Watermarking protocol for protecting user's right in content based image retrieval

Content based image retrieval (CBIR) is a technique to search for images relevant to the user&rsquo;s query from an image collection.In last decade, most attention has been paid to improve the retrieval performance. However, there is no significant effort to investigate the security concerning in CBIR. Under the query by example (QBE) paradigm, the user supplies an image as a query and the system returns a set of retrieved results. If the query image includes user&rsquo;s private information, an untrusted server provider of CBIR may distribute it illegally, which leads to the user&rsquo;s right problem. In this paper, we propose an interactive watermarking protocol to address this problem. A watermark is inserted into the query image by the user in encrypted domain without knowing the exact content. The server provider of CBIR will get the watermarked query image and uses it to perform image retrieval. In case where the user finds an unauthorized copy, a watermark in the unauthorized copy will be used as evidence to prove that the user&rsquo;s legal right is infringed by the server provider.<br />

Content based image retrieval using unclean positive examples

Conventional content-based image retrieval (CBIR) schemes employing relevance feedback may suffer from some problems in the practical applications. First, most ordinary users would like to complete their search in a single interaction especially on the web. Second, it is time consuming and difficult to label a lot of negative examples with sufficient variety. Third, ordinary users may introduce some noisy examples into the query. This correspondence explores solutions to a new issue that image retrieval using unclean positive examples. In the proposed scheme, multiple feature distances are combined to obtain image similarity using classification technology. To handle the noisy positive examples, a new two-step strategy is proposed by incorporating the methods of data cleaning and noise tolerant classifier. The extensive experiments carried out on two different real image collections validate the effectiveness of the proposed scheme.<br />

"You Tube and I Find" - personalizing multimedia content access

Recent growth in broadband access and proliferation of small personal devices that capture images and videos has led to explosive growth of multimedia content available everywhereVfrom personal disks to the Web. While digital media capture and upload has become nearly universal with newer device technology, there is still a need for better tools and technologies to search large collections of multimedia data and to find and deliver the right content to a user according to her current needs and preferences. A renewed focus on the subjective dimension in the multimedia lifecycle, fromcreation, distribution, to delivery and consumption, is required to address this need beyond what is feasible today. Integration of the subjective aspects of the media itselfVits affective, perceptual, and physiological potential (both intended and achieved), together with those of the users themselves will allow for personalizing the content access, beyond today&rsquo;s facility. This integration, transforming the traditional multimedia information retrieval (MIR) indexes to more effectively answer specific user needs, will allow a richer degree of personalization predicated on user intention and mode of interaction, relationship to the producer, content of the media, and their history and lifestyle. In this paper, we identify the challenges in achieving this integration, current approaches to interpreting content creation processes, to user modelling and profiling, and to personalized content selection, and we detail future directions. The structure of the paper is as follows: In Section I, we introduce the problem and present some definitions. In Section II, we present a review of the aspects of personalized content and current approaches for the same. Section III discusses the problem of obtaining metadata that is required for personalized media creation and present eMediate as a case study of an integrated media capture environment. Section IV presents the MAGIC system as a case study of capturing effective descriptive data and putting users first in distributed learning delivery. The aspects of modelling the user are presented as a case study in using user&rsquo;s personality as a way to personalize summaries in Section V. Finally, Section VI concludes the paper with a discussion on the emerging challenges and the open problems.

A fuzzy clustering approach to content-based image retrieval

In this study, an interactive Content-Based Image Retrieval (CBIR) system that allows searching and retrieving images from databases is designed and developed. Based on the fuzzy c-means clustering algorithm, the CBIR system fuses color and texture features in image segmentation. A technique to form compound queries based on the combined features of different images is devised. This technique allows users to have a better control on the search criteria, thus a higher retrieval performance can be achieved. A database consisting of skin cancer imagery is used to demonstrate the applicability of the CBIR system.<br />

An analysis of hatchling resting metabolism: in search of ecological correlates that explain deviations from allometric relations

From data in the literature, an allometric equation is compiled for hatchling resting metabolic rate and an attempt is made to explain residual variation in terms of hatchling type, yolk and water content, embryonic and postnatal growth rate, and environmental circumstances (latitudinal distribution). The body mass exponent for resting metabolism in hatchlings was 0.86 and, thus, substantially different from the values compiled for adult birds (0.67-0.75). Relatively high hatchling metabolic rates were found for birds exhibiting high embryonic and postnatal growth rates, as well as for those species that hatched at high latitudes. A functional explanation is postulated for the correlations between hatchling metabolism and these three variables.

Infant feeding websites and apps: a systematic assessment of quality and content

Background: Internet websites and smartphone apps have become a popular resource to guide parents in their children&rsquo;s feeding and nutrition. Given the diverse range of websites and apps on infant feeding, the quality of information in these resources should be assessed to identify whether consumers have access to credible and reliable information.<br /><br />Objective: This systematic analysis provides perspectives on the information available about infant feeding on websites and smartphone apps.<br /><br />Methods: A systematic analysis was conducted to assess the quality, comprehensibility, suitability, and readability of websites and apps on infant feeding using a developed tool. Google and Bing were used to search for websites from Australia, while the App Store for iOS and Google Play for Android were used to search for apps. Specified key words including baby feeding, breast feeding, formula feeding and introducing solids were used to assess websites and apps addressing feeding advice. Criteria for assessing the accuracy of the content were developed using the Australian Infant Feeding Guidelines.<br /><br />Results: A total of 600 websites and 2884 apps were screened, and 44 websites and 46 apps met the selection criteria and were analyzed. Most of the websites (26/44) and apps (43/46) were noncommercial, some websites (10/44) and 1 app were commercial and there were 8 government websites; 2 apps had university endorsement. The majority of the websites and apps were rated poor quality. There were two websites that had 100% coverage of information compared to those rated as fair or poor that had low coverage. Two-thirds of the websites (65%) and almost half of the apps (47%) had a readability level above the 8th grade level.<br /><br />Conclusions: The findings of this unique analysis highlight the potential for website and app developers to merge user requirements with evidence-based content to ensure that information on infant feeding is of high quality. There are currently no apps available to consumers that address a variety of infant feeding topics. To keep up with the rapid turnover of the evolving technology, health professionals need to consider developing an app that will provide consumers with a credible and reliable source of information about infant feeding, using quality assessment tools and evidence-based content.

Developing primary pre-service teachers' mathematical content knowledge during practicum teaching

While it is recognised that a teachers' mathematical content knowledge (MCK) is crucial for teaching, less is known about when different categories of MCK develop during teacher education. This paper reports on two primary pre-service teachers, whose MCK was investigated during their practicum experiences in first, second and fourth years of a four-year Bachelor of Education program. The results identify when and under what conditions pre-service teachers' developed different categories of their MCK during practicum. Factors that assisted pre-service teachers to develop their MCK included program structure providing breadth and depth of experiences; sustained engagement for learning MCK; and quality of pre-service teachers' learning experiences.