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MODIFIED TRAINING METHOD FOR FEEDFORWARD NEURAL NETWORKS AND ITS APPLICATION in 4-LINK SCARA ROBOT IDENTIFICATION
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In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach has been performed very successfully, with better results obtained with the FFNN with modified wavelet activation function (FFMW) when compared with classic FFNN with Sigmoid activation function (FFS) .One can notice from the simulation that the FFMW can be capable of identifying the 4-Links of SCARA robot more efficiently than the classic FFS

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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Identification of Acinetobacter baumannii and Determination of MDR and XDR Strains
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The current study focuses on the bacterium Acinetobacter baumannii due to its importance as a nosocomial infections source in addition to its increased resistance against antibiotics. Different clinical and hospital environment samples were collected, and cultured on A. baumannii selective media: Leed Acinetobacter agar and Herellea agar. A. baumannii have been identified by traditional methods, followed by confirmation using molecular identification to detect blaoxa-51 like gene which is considered a diagnostic gene since it is present in genome of all A. baumannii strains. The result was, nineteen bacterial isolates of A.baumannii were obtained, from twenty-seven suspected isolate

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Publication Date
Sun Dec 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
The role of training human resources in the elements of administrative innovation
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The current research aims to identify the nature of the relationship between training human resources in administrative innovation elements In the General Directorate for the education of the third Rusafa one of the formations of the Iraqi Ministry of Education in Baghdad, In order to achieve the objectives of the research, the researcher provided a comprehensive theoretical framework and the preparation and development of a questionnaire as a tool for collecting data based on the prepared measurements and benefit from previous studies, which contains (28) For the purpose of obtaining realistic results for the variables of the research, the researcher used the random sample in the selection of the research sample A total of (63)

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Publication Date
Thu Feb 24 2022
Journal Name
Journal Of Educational And Psychological Researches
The Training Needs of Middle StagLeaders in Bisha, Saudi Arabi Teachers’ Perceptions
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The present study is meant to inquire about the training needs of middle stage leaders in Bisha, (Saudi Arabia) from the perspective of teachers. To achieve this purpose, the researcher has designed a questionnaire containing (31) items, distributed to a sample of (157) teacher (male and female) from the target population.

This research has demonstrated that the level of training needs for middle stage leaders was moderately reported with an arithmetic mean equivalent to (2.42), and a standard deviation of (0.36). Results have shown no significant differences at (α=0.05) in the sample’s expectations of the study’s variables.

The study concludes with a list of recommendations such as working on developing training pro

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Publication Date
Fri Jun 05 2026
Journal Name
Journal Of Physical Education
A Study of Actual Training Time Administration in Bedra Specialized Weightlifting Club
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Publication Date
Mon Oct 31 2022
Journal Name
International Journal Of Intelligent Engineering And Systems
Robot Path Planning in Unknown Environments with Multi-Objectives Using an Improved COOT Optimization Algorithm
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Publication Date
Wed Sep 01 2021
Journal Name
Egyptian Journal Of Petroleum
Identification of the best correlations of permeability anisotropy for Mishrif reservoir in West Qurna/1 oil Field, Southern Iraq
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Publication Date
Thu Aug 01 2024
Journal Name
Indonesian Journal Of Chemistry
Cloud Point Extraction Method for Spectrophotometric Determination of 3-Aminophenol in Environmental Samples
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This work describes the development of new spectrophotometric techniques for 3-aminophenol assessment. The first technique involves using benzidine in an alkaline solution to convert 3-aminophenol into a colored complex. The produced complex has a red color with an absorbance of 462 nm. Between the concentration range 5–14 μg mL−1, Beer's law is obeyed with a correlation coefficient (R2) of 0.99781, a limit of detection (LOD) of 0.0423 μg mL−1, and a limit of quantification (LOQ) of 0.1411 μg mL−1. The recovery was between 87.2–95.43%, the relative standard deviation (%RSD) was 2.40–3.31% and the molar absorptivity was 3.545 × 103 L mol−1 cm−1. Secondly, cloud point extraction (CPE) was used to determ

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Publication Date
Wed Sep 01 2021
Journal Name
Journal Of Engineering
Spike neural network as a controller in SDN network
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The paper proposes a methodology for predicting packet flow at the data plane in smart SDN based on the intelligent controller of spike neural networks(SNN). This methodology is applied to predict the subsequent step of the packet flow, consequently reducing the overcrowding that might happen. The centralized controller acts as a reactive controller for managing the clustering head process in the Software Defined Network data layer in the proposed model. The simulation results show the capability of Spike Neural Network controller in SDN control layer to improve the (QoS) in the whole network in terms of minimizing the packet loss ratio and increased the buffer utilization ratio.

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Publication Date
Fri Jun 01 2007
Journal Name
Al-khwarizmi Engineering Journal
Reduction of the error in the hardware neural network
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Specialized hardware implementations of Artificial Neural Networks (ANNs) can offer faster execution than general-purpose microprocessors by taking advantage of reusable modules, parallel processes and specialized computational components. Modern high-density Field Programmable Gate Arrays (FPGAs) offer the required flexibility and fast design-to-implementation time with the possibility of exploiting highly parallel computations like those required by ANNs in hardware. The bounded width of the data in FPGA ANNs will add an additional error to the result of the output. This paper derives the equations of the additional error value that generate from bounded width of the data and proposed a method to reduce the effect of the error to give

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Publication Date
Fri Aug 27 2021
Journal Name
Human Interaction, Emerging Technologies And Future Systems V: Proceedings Of The 5th International Virtual Conference On Human Interaction And Emerging Technologies, Ihiet 2021, August 27-29, 2021 And The 6th Ihiet: Future Systems (ihiet-fs 2021), October 28-30, 2021, France
Electricity Consumption Forecasting in Iraq with Artificial Neural Network
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