Information Flow Audit for Transparency and Compliance in the Handling of Personal Data

This is the author accepted manuscript. The final version is available from IEEE via http://dx.doi.org/10.1109/IC2EW.2016.29The adoption of cloud computing is increasing and its use is becoming widespread in many sectors. As the proportion of services provided using cloud computing increases, legal and regulatory issues are becoming more significant. In this paper we explore how an Information Flow Audit (IFA) mechanism, that provides key data regarding provenance, can be used to verify compliance with regulatory and contractual duty, and survey potential extensions. We explore the use of IFA for such a purpose through a smart electricity metering use case derived from a French Data Protection Agency recommendation.This work was supported by UK Engineering and Physical Sciences Research Council grant EP/K011510 CloudSafetyNet: End-to-End Application Security in the Cloud. We acknowledge the support of Microsoft through the Microsoft Cloud Computing Research Centre

Joint Estimation of Linear and Non-linear Signal-to-Noise Ratio based on Neural Networks

A novel technique estimating ASE and non-linear SNR is presented. Our method is evaluated by simulations obtaining a std error of 0.23 dB for both ASE and non-linear SNR

Linear Estimation of Location and Scale Parameters Using Partial Maxima

Consider an i.i.d. sample X^*_1,X^*_2,...,X^*_n from a location-scale family, and assume that the only available observations consist of the partial maxima (or minima)sequence, X^*_{1:1},X^*_{2:2},...,X^*_{n:n}, where X^*_{j:j}=max{X^*_1,...,X^*_j}. This kind of truncation appears in several circumstances, including best performances in athletics events. In the case of partial maxima, the form of the BLUEs (best linear unbiased estimators) is quite similar to the form of the well-known Lloyd's (1952, Least-squares estimation of location and scale parameters using order statistics, Biometrika, vol. 39, pp. 88-95) BLUEs, based on (the sufficient sample of) order statistics, but, in contrast to the classical case, their consistency is no longer obvious. The present paper is mainly concerned with the scale parameter, showing that the variance of the partial maxima BLUE is at most of order O(1/log n), for a wide class of distributions.Comment: This article is devoted to the memory of my six-years-old, little daughter, Dionyssia, who leaved us on August 25, 2010, at Cephalonia isl. (26 pages, to appear in Metrika

The integrated dynamic land use and transport model MARS

Cities worldwide face problems like congestion or outward migration of businesses. The involved transport and land use interactions require innovative tools. The dynamic Land Use and Transport Interaction model MARS (Metropolitan Activity Relocation Simulator) is part of a structured decision making process. Cities are seen as self organizing systems. MARS uses Causal Loop Diagrams from Systems Dynamics to explain cause and effect relations. MARS has been benchmarked against other published models. A user friendly interface has been developed to support decision makers. Its usefulness was tested through workshops in Asia. This paper describes the basis, capabilities and uses of MARS

FOXM1 repression increases mitotic death upon antimitotic chemotherapy through BMF upregulation

Inhibition of spindle microtubule (MT) dynamics has been effectively used in cancer treatment. Although the mechanisms by which MT poisons elicit mitotic arrest are fairly understood, efforts are still needed towards elucidating how cancer cells respond to antimitotic drugs owing to cytotoxicity and resistance side effects. Here, we identified the critical G2/M transcription factor Forkhead box M1 (FOXM1) as a molecular determinant of cell response to antimitotics. We found FOXM1 repression to increase death in mitosis (DiM) due to upregulation of the BCL-2 modifying factor (BMF) gene involved in anoikis, an apoptotic process induced upon cell detachment from the extracellular matrix. FOXM1 binds to a BMF intronic cis-regulatory element that interacts with both the BMF and the neighbor gene BUB1B promoter regions, to oppositely regulate their expression. This mechanism ensures that cells treated with antimitotics repress BMF and avoid DiM when FOXM1 levels are high. In addition, we show that this mechanism is partly disrupted in anoikis/antimitotics-resistant tumor cells, with resistance correlating with lower BMF expression but in a FOXM1-independent manner. These findings provide a stratification biomarker for antimitotic chemotherapy response.This work was supported by: FEDER (Fundo Europeu de Desenvolvimento Regional) funds through the COMPETE 2020 - Operational Programme for Competitiveness and Internationalization (POCI), Portugal 2020 and by Portuguese funds through FCT (Fundação para a Ciência e a Tecnologia) in the framework of the project POCI-01-0145-FEDER-031120 (PTDC/BIA-CEL/31120/ 2017); and POCI-01-0145-FEDER-007274 i3S framework project co-funded by COMPETE 2020/ PORTUGAL 2020 through FEDER. S.V. and F.F. were supported by FCT fellowships SFRH/BD/125017/2016 and PD/BD/105745/2014. E.L. was supported by an FCT Investigator Grant (IF/00916/2014). U.B-D. and G.L. were supported by the Azrieli Faculty Fellowship (to U.D.-D.) and the DoD CDMRP Career Development Award (CA191138 to U.B.-D.). J.B. was supported by an FCT Investigator Grant (CEECIND/03482/2018) and the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (ERC-2015-StG-680156-ZPR)

KS(conf ): A Light-Weight Test if a ConvNet Operates Outside of Its Specifications

Computer vision systems for automatic image categorization have become accurate and reliable enough that they can run continuously for days or even years as components of real-world commercial applications. A major open problem in this context, however, is quality control. Good classification performance can only be expected if systems run under the specific conditions, in particular data distributions, that they were trained for. Surprisingly, none of the currently used deep network architectures has a built-in functionality that could detect if a network operates on data from a distribution that it was not trained for and potentially trigger a warning to the human users. In this work, we describe KS(conf), a procedure for detecting such outside of the specifications operation. Building on statistical insights, its main step is the applications of a classical Kolmogorov-Smirnov test to the distribution of predicted confidence values. We show by extensive experiments using ImageNet, AwA2 and DAVIS data on a variety of ConvNets architectures that KS(conf) reliably detects out-of-specs situations. It furthermore has a number of properties that make it an excellent candidate for practical deployment: it is easy to implement, adds almost no overhead to the system, works with all networks, including pretrained ones, and requires no a priori knowledge about how the data distribution could change

Recent Food Shortage Is Associated with Leprosy Disease in Bangladesh: A Case-Control Study

Although intensive control programs reduced the prevalence of leprosy worldwide, new cases of this infectious disease are still detected in several of the poorest areas of the world. Therefore the disease is known as a disease of poverty. To be able to control the disease it is important to know which aspects of poverty play a role in transmission and acquiring clinical signs of disease. In this study socio-economic circumstances of recently diagnosed leprosy patients were compared with those of a control population in the poverty stricken northwest area of Bangladesh where leprosy is common. A recent period of food shortage was the only socio-economic factor that was found related to leprosy disease in this study and not poverty as such. Food shortage is seasonal and poverty related in northwest Bangladesh, while malnutrition is known to lower immunity and make people more vulnerable to infectious diseases. Therefore it was concluded that malnutrition as an aspect of poverty played an important role in the development of the clinical signs of leprosy. We therefore recommend that nutritional support for high risk groups should be included in leprosy control programmes to reduce risk of disease in areas where leprosy is common

The Prevalence of Previously Undiagnosed Leprosy in the General Population of Northwest Bangladesh

In order to estimate the level of leprosy in an area with many leprosy patients, we determined the prevalence of previously undiagnosed leprosy in the general population and compared this with the registered (or known) number of leprosy patients. We also compared it with the known prevalence of leprosy in contacts of leprosy patients. We examined 20 randomly selected geographical clusters of 1,000 persons each in two districts of Bangladesh, with over 4 million population. Physical examination was performed on all individuals. The number of newly found leprosy cases among 17,862 people above 5 years of age from the clusters was 27, giving a rate of previously undiagnosed leprosy of 15.1 per 10,000. This rate is six times higher than the registered prevalence, but three times lower than the rate in the most distant subgroup of contacts (neighbour of neighbour and social contacts) of leprosy patients in the same area. We conclude that in areas where leprosy is common, it may be preferable to do full village or neighbourhood surveys when a new leprosy patient is found, rather than to limit contact surveys to close contacts only, such as household members