An information foraging theory based user study of an adaptive user interaction framework for content-based image retrieval

This paper presents the design and results of a task-based user study, based on Information Foraging Theory, on a novel user interaction framework - uInteract - for content-based image retrieval (CBIR). The framework includes a four-factor user interaction model and an interactive interface. The user study involves three focused evaluations, 12 simulated real life search tasks with different complexity levels, 12 comparative systems and 50 subjects. Information Foraging Theory is applied to the user study design and the quantitative data analysis. The systematic findings have not only shown how effective and easy to use the uInteract framework is, but also illustrate the value of Information Foraging Theory for interpreting user interaction with CBIR

Using Markov Chains for link prediction in adaptive web sites

The large number of Web pages on many Web sites has raised navigational problems. Markov chains have recently been used to model user navigational behavior on the World Wide Web (WWW). In this paper, we propose a method for constructing a Markov model of a Web site based on past visitor behavior. We use the Markov model to make link predictions that assist new users to navigate the Web site. An algorithm for transition probability matrix compression has been used to cluster Web pages with similar transition behaviors and compress the transition matrix to an optimal size for efficient probability calculation in link prediction. A maximal forward path method is used to further improve the efficiency of link prediction. Link prediction has been implemented in an online system called ONE (Online Navigation Explorer) to assist users' navigation in the adaptive Web site

Investigating people: a qualitative analysis of the search behaviours of open-source intelligence analysts

The Internet and the World Wide Web have become integral parts of the lives of many modern individuals, enabling almost instantaneous communication, sharing and broadcasting of thoughts, feelings and opinions. Much of this information is publicly facing, and as such, it can be utilised in a multitude of online investigations, ranging from employee vetting and credit checking to counter-terrorism and fraud prevention/detection. However, the search needs and behaviours of these investigators are not well documented in the literature. In order to address this gap, an in-depth qualitative study was carried out in cooperation with a leading investigation company. The research contribution is an initial identification of Open-Source Intelligence investigator search behaviours, the procedures and practices that they undertake, along with an overview of the difficulties and challenges that they encounter as part of their domain. This lays the foundation for future research in to the varied domain of Open-Source Intelligence gathering

An Editor for Helping Novices to Learn Standard ML

This paper describes a novel editor intended as an aid in the learning of the functional programming language Standard ML. A common technique used by novices is programming by analogy whereby students refer to similar programs that they have written before or have seen in the course literature and use these programs as a basis to write a new program. We present a novel editor for ML which supports programming by analogy by providing a collection of editing commands that transform old programs into new ones. Each command makes changes to an isolated part of the program. These changes are propagated to the rest of the program using analogical techniques. We observed a group of novice ML students to determine the most common programming errors in learning ML and restrict our editor such that it is impossible to commit these errors. In this way, students encounter fewer bugs and so their rate of learning increases. Our editor, C Y NTHIA, has been implemented and is due to be tested on st..

The Impact of Link Suggestions on User Navigation and User Perception

The study reported in this paper explores the effects of providing web users with link suggestions that are relevant to their tasks. Results indicate that link suggestions were positively received. Furthermore, users perceived sites with link suggestions as more usable and themselves as less disoriented. The average task execution time was significantly lower than in the control condition and users appeared to navigate in a more structured manner. Unexpectedly, men took more advantage from link suggestions than women

'Datafication': Making sense of (big) data in a complex world

This is a pre-print of an article published in European Journal of Information Systems. The definitive publisher-authenticated version is available at the link below. Copyright @ 2013 Operational Research Society Ltd.No abstract available (Editorial

The future of social is personal: the potential of the personal data store

This chapter argues that technical architectures that facilitate the longitudinal, decentralised and individual-centric personal collection and curation of data will be an important, but partial, response to the pressing problem of the autonomy of the data subject, and the asymmetry of power between the subject and large scale service providers/data consumers. Towards framing the scope and role of such Personal Data Stores (PDSes), the legalistic notion of personal data is examined, and it is argued that a more inclusive, intuitive notion expresses more accurately what individuals require in order to preserve their autonomy in a data-driven world of large aggregators. Six challenges towards realising the PDS vision are set out: the requirement to store data for long periods; the difficulties of managing data for individuals; the need to reconsider the regulatory basis for third-party access to data; the need to comply with international data handling standards; the need to integrate privacy-enhancing technologies; and the need to future-proof data gathering against the evolution of social norms. The open experimental PDS platform INDX is introduced and described, as a means of beginning to address at least some of these six challenges

A computational fluid dynamic investigation of inhomogeneous hydrogen flame acceleration and transition to detonation

Gas explosions in homogeneous reactive mixtures have been widely studied both experimentally and numerically. However, in practice and industrial applications, combustible mixtures are usually inhomogeneous and subject to vertical concentration gradients. Limited studies have been conducted in such context which resulted in limited understanding of the explosion characteristics in such situations. The present numerical investigation aims to study the dynamics of Deflagration to Detonation Transition (DDT) in inhomogeneous hydrogen/air mixtures and examine the effects of obstacle blockage ratio in DDT. VCEFoam, a reactive density-based solver recently assembled by the authors within the frame of OpenFOAM CFD toolbox has been used. VCEFoam uses the Harten–Lax–van Leer–Contact (HLLC) scheme fr the convective fluxes contribution and shock capturing. The solver has been verified by comparing its predictions with the analytical solutions of two classical test cases. For validation, the experimental data of Boeck et al. (1) is used. The experiments were conducted in a rectangular channel the three different blockage ratios and hydrogen concentrations. Comparison is presented between the predicted and measured flame tip velocities. The shaded contours of the predicted temperature and numerical Schlieren (magnitude of density gradient) will be analysed to examine the effects of the blockage ratio on flame acceleration and DDT

Information scent, searching and stopping : modelling SERP level stopping behaviour

Current models and measures of the \emph{Interactive Information Retrieval (IIR)} process typically assume that a searcher will always examine the first snippet in a given \emph{Search Engine Results Page (SERP)}, and then with some probability or cutoff, he or she will stop examining snippets and/or documents in the ranked list (snippet level stopping). Prior work has however shown that searchers will form an initial impression of the SERP, and will often abandon a page without clicking on or inspecting in detail any snippets or documents. That is, the \emph{information scent} affects their decision to continue. In this work, we examine whether considering the information scent of a page leads to better predictions of stopping behaviour. In a simulated analysis, grounded with data from a prior user study, we show that introducing a SERP level stopping strategy can improve the performance attained by simulated users, resulting in an increase in gain across most snippet level stopping strategies. When compared to actual search and stopping behaviour, incorporating SERP level stopping offers a closer approximation than without. These findings show that models and measures that na\"{i}vely assume snippets and documents in a ranked list are actually examined in detail are less accurate, and that modelling SERP level stopping is required to create more realistic models of the search process

RIP1-HAT1-SirT complex identification and targeting in treatment and prevention of cancer

Purpose: Alteration in cell death is a hallmark of cancer. A functional role regulating survival, apoptosis, and necroptosis has been attributed to RIP1/3 complexes.Experimental Design: We have investigated the role of RIP1 and the effects of MC2494 in cell death induction, using different methods as flow cytometry, transcriptome analysis, immunoprecipitation, enzymatic assays, transfections, mutagenesis, and in vivo studies with different mice models.Results: Here, we show that RIP1 is highly expressed in cancer, and we define a novel RIP1/3-SIRT1/2-HAT1/4 complex. Mass spectrometry identified five acetylations in the kinase and death domain of RIP1. The novel characterized pan-SIRT inhibitor, MC2494, increases RIP1 acetylation at two additional sites in the death domain. Mutagenesis of the acetylated lysine decreases RIP1-dependent cell death, suggesting a role for acetylation of the RIP1 complex in cell death modulation. Accordingly, MC2494 displays tumor-selective potential in vitro, in leukemic blasts ex vivo, and in vivo in both xenograft and allograft cancer models. Mechanistically, MC2494 induces bona fide tumor-restricted acetylated RIP1/caspase-8-mediated apoptosis. Excitingly, MC2494 displays tumor-preventive activity by blocking 7,12-dimethylbenz(α)anthracene-induced mammary gland hyperproliferation in vivoConclusions: These preventive features might prove useful in patients who may benefit from a recurrence-preventive approach with low toxicity during follow-up phases and in cases of established cancer predisposition. Thus, targeting the newly identified RIP1 complex may represent an attractive novel paradigm in cancer treatment and prevention