Querying a building information model for construction-specific spatial information

The design and construction community has shown increasing interest in adopting building information models (BIMs). The richness of information provided by BIMs has the potential to streamline the design and construction processes by enabling enhanced communication, coordination, automation and analysis. However, there are many challenges in extracting construction-specific information out of BIMs. In most cases, construction practitioners have to manually identify the required information, which is inefficient and prone to error, particularly for complex, large-scale projects. This paper describes the process and methods we have formalized to partially automate the extraction and querying of construction-specific information from a BIM. We describe methods for analyzing a BIM to query for spatial information that is relevant for construction practitioners, and that is typically represented implicitly in a BIM. Our approach integrates ifcXML data and other spatial data to develop a richer model for construction users. We employ custom 2D topological XQuery predicates to answer a variety of spatial queries. The validation results demonstrate that this approach provides a richer representation of construction-specific information compared to existing BIM tools.

Higher degree research at Australian Universities : Responding to diversity in engineering and information technology

BACKGROUND There is increasing enrolment of international students in the Engineering and Information Technology disciplines and anecdotal evidence of a need for additional understanding and support for these students and their supervisors due to differences both in academic and social cultures. While there is a growing literature on supervisory styles and guidelines on effective supervision, there is little on discipline-specific, cross-cultural supervision responding to the growing diversity. In this paper, we report findings from a study of Engineering and Information technology Higher Degree Research (HDR)students and supervision in three Australian universities. PURPOSE The aim was to assess perceptions of students and supervisors of factors influencing success that are particular to international or culturally and linguistically diverse (CaLD) HDR students in Engineering and Information technology. DESIGN/METHOD Online survey and qualitative data was collected from international and CaLD HDR students and supervisors at the three universities. Bayesian network analysis, inferential statistics, and qualitative analysis provided the main findings. RESULTS Survey results indicate that both students and supervisors are positive about their experiences, and do not see language or culture as particularly problematic. The survey results also reveal strong consistency between the perceptions of students and supervisors on most factors influencing success. Qualitative analysis of critical supervision incidents has provided rich data that could help improve support services. CONCLUSIONS In contrast with anecdotal evidence, HDR completion data from the three universities reveal that international students, on average, complete in shorter time periods than domestic students. The analysis suggests that success is linked to a complex set of factors involving the student, supervision, the institution and broader community.

Collaborating to develop research data management services and collections

The Queensland University of Technology (QUT) Library, like many other academic and research institution libraries in Australia, has been collaborating with a range of academic and service provider partners to develop a range of research data management services and collections. Three main strategies are being employed and an overview of process, infrastructure, usage and benefits is provided of each of these service aspects. The development of processes and infrastructure to facilitate the strategic identification and management of QUT developed datasets has been a major focus. A number of Australian National Data Service (ANDS) sponsored projects - including Seeding the Commons; Metadata Hub / Store; Data Capture and Gold Standard Record Exemplars have / will provide QUT with a data registry system, linkages to storage, processes for identifying and describing datasets, and a degree of academic awareness. QUT supports open access and has established a culture for making its research outputs available via the QUT ePrints institutional repository. Incorporating open access research datasets into the library collections is an equally important aspect of facilitating the adoption of data-centric eresearch methods. Some datasets are available commercially, and the library has collaborated with QUT researchers, in the QUT Business School especially strongly, to identify and procure a rapidly growing range of financial datasets to support research. The library undertakes licensing and uses the Library Resource Allocation to pay for the subscriptions. It is a new area of collection development for with much to be learned. The final strategy discussed is the library acting as “data broker”. QUT Library has been working with researchers to identify these datasets and undertake the licensing, payment and access as a centrally supported service on behalf of researchers.

Media and information literacy at Queensland University of Technology and in Australia

Media and Information Literacy is the focus of several teaching and research projects at Queensland University of Technology and there is particular emphasis placed on digital technologies and how they are used for communication, information use and learning in formal contexts such as schools. Research projects are currently taking place in several locations where investigators are collecting data on approaches to the use of digital media tools like cameras and editing systems, tablet computers and video games. This complements QUT’s teacher preparation courses, including preparation to implement UNESCO’s Online Course in Media and Information Literacy and Intercultural Dialogue in 2013. This work takes place in the context of projects occurring at the National level in Australia that continue to promote Media and Information Literacy.

Developing a dashboard for real-time data stream composition and visualization

Technological advances have led to an influx of affordable hardware that supports sensing, computation and communication. This hardware is increasingly deployed in public and private spaces, tracking and aggregating a wealth of real-time environmental data. Although these technologies are the focus of several research areas, there is a lack of research dealing with the problem of making these capabilities accessible to everyday users. This thesis represents a first step towards developing systems that will allow users to leverage the available infrastructure and create custom tailored solutions. It explores how this notion can be utilized in the context of energy monitoring to improve conventional approaches. The project adopted a user-centered design process to inform the development of a flexible system for real-time data stream composition and visualization. This system features an extensible architecture and defines a unified API for heterogeneous data streams. Rather than displaying the data in a predetermined fashion, it makes this information available as building blocks that can be combined and shared. It is based on the insight that individual users have diverse information needs and presentation preferences. Therefore, it allows users to compose rich information displays, incorporating personally relevant data from an extensive information ecosystem. The prototype was evaluated in an exploratory study to observe its natural use in a real-world setting, gathering empirical usage statistics and conducting semi-structured interviews. The results show that a high degree of customization does not warrant sustained usage. Other factors were identified, yielding recommendations for increasing the impact on energy consumption.

'Explain in plain English' questions revisited : data structures problems

Recent studies have linked the ability of novice (CS1) programmers to read and explain code with their ability to write code. This study extends earlier work by asking CS2 students to explain object-oriented data structures problems that involve recursion. Results show a strong correlation between ability to explain code at an abstract level and performance on code writing and code reading test problems for these object-oriented data structures problems. The authors postulate that there is a common set of skills concerned with reasoning about programs that explains the correlation between writing code and explaining code. The authors suggest that an overly exclusive emphasis on code writing may be detrimental to learning to program. Non-code writing learning activities (e.g., reading and explaining code) are likely to improve student ability to reason about code and, by extension, improve student ability to write code. A judicious mix of code-writing and code-reading activities is recommended.

Cryptology and network security

This book constitutes the refereed proceedings of the 11th International Conference on Cryptology and Network Security, CANS 2012, held in Darmstadt, Germany, in December 2012. The 22 revised full papers, presented were carefully reviewed and selected from 99 submissions. The papers are organized in topical sections on cryptanalysis; network security; cryptographic protocols; encryption; and s-box theory.

Untangling the evidence : introducing an empirical model for evidence-based library and information practice

Introduction This research is the first to investigate the experiences of teacher-librarians as evidence-based practice. An empirically derived model is presented in this paper. Method This qualitative study utilised the expanded critical incident approach, and investigated the real-life experiences of fifteen Australian teacher-librarians, through semi-structured interviews and inductive data analysis. Data collection utilised semi-structured interviews, on-site observations, journaling and the rubric for contextual information. These approaches allowed each of the interviewees to tell their own story and provided richness to the data. Analysis The analysis involved two types of data categorisation: binary and thematic. Binary classification was used to identify factual details. Thematic analysis involved categorising the emerging themes. Results An empirically derived model for evidence-based practice was devised and associated critical findings identified. The results demonstrate that evidence-based practice for teacher-librarians is a holistic practice. It is not a linear, step-by-step process. Conclusions This study is significant for teacher-librarians and library and information professionals as it provides new understanding of evidence-based practice.

Anomaly detection in online social networks : using data-mining techniques and fuzzy logic

This research is a step forward in improving the accuracy of detecting anomaly in a data graph representing connectivity between people in an online social network. The proposed hybrid methods are based on fuzzy machine learning techniques utilising different types of structural input features. The methods are presented within a multi-layered framework which provides the full requirements needed for finding anomalies in data graphs generated from online social networks, including data modelling and analysis, labelling, and evaluation.

Low probability differentials and the cryptanalysis of full-round CLEFIA-128

So far, low probability differentials for the key schedule of block ciphers have been used as a straightforward proof of security against related-key differential analysis. To achieve resistance, it is believed that for cipher with k-bit key it suffices the upper bound on the probability to be 2− k . Surprisingly, we show that this reasonable assumption is incorrect, and the probability should be (much) lower than 2− k . Our counter example is a related-key differential analysis of the well established block cipher CLEFIA-128. We show that although the key schedule of CLEFIA-128 prevents differentials with a probability higher than 2− 128, the linear part of the key schedule that produces the round keys, and the Feistel structure of the cipher, allow to exploit particularly chosen differentials with a probability as low as 2− 128. CLEFIA-128 has 214 such differentials, which translate to 214 pairs of weak keys. The probability of each differential is too low, but the weak keys have a special structure which allows with a divide-and-conquer approach to gain an advantage of 27 over generic analysis. We exploit the advantage and give a membership test for the weak-key class and provide analysis of the hashing modes. The proposed analysis has been tested with computer experiments on small-scale variants of CLEFIA-128. Our results do not threaten the practical use of CLEFIA.

Indonesian library and information science professionals’ understanding of Library 2.0: A pilot study

The literature around Library 2.0 remains largely theoretical with few empirical studies and is particularly limited in developing countries such as Indonesia. This study addresses this gap and aims to provide information about the current state of knowledge on Indonesian LIS professionals’ understanding of Library 2.0. The researchers used qualitative and quantitative approaches for this study, asking thirteen closed- and open-ended questions in an online survey. The researchers used descriptive and in vivo coding to analyze the responses. Through their analysis, they identified three themes: technology, interactivity, and awareness of Library 2.0. Respondents demonstrated awareness of Library 2.0 and a basic understanding of the roles of interactivity and technology in libraries. However, overreliance on technology used in libraries to conceptualize Library 2.0 without an emphasis on its core characteristics and principles could lead to the misalignment of limited resources. The study results will potentially strengthen the research base for Library 2.0 practice as well as inform LIS curriculum in Indonesia so as to develop practitioners who are able to adapt to users’ changing needs and expectations. It is expected that the preliminary data from this study could be used to design a much larger and more complex future research project in this area.

Secondary attribute retrieval using tree data structures

Several techniques are known for searching an ordered collection of data. The techniques and analyses of retrieval methods based on primary attributes are straightforward. Retrieval using secondary attributes depends on several factors. For secondary attribute retrieval, the linear structures—inverted lists, multilists, doubly linked lists—and the recently proposed nonlinear tree structures—multiple attribute tree (MAT), K-d tree (kdT)—have their individual merits. It is shown in this paper that, of the two tree structures, MAT possesses several features of a systematic data structure for external file organisation which make it superior to kdT. Analytic estimates for the complexity of node searchers, in MAT and kdT for several types of queries, are developed and compared.

Interval Data Classification under Partial Information: A Chance-Constraint Approach

This paper presents a Chance-constraint Programming approach for constructing maximum-margin classifiers which are robust to interval-valued uncertainty in training examples. The methodology ensures that uncertain examples are classified correctly with high probability by employing chance-constraints. The main contribution of the paper is to pose the resultant optimization problem as a Second Order Cone Program by using large deviation inequalities, due to Bernstein. Apart from support and mean of the uncertain examples these Bernstein based relaxations make no further assumptions on the underlying uncertainty. Classifiers built using the proposed approach are less conservative, yield higher margins and hence are expected to generalize better than existing methods. Experimental results on synthetic and real-world datasets show that the proposed classifiers are better equipped to handle interval-valued uncertainty than state-of-the-art.

A network forensics tool for precise data packet capture and replay in cyber-physical systems

Network data packet capture and replay capabilities are basic requirements for forensic analysis of faults and security-related anomalies, as well as for testing and development. Cyber-physical networks, in which data packets are used to monitor and control physical devices, must operate within strict timing constraints, in order to match the hardware devices' characteristics. Standard network monitoring tools are unsuitable for such systems because they cannot guarantee to capture all data packets, may introduce their own traffic into the network, and cannot reliably reproduce the original timing of data packets. Here we present a high-speed network forensics tool specifically designed for capturing and replaying data traffic in Supervisory Control and Data Acquisition systems. Unlike general-purpose "packet capture" tools it does not affect the observed network's data traffic and guarantees that the original packet ordering is preserved. Most importantly, it allows replay of network traffic precisely matching its original timing. The tool was implemented by developing novel user interface and back-end software for a special-purpose network interface card. Experimental results show a clear improvement in data capture and replay capabilities over standard network monitoring methods and general-purpose forensics solutions.

The effects of community attachment and information seeking on displaced disaster victims’ decision making

This paper uses original survey data of the Great East Japan earthquake disaster victims to examine their decision to apply for the temporary housing as well as the timing of application. We assess the effects of victims’ attachment to their locality as well as variation in victims’ information seeking behavior. We additionally consider various factors such as income, age, employment and family structure that are generally considered to affect the decision to choose temporary housing as victims’ solution for their displacement. Empirical results indicate that, ceteris paribus, as the degree of attachment increases, victims are more likely to apply for the temporary housing but attachment does not affect the timing of application. On the other hand, the victims who actively seek information and are able to collect higher quality information are less likely to apply for the temporary housing and if they do apply then they apply relatively later.