Search results for "Machine learning"

A Concurrent Neural Classifier for HTML Documents Retrieval

2003

A neural based multi-agent system for automatic HTML pages retrieval is presented. The system is based on the EαNet architecture, a neural network having good generalization capabilities and able to learn the activation function of its hidden units. The starting hypothesis is that the HTML pages are stored in networked repositories. The system goal is to retrieve documents satisfying a user query and belonging to a given class (i.e. documents containing the word “football” and talking about “Sports”). The system is composed by three interacting agents: the EαNet Neural Classifier Mobile Agent, the Query Agent, and the Locator Agent. The whole system was successfully implemented exploiting t…

Assessment of mental stress through the analysis of physiological signals acquired from wearable devices

2019

Mental stress is a physiological state that directly correlates to the quality of life of individuals. Generally speaking, but especially true for disabled or elderly subjects, the assessment of such condition represents a very strong indicator correlated to the difficulties, and, in some case, to the frustration that derives from the execution of a task that results troublesome to be accomplished. This article describes a novel procedure for the assessment of the mental stress level through the use of low invasive wireless wearable devices. The information contained in electrocardiogram, respiratory signal, blood volume pulse, and electroencephalogram was extracted to set up an estimator f…

Analysis and simulation of creativity learning by means of artificial neural networks

2007

The paper presents a new neural network approach for analysis and simulation of creative behavior. The used concept of Dynamically Controlled Neural Gas (DyCoNG) entails a combination of Dynamically Controlled Network [Perl, J. (2004a). A neural network approach to movement pattern analysis. Human Movement Science,23, 605-620] and Growing Neural Gas (Fritzke, 1995) by quality neurons. A quality neuron reflects the rareness of a piece of information and therefore can measure the originality of a recorded activity that was assigned to the neuron during the network training. The DyCoNG approach was validated using data from a longitudinal field-based study. The creative behavior of 42 particip…

Psychophysically Tuned Divisive Normalization Approximately Factorizes the PDF of Natural Images

2010

The conventional approach in computational neuroscience in favor of the efficient coding hypothesis goes from image statistics to perception. It has been argued that the behavior of the early stages of biological visual processing (e.g., spatial frequency analyzers and their nonlinearities) may be obtained from image samples and the efficient coding hypothesis using no psychophysical or physiological information. In this work we address the same issue in the opposite direction: from perception to image statistics. We show that psychophysically fitted image representation in V1 has appealing statistical properties, for example, approximate PDF factorization and substantial mutual informatio…

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…