Efficient top-k retrieval with signatures

This paper describes a new method of indexing and searching large binary signature collections to efficiently find similar signatures, addressing the scalability problem in signature search. Signatures offer efficient computation with acceptable measure of similarity in numerous applications. However, performing a complete search with a given search argument (a signature) requires a Hamming distance calculation against every signature in the collection. This quickly becomes excessive when dealing with large collections, presenting issues of scalability that limit their applicability. Our method efficiently finds similar signatures in very large collections, trading memory use and precision for greatly improved search speed. Experimental results demonstrate that our approach is capable of finding a set of nearest signatures to a given search argument with a high degree of speed and fidelity.

Predicting fault-prone software modules with rank sum classification

The detection and correction of defects remains among the most time consuming and expensive aspects of software development. Extensive automated testing and code inspections may mitigate their effect, but some code fragments are necessarily more likely to be faulty than others, and automated identification of fault prone modules helps to focus testing and inspections, thus limiting wasted effort and potentially improving detection rates. However, software metrics data is often extremely noisy, with enormous imbalances in the size of the positive and negative classes. In this work, we present a new approach to predictive modelling of fault proneness in software modules, introducing a new feature representation to overcome some of these issues. This rank sum representation offers improved or at worst comparable performance to earlier approaches for standard data sets, and readily allows the user to choose an appropriate trade-off between precision and recall to optimise inspection effort to suit different testing environments. The method is evaluated using the NASA Metrics Data Program (MDP) data sets, and performance is compared with existing studies based on the Support Vector Machine (SVM) and Naïve Bayes (NB) Classifiers, and with our own comprehensive evaluation of these methods.

Genome-wide DNA methylation analysis of human brain tissue from schizophrenia patients

Recent studies suggest that genetic and environmental factors do not account for all the schizophrenia risk and epigenetics also plays a role in disease susceptibility. DNA methylation is a heritable epigenetic modification that can regulate gene expression. Genome-Wide DNA methylation analysis was performed on post-mortem human brain tissue from 24 patients with schizophrenia and 24 unaffected controls. DNA methylation was assessed at over 485 000 CpG sites using the Illumina Infinium Human Methylation450 Bead Chip. After adjusting for age and post-mortem interval (PMI), 4 641 probes corresponding to 2 929 unique genes were found to be differentially methylated. Of those genes, 1 291 were located in a CpG island and 817 were in a promoter region. These include NOS1, AKT1, DTNBP1, DNMT1, PPP3CC and SOX10 which have previously been associated with schizophrenia. More than 100 of these genes overlap with a previous DNA methylation study of peripheral blood from schizophrenia patients in which 27 000 CpG sites were analysed. Unsupervised clustering analysis of the top 3 000 most variable probes revealed two distinct groups with significantly more people with schizophrenia in cluster one compared to controls (p = 1.74x10-4). The first cluster was composed of 88% of patients with schizophrenia and only 12% controls while the second cluster was composed of 27% of patients with schizophrenia and 73% controls. These results strongly suggest that differential DNA methylation is important in schizophrenia etiology and add support for the use of DNA methylation profiles as a future prognostic indicator of schizophrenia.

Student focus and prioritization of design parameters in first-year engineering design projects

BACKGROUND Research on engineering design is a core area of concern within engineering education and a fundamental understanding of how engineering students approach and undertake design is necessary in order to develop effective design models and pedagogies. Understanding the factors related to design experiences in education and how they affect student practice can help educators as well as designers to leverage these factors as part of the design process. PURPOSE This study investigated the design practices of first-year engineering students’ and their experiences with a first-year engineering course design project. The research questions that guided the investigation were: 1. From a student perspective, what design parameters or criteria are most important? 2. How does this perspective impact subsequent student design practice throughout the design process? DESIGN/METHOD The authors employed qualitative multi-case study methods (Miles & Huberman, 1994) in order to the answer the research questions. Participant teams were observed and video recorded during team design meetings in which they researched the background for the design problem, brainstormed and sketched possible solutions, as well as built prototypes and final models of their design solutions as part of a course design project. Analysis focused on explanation building (Yin, 2009) and utilized within-case and cross-case analysis (Miles & Huberman, 1994). RESULTS We found that students focused disproportionally on the functional parameter, i.e. the physical implementation of their solution, and the possible/applicable parameter, i.e. a possible and applicable solution that benefited the user, in comparison to other given parameters such as safety and innovativeness. In addition, we found that individual teams focused on the functional and possible/ applicable parameters in early design phases such as brainstorming/ ideation and sketching. When prompted to discuss these non-salient parameters (from the student perspective) in the final design report, student design teams often used a post-hoc justification to support how the final designs fit the parameters that they did not initially consider. CONCLUSIONS This study suggests is that student design teams become fixated on (and consequently prioritize) certain parameters they interpret as important because they feel these parameters were described more explicitly in terms how they were met and assessed. Students fail to consider other parameters, perceived to be less directly assessable, unless prompted to do so. Failure to consider other parameters in the early design phases subsequently affects their approach in design phases as well. Case studies examining students’ study strategies within three Australian Universities illustrate similarities with some student approaches to design.

Social engineering in social networking sites : phase-based and source-based models

Social networking sites (SNSs), with their large numbers of users and large information base, seem to be perfect breeding grounds for exploiting the vulnerabilities of people, the weakest link in security. Deceiving, persuading, or influencing people to provide information or to perform an action that will benefit the attacker is known as “social engineering.” While technology-based security has been addressed by research and may be well understood, social engineering is more challenging to understand and manage, especially in new environments such as SNSs, owing to some factors of SNSs that reduce the ability of users to detect the attack and increase the ability of attackers to launch it. This work will contribute to the knowledge of social engineering by presenting the first two conceptual models of social engineering attacks in SNSs. Phase-based and source-based models are presented, along with an intensive and comprehensive overview of different aspects of social engineering threats in SNSs.

Social engineering in social networking sites : affect-based model

While social engineering represents a real and ominous threat to many organizations, companies, governments, and individuals, social networking sites (SNSs), have been identified as among the most common means of social engineering attacks. Owing to factors that reduce the ability of users to detect social engineering tricks and increase the ability of attackers to launch them, SNSs seem to be perfect breeding ground for exploiting the vulnerabilities of people, and the weakest link in security. This work will contribute to the knowledge of social engineering by identifying different entities and subentities that affect social engineering based attacks in SNSs. Moreover, this paper includes an intensive and comprehensive overview of different aspects of social engineering threats in SNSs.

Toward understanding social engineering

There is no doubt that social engineering plays a vital role in compromising most security defenses, and in attacks on people, organizations, companies, or even governments. It is the art of deceiving and tricking people to reveal critical information or to perform an action that benefits the attacker in some way. Fraudulent and deceptive people have been using social engineering traps and tactics using information technology such as e-mails, social networks, web sites, and applications to trick victims into obeying them, accepting threats, and falling victim to various crimes and attacks such as phishing, sexual abuse, financial abuse, identity theft, impersonation, physical crime, and many other forms of attack. Although organizations, researchers, practitioners, and lawyers recognize the severe risk of social engineering-based threats, there is a severe lack of understanding and controlling of such threats. One side of the problem is perhaps the unclear concept of social engineering as well as the complexity of understand human behaviors in behaving toward, approaching, accepting, and failing to recognize threats or the deception behind them. The aim of this paper is to explain the definition of social engineering based on the related theories of the many related disciplines such as psychology, sociology, information technology, marketing, and behaviourism. We hope, by this work, to help researchers, practitioners, lawyers, and other decision makers to get a fuller picture of social engineering and, therefore, to open new directions of collaboration toward detecting and controlling it.

Forming a joint venture project team for multi-discipline engineering services in Australia

Joint venture design teams are formed to combine resources and expertise in order to secure multi-discipline engineering design services on major projects. Bringing together resources from two ordinarily competing companies to form one joint team is however challenging as each parent company brings to the project its own organisational culture, processes and team attitudes. This study examined the factors that impact on forming a successful joint venture project team. Three critical areas were identified from an extensive literature review; Joint Venture Arrangements, Parent Companies and Forming the Team; and a survey was conducted with professionals who have worked in joint venture project teams in the Australian building industry in order to identify factors that affected successful joint venture team formation, and the common lessons learnt. This study reinforced the importance of three key criteria - trust, commitment and compatibility - for partner alignment. The results also identified four key lessons learnt which included; selecting the right resources, enabling a collaborative working environment by way of project office, implementing an independent Joint Venture Manager, and allocating work which is best for project with fees reflecting risk where risk is disproportionate.

Error modeling and calibration of exteroceptive sensors for accurate mapping applications

Reliable robotic perception and planning are critical to performing autonomous actions in uncertain, unstructured environments. In field robotic systems, automation is achieved by interpreting exteroceptive sensor information to infer something about the world. This is then mapped to provide a consistent spatial context, so that actions can be planned around the predicted future interaction of the robot and the world. The whole system is as reliable as the weakest link in this chain. In this paper, the term mapping is used broadly to describe the transformation of range-based exteroceptive sensor data (such as LIDAR or stereo vision) to a fixed navigation frame, so that it can be used to form an internal representation of the environment. The coordinate transformation from the sensor frame to the navigation frame is analyzed to produce a spatial error model that captures the dominant geometric and temporal sources of mapping error. This allows the mapping accuracy to be calculated at run time. A generic extrinsic calibration method for exteroceptive range-based sensors is then presented to determine the sensor location and orientation. This allows systematic errors in individual sensors to be minimized, and when multiple sensors are used, it minimizes the systematic contradiction between them to enable reliable multisensor data fusion. The mathematical derivations at the core of this model are not particularly novel or complicated, but the rigorous analysis and application to field robotics seems to be largely absent from the literature to date. The techniques in this paper are simple to implement, and they offer a significant improvement to the accuracy, precision, and integrity of mapped information. Consequently, they should be employed whenever maps are formed from range-based exteroceptive sensor data. © 2009 Wiley Periodicals, Inc.

Genome stability pathways in head and neck cancers

Genomic instability underlies the transformation of host cells toward malignancy, promotes development of invasion and metastasis and shapes the response of established cancer to treatment. In this review, we discuss recent advances in our understanding of genomic stability in squamous cell carcinoma of the head and neck (HNSCC), with an emphasis on DNA repair pathways. HNSCC is characterized by distinct profiles in genome stability between similarly staged cancers that are reflected in risk, treatment response and outcomes. Defective DNA repair generates chromosomal derangement that can cause subsequent alterations in gene expression, and is a hallmark of progression toward carcinoma. Variable functionality of an increasing spectrum of repair gene polymorphisms is associated with increased cancer risk, while aetiological factors such as human papillomavirus, tobacco and alcohol induce significantly different behaviour in induced malignancy, underpinned by differences in genomic stability. Targeted inhibition of signalling receptors has proven to be a clinically-validated therapy, and protein expression of other DNA repair and signalling molecules associated with cancer behaviour could potentially provide a more refined clinical model for prognosis and treatment prediction. Development and expansion of current genomic stability models is furthering our understanding of HNSCC pathophysiology and uncovering new, promising treatment strategies. © 2013 Glenn Jenkins et al.

Strain engineering of selective chemical adsorption on monolayer MoS2

Nanomaterials are prone to influence by chemical adsorption because of their large surface to volume ratios. This enables sensitive detection of adsorbed chemical species which, in turn, can tune the property of the host material. Recent studies discovered that single and multi-layer molybdenum disulfide (MoS2) films are ultra-sensitive to several important environmental molecules. Here we report new findings from ab inito calculations that reveal substantially enhanced adsorption of NO and NH3 on strained monolayer MoS2 with significant impact on the properties of the adsorbates and the MoS2 layer. The magnetic moment of adsorbed NO can be tuned between 0 and 1 μB; strain also induces an electronic phase transition between half-metal and metal. Adsorption of NH3 weakens the MoS2 layer considerably, which explains the large discrepancy between the experimentally measured strength and breaking strain of MoS2 films and previous theoretical predictions. On the other hand, adsorption of NO2, CO, and CO2 is insensitive to the strain condition in the MoS2 layer. This contrasting behavior allows sensitive strain engineering of selective chemical adsorption on MoS2 with effective tuning of mechanical, electronic, and magnetic properties. These results suggest new design strategies for constructing MoS2-based ultrahigh-sensitivity nanoscale sensors and electromechanical devices.

Critical success factors for the implementation of a knowledge management system in a knowledge-based engineering firm

This research identifies factors that are crucial to the success of a knowledge management system (KMS) implementation in a prominent Australian engineering consultancy firm. The study employs the Delphi method to solicit the opinions of experienced market leaders in the Australian construction industry, and then benchmarks the organisational profile of the consultancy firm against the Delphi findings. From this comparative case study, recommendations are made pertaining to the organisational and cultural changes required within the consultancy firm in order to improve its readiness to successfully implement a KMS.

Starting out in STEM : a study of young men and women in first year science, technology, engineering and mathematics courses

In late 2011, first year university students in science, technology, engineering and mathematics (STEM) courses across Australia were invited to participate in the international Interests and Recruitment in Science (IRIS) study. IRIS investigates the influences on young people's decisions to choose university STEM courses and their subsequent experiences of these courses. The study also has a particular focus on the motivations and experiences of young women in courses such as physics, IT and engineering given the low rates of female participation in these fields. Around 3500 students from 30 Australian universities contributed their views on the relative importance of various school and non-school influences on their decisions, as well as insights into their experiences of university STEM courses so far. It is hoped that their contributions will help improve recruitment, retention and gender equity in STEM higher education and careers.

Digital tablets as a tool for blended learning in power engineering education

Digital tablets have been identified as a tool for enabling blended learning and supporting online teaching and learning. A small scale trial was undertaken to assess the effectiveness of this technology when applied to power engineering education. Critical findings and experiences gained from this trial, including potential benefits, presentation techniques and the resulting student feedback are presented in this paper.

An exploration of the professional competencies required in engineering asset management

Engineering asset management (EAM) is a rapidly growing and developing field. However, efforts to select and develop engineers in this area are complicated by our lack of understanding of the full range of competencies required to perform. This exploratory study sought to clarify and categorise the professional competencies required of individuals at different hierarchical levels within EAM. Data from 14 field interviews, 61 online surveys, and 10 expert panel interviews were used to develop an initial professional competency framework. Overall, nine competency clusters were identified. These clusters indicate that engineers working in this field need to be able to collaborate and influence others, complete objectives within organisational guidelines, and be able to manage themselves effectively. Limitations and potential uses of this framework in engineering education and research are discussed.