David A. McMeekin

Classifying eye and head movement artifacts in EEG signals

Brain Computer Interfaces has some exciting prospects such as controlling devices at the speed of thought. However BCI technology is far from attaining this goal. A significant challenge the EEG-based system has is the interference of artifacts in the EEG generated by eye and head movement. This paper presents the use of machine learning techniques to classify artifacts in the EEG. Successful artifact classification was then be applied to improve existing artifact removal techniques. The experiment used a state-of-the-art EEG system to gather the classifier input. An eye tracker and motion sensor were also used to measure and provide the ground truth for the classification experiments. The data from these devices were captured using custom built software developed for this research. The classifiers tested showed potential to classify artifacts in the EEG when trained on a per-person basis. This research paves the way for further work to be carried out to explore subject-independent artifact classification.

Evaluating Software Inspection Cognition Levels Using Bloom's Taxonomy

This paper reports on results from a pilot study that used Bloom’s Taxonomy to observe cognition levels during software inspections conducted by undergraduate computer science and software engineering students. Cognition levels associated with three different code inspection techniques were investigated. These were the Ad hoc, Abstraction Driven, and Checklist-based reading strategies. Higher cognition levels were observed when using inspection techniques that utilise a more structured reading process. This result highlights the importance of introducing novice programmers to structured code reading strategies. Findings suggest that teaching different software inspection techniques throughout software courses, beginning with structured techniques, is an excellent way to build a student’s critical software reading and analysis skills.

Checklist Inspections and Modifications: Applying Bloom's Taxonomy to Categorise Developer Comprehension

Software maintenance can consume up to 70% of the effort spent on a software project, with more than half of this devoted to understanding the system. Performing a software inspection is expected to contribute to comprehension of the software. The question is: at what cognition levels do novice developers operate during a checklist-based code inspection followed by a code modification? This paper reports on a pilot study of Blooms taxonomy levels observed during a checklist-based inspection and while adding new functionality unrelated to the defects detected. Blooms taxonomy was used to categorise think-aloud data recorded while performing these activities. Results show the checklist-based reading technique facilitates inspectors to function at the highest cognitive level within the taxonomy and indicates that using inspections with novice developers to improve cognition and understanding may assist integrating developers into existing project teams.

The Significance of Participant Experience when Evaluating Software Inspection Techniques

Software inspections have been used to improve software quality for 30 years. The Checklist Based Reading strategy has traditionally been the most prevalent reading strategy. Increased Object Oriented usage has raised questions regarding this techniques efficacy, given issues such as delocalisation. This study compared two OO inspection techniques: Use-Case Reading and Usage-Based Reading, with Checklist Based Reading. Students and industry professionals were recruited to participate in the study. The effectiveness of each reading strategy was analysed, and the effect experience had on inspection efficacy. The results showed no significant difference between inspection techniques, whether used by student or professional developers but a significant difference was identified between student and professional developers in applying the different techniques. Qualitative results highlighted the differences in ability between industry and students with respect to what each group considered important when inspecting and writing code. These results highlight the differences between student and industry professionals when applying inspections. Therefore, when selecting participants for empirical software engineering studies, participant experience level must be accounted for within the reporting of results.

Checklist Based Reading's Influence on a Developer's Understanding

This paper addresses the influence the checklist based reading inspection technique has on a developers ability to modify inspected code. Traditionally, inspections have been used to detect defects within the development life cycle. This research identified a correlation between the number of defects detected and the successful code extensions for new functionality unrelated to the defects. Participants reported that having completed a checklist inspection, modifying the code was easier because the inspection had given them an understanding of the code that would not have existed otherwise. The results also showed a significant difference in how developers systematically modified code after completing a checklist inspection when compared to those who had not performed a checklist inspection. This study has shown that applying software inspections for purposes other than defect detection include software understanding and comprehension.

Spatial Data Infrastructures and the Semantic Web of Spatial Things in Australia: Research Opportunities in SDI and the Semantic Web

Spatial Data Infrastructures have recently become a crucial part of national infrastructures. Example users are governments using them to make informed policy decisions and the private sector using them in order to understand their customers better. It is estimated that Australian spatial industry revenue is in excess of

Practical Segmentation Methods for Logical and Geometric Layout Analysis to Improve Scanned PDF Accessibility to Vision Impaired

1.35 billion annually. The Cooperative Research Centre for Spatial Information in Australia is currently working with the Commonwealth, jurisdictions and the private sector to understand the research required in this area to support both the public and private sectors in their decision and policy making based upon these infrastructures. This paper presents an early perspective as to possible research areas in this field. An underlying theme that reoccurs in the research is the need to consider usability of such systems and the need to move beyond just data to orchestration of processes to obtain derived products.

Layout Analysis for Scanned PDF and Transformation to the Structured PDF Suitable for Vocalization and Navigation

The use of electronic documents has rapidly increased in recent decades and the PDF is one the most commonly used electronic document formats. A scanned PDF is an image and does not actually contain any text. For the vision–impaired user who is dependent upon a screen reader to access this information, this format is not useful. Thus addressing PDF accessibility through assistive technology has now become an important concern. PDF layout analysis provides precious formatting information that supports PDF component classification. This classification facilitates the tag generation. Accurate tagging produces a searchable and navigable scanned PDF document. This paper describes several practical segmentation methods which are easy to implement and efficient for PDF layout analysis so that the scanned PDF document can be navigated or searched using assistive technologies.

Complex environment evolution: Challenges with semantic service infrastructures

Information can include text, pictures and signatures that can be scanned into a document format, such as the Portable Document Format (PDF), and easily emailed to recipients around the world. Upon the document’s arrival, the receiver can open and view it using a vast array of different PDF viewing applications such as Adobe Reader and Apple Preview. Hence, today the use of the PDF has become pervasive. Since the scanned PDF is an image format, it is inaccessible to assistive technologies such as a screen reader. Therefore, the retrieval of the information needs Optical Character Recognition (OCR). The OCR software scans the scanned PDF file and through text extraction generates an editable text formatted document. This text document can then be edited, formatted, searched and indexed as well as translated or converted to speech. A problem that the OCR software does not solve is the accurate regeneration of the full text layout. This paper presents a technology that addresses this issue by closely preserving the original textual layout of the scanned PDF using the open source document analysis and OCR system (OCRopus) based on geometric layout and positioning information. The main issues considered in this research are the preservation of the correct reading order, and the representation of common logical structured elements such as section headings, line breaks, paragraphs, captions, and sidebars, foot-bars, running headers, embedded images, graphics, tables and mathematical expressions.

Quantitative study of geological target spotting with the use of eye tracking

Service infrastructures are often key for the efficient operation of complex environments, such as a large Smart Home infrastructure for a mining camp. The evolution of such service infrastructures, in response to an increased workload on the system or a changing resource allocation, is often tedious and expensive, due to weak evolvability support of its service portfolio. This underpins the need for services to be designed with high evolvability characteristics. Semantic Web technologies have been anticipated as a basis for the required Web service evolution. JSON-LD is a prominent Semantic Web technology used in combination with ontologies, developed with the Web Ontology Language (OWL), to face the evolutionary challenges. Our applied research investigates common Web service tasks, automated using above technologies. It is explained, that this enables the creation of evolutionary building blocks. These building blocks are incrementally combined here for the overall service portfolio, culminating in a model of a semantic agent which excels in its capacity to evolve. Our model is then adopted and assessed for the system infrastructure of the Smart Camp project, as a use case for an agile, complex logistic environment.