Search results for "Neural"

Development of Neural Network Prediction Models for the Energy Producibility of a Parabolic Dish: A Comparison with the Analytical Approach

2022

Solar energy is one of the most widely exploited renewable/sustainable resources for electricity generation, with photovoltaic and concentrating solar power technologies at the forefront of research. This study focuses on the development of a neural network prediction model aimed at assessing the energy producibility of dish–Stirling systems, testing the methodology and offering a useful tool to support the design and sizing phases of the system at different installation sites. Employing the open-source platform TensorFlow, two different classes of feedforward neural networks were developed and validated (multilayer perceptron and radial basis function). The absolute novelty of this approac…

2015

Study que Stion What are the long term trends in the total (live births, fetal deaths, and terminations of pregnancy for fetal anomaly) and live birth prevalence of neural tube defects (NTD) in Europe, where many countries have issued recommendations for folic acid supplementation but a policy for mandatory folic acid fortification of food does not exist? Method S This was a population based, observational study using data on 11 353 cases of NTD not associated with chromosomal anomalies, including 4162 cases of anencephaly and 5776 cases of spina bifida from 28 EUROCAT (European Surveillance of Congenital Anomalies) registries covering approximately 12.5 million births in 19 countries betwe…

Follow-up in transthyretin familial amyloid polyneuropathy: Useful investigations

2020

Patients with transthyretin amyloid polyneuropathy (TTR-FAP) and asymptomatic mutation-carriers have to be regularly followed-up in order to identify disease progression and the time point for starting or modifying therapy. In this case series we describe the potential suitability of different variables as progression markers. We retrospectively analyzed the follow-up charts of 10 TTR-FAP patients. Clinical examination included the Neuropathy Impairment Score of Lower Limb (NIS-LL), temperature perception thresholds, nerve conduction and autonomic function tests. The NIS-LL had the greatest value for a sensitive and correct follow-up for all TTR-FAP stages. All other examinations provided u…

Analisi e previsione dei consumi urbani attraverso l’applicazione di modelli a rete neurale

2007

One-Dimensional Convolutional Neural Networks Combined with Channel Selection Strategy for Seizure Prediction Using Long-Term Intracranial EEG

2022

Seizure prediction using intracranial electroencephalogram (iEEG) has attracted an increasing attention during recent years. iEEG signals are commonly recorded in the form of multiple channels. Many previous studies generally used the iEEG signals of all channels to predict seizures, ignoring the consideration of channel selection. In this study, a method of one-dimensional convolutional neural networks (1D-CNN) combined with channel selection strategy was proposed for seizure prediction. First, we used 30-s sliding windows to segment the raw iEEG signals. Then, the 30-s iEEG segments, which were in three channel forms (single channel, channels only from seizure onset or free zone and all c…

One and Two Dimensional Convolutional Neural Networks for Seizure Detection Using EEG Signals

2021

Deep learning for the automated detection of epileptic seizures has received much attention during recent years. In this work, one dimensional convolutional neural network (1D-CNN) and two dimensional convolutional neural network (2D-CNN) are simultaneously used on electroencephalogram (EEG) data for seizure detection. Firstly, using sliding windows without overlap on raw EEG to obtain the definite one-dimension time EEG segments (1D-T), and continuous wavelet transform (CWT) for 1D-T signals to obtain the two-dimension time-frequency representations (2D-TF). Then, 1D-CNN and 2D-CNN model architectures are used on 1D-T and 2D-TF signals for automatic classification, respectively. Finally, t…

Cortical gene expression in spinal cord injury and repair: insight into the functional complexity of the neural regeneration program

2011

Traumatic spinal cord injury (SCI) results in the formation of a fibrous scar acting as a growth barrier for regenerating axons at the lesion site. We have previously shown (Klapka et al., 2005) that transient suppression of the inhibitory lesion scar in rat spinal cord leads to long distance axon regeneration, retrograde rescue of axotomized cortical motoneurons, and improvement of locomotor function. Here we applied a systemic approach to investigate for the first time specific and dynamic alterations in the cortical gene expression profile following both thoracic SCI and regeneration-promoting anti-scarring treatment (AST). In order to monitor cortical gene expression we carried out micr…

Data-Driven Interactive Multiobjective Optimization Using a Cluster-Based Surrogate in a Discrete Decision Space

2019

In this paper, a clustering based surrogate is proposed to be used in offline data-driven multiobjective optimization to reduce the size of the optimization problem in the decision space. The surrogate is combined with an interactive multiobjective optimization approach and it is applied to forest management planning with promising results. peerReviewed

Computational Modeling of Human Visual Function using Psychophysics, Deep Neural Networks, and Information Theory

2023

Visual perception is a key to unlocking the secrets of brain functions because most of the information is processed through the early visual system and then transmitted to the high-level cognitive perception brain regions. The brain functions as a self-organizing, bio-dynamic, and chaotic system that receives outside information and then decomposes it into pieces of information that can be processed efficiently and independently. The work connects natural image statistics, psychophysics, deep neural networks, and information theory to perceptual vision systems to explore how vision processes information from the outside world and how the information coupled drives functional connectivity be…

Peripheral Nerve Responses to Muscle Stretching: A Systematic Review

2021

Stretching is commonly used to increase range of motion and flexibility. Therefore, investigations are usually oriented towards the muscle-tendon unit. Limited evidence exists regarding potential effects of stretching on peripheral nerves which lie within muscles. The objective of this investigation will be to elucidate the responses of peripheral nerves to stretching. A literature search was performed using the following databases: Scopus, NLM Pubmed and ScienceDirect. Studies regarding the effects of stretching protocols on responses of peripheral nerves were retrieved for investigation. The NHLBI tool was used for quality assessment. Outcomes included nerve stiffness, nerve displacement,…