Search results for "Neural"
showing 10 items of 2783 documents
Neural correlates of intimate picture stimuli in females
2018
Jacob et al. (2011) previously reported on intimate picture stimuli for emotion research in females in Psychiatry Research. Difficulties to engage in intimate relations constitute problems of many mental disorders, and intimacy must be differentiated from pure sex drive. Functional neuroimaging is an important tool to understand the pathophysiology of psychiatric disorders. We now studied cerebral activation in response to intimate stimuli in 35 healthy women. Comparison stimuli were taken from the International Affective Picture System. Neuroimaging revealed increased activation in bilateral occipitotemporal, parietal and anterior cingulate cortices extending to the orbitofrontal area. The…
Auditory brain stem responses in patients with human immunotropic virus infection of different stages.
1992
Thirty patients (26 men, 4 women) with human immunotropic virus infection of different stages were examined. Eleven patients had a history of i.v. drug abuse, nine patients had a history of treated lues infection, and one patient suffered from Kaposi's sarcoma. At the time of the examination, opportunistic infections or acute encephalitis were not apparent in any patient. All patients underwent otoneurological examinations, including pure-tone audiometry, caloric vestibular testing, and recording of the auditory brain stem responses (ABR). Six patients reported onset of hearing impairment during the last 3 yr. Two of them had flat sensorineural hearing loss; in the other cases, pure-tone au…
The colocalizations of pulp neural stem cells markers with dentin matrix protein-1, dentin sialoprotein and dentin phosphoprotein in human denticle (…
2021
Abstract Background The primary dentin, secondary dentin, and reactive tertiary dentin are formed by terminal differentiated odontoblasts, whereas atubular reparative tertiary dentin is formed by odontoblast-like cells. Odontoblast-like cells differentiate from pulpal stem cells, which express the neural stem cell markers nestin, S100β, Sox10, and P0. The denticle (pulp stone) is an unique mineralized extracellular matrix that frequently occurs in association with the neurovascular structures in the dental pulp. However, to date, the cellular origin of denticles in human dental pulp is unclear. In addition, the non-collagenous extracellular dentin matrix proteins dentin matrix protein 1 (DM…
Rapid parameter estimation of discrete decaying signals using autoencoder networks
2021
Machine learning: science and technology 2(4), 045024 (2021). doi:10.1088/2632-2153/ac1eea
Nonlinear Distribution Regression for Remote Sensing Applications
2020
In many remote sensing applications, one wants to estimate variables or parameters of interest from observations. When the target variable is available at a resolution that matches the remote sensing observations, standard algorithms, such as neural networks, random forests, or the Gaussian processes, are readily available to relate the two. However, we often encounter situations where the target variable is only available at the group level, i.e., collectively associated with a number of remotely sensed observations. This problem setting is known in statistics and machine learning as multiple instance learning (MIL) or distribution regression (DR). This article introduces a nonlinear (kern…
SHARP: Environment and Person Independent Activity Recognition with Commodity IEEE 802.11 Access Points
2022
In this article we present SHARP, an original approach for obtaining human activity recognition (HAR) through the use of commercial IEEE 802.11 (Wi-Fi) devices. SHARP grants the possibility to discern the activities of different persons, across different time-spans and environments. To achieve this, we devise a new technique to clean and process the channel frequency response (CFR) phase of the Wi-Fi channel, obtaining an estimate of the Doppler shift at a radio monitor device. The Doppler shift reveals the presence of moving scatterers in the environment, while not being affected by (environment-specific) static objects. SHARP is trained on data collected as a person performs seven differe…
Learning Automata Based Q-learning for Content Placement in Cooperative Caching
2019
An optimization problem of content placement in cooperative caching is formulated, with the aim of maximizing sum mean opinion score (MOS) of mobile users. Firstly, a supervised feed-forward back-propagation connectionist model based neural network (SFBC-NN) is invoked for user mobility and content popularity prediction. More particularly, practical data collected from GPS-tracker app on smartphones is tackled to test the accuracy of mobility prediction. Then, a learning automata-based Q-learning (LAQL) algorithm for cooperative caching is proposed, in which learning automata (LA) is invoked for Q-learning to obtain an optimal action selection in a random and stationary environment. It is p…
Emergency Detection with Environment Sound Using Deep Convolutional Neural Networks
2020
In this paper, we propose a generic emergency detection system using only the sound produced in the environment. For this task, we employ multiple audio feature extraction techniques like the mel-frequency cepstral coefficients, gammatone frequency cepstral coefficients, constant Q-transform and chromagram. After feature extraction, a deep convolutional neural network (CNN) is used to classify an audio signal as a potential emergency situation or not. The entire model is based on our previous work that sets the new state of the art in the environment sound classification (ESC) task (Our paper is under review in the IEEE/ACM Transactions on Audio, Speech and Language Processing and also avai…
Online Fault Diagnosis System for Electric Powertrains Using Advanced Signal Processing and Machine Learning
2018
Online condition monitoring and fault diagnosis systems are necessary to prevent unexpected downtimes in critical electric powertrains. The machine learning algorithms provide a better way to diagnose faults in complex cases, such as mixed faults and/or in variable speed conditions. Most of studies focus on training phases of the machine learning algorithms, but the development of the trained machine learning algorithms for an online diagnosis system is not detailed. In this study, a complete procedure of training and implementation of an online fault diagnosis system is presented and discussed. Aspects of the development of an online fault diagnosis based on machine learning algorithms are…
Proba-V cloud detection Round Robin: Validation results and recommendations
2017
This paper discusses results from 12 months of a Round Robin exercise aimed at the inter-comparison of different cloud detection algorithms for Proba-V. Clouds detection is a critical issue for satellite optical remote sensing, since potential errors in cloud masking directly translates into significant uncertainty in the retrieved downstream geophysical products. Cloud detection is particularly challenging for Proba-V due to the presence of a limited number of spectral bands and the lack of thermal infrared bands. The main objective of the project was the inter-comparison of several cloud detection algorithms for Proba-V over a wide range of surface types and environmental conditions. Prob…