Directed Exploration using a Modified Distance Transform

Mobile robots operating in unknown environments need to build maps. To do so they must have an exploration algorithm to plan a path. This algorithm should guarantee that the whole of the environment, or at least some designated area, will be mapped. The path should also be optimal in some sense and not simply a "random walk" which is clearly inefficient. When multiple robots are involved, the algorithm also needs to take advantage of the fact that the robots can share the task. In this paper we discuss a modification to the well-known distance transform that satisfies these requirements

Personalizing the design of computer‐based instruction to enhance learning

This paper reports two studies designed to investigate the effect on learning outcomes of matching individuals’ preferred cognitive styles to computer‐based instructional (CBI) material. Study 1 considered the styles individually as Verbalizer, Imager, Wholist and Analytic. Study 2 considered the bi‐dimensional nature of cognitive styles in order to assess the full ramification of cognitive styles on learning: Analytic/Imager, Analytic/ Verbalizer, Wholist/Imager and the Wholist/Verbalizer. The mix of images and text, the nature of the text material, use of advance organizers and proximity of information to facilitate meaningful connections between various pieces of information were some of the considerations in the design of the CBI material. In a quasi‐experimental format, students’ cognitive styles were analysed by Cognitive Style Analysis (CSA) software. On the basis of the CSA result, the system defaulted students to either matched or mismatched CBI material by alternating between the two formats. The instructional material had a learning and a test phase. Learning outcome was tested on recall, labelling, explanation and problem‐solving tasks. Comparison of the matched and mismatched instruction did not indicate significant difference between the groups, but the consistently better performance by the matched group suggests potential for further investigations where the limitations cited in this paper are eliminated. The result did indicate a significant difference between the four cognitive styles with the Wholist/Verbalizer group performing better then all other cognitive styles. Analysing the difference between cognitive styles on individual test tasks indicated significant difference on recall, labelling and explanation, suggesting that certain test tasks may suit certain cognitive styles

Monocular Vision as a Range Sensor

One of the most important abilities for a mobile robot is detecting obstacles in order to avoid collisions. Building a map of these obstacles is the next logical step. Most robots to date have used sensors such as passive or active infrared, sonar or laser range finders to locate obstacles in their path. In contrast, this work uses a single colour camera as the only sensor, and consequently the robot must obtain range information from the camera images. We propose simple methods for determining the range to the nearest obstacle in any direction in the robot’s field of view, referred to as the Radial Obstacle Profile. The ROP can then be used to determine the amount of rotation between two successive images, which is important for constructing a 360º view of the surrounding environment as part of map construction

From Review to Rating: Exploring Dependency Measures for Text Classification

Various text analysis techniques exist, which attempt to uncover unstructured information from text. In this work, we explore using statistical dependence measures for textual classification, representing text as word vectors. Student satisfaction scores on a 3-point scale and their free text comments written about university subjects are used as the dataset. We have compared two textual representations: a frequency word representation and term frequency relationship to word vectors, and found that word vectors provide a greater accuracy. However, these word vectors have a large number of features which aggravates the burden of computational complexity. Thus, we explored using a non-linear dependency measure for feature selection by maximizing the dependence between the text reviews and corresponding scores. Our quantitative and qualitative analysis on a student satisfaction dataset shows that our approach achieves comparable accuracy to the full feature vector, while being an order of magnitude faster in testing. These text analysis and feature reduction techniques can be used for other textual data applications such as sentiment analysis.Comment: 8 page

Digital image watermarking: its formal model, fundamental properties and possible attacks

While formal definitions and security proofs are well established in some fields like cryptography and steganography, they are not as evident in digital watermarking research. A systematic development of watermarking schemes is desirable, but at present their development is usually informal, ad hoc, and omits the complete realization of application scenarios. This practice not only hinders the choice and use of a suitable scheme for a watermarking application, but also leads to debate about the state-of-the-art for different watermarking applications. With a view to the systematic development of watermarking schemes, we present a formal generic model for digital image watermarking. Considering possible inputs, outputs, and component functions, the initial construction of a basic watermarking model is developed further to incorporate the use of keys. On the basis of our proposed model, fundamental watermarking properties are defined and their importance exemplified for different image applications. We also define a set of possible attacks using our model showing different winning scenarios depending on the adversary capabilities. It is envisaged that with a proper consideration of watermarking properties and adversary actions in different image applications, use of the proposed model would allow a unified treatment of all practically meaningful variants of watermarking schemes

Using reflective writing and textual explanations to evaluate students' conceptual knowledge

BACKGROUND OR CONTEXT - Writing is one method used to prompt students to reflect on their own thought processes. Eliciting students’ explanations in the form of text, or writing, also provides lecturers with information about students’ thinking (Goncher, Boles, Jayalath, 2014; Boles, Goncher, Jayalath, 2015). Often in engineering courses, students adopt algorithmic problem-solving approaches without demonstrating conceptual reasoning. Adding a written, or explanatory component, to problems or questions is one approach that can elicit conceptual reasoning. PURPOSE OR GOAL - The purpose of this study was to identify and compare affordances of using students’ written explanations based the type of problem and response. This comparative study sought to answer two research questions, 1) How were the students’ textual answers different for the type of problem and requested explanations? and 2) What does the type and organization of the text of students’ explanations reveal about their conceptual knowledge? APPROACH - We analyzed students’ explanations for procedurally based problems in the statics discipline and conceptually based problems in the signal processing discipline. The first method used “process problems” that required students to explain, using only words, the process that they used to solve a statics homework problem. The second method utilized the Signals and Systems Concept Inventory items, and required students to provide a written explanation for their multiple-choice selection to each item. We categorized responses by the type of problem and structure of the written explanations to evaluate conceptual knowledge. DISCUSSION - We found that the structure of the text and type of problem provided different insights into students’ reasoning. The results showed that students approach learning in statics with varying emphasis placed on procedural and conceptual knowledge, and some students had difficulties explaining underlying concepts in signal processing and reverted to procedural explanations. Regardless of the type of problem, students that are able to get feedback on their thought processes can use the feedback to formatively evaluate their own understanding. RECOMMENDATIONS/IMPLICATIONS/CONCLUSION - Educators who incorporate or require students to reflect on their thinking through textual explanations can promote the revision of incorrect and/or inconsistent knowledge, leading to improved conceptual knowledge development. Assignments or activities that include more incidental writing will engage students in more freethinking and reflection (Essig et al., 2014;Hawkins, Coney, & Bystrom, 1996), and can lead to a richer understanding of technical concepts

A model for enhancing assessment and teaching practice at the coalface: Insights from a Fellow-In-Residence Engagement program

Australian universities are currently engaging with new governmental policies and regulations that require them to demonstrate enhanced quality and accountability in teaching and research. The development of national academic standards for learning outcomes in higher education is one such instance of this drive for excellence. These discipline-specific standards articulate the minimum, or Threshold Learning Outcomes, to be addressed by higher education institutions so that graduating students can demonstrate their achievement to their institutions, accreditation agencies, and industry recruiters. This impacts not only on the design of Engineering courses (with particular emphasis on pedagogy and assessment), but also on the preparation of academics to engage with these standards and implement them in their day-to-day teaching practice on a micro level. This imperative for enhanced quality and accountability in teaching is also significant at a meso level, for according to the Australian Bureau of Statistics, about 25 per cent of teachers in Australian universities are aged 55 and above and more than 54 per cent are aged 45 and above (ABS, 2006). A number of institutions have undertaken recruitment drives to regenerate and enrich their academic workforce by appointing capacity-building research professors and increasing the numbers of early- and mid-career academics. This nationally driven agenda for quality and accountability in teaching permeates also the micro level of engineering education, since the demand for enhanced academic standards and learning outcomes requires both a strong advocacy for a shift to an authentic, collaborative, outcomes-focused education and the mechanisms to support academics in transforming their professional thinking and practice. Outcomes-focused education means giving greater attention to the ways in which the curriculum design, pedagogy, assessment approaches and teaching activities can most effectively make a positive, verifiable difference to students’ learning. Such education is authentic when it is couched firmly in the realities of learning environments, student and academic staff characteristics, and trustworthy educational research. That education will be richer and more efficient when staff works collaboratively, contributing their knowledge, experience and skills to achieve learning outcomes based on agreed objectives. We know that the school or departmental levels of universities are the most effective loci of changes in approaches to teaching and learning practices in higher education (Knight & Trowler, 2000). Heads of Schools are being increasingly entrusted with more responsibilities - in addition to setting strategic directions and managing the operational and sometimes financial aspects of their school, they are also expected to lead the development and delivery of the teaching, research and other academic activities. Guiding and mentoring individuals and groups of academics is one critical aspect of the Head of School’s role. Yet they do not always have the resources or support to help them mentor staff, especially the more junior academics. In summary, the international trend in undergraduate engineering course accreditation towards the demonstration of attainment of graduate attributes poses new challenges in addressing academic staff development needs and the assessment of learning. This paper will give some insights into the conceptual design, implementation and empirical effectiveness to date, of a Fellow-In-Residence Engagement (FIRE) program. The program is proposed as a model for achieving better engagement of academics with contemporary issues and effectively enhancing their teaching and assessment practices. It will also report on the program’s collaborative approach to working with Heads of Schools to better support academics, especially early-career ones, by utilizing formal and informal mentoring. Further, the paper will discuss possible factors that may assist the achievement of the intended outcomes of such a model, and will examine its contributions to engendering an outcomes-focussed thinking in engineering education

Vibration Compensation for Fisheye Lenses in UAV Applications

Low-cost aerial vision systems need to face the challenges of using low quality products to perform aerial photography. Such systems are widely used in remote controlled aircrafts and unmanned aerial vehicles (UAVs) to collect aerial imagery and are used for image acquisition, terrain mapping or remote sensing. A one-pixel shift in a 0.8 mega pixel resolution image captured from a UAV operating at 1000ft will correspond to about 2.5m measurement error on the ground. In our case, a vibrating fisheye lens moving relative to the camera added new uncertainties in the collected images and required compensation. This paper presents a vibration compensation approach using a modified Hough Transform utilizing the circle shaped image provided by a fisheye lens. We define the fisheye circle boundary by using a Canny edge detector. Our vibration compensation was tested using our collected aerial images with enhanced performance in more than 80% of the cases

Vision-based Pirouettes using the Radial Obstacle Profile

Mapping algorithms commonly use "radial sweeps" of the surrounding environment as input. Producing a sweep is a challenging task for a robot using only vision. With no odometers to measure turn angles, a vision-based robot must have another method to verify rotations. In this paper we propose using the Radial Obstacle Profile (ROP) which gives the radial distance to the nearest obstacle in any direction in the robot’s field of view. By matching the ROPs before and after a turn, the robot should be able to verify that the expected angle of rotation matches the actual angle. Combining successive ROPs then produces a radial sweep