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.
A particle swarm optimization algorithm and neural network like self-tuning PID controller for CSTR system is presented. The scheme of the discrete-time PID control structure is based on neural network and tuned the parameters of the PID controller by using a particle swarm optimization PSO technique as a simple and fast training algorithm. The proposed method has advantage that it is not necessary to use a combined structure of identification and decision because it used PSO. Simulation results show the effectiveness of the proposed adaptive PID neural control algorithm in terms of minimum tracking error and smoothness control signal obtained for non-linear dynamical CSTR system.
This paper reviews the studies on expansive soil with a main focus on failure mechanism, financial losses, mineralogy, determination of swelling parameters and others. Effect of hydrocarbon pollution on geotechnical properties of expansive soil was presented. The paper discussed the assessment of electrical response of contaminated swelling soils. Wide extend of expansive grounds around the world and the serious impact created on infrastructures requires to identify its influential aspects and the appropriate treatments. Also, it was found that petroleum product affect significantly on the basic properties of swelling soils such as gradation, consistency, compaction, swelling and othe
يحتل موضوع الاستهلاك اهمية كبيرة في الدراسات الاقتصادية في حالتي السلم والحرب وذلك لارتباط هذا الموضوع بالانسان والمجتمع ولكونه احد مؤشرات مستوى الرفاهية الاقتصادية والاجتماعية وتزداد اهمية ضبط حركة هذا المتغير السلوكي والكمي في زمن الحرب اكثر مما هو عليه في حالة السلم، في هذا البحث تم استخدام بيانات احصائية عن الانفاق الاستهلاكي الخاص ونصيب الفرد من الدخل القومي اضافة الى الرقم القياسي لاسعار المس
... Show MoreSewer sediment deposition is an important aspect as it relates to several operational and environmental problems. It concerns municipalities as it affects the sewer system and contributes to sewer failure which has a catastrophic effect if happened in trunks or interceptors. Sewer rehabilitation is a costly process and complex in terms of choosing the method of rehabilitation and individual sewers to be rehabilitated. For such a complex process, inspection techniques assist in the decision-making process; though, it may add to the total expenditure of the project as it requires special tools and trained personnel. For developing countries, Inspection could prohibit the rehabilitation proceeds. In this study, the researchers propos
... Show MoreThe turning process has various factors, which affecting machinability and should be investigated. These are surface roughness, tool life, power consumption, cutting temperature, machining force components, tool wear, and chip thickness ratio. These factors made the process nonlinear and complicated. This work aims to build neural network models to correlate the cutting parameters, namely cutting speed, depth of cut and feed rate, to the machining force and chip thickness ratio. The turning process was performed on high strength aluminum alloy 7075-T6. Three radial basis neural networks are constructed for cutting force, passive force, and feed force. In addition, a radial basis network is constructed to model the chip thickness ratio. T
... Show MoreThe study aims to predict Total Dissolved Solids (TDS) as a water quality indicator parameter at spatial and temporal distribution of the Tigris River, Iraq by using Artificial Neural Network (ANN) model. This study was conducted on this river between Mosul and Amarah in Iraq on five positions stretching along the river for the period from 2001to 2011. In the ANNs model calibration, a computer program of multiple linear regressions is used to obtain a set of coefficient for a linear model. The input parameters of the ANNs model were the discharge of the Tigris River, the year, the month and the distance of the sampling stations from upstream of the river. The sensitivity analysis indicated that the distance and discharge
... Show MoreIn this work, two graphene oxide (GO) samples were prepared using the Hummers method with graphite (g) and KMnO4 (g) ratios of 1:3 (GO3) and 1:6 (GO6). The effect of oxidation degree on the structural, electrical, and dielectric properties of the GO samples was investigated. The structures of the GO samples were studied using various techniques, including X-ray diffraction (XRD), Fourier transform infrared (FT-IR) spectroscopy, scanning electron microscopy (SEM), and energy-dispersive X-ray spectroscopy (EDXS). XRD analysis revealed an increase in the interlayer spacing and a decrease in the number of layers of the samples with increasing oxidant content. The two GO samples have giant permittivity values of ~105 in the low-frequency
... Show MoreNano-structural of vanadium pentoxide (V2O5) thin films were
deposited by chemical spray pyrolysis technique (CSPT). Nd and Ce
doped vanadium oxide films were prepared, adding Neodymium
chloride (NdCl3) and ceric sulfate (Ce(SO4)2) of 3% in separate
solution. These precursor solutions were used to deposit un-doped
V2O5 and doped with Nd and Ce films on the p-type Si (111) and
glass substrate at 250°C. The structural, optical and electrical
properties were investigated. The X-ray diffraction study revealed a
polycrystalline nature of the orthorhombic structure with the
preferred orientation of (010) with nano-grains. Atomic force
microscopy (AFM) was used to characterize the morphology of the
films. Un-do
In this paper, we used two monomers, 3,3',4,4'-benzophenone tetracarboxylic dianhydride (BTDA) and m,m'-diaminobenzophenone (m, m’-DABP), to produce polyamide acid and then converted it to polyimide (PI). The effects of phosphoric acid (H3PO4) molarity (1, 2, and 3 M) on the structural, thermal, mechanical, and electrical characteristics of the polyimides/polyaniline (PI/PANI) nanocomposites were studied. Two sharp reflection peaks were developed by the addition of PANI to PI. When 3 M H3PO4 is added, the crystalline sharp peak loses some of its intensity. The complex formation of PI/PANI-H3PO4 was confi
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