Research on the automated extraction of essential data from an electrocardiography (ECG) recording has been a significant topic for a long time. The main focus of digital processing processes is to measure fiducial points that determine the beginning and end of the P, QRS, and T waves based on their waveform properties. The presence of unavoidable noise during ECG data collection and inherent physiological differences among individuals make it challenging to accurately identify these reference points, resulting in suboptimal performance. This is done through several primary stages that rely on the idea of preliminary processing of the ECG electrical signal through a set of steps (preparing raw data and converting them into files that are read and then processed by removing empty data and unifying the width of the signal at a length of 250 in order to remove noise accurately, and then performing the process of identifying the QRS in the first place and P-T implicitly, and then the task stage is determining the required peak and making a cut based on it. The U-Net pre-trained model is used for deep learning. It takes an ECG signal with a customisable sampling rate as input and generates a list of the beginning and ending points of P and T waves, as well as QRS complexes, as output. The distinguishing features of our segmentation method are its high speed, minimal parameter requirements, and strong generalization capabilities, which are used to create data that can be used in diagnosing diseases or biometric systems.
Visible light communication (VLC) is an upcoming wireless technology for next-generation communication for high-speed data transmission. It has the potential for capacity enhancement due to its characteristic large bandwidth. Concerning signal processing and suitable transceiver design for the VLC application, an amplification-based optical transceiver is proposed in this article. The transmitter consists of a driver and laser diode as the light source, while the receiver contains a photodiode and signal amplifying circuit. The design model is proposed for its simplicity in replacing the trans-impedance and transconductance circuits of the conventional modules by a simple amplification circuit and interface converter. Th
... Show MoreDiagnosing heart disease has become a very important topic for researchers specializing in artificial intelligence, because intelligence is involved in most diseases, especially after the Corona pandemic, which forced the world to turn to intelligence. Therefore, the basic idea in this research was to shed light on the diagnosis of heart diseases by relying on deep learning of a pre-trained model (Efficient b3) under the premise of using the electrical signals of the electrocardiogram and resample the signal in order to introduce it to the neural network with only trimming processing operations because it is an electrical signal whose parameters cannot be changed. The data set (China Physiological Signal Challenge -cspsc2018) was ad
... Show MoreIn this article, the influence of group nano transition metal oxides such as {(MnO2), (Fe2O3) and (CuO)} thin films on the (ZnO-TiO2) electric characteristics have been analyzed. The prepared films deposited on glass substrate laser Nd-YAG with wavelength (ℷ =1064 nm) ,energy of (800mJ) and number of shots (400). The density of the film was found to be (200 nm) at room temperature (RT) and annealing temperature (573K).Using DC Conductivity and Hall Effect, we obtained the electrical properties of the films. The DC Conductivity shows that that the activation energies decrease while the σRT at annealing temperature with different elements increases the formation of mixed oxides. The Hall effect, the elec
... Show MoreCdS films were prepared by thermal evaporation technique at thickness 1 µm on glass substrates and these films were doped with indium (3%) by thermal diffusion method. The electrical properties of these have been investigated in the range of diffusion temperature (473-623 K)> Activation energy is increased with diffusion temperature unless at 623 K activation energy had been decreased. Hall effect results have shown that all the films n-type except at 573 and 623 K and with increase diffusion temperature both of concentration and mobility carriers were increased.
Ad-Hoc Networks are a generation of networks that are truly wireless, and can be easily constructed without any operator. There are protocols for management of these networks, in which the effectiveness and the important elements in these networks are the Quality of Service (QoS). In this work the evaluation of QoS performance of MANETs is done by comparing the results of using AODV, DSR, OLSR and TORA routing protocols using the Op-Net Modeler, then conduct an extensive set of performance experiments for these protocols with a wide variety of settings. The results show that the best protocol depends on QoS using two types of applications (+ve and –ve QoS in the FIS evaluation). QoS of the protocol varies from one prot
... Show Moreتعد الموازنة الأداة الأساسية لتنفيذ أولويات أية دولة، ويتوجب النظر إليها في ضوء المناخ الاجتماعي والسياسي والاقتصادي، لأنها تساعد في توجيه الاقتصاد لتحقيق النمو ورفع مستوى الرفاهية. اعتمدت وزارة المالية في أعداد الموازنة السنوية بعد 9/4/ 2003 أسلوباً مغايراً لما كان معتمداً في العقود الماضية، إذ كانت هناك موازنتين الأولى الموازنة الجارية، والثانية الموازنة الاستثمارية رغم وجود قانون يحتم إصدار موازنة
... Show MoreIn this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respectively. For
... Show MoreIn this paper we present a method to analyze five types with fifteen wavelet families for eighteen different EMG signals. A comparison study is also given to show performance of various families after modifying the results with back propagation Neural Network. This is actually will help the researchers with the first step of EMG analysis. Huge sets of results (more than 100 sets) are proposed and then classified to be discussed and reach the final.