This paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is better than RS and RW in identification the forward dynamics and provides good results in the Direct Inverse Neuro- Controller (DINC).
A total number of 68 water samples was revealed 20 isolates being Staphylococcus aureus. Irrigation water isolates represented 25% of isolates while wastewater 75%. all isolates were identified by morphological, microscopial, biochemical tests and VITEK®2 Compact. Bacterial isolates were subjected to 16 antibiotics, all irrigation water and wastewater isolates were resistant to penicillin while they were fully sensitive to Ciprofloxcin. Irrigation water isolates showed relatively greater multi-drug resistance than wastewater, wherein irrigation water isolates showed 100% multi-drug resistance while wastewater isolates showed 73.3% multi-drug resistance, indicating the ability of S. aureus MDR to move from one site to another, which means t
... Show MoreThis work aimed to use conventional PCR to identify Salmonella spp. that were isolated from diarrheal children and healthy and diarrheic dogs based on four virulence genes, hilA, stn, spvR, and marT. Sixteen Salmonella isolates including: 9 isolated from children's diarrhea from three species (S. Typhimurium, S. Enteritidis, S. Typhi) and seven isolated from dogs including (S. Typhimurium, S. Enteritidis, S. Muenchen), were identified primarily by several methods. The PCR products of the 16S rRNA gene were sequenced and examined using BLAST analysis to find differences and similarities between these Iraqi isolates and already-known global strains in order to construct the phylogenetic tree of S.
... Show MoreThe duration of sunshine is one of the important indicators and one of the variables for measuring the amount of solar radiation collected in a particular area. Duration of solar brightness has been used to study atmospheric energy balance, sustainable development, ecosystem evolution and climate change. Predicting the average values of sunshine duration (SD) for Duhok city, Iraq on a daily basis using the approach of artificial neural network (ANN) is the focus of this paper. Many different ANN models with different input variables were used in the prediction processes. The daily average of the month, average temperature, maximum temperature, minimum temperature, relative humidity, wind direction, cloud level and atmosp
... Show MoreThis paper is interested in certain subclasses of univalent and bi-univalent functions concerning to shell- like curves connected with k-Fibonacci numbers involving modified Sigmoid activation function θ(t)=2/(1+e^(-t) ) ,t ≥0 in unit disk |z|<1 . For estimating of the initial coefficients |c_2 | , |c_3 |, Fekete-Szego ̈ inequality and the second Hankel determinant have been investigated for the functions in our classes.
Hydrated lime has been recognized as an effective additive used to improve asphalt concrete properties in pavement applications. However, further work is still needed to quantify the effect of hydrated lime on asphaltic concrete performance under varied weather, temperature, and environmental conditions and in the application of different pavement courses. A research project was conducted using hydrated lime to modify the asphalt concretes used for the applications of wearing (surface), leveling (binder), and base courses. A previous publication reported the experimental study on the resistance to Marshall stability and the volumetric properties, the resilient modulus, and permanent deformation at three different weather temperatures. This
... Show MoreThe present paper aims at evaluating the vailability quality and future horizons of potable water in the city of Shatra as a model. This is done in accordance with certain subjective and objective factors alongside the classification map of Shatra as a residential area. This system follows geographical studies specialized in urban construction. The problem of the present paper as well as the data approaching that problem have been chosen from the records of 2018. The researcher offered (919) questionnaire forms to be answered by a sample of dwellers in that area. Besides, the researcher also followed lab analysis of water samples collected from districts in the city of Shatra. GIS technology was also used to arrive at the real water shar
... Show MoreOne of the recent significant but challenging research studies in computational biology and bioinformatics is to unveil protein complexes from protein-protein interaction networks (PPINs). However, the development of a reliable algorithm to detect more complexes with high quality is still ongoing in many studies. The main contribution of this paper is to improve the effectiveness of the well-known modularity density ( ) model when used as a single objective optimization function in the framework of the canonical evolutionary algorithm (EA). To this end, the design of the EA is modified with a gene ontology-based mutation operator, where the aim is to make a positive collaboration between the modularity density model and the proposed
... Show MoreSensibly highlighting the hidden structures of many real-world networks has attracted growing interest and triggered a vast array of techniques on what is called nowadays community detection (CD) problem. Non-deterministic metaheuristics are proved to competitively transcending the limits of the counterpart deterministic heuristics in solving community detection problem. Despite the increasing interest, most of the existing metaheuristic based community detection (MCD) algorithms reflect one traditional language. Generally, they tend to explicitly project some features of real communities into different definitions of single or multi-objective optimization functions. The design of other operators, however, remains canonical lacking any inte
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