In this paper, we focus on designing feed forward neural network (FFNN) for solving Mixed Volterra – Fredholm Integral Equations (MVFIEs) of second kind in 2–dimensions. in our method, we present a multi – layers model consisting of a hidden layer which has five hidden units (neurons) and one linear output unit. Transfer function (Log – sigmoid) and training algorithm (Levenberg – Marquardt) are used as a sigmoid activation of each unit. A comparison between the results of numerical experiment and the analytic solution of some examples has been carried out in order to justify the efficiency and the accuracy of our method.

Solar energy is one of the immeasurable renewable energy in power generation for a green, clean and healthier environment. The silicon-layer solar panels absorb sun energy and converts it into electricity by off-grid inverter. Electricity is transferred either from this inverter or from transformer, consumed by consumption unit(s) available for residential or economic purposes. The artificial neural network is the foundation of artificial intelligence and solves many complex problems which are difficult by statistical methods or by humans. In view of this, the purpose of this work is to assess the performance of the Solar - Transformer - Consumption (STC) system. The system may be in complete breakdown situation due to failure of both so

A Genetic Algorithm optimization model is used in this study to find the optimum flow values of the Tigris river branches near Ammara city, which their water is to be used for central marshes restoration after mixing in Maissan River. These tributaries are Al-Areed, AlBittera and Al-Majar Al-Kabeer Rivers. The aim of this model is to enhance the water quality in Maissan River, hence provide acceptable water quality for marsh restoration. The model is applied for different water quality change scenarios ,i.e. , 10%,20% increase in EC,TDS and BOD. The model output are the optimum flow values for the three rivers while, the input data are monthly flows(1994-2011),monthly water requirements and water quality parameters (EC, TDS, BOD, DO and

Wind turbine (WT) is now a major renewable energy resource used in the modern world. One of the most significant technologies that use the wind speed (WS) to generate electric power is the horizontal-axis wind turbine. In order to enhance the output power over the rated WS, the blade pitch angle (BPA) is controlled and adjusted in WT. This paper proposes and compares three different controllers of BPA for a 500-kw WT. A PID controller (PIDC), a fuzzy logic controller (FLC) based on Mamdani and Sugeno fuzzy inference systems (FIS), and a hybrid fuzzy-PID controller (HFPIDC) have been applied and compared. Furthermore, Genetic Algorithm (GA) and Particle swarm optimization (PSO) have been applied and compared in order to identify the optimal

A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m

Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD

Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

Abstract

This work is considered the first study for the components of the Iraqi Leucaena leucocephala plant, where the different phytochemical compounds that present in the aerial parts were identified by using the gas chromatography/mass spectrometry technique (GC/MS). The type of the components and their concentration will differ according to the part of the plant used and the method of extraction (hot and cold). This study made a comparison in lupeol concentration that was identified and isolated from petroleum ether fractions of Leucaena leucocephala by using Gas Chromatography/Mass Spectrometry (GC/MS), High-performance thin-layer chromatography (HPTLC), and Preparative High-Performance Li

This paper presents thermal characteristics analysis of a modified Closed Wet Cooling Tower (CWCT) based on heat and mass transfer principles to improve the performance of this tower in Iraq. A prototype of CWCT optimized by added packing was designed, manufactured and tested for cooling capacity of 9 kW. Experiments are conducted to explore the effects of various operational and conformational parameters on the thermal performance. In the test section, spray water temperature and both dry bulb temperature and relative humidity of the air measured at intermediate points of the heat exchanger and packing. Heat exchangers consist of four rows and eight columns for an inline tubes arrangement and six rows and five columns f

Diesel generators is widely used in Iraq for the purpose of maintaining electric power demand. Large number of operators engaged in this work encounters high level of noise generated by back pack type diesel generators used for this purpose. High level of noise exposure gives different kinds of ill effect on human operators. Exact nature of deteriorated work performance is not known., in present research , quastionaire was adsministered 86 repondents in Baghdad city were exposured to wide range of noise level (80-110) dB(A) with different ages and they have different skill discretion levels. Noise levels A-weigthed decibles dB(A) were measured over 8 weeks two times aday during the 2019 summer using a sound level meter.For predicting the wo