University of Salford

About: University of Salford is a education organization based out in Salford, Manchester, United Kingdom. It is known for research contribution in the topics: Population & Context (language use). The organization has 13049 authors who have published 22957 publications receiving 537330 citations. The organization is also known as: University of Salford Manchester & The University of Salford Manchester.

On-Line and on Message? Candidate Websites in the 2001 General Election

Abstract: The 2001 General Election generated considerable interest and also much criticism of politicians' use of the Internet. Via content analysis, search engines and database material, this article exami...

Achieving effective cloud search services: multi-keyword ranked search over encrypted cloud data supporting synonym query

Abstract: In recent years, consumer-centric cloud computing paradigm has emerged as the development of smart electronic devices combined with the emerging cloud computing technologies. A variety of cloud services are delivered to the consumers with the premise that an effective and efficient cloud search service is achieved. For consumers, they want to find the most relevant products or data, which is highly desirable in the "pay-as-you use" cloud computing paradigm. As sensitive data (such as photo albums, emails, personal health records, financial records, etc.) are encrypted before outsourcing to cloud, traditional keyword search techniques are useless. Meanwhile, existing search approaches over encrypted cloud data support only exact or fuzzy keyword search, but not semantics-based multi-keyword ranked search. Therefore, how to enable an effective searchable system with support of ranked search remains a very challenging problem. This paper proposes an effective approach to solve the problem of multi-keyword ranked search over encrypted cloud data supporting synonym queries. The main contribution of this paper is summarized in two aspects: multi-keyword ranked search to achieve more accurate search results and synonym-based search to support synonym queries. Extensive experiments on real-world dataset were performed to validate the approach, showing that the proposed solution is very effective and efficient for multikeyword ranked searching in a cloud environment.

Standardized comparison of performance indicators in trauma: a new approach to case-mix variation

Abstract: An institution's trauma survival rate can be compared with that predicted by TRISS using definitive outcome-based evaluation. This examines W, the difference between actual and predicted survival rates; Z, the statistical significance of this difference; and M, a measure of the similarity of injury severity mix to the prediction data base. However, it is possible for two institutions with the same survival rate within each band of injury severity to have very different W and Z scores whilst retaining a similar M score. Clearly this is unsatisfactory. A new statistic, Ws, is therefore proposed, which is standardized with respect to injury severity mix, producing more accurate comparisons between different institutions. Confidence intervals are used to graphically illustrate the magnitude of Ws, its direction, accuracy, and statistical significance. Data from the U.K. Major Trauma Outcome Study are used to demonstrate the calculations and presentation of Ws and its advantages.