A descriptive approach for power system stability and security assessment

Power system dynamic analysis and security assessment are becoming more significant today due to increases in size and complexity from restructuring, emerging new uncertainties, integration of renewable energy sources, distributed generation, and micro grids. Precise modelling of all contributed elements/devices, understanding interactions in detail, and observing hidden dynamics using existing analysis tools/theorems are difficult, and even impossible. In this chapter, the power system is considered as a continuum and the propagated electomechanical waves initiated by faults and other random events are studied to provide a new scheme for stability investigation of a large dimensional system. For this purpose, the measured electrical indices (such as rotor angle and bus voltage) following a fault in different points among the network are used, and the behaviour of the propagated waves through the lines, nodes, and buses is analyzed. The impact of weak transmission links on a progressive electromechanical wave using energy function concept is addressed. It is also emphasized that determining severity of a disturbance/contingency accurately, without considering the related electromechanical waves, hidden dynamics, and their properties is not secure enough. Considering these phenomena takes heavy and time consuming calculation, which is not suitable for online stability assessment problems. However, using a continuum model for a power system reduces the burden of complex calculations

Introductions to the profession : curricular approach

In 2008, extra-curricular career development programs developed for psychology undergraduates at the Queensland University of Technology were incorporated into the formal curriculum. While a whole of course approach has been adopted, this session will explore the impact of a new introductory unit, Psychology in Professional Contexts, which adopts a constructivist approach to student career exploration. First-year students are introduced to key theories, models, and processes of career development, and the diversity of contexts in which their psychological knowledge can be applied, while developing and highlighting the value of important generic abilities such as critical thinking, team communication, critical reflection, and information literacy. Materials are drawn from the media, guest speakers’ professional profiles, the students’ own experiences, and traditional and emerging areas of psychology. Assessment and learning activities involve case analysis, problem-based learning, and discussion-based classes. The content of these professional development classes is also aligned with that of the core discipline units studied concurrently, to encourage the transfer of career development skills and knowledge across the psychology curriculum. This presentation will focus on 4 years of curriculum development in Psychology in Professional Contexts, and discuss changes initiated in 2011 which incorporate interactive online environments and extend the role of problem-based learning.

A child led participatory approach for technology-based intervention

There is significant interest in Human-computer interaction methods that assist in the design of applications for use by children. Many of these approaches draw upon standard HCI methods,such as personas, scenarios, and probes. However, often these techniques require communication and kinds of thinking skills that are designer centred,which prevents children with Autism Spectrum Disorders or other learning and communication disabilities from being able to participate. This study investigates methods that might be used with children with ASD or other learning and communication disabilities to inspire the design of technology based intervention approaches to support their speech and language development. Similar to Iversen and Brodersen, we argue that children with ASD should not be treated as being in some way “cognitively incomplete”. Rather they are experts in their everyday lives and we cannot design future IT without involving them. However, how do we involve them Instead of beginning with HCI methods, we draw upon easy to use technologies and methods used in the therapy professions for child engagement, particularly utilizing the approaches of Hanen (2011) and Greenspan (1998). These approaches emphasize following the child’s lead and ensuring that the child always has a legitimate turn at a detailed level of interaction. In a pilot project, we have studied a child’s interactions with their parents about activities over which they have control – photos that they have taken at school on an iPad. The iPad was simple enough for this child with ASD to use and they enjoyed taking and reviewing photos. We use this small case study as an example of a child-led approach for a child with ASD. We examine interactions from this study in order to assess the possibilities and limitations of the child-led approach for supporting the design of technology based interventions to support speech and language development.

Fuzzy methods for analysis of microarrays and networks

Bioinformatics involves analyses of biological data such as DNA sequences, microarrays and protein-protein interaction (PPI) networks. Its two main objectives are the identification of genes or proteins and the prediction of their functions. Biological data often contain uncertain and imprecise information. Fuzzy theory provides useful tools to deal with this type of information, hence has played an important role in analyses of biological data. In this thesis, we aim to develop some new fuzzy techniques and apply them on DNA microarrays and PPI networks. We will focus on three problems: (1) clustering of microarrays; (2) identification of disease-associated genes in microarrays; and (3) identification of protein complexes in PPI networks. The first part of the thesis aims to detect, by the fuzzy C-means (FCM) method, clustering structures in DNA microarrays corrupted by noise. Because of the presence of noise, some clustering structures found in random data may not have any biological significance. In this part, we propose to combine the FCM with the empirical mode decomposition (EMD) for clustering microarray data. The purpose of EMD is to reduce, preferably to remove, the effect of noise, resulting in what is known as denoised data. We call this method the fuzzy C-means method with empirical mode decomposition (FCM-EMD). We applied this method on yeast and serum microarrays, and the silhouette values are used for assessment of the quality of clustering. The results indicate that the clustering structures of denoised data are more reasonable, implying that genes have tighter association with their clusters. Furthermore we found that the estimation of the fuzzy parameter m, which is a difficult step, can be avoided to some extent by analysing denoised microarray data. The second part aims to identify disease-associated genes from DNA microarray data which are generated under different conditions, e.g., patients and normal people. We developed a type-2 fuzzy membership (FM) function for identification of diseaseassociated genes. This approach is applied to diabetes and lung cancer data, and a comparison with the original FM test was carried out. Among the ten best-ranked genes of diabetes identified by the type-2 FM test, seven genes have been confirmed as diabetes-associated genes according to gene description information in Gene Bank and the published literature. An additional gene is further identified. Among the ten best-ranked genes identified in lung cancer data, seven are confirmed that they are associated with lung cancer or its treatment. The type-2 FM-d values are significantly different, which makes the identifications more convincing than the original FM test. The third part of the thesis aims to identify protein complexes in large interaction networks. Identification of protein complexes is crucial to understand the principles of cellular organisation and to predict protein functions. In this part, we proposed a novel method which combines the fuzzy clustering method and interaction probability to identify the overlapping and non-overlapping community structures in PPI networks, then to detect protein complexes in these sub-networks. Our method is based on both the fuzzy relation model and the graph model. We applied the method on several PPI networks and compared with a popular protein complex identification method, the clique percolation method. For the same data, we detected more protein complexes. We also applied our method on two social networks. The results showed our method works well for detecting sub-networks and give a reasonable understanding of these communities.

Personalised search – a hybrid approach for web information retrieval and its evaluation

Nowadays, everyone can effortlessly access a range of information on the World Wide Web (WWW). As information resources on the web continue to grow tremendously, it becomes progressively more difficult to meet high expectations of users and find relevant information. Although existing search engine technologies can find valuable information, however, they suffer from the problems of information overload and information mismatch. This paper presents a hybrid Web Information Retrieval approach allowing personalised search using ontology, user profile and collaborative filtering. This approach finds the context of user query with least user’s involvement, using ontology. Simultaneously, this approach uses time-based automatic user profile updating with user’s changing behaviour. Subsequently, this approach uses recommendations from similar users using collaborative filtering technique. The proposed method is evaluated with the FIRE 2010 dataset and manually generated dataset. Empirical analysis reveals that Precision, Recall and F-Score of most of the queries for many users are improved with proposed method.

Towards semantic search and inference in electronic medical records : an approach using concept-based information retrieval

For more than a decade research in the field of context aware computing has aimed to find ways to exploit situational information that can be detected by mobile computing and sensor technologies. The goal is to provide people with new and improved applications, enhanced functionality and better use experience (Dey, 2001). Early applications focused on representing or computing on physical parameters, such as showing your location and the location of people or things around you. Such applications might show where the next bus is, which of your friends is in the vicinity and so on. With the advent of social networking software and microblogging sites such as Facebook and Twitter, recommender systems and so on context-aware computing is moving towards mining the social web in order to provide better representations and understanding of context, including social context. In this paper we begin by recapping different theoretical framings of context. We then discuss the problem of context- aware computing from a design perspective.

A Bayesian approach for estimating detection times in horses : exploring the pharmacokinetics of a urinary acepromazine metabolite

We describe the population pharmacokinetics of an acepromazine (ACP) metabolite (2-(1-hydroxyethyl)promazine) (HEPS) in horses for the estimation of likely detection times in plasma and urine. Acepromazine (30 mg) was administered to 12 horses, and blood and urine samples were taken at frequent intervals for chemical analysis. A Bayesian hierarchical model was fitted to describe concentration-time data and cumulative urine amounts for HEPS. The metabolite HEPS was modelled separately from the parent ACP as the half-life of the parent was considerably less than that of the metabolite. The clearance ($Cl/F_{PM}$) and volume of distribution ($V/F_{PM}$), scaled by the fraction of parent converted to metabolite, were estimated as 769 L/h and 6874 L, respectively. For a typical horse in the study, after receiving 30 mg of ACP, the upper limit of the detection time was 35 hours in plasma and 100 hours in urine, assuming an arbitrary limit of detection of 1 $\mu$g/L, and a small ($\approx 0.01$) probability of detection. The model derived allowed the probability of detection to be estimated at the population level. This analysis was conducted on data collected from only 12 horses, but we assume that this is representative of the wider population.

Arc voltage behavior in GMAW-P under different drop transfer modes

Purpose: Experimental measurements have been made to investigate meaning of the change in voltage for the pulse gas metal arc welding (GMAW-P) process operating under different drop transfer modes. Design/methodology/approach: Welding experiments with different values of pulsing parameter and simultaneous recording of high speed camera pictures and welding signals (such as current and voltage) were used to identify different drop transfer modes in GMAW-P. The investigation is based on the synchronization of welding signals and high speed camera to study the behaviour of voltage signal under different drop transfer modes. Findings: The results reveal that the welding arc is significantly affected by the molten droplet detachment. In fact, results indicate that sudden increase and drop in voltage just before and after the drop detachment can be used to characterize the voltage behaviour of different drop transfer mode in GMAW-P. Research limitations/implications: The results show that voltage signal carry rich information about different drop transfer occurring in GMAW-P. Hence it’s possible to detect different drop transfer modes. Future work should concentrate on development of filters for detection of different drop transfer modes. Originality/value: Determination of drop transfer mode with GMAW-P is crucial for the appropriate selection of pulse welding parameters. As change in drop transfer mode results in poor weld quality in GMAW-P, so in order to estimate the working parameters and ensure stable GMAW-P understanding the voltage behaviour of different drop transfer modes in GMAW-P will be useful. However, in case of GMAW-P hardly any attempt is made to analyse the behaviour of voltage signal for different drop transfer modes. This paper analyses the voltage signal behaviour of different drop transfer modes for GMAW-P.

Determining the appropriate proportion of owner-provided design in design-build contracts - a content analysis approach

The Request For Proposal (RFP) with the design‐build (DB) procurement arrangement is a document in which an owner develops his requirements and conveys the project scope to DB contractors. Owners should provide an appropriate level of design in DB RFPs to adequately describe their requirements without compromising the prospects for innovation. This paper examines and compares the different levels of owner‐provided design in DB RFPs by the content analysis of 84 requests for RFPs for public DB projects advertised between 2000 and 2010 with an aggregate contract value of over $5.4 billion. A statistical analysis was also conducted in order to explore the relationship between the proportion of owner‐provided design and other project information, including project type, advertisement time, project size, contractor selection method, procurement process and contract type. The results show that the majority (64.8%) of the RFPs provide less than 10% of the owner‐provided design. The owner‐provided design proportion has a significant association with project type, project size, contractor selection method and contract type. In addition, owners are generally providing less design in recent years than hitherto. The research findings also provide owners with perspectives to determine the appropriate level of owner‐provided design in DB RFPs.

Rule-based approach for identifying assertions in clinical free-text data

A rule-based approach for classifying previously identified medical concepts in the clinical free text into an assertion category is presented. There are six different categories of assertions for the task: Present, Absent, Possible, Conditional, Hypothetical and Not associated with the patient. The assertion classification algorithms were largely based on extending the popular NegEx and Context algorithms. In addition, a health based clinical terminology called SNOMED CT and other publicly available dictionaries were used to classify assertions, which did not fit the NegEx/Context model. The data for this task includes discharge summaries from Partners HealthCare and from Beth Israel Deaconess Medical Centre, as well as discharge summaries and progress notes from University of Pittsburgh Medical Centre. The set consists of 349 discharge reports, each with pairs of ground truth concept and assertion files for system development, and 477 reports for evaluation. The system’s performance on the evaluation data set was 0.83, 0.83 and 0.83 for recall, precision and F1-measure, respectively. Although the rule-based system shows promise, further improvements can be made by incorporating machine learning approaches.

A capabilities-based approach to obtaining a deeper understanding of information technology governance effectiveness : evidence from IT steering committees

Given the substantial investment in information technology (IT), and the significant impact IT has on organizational success, organizations consume considerable resources to manage acquisition and use of their IT resources. While various arguments proposed suggest which IT governance arrangements may work best, our understanding of the effectiveness of such initiatives is limited. We examine the relationship between the effectiveness of IT steering committee driven IT governance initiatives and firm's IT management and IT infrastructure related capabilities. We further propose that firm's ITrelated capabilities generated through IT governance initiatives should improve its business processes and firm-level performance. We test these relationships empirically by a field survey. Results suggest that firms' effectiveness of IT steering committee driven IT governance initiatives positively relates to the level of their IT-related capabilities. We also found positive relationships between IT-related capabilities and internal process-level performance. Our results also support that improvement in internal process-level performance positively relates to improvement in customer service and firm-level performance.

On IT and business value in developing countries : A complementarities-based approach

Developing economies accommodate more than three quarters of the world's population. This means understanding their growth and well-being is of critical importance. Information technology (IT) is one resource that has had a profound effect in shaping the global economy. IT is also an important resource for driving growth and development in developing economies. Investments in developing economies, however, have focused on the exploitation of labor and natural resources. Unlike in developed economies, focus on IT investment to improve efficiency and effectiveness of business process in developing economies has been sparse, and mechanisms for deriving better IT-related business value is not well understood. This study develops a complementarities-based business value model for developing economies, and tests the relationship between IT investments, IT-related complementarities, and business process performance. It also considers the relationship between business processes performance and firm-level performance. The results suggest that a coordinated investment in IT and IT-related complementarities related favorably to business process performance. Improvements in process-level performance lead to improvements in firm-level performance. The results also suggest that the IT-related complementarities are not only a source of business value on their own, but also enhance the IT resources' ability to contribute to business process performance. This study demonstrates that a coordinated investment approach is required in developing economies. With this approach, their IT resources and IT-related complementaries would help them significantly in improving their business processes, and eventually their firm-level performances.

Internet usage, internet intensity and international sales performance SME's : a structural model approach

There has been much written about the Internet’s potential to enhance international market growth opportunities for SME’s. However, the literature is vague as to how Internet usage and the application of Internet marketing also known as Internet marketing intensity has an impact on firm international market growth. This paper examines the level and role of the Internet in the international operations of a sample of 218 Australian SMEs with international customers. This study shows evidence of a statistical relationship between Internet usage and Internet marketing intensity, which in turn leads to international market growth, in terms of increased sales from new customers in new countries, new customers in existing countries and from existing customers.

Virtual worlds as a model-view approach to the communication of business processes models

The improvement and optimization of business processes is one of the top priorities in an organization. Although process analysis methods are mature today, business analysts and stakeholders are still hampered by communication issues. That is, analysts cannot effectively obtain accurate business requirements from stakeholders, and stakeholders are often confused about analytic results offered by analysts. We argue that using a virtual world to model a business process can benefit communication activities. We believe that virtual worlds can be used as an efficient model-view approach, increasing the cognition of business requirements and analytic results, as well as the possibility of business plan validation. A healthcare case study is provided as an approach instance, illustrating how intuitive such an approach can be. As an exploration paper, we believe that this promising research can encourage people to investigate more research topics in the interdisciplinary area of information system, visualization and multi-user virtual worlds.

New perspectives on context-based chemistry education : using a dialectical sociocultural approach to view teaching and learning

Context-based chemistry education aims to improve student interest and motivation in chemistry by connecting canonical chemistry concepts with real-world contexts. Implementation of context-based chemistry programmes began 20 years ago in an attempt to make the learning of chemistry meaningful for students. This paper reviews such programmes through empirical studies on six international courses, ChemCom (USA), Salters (UK), Industrial Science (Israel), Chemie im Kontext (Germany), Chemistry in Practice (The Netherlands) and PLON (The Netherlands). These studies are categorised through emergent characteristics of: relevance, interest/attitudes motivation and deeper understanding. These characteristics can be found to an extent in a number of other curricular initiatives, such as science-technology-society approaches and problem-based learning or project based science, the latter of which often incorporates an inquiry-based approach to science education. These initiatives in science education are also considered with a focus on the characteristics of these approaches that are emphasised in context-based education. While such curricular studies provide a starting point for discussing context-based approaches in chemistry, to advance our understanding of how students connect canonical science concepts with the real-world context, a new theoretical framework is required. A dialectical sociocultural framework originating in the work of Vygotsky is used as a referent for analysing the complex human interactions that occur in context-based classrooms, providing teachers with recent information about the pedagogical structures and resources that afford students the agency to learn.