Closing the loop of design and analysis : Parametric modelling tools for early decision support

There is a growing need for parametric design software that communicates building performance feedback in early architectural exploration to support decision-making. This paper examines how the circuit of design and analysis process can be closed to provide active and concurrent feedback between architecture and services engineering domains. It presents the structure for an openly customisable design system that couples parametric modelling and energy analysis software to allow designers to assess the performance of early design iterations quickly. Finally, it discusses how user interactions with the system foster information exchanges that facilitate the sharing of design intelligence across disciplines.

Volatile properties of particles emitted by compressed natural gas and diesel buses during steady state and transient driving modes

Volatile properties of particle emissions from four compressed natural gas (CNG) and four diesel buses were investigated under steady state and transient driving modes on a chassis dynamometer. The exhaust was diluted utilising a full-flow continuous volume sampling system and passed through a thermodenuder at controlled temperature. Particle number concentration and size distribution were measured with a condensation particle counter and a scanning mobility particle sizer, respectively. We show that, while almost all the particles emitted by the CNG buses were in the nanoparticle size range, at least 85% and 98% were removed at 100ºC and 250ºC, respectively. Closer analysis of the volatility of particles emitted during transient cycles showed that volatilisation began at around 40°C with the majority occurring by 80°C. Particles produced during hard acceleration from rest exhibited lower volatility than that produced during other times of the cycle. Based on our results and the observation of ash deposits on the walls of the tailpipes, we suggest that these non-volatile particles were composed mostly of ash from lubricating oil. Heating the diesel bus emissions to 100ºC removed ultrafine particle numbers by 69% to 82% when a nucleation mode was present and just 18% when it was not.

The Use of Social Technology to Support Organisational Knowledge

In the current economy, knowledge has been recognized to be a valuable organisational asset, a crucial factor that aids organisations to succeed in highly competitive environments. Many organisations have begun projects and special initiatives aimed at fostering better knowledge sharing amongst their employees. Not surprisingly, information technology (IT) has been a central element of many of these projects and initiatives, as the potential of emerging information technologies such as Web 2.0 for enabling the process of managing organisational knowledge is recognised. This technology could be used as a collaborative system for knowledge management (KM) within enterprises. Enterprise 2.0 is the application of Web 2.0 in an organisational context. Enterprise 2.0 technologies are web-based social software that facilitate collaboration, communication and information flow in a bidirectional manner: an essential aspect of organisational knowledge management. This chapter explains how Enterprise 2.0 technologies (Web 2.0 technologies within organisations) can support knowledge management. The chapter also explores how such technologies support the codifying (technology-centred) and social network (people-centred) approaches of KM, towards bridging the current gap between these two approaches.

Evidence for CRHR1 in multiple sclerosis using supervised machine learning and meta-analysis in 12 566 individuals

The primary genetic risk factor in multiple sclerosis (MS) is the HLA-DRB1*1501 allele; however, much of the remaining genetic contribution to MS has yet to be elucidated. Several lines of evidence support a role for neuroendocrine system involvement in autoimmunity which may, in part, be genetically determined. Here, we comprehensively investigated variation within eight candidate hypothalamic-pituitary-adrenal (HPA) axis genes and susceptibility to MS. A total of 326 SNPs were investigated in a discovery dataset of 1343 MS cases and 1379 healthy controls of European ancestry using a multi-analytical strategy. Random Forests, a supervised machine-learning algorithm, identified eight intronic SNPs within the corticotrophin-releasing hormone receptor 1 or CRHR1 locus on 17q21.31 as important predictors of MS. On the basis of univariate analyses, six CRHR1 variants were associated with decreased risk for disease following a conservative correction for multiple tests. Independent replication was observed for CRHR1 in a large meta-analysis comprising 2624 MS cases and 7220 healthy controls of European ancestry. Results from a combined meta-analysis of all 3967 MS cases and 8599 controls provide strong evidence for the involvement of CRHR1 in MS. The strongest association was observed for rs242936 (OR = 0.82, 95% CI = 0.74-0.90, P = 9.7 × 10-5). Replicated CRHR1 variants appear to exist on a single associated haplotype. Further investigation of mechanisms involved in HPA axis regulation and response to stress in MS pathogenesis is warranted. © The Author 2010. Published by Oxford University Press. All rights reserved.

The ghrelin signalling system is involved in the consumption of sweets

The gastric-derived orexigenic peptide ghrelin affects brain circuits involved in energy balance as well as in reward. Indeed, ghrelin activates an important reward circuit involved in natural- as well as drug-induced reward, the cholinergic-dopaminergic reward link. It has been hypothesized that there is a common reward mechanism for alcohol and sweet substances in both animals and humans. Alcohol dependent individuals have higher craving for sweets than do healthy controls and the hedonic response to sweet taste may, at least in part, depend on genetic factors. Rat selectively bred for high sucrose intake have higher alcohol consumption than non-sucrose preferring rats and vice versa. In the present study a group of alcohol-consuming individuals selected from a population cohort was investigated for genetic variants of the ghrelin signalling system in relation to both their alcohol and sucrose consumption. Moreover, the effects of GHS-R1A antagonism on voluntary sucrose- intake and operant self-administration, as well as saccharin intake were investigated in preclinical studies using rodents. The effects of peripheral grelin administration on sucrose intake were also examined. Here we found associations with the ghrelin gene haplotypes and increased sucrose consumption, and a trend for the same association was seen in the high alcohol consumers. The preclinical data show that a GHS-R1A antagonist reduces the intake and self-administration of sucrose in rats as well as saccharin intake in mice. Further, ghrelin increases the intake of sucrose in rats. Collectively, our data provide a clear indication that the GHS-R1A antagonists reduces and ghrelin increases the intake of rewarding substances and hence, the central ghrelin signalling system provides a novel target for the development of drug strategies to treat addictive behaviours. © 2011 Landgren et al.

State convergence and the effectiveness of time-memory-data tradeoffs

Various time-memory tradeoffs attacks for stream ciphers have been proposed over the years. However, the claimed success of these attacks assumes the initialisation process of the stream cipher is one-to-one. Some stream cipher proposals do not have a one-to-one initialisation process. In this paper, we examine the impact of this on the success of time-memory-data tradeoff attacks. Under the circumstances, some attacks are more successful than previously claimed while others are less. The conditions for both cases are established.

Using the work system method with freshman information systems students

Recent surveys of information technology management professionals show that understanding business domains in terms of business productivity and cost reduction potential, knowledge of different vertical industry segments and their information requirements, understanding of business processes and client-facing skills are more critical for Information Systems personnel than ever before. In an attempt to restrucuture the information systems curriculum accordingly, our view it that information systems students need to develop an appreciation for organizational work systems in order to understand the operation and significance of information systems within such work systems.

The Measurement of Information System Use: Preliminary Considerations

DeLone and McLean (1992, p. 16) argue that the concept of “system use” has suffered from a “too simplistic definition.” Despite decades of substantial research on system use, the concept is yet to receive strong theoretical scrutiny. Many measures of system use and the development of measures have been often idiosyncratic and lack credibility or comparability. This paper reviews various attempts at conceptualization and measurement of system use and then proposes a re-conceptualization of it as “the level of incorporation of an information system within a user’s processes.” The definition is supported with the theory of work systems, system, and Key-User-Group considerations. We then go on to develop the concept of a Functional- Interface-Point (FIP) and four dimensions of system usage: extent, the proportion of the FIPs used by the business process; frequency, the rate at which FIPs are used by the participants in the process; thoroughness, the level of use of information/functionality provided by the system at an FIP; and attitude towards use, a set of measures that assess the level of comfort, degree of respect and the challenges set forth by the system. The paper argues that the automation level, the proportion of the business process encoded by the information system has a mediating impact on system use. The article concludes with a discussion of some implications of this re-conceptualization and areas for follow on research.

Cellulosic ethanol from sugarcane bagasse in Australia : exploring industry feasibility through systems analysis, techno-economic assessment and pilot plant development

Overcoming many of the constraints to early stage investment in biofuels production from sugarcane bagasse in Australia requires an understanding of the complex technical, economic and systemic challenges associated with the transition of established sugar industry structures from single product agri-businesses to new diversified multi-product biorefineries. While positive investment decisions in new infrastructure requires technically feasible solutions and the attainment of project economic investment thresholds, many other systemic factors will influence the investment decision. These factors include the interrelationships between feedstock availability and energy use, competing product alternatives, technology acceptance and perceptions of project uncertainty and risk. This thesis explores the feasibility of a new cellulosic ethanol industry in Australia based on the large sugarcane fibre (bagasse) resource available. The research explores industry feasibility from multiple angles including the challenges of integrating ethanol production into an established sugarcane processing system, scoping the economic drivers and key variables relating to bioethanol projects and considering the impact of emerging technologies in improving industry feasibility. The opportunities available from pilot scale technology demonstration are also addressed. Systems analysis techniques are used to explore the interrelationships between the existing sugarcane industry and the developing cellulosic biofuels industry. This analysis has resulted in the development of a conceptual framework for a bagassebased cellulosic ethanol industry in Australia and uses this framework to assess the uncertainty in key project factors and investment risk. The analysis showed that the fundamental issue affecting investment in a cellulosic ethanol industry from sugarcane in Australia is the uncertainty in the future price of ethanol and government support that reduces the risks associated with early stage investment is likely to be necessary to promote commercialisation of this novel technology. Comprehensive techno-economic models have been developed and used to assess the potential quantum of ethanol production from sugarcane in Australia, to assess the feasibility of a soda-based biorefinery at the Racecourse Sugar Mill in Mackay, Queensland and to assess the feasibility of reducing the cost of production of fermentable sugars from the in-planta expression of cellulases in sugarcane in Australia. These assessments show that ethanol from sugarcane in Australia has the potential to make a significant contribution to reducing Australia’s transportation fuel requirements from fossil fuels and that economically viable projects exist depending upon assumptions relating to product price, ethanol taxation arrangements and greenhouse gas emission reduction incentives. The conceptual design and development of a novel pilot scale cellulosic ethanol research and development facility is also reported in this thesis. The establishment of this facility enables the technical and economic feasibility of new technologies to be assessed in a multi-partner, collaborative environment. As a key outcome of this work, this study has delivered a facility that will enable novel cellulosic ethanol technologies to be assessed in a low investment risk environment, reducing the potential risks associated with early stage investment in commercial projects and hence promoting more rapid technology uptake. While the study has focussed on an exploration of the feasibility of a commercial cellulosic ethanol industry from sugarcane in Australia, many of the same key issues will be of relevance to other sugarcane industries throughout the world seeking diversification of revenue through the implementation of novel cellulosic ethanol technologies.

User behaviour modelling in a multi-dimensional environment for personalization and recommendation

Handling information overload online, from the user's point of view is a big challenge, especially when the number of websites is growing rapidly due to growth in e-commerce and other related activities. Personalization based on user needs is the key to solving the problem of information overload. Personalization methods help in identifying relevant information, which may be liked by a user. User profile and object profile are the important elements of a personalization system. When creating user and object profiles, most of the existing methods adopt two-dimensional similarity methods based on vector or matrix models in order to find inter-user and inter-object similarity. Moreover, for recommending similar objects to users, personalization systems use the users-users, items-items and users-items similarity measures. In most cases similarity measures such as Euclidian, Manhattan, cosine and many others based on vector or matrix methods are used to find the similarities. Web logs are high-dimensional datasets, consisting of multiple users, multiple searches with many attributes to each. Two-dimensional data analysis methods may often overlook latent relationships that may exist between users and items. In contrast to other studies, this thesis utilises tensors, the high-dimensional data models, to build user and object profiles and to find the inter-relationships between users-users and users-items. To create an improved personalized Web system, this thesis proposes to build three types of profiles: individual user, group users and object profiles utilising decomposition factors of tensor data models. A hybrid recommendation approach utilising group profiles (forming the basis of a collaborative filtering method) and object profiles (forming the basis of a content-based method) in conjunction with individual user profiles (forming the basis of a model based approach) is proposed for making effective recommendations. A tensor-based clustering method is proposed that utilises the outcomes of popular tensor decomposition techniques such as PARAFAC, Tucker and HOSVD to group similar instances. An individual user profile, showing the user's highest interest, is represented by the top dimension values, extracted from the component matrix obtained after tensor decomposition. A group profile, showing similar users and their highest interest, is built by clustering similar users based on tensor decomposed values. A group profile is represented by the top association rules (containing various unique object combinations) that are derived from the searches made by the users of the cluster. An object profile is created to represent similar objects clustered on the basis of their similarity of features. Depending on the category of a user (known, anonymous or frequent visitor to the website), any of the profiles or their combinations is used for making personalized recommendations. A ranking algorithm is also proposed that utilizes the personalized information to order and rank the recommendations. The proposed methodology is evaluated on data collected from a real life car website. Empirical analysis confirms the effectiveness of recommendations made by the proposed approach over other collaborative filtering and content-based recommendation approaches based on two-dimensional data analysis methods.

The impact of knowledge integration on enterprise system success

Despite promising benefits and advantages, there are reports of failures and low realisation of benefits in Enterprise System (ES) initiatives. Among the research on the factors that influence ES success, there is a dearth of studies on the knowledge implications of multiple end-user groups using the same ES application. An ES facilitates the work of several user groups, ranging from strategic management, management, to operational staff, all using the same system for multiple objectives. Given the fundamental characteristics of ES – integration of modules, business process views, and aspects of information transparency – it is necessary that all frequent end-users share a reasonable amount of common knowledge and integrate their knowledge to yield new knowledge. Recent literature on ES implementation highlights the importance of Knowledge Integration (KI) for implementation success. Unfortunately, the importance of KI is often overlooked and little about the role of KI in ES success is known. Many organisations do not achieve the potential benefits from their ES investment because they do not consider the need or their ability to integrate their employees’ knowledge. This study is designed to improve our understanding of the influence of KI among ES end-users on operational ES success. The three objectives of the study are: (I) to identify and validate the antecedents of KI effectiveness, (II) to investigate the impact of KI effectiveness on the goodness of individuals’ ES-knowledge base, and (III) to examine the impact of the goodness of individuals’ ES-knowledge base on the operational ES success. For this purpose, we employ the KI factors identified by Grant (1996) and an IS-impact measurement model from the work of Gable et al. (2008) to examine ES success. The study derives its findings from data gathered from six Malaysian companies in order to obtain the three-fold goal of this thesis as outlined above. The relationships between the antecedents of KI effectiveness and its consequences are tested using 188 responses to a survey representing the views of management and operational employment cohorts. Using statistical methods, we confirm three antecedents of KI effectiveness and the consequences of the antecedents on ES success are validated. The findings demonstrate a statistically positive impact of KI effectiveness of ES success, with KI effectiveness contributing to almost one-third of ES success. This research makes a number of contributions to the understanding of the influence of KI on ES success. First, based on the empirical work using a complete nomological net model, the role of KI effectiveness on ES success is evidenced. Second, the model provides a theoretical lens for a more comprehensive understanding of the impact of KI on the level of ES success. Third, restructuring the dimensions of the knowledge-based theory to fit the context of ES extends its applicability and generalisability to contemporary Information Systems. Fourth, the study develops and validates measures for the antecedents of KI effectiveness. Fifth, the study demonstrates the statistically significant positive influence of the goodness of KI on ES success. From a practical viewpoint, this study emphasises the importance of KI effectiveness as a direct antecedent of ES success. Practical lessons can be drawn from the work done in this study to empirically identify the critical factors among the antecedents of KI effectiveness that should be given attention.