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Author reputation is a very important variable for evaluating web comments. However, there is no formal definition for calculating its value. This paper presents an adaptation of the approach presented by Sousa (2015) for evaluating the importance of comments about products and services available online, emphasizing measures of author reputation. The implemented adaptation consists in defining six...
This paper present a keystroke dynamics Biometrie system using neural network as its classifier to recognize an individual. Biometric scheme are being widely used as their security merits over the earlier authentication system based on their history, that is the records were easily lost, guessed or forget. Biometric is more complex than password and is unique for each individual. Keystroke dynamics,...
In this paper, we present a study done on quadratic neurons to solve the pattern classification problems. The paper compares the classification results obtained by quadratic neural network(QUAD) with normal single and multilayer perceptron(MLP). Examples with randomly generated toy datasets are used for understanding and visualization. The standard datasets such as Iris, MNIST and others are used...
Accurately and fast detection of weight of objects has an important place for lots of academic and industrial application at the present time. In this work, it was aimed to estimate weight of eggs in a distance independent manner using image processing and artificial neural networks (ANN). The constituted system consists of a camera, artificial lighting system, reflector and reference image. Object...
Artificial neural networks (ANN) are one of the dominant learning techniques used in the field of artificial intelligence and have significant assets as their properties imitate the behavior of neurons in human brain. In this paper is presented the research focused on ANN, specifically Multilayer perceptron (MPL) with the aim of detection of human face in the still image. This system was implemented...
Smartphones are the singular most utilised device able to track and monitor our activity continuously from which signatures such as our typing can be detecting. Various situations such as loss of phone, passing on to family members or friends require us to consider continuous modes of passive authentication. This paper explores how typing heat maps can improve user authentication for touch enabled...
Estimation of depth in a Neural Network (NN) or Artificial Neural Network (ANN) is an integral as well as complicated process. In this article, we propose a way of using the transformation of functions combined with recursive nature to have an adaptive, transcursive algorithm to represent the backpropagation concept used in deep learning for a Multilayer Perceptron Network. Each function can be used...
The main body of the literature states that Artificial Neural Networks must be regarded as a "black box" without further interpretation due to the inherent difficulties for analyze the weights and bias terms. Some authors claim that ANN trained as a regression device tend to organize itself by specializing some neurons to learn the main relationships embedded in the training set, while other...
When faced with the struggle to extract insights from complex and noisy data, often the end user may assume that there exist no significant relation between the features and target in the dataset and is forced to either quit the study or resort to alternate means. Artificial Neural Networks (ANNs) might be of help to predict some of the most complex data used in the industry. But it is neither easy...
Tourism industry outperformed the rest of the economy in recent years, growing faster than other industries such as manufacturing, financial services and retail. Tourism is gaining prominence in enhancing country's income, but, in India it is still largely unorganized. In this paper, an in-depth investigation of Indian tourists' hospitality preference has been done. Factor analysis was carried out...
Using EMG signals as control signals has been a widely accepted option in the last decades. Using a wide array of techniques, EMG signals can be used in a variety of practical ways, from prostethics to exoesqueletons, however a concrete functional relationship between EMG signals and the dynamic and kinematic aspects of the upper limbs has not been established. Nowadays, almost every device that uses...
Electric energy plays a vital role in the achievement of social, economic and environment development of any nation. Thus, efficient demand planning and production of energy is needed to avoid too much over/under-estimation of electric load. In this study, the researchers proposed a scheme with eight steps for a dynamic time series forecasting using adaptive multilayer perceptron with minimal complexity...
Since the development of the Multilayer Perceptron, many types of artificial neural networks (ANNs) have emerged, each having best performances in solving particular types of problems. Current research developments focus on hybrid neural models, which combine neural and symbolic computation elements. In power engineering, ANNs are used today in a variety of applications, including optimization, approximation,...
Query response time prediction is an important and challenging problem in database systems. Especially for applications which handle large amounts of data or where time loss and deadlocks are hardly tolerated, it is very useful to predict the query response times before actual execution. This paper aims to predict query response times automatically using neural network-based approaches, and compares...
Metamaterials are a broad class of artificial materials that could be engineered to wield effective permittivity and permeability characteristics to system requirements. In this work, a hybrid EM-optimization method using continuous-GA blended with MLP-ANN models is used for fast and accurate evaluation of cost function into continuous-GA simulations, in order to overcome the computational requirements...
In this paper, a highly integrable Field Programmable Gate Array-based hardware design of multilayer perceptron as a realization of an artificial neural network is presented. Such a hardware solution ensures a deterministic behavior required for any hard real-time compositions. The integration into existing systems is achieved by the application of UDP/IP. %A developed protocol enables the hardware...
In order to empower physical rehabilitation processes of motor disabled people, currently there is emergent efforts at scientific level aimed at developing new robotic devices such as exoskeletons. In physical therapy using robotic systems it is fundamental a high identification of human intentional movements to command such systems. To accomplish such movements identification or recognizing, in literature...
The novel instruments of the COSMO-SkyMed (CSK) Earth Observation programme, offer an opportunity to explore at various resolutions the information content of X-band signal backscattered with different polarizations. In spite of their potential to render additional information about an area of interest, speckle noise and artifacts make X-band acquisitions difficult to interpret. This is a motivating...
This paper describes a method of training an artificial neural network, specifically a multilayer perceptron (MLP), to act as a tool to help identify plants using morphological characters collected automatically from images of botanical herbarium specimens. A methodology is presented here to provide a practical way for taxonomists to use neural networks as automated identification tools, by collating...
The sanitation sector of São Paulo is responsible for a significant share of the brazilian market and the private sector participation in this segment has gained strength in recent years. To address the needs of the population and also give returns to shareholders, the sanitation company is constantly seeking to improve their results. Increase sales have become a major challenge for the managers of...
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