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Spiking Neural Network in Precision Agriculture
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In this paper, precision agriculture system is introduced based on Wireless Sensor Network (WSN). Soil moisture considered one of environment factors that effect on crop. The period of irrigation must be monitored. Neural network capable of learning the behavior of the agricultural soil in absence of mathematical model. This paper introduced modified type of neural network that is known as Spiking Neural Network (SNN). In this work, the precision agriculture system  is modeled, contains two SNNs which have been identified off-line based on logged data, one of these SNNs represents the monitor that located at sink where the period of irrigation is calculated and the other represents the soil. In addition, to reduce power consumption of sensor nodes Modified Chain-Cluster based Mixed (MCCM) routing algorithm is used. According to MCCM, the sensors will send their packets that are less than threshold moisture level to the sink. The SNN with Modified Spike-Prop (MSP) training algorithm is capable of identifying soil, irrigation periods and monitoring the soil moisture level, this means that SNN has the ability to be an identifier and monitor. By applying this system the particular agriculture area reaches to the desired moisture level.

 

 

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Publication Date
Sun Dec 07 2014
Journal Name
Baghdad Science Journal
Genotypic Study of Two Virulence Factors fimH and kpsMTII in Uropathogenic Escherichia coli Isolates from Children Patients with Urinary Tract Infections
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Adhesion (type 1 fimbriae) and host defense avoidance mechanisms (capsule or lipopolysaccharide) have been shown to be prevalent in Escherichia coli isolates associated with urinary tract infections. In this work, 50 uropathogenic Escherichia coli (UPEC) isolated from children with urinary tract infections were genotypically characterized by polymerase chain reaction (PCR) assay. We used two genes; fimH and kpsMTII, both of them previously identified in uropathogenic E.coli (UPEC) isolates. The PCR assay results identified fimH (90.0)% and kpsMTII (72.0)% isolates. In the present study, was also demonstrated that these genes may be included in both or one of them within a single isolate.

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Publication Date
Mon Nov 11 2019
Journal Name
Spe
Modeling Rate of Penetration using Artificial Intelligent System and Multiple Regression Analysis
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Abstract<p>Over the years, the prediction of penetration rate (ROP) has played a key rule for drilling engineers due it is effect on the optimization of various parameters that related to substantial cost saving. Many researchers have continually worked to optimize penetration rate. A major issue with most published studies is that there is no simple model currently available to guarantee the ROP prediction.</p><p>The main objective of this study is to further improve ROP prediction using two predictive methods, multiple regression analysis (MRA) and artificial neural networks (ANNs). A field case in SE Iraq was conducted to predict the ROP from a large number of parame</p> ... Show More
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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
FACE IDENTIFICATION USING BACK-PROPAGATION ADAPTIVE MULTIWAVENET
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Face Identification is an important research topic in the field of computer vision and pattern recognition and has become a very active research area in recent decades. Recently multiwavelet-based neural networks (multiwavenets) have been used for function approximation and recognition, but to our best knowledge it has not been used for face Identification. This paper presents a novel approach for the Identification of human faces using Back-Propagation Adaptive Multiwavenet. The proposed multiwavenet has a structure similar to a multilayer perceptron (MLP) neural network with three layers, but the activation function of hidden layer is replaced with multiscaling functions. In experiments performed on the ORL face database it achieved a

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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
Face Identification Using Back-Propagation Adaptive Multiwavenet
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Face Identification is an important research topic in the field of computer vision and pattern recognition and has become a very active research area in recent decades. Recently multiwavelet-based neural networks (multiwavenets) have been used for function approximation and recognition, but to our best knowledge it has not been used for face Identification. This paper presents a novel approach for the Identification of human faces using Back-Propagation Adaptive Multiwavenet. The proposed multiwavenet has a structure similar to a multilayer perceptron (MLP) neural network with three layers, but the activation function of hidden layer is replaced with multiscaling functions. In experiments performed on the ORL face database it achieved a

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Publication Date
Wed Mar 01 2017
Journal Name
International Communications In Heat And Mass Transfer
Optimization, modeling and accurate prediction of thermal conductivity and dynamic viscosity of stabilized ethylene glycol and water mixture Al 2 O 3 nanofluids by NSGA-II using ANN
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In this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and

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Publication Date
Fri Sep 27 2024
Journal Name
Journal Of Applied Mathematics And Computational Mechanics
Fruit classification by assessing slice hardness based on RGB imaging. Case study: apple slices
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Correct grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 %  1.66 %. This

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Publication Date
Tue Feb 14 2023
Journal Name
Journal Of Educational And Psychological Researches
The Role of Ethical Leadership in Achieving Comprehensive Quality Standards in Public Education Schools in Al-Ardha Governorate
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Abstract

The aim of the research is to identify the role of ethical leadership in achieving comprehensive quality standards in public education schools in the Al-Ardha governorate. To achieve this goal, the descriptive approach was used, the researcher developed a questionnaire consisting of (35) items, divided into two sections: the first one is related to ethical leadership includes (17) items, and the second section relates to total quality management includes (18) items. The research sample consisted of (405) teachers from the stages of public education. The results showed that the level of ethical leadership practice (ethical personal characteristics, ethical administrative features, teamwork, and human rela

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Publication Date
Mon Jul 03 2023
Journal Name
Iraqi Journal Of Biotechnology
In Vivo Cytogenetic Effects of Ephedra alata L. Stems Extracts in Mitosis of Meristematic Cells in Onion Roots
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Ephedra alata. is a plant that widely available around the world and long used in folk medicine as a natural medication, was employed in the current work to prepare extracts rich in alkaloids and to test their cytotoxic potential. Alkaloids-rich and crude extracts of E.alata were compared to pure ephedrine medication for mitosis on Allium cepa. test system. Alkaloids and crude aqueous extracts of A. cepa root tips were examined for a total of five hours at five different concentrations compared to ephedrine standard. Mitotic index, phase index, and chromosomal aberration as part of the study. IC50 values of 35 mg/ml were found for each extract, indicating a sub-lethal influence on cell viability. (Toxic and sublethal effects are thought to

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Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Some Organizational Factors Role in Limited Talent Management Strategies Field Research in Number of Talent Schools in Iraq)
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Abstract:

 The purpose of this research is measuring relationship level and impact between Organizational Factors and their Dimensions (Leadership, Organizational Structure, Organizational Culture), and Talent Management Strategies (Talent Recruitment,Talent performance management, Talent Development, Talent Retention ). it was relied on the Questionnaire form as a basic instrument in collecting the Data by using (Likert) instrument ,which was distributed on the research Sample which number was (100) individual included (Managers of schools, assistants  (scientific and Administration ) and teachers in Four schools of Talents in Iraq (Baghdad , AL-Nagaf , AL-Basra, Mesan). All fo

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Publication Date
Thu Nov 09 2023
Journal Name
Biomedicine
Role of immunological and biochemical markers in bone turnover in type I diabetic patients in Karbala province, Iraq
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Introduction & Aim: Long-term diabetes mellitus (DM) is known to have a deleterious impact on bone health, resulting in change in bone mineral density, bone turnover, and bone quality, all of which increase the risk of fractures. The aim of. this study was to link immunological and pro-inflammatory cytokine (I.L-6, I.L-1, and TNF-alpha) markers in patients.with type 1 diabetes to Their connection to bones formation (sPINP) and bone resorption parameters (sCTX).   Materials & Methods: This study included 80 patients suffering from T1DM in the age range of 20-45 years. The patients were assayed for their biochemical (Vitamin D and HbA1c), Immunological (IL-6, IL-1 and TNF-alpha) parameters, as well as bone formation and resor

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