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Smart Flow Steering Agent for End-to-End Delay Improvement in Software-Defined Networks
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Publication Date
Thu Oct 01 2015
Journal Name
Iraqi Journal Of Science
improvement and partial purification for pectinase production from pseudomonas aeuroginosa
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Publication Date
Wed Aug 01 2018
Mixed Linearity Improvement Techniques for Ultra-wideband Low Noise Amplifier
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<span>We present the linearization of an ultra-wideband low noise amplifier (UWB-LNA) operating from 2GHz to 11GHz through combining two linearization methods. The used linearization techniques are the combination of post-distortion cancellation and derivative-superposition linearization methods. The linearized UWB-LNA shows an improved linearity (IIP3) of +12dBm, a minimum noise figure (NF<sub>min.</sub>) of 3.6dB, input and output insertion losses (S<sub>11</sub> and S<sub>22</sub>)  below -9dB over the entire working bandwidth, midband gain of 6dB at 5.8GHz, and overall circuit power consumption of 24mW supplied from a 1.5V voltage source. Both UWB-LNA and linearized UWB-LNA designs are

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Publication Date
Sat Apr 01 2023
Journal Name
Journal Of Engineering
Improvement of Moisture Susceptibility for Asphalt Mixture with Ceramic Fiber
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Moisture damage is one of the most significant troubles that destroy asphaltic pavement and reduces road serviceability. Recently, academics have noticed a trend to utilize fibers to enhance the efficiency of asphalt pavement. This research explores the effect of low-cost ceramic fiber, which has high tensile strength and a very high thermal insulation coefficient, on the asphalt mixture's characteristics by adding three different proportions (0.75%, 1.5%, and 2.25%). The Marshall test and the Tensile Strength Ratio Test (TSR) were utilized to describe the impact of ceramic fiber on the characteristics of Marshall and the moisture susceptibility of the hot mix asphalt mixture. The Field Emission Scanning Electron Microsc

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Publication Date
Mon Nov 01 2021
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Proposed emerged and enhanced routing protocols for wireless networks
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The problem motivation of this work deals with how to control the network overhead and reduce the network latency that may cause many unwanted loops resulting from using standard routing. This work proposes three different wireless routing protocols which they are originally using some advantages for famous wireless ad-hoc routing protocols such as dynamic source routing (DSR), optimized link state routing (OLSR), destination sequenced distance vector (DSDV) and zone routing protocol (ZRP). The first proposed routing protocol is presented an enhanced destination sequenced distance vector (E-DSDV) routing protocol, while the second proposed routing protocol is designed based on using the advantages of DSDV and ZRP and we named it as

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Publication Date
Sat May 19 2012
Journal Name
Wireless Personal Communications
Stable-Aware Evolutionary Routing Protocol for Wireless Sensor Networks
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Publication Date
Sun Dec 02 2012
Journal Name
Baghdad Science Journal
Stability of Back Propagation Training Algorithm for Neural Networks
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In this paper, we derive and prove the stability bounds of the momentum coefficient µ and the learning rate ? of the back propagation updating rule in Artificial Neural Networks .The theoretical upper bound of learning rate ? is derived and its practical approximation is obtained

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Publication Date
Tue Jun 03 2025
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Comparison of some artificial neural networks for graduate students
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Artificial Neural Networks (ANN) is one of the important statistical methods that are widely used in a range of applications in various fields, which simulates the work of the human brain in terms of receiving a signal, processing data in a human cell and sending to the next cell. It is a system consisting of a number of modules (layers) linked together (input, hidden, output). A comparison was made between three types of neural networks (Feed Forward Neural Network (FFNN), Back propagation network (BPL), Recurrent Neural Network (RNN). he study found that the lowest false prediction rate was for the recurrentt network architecture and using the Data on graduate students at the College of Administration and Economics, Univer

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Compression-based Data Reduction Technique for IoT Sensor Networks
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Energy savings are very common in IoT sensor networks because IoT sensor nodes operate with their own limited battery. The data transmission in the IoT sensor nodes is very costly and consume much of the energy while the energy usage for data processing is considerably lower. There are several energy-saving strategies and principles, mainly dedicated to reducing the transmission of data. Therefore, with minimizing data transfers in IoT sensor networks, can conserve a considerable amount of energy. In this research, a Compression-Based Data Reduction (CBDR) technique was suggested which works in the level of IoT sensor nodes. The CBDR includes two stages of compression, a lossy SAX Quantization stage which reduces the dynamic range of the

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Educational And Psychological Researches
Psychological Flow and Its Relation to Futuristic Thinking among Postgraduates
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The research seeks to find the relationship between psychological flow and futuristic thinking among postgraduate students. To this end, the researchers have made up two scales: one scale to measure the psychological flow which consisted of (32) items and the other to measure the futuristic thinking included (39) items which were distributed into three domains. As to collect the required data, the two scales had applied on a sample comprised (200) postgraduate students. The findings revealed that there is a correlation between psychological flow and futuristic thinking. The researcher recommended the coming studies take the relationship between psychological flow and psychological happiness.

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Publication Date
Thu Dec 01 2016
Journal Name
Swarm And Evolutionary Computation
A new multi-objective evolutionary framework for community mining in dynamic social networks
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