This paper is focused on the development of intelligent classifiers in the area of biomedicine, focusing on the problem of diagnosing cardiac diseases based on the electrocardiogram (ECG), or more precisely, on the di...
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ISBN:
(纸本)9781479915194
This paper is focused on the development of intelligent classifiers in the area of biomedicine, focusing on the problem of diagnosing cardiac diseases based on the electrocardiogram (ECG), or more precisely, on the differentiation of several arrhythmia using a large data set, by an autonomous intelligent system which can be used as an expert system to support human experts in the diagnosis and, moreover, to autonomously display an alarm to the user in case of a dangerous situation. We will study and imitate the ECG treatment methodologies and the features extracted from the electrocardiograms used by the researchers, which obtained the best results in the PhysioNet Challenge. We will extract a great amount of features, partly those used by these researchers and some additional others we considered to be important for the distinction previously mentioned. A new method based on different paradigms of intelligent computation (such as extreme learning machine, support vector machine and feature selection) will be used to select the most relevant characteristics and to obtain a classifier capable of autonomously distinguishing the different types arrhythmia from the ECG signal. Finally, the behavior and performance of the classifier have been tested using data from several cardiac pathologies, obtaining good classification results.
The electrocardiogram (ECG) is a noninvasive technique used to reflect underlying heart conditions by measuring the electrical activity of the heart, and nowadays it is possible with just a few derivation (with just o...
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The electrocardiogram (ECG) is a noninvasive technique used to reflect underlying heart conditions by measuring the electrical activity of the heart, and nowadays it is possible with just a few derivation (with just only two), obtain important information in order than an expert can recognize abnormal heart rhythms (the heart rate is very fast, very slow, or irregular) or a heart attack (myocardial infarction), and if it was recent or some time ago. In this paper, several intelligent classifiers are developed, focusing on the problem of diagnosing cardiac diseases based on the electrocardiogram (ECG), or more precisely, on the differentiation of several arrhythmia using a large data set. We will study and imitate the ECG treatment methodologies and the features extracted from the electrocardiograms used by the researchers, which obtained the best results in the PhysioNet Challenge (***/). We will extract a great amount of features, partly those used by these researchers and some additional others we considered to be important for the distinction previously mentioned. A new method based on different paradigms of intelligent computation (such as extreme learning machine, support vector machine, decision trees, genetic algorithms and feature selection) will be used to select the most relevant characteristics and to obtain a classifier capable of autonomously distinguishing the different types arrhythmia from the ECG signal.
Effective design of shared mediated spaces, information and connectedness requires theory and practice from a range of disciplines such as found in European projects like Together Anywhere, Together Anytime (TA2) and ...
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Mastermind is a puzzle in which a hidden code of length ? and made with k colors has to be discovered via making guesses of the code and receiving hints that express the distance from the guess to the code, in terms o...
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ISBN:
(纸本)9781467359009
Mastermind is a puzzle in which a hidden code of length ? and made with k colors has to be discovered via making guesses of the code and receiving hints that express the distance from the guess to the code, in terms of number of symbols in the right position and with the right color. Solutions to these problem are mainly heuristic and thus finding the correct parameters for these solutions has to be done via systematic experimentation. Since diversity in the population is one of the main factors affecting performance, in this paper we will experiment with selective pressure via two different parameters: population size and size of tournament in tournament *** will study the influence of them in three different measures: algorithm performance (measured in average number of guesses needed), number of evaluations and time needed to find the solution. We will prove that while, in general, increasing population size improves performance, there is an optimal size over which no further improvement is achieved. On the other hand, tournament size does not have a clear influence on performance, although it influences time needed to find the *** will also show that the number of evaluations is correlated positively with time, and it increases with population size so that a trade-off has to be found among solution quality and population size. After evaluating the result of the experiments, we will try to advance a rule of thumb for sizing population for the general MasterMind problem.
This paper compares the use of RGB and HSV histograms during the execution of an Evolutionary Algorithm. This algorithm generates abstract images that try to match the histograms of a target image. Three different fit...
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ISBN:
(纸本)9789898565778
This paper compares the use of RGB and HSV histograms during the execution of an Evolutionary Algorithm. This algorithm generates abstract images that try to match the histograms of a target image. Three different fitness functions have been used to compare: the differences between the individual with the RGB histogram of the test image, the HSV histogram, and an average of the two histograms at the same time. Results show that the HSV fitness also increases the similarities of the RGB (and therefore, the average) more than the other two measures.
We investigate on-line on-board evolution of robot controllers based on the so-called hybrid approach (island-based). Inherently to this approach each robot hosts a population (island) of evolving controllers and exch...
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Automatic Repeat Request (ARQ) protocols are a very important functionality in computer networks, which steer information transmission between network devices. Its knowledge is essential for students in computer Scien...
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