Search results for "machine learning."

Hyperspectral Imaging for Non-invasive Diagnostics of Melanocytic Lesions

2022

Malignant melanoma poses a clinical diagnostic problem, since a large number of benign lesions are excised to find a single melanoma. This study assessed the accuracy of a novel non-invasive diagnostic technology, hyperspectral imaging, for melanoma detection. Lesions were imaged prior to excision and histopathological analysis. A deep neural network algorithm was trained twice to distinguish between histopathologically verified malignant and benign melanocytic lesions and to classify the separate subgroups. Furthermore, 2 different approaches were used: a majority vote classification and a pixel-wise classification. The study included 325 lesions from 285 patients. Of these, 74 were invasi…

2021

Aging and diabetes lead to protein glycation and cause dysfunction of collagen-containing tissues. The accompanying structural and functional changes of collagen significantly contribute to the development of various pathological malformations affecting the skin, blood vessels, and nerves, causing a number of complications, increasing disability risks and threat to life. In fact, no methods of non-invasive assessment of glycation and associated metabolic processes in biotissues or prediction of possible skin complications, e.g., ulcers, currently exist for endocrinologists and clinical diagnosis. In this publication, utilizing emerging photonics-based technology, innovative solutions in mac…

Treatment with Nicotine derived Nitrosamine Ketone NNK Causes Disruption of Blood Brain Barrier BBB and Microglia Activation in Mice

2022

4-Methylnitrosamino-1-(3-pyridyl)-1-butanone (NNK) is a nicotine metabolite produced within the tobacco plant, from combustion, and from metabolic breakdown. Cigarette Smoke (CS) continues to be a leading cause for decline of quality of life as well as deaths globally. While the link to poor health and eventually early death has been accepted for decades, it is increasingly recognized that smoking may contribute to a broad range of disorders. Epidemiologically, CS has been associated with neuroinflammation and several neurological disorders including Alzheimer’s disease, stroke, and multiple sclerosis. While direct links are not fully understood, studies in a humanized flow-based in vitro b…

Active Learning of Recursive Functions by Ultrametric Algorithms

2014

We study active learning of classes of recursive functions by asking value queries about the target function f, where f is from the target class. That is, the query is a natural number x, and the answer to the query is f(x). The complexity measure in this paper is the worst-case number of queries asked. We prove that for some classes of recursive functions ultrametric active learning algorithms can achieve the learning goal by asking significantly fewer queries than deterministic, probabilistic, and even nondeterministic active learning algorithms. This is the first ever example of a problem where ultrametric algorithms have advantages over nondeterministic algorithms.

Combining Inter-Subject Modeling with a Subject-Based Data Transformation to Improve Affect Recognition from EEG Signals

2019

Existing correlations between features extracted from Electroencephalography (EEG) signals and emotional aspects have motivated the development of a diversity of EEG-based affect detection methods. Both intra-subject and inter-subject approaches have been used in this context. Intra-subject approaches generally suffer from the small sample problem, and require the collection of exhaustive data for each new user before the detection system is usable. On the contrary, inter-subject models do not account for the personality and physiological influence of how the individual is feeling and expressing emotions. In this paper, we analyze both modeling approaches, using three public repositories. T…

First observation of a baryonic Bc+ decay

2014

A baryonic decay of the $B_c^+$ meson, $B_c^+\to J/\psi p\overline{p}\pi^+$, is observed for the first time, with a significance of $7.3$ standard deviations, in $pp$ collision data collected with the LHCb detector and corresponding to an integrated luminosity of $3.0$ fb$^{-1}$ taken at center-of-mass energies of $7$ and $8$ $\mathrm{TeV}$. With the $B_c^+\to J/\psi \pi^+$ decay as normalization channel, the ratio of branching fractions is measured to be \begin{equation*} \frac{\mathcal{B}(B_c^+\to J/\psi p\overline{p}\pi^+)}{\mathcal{B}(B_c^+\to J/\psi \pi^+)} = 0.143^{\,+\,0.039}_{\,-\,0.034}\,(\mathrm{stat})\pm0.013\,(\mathrm{syst}). \end{equation*} The mass of the $B_c^+$ meson is dete…

Artificial neural networks for neutron/ γ discrimination in the neutron detectors of NEDA

2020

Three different Artificial Neural Network architectures have been applied to perform neutron/? discrimination in NEDA based on waveform and time-of-flight information. Using the coincident ?-rays from AGATA, we have been able to measure and compare on real data the performances of the Artificial Neural Networks as classifiers. While the general performances are quite similar for the data set we used, differences, in particular related to the computing times, have been highlighted. One of the Artificial Neural Network architecture has also been found more robust to time misalignment of the waveforms. Such a feature is of great interest for online processing of waveforms. Narodowe Centrum Nau…

Assessment of Proton Direct Ionization for the Radiation Hardness Assurance of Deep Submicron SRAMs Used in Space Applications

2021

Proton direct ionization from low-energy protons has been shown to have a potentially significant impact on the accuracy of prediction methods used to calculate the upset rates of memory devices in space applications for state-of-the-art deep sub-micron technologies. The general approach nowadays is to consider a safety margin to apply over the upset rate computed from high-energy proton and heavy ion experimental data. The data reported here present a challenge to this approach. Different upset rate prediction methods are used and compared in order to establish the impact of proton direct ionization on the total upset rate. No matter the method employed the findings suggest that proton dir…

A comparison between industrial experts' and novices' haptic perceptual organization: a tool to identify descriptors of the handle of fabrics

2004

Abstract In descriptive analysis, the establishing of the list of attributes is crucial. Attributes should account for consumers' perceptions and be understood by professionals for efficient communication. This work was aimed at identifying the most appropriate attributes for fabric description from the terminology associated with both experts' and novices' haptic perceptual spaces. Eleven industrial experts and two groups of novices (20 males and 20 females) evaluated 26 clothing fabrics. They performed (1) a free-sorting task based on haptic similarities, (2) a description of the previously formed groups, and (3) a hedonic rating task for each fabric. The perceptual organization was simil…

Classification and retrieval on macroinvertebrate image databases

2011

Aquatic ecosystems are continuously threatened by a growing number of human induced changes. Macroinvertebrate biomonitoring is particularly efficient in pinpointing the cause-effect structure between slow and subtle changes and their detrimental consequences in aquatic ecosystems. The greatest obstacle to implementing efficient biomonitoring is currently the cost-intensive human expert taxonomic identification of samples. While there is evidence that automated recognition techniques can match human taxa identification accuracy at greatly reduced costs, so far the development of automated identification techniques for aquatic organisms has been minimal. In this paper, we focus on advancing …