Abstract—A new method is used in this work to classify ECG beats. The new method is about using an optimization algorithm for selecting the features of each beat then classify them. For each beat, twenty-four higher order statistical features and three timing interval features are obtained. Five types of beat classes are used for classification in this work, atrial premature contractions (APC), normal (NOR), premature ventricular contractions (PVC), left bundle branch (LBBB) and right bundle branch (RBBB). Cuttlefish algorithm is used for feature selection which is a new bio-inspired optimization algorithm. Four classifiers are used within CFA, Scaled Conjugate Gradient Artificial Neural Network (SCG-ANN), K-Nearest Neighborhood (KNN), Interactive Dichotomizer 3 (ID3) and Support Vector Machine (SVM). The final results show an accuracy of 97.96% for ANN, 95.71% for KNN, 94.69% for ID3 and 93.06% for SVM, these results were tested on fourteen signal records from MIT-HIH database, where 1400 beats were extracted from these records.

This study is based on classifying the ECG signal into five types of classes by using statistical and timing intervals features. First, the data signals were denoised and prepared for classification. Second, 24 higher order statistical features with 3 timing interval features were extracted from each selected beat. In this work, we have 5 types of classes, atrial premature contractions (APC), normal (NOR), premature ventricular contractions (PVC), left bundle branch block (LBBB) and right bundle branch block (RBBB) were used for classification. Third, each beat was classified according to one of these classes by using the learner algorithm scaled conjugate gradient (SCG) artificial neural network (ANN). SCG is a fast algorithm and suitable in cases of less memory and ANN is a machine learning algorithm that is based on the biological neural system. The experimental results of this work show an accuracy of 96% in 1400.

Electrocardiography passes on information regarding the electrical function of the heart, by changing the state of its constituent waves, namely the P, QRS, and T-waves which represent one cardiac cycle. The amplitude and interval of P-QRS-T segment determine the function of the heart. Cardiac arrhythmia demonstrates a state of abnormal electrical activity in the heart which is a risk for humans. Currently, onsets of cerebrovascular disease of ischemic nature have electrocardiographic changes, in those patients who had no primary heart disease. We estimated the prevalence of electrocardiographic changes for being of noteworthy one. The aim of this study presents analyses cardiac disease in electrocardiogram (ECG) signals for cardiac arrhythmia which leads to ischemic heart - stroke utilizing investigation of resulting ECG normal and abnormal wave forms. In results 75 of Patient group about (58.67%) were males.

Electrocardiographic is for the finding and diagnostic of abnormal cardiac rhythms. It assists in the analysis of the reason for chest torment, and the best possible utilization of early medication in myocardial dead tissue relies on it. It can help with the conclusion of the reason for tipsiness, syncope, and breathlessness. Currently, there is a personal computer-based investigation which utilizes certain signal processing to analyze a patient in view of ECG recording. Noise dependably debases the nature of ECG signal, preprocessing of electrocardiograph is utilized for denoising electrocardiogram signal. Investigation of ECG signal gives data about the status of the heart. ECG signal is a biomedical signal that provides information about the electrical activities of the heart. Different noises of high frequencies and low frequencies are debased with ECG signal that may lead to wrong interpretations. To avoid this problem, we utilize different ECG signal denoising techniques. Applications of the denoising system is essential for the precise analysis of cardiovascular issues like Fast Fourier Transforms, Wavelet Transform, and so on and have been utilized for the location of cardiac diseases. In this paper, we have given an overview of Noising - Denoising of signal analysis of human electrocardiographs.

This study is about using the genetic algorithm (GA) with wavelet transform (WT) for Arrhythmia Electrocardiogram (ECG) signal denoising purposes. The WT is a time-frequency signal analysis, and the GA is an optimization technique based on survival of the best solution using the maximized or minimized fitness value obtained from the fitness function. In this study, the parameters of WT are used as inputs for the GA for denoising the input signal that is corrupted by white Gaussian noise and gives an output of as fitness value. The input corrupted signal will pass through decomposition process to extract approximation and details coefficients, then thresholding the details coefficients using a threshold value in order to remove the noise, and finally reconstruction of the signal using the approximation and denoised details coefficients. The results of denoising ECG Arrhythmia records were compared with other studies.

Craters occur when an objects like Asteroids, Comets and Meteorites hits onto the surfaces of Moon and Planets and their impact has became a major geological process. The objective of the project is to investigate how the size of a Meteorite and Asteroid on the Moon and Planets is related to the size of impact crater. We started with a two round stone of different mass and size covered slightly with a layer of a viscous mud fluid as a fragmentation were dropped at variable height onto the flour. However, we have used a layer of sprinkles as a mineral diversity of the surface impacted. We have measured the diameter, depth and the Ejecta distance of the crater each time, there were three trails for each stone drop height. The results shows that, the crater diameter and the crater depth increased as the height and mass of the ball drop increased in addition of increasing Ejecta distance.

The DyeSensitized Solar Cell (DSSC) plays an important role because of low material cost, ease of production and high conversion efficiency as compared to other thin-film solar cell technologies. The main objective is to create and find the best configuration of the solar cell based on materials that are inexpensive and highly efficient in solar energy conversion and subsequently test the efficiency of dye sensitized titanium dioxide solar cell. We begin the process with two glass plates coated with Fluorine tin oxide (FTO). Titanium dioxide is applied to the conductive side of one plate and the other plate is coated with graphite. Adye is adsorbed on to the TiOzlayer and then the plates are sandwiched together. Adrop ofiodide electrolyte is then added between the plates. The tests carried out indoors under a lamp emitting all wavelengths inthe visible spectrum were not found to provide consistent data due to substantial heating of the cell. The outdoor tests carried out in natural sunlight exhibited steady voltage at much higher level. Future research will involve the incorporation of quantum dots instead of the organic dye as a sensitizer. Quantum dots have the advantages ofproviding tunable band gaps and the ability to absorb specific wavelength.

The present work measured the bulk etch rate (VB ) of solid state nuclear track detector by taking the diameter time measurement of alpha particle in CR-39 detector. The values of the track diameter have been found by using TRACK-TEST program from Yu et al. function and Brun et al. function with different energies of alpha particles. The results showed that the time-diameter (t-d) method gave good results of the bulk etch rate (VB ) and these values were (1.705 and 1.72) μm·hr-1. They showed good agreement with the values measured by using the other methods, and it was a simple method because it required getting diameters of the tracks in the detector with the etching time.

In-doped (Se0.7Te0.3) thin films (In: 0, 0.05, and 0.08wt%) with thickness of (150 ± 25 nm) have been deposited on glass substrates by chemical vapor deposition by using selenium, tellurium and indium whose purity is (99.99%) compound alloy. The electrical and optical properties of the thin films were analyzed. The effects of In-doping concentration on the thermoelectric properties of the thin films were investigated by room-temperature measurement of the See beck coefficient and electrical resistivity. The thermoelectric power factor shows the best result at 0.05wt% in doping. The See beck coefficients are positive with increasing in doping concentration from 0 to 0.08wt%. And the thin films show p-type conduction. For optical properties, the transmission of all samples was approximated to 90%.

The aim of this paper is to determine the maximum values of the track length (Lmax) of alpha particles in Nuclear Track Detector (type CR-39) using a new method by taking the relation between the etching time and the diameter square of alpha particle with different energies at constant bulk etch rate VB (1.45 μm/hr) by using TRACK_TEST program from Brun et al. function and Yu et al. function. Using the new equation, the maximum values of the track lengths of alpha particles measured in CR-39 detector have been found to be in a good agreement with the values measured by using Brun et al. function and Yu et al. function in TRACK_TEST program.