Search results for "Percept"
showing 10 items of 3839 documents
Artificial Neural Networks to Predict the Power Output of a PV Panel
2014
The paper illustrates an adaptive approach based on different topologies of artificial neural networks (ANNs) for the power energy output forecasting of photovoltaic (PV) modules. The analysis of the PV module’s power output needed detailed local climate data, which was collected by a dedicated weather monitoring system. The Department of Energy, Information Engineering, and Mathematical Models of the University of Palermo (Italy) has built up a weather monitoring system that worked together with a data acquisition system. The power output forecast is obtained using three different types of ANNs: a one hidden layer Multilayer perceptron (MLP), a recursive neural network (RNN), and a gamma m…
What Factors Facilitate Good Learning Experiences in Clinical Studies in Nursing: Bachelor Students’ Perceptions
2013
Published version of an article from the journal:ISRN Nursing. Also available from the publisher: http://dx.doi.org/10.1155/2013/628679 Clinical studies constitute 50% of the bachelor program in nursing education in Norway, and the quality of these studies may be decisive for the students’ opportunities to learn and develop their professional competences. The aim of this study was to explore what bachelor students’ in nursing perceived to be important for having good learning experiences in clinical studies. Data was collected in a focus group interview with eight nursing students who were in the last year of the educational program. The interview was transcribed verbatim, and qualitative c…
Collecting and Using Students’ Digital Well-Being Data in Multidisciplinary Teaching
2018
This article examines how students (N=198; aged 13 to 17) experienced the new methods for sensor-based learning in multidisciplinary teaching in lower and upper secondary education that combine the use of new sensor technology and learning from self-produced well-being data. The aim was to explore how students perceived new methods from the point of view of their learning and did the teaching methods provide new information that could promote their own well-being. We also aimed to find out how to collect digital well-being data from a large number of students and how the collected big data set can be utilized to predict school success from the students’ well-being data by using machine lear…
Great Minds Think Alike? Spatial Search Processes Can Be More Idiosyncratic When Guided by More Accurate Information.
2022
Existing research demonstrates that pre-decisional information sampling strategies are often stablewithin a given person while varying greatly across people. However, it remains largely unknown whatdrives these individual differences, that is, why in some circumstances we collect information moreidiosyncratically. In this brief report, we present a pre-registered online study of spatial search. Usinga novel technique that combines machine-learning dimension reduction and sequence alignment algo-rithms, we quantify the extent to which the shape and temporal properties of a search trajectory areidiosyncratic. We show that this metric increases (trajectories become more idiosyncratic) when a p…
Imaging Quality of Bifocal Piggyback Intraocular Lens versus ReSTOR and TECNIS Multifocal Lenses
2009
Purpose The imaging quality provided by a piggyback integrated by a monofocal intraocular lens (IOL) + a bifocal IOL of zero power and +3.75 diopters of addition is compared with the optics quality of a simple multifocal IOL of the same power and addition. Methods The imaging quality was evaluated by determining the modulation transfer function (MTF), using an artificial eye simulating in vivo conditions of the anterior chamber, including an artificial cornea and a wet cell containing physiologic solution where the IOL was positioned. The MTFs of the bifocal piggyback for near and distance vision were measured, with pupil diameters of 3 and 5 mm, and compared with the MTFs of an equivalent …
Artificial Neural Networks and Linear Discriminant Analysis: A Valuable Combination in the Selection of New Antibacterial Compounds
2004
A set of topological descriptors has been used to discriminate between antibacterial and nonantibacterial drugs. Topological descriptors are simple integers calculated from the molecular structure represented in SMILES format. The methods used for antibacterial activity discrimination were linear discriminant analysis (LDA) and artificial neural networks of a multilayer perceptron (MLP) type. The following plot frequency distribution diagrams were used: a function of the number of drugs within a value interval of the discriminant function and the output value of the neural network versus these values. Pharmacological distribution diagrams (PDD) were used as a visualizing technique for the i…
Neural Classification of HEP Experimental Data
2009
High Energy Physics (HEP) experiments require discrimination of a few interesting events among a huge number of background events generated during an experiment. Hierarchical triggering hardware architectures are needed to perform this tasks in real-time. In this paper three neural network models are studied as possible candidate for such systems. A modified Multi-Layer Perception (MLP) architecture and a E alpha Net architecture are compared against a traditional MLP Test error below 25% is archived by all architectures in two different simulation strategies. E alpha Net performance are 1 to 2% better on test error with respect to the other two architectures using the smaller network topol…
A Study of Perceptron Mapping Capability to Design Speech Event Detectors
2006
Event detection is a fundamental yet critical component in automatic speech recognition (ASR) systems that attempt to extract knowledge-based features at the front-end level. In this context, it is common practice to design the detectors inside well-known frameworks based on artificial neural network (ANN) or support vector machine (SVM). In the case of ANN, speech scientists often design their detector architecture relying on conventional feed-forward multi-layer perceptron (MLP) with sigmoidal activation function. The aim of this paper is to introduce other ANN architectures inside the context of detection-based ASR. In particular, a bank of feed-forward MLPs using sinusoidal activation f…
Assigning discounts in a marketing campaign by using reinforcement learning and neural networks
2009
In this work, RL is used to find an optimal policy for a marketing campaign. Data show a complex characterization of state and action spaces. Two approaches are proposed to circumvent this problem. The first approach is based on the self-organizing map (SOM), which is used to aggregate states. The second approach uses a multilayer perceptron (MLP) to carry out a regression of the action-value function. The results indicate that both approaches can improve a targeted marketing campaign. Moreover, the SOM approach allows an intuitive interpretation of the results, and the MLP approach yields robust results with generalization capabilities.
Crane collision modelling using a neural network approach
2004
Abstract The objective of the present work is to find a Collision Detection algorithm to be used in the Virtual Reality crane simulator (UVSim®), developed by the Robotics Institute of the University of Valencia for the Port of Valencia. The method is applicable to box-shaped objects and is based on the relationship between the colliding object positions and their impact points. The tool chosen to solve the problem is a neural network, the multilayer perceptron, which adapts to the characteristics of the problem, namely, non-linearity, a large amount of data, and no a priori knowledge. The results achieved by the neural network are very satisfactory for the case of box-shaped objects. Furth…