Exchange design patterns for electronic intermediairies

Intermediaries have introduced electronic services with varying success. One of the problems an intermediary faces is deciding what kind of exchange service it should offer to its customers and suppliers. For example, should it only provide a catalogue or should it also enable customers to order products? Developing the right exchange design is a complex undertaking because of the many design options on the one hand and the interests of multiple actors to be considered on the other. This is far more difficult than simple prescriptions like ‘creating a win-win situation’ suggest. We address this problem by developing design patterns for the exchanges between customers, intermediary, and suppliers related to role, linkage, transparency, and ovelty choices. For developing these design patterns, we studied four distinct electronic intermediaries and dentified exchange design choices that require trade-offs relating to the interests of customers, intermediary, and suppliers. The exchange design patterns contribute to the development of design theory for electronic intermediaries by filling a gap between basic business models and detailed business process designs.

A rights management approach to protection of privacy in a cloud of electronic health records

A patient-centric DRM approach is proposed for protecting privacy of health records stored in a cloud storage based on the patient's preferences and without the need to trust the service provider. Contrary to the current server-side access control solutions, this approach protects the privacy of records from the service provider, and also controls the usage of data after it is released to an authorized user.

Tool-supported dataflow analysis of a security-critical embedded device

Defence organisations perform information security evaluations to confirm that electronic communications devices are safe to use in security-critical situations. Such evaluations include tracing all possible dataflow paths through the device, but this process is tedious and error-prone, so automated reachability analysis tools are needed to make security evaluations faster and more accurate. Previous research has produced a tool, SIFA, for dataflow analysis of basic digital circuitry, but it cannot analyse dataflow through microprocessors embedded within the circuit since this depends on the software they run. We have developed a static analysis tool that produces SIFA compatible dataflow graphs from embedded microcontroller programs written in C. In this paper we present a case study which shows how this new capability supports combined hardware and software dataflow analyses of a security critical communications device.

The child, the text and the teacher : reading primers and reading instruction

From the late sixteenth century, in response to the problem of how best to teach children to read, a variety of texts such as primers, spellers and readers were produced in England for vernacular instruction. This paper describes how these materials were used by teachers to develop first, a specific religious understanding according to the stricture of the time and second, a moral reading practice that provided the child with a guide to secular conduct. The analysis focuses on the use of these texts as a productive means for shaping the child-reader in the context of newly emerging educational spaces which fostered a particular, morally formative relation among teacher, child and text.

Relevance feature discovery for text analysis

It is a big challenge to guarantee the quality of discovered relevance features in text documents for describing user preferences because of the large number of terms, patterns, and noise. Most existing popular text mining and classification methods have adopted term-based approaches. However, they have all suffered from the problems of polysemy and synonymy. Over the years, people have often held the hypothesis that pattern-based methods should perform better than term- based ones in describing user preferences, but many experiments do not support this hypothesis. This research presents a promising method, Relevance Feature Discovery (RFD), for solving this challenging issue. It discovers both positive and negative patterns in text documents as high-level features in order to accurately weight low-level features (terms) based on their specificity and their distributions in the high-level features. The thesis also introduces an adaptive model (called ARFD) to enhance the exibility of using RFD in adaptive environment. ARFD automatically updates the system's knowledge based on a sliding window over new incoming feedback documents. It can efficiently decide which incoming documents can bring in new knowledge into the system. Substantial experiments using the proposed models on Reuters Corpus Volume 1 and TREC topics show that the proposed models significantly outperform both the state-of-the-art term-based methods underpinned by Okapi BM25, Rocchio or Support Vector Machine and other pattern-based methods.

Towards semantic search and inference in electronic medical records : an approach using concept-based information retrieval

For more than a decade research in the field of context aware computing has aimed to find ways to exploit situational information that can be detected by mobile computing and sensor technologies. The goal is to provide people with new and improved applications, enhanced functionality and better use experience (Dey, 2001). Early applications focused on representing or computing on physical parameters, such as showing your location and the location of people or things around you. Such applications might show where the next bus is, which of your friends is in the vicinity and so on. With the advent of social networking software and microblogging sites such as Facebook and Twitter, recommender systems and so on context-aware computing is moving towards mining the social web in order to provide better representations and understanding of context, including social context. In this paper we begin by recapping different theoretical framings of context. We then discuss the problem of context- aware computing from a design perspective.

Rule-based approach for identifying assertions in clinical free-text data

A rule-based approach for classifying previously identified medical concepts in the clinical free text into an assertion category is presented. There are six different categories of assertions for the task: Present, Absent, Possible, Conditional, Hypothetical and Not associated with the patient. The assertion classification algorithms were largely based on extending the popular NegEx and Context algorithms. In addition, a health based clinical terminology called SNOMED CT and other publicly available dictionaries were used to classify assertions, which did not fit the NegEx/Context model. The data for this task includes discharge summaries from Partners HealthCare and from Beth Israel Deaconess Medical Centre, as well as discharge summaries and progress notes from University of Pittsburgh Medical Centre. The set consists of 349 discharge reports, each with pairs of ground truth concept and assertion files for system development, and 477 reports for evaluation. The system’s performance on the evaluation data set was 0.83, 0.83 and 0.83 for recall, precision and F1-measure, respectively. Although the rule-based system shows promise, further improvements can be made by incorporating machine learning approaches.

Privacy oriented access control for electronic health records

Security and privacy in electronic health record systems have been hindering the growth of e-health systems since their emergence. The development of policies that satisfy the security and privacy requirements of different stakeholders in healthcare has proven to be difficult. But, these requirements have to be met if the systems developed are to succeed in achieving their intended goals. Access control is a fundamental security barrier for securing data in healthcare information systems. In this paper we present an access control model for electronic health records. We address patient privacy requirements, confidentiality of private information and the need for flexible access for health professionals for electronic health records. We carefully combine three existing access control models and present a novel access control model for EHRs which satisfies requirements of electronic health records.

Text mining and probabilistic language modeling for online review spam detecting

In the era of Web 2.0, huge volumes of consumer reviews are posted to the Internet every day. Manual approaches to detecting and analyzing fake reviews (i.e., spam) are not practical due to the problem of information overload. However, the design and development of automated methods of detecting fake reviews is a challenging research problem. The main reason is that fake reviews are specifically composed to mislead readers, so they may appear the same as legitimate reviews (i.e., ham). As a result, discriminatory features that would enable individual reviews to be classified as spam or ham may not be available. Guided by the design science research methodology, the main contribution of this study is the design and instantiation of novel computational models for detecting fake reviews. In particular, a novel text mining model is developed and integrated into a semantic language model for the detection of untruthful reviews. The models are then evaluated based on a real-world dataset collected from amazon.com. The results of our experiments confirm that the proposed models outperform other well-known baseline models in detecting fake reviews. To the best of our knowledge, the work discussed in this article represents the first successful attempt to apply text mining methods and semantic language models to the detection of fake consumer reviews. A managerial implication of our research is that firms can apply our design artifacts to monitor online consumer reviews to develop effective marketing or product design strategies based on genuine consumer feedback posted to the Internet.

Mining a data reasoning model for personalized text classification

It is a big challenge to acquire correct user profiles for personalized text classification since users may be unsure in providing their interests. Traditional approaches to user profiling adopt machine learning (ML) to automatically discover classification knowledge from explicit user feedback in describing personal interests. However, the accuracy of ML-based methods cannot be significantly improved in many cases due to the term independence assumption and uncertainties associated with them. This paper presents a novel relevance feedback approach for personalized text classification. It basically applies data mining to discover knowledge from relevant and non-relevant text and constraints specific knowledge by reasoning rules to eliminate some conflicting information. We also developed a Dempster-Shafer (DS) approach as the means to utilise the specific knowledge to build high-quality data models for classification. The experimental results conducted on Reuters Corpus Volume 1 and TREC topics support that the proposed technique achieves encouraging performance in comparing with the state-of-the-art relevance feedback models.

The market structure and characteristics of electronic games

A multi-billion dollar industry, electronic games have been experiencing strong and rapid growth in recent times. The world of games is not only exciting due to the magnificent growth of the industry however, but due to a host of other factors. This chapter explores electronic games, providing an analysis of the industry, key motivators for game play, the game medium and academic research concerning the effects of play. It also reviews the emerging relationship games share with sport, recognizing that they can replicate sports, facilitate sports participation and be played as a sport. These are complex relationships that have not yet been comprehensively studied. The current chapter serves to draw academic attention to the area and presents ideas for future research.

Controlled growth of carbon nanotubes for electronic and photovoltaic applications

Carbon nanotubes (CNTs), experimentally observed for the first time twenty years ago, have triggered an unprecedented research effort, on the account of their astonishing structural, mechanical and electronic properties. Unfortunately, the current inability in predicting the CNTs’ properties and the difficulty in controlling their position on a substrate are often limiting factors for the application of this material in actual devices. This research aims at the creation of specific methodologies for controlled synthesis of CNTs, leading to effectively employ them in various fields of electronics, e.g. photovoltaics. Focused Ion Beam (FIB) patterning of Si surfaces is here proposed as a means for ordering the assembly of vertical-aligned CNTs. With this technique, substrates with specific nano-structured morphologies have been prepared, enabling a high degree of control over CNTs’ position and size. On these nano-structured substrates, the growth of CNTs has been realized by chemical vapor deposition (CVD), i.e. thermal decomposition of hydrocarbon gases over a heated catalyst. The most common materials used as catalysts in CVD are transition metals like Fe and Ni; however, their presence in the CNT products often results in shortcomings for electronic applications, especially for those based on silicon, being the metallic impurities incompatible with very-large-scale integration (VLSI) technology. In the present work the role of Ge dots as an alternative catalysts for CNTs synthesis on Si substrates has been thoroughly assessed, finding a close connection between the catalytic activity of such material and the CVD conditions, which can affect both size and morphology of the dots. Successful CNT growths from Ge dots have been obtained by CVD at temperatures ranging from 750 to 1000°C, with mixtures of acetylene and hydrogen in an argon carrier gas. The morphology of the Si surface is observed to play a crucial role for the outcome of the CNT synthesis: natural (i.e. chemical etching) and artificial (i.e. FIB patterning, nanoindentation) means of altering this morphology in a controlled way have been then explored to optimize the CNTs yield. All the knowledge acquired in this study has been finally applied to synthesize CNTs on transparent conductive electrodes (indium-tin oxide, ITO, coated glasses), for the creation of a new class of anodes for organic photovoltaics. An accurate procedure has been established which guarantees a controlled inclusion of CNTs on ITO films, preserving their optical and electrical properties. By using this set of conditions, a CNTenhanced electrode has been built, contributing to improve the power conversion efficiency of polymeric solar cells.

Homo- and heteronuclear meso,meso-(E)-Ethene-1,2-diyl-Linked Diporphyrins : preparation, X-ray crystal structure, electronic absorption and emission spectra and density functional theory calculations

Homo-and heteronuclear meso,meso-(E)-ethene-1,2-diyl-linked diporphyrins have been prepared by the Suzuki coupling of porphyrinylboronates and iodovinylporphyrins. Combinations comprising 5,10,15-triphenylporphyrin (TriPP) on both ends of the ethene-1,2-diyl bridge M 210 (M 2=H 2/Ni, Ni 2, Ni/Zn, H 4, H 2Zn, Zn 2) and 5,15-bis(3,5-di-tert-butylphenyl)porphyrinato-nickel(II) on one end and H 2, Ni, and ZnTriPP on the other (M 211), enable the first studies of this class of compounds possessing intrinsic polarity. The compounds were characterized by electronic absorption and steady state emission spectra, 1H NMR spectra, and for the Ni 2 bis(TriPP) complex Ni 210, single crystal X-ray structure determination. The crystal structure shows ruffled distortions of the porphyrin rings, typical of Ni II porphyrins, and the (E)-C 2H 2 bridge makes a dihedral angle of 50° with the mean planes of the macrocycles. The result is a stepped parallel arrangement of the porphyrin rings. The dihedral angles in the solid state reflect the interplay of steric and electronic effects of the bridge on interporphyrin communication. The emission spectra in particular, suggest energy transfer across the bridge is fast in conformations in which the bridge is nearly coplanar with the rings. Comparisons of the fluorescence behaviour of H 410 and H 2Ni10 show strong quenching of the free base fluorescence when the complex is excited at the lower energy component of the Soret band, a feature associated in the literature with more planar conformations. TDDFT calculations on the gas-phase optimized geometry of Ni 210 reproduce the features of the experimental electronic absorption spectrum within 0.1 eV. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Loss and grief at the heart of text messages [REVIEW]

WHAT if you lost someone you loved? What if you had to let go for the sake of your own sanity? Lachlan Philpott's Colder and Dennis Kelly's Orphans, playing as part of La Boite's and Queensland Theatre Company's independents programs, are emotionally and textually dense theatrical works...