Database relation watermarking resilient against secondary watermarking attacks

There has been tremendous interest in watermarking multimedia content during the past two decades, mainly for proving ownership and detecting tamper. Digital fingerprinting, that deals with identifying malicious user(s), has also received significant attention. While extensive work has been carried out in watermarking of images, other multimedia objects still have enormous research potential. Watermarking database relations is one of the several areas which demand research focus owing to the commercial implications of database theft. Recently, there has been little progress in database watermarking, with most of the watermarking schemes modeled after the irreversible database watermarking scheme proposed by Agrawal and Kiernan. Reversibility is the ability to re-generate the original (unmarked) relation from the watermarked relation using a secret key. As explained in our paper, reversible watermarking schemes provide greater security against secondary watermarking attacks, where an attacker watermarks an already marked relation in an attempt to erase the original watermark. This paper proposes an improvement over the reversible and blind watermarking scheme presented in [5], identifying and eliminating a critical problem with the previous model. Experiments showing that the average watermark detection rate is around 91% even with attacker distorting half of the attributes. The current scheme provides security against secondary watermarking attacks.

Reversible and blind database watermarking using difference expansion

Database watermarking has received significant research attention in the current decade. Although, almost all watermarking models have been either irreversible (the original relation cannot be restored from the watermarked relation) and/or non-blind (requiring original relation to detect the watermark in watermarked relation). This model has several disadvantages over reversible and blind watermarking (requiring only watermarked relation and secret key from which the watermark is detected and original relation is restored) including inability to identify rightful owner in case of successful secondary watermarking, inability to revert the relation to original data set (required in high precision industries) and requirement to store unmarked relation at a secure secondary storage. To overcome these problems, we propose a watermarking scheme that is reversible as well as blind. We utilize difference expansion on integers to achieve reversibility. The major advantages provided by our scheme are reversibility to high quality original data set, rightful owner identification, resistance against secondary watermarking attacks, and no need to store original database at a secure secondary storage.

Fluid-structure interaction analysis by coupled FE-SPH model based on a novel searching algorithm

Fluid–Structure Interaction (FSI) problem is significant in science and engineering, which leads to challenges for computational mechanics. The coupled model of Finite Element and Smoothed Particle Hydrodynamics (FE-SPH) is a robust technique for simulation of FSI problems. However, two important steps of neighbor searching and contact searching in the coupled FE-SPH model are extremely time-consuming. Point-In-Box (PIB) searching algorithm has been developed by Swegle to improve the efficiency of searching. However, it has a shortcoming that efficiency of searching can be significantly affected by the distribution of points (nodes in FEM and particles in SPH). In this paper, in order to improve the efficiency of searching, a novel Striped-PIB (S-PIB) searching algorithm is proposed to overcome the shortcoming of PIB algorithm that caused by points distribution, and the two time-consuming steps of neighbor searching and contact searching are integrated into one searching step. The accuracy and efficiency of the newly developed searching algorithm is studied on by efficiency test and FSI problems. It has been found that the newly developed model can significantly improve the computational efficiency and it is believed to be a powerful tool for the FSI analysis.

Analysis of expressed sequence tags from Actinidia : Applications of a cross species EST database for gene discovery in the areas of flavor, health, color and ripening

Background Kiwifruit (Actinidia spp.) are a relatively new, but economically important crop grown in many different parts of the world. Commercial success is driven by the development of new cultivars with novel consumer traits including flavor, appearance, healthful components and convenience. To increase our understanding of the genetic diversity and gene-based control of these key traits in Actinidia, we have produced a collection of 132,577 expressed sequence tags (ESTs). Results The ESTs were derived mainly from four Actinidia species (A. chinensis, A. deliciosa, A. arguta and A. eriantha) and fell into 41,858 non redundant clusters (18,070 tentative consensus sequences and 23,788 EST singletons). Analysis of flavor and fragrance-related gene families (acyltransferases and carboxylesterases) and pathways (terpenoid biosynthesis) is presented in comparison with a chemical analysis of the compounds present in Actinidia including esters, acids, alcohols and terpenes. ESTs are identified for most genes in color pathways controlling chlorophyll degradation and carotenoid biosynthesis. In the health area, data are presented on the ESTs involved in ascorbic acid and quinic acid biosynthesis showing not only that genes for many of the steps in these pathways are represented in the database, but that genes encoding some critical steps are absent. In the convenience area, genes related to different stages of fruit softening are identified. Conclusion This large EST resource will allow researchers to undertake the tremendous challenge of understanding the molecular basis of genetic diversity in the Actinidia genus as well as provide an EST resource for comparative fruit genomics. The various bioinformatics analyses we have undertaken demonstrates the extent of coverage of ESTs for genes encoding different biochemical pathways in Actinidia.

The ranking based constrained document clustering method and its application to social event detection

With the growing size and variety of social media files on the web, it’s becoming critical to efficiently organize them into clusters for further processing. This paper presents a novel scalable constrained document clustering method that harnesses the power of search engines capable of dealing with large text data. Instead of calculating distance between the documents and all of the clusters’ centroids, a neighborhood of best cluster candidates is chosen using a document ranking scheme. To make the method faster and less memory dependable, the in-memory and in-database processing are combined in a semi-incremental manner. This method has been extensively tested in the social event detection application. Empirical analysis shows that the proposed method is efficient both in computation and memory usage while producing notable accuracy.

Understanding negation and family history to improve clinical information retrieval

We present a study to understand the effect that negated terms (e.g., "no fever") and family history (e.g., "family history of diabetes") have on searching clinical records. Our analysis is aimed at devising the most effective means of handling negation and family history. In doing so, we explicitly represent a clinical record according to its different content types: negated, family history and normal content; the retrieval model weights each of these separately. Empirical evaluation shows that overall the presence of negation harms retrieval effectiveness while family history has little effect. We show negation is best handled by weighting negated content (rather than the common practise of removing or replacing it). However, we also show that many queries benefit from the inclusion of negated content and that negation is optimally handled on a per-query basis. Additional evaluation shows that adaptive handing of negated and family history content can have significant benefits.

The effectiveness of information-sharing interventions as a means to reduce anxiety in families waiting for surgical patients undergoing an elective surgical procedure : a systematic review protocol

Review question/objective What are the most effective information sharing strategies used to reduce anxiety in families of patients undergoing elective surgery? This review seeks to synthesize the best available evidence in relation to the most effective information-sharing intervention to reduce anxiety for families waiting for patients undergoing an elective surgical procedure. The specific objectives are to review the effectiveness of evidence of interventions designed to reduce the anxiety of families waiting whilst their loved one undergoes a surgical intervention. A variety of interventions exist and include surgical nurse liaison services, intraoperative reporting either by face-to-face or telephone delivery, informational cards, visual information screens, and intraoperative paging devices for families. Inclusion criteria Types of participants All studies of family members over 18 years of age waiting for patients undergoing an elective surgical procedure will be included, including those waiting for both adult and paediatric patients. Studies of families waiting for other patient populations, eg emergency surgery, chemotherapy or intensive care patients will be excluded. Types of intervention(s)/phenomena of interest All information-sharing Interventions for families of patients undergoing an elective surgical procedure will be included, including but not limited to: surgical nurse liaison services, in-person intraoperative reporting, visual information screens, paging devices, informational cards and telephone delivery of intraoperative progress reports. Interventions that take place during the intraoperative phase of care only will be included in the review. Preadmission information sharing interventions will be excluded. Types of outcomes The outcomes of interest include: Primary outcome: the level of anxiety amongst family members or close relatives whilst waiting for patients undergoing surgery, as measured by a validated instrument (such as the S-Anxiety portion of the State-Trait Anxiety Inventory).4 Secondary outcomes: family satisfaction and other measurements that may be considered indicators of stress and anxiety, such as mean arterial pressure (MAP) and heart rate.

A transcriptomic analysis of striped catfish (Pangasianodon hypophthalmus) in response to salinity adaptation: De novo assembly, gene annotation and marker discovery

The striped catfish (Pangasianodon hypophthalmus) culture industry in the Mekong Delta in Vietnam has developed rapidly over the past decade. The culture industry now however, faces some significant challenges, especially related to climate change impacts notably from predicted extensive saltwater intrusion into many low topographical coastal provinces across the Mekong Delta. This problem highlights a need for development of culture stocks that can tolerate more saline culture environments as a response to expansion of saline water-intruded land. While a traditional artificial selection program can potentially address this need, understanding the genomic basis of salinity tolerance can assist development of more productive culture lines. The current study applied a transcriptomic approach using Ion PGM technology to generate expressed sequence tag (EST) resources from the intestine and swim bladder from striped catfish reared at a salinity level of 9 ppt which showed best growth performance. Total sequence data generated was 467.8 Mbp, consisting of 4,116,424 reads with an average length of 112 bp. De novo assembly was employed that generated 51,188 contigs, and allowed identification of 16,116 putative genes based on the GenBank non-redundant database. GO annotation, KEGG pathway mapping, and functional annotation of the EST sequences recovered with a wide diversity of biological functions and processes. In addition, more than 11,600 simple sequence repeats were also detected. This is the first comprehensive analysis of a striped catfish transcriptome, and provides a valuable genomic resource for future selective breeding programs and functional or evolutionary studies of genes that influence salinity tolerance in this important culture species.

Using police crash databases for injury prevention research - a comparison of opt-out and opt-in approaches to study recruitment

Objective: The study aimed to examine the difference in response rates between opt-out and opt-in participant recruitment in a population-based study of heavy-vehicle drivers involved in a police-attended crash. Methods: Two approaches to subject recruitment were implemented in two different states over a 14-week period and response rates for the two approaches (opt-out versus opt-in recruitment) were compared. Results: Based on the eligible and contactable drivers, the response rates were 54% for the optout group and 16% for the opt-in group. Conclusions and Implications: The opt-in recruitment strategy (which was a consequence of one jurisdiction’s interpretation of the national Privacy Act at the time) resulted in an insufficient and potentially biased sample for the purposes of conducting research into risk factors for heavy-vehicle crashes. Australia’s national Privacy Act 1988 has had a long history of inconsistent practices by state and territory government departments and ethical review committees. These inconsistencies can have profound effects on the validity of research, as shown through the significantly different response rates we reported in this study. It is hoped that a more unified interpretation of the Privacy Act across the states and territories, as proposed under the soon-to-be released Australian Privacy Principles will reduce the recruitment challenges outlined in this study.

Locating people in video from semantic descriptions : a new database and approach

The location of previously unseen and unregistered individuals in complex camera networks from semantic descriptions is a time consuming and often inaccurate process carried out by human operators, or security staff on the ground. To promote the development and evaluation of automated semantic description based localisation systems, we present a new, publicly available, unconstrained 110 sequence database, collected from 6 stationary cameras. Each sequence contains detailed semantic information for a single search subject who appears in the clip (gender, age, height, build, hair and skin colour, clothing type, texture and colour), and between 21 and 290 frames for each clip are annotated with the target subject location (over 11,000 frames are annotated in total). A novel approach for localising a person given a semantic query is also proposed and demonstrated on this database. The proposed approach incorporates clothing colour and type (for clothing worn below the waist), as well as height and build to detect people. A method to assess the quality of candidate regions, as well as a symmetry driven approach to aid in modelling clothing on the lower half of the body, is proposed within this approach. An evaluation on the proposed dataset shows that a relative improvement in localisation accuracy of up to 21 is achieved over the baseline technique.

A Bayesian hurdle model for analysis of an insect resistance monitoring database

Motivated by the analysis of the Australian Grain Insect Resistance Database (AGIRD), we develop a Bayesian hurdle modelling approach to assess trends in strong resistance of stored grain insects to phosphine over time. The binary response variable from AGIRD indicating presence or absence of strong resistance is characterized by a majority of absence observations and the hurdle model is a two step approach that is useful when analyzing such a binary response dataset. The proposed hurdle model utilizes Bayesian classification trees to firstly identify covariates and covariate levels pertaining to possible presence or absence of strong resistance. Secondly, generalized additive models (GAMs) with spike and slab priors for variable selection are fitted to the subset of the dataset identified from the Bayesian classification tree indicating possibility of presence of strong resistance. From the GAM we assess trends, biosecurity issues and site specific variables influencing the presence of strong resistance using a variable selection approach. The proposed Bayesian hurdle model is compared to its frequentist counterpart, and also to a naive Bayesian approach which fits a GAM to the entire dataset. The Bayesian hurdle model has the benefit of providing a set of good trees for use in the first step and appears to provide enough flexibility to represent the influence of variables on strong resistance compared to the frequentist model, but also captures the subtle changes in the trend that are missed by the frequentist and naive Bayesian models.

Reversible and semi-blind relational database watermarking

Database watermarking has received significant research attention in the current decade. Although, almost all watermarking models have been either irreversible (the original relation cannot be restored from the watermarked relation) and/or non-blind (requiring original relation to detect the watermark in watermarked relation). This model has several disadvantages over reversible and blind watermarking (requiring only watermarked relation and secret key from which the watermark is detected and original relation is restored) including inability to identify rightful owner in case of successful secondary watermarking, inability to revert the relation to original data set (required in high precision industries) and requirement to store unmarked relation at a secure secondary storage. To overcome these problems, we propose a watermarking scheme that is reversible as well as blind. We utilize difference expansion on integers to achieve reversibility. The major advantages provided by our scheme are reversibility to high quality original data set, rightful owner identification, resistance against secondary watermarking attacks, and no need to store original database at a secure secondary storage.

Users’ perception of using web search engines and their impact on the perceived intention to reuse the systems

In today’s world of information-driven society, many studies are exploring usefulness and ease of use of the technology. The research into personalizing next-generation user interface is also ever increasing. A better understanding of factors that influence users’ perception of web search engine performance would contribute in achieving this. This study measures and examines how users’ perceived level of prior knowledge and experience influence their perceived level of satisfaction of using the web search engines, and how their perceived level of satisfaction affects their perceived intention to reuse the system. 50 participants from an Australian university participated in the current study, where they performed three search tasks and completed survey questionnaires. A research model was constructed to test the proposed hypotheses. Correlation and regression analyses results indicated a significant correlation between (1) users’ prior level of experience and their perceived level of satisfaction in using the web search engines, and (2) their perceived level of satisfaction in using the systems and their perceived intention to reuse the systems. A theoretical model is proposed to illustrate the causal relationships. The implications and limitations of the study are also discussed.

Emerging methods in using GIS to analyse Barmah Forest virus disease in Queensland, Australia

Barmah Forest virus (BFV) disease is an emerging mosquito-borne disease in Australia. We aimed to outline some recent methods in using GIS for the analysis of BFV disease in Queensland, Australia. A large database of geocoded BFV cases has been established in conjunction with population data. The database has been used in recently published studies conducted by the authors to determine spatio-temporal BFV disease hotspots and spatial patterns using spatial autocorrelation and semi-variogram analysis in conjunction with the development of interpolated BFV disease standardised incidence maps. This paper briefly outlines spatial analysis methodologies using GIS tools used in those studies. This paper summarises methods and results from previous studies by the authors, and presents a GIS methodology to be used in future spatial analytical studies in attempt to enhance the understanding of BFV disease in Queensland. The methodology developed is useful in improving the analysis of BFV disease data and will enhance the understanding of the BFV disease distribution in Queensland, Australia.