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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
Thu Feb 01 2018
Journal Name
Journal Of Pharmacy Research
Synthesis and antimicrobial evaluation of new-[2-amino-4- (4-chloro-/4-bromophenyl)-1,3-thiazole derivatives
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Publication Date
Thu Nov 14 2019
Journal Name
Advances In Intelligent Systems And Computing
The Application of Bus Rapid Transit System in the City of Baquba and Its Impact on Reducing Daily Trips
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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
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
Wed Dec 16 2020
Journal Name
Electronics
Downlink Training Design for FDD Massive MIMO Systems in the Presence of Colored Noise
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Massive multiple-input multiple-output (MaMi) systems have attracted much research attention during the last few years. This is because MaMi systems are able to achieve a remarkable improvement in data rate and thus meet the immensely ongoing traffic demands required by the future wireless networks. To date, the downlink training sequence (DTS) for the frequency division duplex (FDD) MaMi communications systems have been designed based on the idealistic assumption of white noise environments. However, it is essential and more practical to consider the colored noise environments when designing an efficient DTS for channel estimation. To this end, this paper proposes a new DTS design by exploring the joint use of spatial channel and n

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Publication Date
Sun Mar 02 2014
Journal Name
Baghdad Science Journal
An Ecological and Identification Study for Algae in Groundwater of Selected Area in Tikrit city and It’s Surrounding Area
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The present study is carried out to identify the algae in the groundwater of the three areas of Tikrit city, including (the center of Tikrit , the region of AL-Jazira , Awainat village) by nine wells, a depths ranged between 9 meter at well 8 and 110 meter at wells 3 and 5 . And examined the environmental characteristics of physical, chemical and biological factors during the study period from September 2009 to June 2010. It is obtained that wells in the study area is lower alkalinity, average it ranged (6.448-7.418). It was noted that the values of the dissolved oxygen are few and almost non-existent in some cases it ranged between (6.5-6.3)mg/l , analysis of biological oxygen demand refers to wells water (clean- very clean) average

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Publication Date
Sun Jun 01 2025
Journal Name
Civil Engineering Journal
Street Networks and Urban Sustainability by Quantifying Connectivity, Accessibility, and Walkability for Resilient Cities
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Street networks are crucial in shaping the quality of urban life. Through their impact on mobility and social interaction, they play a critical role in shaping how people move around the city and determine the connectivity, accessibility, safety, and convenience of different areas. Thus, it is essential to develop a systematic understanding of street networks to create livable, sustainable, accessible, and equitable cities. The aim of this study is to analyze and develop the role of street networks in shaping urban mobility, connectivity, and accessibility, and thereby enhance sustainable urban living by creating people-centric cities. Quantitative techniques and measures are employed to examine urban structure metrics to understand

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Publication Date
Wed Dec 13 2023
Journal Name
2023 3rd International Conference On Intelligent Cybernetics Technology & Applications (icicyta)
GPT-4 versus Bard and Bing: LLMs for Fake Image Detection
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The recent emergence of sophisticated Large Language Models (LLMs) such as GPT-4, Bard, and Bing has revolutionized the domain of scientific inquiry, particularly in the realm of large pre-trained vision-language models. This pivotal transformation is driving new frontiers in various fields, including image processing and digital media verification. In the heart of this evolution, our research focuses on the rapidly growing area of image authenticity verification, a field gaining immense relevance in the digital era. The study is specifically geared towards addressing the emerging challenge of distinguishing between authentic images and deep fakes – a task that has become critically important in a world increasingly reliant on digital med

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Publication Date
Wed Jan 01 2020
Journal Name
Arab Journal Of Basic And Applied Sciences
Boundary-domain integral method and homotopy analysis method for systems of nonlinear boundary value problems in environmental engineering
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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Geological Journal
Estimation of Initial Oil in Place for Buzurgan Oil Field by Using Volumetric Method and Reservoir Simulation Method
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The estimation of the initial oil in place is a crucial topic in the period of exploration, appraisal, and development of the reservoir. In the current work, two conventional methods were used to determine the Initial Oil in Place. These two methods are a volumetric method and a reservoir simulation method. Moreover, each method requires a type of data whereet al the volumetric method depends on geological, core, well log and petrophysical properties data while the reservoir simulation method also needs capillary pressure versus water saturation, fluid production and static pressure data for all active wells at the Mishrif reservoir. The petrophysical properties for the studied reservoir is calculated using neural network technique

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