An interpretative structural modeling based network reconfiguration strategy for power systems

The network reconfiguration is an important stage of restoring a power system after a complete blackout or a local outage. Reasonable planning of the network reconfiguration procedure is essential for rapidly restoring the power system concerned. An approach for evaluating the importance of a line is first proposed based on the line contraction concept. Then, the interpretative structural modeling (ISM) is employed to analyze the relationship among the factors having impacts on the network reconfiguration. The security and speediness of restoring generating units are considered with priority, and a method is next proposed to select the generating unit to be restored by maximizing the restoration benefit with both the generation capacity of the restored generating unit and the importance of the line in the restoration path considered. Both the start-up sequence of generating units and the related restoration paths are optimized together in the proposed method, and in this way the shortcomings of separately solving these two issues in the existing methods are avoided. Finally, the New England 10-unit 39-bus power system and the Guangdong power system in South China are employed to demonstrate the basic features of the proposed method.

Modeling conditional correlations of asset returns : a smooth transition approach

In this paper we propose a new multivariate GARCH model with time-varying conditional correlation structure. The time-varying conditional correlations change smoothly between two extreme states of constant correlations according to a predetermined or exogenous transition variable. An LM–test is derived to test the constancy of correlations and LM- and Wald tests to test the hypothesis of partially constant correlations. Analytical expressions for the test statistics and the required derivatives are provided to make computations feasible. An empirical example based on daily return series of five frequently traded stocks in the S&P 500 stock index completes the paper.

Computation of Mathematical Models for Complex Industrial Processes

Designed for undergraduate and postgraduate students, academic researchers and industrial practitioners, this book provides comprehensive case studies on numerical computing of industrial processes and step-by-step procedures for conducting industrial computing. It assumes minimal knowledge in numerical computing and computer programming, making it easy to read, understand and follow. Topics discussed include fundamentals of industrial computing, finite difference methods, the Wavelet-Collocation Method, the Wavelet-Galerkin Method, High Resolution Methods, and comparative studies of various methods. These are discussed using examples of carefully selected models from real processes of industrial significance. The step-by-step procedures in all these case studies can be easily applied to other industrial processes without a need for major changes and thus provide readers with useful frameworks for the applications of engineering computing in fundamental research problems and practical development scenarios.

Predicting reduced driver alertness on monotonous highways : a driving simulator study

Impaired driver alertness increases the likelihood of drivers’ making mistakes and reacting too late to unexpected events while driving. This is particularly a concern on monotonous roads, where a driver’s attention can decrease rapidly. While effective countermeasures do not currently exist, the development of in-vehicle sensors opens avenues for monitoring driving behavior in real-time. The aim of this study is to predict drivers’ level of alertness through surrogate measures collected from in-vehicle sensors. Electroencephalographic activity is used as a reference to evaluate alertness. Based on a sample of 25 drivers, data was collected in a driving simulator instrumented with an eye tracking system, a heart rate monitor and an electrodermal activity device. Various classification models were tested from linear regressions to Bayesians and data mining techniques. Results indicated that Neural Networks were the most efficient model in detecting lapses in alertness. Findings also show that reduced alertness can be predicted up to 5 minutes in advance with 90% accuracy, using surrogate measures such as time to line crossing, blink frequency and skin conductance level. Such a method could be used to warn drivers of their alertness level through the development of an in-vehicle device monitoring, in real-time, drivers' behavior on highways.

A critical review of structural equation modeling applications in construction research

Structural equation modeling (SEM) is a versatile multivariate statistical technique, and applications have been increasing since its introduction in the 1980s. This paper provides a critical review of 84 articles involving the use of SEM to address construction related problems over the period 1998–2012 including, but not limited to, seven top construction research journals. After conducting a yearly publication trend analysis, it is found that SEM applications have been accelerating over time. However, there are inconsistencies in the various recorded applications and several recurring problems exist. The important issues that need to be considered are examined in research design, model development and model evaluation and are discussed in detail with reference to current applications. A particularly important issue concerns the construct validity. Relevant topics for efficient research design also include longitudinal or cross-sectional studies, mediation and moderation effects, sample size issues and software selection. A guideline framework is provided to help future researchers in construction SEM applications.

The plasticity of NBS resistance genes in sorghum is driven by multiple evolutionary processes

Background Increased disease resistance is a key target of cereal breeding programs, with disease outbreaks continuing to threaten global food production, particularly in Africa. Of the disease resistance gene families, the nucleotide-binding site plus leucine-rich repeat (NBS-LRR) family is the most prevalent and ancient and is also one of the largest gene families known in plants. The sequence diversity in NBS-encoding genes was explored in sorghum, a critical food staple in Africa, with comparisons to rice and maize and with comparisons to fungal pathogen resistance QTL. Results In sorghum, NBS-encoding genes had significantly higher diversity in comparison to non NBS-encoding genes and were significantly enriched in regions of the genome under purifying and balancing selection, both through domestication and improvement. Ancestral genes, pre-dating species divergence, were more abundant in regions with signatures of selection than in regions not under selection. Sorghum NBS-encoding genes were also significantly enriched in the regions of the genome containing fungal pathogen disease resistance QTL; with the diversity of the NBS-encoding genes influenced by the type of co-locating biotic stress resistance QTL. Conclusions NBS-encoding genes are under strong selection pressure in sorghum, through the contrasting evolutionary processes of purifying and balancing selection. Such contrasting evolutionary processes have impacted ancestral genes more than species-specific genes. Fungal disease resistance hot-spots in the genome, with resistance against multiple pathogens, provides further insight into the mechanisms that cereals use in the “arms race” with rapidly evolving pathogens in addition to providing plant breeders with selection targets for fast-tracking the development of high performing varieties with more durable pathogen resistance.

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.

Evaluation of the spatial distribution of γH2AX following ionizing radiation

An early molecular response to DNA double-strand breaks (DSBs) is phosphorylation of the Ser-139 residue within the terminal SQEY motif of the histone H2AX1,2. This phosphorylation of H2AX is mediated by the phosphatidyl-inosito 3-kinase (PI3K) family of proteins, ataxia telangiectasia mutated (ATM), DNA-protein kinase catalytic subunit and ATM and RAD3-related (ATR)3. The phosphorylated form of H2AX, referred to as γH2AX, spreads to adjacent regions of chromatin from the site of the DSB, forming discrete foci, which are easily visualized by immunofluorecence microscopy3. Analysis and quantitation of γH2AX foci has been widely used to evaluate DSB formation and repair, particularly in response to ionizing radiation and for evaluating the efficacy of various radiation modifying compounds and cytotoxic compounds Given the exquisite specificity and sensitivity of this de novo marker of DSBs, it has provided new insights into the processes of DNA damage and repair in the context of chromatin. For example, in radiation biology the central paradigm is that the nuclear DNA is the critical target with respect to radiation sensitivity. Indeed, the general consensus in the field has largely been to view chromatin as a homogeneous template for DNA damage and repair. However, with the use of γH2AX as molecular marker of DSBs, a disparity in γ-irradiation-induced γH2AX foci formation in euchromatin and heterochromatin has been observed5-7. Recently, we used a panel of antibodies to either mono-, di- or tri- methylated histone H3 at lysine 9 (H3K9me1, H3K9me2, H3K9me3) which are epigenetic imprints of constitutive heterochromatin and transcriptional silencing and lysine 4 (H3K4me1, H3K4me2, H3K4me3), which are tightly correlated actively transcribing euchromatic regions, to investigate the spatial distribution of γH2AX following ionizing radiation8. In accordance with the prevailing ideas regarding chromatin biology, our findings indicated a close correlation between γH2AX formation and active transcription9. Here we demonstrate our immunofluorescence method for detection and quantitation of γH2AX foci in non-adherent cells, with a particular focus on co-localization with other epigenetic markers, image analysis and 3Dmodeling.

Turning event logs into process movies: animating what has really happened

Today’s information systems log vast amounts of data. These collections of data (implicitly) describe events (e.g. placing an order or taking a blood test) and, hence, provide information on the actual execution of business processes. The analysis of such data provides an excellent starting point for business process improvement. This is the realm of process mining, an area which has provided a repertoire of many analysis techniques. Despite the impressive capabilities of existing process mining algorithms, dealing with the abundance of data recorded by contemporary systems and devices remains a challenge. Of particular importance is the capability to guide the meaningful interpretation of “oceans of data” by process analysts. To this end, insights from the field of visual analytics can be leveraged. This article proposes an approach where process states are reconstructed from event logs and visualised in succession, leading to an animated history of a process. This approach is customisable in how a process state, partially defined through a collection of activity instances, is visualised: one can select a map and specify a projection of events on this map based on the properties of the events. This paper describes a comprehensive implementation of the proposal. It was realised using the open-source process mining framework ProM. Moreover, this paper also reports on an evaluation of the approach conducted with Suncorp, one of Australia’s largest insurance companies.

Teaching peer review reflective processes in accounting

A well designed peer review process in higher education subjects can lead to more confident and reflective learners who become skilled at making independent judgements of their own and others’ work; essential requirements for successful lifelong learning. The challenge for educators is to ensure their students gain these important graduate attributes within the constraints of a range of internal and external tensions currently facing higher education systems, including, respectively, the realities of large undergraduate Accounting subjects, culturally diverse and time-poor academics and students, and increased calls for public accountability of the Higher Education sector by groups such as the OECD. Innovative curriculum and assessment design and collaborative technologies have the capacity to simultaneously provide some measure of relief from these internal and external tensions and to position students as responsible partners in their own learning. This chapter reports on a two phase implementation of an online peer review process as part of the assessment in a large, under-graduate, International Accounting class. Phase One did not include explicit reflective strategies within the process, and anonymous and voluntary student views served to clearly highlight that students were ‘confused’ and ‘hesitant’ about moving away from their own ideas; often mistrusting the conflicting advice received from multiple peer reviewers. A significant number of students also felt that they did not have the skills to constructively review the work of their peers. Phase Two consequently utilised the combined power of e-Technology, peer review feedback and carefully scaffolded and supported reflective practices from Ryan and Ryan’s Teaching and Assessing Reflective Learning (TARL) model (see Chap. 2). Students found the reflective skills support workshop introduced in Phase Two to be highly useful in maximising the benefits of the peer review process, with 83 % reporting it supported them in writing peer reviews, while 90 % of the respondents reporting the workshop supported them in utilising peer and staff feedback.

The decision-making processes of early childhood teachers when working with children experiencing parental separation and divorce

In this study, the pedagogical decision-making processes of 21 Australian early childhood teachers working with children experiencing parental separation and divorce were examined. Transcripts from interviews and a focus group with teachers were analysed using grounded theory methodology. The findings showed that as teachers interacted with young children experiencing parental separation and divorce, they reported using strategic, reflexive pedagogical decision-making processes. These processes comprised five stages: (1) teachers constructing their knowledge; (2) teachers thinking about their knowledge; (3) teachers using decision-making schemas; (4) teachers taking action, and; (5) teachers monitoring action and evaluating. This understanding of teachers’ reflexive pedagogical decision-making is useful for identifying how teachers and educational leaders can support children experiencing parental separation and divorce or other life challenges.

Can’t we all just get along? A qualitative investigation of the cognitive processes motivating driver aggression.

Although driver aggression has been identified as contributing to crashes, current understanding of the fundamental causes of the behaviour is poor. Two key reasons for this are evident. Firstly, existing research has been largely atheoretical, with no unifying conceptual framework guiding investigation. Secondly, emphasis on observable behaviours has resulted in limited knowledge of the underlying thought processes that motivate behaviour. Since driving is fundamentally a social situation, requiring drivers to interpret on-road events, insight regarding these perception and appraisal processes is paramount in advancing understanding of the underlying causes. Thus, the current study aimed to explore the cognitive appraisal processes involved in driver aggression, using a conceptual model founded on the General Aggression Model (Anderson & Bushman, 2002). The present results reflect the first of several studies testing this model. Participants completed 3 structured driving diaries to explore perceptions and cognitions. Thematic analysis of diaries identified several cognitive themes. The first, ‘driving etiquette’ concerned an implied code of awareness and consideration for other motorists, breaches of which were strongly associated with reports of anger and frustration. Such breaches were considered intentional; attributed to dispositional traits of another driver, and precipitated the second theme, ‘justified retaliation’. This theme showed that drivers view their aggressive behaviour as warranted, to convey criticism towards another motorist’s etiquette violation. However, the third theme, ‘superiority’ suggested that those refraining from an aggressive response were motivated by a desire to perceive themselves as ‘better’ than the offending motorists. Collectively, the themes indicate deep-seated and complex thought patterns underlying driver aggression, and suggest the behaviour will be challenging to modify. Implications of these themes in relation to the proposed model will be discussed, and continued research will explore these cognitive processes further, to examine their interaction with person-related factors.

AITSL pilot projects [Queensland University of Technology : The existing school-based practices and processes for the use of NAPLAN data] Final report

This pilot project investigated the existing practices and processes of Proficient, Highly Accomplished and Lead teachers in the interpretation, analysis and implementation of National Assessment Program – Literacy and Numeracy (NAPLAN) data. A qualitative case study approach was the chosen methodology, with nine teachers across a variety of school sectors interviewed. Themes and sub-themes were identified from the participants’ interview responses revealing the ways in which Queensland teachers work with NAPLAN data. The data illuminated that generally individual schools and teachers adopted their own ways of working with data, with approaches ranging from individual/ad hoc, to hierarchical or a whole school approach. Findings also revealed that data are the responsibility of various persons from within the school hierarchy; some working with the data electronically whilst others rely on manual manipulation. Manipulation of data is used for various purposes including tracking performance, value adding and targeting programmes for specific groups of students, for example the gifted and talented. Whilst all participants had knowledge of intervention programmes and how practice could be modified, there were large inconsistencies in knowledge and skills across schools. Some see the use of data as a mechanism for accountability, whilst others mention data with regards to changing the school culture and identifying best practice. Overall, the findings showed inconsistencies in approach to focus area 5.4. Recommendations therefore include a more national approach to the use of educational data.

Audit committee effectiveness : informal processes and behavioural effects

Purpose This paper seeks to investigate the conditions and processes affecting the operation and potential effectiveness of audit committees (ACs), with particular focus on the interaction between the AC, individuals from financial reporting and internal audit functions and the external auditors. Design/methodology/approach A case study approach is employed, based on direct engagement with participants in AC activities, including the AC chair, external auditors, internal auditors, and senior management. Findings The authors find that informal networks between AC participants condition the impact of the AC and that the most significant effects of the AC on governance outcomes occur outside the formal structures and processes. An AC has pervasive behavioural effects within the organization and may be used as a threat, an ally and an arbiter in bringing solutions to issues and conflicts. ACs are used in organizational politics, communication processes and power plays and also affect interpretations of events and cultural values. Research limitations/implications Further research on AC and governance processes is needed to develop better understanding of effectiveness. Longitudinal studies, focusing on the organizational and institutional context of AC operations, can examine how historical events in an organization and significant changes in the regulatory environment affect current structures and processes. Originality/value The case analysis highlights a number of significant factors which are not fully recognised either in theorizing the governance role of ACs or in the development of policy and regulations concerning ACs but which impinge on their governance contribution. They include the importance of informal processes around the AC; its influence on power relations between organizational participants; the relevance of the historical development of governance in an organization; and the possibility that the AC’s impact on governance may be greatest in non-routine situations.

Recent advances in modeling the vulnerability of transportation networks

It is well known that, for major infrastructure networks such as electricity, gas, railway, road, and urban water networks, disruptions at one point have a knock on effect throughout the network. There is an impressive amount of individual research projects examining the vulnerability of critical infrastructure network. However, there is little understanding of the totality of the contribution made by these projects and their interrelationships. This makes their review a difficult process for both new and existing researchers in the field. To address this issue, a two-step literature review process is used, to provide an overview of the vulnerability of the transportation network in terms of four main themes - research objective, transportation mode, disruption scenario and vulnerability indicator –involving the analysis of related articles from 2001 to 2013. Two limitations of existing research are identified: (1) the limited amount of studies relating to multi-layer transportation network vulnerability analysis, and (2) the lack of evaluation methods to explore the relationship between structure vulnerability and dynamical functional vulnerability. In addition to indicating that more attention needs to be paid to these two aspects in future, the analysis provides a new avenue for the discovery of knowledge, as well as an improved understanding of transportation network vulnerability.