A topic based document relevance ranking model

Topic modelling has been widely used in the fields of information retrieval, text mining, machine learning, etc. In this paper, we propose a novel model, Pattern Enhanced Topic Model (PETM), which makes improvements to topic modelling by semantically representing topics with discriminative patterns, and also makes innovative contributions to information filtering by utilising the proposed PETM to determine document relevance based on topics distribution and maximum matched patterns proposed in this paper. Extensive experiments are conducted to evaluate the effectiveness of PETM by using the TREC data collection Reuters Corpus Volume 1. The results show that the proposed model significantly outperforms both state-of-the-art term-based models and pattern-based models.

Partitioning of dioxins (PCDDs/Fs) in ambient air at urban residential locations

In this work, 17-polychlorinated dibenzo-pdioxin/furan (PCDD/Fs) isomers were measured in ambient air at four urban sites in Seoul, Korea (from February to June 2009). The concentrations of their summed values RPCDD/Fs) across all four sites ranged from 1,947 (271 WHO05 TEQ) (Jong Ro) to 2,600 (349 WHO05 TEQ) fg/m3 (Yang Jae) with a mean of 2,125 ± 317) fg/m3 (292 WHO05 TEQ fg/m3). The sum values for the two isomer groups of RPCDD and RPCDF were 527 (30 WHO05 TEQ) and 1,598 (263 WHO05 TEQ) fg/m3, respectively. The concentration profile of individual species was dominated by the 2,3,4,7,8-PeCDF isomer, which contributed approximately 36 % of the RPCDD/Fs value. The observed temporal trends in PCDD/F concentrations were characterized by relative enhancement in the winter and spring. The relative contribution of different sources, when assessed by principal component analysis, is explained by the dominance of vehicular emissions along with coal (or gas) burning as the key source of ambient PCDD/Fs in the residential areas studied.

Tensor-based item recommendation using probabilistic ranking in social tagging systems

A common problem with the use of tensor modeling in generating quality recommendations for large datasets is scalability. In this paper, we propose the Tensor-based Recommendation using Probabilistic Ranking method that generates the reconstructed tensor using block-striped parallel matrix multiplication and then probabilistically calculates the preferences of user to rank the recommended items. Empirical analysis on two real-world datasets shows that the proposed method is scalable for large tensor datasets and is able to outperform the benchmarking methods in terms of accuracy.

Constructions of cheating immune secret sharing

The work addresses the problem of cheating prevention in secret sharing. Two cheating scenarios are considered. In the first one, the cheaters always submit invalid shares to the combiner. In the second one, the cheaters collectively decide which shares are to be modified so the combiner gets a mixture of valid and invalid shares from the cheaters. The secret scheme is said to be k-cheating immune if any group of k cheaters has no advantage over honest participants. The paper investigates cryptographic properties of the defining function of secret sharing so the scheme is k-cheating immune. Constructions of secret sharing immune against k cheaters are given.

Influence of jet inclination on structural loading in an experimentally simulated microburst

Steady and pulsed flow stationary impinging jets have been employed to simulate the wind field produced by a thunderstorm microburst. The effect on the low level wind field due to jet inclination with respect to the impingement surface has been studied. A single point velocity time history has been compared to the full-scale Andrews AFB microburst for model validation. It was found that for steady flow, jet inclination increased the radial extent of high winds but did not increase the magnitude of these winds when compared to the perpendicular impingement case. It was found that for inclined pulsed flow the design wind conditions could increase compared to perpendicular impingement. It was found that the location of peak winds was affected by varying the outlet conditions.

An MRF based abnormal event detection approach using motion and appearance features

Abnormal event detection has attracted a lot of attention in the computer vision research community during recent years due to the increased focus on automated surveillance systems to improve security in public places. Due to the scarcity of training data and the definition of an abnormality being dependent on context, abnormal event detection is generally formulated as a data-driven approach where activities are modeled in an unsupervised fashion during the training phase. In this work, we use a Gaussian mixture model (GMM) to cluster the activities during the training phase, and propose a Gaussian mixture model based Markov random field (GMM-MRF) to estimate the likelihood scores of new videos in the testing phase. Further-more, we propose two new features: optical acceleration, and the histogram of optical flow gradients; to detect the presence of any abnormal objects and speed violations in the scene. We show that our proposed method outperforms other state of the art abnormal event detection algorithms on publicly available UCSD dataset.

All about that base : differing player experiences in video game genres and the unique case of MOBA games

Video games provide unique interactive player experiences (PX) often categorised into different genres. Prior research has looked at different game genres, but rarely through a PX lens. Especially, PX in the emerging area of massive online battle arena (MOBA) games is not well understood by researchers in the field. We address this knowledge gap by presenting a PX study of different game genres, which we followed up with a second semi-structured interview study about PX in MOBA games. Among the results of our analyses are that games that are likely played with other players, such as MOBA games, stimulate less immersion and presence for players. Additionally, while challenge and frustration are significantly higher in this genre, players get a sense of satisfaction from teamwork, competition and mastery of complex gameplay interactions. Our study is the first to contribute a comprehensive insight into key motivators of MOBA players and how PX in this genre is different from other genres.

Autonomous helicopter hover using an artificial neural network

Details the developments to date of an unmanned air vehicle (UAV) based on a standard size 60 model helicopter. The design goal is to have the helicopter achieve stable hover with the aid of an INS and stereo vision. The focus of the paper is on the development of an artificial neural network (ANN) that makes use of only the INS data to generate hover commands, which are used to directly manipulate the flight servos. Current results show that networks incorporating some form of recurrency (state history) offer little advantage over those without. At this stage, the ANN has partially maintained periods of hover even with misaligned sensors.

Exploring physical activities in an employer-sponsored health program

This work brings a perspective from an employer-sponsored health and wellness program called Global Corporate Challenge (GCC) to the 'quantified self' research. We present preliminary findings from a study with 17 university employees who participated in the GCC. We aimed to explore how participants derived meaningfulness from their self-tracking experiences. Our findings echo the growing body of work that advocates for conceptualizing activity tracking beyond the rationalistic, data-oriented perspectives and supporting more social and lived experiences.

Exploring motivations of young adults to participate in physical activities

This paper investigates the motivations of young adults aged 18 to 24 years to participate in physical activities and how technology might best support this motivation. Motivational factors were studied through contextual interviews, an adapted cultural probe activity and a survey with a group of young adults currently active in sports. From our preliminary findings we determine that staying healthy, achieving specific goals and socialising represent key motivational factors for young adults to be active in sports, but also, that exercise is not considered a high priority in their daily lives. A link between the motivation of achieving specific goals and a technology to measure and track activities was established. The study concludes with three implications for the design of technology to motivate young adults to participate in sports.

Fixing the alignment: An exploration of budgeting practices in the home

Budgeting is an important means of controlling ones finances and reducing debt. This paper outlines our work towards designing more user centred technology for individual and household budgeting. Based on an ethnographically informed study with 15 participants, we highlight a misalignment between people's actual budgeting practices and those supported by off-the-shelf budgeting aids. In addressing this misalignment we outline three tenets that may be incorporated into future work in this area. These include (1) catering for the different phases of engagement with technology; (2) catering for the practices of hiding and limiting access to money, and; (3) integrating materiality into technical solutions.

The messaging kettle: Prototyping connection over a distance between adult children and older parents

A prototype "messaging kettle" is described. The connected kettle aims to foster communication and engagement with an older friend or relative who lives remotely, during the routine of boiling the kettle. We describe preliminary encounters and findings from demonstrating a working prototype in morning tea gatherings of people in their 50s-late 70s and from introducing it into the homes of two people in their 80s who live on another continent. Key findings are that: The concept of keeping in touch around a "habituated object" such as a kettle was well received; Simple and varied interaction modalities that allow asymmetric forms of communication are needed; Designing for use across different time zones requires attention; And, that even when augmenting a habituated object, the process of introduction, appropriation and habituation still needs significant attention and investigation.

Bringing the farmer perspective to agricultural robots

The research reported in this paper explores autonomous technologies for agricultural farming application and is focused on the development of multiple-cooperative agricultural robots (AgBots). These are highly autonomous, small, lightweight, and unmanned machines that operate cooperatively (as opposed to a traditional single heavy machine) and are suited to work on broadacre land (large-scale crop operations on land parcels greater than 4,000m2). Since this is a new, and potentially disruptive technology, little is yet known about farmer attitudes towards robots, how robots might be incorporated into current farming practice, and how best to marry the capability of the robot with the work of the farmer. This paper reports preliminary insights (with a focus on farmer-robot control) gathered from field visits and contextual interviews with farmers, and contributes knowledge that will enable further work toward the design and application of agricultural robotics.

Knowledge transfer through a transnational program partnership between Indonesian and Australian universities

As transnational programs are often advocated as a knowledge transfer opportunity between the partner universities, this case study investigated the knowledge transfer (KT) processes between Indonesian and Australian universities through an undergraduate transnational program partnership (TPP). An inter-organisational KT theoretical framework from the business sector was adapted and used to guide the study. The data were generated through semi-structured interviews with key university officers and document analysis from two partner universities. Based on the thematic analysis of the data, the findings demonstrated that the curriculum mapping process facilitated KT. However, different intentions of the partner universities in establishing the program led to declining interest to conduct more KT when expectations were not met. The Indonesian university’s existing knowledge, acquired from other sources through processes that were serendipitous and based on individual lecturers’ personal experience, meant that KT opportunities through the TPP were not always pursued despite written agreement to exchange knowledge with the Australian partner. While KT most evidently resulted in institutional capacity development for the Indonesian university’s school that managed the TPP, dissemination of knowledge to other units within the university was more challenging due to communication problems between the units. Hence, other universities seeking to conduct KT through TPPs need to understand each partner university's intention in establishing the partnerships, identify the institutions' needs before seeking knowledge input from the partner university and improve the communication between and within the universities for sustainable benefits.