Open challenges for Machine Learning based Early Decision-Making research

More and more applications require early decisions, i.e. taken as soon as possible from partially observed data. However, the later a decision is made, the more its accuracy tends to improve, since the description of the problem to hand is enriched over time. Such a compromise between the earliness and the accuracy of decisions has been particularly studied in the field of Early Time Series Classification. This paper introduces a more general problem, called Machine Learning based Early Decision Making (ML-EDM), which consists in optimizing the decision times of models in a wide range of settings where data is collected over time. After defining the ML-EDM problem, ten challenges are identified and proposed to the scientific community to further research in this area. These challenges open important application perspectives, discussed in this paper

Quantitative Evaluation of Percussive Gestures by Ranking Trainees versus Teacher

International audienceIn this paper we characterize timpani gestures by temporal kinematic features, containing most information responsible for the sound-producing actions. In order to evaluate the feature sets, a classification approach is conducted under three main attack categories (legato, accent and vertical accent) and sub-categories (dynamics, striking position). Two studies are carried out: intra-subject and inter-subjects classification. Results are presented in terms of a quantitative ranking of students, using professional gestures as training set, and their gestures as test set

Low prevalence of colonoscopic surveillance of inflammatory bowel disease patients with longstanding extensive colitis: a clinical practice survey nested in the CESAME cohort

International audienceBackground: Surveillance colonoscopy is recommended for inflammatory bowel disease (IBD) patients with longstanding extensive colitis (LEC). Aims: To assess modalities and results of colonoscopic surveillance in a subset of CESAME cohort patients at high risk of colorectal cancer (CRC) and followed in university French hospitals. Methods: Among 910 eligible patients with more than a 7-year history of extensive colitis at CESAME enrolment, 685 patients completed a questionnaire on surveillance colonoscopy and 102 were excluded because of prior proctocolectomy. Finally, 583 patients provided information spanning a median period of 41 months (IQR 38-43) between cohort enrolment and the end of follow-up. Details of the colonoscopic procedures and histological findings were obtained for 440 colonoscopies in 270 patients. Results: Only 53.5% (n=312) of the patients with LEC had at least one surveillance colonoscopy during the study period, with marked variations across the 9 participating centres (27.3% to 70.0%, p= < 0.0001). Surveillance rate was significantly lower in Crohn's colitis than in ulcerative colitis (UC) (47.6% vs 68.5%, p=< 0.0001). Independent predictors of colonoscopic surveillance were male sex, UC IBD subtype, longer disease duration, previous history of CRC, and disease management in a centre with large IBD population. Random biopsies, targeted biopsies and chromoendoscopy were performed during respectively 70.7%, 26.6 and 30.0% of surveillance colonoscopies. Two cases of high-grade dysplasia were detected in patients undergoing colonoscopic surveillance. Two advanced-stage CRC were diagnosed in patients who did not have colonosocopic surveillance. Conclusions: Colonoscopic surveillance rate is low in IBD patients with longstanding extensive colitis

DEIMOS: A beamline dedicated to dichroism measurements in the 350-2500 eV energy range:

The DEIMOS (Dichroism Experimental Installation for Magneto-Optical Spectroscopy) beamline was part of the second phase of the beamline development at French Synchrotron SOLEIL (Source Optimisee de Lumiere a Energie Intermediaire du LURE) and opened to users in March 2011. It delivers polarized soft x-rays to perform x-ray absorption spectroscopy, x-ray magnetic circular dichroism, and x-ray linear dichroism in the energy range 350-2500 eV. The beamline has been optimized for stability and reproducibility in terms of photon flux and photon energy. The main end-station consists in a cryo-magnet with 2 split coils providing a 7 T magnetic field along the beam or 2 T perpendicular to the beam with a controllable temperature on the sample from 370 K down to 1.5 K. (C) 2014 AIP Publishing LLC

A Heuristic Method for Large-Scale Cognitive-Diagnostic Computerized Adaptive Testing

© ACM 2017. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in ACM Digital Library, http://dx.doi.org/10.1145/3051457.3054015.International audienceIn formative assessments, one wants to provide a useful feedback to the examinee at the end of the test. In order to reduce the number of questions asked in an assessment, adaptive testing models have been developed for cognitive diagnosis, such as the ones encountered in knowledge space theory. However, when the number of skills assessed is very huge, such methods cannot scale. In this paper, we present a new method to provide adaptive tests and useful feedback to the examinee, even with large databases of skills. It will be used in Pix, a platform for certification of digital competencies for every French citizen

Permanent Magnet-Based Quadrupoles for Plasma Acceleration Sources

The laser plasma accelerator has shown a great promise where it uses plasma wakefields achieving gradients as high as GeV/cm. With such properties, one would be able to build much more compact accelerators, compared to the conventional RF ones, that could be used for a wide range of fundamental research and applied applications. However, the electron beam properties are quite different, in particular, the high divergence, leading to a significant growth of the emittance along the transport line. It is, thus, essential to mitigate it via a strong focusing of the electron beam to enable beam transport. High-gradient quadrupoles achieving a gradient greater than 100 T/m are key components for handling laser plasma accelerator beams. Permanent magnet technology can be used to build very compact quadrupoles capable of providing a very large gradient up to 500 T/m. We present different designs, modeled with a 3D magnetostatic code, of fixed and variable systems. We also review different quadrupoles that have already been built and one design is compared to measurements

A TRADE OF STUDY FOR THE STRUCTURE OF THE CALLISTO VEHICLE EQUIPMENT BAY

During the preliminary design of the Vehicle Equipment Bay (VEB), a section of the CALLISTO experimental launcher, three structural concepts emerged. This paper gives an insight into the trade of study, leading to a consolidated concept for detailed design. The different concepts of accommodation are described. From a mechanical standpoint, structural analyses for strength, stability and stiffness are presented. The VEB is loaded by aerodynamic forces acting on the fins (the aerodynamic control system FCS/A), longitudinal loads from the Nose Fairing, acceleration loads on equipment unit’s and ground load cases (handling for verticalization and lifting of the vehicle). Based on simplified assumptions, each concept is sized to obtain a feasible design. The resulting masses and amplifications are compared and used for the trade of study. Furthermore, the evaluation of the concepts from an Assembly, Integration and Test (AIT) point of view (demonstrate feasibility of mounting/dismounting of equipment’s, access to screw connectors and equipment screws, accessibility, harness length, growth potential), from a Maintenance and Refurbishment Operations (MRO) standpoint (access to batteries, specific access to some critical items) and from a safety point of view (position and segregation of the safety chains) is presented. The results are sorted and compared in a trade of table. The final design again is checked for feasibility and key performance values like mass and stiffness. An outlook is given on the impact of certain unit requirements like e.g. a horizontal integration

Status and trends of albatrosses in the French Southern Territories, Western Indian Ocean

Today albatrosses are threatened worldwide, especially by fishing activities, and many populations are currently in decline. Albatrosses breeding at the French Southern Territories in the south-western Indian Ocean, on the Crozet, Kerguelen and Saint-Paul–Amsterdam island archipelagos, are monitored regularly. This monitoring has been based on a sample of species and sites, and there was a need for an assessment of the population trends for all species at each site. During the past 3 years most populations have been surveyed, allowing an assessment of the trends of albatrosses breeding at the archipelagos of the French Southern Territories over the past 40 years. Wandering Albatrosses show similar trends at all sites within the Crozet and Kerguelen archipelagos, with a recent recovery of colonies after strong declines in the 1970s. Amsterdam Albatrosses are increasing, albeit at lower rates during recent years. Indian Yellow-nosed Albatrosses show a global decline over the entire range. The trends among Black-browed and Grey-headed Albatrosses vary between colonies and archipelagos. Sooty Albatrosses have continuously decreased in numbers whereas Light-mantled Albatross numbers vary considerably between years, with an overall increase over the past 30 years. These results confirm that the French Southern Territories in the south-west Indian Ocean support a significant portion of the world populations of several albatross species. Several species appear to be steadily decreasing probably because of the impact of fisheries and disease outbreaks. The reasons for different trends among populations of the same species are not well understood and require further investigation

Open challenges for Machine Learning based Early Decision-Making research

International audienceMore and more applications require early decisions, i.e. taken as soon as possible from partially observed data. However, the later a decision is made, the more its accuracy tends to improve, since the description of the problem to hand is enriched over time. Such a compromise between the earliness and the accuracy of decisions has been particularly studied in the field of Early Time Series Classification. This paper introduces a more general problem, called Machine Learning based Early Decision Making (ML-EDM), which consists in optimizing the decision times of models in a wide range of settings where data is collected over time. After defining the ML-EDM problem, ten challenges are identified and proposed to the scientific community to further research in this area. These challenges open important application perspectives, discussed in this paper

Simulations, Measurements, and Sorting of THOMX Ring Bending Magnets

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