An Automated Recording Method in Clinical Consultation to Rate the Limp in Lower Limb Osteoarthritis

For diagnosis and follow up, it is important to be able to quantify limp in an objective, and precise way adapted to daily clinical consultation. The purpose of this exploratory study was to determine if an inertial sensor-based method could provide simple features that correlate with the severity of lower limb osteoarthritis evaluated by the WOMAC index without the use of step detection in the signal processing. Forty-eight patients with lower limb osteoarthritis formed two severity groups separated by the median of the WOMAC index (G1, G2). Twelve asymptomatic age-matched control subjects formed the control group (G0). Subjects were asked to walk straight 10 meters forward and 10 meters back at self-selected walking speeds with inertial measurement units (IMU) (3-D accelerometers, 3-D gyroscopes and 3-D magnetometers) attached on the head, the lower back (L3-L4) and both feet. Sixty parameters corresponding to the mean and the root mean square (RMS) of the recorded signals on the various sensors (head, lower back and feet), in the various axes, in the various frames were computed. Parameters were defined as discriminating when they showed statistical differences between the three groups. In total, four parameters were found discriminating: mean and RMS of the norm of the acceleration in the horizontal plane for contralateral and ipsilateral foot in the doctor’s office frame. No discriminating parameter was found on the head or the lower back. No discriminating parameter was found in the sensor linked frames. This study showed that two IMUs placed on both feet and a step detection free signal processing method could be an objective and quantitative complement to the clinical examination of the physician in everyday practice. Our method provides new automatically computed parameters that could be used for the comprehension of lower limb osteoarthritis. It may not only be used in medical consultation to score patients but also to monitor the evolution of their clinical syndrome during and after rehabilitation. Finally, it paves the way for the quantification of gait in other fields such as neurology and for monitoring the gait at a patient’s home

Sloshing in the shipping industry: risk modelling through multivariate heavy-tail analysis

International audienceIn the liquefied natural gas (LNG) shipping industry, the phenomenon of sloshing can lead to the occurrence of very high pressures in the tanks of the vessel. The issue of modelling or estimating the probability of the simultaneous occurrence of such extremal pressures is now crucial from the risk assessment point of view. In this paper, heavy-tail modelling, widely used as a conservative approach to risk assessment and corresponding to a worst-case risk analysis, is applied to the study of sloshing. Multivariate heavy-tailed distributions are considered, with Sloshing pressures investigated by means of small-scale replica tanks instrumented with d >1 sensors. When attempting to fit such nonparametric statistical models, one naturally faces computational issues inherent in the phenomenon of dimensionality. The primary purpose of this article is to overcome this barrier by introducing a novel methodology. For d-dimensional heavy-tailed distributions, the structure of extremal dependence is entirely characterised by the angular measure, a positive measure on the intersection of a sphere with the positive orthant in Rd. As d increases, the mutual extremal dependence between variables becomes difficult to assess. Based on a spectral clustering approach, we show here how a low dimensional approximation to the angular measure may be found. The nonparametric method proposed for model sloshing has been successfully applied to pressure data. The parsimonious representation thus obtained proves to be very convenient for the simulation of multivariate heavy-tailed distributions, allowing for the implementation of Monte-Carlo simulation schemes in estimating the probability of failure. Besides confirming its performance on artificial data, the methodology has been implemented on a real data set specifically collected for risk assessment of sloshing in the LNG shipping industry

Recent developments in pattern mining

Pattern Mining is one of the most researched topics in the data mining community. Literally hundreds of algorithms for efficiently enumerating all frequent itemsets have been proposed. These exhaustive algorithms, however, all suffer from the pattern explosion problem. Depending on the minimal support threshold, even for moderately sized databases, millions of patterns may be generated. Although this problem is by now well recognized in te pattern mining community, it has not yet been solved satisfactorily. In my talk I will give an overview of the different approaches that have been proposed to alleviate this problem. As a first step, constraint-based mining and condensed representations such as the closed itemsets and the non-derivable itemsets were introduced. These methods, however, still produce too many and redundant results. More recently, promising methods based upon the minimal description length principle, information theory, and statistical models have been introduced. We show the respective advantages and disadvantages of these approaches and their connections, and illustrate their usefulness on real life data. After this overview we move from itemsets to more complex patterns, such as sequences and graphs. Even though these extensions seem trivial at first, they turn out to be quite challenging. I will end my talk with an overview of what I consider to be important open questions in this fascinating research area

Quantitative Analysis of Dynamic Fault Trees Based on the Coupling of Structure Functions and Monte Carlo Simulation

International audienceThis paper focuses on the quantitative analysis of Dynamic Fault Trees (DFTs) by means of Monte Carlo simulation. In a previous article, we defined an algebraic framework allowing to determine the structure function of DFTs. We exploit this structure function and the minimal cut sequences that it allows to determine, to know the failure mode configuration of the system, which is an input of Monte Carlo simulation. We show that the results obtained are in good accordance with theoretical results and that some results, such as importance measures and sensitivity indexes, are not provided by common quantitative analysis and yet interesting. We finally illustrate our approach on a DFT example from the literature

submitted to IFAC World Congress 2008 Gap-free Bounds for Stochastic Multi-Armed Bandit

Abstract: We consider the stochastic multi-armed bandit problem with unknown horizon. We present a randomized decision strategy which is based on updating a probability distribution through a stochastic mirror descent type algorithm. We consider separately two assumptions: nonnegative losses or arbitrary losses with an exponential moment condition. We prove optimal (up to logarithmic factors) gap-free bounds on the excess risk of the average over time of the instantaneous losses induced by the choice of a specific action. 1

Regular Inference as Vertex Coloring

Contains fulltext : 103689.pdf (preprint version ) (Closed access

The State of Black Criminology: A Focus Group of the Perspectives of African American Criminologists

According to Minnesota State University, Mankato, diversity is a commitment to create an understanding and appreciation of diverse peoples and diverse perspectives; a commitment to create an academic, cultural workplace environment and community that develops mutual respect for all and celebrates our differences. Realizing that all perspectives cannot be easily addressed by any one course, Diverse Culture Graduation Requirements implemented Corrections courses under its Goal1, that failed to address or include perspectives of African American criminologists. To date, the Criminal Justice textbooks used in Corrections 106 and Corrections 444 do not include any African American criminologist’s perspective. From this study we hoped to gain a better understanding of African American criminologist perspectives on criminal justice and corrections policy. We hoped that our findings would have an impact on the corrections department and its faculty as well as encourage the implementation of a more diverse curriculum. In order to gain a better insight into the perspective of African American criminologist a focus group was conducted to examine two issues; their attitudes towards criminal justice punitive policy in the criminal justice system and the exclusion of their perspectives within in the classroom