Learning detectors quickly with stationary statistics

Computer vision is increasingly becoming interested in the rapid estimation of object detectors. The canonical strategy of using Hard Negative Mining to train a Support Vector Machine is slow, since the large negative set must be traversed at least once per detector. Recent work has demonstrated that, with an assumption of signal stationarity, Linear Discriminant Analysis is able to learn comparable detectors without ever revisiting the negative set. Even with this insight, the time to learn a detector can still be on the order of minutes. Correlation filters, on the other hand, can produce a detector in under a second. However, this involves the unnatural assumption that the statistics are periodic, and requires the negative set to be re-sampled per detector size. These two methods differ chie y in the structure which they impose on the co- variance matrix of all examples. This paper is a comparative study which develops techniques (i) to assume periodic statistics without needing to revisit the negative set and (ii) to accelerate the estimation of detectors with aperiodic statistics. It is experimentally verified that periodicity is detrimental.

Learning information literacy

Introduction This paper reports on university students' experiences of learning information literacy. Method Phenomenography was selected as the research approach as it describes the experience from the perspective of the study participants, which in this case is a mixture of undergraduate and postgraduate students studying education at an Australian university. Semi-structured, one-on-one interviews were conducted with fifteen students. Analysis The interview transcripts were iteratively reviewed for similarities and differences in students' experiences of learning information literacy. Categories were constructed from an analysis of the distinct features of the experiences that students reported. The categories were grouped into a hierarchical structure that represents students' increasingly sophisticated experiences of learning information literacy. Results The study reveals that students experience learning information literacy in six ways: learning to find information; learning a process to use information; learning to use information to create a product; learning to use information to build a personal knowledge base; learning to use information to advance disciplinary knowledge; and learning to use information to grow as a person and to contribute to others. Conclusions Understanding the complexity of the concept of information literacy, and the collective and diverse range of ways students experience learning information literacy, enables academics and librarians to draw on the range of experiences reported by students to design academic curricula and information literacy education that targets more powerful ways of learning to find and use information.

Strategic capability development : a multi-level case study of the role of knowledge integration within product innovation

Capability development is at the heart of creating competitive advantage. This thesis intends to conceptualise Strategic Capability Development as a renewal of an organisation's existing capability in line with the requirements of the market. It followed and compared four product innovation projects within Iran Khodro Company (IKCO), an exemplar of capability development within the Iranian Auto industry. Findings show that the maturation of strategic capability at the organisational level has occurred through a sequence of product innovation projects and by dynamically shaping the learning and knowledge integration processes in accordance with emergence of the new structure within the industry. Accordingly, Strategic Capability Development is conceptualised in an interpretive model. Such findings are useful for development of an explanatory model and a practical capability development framework for managing learning and knowledge across different product innovation projects.

Characterising an ECG signal using statistical modelling : a feasibility study

For clinical use, in electrocardiogram (ECG) signal analysis it is important to detect not only the centre of the P wave, the QRS complex and the T wave, but also the time intervals, such as the ST segment. Much research focused entirely on qrs complex detection, via methods such as wavelet transforms, spline fitting and neural networks. However, drawbacks include the false classification of a severe noise spike as a QRS complex, possibly requiring manual editing, or the omission of information contained in other regions of the ECG signal. While some attempts were made to develop algorithms to detect additional signal characteristics, such as P and T waves, the reported success rates are subject to change from person-to-person and beat-to-beat. To address this variability we propose the use of Markov-chain Monte Carlo statistical modelling to extract the key features of an ECG signal and we report on a feasibility study to investigate the utility of the approach. The modelling approach is examined with reference to a realistic computer generated ECG signal, where details such as wave morphology and noise levels are variable.

The importance of understanding student learning styles in accounting degree programs

Accounting education is critical and any improvements in tertiary education of accounting students should result in better prepared graduates entering the profession. This study evaluates accounting students’ learning styles and the interaction of learning styles and teaching methodologies during degree programmes. Nine classes of accounting students (648 students) spread across four years and two degree programmes were evaluated. Students self-evaluated their learning style, pre-instruction. They were then subject to two separate teaching techniques (one active and one passive) in each course. Learning styles were then re-assessed and teaching techniques evaluated. Accounting students displayed a preference for passive learning, even those far advanced in their degrees. Furthermore, when learning styles matched teaching methods used, usefulness was assessed as high but when learning styles and teaching methods differed, usefulness deteriorated. Overall, the teaching methods were deemed more effective by active rather than passive learners. The implications are significant. To maximise educational benefit for the accounting profession, student learning styles should be assessed before designing appropriate teaching methodologies. This has resource implications which would have to be considered.

Learner autonomy in language learning : teachers' beliefs

This case study research investigated the extent to which Vietnamese teachers understood the concept of learner autonomy and how their beliefs about this concept were applied in their teaching practices. Data were collected through two phases of the study and revealed that teachers generally lacked understanding about learner autonomy; there was an alignment between this lack of understanding and teachers' actual teaching practices regarding learner autonomy. The findings of this study will provide teachers and policy-makers new insights into learner autonomy against the backdrop of educational reforms in Vietnam.

Perceptions of online learning in an Australian university : Malaysian students’ perspectives-usability of the online learning tools

This study set out to investigate the kinds of learning difficulties encountered by the Malaysian students and how they actually coped with online learning. The modified Online Learning Environment Survey (OLES) instrument was used to collect data from the sample of 40 Malaysian students at a university in Brisbane, Australia. A controlled group of 35 Australian students was also included for comparison purposes. Contrary to assumptions from previous researches, the findings revealed that there were only a few differences between the international Asian and Australian students with regards to their perceptions of online learning. Recommendations based on the findings of this research study were applicable for Australian universities which have Asian international students enrolled to study online.

Perceptions of online learning in an Australian university: an international students’ (Asian Region) perspective – enjoyment

Several researchers have reported that cultural and language differences can affect online interactions and communications between students from different cultural backgrounds. Other researchers have asserted that online learning is a tool that can improve teaching and learning skills, but its effectiveness depends on how the tool is used. To delve into these aspects further, this study set out to investigate the kinds of learning difficulties encountered by the international students and how they actually coped with online learning. The modified Online Learning Environment Survey (OLES) instrument was used to collect data from the sample of 109 international students at a university in Brisbane. A smaller group of 35 domestic students was also included for comparison purposes. Contrary to assumptions from previous research, the findings revealed that there were only few differences between the international Asian and Australian students with regards to their perceptions of online learning. Recommendations based on the findings of this research study were made for Australian universities where Asian international students study online. Specifically the recommendations highlighted the importance of upskilling of lecturers’ ability to structure their teaching online and to apply strong theoretical underpinnings when designing learning activities such as discussion forums, and for the university to establish a degree of consistency with regards to how content is located and displayed in a learning management system like Blackboard.

The why dimension - opening frontiers for digital learning

Digital learning has come a long way from the days of simple 'if-then' queries. It is now enabled by countless innovations that support knowledge sharing, openness, flexibility, and independent inquiry. Set against an evolutionary context this study investigated innovations that directly support human inquiry. Specifically, it identified five activities that together are defined as the 'why dimension' – asking, learning, understanding, knowing, and explaining why. Findings highlight deficiencies in mainstream search-based approaches to inquiry, which tend to privilege the retrieval of information as distinct from explanation. Instrumental to sense-making, the 'why dimension' provides a conceptual framework for development of 'sense-making technologies'.

Predicting freeway pavement construction cost using a back-propagation neural network : a case study in Henan, China

The objective of this research was to develop a model to estimate future freeway pavement construction costs in Henan Province, China. A comprehensive set of factors contributing to the cost of freeway pavement construction were included in the model formulation. These factors comprehensively reflect the characteristics of region and topography and altitude variation, the cost of labour, material, and equipment, and time-related variables such as index numbers of labour prices, material prices and equipment prices. An Artificial Neural Network model using the Back-Propagation learning algorithm was developed to estimate the cost of freeway pavement construction. A total of 88 valid freeway cases were obtained from freeway construction projects let by the Henan Transportation Department during the period 1994−2007. Data from a random selection of 81 freeway cases were used to train the Neural Network model and the remaining data were used to test the performance of the Neural Network model. The tested model was used to predict freeway pavement construction costs in 2010 based on predictions of input values. In addition, this paper provides a suggested correction for the prediction of the value for the future freeway pavement construction costs. Since the change in future freeway pavement construction cost is affected by many factors, the predictions obtained by the proposed method, and therefore the model, will need to be tested once actual data are obtained.

An alternate learning approach for destructive testing in civil engineering - Benefits from remote laboratory experimentation

An alternative learning approach for destructive testing of structural specimens in civil engineering is explored by using a remote laboratory experimentation method. The remote laboratory approach focuses on overcoming the constraints in the hands-on experimentation without compromising the understanding of the students on the concepts and mechanics of reinforced concrete structures. The goal of this study is to evaluate whether or not the remote laboratory experimentation approach can become a standard in civil engineering teaching. The teaching activity using remote-laboratory experimentation is presented here and the outcomes of this activity are outlined. The experience and feedback gathered from this study are used to improve the remote-laboratory experimentation approach in future years to other aspects of civil engineering where destructive testing is essential.

Applying threshold learning theory to teach sustainable business practice in post-graduate engineering education

This paper presents the results of a qualitative action-research inquiry into how a highly diverse cohort of post-graduate students could develop significant capacity in sustainable development within a single unit (course), in this case a compulsory component of four built environment masters programs. The method comprised applying threshold learning theory within the technical discipline of sustainable development, to transform student understanding of sustainable business practice in the built environment. This involved identifying a number of key threshold concepts, which once learned would provide a pathway to having a transformational learning experience. Curriculum was then revised, to focus on stepping through these targeted concepts using a scaffolded, problem-based-learning approach. Challenges included a large class size of 120 students, a majority of international students, and a wide span of disciplinary backgrounds across the spectrum of built environment professionals. Five ‘key’ threshold learning concepts were identified and the renewed curriculum was piloted in Semester 2 of 2011. The paper presents details of the study and findings from a mixed-method evaluation approach through the semester. The outcomes of this study will be used to inform further review of the course in 2012, including further consideration of the threshold concepts. In future, it is anticipated that this case study will inform a framework for rapidly embedding sustainability within curriculum.

Enhancing learning in large undergraduate classes using custom made audio-visual cases

This is an exploratory study into the effective use of embedding custom made audiovisual case studies (AVCS) in enhancing the student’s learning experience. This paper describes a project that used AVCS for a large divergent cohort of undergraduate students, enrolled in an International Business course. The study makes a number of key contributions to advancing learning and teaching within the discipline. AVCS provide first hand reporting of the case material, where the students have the ability to improve their understanding from both verbal and nonverbal cues. The paper demonstrates how AVCS can be embedded in a student-centred teaching approach to capture the students’ interest and to enhance a deep approach to learning by providing real-world authentic experience.

Application of machine learning technique in wind turbine fault diagnosis

In this study, a machine learning technique called anomaly detection is employed for wind turbine bearing fault detection. Basically, the anomaly detection algorithm is used to recognize the presence of unusual and potentially faulty data in a dataset, which contains two phases: a training phase and a testing phase. Two bearing datasets were used to validate the proposed technique, fault-seeded bearing from a test rig located at Case Western Reserve University to validate the accuracy of the anomaly detection method, and a test to failure data of bearings from the NSF I/UCR Center for Intelligent Maintenance Systems (IMS). The latter data set was used to compare anomaly detection with SVM, a previously well-known applied method, in rapidly finding the incipient faults.

Using visualization tool to help engineering students learning dynamics

Dynamics is an essential core engineering subject. It includes high level mathematical and theoretical contents, and basic concepts which are abstract in nature. Hence, Dynamics is considered as one of the hardest subjects in the engineering discipline. To assist our students in learning this subject, we have conducted a Teaching & Learning project to study ways and methods to effectively teach Dynamics based on visualization techniques. The research project adopts the five basic steps of Action Learning Cycle. It is found that visualization technique is a powerful tool for students learning Dynamics and helps to break the barrier of students who perceived Dynamics as a hard subject.