991 resultados para Digital filtering
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The analysis and value of digital evidence in an investigation has been the domain of discourse in the digital forensic community for several years. While many works have considered different approaches to model digital evidence, a comprehensive understanding of the process of merging different evidence items recovered during a forensic analysis is still a distant dream. With the advent of modern technologies, pro-active measures are integral to keeping abreast of all forms of cyber crimes and attacks. This paper motivates the need to formalize the process of analyzing digital evidence from multiple sources simultaneously. In this paper, we present the forensic integration architecture (FIA) which provides a framework for abstracting the evidence source and storage format information from digital evidence and explores the concept of integrating evidence information from multiple sources. The FIA architecture identifies evidence information from multiple sources that enables an investigator to build theories to reconstruct the past. FIA is hierarchically composed of multiple layers and adopts a technology independent approach. FIA is also open and extensible making it simple to adapt to technological changes. We present a case study using a hypothetical car theft case to demonstrate the concepts and illustrate the value it brings into the field.
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The protection of privacy has gained considerable attention recently. In response to this, new privacy protection systems are being introduced. SITDRM is one such system that protects private data through the enforcement of licenses provided by consumers. Prior to supplying data, data owners are expected to construct a detailed license for the potential data users. A license specifies whom, under what conditions, may have what type of access to the protected data. The specification of a license by a data owner binds the enterprise data handling to the consumer’s privacy preferences. However, licenses are very detailed, may reveal the internal structure of the enterprise and need to be kept synchronous with the enterprise privacy policy. To deal with this, we employ the Platform for Privacy Preferences Language (P3P) to communicate enterprise privacy policies to consumers and enable them to easily construct data licenses. A P3P policy is more abstract than a license, allows data owners to specify the purposes for which data are being collected and directly reflects the privacy policy of an enterprise.
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Digital rights management allows information owners to control the use and dissemination of electronic documents via a machine-readable licence. This paper describes the design and implementation of a system for creating and enforcing licences containing location constraints that can be used to restrict access to sensitive documents to a defined area. Documents can be loaded onto a portable device and used in the approved areas, but cannot be used if the device moves to another area. Our contribution includes a taxonomy for access control in the presence of requests to perform non-instantaneous controlled actions.
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This chapter outlines examples of classroom activities that aim to make connections between young people’s everyday experiences with video games and the formal high school curriculum. These classroom activities were developed within the emerging field of digital media literacy. Digital media literacy combines elements of ‘traditional’ approaches to media education with elements of technology and information education (Buckingham, 2007; Warschauer, 2006). It is an educational field that has gained significant attention in recent years. For example, digital media literacy has become a significant objective for media policy makers in response to the increased social and cultural roles of new media technologies and controversies associated with young people’s largely unregulated online participation. Media regulators, educational institutions and independent organizations1 in the United States, Canada, the United Kingdom and Australia have developed digital media literacy initiatives that aim to provide advice to parents, teachers and young people.
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China’s accession to the World Trade Organisation (WTO) has greatly enhanced global interest in investment in the Chinese media market, where demand for digital content is growing rapidly. The East Asian region is positioned as a growth area in many forms of digital content and digital service industries. China is attempting to catch up and take its place as a production centre to offset challenges from neighbouring countries. Meanwhile, Taiwan is seeking to use China both as an export market and as a production site for its digital content. This research investigates entry strategies of Taiwanese digital content firms into the Chinese market. By examining the strategies of a sample of Taiwan-based companies, this study also explores the evolution of their market strategies. However, the focus is on how distinctive business practices such as guanxi are important to Taiwanese business and to relations with Mainland China. This research examines how entrepreneurs manage the characteristics of digital content products and in turn how digital content entrepreneurs adapt to changing market circumstances. This project selected five Taiwan-based digital content companies that have business operations in China: Wang Film, Artkey, CnYES, Somode and iPartment. The study involved a field trip, undertaken between November 2006 and March 2007 to Shanghai and Taiwan to conduct interviews and to gather documentation and archival reports. Six senior managers and nine experts were interviewed. Data were analysed according to Miller’s firm-level entrepreneurship theory, foreign direct investment theory, Life Cycle Model and guanxi philosophy. Most studies of SMEs have focused on free market (capitalist) environments. In contrast, this thesis examines how Taiwanese digital content firms’ strategies apply in the Chinese market. I identified three main types of business strategy: cost-reduction, innovation and quality-enhancement; and four categories of functional strategies: product, marketing, resource acquisition and organizational restructuring. In this study, I introduce the concept of ‘entrepreneurial guanxi’, special relationships that imply mutual obligation, assurance and understanding to secure and exchange favors in entrepreneurial activities. While guanxi is a feature of many studies of business in Pan-Chinese society, it plays an important mediating role in digital content industries. In this thesis, I integrate the ‘Life Cycle Model’ with the dynamic concept of strategy. I outline the significant differences in the evolution of strategy between two types of digital content companies: off-line firms (Wang Film and Artkey) and web-based firms (CnYES, Somode and iPartment). Off-line digital content firms tended to adopt ‘resource acquisition strategies’ in their initial stages and ‘marketing strategies’ in second and subsequent stages. In contrast, web-based digital content companies mainly adopted product and marketing strategies in the early stages, and would adopt innovative approaches towards product and marketing strategies in the whole process of their business development. Some web-based digital content companies also adopted organizational restructuring strategies in the final stage. Finally, I propose the ‘Taxonomy Matrix of Entrepreneurial Strategies’ to emphasise the two dimensions of this matrix: innovation, and the firm’s resource acquisition for entrepreneurial strategy. This matrix is divided into four cells: Effective, Bounded, Conservative, and Impoverished.
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Curriculum initiatives in Australia emphasise the use of technologies and new media in classrooms. Some English teachers might fear this deployment of technologies because we are not all ‘digital natives’ like our students. If we embrace new media forms such as podcasts, blogs, vodcasts, and digital stories, a whole new world of possibilities open up for literary response and recreative texts, with new audiences and publication spaces. This article encourages English teachers to embrace these new digital forms and how shows we can go about it.
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This article discusses a pilot project that adapted the methods of digital storytelling and oral history to capture a range of personal responses to the official Apology to Australia’s Indigenous Peoples delivered by Prime Minister Kevin Rudd on 13 February 2008. The project was an initiative of State Library of Queensland and resulted in a small collection of multimedia stories, incorporating a variety of personal and political perspectives. The article describes how the traditional digital storytelling workshop method was adapted for use in the project, and then proceeds to reflect on the outcomes and continuing life of the project. The article concludes by suggesting that aspects of the resultant model might be applied to other projects carried out by cultural institutions and community-based media organizations.
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This report provides an overview of trends in digital media over the period from 2009-2015. It applies scenario analysis to provide foresight on macro trends in the economy, politics, society and culture that will impact upon digital media market development in Australia, and the prospects for growth in online and digital media industries. It considers developments in the diffusion of innovations in advertising and marketing, mobile media, user-created content, and legal issues for consumers engaging in online transactions.
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We all know that the future of news is digital. But mainstream news providers are still grappling with how to entice more customers to digital news. This paper provides context for a survey currently underway on user intentions towards digital news and entertainment, by exploring: 1. Consumer behaviours and intentions towards digital news and information use; 2. Current trends in the Australian online news and information sector; 3. Issues and emerging opportunities in the Australian (and global) environment. Key influences on digital use of news and information are pricing and access. The paper highlights emerging technical opportunities and flags service gaps as at December 2008. These gaps include multiple disconnects between: 1. Changing user intentions towards online and location based news (news based on a specific locality as chosen by the user) and information; 2. The ability by consumers to act on these intentions via the availability and cost of technologies; 3. Younger users prefer entertainment to news; 4. Current digital offerings of traditional news providers and opportunities. These disconnects present an opportunity for online news suppliers to appraise and resolve. Doing so may enhance their online news and information offering, attract consumers and improve loyalty. Outcomes from this paper will be used to identify knowledge gaps and contribute to the development of further analysis on Australian consumers and their behaviours and intentions towards online news and information. This will be ndertaken via focus groups as part of a broader study by researchers at the Creative Industries Faculty at the Queensland University of Technology supported by the Smart Services Cooperative Research Centre.
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Co-creative media production practices offer important new modes and opportunities for social participation and engagement. In mid-2009 Institute for Creative Industries and Innovation researchers at QUT adapted a specific model of co-creative media production, known as ‘digital storytelling’ and piloted it as an action research platform for facilitating and researching knowledge production based on intergenerational dialogue and exchange. Nine stories were produced and important insights were generated into this particular use of digital storytelling, as well as the impact of institutional constraints and opportunities on the possibilities and outcomes co-creative media practices and processes.
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Public key cryptography, and with it,the ability to compute digital signatures, have made it possible for electronic commerce to flourish. It is thus unsurprising that the proposed Australian NECS will also utilise digital signatures in its system so as to provide a fully automated process from the creation of electronic land title instrument to the digital signing, and electronic lodgment of these instruments. This necessitates an analysis of the fraud risks raised by the usage of digital signatures because a compromise of the integrity of digital signatures will lead to a compromise of the Torrens system itself. This article will show that digital signatures may in fact offer greater security against fraud than handwritten signatures; but to achieve this, digital signatures require an infrastructure whereby each component is properly implemented and managed.
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It is a big challenge to clearly identify the boundary between positive and negative streams. Several attempts have used negative feedback to solve this challenge; however, there are two issues for using negative relevance feedback to improve the effectiveness of information filtering. The first one is how to select constructive negative samples in order to reduce the space of negative documents. The second issue is how to decide noisy extracted features that should be updated based on the selected negative samples. This paper proposes a pattern mining based approach to select some offenders from the negative documents, where an offender can be used to reduce the side effects of noisy features. It also classifies extracted features (i.e., terms) into three categories: positive specific terms, general terms, and negative specific terms. In this way, multiple revising strategies can be used to update extracted features. An iterative learning algorithm is also proposed to implement this approach on RCV1, and substantial experiments show that the proposed approach achieves encouraging performance.
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Over the years, people have often held the hypothesis that negative feedback should be very useful for largely improving the performance of information filtering systems; however, we have not obtained very effective models to support this hypothesis. This paper, proposes an effective model that use negative relevance feedback based on a pattern mining approach to improve extracted features. This study focuses on two main issues of using negative relevance feedback: the selection of constructive negative examples to reduce the space of negative examples; and the revision of existing features based on the selected negative examples. The former selects some offender documents, where offender documents are negative documents that are most likely to be classified in the positive group. The later groups the extracted features into three groups: the positive specific category, general category and negative specific category to easily update the weight. An iterative algorithm is also proposed to implement this approach on RCV1 data collections, and substantial experiments show that the proposed approach achieves encouraging performance.
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An information filtering (IF) system monitors an incoming document stream to find the documents that match the information needs specified by the user profiles. To learn to use the user profiles effectively is one of the most challenging tasks when developing an IF system. With the document selection criteria better defined based on the users’ needs, filtering large streams of information can be more efficient and effective. To learn the user profiles, term-based approaches have been widely used in the IF community because of their simplicity and directness. Term-based approaches are relatively well established. However, these approaches have problems when dealing with polysemy and synonymy, which often lead to an information overload problem. Recently, pattern-based approaches (or Pattern Taxonomy Models (PTM) [160]) have been proposed for IF by the data mining community. These approaches are better at capturing sematic information and have shown encouraging results for improving the effectiveness of the IF system. On the other hand, pattern discovery from large data streams is not computationally efficient. Also, these approaches had to deal with low frequency pattern issues. The measures used by the data mining technique (for example, “support” and “confidences”) to learn the profile have turned out to be not suitable for filtering. They can lead to a mismatch problem. This thesis uses the rough set-based reasoning (term-based) and pattern mining approach as a unified framework for information filtering to overcome the aforementioned problems. This system consists of two stages - topic filtering and pattern mining stages. The topic filtering stage is intended to minimize information overloading by filtering out the most likely irrelevant information based on the user profiles. A novel user-profiles learning method and a theoretical model of the threshold setting have been developed by using rough set decision theory. The second stage (pattern mining) aims at solving the problem of the information mismatch. This stage is precision-oriented. A new document-ranking function has been derived by exploiting the patterns in the pattern taxonomy. The most likely relevant documents were assigned higher scores by the ranking function. Because there is a relatively small amount of documents left after the first stage, the computational cost is markedly reduced; at the same time, pattern discoveries yield more accurate results. The overall performance of the system was improved significantly. The new two-stage information filtering model has been evaluated by extensive experiments. Tests were based on the well-known IR bench-marking processes, using the latest version of the Reuters dataset, namely, the Reuters Corpus Volume 1 (RCV1). The performance of the new two-stage model was compared with both the term-based and data mining-based IF models. The results demonstrate that the proposed information filtering system outperforms significantly the other IF systems, such as the traditional Rocchio IF model, the state-of-the-art term-based models, including the BM25, Support Vector Machines (SVM), and Pattern Taxonomy Model (PTM).