Peter James Vial

Decoding Student Satisfaction: How to Manage and Improve the Laboratory Experience

The laboratory plays an important role in teaching engineering skills. An Electrical Engineering department at an Australian University implemented a reform to monitor and improve student satisfaction with the teaching laboratories. A Laboratory Manager was employed to oversee the quality of 27 courses containing instructional laboratories. Student satisfaction surveys were carried out on all relevant laboratories every year, and the data were used for continuous improvement. This paper will investigate the reforms that were implemented and outline a number of the improvements made. It also examines the programs overall impact on: (1) overall satisfaction; (2) laboratory notes; (3) learning experiences; (4) computer facilities; (5) engineering equipment; and (6) condition of the laboratory. Student satisfaction with the laboratories increased by 32% between 2007 and 2013. The results show that the laboratory notes (activity and clarity) and the quality of the equipment used are among the most influential factors on student satisfaction. In particular, it is important to have notes or resources that explain in some detail how to use and troubleshoot equipment and software used in the laboratory.

Hand gesture recognition: An overview

Hand gesture recognition has been applied to many fields in recent years, especially in man-machine interaction (MMI) area, which is regarded as a more natural and flexible input. In this paper, an overview of hand gesture recognition research up to date is presented, which includes common stages of hand gesture recognition, common methods and technique of each stage, the state of the recent research and summaries of some successful hand gesture recognition models.

Using online and multimedia resources to enhance the student learning experience in a telecommunications laboratory within an Australian University

ABSTRACT A laboratory component of an undergraduate telecommunications course consistently scored poorly for student learning experience on student surveys at an Australian university. Consultation with experienced academic staff revealed the need to modify the teaching resources available for the laboratory to include web-based multimedia and interactive resources. This new material was developed and made available to students and teaching staff in early 2011 via an Australian university e-learning package which was used to deliver the subject. The students and demonstrators were then encouraged to use this new resource to prepare for the three hour laboratory sessions. Surveys of students who took this laboratory in previous years were then compared to surveys of students using the latest version of the telecommunications laboratory in 2011 and 2012. The demonstrators themselves were also asked to provide feedback on their impressions of student learning. The comments from the laboratory demonstrators, feedback from the students, and assessment results indicate that the new online teaching material for both laboratory teaching staff and students has significantly improved the student learning experience. That this occurred two years in a row indicates that this improvement has ongoing benefits, irrespective of the teaching staff involved with the subject. The lessons learned can be applied to other similar learning environments.

Australian sign language recognition using moment invariants

Human Computer Interaction is geared towards seamless human machine integration without the need for LCDs, Keyboards or Gloves. Systems have already been developed to react to limited hand gestures especially in gaming and in consumer electronics control. Yet, it is a monumental task in bridging the well-developed sign languages in different parts of the world with a machine to interpret the meaning. One reason is the sheer extent of the vocabulary used in sign language and the sequence of gestures needed to communicate different words and phrases. Auslan the Australian Sign Language is comprised of numbers, finger spelling for words used in common practice and a medical dictionary. There are 7415 words listed in Auslan website. This research article tries to implement recognition of numerals using a computer using the static hand gesture recognition system developed for consumer electronics control at the University of Wollongong in Australia. The experimental results indicate that the numbers, zero to nine can be accurately recognized with occasional errors in few gestures. The system can be further enhanced to include larger numerals using a dynamic gesture recognition system.

Space time spreading with modified Walsh-Hadamard sequences

Previous work has shown that the performance of a space time spreading (STS) system using Walsh codes with two transmit antennas at the base station (BS) is degraded in the presence of mutual interference from adjacent sectors in the same cell. We use modified Walsh-Hadamard sequences exhibiting improved cross-correlation performance, which potentially mitigates the effects of MAI (multiple access interference). The presented study also looks at variation of sets of different modified Walsh-Hadamard codes being used by the adjacent interferer, with a hundred randomly selected pairings being chosen, as well as the case where one set of alternate codes is used. It is shown using simulation that significant improvement of the order of 0.5-2 dB is possible using these sequences instead of the standard Walsh code previously proposed.

A hybrid feature extraction technique for face recognition

The accuracy of any face recognition is important for many military and civilian real time applications. Based on current literature it has been proven that, the accuracy of a face recognition system can be extremely improved using a hybrid feature extraction technique. This paper presents a hybrid feature extraction technique to obtain high level of recognition accuracy. The facial topographical features are extracted using manual segmentation of facial regions of eyes, nose and mouth. The Gabor transform of the maximum of these regions are then extracted to calculate the local representations of these regions. In the classification stage, the Nearest Neighbour method (KNN) is exploited to calculate the distances between the three regions feature vectors and the corresponding stored vectors. The system results in excellent recognition accuracy using faces94, FEI and ORL databases. It is observed that, high recognition accuracy rate can be obtained when the facial images are taken carefully with front pose and with only slight expression changes. The future work will be on implementing this system in a FPGA device for a real time application such as a door access control system.

Computer Vision Based Traffic Monitoring System for Multi-track Freeways

Nowadays, development is synonymous with construction of infrastructure. Such road infrastructure needs constant attention in terms of traffic monitoring as even a single disaster on a major artery will disrupt the way of life. Humans cannot be expected to monitor these massive infrastructures over 24/7 and computer vision is increasingly being used to develop automated strategies to notify the human observers of any impending slowdowns and traffic bottlenecks. However, due to extreme costs associated with the current state of the art computer vision based networked monitoring systems, innovative computer vision based systems can be developed which are standalone and efficient in analyzing the traffic flow and tracking vehicles for speed detection. In this article, a traffic monitoring system is suggested that counts vehicles and tracks their speeds in realtime for multi-track freeways in Australia. Proposed algorithm uses Gaussian mixture model for detection of foreground and is capable of tracking the vehicle trajectory and extracts the useful traffic information for vehicle counting. This stationary surveillance system uses a fixed position overhead camera to monitor traffic.

An Approach to Ultra-Wideband Channel Calibration using a Vector Network Analyser

In this paper, two calibration methods are investigated to determine the most suitable approach for ultra-wideband (UWB) communication channel measurements. The first method is the through, open, short and match (TOSM) calibration technique. The second method is through, reflection and load calibration technique. Presented experiment results show that the through, reflection and load calibration process is more precise for calibration of coaxial cables and the UWB channel as clearly seen by increased magnitudes of the channel transfer function. It is also shown that the proposed through, reflection and load technique leads to an improved larger measured root-mean-square value and that the measured magnitude transfer function of the wireless channel is increased by an absolute value of approximately 5 dB after calibration compared with results achieved when TOSM technique is used. In the paper, it is also shown that the time delay associated with test equipment of the UWB channel measurement can be equally well removed by using either the through, reflection and load or TOSM calibration techniques.

Embedded door access control systems based on face recognition: A survey

The implementation of face recognition techniques in an embedded system is a very important aspect of various security applications, such as authorization identification in cash machines and door access for employee attendance. The purpose of this paper is to survey the existing hardware implementations of a face recognition system, particularly those who used for developing an embedded door access control system. This includes a brief discussion about face recognition algorithms and the hardware platforms outlining the importance of using a Field Programmable Gate Array (FPGA) device, which can be used to design an embedded door access control system. It is found that the success of any door access control system depends on the type of face recognition algorithm in the feature extraction phase of the face recognition system and the selected hardware device. Based on a comparison between different feature extraction algorithms, the use of a hybrid feature extraction technique can improve the accuracy of face recognition system. An efficient door access control system can be obtained using a FPGA device, which is preferable because of its technical characteristics of parallelism, re-programmability and very high speed, in the implementation of a face recognition system.

Mitagation against MAI in a Space Time Spreading Software Defined Radio Test Bed

A Software Defined Radio test bed using the Gnu Radio project was installed on Unix boxes and modified so that estimates of the channel state coefficients were taken for a Multiple Input Multiple output (MIMO) system to take advantage of space time transmission at a frequency of 2.4GHz. This system was modified to provide a Space Time Spreading test bed. The test bed was modified so that multiple access interference was experienced by offsetting different users data streams. The Walsh-Hadamard and Wysocki (low correlation) spreading sequences were deployed in the test bed to compare their Bit Error Rate performance. We confirmed that the low cross correlation spreading sequences experienced an improved Bit Error Rate compared to that obtained when using the Walsh-Hadamard Spreading sequence for high signal to noise ratios.