Image mining: trends and developments

[Abstract]: Advances in image acquisition and storage technology have led to tremendous growth in very large and detailed image databases. These images, if analyzed, can reveal useful information to the human users. Image mining deals with the extraction of implicit knowledge, image data relationship, or other patterns not explicitly stored in the images. Image mining is more than just an extension of data mining to image domain. It is an interdisciplinary endeavor that draws upon expertise in computer vision, image processing, image retrieval, data mining, machine learning, database, and artificial intelligence. In this paper, we will examine the research issues in image mining, current developments in image mining, particularly, image mining frameworks, state-of-the-art techniques and systems. We will also identify some future research directions for image mining

Contextual Localization Through Network Traffic Analysis

opportunitiesforcontentserviceproviderstooptimizethecontent delivery based on user’s location. Since sharing precise location remainsamajorprivacyconcernamongtheusers,manylocationbased services rely on contextual location (e.g. residence, cafe etc.) as opposed to acquiring user’s exact physical location. In this paper, we present PACL (Privacy-Aware Contextual Localizer), which can learn user’s contextual location just by passively monitoring user’s network traffic. PACL can discern a set of vital attributes (statistical and application-based) from user’s network traffic, and predict user’s contextual location with a very high accuracy.WedesignandevaluatePACLusingreal-worldnetwork traces of over 1700 users with over 100 gigabytes of total data. OurresultsshowthatPACL(builtusingdecisiontree)canpredict user’s contextual location with the accuracy of around 87%. I

Bibliometric analysis of emerging technologies in the field of computer science helping in ovarian cancer research

This study is carried out to provide an analysis of the literature available at the intersection of ovarian cancer and computing. A comprehensive search was conducted using Scopus database for English-language peer-reviewed articles. The study administers chronological, domain clustering and text analysis of the articles under consideration to provide high-level concept map composed of specific words and the connections between them