931 resultados para User-centric API Framework
Resumo:
Computer resource allocation represents a significant challenge particularly for multiprocessor systems, which consist of shared computing resources to be allocated among co-runner processes and threads. While an efficient resource allocation would result in a highly efficient and stable overall multiprocessor system and individual thread performance, ineffective poor resource allocation causes significant performance bottlenecks even for the system with high computing resources. This thesis proposes a cache aware adaptive closed loop scheduling framework as an efficient resource allocation strategy for the highly dynamic resource management problem, which requires instant estimation of highly uncertain and unpredictable resource patterns. Many different approaches to this highly dynamic resource allocation problem have been developed but neither the dynamic nature nor the time-varying and uncertain characteristics of the resource allocation problem is well considered. These approaches facilitate either static and dynamic optimization methods or advanced scheduling algorithms such as the Proportional Fair (PFair) scheduling algorithm. Some of these approaches, which consider the dynamic nature of multiprocessor systems, apply only a basic closed loop system; hence, they fail to take the time-varying and uncertainty of the system into account. Therefore, further research into the multiprocessor resource allocation is required. Our closed loop cache aware adaptive scheduling framework takes the resource availability and the resource usage patterns into account by measuring time-varying factors such as cache miss counts, stalls and instruction counts. More specifically, the cache usage pattern of the thread is identified using QR recursive least square algorithm (RLS) and cache miss count time series statistics. For the identified cache resource dynamics, our closed loop cache aware adaptive scheduling framework enforces instruction fairness for the threads. Fairness in the context of our research project is defined as a resource allocation equity, which reduces corunner thread dependence in a shared resource environment. In this way, instruction count degradation due to shared cache resource conflicts is overcome. In this respect, our closed loop cache aware adaptive scheduling framework contributes to the research field in two major and three minor aspects. The two major contributions lead to the cache aware scheduling system. The first major contribution is the development of the execution fairness algorithm, which degrades the co-runner cache impact on the thread performance. The second contribution is the development of relevant mathematical models, such as thread execution pattern and cache access pattern models, which in fact formulate the execution fairness algorithm in terms of mathematical quantities. Following the development of the cache aware scheduling system, our adaptive self-tuning control framework is constructed to add an adaptive closed loop aspect to the cache aware scheduling system. This control framework in fact consists of two main components: the parameter estimator, and the controller design module. The first minor contribution is the development of the parameter estimators; the QR Recursive Least Square(RLS) algorithm is applied into our closed loop cache aware adaptive scheduling framework to estimate highly uncertain and time-varying cache resource patterns of threads. The second minor contribution is the designing of a controller design module; the algebraic controller design algorithm, Pole Placement, is utilized to design the relevant controller, which is able to provide desired timevarying control action. The adaptive self-tuning control framework and cache aware scheduling system in fact constitute our final framework, closed loop cache aware adaptive scheduling framework. The third minor contribution is to validate this cache aware adaptive closed loop scheduling framework efficiency in overwhelming the co-runner cache dependency. The timeseries statistical counters are developed for M-Sim Multi-Core Simulator; and the theoretical findings and mathematical formulations are applied as MATLAB m-file software codes. In this way, the overall framework is tested and experiment outcomes are analyzed. According to our experiment outcomes, it is concluded that our closed loop cache aware adaptive scheduling framework successfully drives co-runner cache dependent thread instruction count to co-runner independent instruction count with an error margin up to 25% in case cache is highly utilized. In addition, thread cache access pattern is also estimated with 75% accuracy.
Resumo:
This report is an update of an earlier version produced in January 2010 (see Carrington et al. 2010) which remains as an ePrint through the project’s home page. The report provides an introduction to our analyses of extant secondary data with respect to violent acts and incidents relating to males living in rural settings in Australia using data which were available in public data bases at the time of production. It clarifies important aspects of our overall approach primarily by concentrating on three elements that required early scoping and resolution.
Resumo:
PPP is a general term covering all contracted relationships between the public and private sectors to produce a public asset or to deliver a public service. Its major advantage lies in utilising resources from the private sector to alleviate some of the financial burdens of the government. The Asian financial turmoil in the late 1990s has imposed enormous pressure on the budget of the Hong Kong Special Administrative Region (HKSAR) Government. With a continuous outcry for better public services due to the rapid development of Hong Kong, alternative financing models need to be sought to ensure sustainability. Hong Kong has the advantage of being the international gateway to Mainland China, and with this benefit has attracted overseas enterprises to base their offices in Hong Kong for the Asian market. Obviously the private sector has much to contribute. The HKSAR Government has realised the benefits of using PPP in Hong Kong as well as the success achieved overseas. But a more thorough research is needed to develop the most suitable practice of PPP in terms of project nature, project complexity, project type and project scale under which PPP is most appropriate for Hong Kong. This paper provides an initial report of a research project being funded by the Research Grants Council (RGC) of the HKSAR. The project aims to evaluate the benefits and risks of PPP adopted in Australia and the United Kingdom, and from these previous experiences to develop a best practice framework for implementing PPP in Hong Kong. It firstly reports on the status of PPP development trend and the hands-on experiences which have been drawn in these countries. Qualitative and quantitative research methods applied in conducting the research are discussed. The likely impacts of the study are highlighted. It is believed that the construction industry and the government would benefit a lot as a result of this study, and further procurement and project financing options would be opened up for delivering better future public service.
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Six Sigma is considered to be an important management philosophy to obtain satisfied customers. But financial service organisations have been slow to adopt Six Sigma issues so far. Despite the extensive effort that has been invested and benefits that can be obtained, the systematic implementation of Six Sigma in financial service organisations is limited. As a company wide implementation framework is missing so far, this paper tries to fill this gap. Based on theory, a conceptual framework is developed and evaluated by experts from financial institutions. The results show that it is very important to link Six Sigma with the strategic as well as the operations level. Furthermore, although Six Sigma is a very important method for improving quality of processes others such as Lean Management are also used This requires a superior project portfolio management to coordinate resources and projects of Six Sigma with the other methods used. Beside the theoretical contribution, the framework can be used by financial service companies to evaluate their Six Sigma activities. Thus, the framework grounded through literature and empirical data will be a useful guide for sustainable and successful implementation of a Six Sigma initiative in financial service organisations.
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Purpose: Web search engines are frequently used by people to locate information on the Internet. However, not all queries have an informational goal. Instead of information, some people may be looking for specific web sites or may wish to conduct transactions with web services. This paper aims to focus on automatically classifying the different user intents behind web queries. Design/methodology/approach: For the research reported in this paper, 130,000 web search engine queries are categorized as informational, navigational, or transactional using a k-means clustering approach based on a variety of query traits. Findings: The research findings show that more than 75 percent of web queries (clustered into eight classifications) are informational in nature, with about 12 percent each for navigational and transactional. Results also show that web queries fall into eight clusters, six primarily informational, and one each of primarily transactional and navigational. Research limitations/implications: This study provides an important contribution to web search literature because it provides information about the goals of searchers and a method for automatically classifying the intents of the user queries. Automatic classification of user intent can lead to improved web search engines by tailoring results to specific user needs. Practical implications: The paper discusses how web search engines can use automatically classified user queries to provide more targeted and relevant results in web searching by implementing a real time classification method as presented in this research. Originality/value: This research investigates a new application of a method for automatically classifying the intent of user queries. There has been limited research to date on automatically classifying the user intent of web queries, even though the pay-off for web search engines can be quite beneficial. © Emerald Group Publishing Limited.
Resumo:
This special issue of the Journal of Urban Technology brings together five articles that are based on presentations given at the Street Computing workshop held on 24 November 2009 in Melbourne in conjunction with the Australian Computer-Human Interaction conference (OZCHI 2009). Our own article introduces the Street Computing vision and explores the potential, challenges and foundations of this research vision. In order to do so, we first look at the currently available sources of information and discuss their link to existing research efforts. Section 2 then introduces the notion of Street Computing and our research approach in more detail. Section 3 looks beyond the core concept itself and summarises related work in this field of interest.
Resumo:
Discovering proper search intents is a vi- tal process to return desired results. It is constantly a hot research topic regarding information retrieval in recent years. Existing methods are mainly limited by utilizing context-based mining, query expansion, and user profiling techniques, which are still suffering from the issue of ambiguity in search queries. In this pa- per, we introduce a novel ontology-based approach in terms of a world knowledge base in order to construct personalized ontologies for identifying adequate con- cept levels for matching user search intents. An iter- ative mining algorithm is designed for evaluating po- tential intents level by level until meeting the best re- sult. The propose-to-attempt approach is evaluated in a large volume RCV1 data set, and experimental results indicate a distinct improvement on top precision after compared with baseline models.
Resumo:
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.
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This research examines why and how brand owners in China adopt and use mobile media in marketing campaigns to deliver co-creation brand experiences and build consumer relationships. China represents an interesting case to study as it has leapfrogged into the age of consumer society and mobile media adoption. As the largest mobile market globally, it has experienced the intensity of mobile technology diffusion; and with it the rise of mobile consumer culture and participatory culture. Further, the rising individualism and the socio-cultural heritage in collectivism serve as a structuring tension in how mobile media is leveraged in marketing to cater to consumers' desires for individuality and social interaction. First, through expert interviews guided by the technology-organization-environment (TOE) framework (Tornatzky & Fleischer, 1990) as well as integrating innovation diffusion theory (E. Rogers, 2003), this research attempts to fill the gap of theoretical application in mobile marketing adoption at the firm level in China, and unravel the adoption factors of mobile marketing by brand owners in China. In total, 27 semi-structured interviews were conducted with key industry informants from mobile agencies, traditional agencies, venture capital firms, mobile content and service providers, mobile portals, and marketing management at brand owners. Second, based on case studies in China, this research investigates the use of mobile marketing to facilitate innovative co-creation of brand experience to cater to both individualistic as well as collective tendencies and desires amongst Chinese consumers. Through multiple case studies of the campaigns conducted by Nokia, Clean & Clear, and The North Face, and informed by in-depth interviews and document analysis, this research analyses the role of mobile media in marketing campaigns along three dimensions: the role of mobile media in content generation and consumption, the centrality of mobile media as text, tools or platforms; and the interactive environment. Specifically, the cases are organized along the spectrum from user-generated content to corporate-generated content, mobile media's role from being supplementary to it being central, and from a virtual environment to a hybrid environment. Overall, these cases demonstrate how brand owners adapt mobile media as text, tools, platforms, and environments to deliver co-creation brand experiences exploiting both individualistic as well as collective tendencies and desires amongst Chinese consumers. This research contributes to the literature on firm adoption of mobile marketing, and the role of the mobile media in facilitating co-creation experiences for Chinese consumers. It develops a model of the technological, organizational and environmental factors influencing mobile marketing adoption by firms, and provides a model explaining the role of mobile media in facilitating brand experience co-creation. The findings also demonstrate that mobile media can be leveraged to facilitate co-creation brand experience to generate added value; and meanwhile cater to both the rising individualism and the deep-seated collectivism of Chinese consumers. Empirically, it assists industry practitioners in understanding the adoption of mobile marketing in China, especially those on the supply side in order to improve their offerings and propositions. It also assists brand owners and agencies in designing their mobile marketing strategies to build consumer relationships in China.
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Safety culture is a concept that has long been accepted in high risk industries such as aviation, nuclear industries and mining, however, considerable research is now being undertaken within the construction sector, with varying levels of success. The current paper discusses three recent interlocked projects that have had some success in the Australian construction industry. The first project examined the development and implementation of a safety competency framework targeted at safety critical positions across first tier construction organisations. Combining qualitative and quantitative methods, the project: developed a matrix of safety critical positions (n=11) and safety managements tasks (SMTs; n=39); mapped the process steps for their acquisition and ongoing development; detailed the knowledge, skills and behaviours required for all SMTs; and outlined organisational cultural outcomes that could be anticipated in a successful implementation of the framework. The second project extended research on safety competency and leadership to develop behavioural guidelines for leaders to drive safety culture change down to second tier companies. This was designed to assist smaller construction companies to customise their own competency framework and develop implementation guidelines that match their aspirations and resources. The third interlocked project explored the use of safety effectiveness indicators (SEIs) as an industry-relevant assessment tool for reducing risk on construction sites. With direct linkages to safety competencies and safety management tasks, the SEIs are the next step towards an integrated safety cultural approach to safety and extend the concept of positive performance indicators (PPIs) by providing a valid, reliable, and user friendly measurement platform. Taken together, the results of the interlocked projects suggest that safety culture research has many potential benefits for the construction industry, particularly when research is conducted in partnership with industry stakeholders. Suggestions are made for future research, including further application and testing of the safety competency framework and aligning SEIs across construction projects of varying size, location and design.
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University libraries play an important role in contributing to student and faculty members’ academic achievement. This study examines perceptions of university library usage to consider factors that influence achievement of students, academics and administrators. A thorough review of relevant literature examined approaches to determining user satisfaction of students and faculty, and factors that influence library usage. It highlighted the value of usage on educational performance. It enabled development of a theoretical framework leading to the Factors of Academic Library Usage (FALU) model, which was developed to investigate the effect of usage factors. FALU was tested in Kuwait university libraries. The study used validated questionnaires from 792 students, 143 academics and 121 administrators to measure five library factors. Interviews were conducted across the three University libraries. The findings are useful in measuring the correlation between the current academic library usage and educational performance.
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The issue of carbon sequestration rights has become topical following the United Nations Convention on Climate Change and the subsequent Kyoto Protocol which identified emissions trading as one of the mechanisms to reduce greenhouse gas emissions. The Australian Government has responded by initiating the Garnaut Climate Change Review which in its final report, proposed that an emissions trading scheme be introduced and set out some of the desirable features of such a trading scheme. This proposal has been the subject of much debate and at this stage there still seems to be little clarity surrounding the topic of emissions trading in Australia. The treatment of rights to carbon sequestered in vegetation is also an issue when reconciled with the system of land tenure and ownership in many jurisdictions. These carbon property rights are treated differently in different Australian and international jurisdictions ranging from recognition of their new and unique nature to fitting them within a more established common law framework, e.g.a profit a prendre. This paper identifies the treatment of these sequestered carbon rights within the wider property rights framework in Australia and considers issues that this treatment may inflict on land holders when there is a fracturing of ownership between the rights of the carbon in vegetation and the ownership of the land.
Resumo:
In response to the need to leverage private finance and the lack of competition in some parts of the Australian public sector infrastructure market, especially in the very large economic infrastructure sector procured using Pubic Private Partnerships, the Australian Federal government has demonstrated its desire to attract new sources of in-bound foreign direct investment (FDI). This paper aims to report on progress towards an investigation into the determinants of multinational contractors’ willingness to bid for Australian public sector major infrastructure projects. This research deploys Dunning’s eclectic theory for the first time in terms of in-bound FDI by multinational contractors into Australia. Elsewhere, the authors have developed Dunning’s principal hypothesis to suit the context of this research and to address a weakness arising in this hypothesis that is based on a nominal approach to the factors in Dunning's eclectic framework and which fails to speak to the relative explanatory power of these factors. In this paper, a first stage test of the authors' development of Dunning's hypothesis is presented by way of an initial review of secondary data vis-à-vis the selected sector (roads and bridges) in Australia (as the host location) and with respect to four selected home countries (China; Japan; Spain; and US). In doing so, the next stage in the research method concerning sampling and case studies is also further developed and described in this paper. In conclusion, the extent to which the initial review of secondary data suggests the relative importance of the factors in the eclectic framework is considered. It is noted that more robust conclusions are expected following the future planned stages of the research including primary data from the case studies and a global survey of the world’s largest contractors and which is briefly previewed. Finally, and beyond theoretical contributions expected from the overall approach taken to developing and testing Dunning’s framework, other expected contributions concerning research method and practical implications are mentioned.
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The lack of satisfactory consensus for characterizing the system intelligence and structured analytical decision models has inhibited the developers and practitioners to understand and configure optimum intelligent building systems in a fully informed manner. So far, little research has been conducted in this aspect. This research is designed to identify the key intelligent indicators, and develop analytical models for computing the system intelligence score of smart building system in the intelligent building. The integrated building management system (IBMS) was used as an illustrative example to present a framework. The models presented in this study applied the system intelligence theory, and the conceptual analytical framework. A total of 16 key intelligent indicators were first identified from a general survey. Then, two multi-criteria decision making (MCDM) approaches, the analytic hierarchy process (AHP) and analytic network process (ANP), were employed to develop the system intelligence analytical models. Top intelligence indicators of IBMS include: self-diagnostic of operation deviations; adaptive limiting control algorithm; and, year-round time schedule performance. The developed conceptual framework was then transformed to the practical model. The effectiveness of the practical model was evaluated by means of expert validation. The main contribution of this research is to promote understanding of the intelligent indicators, and to set the foundation for a systemic framework that provide developers and building stakeholders a consolidated inclusive tool for the system intelligence evaluation of the proposed components design configurations.