Reflecting on our own learning: incorporating diverse worldviews into teaching and learning activities.

CONTEXT The teacher’s experience is frequently overlooked as a source of useful data on teaching practice. Nelson (2003, p. 85) points out that “every class is potentially an experiment from which the data are either discarded or never gathered.” This paper presents two academics’ reflections on the impact of their training in te reo Maori and tikanga Maori on their teaching activities. PURPOSE To reflect on academics’ learning of Maori language and culture in order to design teaching and learning activities that incorporate Maori language and the Maori worldview. APPROACH The paper uses three of Brookfield’s (1998) four lenses of reflection on teaching practice. RESULTS The first academic considered it was important to enable students to adequately explore the worldviews of the diverse stakeholders they will design products for in future and to test students on their understanding of these in order to satisfy cultural aspects of the graduate profile outcomes. The second academic found benefits of the use of Maori language in class in creating an atmosphere reflective of the principles of the Treaty of Waitangi. Each academic found something to learn from the other’s work. CONCLUSIONS Adding the Maori language and worldview enables the classroom to better reflect New Zealand’s bi-cultural environment and student projects to better meet the needs of diverse stakeholder groups, and also explicitly addresses the cultural aspects of the graduate profile

FS^3: A Sampling based method for top-k Frequent Subgraph Mining

Mining labeled subgraph is a popular research task in data mining because of its potential application in many different scientific domains. All the existing methods for this task explicitly or implicitly solve the subgraph isomorphism task which is computationally expensive, so they suffer from the lack of scalability problem when the graphs in the input database are large. In this work, we propose FS^3, which is a sampling based method. It mines a small collection of subgraphs that are most frequent in the probabilistic sense. FS^3 performs a Markov Chain Monte Carlo (MCMC) sampling over the space of a fixed-size subgraphs such that the potentially frequent subgraphs are sampled more often. Besides, FS^3 is equipped with an innovative queue manager. It stores the sampled subgraph in a finite queue over the course of mining in such a manner that the top-k positions in the queue contain the most frequent subgraphs. Our experiments on database of large graphs show that FS^3 is efficient, and it obtains subgraphs that are the most frequent amongst the subgraphs of a given size

Engineers for the future; accounting for diversity

tailoring engineering and STEM education to meet the needs of all stakeholders. (External Industry requirement) a. Educational institutions must consider an increasingly diverse group of stakeholders, including students, staff, industry, and the wider community. How can educational activities expand our horizons beyond classroom and industry experience

High capacity steganographic method based upon JPEG

The two most important aspects of any image-based steganographic system are the quality of the stegoimage and the capacity of the cover image. This paper proposes a novel and high capacity steganographic approach based on Discrete Cosine Transformation (DCT) and JPEG compression. JPEG technique divides the input image into non-overlapping blocks of 8x8 pixels and uses the DCT transformation. However, our proposed method divides the cover image into nonoverlapping blocks of 16x16 pixels. For each quantized DCT block, the least two-significant bits (2-LSBs) of each middle frequency coefficient are modified to embed two secret bits. Our aim is to investigate the data hiding efficiency using larger blocks for JPEG compression. Our experiment result shows that the proposed approach can provide a higher information hiding capacity than Jpeg-Jsteg and Chang et al. methods based on the conventional blocks of 8x8 pixels. Furthermore, the produced stego-images are almost identical to the original cover images

Optimum design of composite prestressed concrete girder railway bridges

This paper deals with the formulation of design optimisation of pretsressed concrete bridges. The bridge is of a slab-on-girder type, hence modeled as an equivalent orthotropic plate. The whole bridge system is considered as a simply supported right angle plate. Following linear elastic behaviour, the governing fourth order differential equation of the plate for patch load is solved in order to find out load distribution on the girders forming the bridge as well as the deflections and internal forces at critical sections of the whole bridge. The optimisation problem is formulated for various cross sectional geometries including rectangular, symmetrical I, unsymmetrical I, box, T and inverted T sections. The design variables are the main cross sectional dimensions, prestressing force and tendon eccentricity. The objective function comprises the cost of concrete material, formwork and prestressing steel tendons. The constraint functions are set to satisfy design requirements as per British Standards for bridges (BS 5400). Nonlinear optimisation method based on sequential unconstrained minimisation technique (SUMT) is employed to achieve optimum bridge configuration for specific design parameters of span length, concrete compressive strength and railway loading patterns. A purpose built computer program is set up to carry out the solution of the design optimisation problem efficiently in terms of time and effort. A typical example of unsymmetrical I-section having a small bottom flange as compared to the top flange width with composite deck effect is presented. The results show that the total cost increases as the span increases due to the increase of the initial prestressing force. Furthermore, the total cost decreases as the concrete compressive strength increases in spite of the increasing of the prestressing force. This is due to decrease of the overall depth, top and bottom flange widths, hence leading to a smaller girder size. Such finding will encourage engineers to adopt high strength concrete for bridges as it will help reducing not only the initial cost but also the life cycle cost of the bridge over its entire life

Name Disambiguation from link data in a collaboration graph using temporal and topological features

In a social community, multiple persons may share the same name, phone number or some other identifying attributes. This, along with other phenomena, such as name abbreviation, name misspelling, and human error leads to erroneous aggregation of records of multiple persons under a single reference. Such mistakes affect the performance of document retrieval, web search, database integration, and more importantly, improper attribution of credit (or blame). The task of entity disambiguation partitions the records belonging to multiple persons with the objective that each decomposed partition is composed of records of a unique person. Existing solutions to this task use either biographical attributes, or auxiliary features that are collected from external sources, such as Wikipedia. However, for many scenarios, such auxiliary features are not available, or they are costly to obtain. Besides, the attempt of collecting biographical or external data sustains the risk of privacy violation. In this work, we propose a method for solving entity disambiguation task from link information obtained from a collaboration network. Our method is non-intrusive of privacy as it uses only the time-stamped graph topology of an anonymized network. Experimental results on two real-life academic collaboration networks show that the proposed method has satisfactory performance.Comment: The short version of this paper has been accepted to ASONAM 201

Incremental eigenpair computation for graph Laplacian matrices: theory and applications

The smallest eigenvalues and the associated eigenvectors (i.e., eigenpairs) of a graph Laplacian matrix have been widely used for spectral clustering and community detection. However, in real-life applications, the number of clusters or communities (say, K) is generally unknown a priori. Consequently, the majority of the existing methods either choose K heuristically or they repeat the clustering method with different choices of K and accept the best clustering result. The first option, more often, yields suboptimal result, while the second option is computationally expensive. In this work, we propose an incremental method for constructing the eigenspectrum of the graph Laplacian matrix. This method leverages the eigenstructure of graph Laplacian matrix to obtain the Kth smallest eigenpair of the Laplacian matrix given a collection of all previously compute