Analytical electron microscope investigation of boron carbide microstructures at elevated temperatures

The microstructures of hot-pressed B4C were monitored during in situ heating experiments from room temperature to 1000C by analytical electron microscopy (AEM). Variations in the microstructure of B4C were not observed. However, during heating, secondary phases formed in voids and on the surfaces of the specimen.

Modeling and detection of complex attacks

A complex attack is a sequence of temporally and spatially separated legal and illegal actions each of which can be detected by various IDS but as a whole they constitute a powerful attack. IDS fall short of detecting and modeling complex attacks therefore new methods are required. This paper presents a formal methodology for modeling and detection of complex attacks in three phases: (1) we extend basic attack tree (AT) approach to capture temporal dependencies between components and expiration of an attack, (2) using enhanced AT we build a tree automaton which accepts a sequence of actions from input message streams from various sources if there is a traversal of an AT from leaves to root, and (3) we show how to construct an enhanced parallel automaton that has each tree automaton as a subroutine. We use simulation to test our methods, and provide a case study of representing attacks in WLANs.

Comparison of self-reported driving behaviours and experiences of immediate-uptake and delayed-uptake licence holders

The objective of this paper was to explore experiences of ‘immediate-uptake’ (intermediate licensure at age 17-18 years, n = 928) and ‘delayed-uptake’ (intermediate licensure at age 19-20 years, n = 158) driver’s licence holders in the Australian state of Queensland. In Queensland, the graduated driver licence program applies to all novices irrespective of age. Drivers who obtained a Provisional 1 (intermediate) (P1) licence completed a survey exploring pre-Licence and Learner experiences, including the Behaviour of Young Novice Drivers Scale (BYNDS). Six months later, 351 drivers from this sample (n = 300 immediate-uptake) completed a survey exploring P1 driving. Delayed-uptake Learners reported significantly more difficulty gaining driving practice, which appeared to be associated with significantly greater engagement in unsupervised driving during the Learner period. Whilst a larger proportion of delayed-uptake novices, particularly males, reported the use of more active punishment avoidance strategies (avoiding Police, talking themselves out of a ticket) in the P1 phase, there was no significant difference in the BYNDS scores in the Learner and P1 phases according to licence-uptake category. Delayed-uptake novices report more difficulty meeting GDL requirements and place themselves at increased risk by driving unsupervised during the Learner licence phase. Additional efforts such as mentoring programs which can support the delayed-uptake Learner in meeting their GDL obligations merit further consideration to allow this novice group to gain the full benefits of the GDL program and to reduce their risk of harm in the short-term.

Re-use of domain knowledge to provide confidence for adoption of off-site manufacturing for construction in Australia

Many construction industry decision-makers believe there is a lack of off-site manufacture (OSM) adoption for non-residential construction in Australia. Identification of construction business process was considered imperative in order to assist decision-makers to increase OSM utilisation. The premise that domain knowledge can be re-used to provide an intervention point in the construction process led a team of researchers to construct simple base-line process models for the complete construction process, segmented into six phases. Sixteen domain knowledge industry experts were asked to review the construction phase base-line models to answer the question “Where in the process illustrated by this base-line model phase is an OSM task?”. Through an iterative and generative process a number of off-site manufacture intervention points were identified and integrated into the process models. The re-use of industry expert domain knowledge provided suggestions for new ways to do basic tasks thus facilitating changes to current practice. It is expected that implementation of the new processes will lead to systemic industry change and thus a growth in productivity due to increased adoption of OSM.

Extending and validating the is-impact model in Saudi Arabia : accounting for computer network quality

Organizations from every industry sector seek to enhance their business performance and competitiveness through the deployment of contemporary information systems (IS), such as Enterprise Systems (ERP). Investments in ERP are complex and costly, attracting scrutiny and pressure to justify their cost. Thus, IS researchers highlight the need for systematic evaluation of information system success, or impact, which has resulted in the introduction of varied models for evaluating information systems. One of these systematic measurement approaches is the IS-Impact Model introduced by a team of researchers at Queensland University of technology (QUT) (Gable, Sedera, & Chan, 2008). The IS-Impact Model is conceptualized as a formative, multidimensional index that consists of four dimensions. Gable et al. (2008) define IS-Impact as "a measure at a point in time, of the stream of net benefits from the IS, to date and anticipated, as perceived by all key-user-groups" (p.381). The IT Evaluation Research Program (ITE-Program) at QUT has grown the IS-Impact Research Track with the central goal of conducting further studies to enhance and extend the IS-Impact Model. The overall goal of the IS-Impact research track at QUT is "to develop the most widely employed model for benchmarking information systems in organizations for the joint benefit of both research and practice" (Gable, 2009). In order to achieve that, the IS-Impact research track advocates programmatic research having the principles of tenacity, holism, and generalizability through extension research strategies. This study was conducted within the IS-Impact Research Track, to further generalize the IS-Impact Model by extending it to the Saudi Arabian context. According to Hofsted (2012), the national culture of Saudi Arabia is significantly different from the Australian national culture making the Saudi Arabian culture an interesting context for testing the external validity of the IS-Impact Model. The study re-visits the IS-Impact Model from the ground up. Rather than assume the existing instrument is valid in the new context, or simply assess its validity through quantitative data collection, the study takes a qualitative, inductive approach to re-assessing the necessity and completeness of existing dimensions and measures. This is done in two phases: Exploratory Phase and Confirmatory Phase. The exploratory phase addresses the first research question of the study "Is the IS-Impact Model complete and able to capture the impact of information systems in Saudi Arabian Organization?". The content analysis, used to analyze the Identification Survey data, indicated that 2 of the 37 measures of the IS-Impact Model are not applicable for the Saudi Arabian Context. Moreover, no new measures or dimensions were identified, evidencing the completeness and content validity of the IS-Impact Model. In addition, the Identification Survey data suggested several concepts related to IS-Impact, the most prominent of which was "Computer Network Quality" (CNQ). The literature supported the existence of a theoretical link between IS-Impact and CNQ (CNQ is viewed as an antecedent of IS-Impact). With the primary goal of validating the IS-Impact model within its extended nomological network, CNQ was introduced to the research model. The Confirmatory Phase addresses the second research question of the study "Is the Extended IS-Impact Model Valid as a Hierarchical Multidimensional Formative Measurement Model?". The objective of the Confirmatory Phase was to test the validity of IS-Impact Model and CNQ Model. To achieve that, IS-Impact, CNQ, and IS-Satisfaction were operationalized in a survey instrument, and then the research model was assessed by employing the Partial Least Squares (PLS) approach. The CNQ model was validated as a formative model. Similarly, the IS-Impact Model was validated as a hierarchical multidimensional formative construct. However, the analysis indicated that one of the IS-Impact Model indicators was insignificant and can be removed from the model. Thus, the resulting Extended IS-Impact Model consists of 4 dimensions and 34 measures. Finally, the structural model was also assessed against two aspects: explanatory and predictive power. The analysis revealed that the path coefficient between CNQ and IS-Impact is significant with t-value= (4.826) and relatively strong with â = (0.426) with CNQ explaining 18% of the variance in IS-Impact. These results supported the hypothesis that CNQ is antecedent of IS-Impact. The study demonstrates that the quality of Computer Network affects the quality of the Enterprise System (ERP) and consequently the impacts of the system. Therefore, practitioners should pay attention to the Computer Network quality. Similarly, the path coefficient between IS-Impact and IS-Satisfaction was significant t-value = (17.79) and strong â = (0.744), with IS-Impact alone explaining 55% of the variance in Satisfaction, consistent with results of the original IS-Impact study (Gable et al., 2008). The research contributions include: (a) supporting the completeness and validity of IS-Impact Model as a Hierarchical Multi-dimensional Formative Measurement Model in the Saudi Arabian context, (b) operationalizing Computer Network Quality as conceptualized in the ITU-T Recommendation E.800 (ITU-T, 1993), (c) validating CNQ as a formative measurement model and as an antecedent of IS Impact, and (d) conceptualizing and validating IS-Satisfaction as a reflective measurement model and as an immediate consequence of IS Impact. The CNQ model provides a framework to perceptually measure Computer Network Quality from multiple perspectives. The CNQ model features an easy-to-understand, easy-to-use, and economical survey instrument.

Infrared and Raman spectroscopic characterization of the phosphate mineral kosnarite KZr2(PO4)3 in comparison with other pegmatitic phosphates

In this research, we have used vibrational spectroscopy to study the phosphate mineral kosnarite KZr2(PO4)3. Interest in this mineral rests with the ability of zirconium phosphates (ZP) to lock in radioactive elements. ZP have the capacity to concentrate and immobilize the actinide fraction of radioactive phases in homogeneous zirconium phosphate phases. The Raman spectrum of kosnarite is characterized by a very intense band at 1,026 cm−1 assigned to the symmetric stretching vibration of the PO4 3− ν1 symmetric stretching vibration. The series of bands at 561, 595 and 638 cm−1 are assigned to the ν4 out-of-plane bending modes of the PO4 3− units. The intense band at 437 cm−1 with other bands of lower wavenumber at 387, 405 and 421 cm−1 is assigned to the ν2 in-plane bending modes of the PO4 3− units. The number of bands in the antisymmetric stretching region supports the concept that the symmetry of the phosphate anion in the kosnarite structure is preserved. The width of the infrared spectral profile and its complexity in contrast to the well-resolved Raman spectrum show that the pegmatitic phosphates are better studied with Raman spectroscopy.

Thermogravimetric analysis, PXRD, EDX and XPS study of chrysocolla (Cu,Al)2H2Si2O5(OH)4·nH2O : structural implications

Selected chrysocolla mineral samples from different origins have been studied by using PXRD, SEM, EDX and XPS. The XRD patterns show that the chrysocolla mineral samples are non-diffracting and no other phases are present in the minerals, thus showing the chrysocolla samples are pure. SEM analyses show the chrysocolla surfaces are featureless. EDX analyses enable the formulae of the chrysocolla samples to be calculated. The thermal decomposition of the mineral chrysocolla has been studied using a combination of thermogravimetric analysis and derivative thermogravimetric analysis. Five thermal decomposition mass loss steps are observed for the chrysocolla from Arizona (a) at 125 ◦C with the loss of water, (b) at 340 ◦C with the loss of hydroxyl units, (c) at 468.5 ◦C with a further loss of hydroxyls, (d) at 821 ◦C with oxygen loss and (e) at 895 ◦C with a further loss of oxygen. The thermal analysis of the chrysocolla from Congo shows mass losses at 125, 275.3, 805.6 and 877.4 ◦C and for the Nevada chrysocolla, mass loss steps at 268, 333, 463, 786.0 and 817.7 ◦C are observed. The thermal analysis of spertiniite is very different from that of chrysocolla and thermally decomposes at around 160 ◦C. XPS shows that there are two different copper species present, one which is bonded to oxygen and one to a hydroxyl unit. The O 1s is broad and very symmetrical suggesting two O species of equal number. The bond energy of 102.9 eV for the Si 2p suggests that it is in the form of a silicate. The bond energy is much higher for silicas around ∼103.5 eV. The reported value for silica gel has Si 2p at 103.4 eV. The combination of TG, PXRD, EDX and XPS adds to our fundamental knowledge of the structure of chrysocolla.

Providing query support to leverage BIM for construction

Building information modeling (BIM) is an emerging technology and process that provides rich and intelligent design information models of a facility, enabling enhanced communication, coordination, analysis, and quality control throughout all phases of a building project. Although there are many documented benefits of BIM for construction, identifying essential construction-specific information out of a BIM in an efficient and meaningful way is still a challenging task. This paper presents a framework that combines feature-based modeling and query processing to leverage BIM for construction. The feature-based modeling representation implemented enriches a BIM by representing construction-specific design features relevant to different construction management (CM) functions. The query processing implemented allows for increased flexibility to specify queries and rapidly generate the desired view from a given BIM according to the varied requirements of a specific practitioner or domain. Central to the framework is the formalization of construction domain knowledge in the form of a feature ontology and query specifications. The implementation of our framework enables the automatic extraction and querying of a wide-range of design conditions that are relevant to construction practitioners. The validation studies conducted demonstrate that our approach is significantly more effective than existing solutions. The research described in this paper has the potential to improve the efficiency and effectiveness of decision-making processes in different CM functions.

Real-time risk monitoring in business processes : a sensor-based approach

This article proposes an approach for real-time monitoring of risks in executable business process models. The approach considers risks in all phases of the business process management lifecycle, from process design, where risks are defined on top of process models, through to process diagnosis, where risks are detected during process execution. The approach has been realized via a distributed, sensor-based architecture. At design-time, sensors are defined to specify risk conditions which when fulfilled, are a likely indicator of negative process states (faults) to eventuate. Both historical and current process execution data can be used to compose such conditions. At run-time, each sensor independently notifies a sensor manager when a risk is detected. In turn, the sensor manager interacts with the monitoring component of a business process management system to prompt the results to process administrators who may take remedial actions. The proposed architecture has been implemented on top of the YAWL system, and evaluated through performance measurements and usability tests with students. The results show that risk conditions can be computed efficiently and that the approach is perceived as useful by the participants in the tests.

A formal method for attack modelling and detection

This paper presents a formal methodology for attack modeling and detection for networks. Our approach has three phases. First, we extend the basic attack tree approach 1 to capture (i) the temporal dependencies between components, and (ii) the expiration of an attack. Second, using the enhanced attack trees (EAT) we build a tree automaton that accepts a sequence of actions from input stream if there is a traverse of an attack tree from leaves to the root node. Finally, we show how to construct an enhanced parallel automaton (EPA) that has each tree automaton as a subroutine and can process the input stream by considering multiple trees simultaneously. As a case study, we show how to represent the attacks in IEEE 802.11 and construct an EPA for it.

Prediction of IBD based on population history for fine gene mapping

A novel multiple regression method (RM) is developed to predict identity-by-descent probabilities at a locus L (IBDL), among individuals without pedigree, given information on surrounding markers and population history. These IBDL probabilities are a function of the increase in linkage disequilibrium (LD) generated by drift in a homogeneous population over generations. Three parameters are sufficient to describe population history: effective population size (Ne), number of generations since foundation (T), and marker allele frequencies among founders (p). IBD L are used in a simulation study to map a quantitative trait locus (QTL) via variance component estimation. RM is compared to a coalescent method (CM) in terms of power and robustness of QTL detection. Differences between RM and CM are small but significant. For example, RM is more powerful than CM in dioecious populations, but not in monoecious populations. Moreover, RM is more robust than CM when marker phases are unknown or when there is complete LD among founders or Ne is wrong, and less robust when p is wrong. CM utilises all marker haplotype information, whereas RM utilises information contained in each individual marker and all possible marker pairs but not in higher order interactions. RM consists of a family of models encompassing four different population structures, and two ways of using marker information, which contrasts with the single model that must cater for all possible evolutionary scenarios in CM.

Structural characterisation and environmental application of organoclays for the removal of phenolic compounds

Modified montmorillonite was prepared at different surfactant (HDTMA) loadings through ion exchange. The conformational arrangement of the loaded surfactants within the interlayer space of MMT was obtained by computational modelling. The conformational change of surfactant molecules enhance the visual understanding of the results obtained from characterization methods such as XRD and surface analysis of the organoclays. Batch experiments were carried out for the adsorption of p-chlorophenol (PCP) and different conditions (pH and temperature) were used in order to determine the optimum sorption. For comparison purpose, the experiments were repeated under the same conditions for p-nitrophenol (PNP). Langmuir and Freundlich equations were applied to the adsorption isotherm of PCP and PNP. The Freundlich isotherm model was found to be the best fit for both of the phenolic compounds. This involved multilayer adsorptions in the adsorption process. In particular, the binding affinity value of PNP was higher than that of PCP and this is attributable to their hydrophobicities. The adsorption of the phenolic compounds by organoclays intercalated with highly loaded surfactants was markedly improved possibly due to the fact that the intercalated surfactant molecules within the interlayer space contribute to the partition phases, which result in greater adsorption of the organic pollutants.

A USANS/SANS study of the accessibility of pores in the barnett shale to methane and water

Shale is an increasingly important source of natural gas in the United States. The gas is held in fine pores that need to be accessed by horizontal drilling and hydrofracturing techniques. Understanding the nature of the pores may provide clues to making gas extraction more efficient. We have investigated two Mississippian Barnett Shale samples, combining small-angle neutron scattering (SANS) and ultrasmall-angle neutron scattering (USANS) to determine the pore size distribution of the shale over the size range 10 nm to 10 μm. By adding deuterated methane (CD4) and, separately, deuterated water (D2O) to the shale, we have identified the fraction of pores that are accessible to these compounds over this size range. The total pore size distribution is essentially identical for the two samples. At pore sizes >250 nm, >85% of the pores in both samples are accessible to both CD4 and D2O. However, differences in accessibility to CD4 are observed in the smaller pore sizes (∼25 nm). In one sample, CD4 penetrated the smallest pores as effectively as it did the larger ones. In the other sample, less than 70% of the smallest pores (<25 nm) were accessible to CD4, but they were still largely penetrable by water, suggesting that small-scale heterogeneities in methane accessibility occur in the shale samples even though the total porosity does not differ. An additional study investigating the dependence of scattered intensity with pressure of CD4 allows for an accurate estimation of the pressure at which the scattered intensity is at a minimum. This study provides information about the composition of the material immediately surrounding the pores. Most of the accessible (open) pores in the 25 nm size range can be associated with either mineral matter or high reflectance organic material. However, a complementary scanning electron microscopy investigation shows that most of the pores in these shale samples are contained in the organic components. The neutron scattering results indicate that the pores are not equally proportioned in the different constituents within the shale. There is some indication from the SANS results that the composition of the pore-containing material varies with pore size; the pore size distribution associated with mineral matter is different from that associated with organic phases.

Interpersonal coordination tendencies shape 1-vs-1 sub-phase performance outcomes in youth soccer

This study investigated the influence of interpersonal coordination tendencies on performance outcomes of 1-vs-1 subphases in youth soccer. Eight male developing soccer players (age: 11.8+0.4 years; training experience: 3.6+1.1 years) performed an in situ simulation of a 1-vs-1 sub-phase of soccer. Data from 82 trials were obtained with motion-analysis techniques, and relative phase used to measure the space-time coordination tendencies of attacker-defender dyads. Approximate entropy (ApEn) was then used to quantify the unpredictability of interpersonal interactions over trials. Results revealed how different modes of interpersonal coordination emerging from attacker-defender dyads influenced the 1-vs-1 performance outcomes. High levels of space-time synchronisation (47%) and unpredictability in interpersonal coordination processes (ApEn: 0.91+0.34) were identified as key features of an attacking player’s success. A lead-lag relation attributed to a defending player (34% around 7308 values) and a more predictable coordination mode (ApEn: 0.65+0.27, P50.001), demonstrated the coordination tendencies underlying the success of defending players in 1-vs-1 sub-phases. These findings revealed how the mutual influence of each player on the behaviour of dyadic systems shaped emergent performance outcomes. More specifically, the findings showed that attacking players should be constrained to exploit the space-time synchrony with defenders in an unpredictable and creative way, while defenders should be encouraged to adopt postures and behaviours that actively constrain the attacker’s actions.

Professional development using informal learning networks : an empirical study in Australia’s digital content industry

Informal learning networks play a key role in the skill and professional development of professionals working in micro-businesses within Australia’s digital content industry as they do not necessarily have access to a learning and development or a human resources section that can assist in mapping their learning pathway. Professionals working in this environment would typically adopt an informal learning approach to their skill and professional development by utilising their social and business networks. The overall aim of this PhD research project is to study how these professionals manage their skill and professional development, and to explore what role informal learning networks play in this professional learning context. This paper will describe the theme of the research project and how it fits with previous research and other relevant studies. Secondly, it will present the study’s research focus, and the research questions. It will also present relevant theories and perspectives, and the methods for empirical data collection. Data collection will be through three distinct phases using a mixed methods research design: an online survey, interviews, and case studies. It should be noted the findings presented in this paper offer some early results of the research project.