Preferred Language
Articles
/
alkej-16
Neuro-Self Tuning Adaptive Controller for Non-Linear Dynamical Systems
...Show More Authors

In this paper, a self-tuning adaptive neural controller strategy for unknown nonlinear system is presented. The system considered is described by an unknown NARMA-L2 model and a feedforward neural network is used to learn the model with two stages. The first stage is learned off-line with two configuration serial-parallel model & parallel model to ensure that model output is equal to actual output of the system & to find the jacobain of the system. Which appears to be of critical importance parameter as it is used for the feedback controller and the second stage is learned on-line to modify the weights of the model in order to control the variable parameters that will occur to the system. A back propagation neural network is applied to learn the control structure for self-tuning PID type neuro-controller. Where the neural network is used to minimize the error function by adjusting the PID gains. Simulation results show that the self-tuning PID scheme can deal with a large unknown nonlinearity

View Publication Preview PDF
Quick Preview PDF
Publication Date
Sat Apr 01 2023
Journal Name
Journal Of Engineering
Influence of Design Efficiency of Water Supply Network Inside Building on its Optimum Usage: Review
...Show More Authors

The water supply network inside the building is of high importance due to direct contact with the user that must be optimally designed to meet the water needs of users.  This work aims to review previous research and scientific theories that deal with the design of water networks inside buildings, from calculating the amount of consumption and the optimal distribution of the network, as well as ways to rationalize the use of water by the consumer.  The process of pumping domestic water starts from water treatment plants to be fed to the public distribution networks, then reaching a distribution network inside the building till it is  provided to the user.  The design of the water supply network inside the building is

... Show More
View Publication Preview PDF
Crossref
Publication Date
Thu Jun 20 2019
Journal Name
Baghdad Science Journal
Using Backpropagation to Predict Drought Factor in Keetch-Byram Drought Index
...Show More Authors

Forest fires continue to rise during the dry season and they are difficult to stop. In this case, high temperatures in the dry season can cause an increase in drought index that could potentially burn the forest every time. Thus, the government should conduct surveillance throughout the dry season. Continuous surveillance without the focus on a particular time becomes ineffective and inefficient because of preventive measures carried out without the knowledge of potential fire risk. Based on the Keetch-Byram Drought Index (KBDI), formulation of Drought Factor is used just for calculating the drought today based on current weather conditions, and yesterday's drought index. However, to find out the factors of drought a day after, the data

... Show More
View Publication Preview PDF
Clarivate Crossref
Publication Date
Sun Feb 28 2021
Journal Name
Journal Of Economics And Administrative Sciences
Identifying the leading sector in the Iraqi economy through the interrelationships between sectors - applied research
...Show More Authors

 

   Analyzing the size of the interrelationships between the main economic sectors in the Iraqi economy is an important necessity to know the impact of each sector on other economic sectors on the basis of the interrelationships and reciprocity between them, and what these relationships have achieved in terms of enhancing development and increasing the gross domestic product. To achieve the objectives of the study, we relied on mathematical (quantitative) analysis using user-product tables. Issued by the Ministry of Planning / Central Bureau of Statistics and Research (Directorate of National Accounts) for the economic sectors that make up the Iraqi economy. The study conc

... Show More
View Publication Preview PDF
Crossref
Publication Date
Wed Dec 30 2009
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of the Point Efficiency of Sieve Tray Using Artificial Neural Network
...Show More Authors

An application of neural network technique was introduced in modeling the point efficiency of sieve tray, based on a
data bank of around 33l data points collected from the open literature.Two models proposed,using back-propagation
algorithm, the first model network consists: volumetric liquid flow rate (QL), F foctor for gas (FS), liquid density (pL),
gas density (pg), liquid viscosity (pL), gas viscosity (pg), hole diameter (dH), weir height (hw), pressure (P) and surface
tension between liquid phase and gas phase (o). In the second network, there are six parameters as dimensionless
group: Flowfactor (F), Reynolds number for liquid (ReL), Reynolds number for gas through hole (Reg), ratio of weir
height to hole diqmeter

... Show More
View Publication Preview PDF
Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
Improving IoT Applications Using a Proposed Routing Protocol
...Show More Authors

The main objective of this work is to propose a new routing protocol for wireless sensor network employed to serve IoT systems. The routing protocol has to adapt with different requirements in order to enhance the performance of IoT applications. The link quality, node depth and energy are used as metrics to make routing decisions. Comparison with other protocols is essential to show the improvements achieved by this work, thus protocols designed to serve the same purpose such as AODV, REL and LABILE are chosen to compare the proposed routing protocol with. To add integrative and holistic, some of important features are added and tested such as actuating and mobility. These features are greatly required by some of IoT applications and im

... Show More
View Publication Preview PDF
Crossref (1)
Crossref
Publication Date
Thu Aug 01 2019
Journal Name
International Journal Of Machine Learning And Computing
Emotion Recognition System Based on Hybrid Techniques
...Show More Authors

Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In

... Show More
View Publication Preview PDF
Scopus (20)
Crossref (19)
Scopus Crossref
Publication Date
Fri Sep 30 2022
Journal Name
Nasaq Journal
The Demonic Image of Autoimmunity in Dan Brown's Angels and Demons
...Show More Authors

Autoimmunity is a philosophical term that enhances the fields of life-sciences, and links out to the unnatural behaviour of an individual. It is caused by the defenses of an organism that deceive its own tissues. Obviously, the immune system should protect the body against invading cells with types of white blood cells called antibodies. Nevertheless, when an autoimmune disease attacks, it causes perilous actions like suicide. Psychologically, Jacques Derrida (1930-2004) calls autoimmunity a double suicide, because it harms the self and the other. In this case, the organ disarms betraying cells, as the immune system cannot provide protection. From a literary perspective, Derrida has called autoimmunity as deconstruction for over forty years

... Show More
View Publication Preview PDF
Publication Date
Thu Jan 31 2019
Journal Name
Journal Of Engineering
Mechanical Properties Enhancement of Conventional Glass Ionomer Cement by Adding Zirconium Oxide Micro and Nanoparticles
...Show More Authors

The aim of this work is to enhance the mechanical properties of the glass ionomer cement GIC (dental materials) by adding Zirconium Oxide ZrO2 in both micro and nano particles. GIC were mixed with (3, 5 and 7) wt% of both ZrO2 micro and nanoparticles separately. Compressive strength (CS), biaxial flexural strength (BFS), Vickers Microhardness (VH) and wear rate losses (WR) were investigated. The maximum compression strength was 122.31 MPa with 5 wt. % ZrO2 micro particle, while 3wt% nanoparticles give highest Microhardness and biaxial flexural strength of 88.8 VHN and 35.79 MPa respectively. The minimum wear rate losses were 3.776µg/m with 7 wt. % ZrO2 nanoparticle. GIC-contai

... Show More
View Publication Preview PDF
Crossref (13)
Crossref
Publication Date
Tue Dec 26 2017
Journal Name
Al-khwarizmi Engineering Journal
Optimization of Wear Parameters in AISI 4340 Steel
...Show More Authors

Abstract

 This study investigated the optimization of wear behavior of AISI 4340 steel based on the Taguchi method under various testing conditions. In this paper, a neural network and the Taguchi design method have been implemented for minimizing the wear rate in 4340 steel. A back-propagation neural network (BPNN) was developed to predict the wear rate. In the development of a predictive model, wear parameters like sliding speed, applying load and sliding distance were considered as the input model variables of the AISI 4340 steel. An analysis of variance (ANOVA) was used to determine the significant parameter affecting the wear rate. Finally, the Taguchi approach was applied to determine

... Show More
View Publication Preview PDF
Publication Date
Wed May 22 2024
Journal Name
Scientific Reports
The use of image analysis to study the effect of moisture content on the physical properties of grains
...Show More Authors
Abstract<p>Designing machines and equipment for post-harvest operations of agricultural products requires information about their physical properties. The aim of the work was to evaluate the possibility of introducing a new approach to predict the moisture content in bean and corn seeds based on measuring their dimensions using image analysis using artificial neural networks (ANN). Experimental tests were carried out at three levels of wet basis moisture content of seeds: 9, 13 and 17%. The analysis of the results showed a direct relationship between the wet basis moisture content and the main dimensions of the seeds. Based on the statistical analysis of the seed material, it was shown that the characteristics </p> ... Show More
View Publication
Scopus (6)
Crossref (6)
Scopus Clarivate Crossref