processes: A comparative analysis of four Australian hospitals

Business process analysis and process mining, particularly within the health care domain, remain under-utilised. Applied research that employs such techniques to routinely collected, health care data enables stakeholders to empirically investigate care as it is delivered by different health providers. However, cross-organisational mining and the comparative analysis of processes present a set of unique challenges in terms of ensuring population and activity comparability, visualising the mined models and interpreting the results. Without addressing these issues, health providers will find it difficult to use process mining insights, and the potential benefits of evidence-based process improvement within health will remain unrealised. In this paper, we present a brief introduction on the nature of health care processes; a review of the process mining in health literature; and a case study conducted to explore and learn how health care data, and cross-organisational comparisons with process mining techniques may be approached. The case study applies process mining techniques to administrative and clinical data for patients who present with chest pain symptoms at one of four public hospitals in South Australia. We demonstrate an approach that provides detailed insights into clinical (quality of patient health) and fiscal (hospital budget) pressures in health care practice. We conclude by discussing the key lessons learned from our experience in conducting business process analysis and process mining based on the data from four different hospitals.

A cognitive processing framework for learning analytics

Incorporating a learner’s level of cognitive processing into Learning Analytics presents opportunities for obtaining rich data on the learning process. We propose a framework called COPA that provides a basis for mapping levels of cognitive operation into a learning analytics system. We utilise Bloom’s taxonomy, a theoretically respected conceptualisation of cognitive processing, and apply it in a flexible structure that can be implemented incrementally and with varying degree of complexity within an educational organisation. We outline how the framework is applied, and its key benefits and limitations. Finally, we apply COPA to a University undergraduate unit, and demonstrate its utility in identifying key missing elements in the structure of the course.

A multi-touch notice board fostering social interaction

We report on an alternative OCGM interface for a bulletin board, where a user can pin a note or a drawing, and actually shares contents. Exploiting direct and continuous manipulations, opposite to discrete gestures, to explore containers, the proposed interface supports a more natural and immediate interaction. It manages also the presence of different simultaneous users, allowing for the creation of local multimedia contents, the connection to social networks, providing a suitable working environment for cooperative and collaborative tasks in a multi-touch setup, such as touch-tables, interactive walls or multimedia boards

Efficient top-k retrieval with signatures

This paper describes a new method of indexing and searching large binary signature collections to efficiently find similar signatures, addressing the scalability problem in signature search. Signatures offer efficient computation with acceptable measure of similarity in numerous applications. However, performing a complete search with a given search argument (a signature) requires a Hamming distance calculation against every signature in the collection. This quickly becomes excessive when dealing with large collections, presenting issues of scalability that limit their applicability. Our method efficiently finds similar signatures in very large collections, trading memory use and precision for greatly improved search speed. Experimental results demonstrate that our approach is capable of finding a set of nearest signatures to a given search argument with a high degree of speed and fidelity.

ADCS reaches adulthood : an analysis of the conference and its community over the last eighteen years

How influential is the Australian Document Computing Symposium (ADCS)? What do ADCS articles speak about and who cites them? Who is the ADCS community and how has it evolved? This paper considers eighteen years of ADCS, investigating both the conference and its community. A content analysis of the proceedings uncovers the diversity of topics covered in ADCS and how these have changed over the years. Citation analysis reveals the impact of the papers. The number of authors and where they originate from reveal who has contributed to the conference. Finally, we generate co-author networks which reveal the collaborations within the community. These networks show how clusters of researchers form, the effect geographic location has on collaboration, and how these have evolved over time.

Making mangoes move

A landscape of mangoes most likely brings to mind a place in a tropical location. By the end of the nineteenth century that place could have been located on any continent in the world. Mangoes were found in geographic locations; in scientific institutions; as crop plants; and as a backyard trees. Here I trace the movement of mangoes Mangifera indica Linn., focusing on the transnational links formed through colonial botanic gardens in Australia. Botanic gardens were largely understood through their work in establishing economically successful plantation crops, such as sugar and tea. Mangoes were not a success crop of the age of botanic imperialism. Instead, mangoes were simply one species among the millions of plants that botanic gardens moved in addition to these well known commercial crops. Colonial science moved plants for a myriad of other types of reasons, for ornament, for curiosity, for lesser commercial purposes and for pure science. In each site the mango emerged, the discourses and technologies that traveled with it changed according to local needs. Indeed, rather than finding mangoes located in one place, tracing their movement demonstrates that this was an extended landscape connecting these things across time and space...

A stochastic thermostat algorithm for coarse-grained thermomechanical modeling of large-scale soft matters : theory and application to microfilaments

As all-atom molecular dynamics method is limited by its enormous computational cost, various coarse-grained strategies have been developed to extend the length scale of soft matters in the modeling of mechanical behaviors. However, the classical thermostat algorithm in highly coarse-grained molecular dynamics method would underestimate the thermodynamic behaviors of soft matters (e.g. microfilaments in cells), which can weaken the ability of materials to overcome local energy traps in granular modeling. Based on all-atom molecular dynamics modeling of microfilament fragments (G-actin clusters), a new stochastic thermostat algorithm is developed to retain the representation of thermodynamic properties of microfilaments at extra coarse-grained level. The accuracy of this stochastic thermostat algorithm is validated by all-atom MD simulation. This new stochastic thermostat algorithm provides an efficient way to investigate the thermomechanical properties of large-scale soft matters.

Activity, motivation and games for young children

The research described in this paper examines the extent to which very young children were able to use the Stomp platform (a floor-based gaming system designed to provide new, active participatory experiences) to engage in game play. We are interested in how children's engagement in different activities within the game world influences their motivation to play games. We map activity to motivational needs of competence, autonomy and relatedness. A detailed examination of two Stomp experiences demonstrates how this type of analysis is useful in identifying the strengths and weaknesses of the games for this audience.

Dispelling ageing myths in technology design

We present a review of literature from the fields of gerontology, gerontechnology, HCI and government policy that deals with social and technical solutions for the ageing population. We highlight common assumptions about ageing people, which we argue are still embedded in much of the research related to the domain of ageing. This paper challenges six common assumptions across four broad themes that we identified in the literature. It aims to provide a reminder and resource for designers to eschew assumptions during designing technology for 'older' users.

Visual metrics for the evaluation of sensor data quality in outdoor perception

This paper proposes an experimental study of quality metrics that can be applied to visual and infrared images acquired from cameras onboard an unmanned ground vehicle (UGV). The relevance of existing metrics in this context is discussed and a novel metric is introduced. Selected metrics are evaluated on data collected by a UGV in clear and challenging environmental conditions, represented in this paper by the presence of airborne dust or smoke.

High coexpression of both EGFR and IGF1R correlates with poor patient prognosis in resected non-small-cell lung cancer

Background Recent experimental and biomarker evidence indicates that the epidermal growth factor receptor (EGFR) and insulin-like growth factor receptor 1 (IGF1R) interact in the pathogenesis of malignant epithelial tumors, including lung cancer. This study examines the expression of both receptors and their prognostic significance in surgically resected non-small-cell lung cancer (NSCLC). Methods EGFR and IGF1R expression were evaluated in 184 patients with NSCLC (83 squamous cell carcinomas [SCCs], 83 adenocarcinomas [ADCs], and 18 other types) using immunohistochemical (IHC) analysis. Expression of both receptors was examined in matched fresh frozen normal and tumor tissues from 40 patients with NSCLC (20 SCCs and 20 ADCs) by Western blot analysis. Results High EGFR expression was detected in 51% of patients, and SCCs had higher EGFR expression than did non-SCCs (57.4% vs. 42.5%; P =.028). High IGF1R expression was observed in 53.8% of patients, with SCC having higher expression than non-SCC (62.6% vs. 37.3%; P =.0004). A significant association was shown between EGFR and IGF1R protein overexpression (P <.005). Patients with high expression of both receptors had a poorer overall survival (OS) (P =.04). Higher EGFR and IGF1R expression was detected in resected tumors relative to matched normal tissues (P =.0004 and P =.0009), with SCC having higher expression levels than ADC. Conclusion Our findings indicate a close interrelationship between EGFR and IGF1R. Coexpression of both receptors correlates with poor survival. This subset of patients may benefit from treatments cotargeting EGFR and IGF1R. © 2014 Elsevier Inc. All rights reserved.

A shared reading intervention with parents to enhance young children’s early literacy skills

Parental reading to children from an early age has been shown to enhance children’s emergent literacy skills. A pragmatic randomized controlled trial (RCT) was used to investigate the effects of two forms of shared reading interventions on children’s language and literacy skills. Parents of 80 preparatory year children from outer suburban schools of an Australian metropolitan city were trained to use shared reading strategies in an eight-week home intervention. Families were assigned to one of three groups: Dialogic Reading (DR), Dialogic Reading with the addition of Print Referencing (DR + PR), or an attention-matched control group. The sample comprised 42 boys and 38 girls ranging in age from 4.9 years to 6.3 years (M = 5.5, SD = 0.3). Data were collected at pre, post, and at three months follow-up. Measures assessed children’s oral language (receptive and expressive vocabulary), phonological awareness (rhyme, word completion), alphabet knowledge, and concepts about print. Analyses of change from pre to post showed significant effects for the DR and DR + PR groups compared to the control group on three of the six measures: expressive language, rhyme, and concepts about print. At 3-month follow-up assessment, the two intervention groups maintained significantly better performance on the measure of concepts of print only. At both time points, there were no group differences between the DR and DR+PR conditions. These findings illustrate the potential of a brief home focused intervention on promoting children’s emergent literacy.