375 research outputs found
Classification with Asymmetric Label Noise: Consistency and Maximal Denoising
In many real-world classification problems, the labels of training examples
are randomly corrupted. Most previous theoretical work on classification with
label noise assumes that the two classes are separable, that the label noise is
independent of the true class label, or that the noise proportions for each
class are known. In this work, we give conditions that are necessary and
sufficient for the true class-conditional distributions to be identifiable.
These conditions are weaker than those analyzed previously, and allow for the
classes to be nonseparable and the noise levels to be asymmetric and unknown.
The conditions essentially state that a majority of the observed labels are
correct and that the true class-conditional distributions are "mutually
irreducible," a concept we introduce that limits the similarity of the two
distributions. For any label noise problem, there is a unique pair of true
class-conditional distributions satisfying the proposed conditions, and we
argue that this pair corresponds in a certain sense to maximal denoising of the
observed distributions.
Our results are facilitated by a connection to "mixture proportion
estimation," which is the problem of estimating the maximal proportion of one
distribution that is present in another. We establish a novel rate of
convergence result for mixture proportion estimation, and apply this to obtain
consistency of a discrimination rule based on surrogate loss minimization.
Experimental results on benchmark data and a nuclear particle classification
problem demonstrate the efficacy of our approach
Derivation and quantitative analysis of the differential self-interrogation Feynman-alpha method
A stochastic theory for a branching process in a neutron population with two
energy levels is used to assess the applicability of the differential
self-interrogation Feynman-alpha method by numerically estimated reaction
intensities from Monte Carlo simulations. More specifically, the variance to
mean or Feynman-alpha formula is applied to investigate the appearing
exponentials using the numerically obtained reaction intensities.Comment: Proceedings 52nd INMM conference, Palm Desert, 17-21 July 201
Analysis of postures for handwriting on touch screens without using tools
The act of handwriting affected the evolutionary development of humans and still impacts the motor cognition of individuals. However, the ubiquitous use of digital technologies has drastically decreased the number of times we really need to pick a pen up and write on paper. Nonetheless, the positive cognitive impact of handwriting is widely recognized, and a possible way to merge the benefits of handwriting and digital writing is to use suitable tools to write over touchscreens or graphics tablets. In this manuscript, we focus on the possibility of using the hand itself as a writing tool. A novel hand posture named FingerPen is introduced, and can be seen as a grasp performed by the hand on the index finger. A comparison with the most common posture that people tend to assume (i.e. index finger-only exploitation) is carried out by means of a biomechanical model. A conducted user study shows that the FingerPen is appreciated by users and leads to accurate writing traits
Integrating home monitoring for transcranial direct current stimulation (tDCS) therapy to professional care environment
Daily management of neurodegenerative diseases is one of the most striking scenarios
where an integrated health care system is essential for the continuous assistance to the
patient and requires qualification of the caregivers and their training. In particular,
patients affected by depression or chronic pain, as well as rehabilitating after stroke,
can be treated at home with non-invasive electrical neuromodulation (transcranial
Direct Current Stimulation, tDCS) in order to reduce daily travel expenses between
home and hospital. Home monitoring of patient undergoing tDCS is essential to (1)
optimize the stimulation parameters according to the current health status and to the
stimulation outcomes, and (2) assess disease progression. However, monitoring
effectiveness depends on the exchange of this information between the patient at home
and his/her reference neurologist. Currently, the health IT scenario is composed by two
independent environments, one dedicated to healthcare professionals (e.g., Electronic
Health Records, EHRs), and one including mobile devices applications dedicated to
citizens, caregivers and patients. Safety, communication and interoperability gaps
prevented from an effective data exchange between these two environments. The aim
of our work is to implement an integrated home monitoring system for tDCS patients,
in which a web-based platform for EHR management exchanges data with a patient\u2019s
mobile app
Widespread changes of white matter microstructure in obsessive-compulsive disorder: Effect of drug status.
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Initial Active Interrogation Experiments at The University of Michigan Linear Accelerator Laboratory
To support the mission of the Countering Weapons of Mass Destruction Office of the Department of Homeland Security, the Detection for Nuclear Nonproliferation group is researching active interrogation techniques and the development of new detection algorithms for fast neutron spectroscopy. The Countering Weapons of Mass Destruction Officehas loaned us a Varian M9 linear accelerator (linac), helium-3 detectors, boron-coated straw detectors, and perfluorocarbondetectors as part of this research, providing a variety of tools to conduct our experiments.In the summer of 2018, a thorough licensing process concluded, and preliminary experiments commenced. Later in the year, the facility was approved to possess and irradiate depleted uranium, which enabledus to conduct active interrogation experiments.In the fall of 2018, we conducted our first active interrogation measurements using the linac facility. The measurements used the linac to irradiate depleted uranium,lead, and tungsten targets to induce photonuclear reactions to emit fast neutrons. The neutrons were then detected using a simple helium-3 detector. Simulations were developed using MCNPX-PoliMi and MCNP 6.1 to validate the measured results. The simulations showed close agreement for depleted uranium but indicated that additional investigation is required for the lead and tungsten data. The facility will be indispensable as the researchprogressesbyproviding a mixed-radiation field consisting of fast neutrons and photons, which is similar to the radiation environment encountered in active interrogation scenarios.Additionally, the facility is involved inresearch related toradiation damage, dosimetry, and radiation-oncology.Future activities will involve characterization of photonuclear properties of various materials, and collaborations with other university researchers
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Measurements of Separate Neutron and Gamma-Ray Coincidences with Liquid Scintillators and Digital PSD Technique
A new technique is presented for the measurement of neutron and/or gamma-ray coincidences. Separate neutron neutron, neutron gamma-ray, gamma-ray neutron, and gamma-ray gamma-ray coincidences are acquired with liquid scintillation detectors and a digital pulse shape discrimination (PSD) technique based on standard charge integration method. The measurement technique allows for the collection of fast coincidences in a time window of the order of a few tens of nanoseconds between the coincident particles. The PSD allows for the acquisition of the coincidences in all particle combinations. The measurements are compared to results obtained with the MCNP-PoliMi code, which simulates neutron and gamma-ray coincidences from from a source on an event-by-event basis. This comparison leads to good qualitative agreement
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