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Dermatological diseases are the most prevalent diseases worldwide. Despite being common, its diagnosis is extremely difficult and requires extensive experience in the domain. In this research paper, we provide an approach to detect various kinds of these diseases. We use a dual stage approach which effectively combines Computer Vision and Machine Learning on clinically evaluated histopathological...
The use of artificial neural networks in many fields is still on the increase. The paper deals with application of neural networks as a data mining method to a prediction of the production line performance. Performance of production line was defined by output indicators like number of finished products, flow time and work in progress production. Predictive model was implemented in the program STATISTICA...
A real-time neuro car detection system based on the Haar-like feature is presented in this paper. The proposed system relies on an artificial neural network (ANN) to recognize the car object. ANN was trained using the Haar-like features extracted from the negative and positive car image data. The car objects vary with their sizes and trademarks. However, they have common features which can be assumed...
Due to its ability to solve nonlinear problems, Artificial Neural Network (ANN) could be applied in several areas of life. However, defining its architecture for solving a given problem is not formalized and remains an open research problem. On the other hand the complexity of such a technique due to its “black box” aspect, makes its interpretation more tedious. Since optimal factors completely cover...
In this paper we deal with one of the most relevant problems in the field of data mining, the real time processing and visualization of data streams. To deal with data streams we propose a novel approach that uses a neighborhood-based clustering. Instead of processing each new element one by one, we propose to process each group of new elements simultaneously. A clustering is applied on each new group...
Due to the huge increase in the size of the data it becomes troublesome to perform efficient analysis using the current traditional techniques. Big data put forward a lot of challenges due to its several characteristics like volume, velocity, variety, variability, value and complexity. Today there is not only a necessity for efficient data mining techniques to process large volume of data but in addition...
Cardiotocography is a diagnostic exam performed from the 28th week of pregnancy that registers the fetus cardiac frequency and uterine contractions. From this exam results a cardiotocogram whose reading and observation of the patterns contained in it allow an evaluation of the baby's condition and the fetal vitality in the maternal womb. This work aims the creation of a classification model using...
This paper presents a method for the medium-long-term wind speed prediction based on spatiotemporal evolution of weather fronts and Multi-Layer Perceptron Neural Network (MLP NN) data mining model. The proposed wind speed prediction model is achieved by using historical and current meteorological data, such as pressure, temperature and wind intensity, describing the evolution of the weather fronts...
This review paper explores the attempts made by the numerous authors in the field of material selection. There are ample amounts of works were carried out in the field of materials engineering with data mining approaches. From the literature it is revealed that not much of the work is explored on the classification of advanced composite materials using machine learning approaches.
In this paper a universal, coarse-grained reconfigurable architecture for hardware acceleration of decision trees (DTs), artificial neural networks (ANNs), and support vector machines (SVMs) is proposed. Using proposed architecture, two versions of DTs (Functional DT and Axis-Parallel DT), two versions of SVMs (with polynomial and radial kernels) and two versions of ANNs (Multi Layer Perceptron and...
Intensive Care Unit (ICU) admission is a major factor that affects the healthcare budget. ICU cost is extremely high because its resources are consumed through highly advanced equipment providing quality healthcare service for patients. Thus, the need for a predictive model for the decision to transfer stroke in-patients to the ICU is very important. Also, this predictive model will help to lower...
Closing prices of the financial stock market change daily at the end of each session. These changes happen because of many factors that affect the prices of the stocks. This study attempts to accurately predict closing prices by applying a data mining approach and investigate and identify the most influential factors of Dubai Financial Stock Market prices. The main objective of this study is to help...
In stock market, successful investors can earn maximum profits depended on a stock selection and a suitable time on trading. Generally, investors use two statistical techniques for making a decision, which are the fundamental analysis and the technical analysis. Recently, machine learning models which are a part of artificial intelligence, has been applied to enhance investors for investment. A number...
This paper proposes an intuitive yet simple machine learning (ML) approach that consist of two generic algorithms augmenting one another to solve problems they are not designed to solve. Since most machine learning algorithms are designed for a particular dataset or task, combining multiple ML algorithms can greatly improve the overall result by either helping tune one another, generalize, or adapt...
Automatic translation of out of vocabulary (OOV) terms has been extensively studied in the past, but multi-translatable OOV terms have received little attention. Multi-translatable OOV terms are OOV terms with some possible OOV synonyms, thus they have more than one correct translations. Traditional methods usually ignore such problem and neither identify/extract multi-translatable OOV terms nor translate...
Opinion Mining is the task of extracting opinions from a sentence on an instance. In this paper, we have collected the quotations from websites of three popular newspaper dailies of India - The Hindu, The Times of India and Deccan Chronicle on an instance. We have proposed a methodology to annotate, label and calculate subjectivity and objectivity of quotations. Using Supervised Learning Classifiers...
In these days, chronic diseases are the imperative reason for death in the world. Therefore, there is a noteworthy increment in consideration being paid to individual wellness as a preventative methodology in healthcare. However, creating and building a prediction model for chronic diseases is an extraordinary change to healthcare technology on the premise of data-analysis and decision-making level...
Forecasting renewable production is a key activity in power systems. With the growing penetration of renewable energy sources, there is a pressing need for best manage supply/demand balance, therefore a reliable forecasting method of intermittent energy resources is an important issue. In this field, among renewable sources, the wind power one is characterized by the higher criticalities, due to the...
Electronic health records (EHRs) are providing increased access to healthcare data that can be made available for advanced data analysis. This can be used by the healthcare professionals to make a more informed decision providing improved quality of care. However, due to the inherent heterogeneous and imbalanced characteristics of medical data from EHRs, data analysis task faces a big challenge. In...
This paper presents an approach of data mining technique to predict electricity demand of a geographical region based on the meteorological conditions. The value prediction predictive data mining technique is implemented with the Artificial Neural Networks. The values of the factors such as temperature, humidity and public holiday on which electricity consumption depends and the daily consumption...
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