882 resultados para Portfolio manager


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The news media industry has changed dramatically into a global business with ever-increasing attention being devoted to entertainment and celebrity across the last 10–20 years. There has also been a growing reliance on images produced by citizens (citizen photojournalism), by media outlets and publishers. It is widely acknowledged that in tandem these changes have shrunk publication opportunities for professional photographers undertaking editorial projects. As a result, photographers are increasingly relying on non-government organisations (NGOs) to gain access to photographing issues and events in developing countries and to expand their economic and portfolio opportunities. This increase in photographers working for and alongside NGOs has given rise to a new genre of editorial photography which I call NGO Reportage. By way of a case study, an exploration of this new genre reveals important issues for photographers working with NGOs and examines the constructed narratives of images contained within these emerging practices.

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We introduce Kamouflage: a new architecture for building theft-resistant password managers. An attacker who steals a laptop or cell phone with a Kamouflage-based password manager is forced to carry out a considerable amount of online work before obtaining any user credentials. We implemented our proposal as a replacement for the built-in Firefox password manager, and provide performance measurements and the results from experiments with large real-world password sets to evaluate the feasibility and effectiveness of our approach. Kamouflage is well suited to become a standard architecture for password managers on mobile devices.

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A known limitation of the Probability Ranking Principle (PRP) is that it does not cater for dependence between documents. Recently, the Quantum Probability Ranking Principle (QPRP) has been proposed, which implicitly captures dependencies between documents through “quantum interference”. This paper explores whether this new ranking principle leads to improved performance for subtopic retrieval, where novelty and diversity is required. In a thorough empirical investigation, models based on the PRP, as well as other recently proposed ranking strategies for subtopic retrieval (i.e. Maximal Marginal Relevance (MMR) and Portfolio Theory(PT)), are compared against the QPRP. On the given task, it is shown that the QPRP outperforms these other ranking strategies. And unlike MMR and PT, one of the main advantages of the QPRP is that no parameter estimation/tuning is required; making the QPRP both simple and effective. This research demonstrates that the application of quantum theory to problems within information retrieval can lead to significant improvements.

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The assumptions underlying the Probability Ranking Principle (PRP) have led to a number of alternative approaches that cater or compensate for the PRP's limitations. In this poster we focus on the Interactive PRP (iPRP), which rejects the assumption of independence between documents made by the PRP. Although the theoretical framework of the iPRP is appealing, no instantiation has been proposed and investigated. In this poster, we propose a possible instantiation of the principle, performing the first empirical comparison of the iPRP against the PRP. For document diversification, our results show that the iPRP is significantly better than the PRP, and comparable to or better than other methods such as Modern Portfolio Theory.

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Ranking documents according to the Probability Ranking Principle has been theoretically shown to guarantee optimal retrieval effectiveness in tasks such as ad hoc document retrieval. This ranking strategy assumes independence among document relevance assessments. This assumption, however, often does not hold, for example in the scenarios where redundancy in retrieved documents is of major concern, as it is the case in the sub–topic retrieval task. In this chapter, we propose a new ranking strategy for sub–topic retrieval that builds upon the interdependent document relevance and topic–oriented models. With respect to the topic– oriented model, we investigate both static and dynamic clustering techniques, aiming to group topically similar documents. Evidence from clusters is then combined with information about document dependencies to form a new document ranking. We compare and contrast the proposed method against state–of–the–art approaches, such as Maximal Marginal Relevance, Portfolio Theory for Information Retrieval, and standard cluster–based diversification strategies. The empirical investigation is performed on the ImageCLEF 2009 Photo Retrieval collection, where images are assessed with respect to sub–topics of a more general query topic. The experimental results show that our approaches outperform the state–of–the–art strategies with respect to a number of diversity measures.

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In this thesis we investigate the use of quantum probability theory for ranking documents. Quantum probability theory is used to estimate the probability of relevance of a document given a user's query. We posit that quantum probability theory can lead to a better estimation of the probability of a document being relevant to a user's query than the common approach, i. e. the Probability Ranking Principle (PRP), which is based upon Kolmogorovian probability theory. Following our hypothesis, we formulate an analogy between the document retrieval scenario and a physical scenario, that of the double slit experiment. Through the analogy, we propose a novel ranking approach, the quantum probability ranking principle (qPRP). Key to our proposal is the presence of quantum interference. Mathematically, this is the statistical deviation between empirical observations and expected values predicted by the Kolmogorovian rule of additivity of probabilities of disjoint events in configurations such that of the double slit experiment. We propose an interpretation of quantum interference in the document ranking scenario, and examine how quantum interference can be effectively estimated for document retrieval. To validate our proposal and to gain more insights about approaches for document ranking, we (1) analyse PRP, qPRP and other ranking approaches, exposing the assumptions underlying their ranking criteria and formulating the conditions for the optimality of the two ranking principles, (2) empirically compare three ranking principles (i. e. PRP, interactive PRP, and qPRP) and two state-of-the-art ranking strategies in two retrieval scenarios, those of ad-hoc retrieval and diversity retrieval, (3) analytically contrast the ranking criteria of the examined approaches, exposing similarities and differences, (4) study the ranking behaviours of approaches alternative to PRP in terms of the kinematics they impose on relevant documents, i. e. by considering the extent and direction of the movements of relevant documents across the ranking recorded when comparing PRP against its alternatives. Our findings show that the effectiveness of the examined ranking approaches strongly depends upon the evaluation context. In the traditional evaluation context of ad-hoc retrieval, PRP is empirically shown to be better or comparable to alternative ranking approaches. However, when we turn to examine evaluation contexts that account for interdependent document relevance (i. e. when the relevance of a document is assessed also with respect to other retrieved documents, as it is the case in the diversity retrieval scenario) then the use of quantum probability theory and thus of qPRP is shown to improve retrieval and ranking effectiveness over the traditional PRP and alternative ranking strategies, such as Maximal Marginal Relevance, Portfolio theory, and Interactive PRP. This work represents a significant step forward regarding the use of quantum theory in information retrieval. It demonstrates in fact that the application of quantum theory to problems within information retrieval can lead to improvements both in modelling power and retrieval effectiveness, allowing the constructions of models that capture the complexity of information retrieval situations. Furthermore, the thesis opens up a number of lines for future research. These include: (1) investigating estimations and approximations of quantum interference in qPRP; (2) exploiting complex numbers for the representation of documents and queries, and; (3) applying the concepts underlying qPRP to tasks other than document ranking.

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The application of artificial neural networks (ANN) in finance is relatively new area of research. We employed ANNs that used both fundamental and technical inputs to predict future prices of widely held Australian stocks and used these predicted prices for stock portfolio selection over a 10-year period (2001-2011). We found that the ANNs generally do well in predicting the direction of stock price movements. The stock portfolios selected by the ANNs with median accuracy are able to generate positive alpha over the 10-year period. More importantly, we found that a portfolio based on randomly selected network configuration had zero chance of resulting in a significantly negative alpha but a 27% chance of yielding a significantly positive alpha. This is in stark contrast to the findings of the research on mutual fund performance where active fund managers with negative alphas outnumber those with positive alphas.

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Recently, botnet, a network of compromised computers, has been recognized as the biggest threat to the Internet. The bots in a botnet communicate with the botnet owner via a communication channel called Command and Control (C & C) channel. There are three main C & C channels: Internet Relay Chat (IRC), Peer-to-Peer (P2P) and web-based protocols. By exploiting the flexibility of the Web 2.0 technology, the web-based botnet has reached a new level of sophistication. In August 2009, such botnet was found on Twitter, one of the most popular Web 2.0 services. In this paper, we will describe a new type of botnet that uses Web 2.0 service as a C & C channel and a temporary storage for their stolen information. We will then propose a novel approach to thwart this type of attack. Our method applies a unique identifier of the computer, an encryption algorithm with session keys and a CAPTCHA verification.

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A salient but rarely explicitly studied characteristic of interfirm relationships is that they can intentionally be formed for finite periods of time. What determines firms' intertemporal choices between different alliance time horizons? Shadow of the future theorists suggest that when an alliance has an explicitly set short-term time frame, there is an increased risk that partners may behave opportunistically. This does not readily explain the high incidence of time-bound alliances being formed. Reconciling insights from the shadow of the future perspective with nascent research on the flexibility of temporary organizations, and shifting the focus from the level of individual transactions to that of strategic alliance portfolios, we argue that firms may be willing to accept a higher risk of opportunism when there are offsetting gains in strategic flexibility in managing their strategic alliance portfolio. Consequently, we hypothesize that environmental factors that increase the need for strategic flexibility—namely, dynamism and complexity in the environment—are likely to increase the relative share of time-bound alliances in strategic alliance portfolios. Our analysis of longitudinal data on the intertemporal alliance choices of a large sample of small and medium-sized enterprises provides support for this argument. Our findings fill an important gap in theory about time horizons in interfirm relationships and temporary organizations and show the importance of separating planned terminations from duration-based performance measures.

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We consider the following problem: users of an organization wish to outsource the storage of sensitive data to a large database server. It is assumed that the server storing the data is untrusted so the data stored have to be encrypted. We further suppose that the manager of the organization has the right to access all data, but a member of the organization can not access any data alone. The member must collaborate with other members to search for the desired data. In this paper, we investigate the notion of threshold privacy preserving keyword search (TPPKS) and define its security requirements. We construct a TPPKS scheme and show the proof of security under the assumptions of intractability of discrete logarithm, decisional Diffie-Hellman and computational Diffie-Hellman problems.

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This project was a step forward in developing a 'descriptive theory' of contracting in the oil and gas industry that reflects the operating environment in which the project manager operates. This study investigates the existing processes and methods used in establishing contracts which are very often prescriptive, and not always appropriate or optimal for a given situation. This study contributes to contracting effectiveness or optimal contracting in the oil and gas industry.

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Ken Talbot was one of Australian mining’s most successful entrepreneurs and rose to the top of his industry to become one of Australia’s wealthiest men. Although the nation’s resources industry is synonymous with global names such as Xstrata, BHP Billiton and Rio Tinto, Ken was an individual who made a big impact on the development and growth of the sector. This case study examines Ken’s achievements, his transition from employee to entrepreneur, and the qualities that enabled him to succeed at such a high level. In particular, it focuses on his Jellinbah and Coppabella mining developments that directly led to the creation of Macarthur Coal and the Talbot Group. By the time of his premature death in an African plane crash in 2010, Ken had amassed a fortune estimated at almost $1 billion and was aged just 59. The last publically available Talbot Group annual report for calendar year 2009 showed that the investment portfolio of the group returned 113 per cent that year. Even throughout the global financial crisis the portfolio made a positive return on investment of no less than 10 per cent. Ken’s sense of mateship and his tremendous people skills were keys to his success in the mining industry and the wider community. In addition to excelling in business, he is also remembered for his philanthropy and leaving 30 per cent of his estate to charity through the Talbot Family Foundation.

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The top-k retrieval problem aims to find the optimal set of k documents from a number of relevant documents given the user’s query. The key issue is to balance the relevance and diversity of the top-k search results. In this paper, we address this problem using Facility Location Analysis taken from Operations Research, where the locations of facilities are optimally chosen according to some criteria. We show how this analysis technique is a generalization of state-of-the-art retrieval models for diversification (such as the Modern Portfolio Theory for Information Retrieval), which treat the top-k search results like “obnoxious facilities” that should be dispersed as far as possible from each other. However, Facility Location Analysis suggests that the top-k search results could be treated like “desirable facilities” to be placed as close as possible to their customers. This leads to a new top-k retrieval model where the best representatives of the relevant documents are selected. In a series of experiments conducted on two TREC diversity collections, we show that significant improvements can be made over the current state-of-the-art through this alternative treatment of the top-k retrieval problem.

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A procurement decision-making model is developed based on a novel integration of leading-edge microeconomic theory and empirically tested in major road and health projects. The model provides a more reliable approach to identifying projects suited to Public-Private-Partnerships (PPPs) and it is expected that the model will enable government to deliver improved value-for-money from their portfolio of PPP projects.

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Objective To assess the usability and validity of the Primary Care Practice Improvement Tool (PC-PIT), a practice performance improvement tool based on 13 key elements identified by a systematic review. It was co-created with a range of partners and designed specifically for primary health care. Design This pilot study examined the PC-PIT using a formative assessment framework and mixed-methods research design. Setting and participants Six high-functioning general practices in Queensland, Australia, between February and July 2013. A total of 28 staff participated — 10 general practitioners, six practice or community nurses, 12 administrators (four practice managers; one business manager and eight reception or general administrative staff). Main outcome measures Readability, content validity and staff perceptions of the PC-PIT. Results The PC-PIT offers an appropriate and acceptable approach to internal quality improvement in general practice. Quantitative assessment scores and qualitative data from all staff identified two areas in which the PC-PIT required modification: a reduction in the indicative reading age, and simplification of governance-related terms and concepts. Conclusion The PC-PIT provides an innovative approach to address the complexity of organisational improvement in general practice and primary health care. This initial validation will be used to develop a suite of supporting, high-quality and free-to-access resources to enhance the use of the PC-PIT in general practice. Based on these findings, a national trial is now underway.