Quantifying Privacy: A Novel Entropy-Based Measure of Disclosure Risk

It is well recognised that data mining and statistical analysis pose a serious treat to privacy. This is true for financial, medical, criminal and marketing research. Numerous techniques have been proposed to protect privacy, including restriction and data modification. Recently proposed privacy models such as differential privacy and k-anonymity received a lot of attention and for the latter there are now several improvements of the original scheme, each removing some security shortcomings of the previous one. However, the challenge lies in evaluating and comparing privacy provided by various techniques. In this paper we propose a novel entropy based security measure that can be applied to any generalisation, restriction or data modification technique. We use our measure to empirically evaluate and compare a few popular methods, namely query restriction, sampling and noise addition.Comment: 20 pages, 4 figure

Building information modelling : what is in there for the architects?

Despite the rapid growth in capabilities and availability of BIM supporting technologies the industry has been slow to adopt BIM in practice. A number of factors inhibiting BIM adoption have been reported in literature such as work practice, resistance to change, lack of business initiatives, and so on. Most of these researches have focussed at specific disciplines of the AEC industry and surveys and questionnaires have generally been used to collect data. This paper reports on the findings of an actionoriented research that aims at developing strategies and measures for greater adoption of BIM in the industry. The findings reported in this paper build on the earlier research on BIM by adopting Focus Group Interviews (FGIs) as the source of data collection. FGIs provide a forum for the representatives from different disciplines in the AEC industry including architects, engineers, contractors, software application vendors, consultants, project managers, academicians and people from government agencies, to share their views on BIM adoption issues. The discussions were recorded on tapes and segmented and analyzed using a coding scheme developed specifically for the study. This paper discusses the BIM related issues from the perspective of the architecture, primarily focusing on the awareness, perception and knowledge of BIM among architects. A discussion with respect to the other disciplines is also presented to demonstrate differences in perception across the design (architects/ engineers) and non-design (contractors/ facility managers) disciplines

Can Water-Injected Turbomachines Provide Cost-Effective Emissions and Maintenance Reductions?

An investigation has been performed to evaluate the effect of water injection on the performance of the Air Force Research Laboratory (AFRL, Wright-Patterson Air Force Base (WPAFB)) experimental trapped vortex combustor (TVC) over a range of fuel-to-air and water-to-fuel ratios. Performance is characterized by combustor exit quantities: temperature and emissions measurements using rakes, and overall pressure drop, from upstream plenum to combustor exit. Combustor visualization is performed using gray-scale and color still photographs and high-frame-rate videos. A parallel investigation evaluated the performance of a computational fluid dynamics (CFD) tool for the prediction of the reacting flow in a liquid fueled combustor (e.g., TVC) that uses water injection for control of pollutant emissions and turbine inlet temperature. Generally, reasonable agreement is found between data and NO(x) computations. Based on a study assessing the feasibility and performance impact of using water injection on a Boeing 747-400 aircraft to reduce NO(x) emissions during takeoff, retrofitting does not appear to be cost effective; however, an operator of a newly designed engine and airframe might be able to save up to 1.0 percent in operating costs. Other challenges of water injection will be discussed

Towards Optimal and Expressive Kernelization for d-Hitting Set

d-Hitting Set is the NP-hard problem of selecting at most k vertices of a hypergraph so that each hyperedge, all of which have cardinality at most d, contains at least one selected vertex. The applications of d-Hitting Set are, for example, fault diagnosis, automatic program verification, and the noise-minimizing assignment of frequencies to radio transmitters. We show a linear-time algorithm that transforms an instance of d-Hitting Set into an equivalent instance comprising at most O(k^d) hyperedges and vertices. In terms of parameterized complexity, this is a problem kernel. Our kernelization algorithm is based on speeding up the well-known approach of finding and shrinking sunflowers in hypergraphs, which yields problem kernels with structural properties that we condense into the concept of expressive kernelization. We conduct experiments to show that our kernelization algorithm can kernelize instances with more than 10^7 hyperedges in less than five minutes. Finally, we show that the number of vertices in the problem kernel can be further reduced to O(k^{d-1}) with additional O(k^{1.5 d}) processing time by nontrivially combining the sunflower technique with d-Hitting Set problem kernels due to Abu-Khzam and Moser.Comment: This version gives corrected experimental results, adds additional figures, and more formally defines "expressive kernelization

On Bubble Generators in Directed Graphs

International audienceBubbles are pairs of internally vertex-disjoint (s, t)-paths with applications in the processing of DNA and RNA data. For example, enumerating alternative splicing events in a reference-free context can be done by enumerating all bubbles in a de Bruijn graph built from RNA-seq reads [16]. However, listing and analysing all bubbles in a given graph is usually unfeasible in practice, due to the exponential number of bubbles present in real data graphs. In this paper, we propose a notion of a bubble generator set, i.e. a polynomial-sized subset of bubbles from which all the others can be obtained through the application of a specific symmetric difference operator. This set provides a compact representation of the bubble space of a graph, which can be useful in practice since some pertinent information about all the bubbles can be more conveniently extracted from this compact set. Furthermore, we provide a polynomial-time algorithm to decompose any bubble of a graph into the bubbles of such a generator in a tree-like fashion

Mortality After Pediatric Arterial Ischemic Stroke

OBJECTIVES: Cerebrovascular disease is among the top 10 causes of death in US children, but risk factors for mortality are poorly understood. Within an international registry, we identify predictors of in-hospital mortality after pediatric arterial ischemic stroke (AIS). METHODS: Neonates (0-28 days) and children (29 days- < 19 years) with AIS were enrolled from January 2003 to July 2014 in a multinational stroke registry. Death during hospitalization and cause of death were ascertained from medical records. Logistic regression was used to analyze associations between risk factors and in-hospital mortality. RESULTS: Fourteen of 915 neonates (1.5%) and 70 of 2273 children (3.1%) died during hospitalization. Of 48 cases with reported causes of death, 31 (64.6%) were strokerelated, with remaining deaths attributed to medical disease. In multivariable analysis, congenital heart disease (odds ratio [OR]: 3.88; 95% confidence interval [CI] : 1.23-12.29; P = .021), posterior plus anterior circulation stroke (OR: 5.36; 95% CI: 1.70-16.85; P = .004), and stroke presentation without seizures (OR: 3.95; 95% CI: 1.26-12.37; P = .019) were associated with in-hospital mortality for neonates. Hispanic ethnicity (OR: 3.12; 95% CI: 1.56-6.24; P = .001), congenital heart disease (OR: 3.14; 95% CI: 1.75-5.61; P < .001), and posterior plus anterior circulation stroke (OR: 2.71; 95% CI: 1.40-5.25; P = .003) were associated with in-hospital mortality for children. CONCLUSIONS: In-hospital mortality occurred in 2.6% of pediatric AIS cases. Most deaths were attributable to stroke. Risk factors for in-hospital mortality included congenital heart disease and posterior plus anterior circulation stroke. Presentation without seizures and Hispanic ethnicity were also associated with mortality for neonates and children, respectively. Awareness and study of risk factors for mortality represent opportunities to increase survival

A qualitative meta-synthesis of interpersonal violence prevention programs focused on males

Exceptionally high levels of interpersonal violence have triggered a call by many experts for the need to determine effective ways to address the onset and effects of exposure to interpersonal violence. The specific aim of this study was to identify and draw on existing promising practices to make a more informed decision on strategies to develop a contextually relevant intervention that focused on the promotion of positive forms of masculinity to create safety and peace. This study used a qualitative meta-synthesis (QMS) technique to integrate and interpret findings from various intervention studies that focused on males and/or gender. An in-depth literature search yielded a total of 827 papers that met the search criteria. After removal of duplicates, abstract review, and review of the full texts, the subsequent sample for this meta-synthesis included 12 intervention programs and 23 studies. This QMS revealed the value of a comprehensive approach, using multiple strategies, employing participatory and interactive methods, and promoting social mobilization to address interpersonal violence. The promotion of positive forms of masculinity as an interpersonal violence prevention strategy is a much-needed, relatively untapped approach to generating safety and peace for both males and females

A Family of Tree-Based Generators for Bubbles in Directed Graphs

International audienceBubbles are pairs of internally vertex-disjoint (s, t)-paths in a directed graph. In de Bruijn graphs built from reads of RNA and DNA data, bubbles represent interesting biological events, such as alternative splicing (AS) and allelic differences (SNPs and indels). However, the set of all bubbles in a de Bruijn graph built from real data is usually too large to be efficiently enumerated and analysed in practice. In particular, despite significant research done in this area, listing bubbles still remains the main bottleneck for tools that detect AS events in a reference-free context. Recently, in [1] the concept of a bubble generator was introduced as a way for obtaining a compact representation of the bubble space of a graph. Although this generator was quite effective in finding AS events, preliminary experiments showed that it is about 5 times slower than state-of-art methods. In this paper we propose a new family of bubble generators which improve substantially on the previous generator: generators in this new family are about two orders of magnitude faster and are still able to achieve similar precision in identifying AS events. To highlight the practical value of our new generators, we also report some experimental results on a real dataset