Poly-Articulate

Poly-Articulate was a series of meditations around the paradoxes of articulation, considered in the heterogeneity of its material, visual, aural and conceptual aspects. Taking form through a collaborative working group of four artists/ designers/writers, the project used different technologies from the most ancient (the voice-box) to the most current (real-time rendering engines). With the utilisation of laser sensors crossing the gallery spaces, 20 digital monitors accompanied by vocal syllables would respond to the viewers? movement. Another piece of technology?a theramin installed below the sculpture of a trachea (inner ear)?mutated the vocal sounds upon its engagement along with a microphone suspended in one of the galleries. The visual and sound aspects of this project made it a compelling spatial experience.

An interactive CDRom accompanied with a text by Justin Clemens was published with this project.

How we finance our new and growing firms

Entrepreneurs are the engines that drive new companies and financing is the fuel that propels them. One form of that financing is called informal investing, sometimes called ''business angel activity'' (which we reserve for more professional and commercial investors). Informal investors use their own money and carry out their own due diligence to invest in the entrepreneurial opportunities of other entrepreneurs.

Algorithms and applications of preference based ranking for information retrieval

In this thesis, the author designed three sets of preference based ranking algorithms for information retrieval and provided the corresponsive applications for the algorithms. The main goal is to retrieve recommended, high similar and valuable ranking results to users.

Cracking and distortion of water jackets in engine blocks

This thesis investigated the cracking and distortion of water jackets in engine blocks. The Taguchi method was utilized to improve production process and in doing so, reducing the scrap of water jacket cores by over 60%. Further, by altering core material and pouring temperature, casting distortion was improved.

Dopamine dysregulation syndrome : implications for a dopamine hypothesis of bipolar disorder

Objective: Rational therapeutic development in bipolar is hampered by a lack of pathophysiological model. However, there is a wealth of converging data on the role of dopamine in bipolar disorder. This paper therefore examines the possibility of a dopamine hypothesis for bipolar disorder.

Method: A literature search was conducted using standard search engines Embase, PyschLIT, PubMed and MEDLINE. In addition, papers and book chapters known to the authors were retrieved and examined for further relevant articles.

Results: Collectively, in excess of 100 articles were reviewed from which approximately 75% were relevant to the focus of this paper.

Conclusion: Pharmacological models suggest a role of increased dopaminergic drive in mania and the converse in depression. In Parkinson’s disease, administration of high-dose dopamine precursors can produce a ‘maniform’ picture, which switches into a depressive analogue on withdrawal. It is possible that in bipolar disorder there is a cyclical process, where increased dopaminergic transmission in mania leads to a secondary down regulation of dopaminergic receptor sensitivity over time. This may lead to a period of decreased dopaminergic transmission, corresponding with the depressive phase, and the repetition of the cycle. This model, if verified, may have implications for rational drug development.

Polymorphic malware detection using Hierarchical Hidden Markov Model

Binary signatures have been widely used to detect malicious software on the current Internet. However, this approach is unable to achieve the accurate identification of polymorphic malware variants, which can be easily generated by the malware authors using code generation engines. Code generation engines randomly produce varying code sequences but perform the same desired malicious functions. Previous research used flow graph and signature tree to identify polymorphic malware families. The key difficulty of previous research is the generation of precisely defined state machine models from polymorphic variants. This paper proposes a novel approach, using Hierarchical Hidden Markov Model (HHMM), to provide accurate inductive inference of the malware family. This model can capture the features of self-similar and hierarchical structure of polymorphic malware family signature sequences. To demonstrate the effectiveness and efficiency of this approach, we evaluate it with real malware samples. Using more than 15,000 real malware, we find our approach can achieve high true positives, low false positives, and low computational cost.

Discriminating DDoS attacks from flash crowds using flow correlation coefficient

Distributed Denial of Service (DDoS) attack is a critical threat to the Internet, and botnets are usually the engines behind them. Sophisticated botmasters attempt to disable detectors by mimicking the traffic patterns of flash crowds. This poses a critical challenge to those who defend against DDoS attacks. In our deep study of the size and organization of current botnets, we found that the current attack flows are usually more similar to each other compared to the flows of flash crowds. Based on this, we proposed a discrimination algorithm using the flow correlation coefficient as a similarity metric among suspicious flows. We formulated the problem, and presented theoretical proofs for the feasibility of the proposed discrimination method in theory. Our extensive experiments confirmed the theoretical analysis and demonstrated the effectiveness of the proposed method in practice.

Balanced efficacy, safety, and tolerability recommendations for the clinical management of bipolar disorder

Objective:  To provide practical and clinically meaningful treatment recommendations that amalgamate clinical experience and research findings for each phase of bipolar disorder.

Methods:  A comprehensive search of the literature was undertaken using electronic database search engines (Medline, PubMed, Cochrane reviews) using key words (e.g., bipolar depression, mania, treatment). All relevant randomised controlled trials were examined, along with review papers, meta-analyses, and book chapters known to the authors. In addition, the recommendations from accompanying papers in this supplement have been distilled and captured in the form of summary boxes. The findings, in conjunction with the clinical experience of international researchers and clinicians who are practiced in treating mood disorders, formed the basis of the treatment recommendations within this paper.

Results:  Balancing clinical experience with evidence informed and lead to the development of practical clinical recommendations that emphasise the importance of safety and tolerability alongside efficacy in the clinical management of bipolar disorder.

Conclusions:  The current paper summarises the treatment recommendations relating to each phase of bipolar disorder while providing additional, evidence-based, practical insights. Medication-related side effects and monitoring strategies highlight the importance of safety and tolerability considerations, which, along with efficacy information, should be given equal merit.

Context-aware meta search engine for distributed web service

The ubiquity of the Internet and Web has led to the emergency of several Web search engines with varying capabilities. A weakness of existing search engines is the very extensive amount of hits that they can produce. Moreover, only a small number of web users actually know how to utilize the true power of Web search engines. Therefore, there is a need for searching infrastructure to help ease and guide the searching efforts of web users toward their desired objectives. In this paper, we propose a context-based meta-search engine and discuss its implementation on top of the actual Google.com search engine. The proposed meta-search engine benefits the user the most when the user does not know what exact document he or she is looking for. Comparison of the context-based meta-search engine with both Google and Guided Google shows that the results returned by context-based meta-search engine is much more intuitive and accurate than the results returned by both Google and Guided Google.

A novel exhaust heat recovery system to reduce fuel consumption

Internal combustion engines release about 1/3 of the energy bound in the fuel as exhaust waste gas energy and another 1/3 energy is wasted through heat transfer into the ambient. On the other hand losses through friction are the third largest root cause for energy loss in internal combustion engines. During city driving frictional losses can be of the same size as the effective work, and during cold start these losses are even bigger. Therefore it is obvious to utilise wasted exhaust energy to warm up the engine oil directly. Frictional losses of any engine can be reduced during part load. Sensitivity analyses have been conducted for different concepts that utilise exhaust energy to reduce engine viscosity and friction. For a new system with an exhaust gas/oil heat exchanger the following benefits have been demonstrated:

• Fuel consumption reductions of over 7% measured as an average over 5 NEDC tests
compared to the standard system configuration.
• Significant reductions in exhaust emissions, mainly CO and NOx have been achieved
• Significantly higher oil temperatures during cold start indicate large potential to
reduce engine wear through reduced water condensation in the crankcase
• Fuel consumption reductions of further 3.3% to 4.6% compared to the 7% measured
over the NEDC test can be expected under real world customer usage conditions at
lower ambient temperatures.

Oil temperature measurements and analysis resulted in the idea of a novel system with further potential to reduce fuel consumption. This Oil Viscosity Energy Recovery System (OVER 7™) consists of 3 key features that add significant synergies if combined in a certain way: an oil warm up circuit/bypass, including oil pressure control and Exhaust Gas/Oil Heat Exchanger. The system separates the thermal inertias of the oil in the engine galleries and the oil pan, reduces hydraulic pumping losses, increases the heat transfer from the cylinder head to the oil, and utilises the exhaust heat to reduce oil friction.

The project demonstrated that sensitivity analysis is an important tool for the evaluation of different concepts. Especially for new concepts that include transient heat transfer such a qualitative approach in combination with accurate experiments and measurements can be faster and more efficient in leading to the desired improvements compared to time consuming detailed simulations.

Direct versus search engine traffic : an innovative approach to demand analysis in the property market

Purpose – The application of “Google” econometrics (Geco) has evolved rapidly in recent years and can be applied in various fields of research. Based on accepted theories in existing economic literature, this paper seeks to contribute to the innovative use of research on Google search query data to provide a new innovative to property research.

Design/methodology/approach – In this study, existing data from Google Insights for Search (GI4S) is extended into a new potential source of consumer sentiment data based on visits to a commonly-used UK online real-estate agent platform (Rightmove.co.uk). In order to contribute to knowledge about the use of Geco's black box, namely the unknown sampling population and the specific search queries influencing the variables, the GI4S series are compared to direct web navigation.

Findings – The main finding from this study is that GI4S data produce immediate real-time results with a high level of reliability in explaining the future volume of transactions and house prices in comparison to the direct website data. Furthermore, the results reveal that the number of visits to Rightmove.co.uk is driven by GI4S data and vice versa, and indeed without a contemporaneous relationship.

Originality/value – This study contributes to the new emerging and innovative field of research involving search engine data. It also contributes to the knowledge base about the increasing use of online consumer data in economic research in property markets.

Web 2.0 for networked learning : from collaboration to shared cognition and knowledge networking

This poster presents research-in-progress into the educational affordances of so-called Web 2.0 sites, services, with a particular emphasis on those applications that involve forms of shared human-machine cognition and that promote public knowledge networking. This research involves reviewing many hundreds of Web 2.0 tools and selecting approximately 50 for further analysis and exploration as learning applications. In doing so, the research will generate examples of unusual affordances provided by Web 2.0; it will also present a more structured categorisation of the kinds of uses and benefits of these tools. This approach is valuable because much current research and analysis of the impact of Web 2.0 on education, particularly higher education, has emphasised a relatively limited array of tools – principally blogs, wikis and social networking services – that offer educators and students opportunities for student-led collaborative work. Such opportunities involve strong emphasis on constructivist pedagogy: students’ interactions with each other, mediated via the Internet, are viewed as the positive benefit which networked learning can provide. However, Web 2.0 is far more than just collaboration, and associated shared self-expression. In particular, Web 2.0 includes many examples of services that take one form of input from a user and, rather than just sharing it with others, enable the transformation of that input into different forms, either as visualisations, maps, or other re-representations. Web 2.0 is also starting to see the development of knowledge-work engines that embody the concept of shared cognition, in which the service and the user cooperate in the production of some final knowledge output or which present to users knowledge that has already been processed more extensively than through simple searching. Web 2.0 is also closely associated with the idea that knowledge work is now networked and distributed; it involves users appropriating, creating and sharing knowledge products in a very public way, far beyond the narrow ‘audience’ of a particular course or program of study. The research presented in this poster will provide, firstly, examples of the Web 2.0 tools which emphasise these additional ways of exploiting the Internet for networked learning; secondly, the research will provide a first iteration of the overarching structure of categories and classifications which can be used to assess any proposed Web 2.0 application in terms of its affordances for learning as knowledge networking. By understanding these technologies, truly collaborative networked learning can be developed that blends with the emerging cultures of online behaviour increasingly common to contemporary student populations.

Medication adherence self-report instruments : implications for practice and research

Background: After an acute cardiac event, adhering to recommendations for pharmacologic therapy is important in achieving optimal health outcomes. Considering the impressive evidence base for cardiovascular pharmacotherapy, strategies for promoting adherence are less well developed. Furthermore, accessing reliable, valid, and cost-effective mechanisms of monitoring adherence in the research and clinical settings is challenging. Aim: The aim of this article was to review published self-report measures assessing and monitoring medication adherence in cardiovascular disease and provide recommendations for research into medication adherence. Methods: The electronic databases CINAHL, Medline, and Science Direct were searched using the key search terms medication adherence and/or compliance, cardiovascular, self-report measures, and questionnaires. The World Wide Web was searched using the Google and Google Scholar search engines, and reference lists of retrieved documents were reviewed. The search strategy was verified by a health librarian. Instruments were included if they specifically addressed medication adherence as a discrete construct rather than a disease-specific or a generic health status measurement. Findings: Despite of the problems with medication adherence identified in the literature, only 7 instruments met the search criteria. There was limited use of instruments across studies and settings to enable comparison across populations and extensive psychometric evaluation. Conclusions: Medication adherence is a complex, multifaceted construct dependent on a range of physical, social, economic, and psychological considerations. In spite of the importance of adherence in ensuring optimal cardiovascular outcomes, conceptual underpinnings and methods of assessing medication adherence require further discussion and debate.

Racism as a determinant of health: a protocol for conducting a systematic review and meta-analysis

Background: