Search results for "Neural"
showing 10 items of 2783 documents
Use of machine learning approaches to improve non-invasive skin melanoma diagnostic method in spectral range 450 - 950nm
2020
Non-invasive skin cancer diagnostic methods develop rapidly thanks to Deep Learning and Convolutional Neural Networks (CNN). Currently, two types of diagnostics are popular: (a) using single image taken under white illumination and (b) using multiple images taken in narrow spectral bands. The first method is easier to implement, but it is limited in accuracy. The second method is more sensitive, because it is possible to use illumination considering the absorption bands of the skin chromophores and the optical properties of the skin. Currently CNN use a single white light image, due to the availability of large datasets with lesion images. Since CNN processing and analysis requires a large …
Absorption edge in silica glass
2005
Measurements of optical absorption in the v-UV range in a variety of silica glass are used to determine the width of the absorption edge (Urbach energy). Measured values range from 60 meV up to 180 meV. So high a variability over silica types is tentatively ascribed to the different disorder degree, which characterizes different materials.
Dynamic Economic Load Dispatch using Levenberg Marquardt Algorithm
2018
Abstract Economic Load Dispatch (ELD) is a very important feature of power system network. This work proposes the novel approach which considers the constraint of ramp rate limit (RRL) to solve the ELD problem. It build up the time varying dynamic economic load dispatch in which load dispatching is calculated for each specified time interval, first it is tested with conventional lambda iteration technique and then the outcomes are used to train artificial neural network (ANN) it is based on Levenberg Marquardt algorithm (LMA).As compared with any other ANN method, the Levenberg Marquardt algorithm based dynamic economic load dispatch is more swift and precise. The propose algorithm is teste…
PDGFRα-Positive B Cells Are Neural Stem Cells in the Adult SVZ that Form Glioma-like Growths in Response to Increased PDGF Signaling
2006
Neurons and oligodendrocytes are produced in the adult brain subventricular zone (SVZ) from neural stem cells (B cells), which express GFAP and have morphological properties of astrocytes. We report here on the identification B cells expressing the PDGFRalpha in the adult SVZ. Specifically labeled PDGFRalpha expressing B cells in vivo generate neurons and oligodendrocytes. Conditional ablation of PDGFRalpha in a subpopulation of postnatal stem cells showed that this receptor is required for oligodendrogenesis, but not neurogenesis. Infusion of PDGF alone was sufficient to arrest neuroblast production and induce SVZ B cell proliferation contributing to the generation of large hyperplasias wi…
1-Methyl-?-carboline (Harmane), a potent endogenous inhibitor of benzodiazepine receptor binding
1980
The interaction of several beta-carbolines with specific [3H]-flunitrazepam binding to benzodiazepine receptors in rat brain membranes was investigated. Out of the investigated compounds, harmane and norharmane were the most potent inhibitors of specific [3H]-flunitrazepam binding, with IC50-values in the micromolar range. All other derivatives, including harmine, harmaline, and several tetrahydroderivatives were at least ten times less potent. Harmane has been previously found in rat brain and human urine, so it is the most potent endogenous inhibitor of specific [3H]-flunitrazepam binding known so far, with a several fold higher affinity for the benzodiazepine receptor than inosine and hy…
Convolutional Matrix Factorization for Recommendation Explanation
2018
In this paper, we introduce a novel recommendation model, which harnesses a convolutional neural network to mine meaningful information from customer reviews, and integrates it with matrix factorization algorithm seamlessly. It is a valid method to improve the transparency of CF algorithms.
Comparing Recurrent Neural Networks using Principal Component Analysis for Electrical Load Predictions
2021
Electrical demand forecasting is essential for power generation capacity planning and integrating environment-friendly energy sources. In addition, load predictions will help in developing demand-side management in coordination with renewable power generation. Meteorological conditions influence urban area load pattern; therefore, it is vital to include weather parameters for load predictions. Machine Learning algorithms can effectively be used for electrical load predictions considering impact of external parameters. This paper explores and compares the basic Recurrent Neural Networks (RNN); Simple Recurrent Neural Networks (Vanilla RNN), Gated Recurrent Units (GRU), and Long Short-Term Me…
A Deep Reinforcement Learning scheme for Battery Energy Management
2020
Deep reinforcement learning is considered promising for many energy cost optimization tasks in smart buildings. How-ever, agent learning, in this context, is sometimes unstable and unpredictable, especially when the environments are complex. In this paper, we examine deep Reinforcement Learning (RL) algorithms developed for game play applied to a battery control task with an energy cost optimization objective. We explore how agent behavior and hyperparameters can be analyzed in a simplified environment with the goal of modifying the algorithms for increased stability. Our modified Deep Deterministic Policy Gradient (DDPG) agent is able to perform consistently close to the optimum over multi…
Acute and chronic pain
2017
Acute or chronic pain is a complex multidimensional neuronal response that draws attention to damaging or potentially damaging situations. A complex cascade of events takes place between the triggering occurrence of irritation and the final result of pain perception. In the beginning the nociceptor transforms the noxious threat into a signal.
Epigenetic regulation of stemness maintenance in the neurogenic niches
2015
In the adult mouse brain, the subventricular zone lining the lateral ventricles and the subgranular zone in the dentate gyrus of the hippocampus are two zones that contain neural stem cells (NSCs) with the capacity to give rise to neurons and glia during the entire life of the animal. Spatial and temporal regulation of gene expression in the NSCs population is established and maintained by the coordinated interaction between transcription factors and epigenetic regulators which control stem cell fate. Epigenetic mechanisms are heritable alterations in genome function that do not involve changes in DNA sequence itself but that modulate gene expression, acting as mediators between the environ…