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Performance parameters are pretty important as well as clustering and routing algorithm in order for conditioning network lifetime in Wireless Sensor Network (WSN). The parameters like number of nodes, network area and radius of node coverage affects network lifetime directly. In this study the radius of node coverage's effect on network lifetime was checked out on various number of nodes. In the...
In wireless sensor networks, besides the way and mode the nodes are communicating each other, the location of the base stations has an important effect on the energy efficiency and longevity of the network and as a result the increase of the number of packages. A new dynamic base station positioning algorithm, which incorporates the location as well as the energy of the cluster heads within the network,...
In this study, pattern recognition based brain computer interface is designed using EEG p300 component elicited by visual stimuli. A novel EEG database obtained from 19 subjects is constructed with EMOTIV EPOC+ amplifier and OPENVIBE software. Extreme Learning Machine, a type of single layer neural network, Λ-nearest neighbour, Bayesian network and Multi-Layer Perceptron classifiers are compared for...
Auscultation of the respiratory sounds is an inexpensive and effective method for diagnosing cardio-pulmonary disorders using lung sounds from chest and back. Nowadays, high system performances in the management of robust processes that require great attention were increased using the computer-aided analysis methods and the developments of the diagnosis system. Analysis of the respiratory sounds with...
Color, texture and shape are generally used features in order to recognise an object from an image. In this study centroid-contour distance method is used in order to classify fish species with two dorsal fins. Therefore, fish images with two dorsal fins were used from fish images database taken under specific conditions. Various image processing methods were applied on images in order to extract...
In this study, Second Order Difference Plot (SODP) features are used for ECG based human identification. SODP is a method that allows to determine the features with the statistical analysis of the situations obtained from distributions and the distribution of each of successive points on an unstable and linear signals. ECG records of 90 individuals in Physionet ECG-Id database are used in the study...
The aim of study is creating a new database which contains fish species and classifing this fish species. A new fish database was created by using the fish photos in seas of Turkey. The new feature set are obtained by marking the biometric points on fish to identify family and species of fishes. The features were obtained by using the three different biometric measurement techniques (Euclidean network...
In this study, in order to diagnose congestive heart failure (CHF) patients, second-order difference map (SDOP) features obtained from raw electrocardiogram (EEG) data is used. CHF and normal patients' electrocardiogram data, which are distributed freely via internet, is analyzed. By U-matrix presentation of Self-Organized Maps, distances between groups and clusters are examined. 1×16 sixed SODP features...
Pseudo-random number generators generate sequent of digits that cannot be expected before. Random number generators are used in lots of studies especially physical and statical implementations. In this paper; by using Multi-Layer Perceptron Neural Network, a traditional random number generator is strengthened. In the end of the study; both of random number generators are tested by some randomness...
In this study, in order to diagnose congestive heart failure patients (CHF), Poincare map obtained from raw ECG data is used. CHF and normal ECG data, which are distributed freely via internet, are analyzed. Poincare map is divided into equal rectangle cells and points in all of the cells are determined. These values are used for knn (k-nearest neighbour) classification. At the result of this study,...
In this work, the arrhythmias in the electrocardiograph (ECG) signals are analyzed by using multi-layer perceptron (MLP) network. For training MLP network back-propagation with adaptive learning rate method is used. Feature vectors obtained from consecutive sample values of each peak in different window sizes are normalized and used for training the networks. Performances of different classifiers...
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