Granule mining and its application for network traffic characterization

Decision table and decision rules play an important role in rough set based data analysis, which compress databases into granules and describe the associations between granules. Granule mining was also proposed to interpret decision rules in terms of association rules and multi-tier structure. In this paper, we further extend granule mining to describe the relationships between granules not only by traditional support and confidence, but by diversity and condition diversity as well. Diversity measures how diverse of a granule associated with the other ganules, it provides a kind of novel knowledge in databases. Some experiments are conducted to test the proposed new concepts for describing the characteristics of a real network traffic data collection. The results show that the proposed concepts are promising.

Fire Tests of Cold-formed Steel Wall Systems

Cold-formed steel stud walls are an important component of Light Steel Framing (LSF) building systems used in commercial, industrial and residential buildings. In the conventional LSF stud wall systems, thin-walled steel studs are protected from fire by placing one or two layers of plasterboard on both sides with or without cavity insulation. However, there is very limited data about the structural and thermal performance of these wall systems while past research showed contradicting results about the benefits of cavity insulation. This research proposed a new LSF stud wall system in which a composite panel made of two plasterboards with insulation between them was used to improve the fire rating of walls. Full scale fire tests were conducted using both conventional steel stud walls with and without the use of cavity insulation and the new composite panel system. Eleven full scale load bearing wall specimens were tested to study the thermal and structural performances of the load bearing wall assemblies under standard fire conditions. These tests showed that the use of cavity insulation led to inferior fire performance of walls while also providing good explanations and supporting test data to overcome the incorrect industry assumptions about cavity insulation. Tests demonstrated that the use of external insulation in a composite panel form enhanced the thermal and structural performances of stud walls and increased their fire resistance rating significantly. This paper presents the details of the full scale fire tests of load-bearing wall assemblies lined with plasterboards and different types of insulation under varying load ratios. Test results including the temperature and deflection profiles of walls measured during the fire tests will be presented along with their failure modes and failure times.

Using management objectives to specify management information systems : a contribution to MIS success

Data warehouse projects, today, are in an ambivalent situation. On the one hand, data warehouses are critical for a company’s success and various methodological and technological tools are sophisticatedly developed to implement them. On the other hand, a significant amount of data warehouse projects fails due to non-technical reasons such as insufficient management support or in-corporative employees. But management support and user participation can be increased dramatically with specification methods that are understandable to these user groups. This paper aims at overcoming possible non-technical failure reasons by introducing a user-adequate specification approach within the field of management information systems.

Experimental study of load bearing cold-formed steel wall systems under fire conditions

Light Gauge Steel Framing (LSF) walls made of cold-formed and thin-walled steel lipped channel studs with plasterboard linings on both sides are commonly used in commercial, industrial and residential buildings. However, there is limited data about their structural and thermal performance under fire conditions while past research showed contradicting results about the benefits of using cavity insulation. A new composite wall panel was recently proposed to improve the fire resistance rating of LSF walls, where an insulation layer was used externally between the plasterboards on both sides of the wall frame instead of using it in the cavity. In this research 11 full scale tests were conducted on conventional load bearing steel stud walls with and without cavity insulation, and the new composite panel system to study their thermal and structural performance under standard fire conditions. These tests showed that the use of cavity insulation led to inferior fire performance of walls, and provided supporting research data. They demonstrated that the use of insulation externally in a composite panel enhanced the thermal and structural performance of LSF walls and increased their fire resistance rating. This paper presents the details of the LSF wall tests and the thermal and structural performance data and fire resistance rating of load-bearing wall assemblies lined with varying plasterboard-insulation configurations under two different load ratios. Fire test results including the time–temperature and deflection profiles are presented along with the failure times and modes.

Professional development on-site and in context at Narangba Valley SHS

The implementation of the National Professional Standards for Teachers (Australian Institute for Teaching and School Leadership (AITSL), 2011) will require all teachers to undertake 30 hours per year of professional development (PD) to maintain thei registration. However, defining what constitutes effective PD s complex. This article discusses an approach used by Narangba Valley State High School (SHS) in Queensland which involves effective on-site PD, resulting in improved student outcomes. In addition to the school-administered growth and learning (GAL) plans for each teacher, the school worked collaboratively with an external person (university lecturer) and implemented an effective, sustainable, whole-school approach to PD which was ongoing, on time, on task, on the mark, and on-the-spot (Jetnikoff & Smeed, 2012). The article unpacks an interview with Ross Mackay, the Narangba Valley SHS executive-principal and one of the authors of this paper, and provides practical advice for other school leaders wishing to implement a similar approach to PD.

Computer security incidents against Australian businesses : predictors of victimisation

Drawing on data from the Australian Business Assessment of Computer User Security (ABACUS) survey, this paper examines a range of factors that may influence businesses’ likelihood of being victimised by a computer security incident. It has been suggested that factors including business size, industry sector, level of outsourcing, expenditure on computer security functions and types of computer security tools and/or policies used may influence the probability of particular businesses experiencing such incidents. This paper uses probability modelling to test whether this is the case for the 4,000 businesses that responded to the ABACUS survey. It was found that the industry sector that a business belonged to, and business expenditure on computer security, were not related to businesses’ likelihood of detecting computer security incidents. Instead, the number of employees that a business has and whether computer security functions were outsourced were found to be key indicators of businesses’ likelihood of detecting incidents. Some of the implications of these findings are considered in this paper.

On managing information technology capabilities

Information technology (IT) plays a critical role of enabler of activities that improve the performance of business processes. This enabling role of IT resources means continuous investment in IT is a strategic necessity. It is established that organizations’ IT-related capabilities leverage the enabling potential of IT resources. Today’s turbulent and challenging business environment requires organizations to do more from their existing and newly acquired IT resources. To achieve this, organizations need to discover ways or establish environments to nourish their existing IT-related capabilities, and develop new IT-related capabilities. We suggest one such environment, a dynamic IT-learning environment that could contribute to nourishing existing IT-related capabilities, and developing new IT-related capabilities. This environment is a product of coordination of four organizational factors that relate to the ways in which IT-related knowledge is applied to business processes, the accompanying reward structures, and ways in which the IT-related learning and knowledge is shared within the organization. Using 216 field survey responses, this paper shows that two IT-related capabilities of top management commitment to IT initiatives, and shared organizational knowledge between the IT and business unit managers has a stronger positive influence on business process performance in the presence of this dynamic IT-learning environment. The study also shows that a marginal IT-related capability, technical IT skills, has a positive and significant influence on business process performance in the presence of this environment. These outcomes imply that organizations’ internal environments could contribute to the management of their IT-related capabilities.

Predicting freeway pavement construction cost using a back-propagation neural network : a case study in Henan, China

The objective of this research was to develop a model to estimate future freeway pavement construction costs in Henan Province, China. A comprehensive set of factors contributing to the cost of freeway pavement construction were included in the model formulation. These factors comprehensively reflect the characteristics of region and topography and altitude variation, the cost of labour, material, and equipment, and time-related variables such as index numbers of labour prices, material prices and equipment prices. An Artificial Neural Network model using the Back-Propagation learning algorithm was developed to estimate the cost of freeway pavement construction. A total of 88 valid freeway cases were obtained from freeway construction projects let by the Henan Transportation Department during the period 1994−2007. Data from a random selection of 81 freeway cases were used to train the Neural Network model and the remaining data were used to test the performance of the Neural Network model. The tested model was used to predict freeway pavement construction costs in 2010 based on predictions of input values. In addition, this paper provides a suggested correction for the prediction of the value for the future freeway pavement construction costs. Since the change in future freeway pavement construction cost is affected by many factors, the predictions obtained by the proposed method, and therefore the model, will need to be tested once actual data are obtained.

Kalman filtering for positioning and heading control of ships and offshore rigs

In this article, we have described the main components of a ship motion-control system and two particular motion-control problems that require wave filtering, namely, dynamic positioning and heading autopilot. Then, we discussed the models commonly used for vessel response and showed how these models are used for Kalman filter design. We also briefly discussed parameter and noise covariance estimation, which are used for filter tuning. To illustrate the performance, a case study based on numerical simulations for a ship autopilot was considered. The material discussed in this article conforms to modern commercially available ship motion-control systems. Most of the vessels operating in the offshore industry worldwide use Kalman filters for velocity estimation and wave filtering. Thus, the article provides an up-to-date tutorial and overview of Kalman-filter-based wave filtering.

Classifying natural aerial scenery for autonomous aircraft emergency landing

In this paper, we present an approach for image-based surface classification using multi-class Support Vector Machine (SVM). Classifying surfaces in aerial images is an important step towards an increased aircraft autonomy in emergency landing situations. We design a one-vs-all SVM classifier and conduct experiments on five data sets. Results demonstrate consistent overall performance figures over 88% and approximately 8% more accurate to those published on multi-class SVM on the KTH TIPS data set. We also show per-class performance values by using normalised confusion matrices. Our approach is designed to be executed online using a minimum set of feature attributes representing a feasible and ready-to-deploy system for onboard execution.

Exploring cognitive style and task-specific preferences for process representations

Process models describe someone’s understanding of processes. Processes can be described using unstructured, semi-formal or diagrammatic representation forms. These representations are used in a variety of task settings, ranging from understanding processes to executing or improving processes, with the implicit assumption that the chosen representation form will be appropriate for all task settings. We explore the validity of this assumption by examining empirically the preference for different process representation forms depending on the task setting and cognitive style of the user. Based on data collected from 120 business school students, we show that preferences for process representation formats vary dependent on application purpose and cognitive styles of the participants. However, users consistently prefer diagrams over other representation formats. Our research informs a broader research agenda on task-specific applications of process modeling. We offer several recommendations for further research in this area.

Improving out-domain PLDA speaker verification using unsupervised inter-dataset variability compensation approach

Experimental studies have found that when the state-of-the-art probabilistic linear discriminant analysis (PLDA) speaker verification systems are trained using out-domain data, it significantly affects speaker verification performance due to the mismatch between development data and evaluation data. To overcome this problem we propose a novel unsupervised inter dataset variability (IDV) compensation approach to compensate the dataset mismatch. IDV-compensated PLDA system achieves over 10% relative improvement in EER values over out-domain PLDA system by effectively compensating the mismatch between in-domain and out-domain data.

Reliability control of GNSS carrier-phase integer ambiguity resolution

This research investigates how to obtain accurate and reliable positioning results with global navigation satellite systems (GNSS). The work provides a theoretical framework for reliability control in GNSS carrier phase ambiguity resolution, which is the key technique for precise GNSS positioning in centimetre levels. The proposed approach includes identification and exclusion procedures of unreliable solutions and hypothesis tests, allowing the reliability of solutions to be controlled in the aspects of mathematical models, integer estimation and ambiguity acceptance tests. Extensive experimental results with both simulation and observed data sets effectively demonstrate the reliability performance characteristics based on the proposed theoretical framework and procedures.

QoE modelling for VP9 and H.265 videos on mobile devices

Current mobile devices and streaming video services support high definition (HD) video, increasing expectation for more contents. HD video streaming generally requires large bandwidth, exerting pressures on existing networks. New generation of video compression codecs, such as VP9 and H.265/HEVC, are expected to be more effective for reducing bandwidth. Existing studies to measure the impact of its compression on users’ perceived quality have not been focused on mobile devices. Here we propose new Quality of Experience (QoE) models that consider both subjective and objective assessments of mobile video quality. We introduce novel predictors, such as the correlations between video resolution and size of coding unit, and achieve a high goodness-of-fit to the collected subjective assessment data (adjusted R-square >83%). The performance analysis shows that H.265 can potentially achieve 44% to 59% bit rate saving compared to H.264/AVC, slightly better than VP9 at 33% to 53%, depending on video content and resolution.

Metal-free graphitic carbon nitride as mechano-catalyst for hydrogen evolution reaction

Graphitic carbon nitride (g-C3N4), as a promising metal-free catalyst for photo-catalytic and electrochemical water splitting, has recently attracted tremendous research interest. However, the underlying catalytic mechanism for the hydrogen evolution reaction (HER) is not fully understood. By using density functional theory calculations, here we have established that the binding free energy of hydrogen atom (ΔGH∗0) on g-C3N4 is very sensitive to mechanical strain, leading to substantial tuning of the HER performance of g-C3N4 at different coverages. The experimentally-observed high HER activity in N-doped graphene supported g-C3N4 (Zheng et al., 2014) is actually attributed to electron-transfer induced strain. A more practical strategy to induce mechanical strain in g-C3N4 is also proposed by doping a bridge carbon atom in g-C3N4 with an isoelectronic silicon atom. The calculated ΔGH∗0 on the Si-doped g-C3N4 is ideal for HER. Our results indicate that g-C3N4 would be an excellent metal-free mechano-catalyst for HER and this finding is expected to guide future experiments to efficiently split water into hydrogen based on the g-C3N4 materials.