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Image Georeferencing using Artificial Neural Network Compared with Classical Methods
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Georeferencing process is one of the most important prerequisites for various geomatics applications; for example, photogrammetry, laser scan analysis, remotely sensing, spatial and descriptive data collection, and others. Georeferencing mostly involves the transformation of coordinates obtained from images that are inhomogeneous due to accuracy differences. The georeferencing depends on image resolution and accuracy level of measurements of reference points ground coordinates.  Accordingly, this study discusses the subject of coordinate’s transformation from the image to the global coordinates system (WGS84) to find a suitable method that provides more accurate results. In this study, the Artificial Neural Network (ANN) method was applied, in addition to several numerical methods, namely the Affine divided difference, Newton’s divided difference, and polynomial transformation. The four methods were modelled and coded using Matlab programming language based on an image captured from Google Earth. The image was used to determine reference points within the study area (University of Baghdad campus).  The findings of this study showed that the ANN enhanced the results by about 50% in terms of accuracy and 90% in terms of homogeneity, compared with the other methods.

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Publication Date
Thu Jun 30 2022
Journal Name
Iraqi Journal Of Science
Brain MR Images Classification for Alzheimer’s Disease
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    Alzheimer’s Disease (AD) is the most prevailing type of dementia. The prevalence of AD is estimated to be around 5% after 65 years old and is staggering 30% for more than 85 years old in developed countries. AD destroys brain cells causing people to lose their memory, mental functions and ability to continue daily activities. The findings of this study are likely to aid specialists in their decision-making process by using patients’ Magnetic Resonance Imaging (MRI) to distinguish patients with AD from Normal Control (NC). Performance evolution was applied to 346 Magnetic Resonance images from the Alzheimer's Neuroimaging Initiative (ADNI) collection. The Deep Belief Network (DBN) classifier was used to fulfill classification f

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Publication Date
Thu Jan 30 2020
Journal Name
Journal Of Engineering
Dynamic Response Assessment of the Nigerian 330kV Transmission System
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This paper presents the dynamic responses of generators in a multi-machine power system.  The fundamental swing equations for a multi-machine stability analysis are revisited. The swing equations are solved to investigate the influence of a three-phase fault on the network largest load bus. The Nigerian 330kV transmission network was used as a test case for the study. The time domain simulation approach was explored to determine if the system could withstand a 3-phase fault. The stability of the transmission network is estimated considering the dynamic behaviour of the system under various contingency conditions. This study identifies Egbin, Benin, Olorunsogo, Akangba, Sakete, Omotosho and Oshogbo as the key buses w

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Publication Date
Thu Dec 01 2022
Journal Name
Iraqi Journal Of Physics
Investigation of Radio Frequency Signal Propagation of Wireless Services in Oyo, Oyo State, South Western Nigeria
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This study reported the investigation of the Radio Frequency (RF) signal propagation of Global System for Mobile Communications (GSM) coverage in Emmanuel Alayande College of Education (EACOED), Oyo, Oyo State, Nigeria. The study aims at amplifying the quality of service and augment end users' sensitivity of the wireless services operation. The drive test method is adopted with estimation of coverage level and received signal strength. The Network Cell Info Lite application installed in three INFINIX GSM mobile phones was employed to take the measurement of the signal strength received from the transmitting stations of different mobile networks. The results of the study revealed that MTN has the maximum signal strength with a mean value

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Publication Date
Sat Sep 23 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Real-time control for the transmission of information in wireless networks
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Wireless  lietworking is·  constantly improving,  changing  and

though  ba ic  principle  is the same.  ['nstead of  using standard  cables  to transmit information fmm one point to another (qr more), it .uses  radio signals.  This paper  presents .a case  study considedng real-time remote

cqntroJ using Wireless UDP/JP-based networks,. The aim of-this werk is to

reduce  real-time· remote control  system  based upon a simulatio.n  model,

which can operate via general communication  l"]etworks, whieh on bodies. modern wireles  tcchnolqgy.

The  first  part includes· a  brief

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Publication Date
Mon Aug 01 2016
Journal Name
Arpn Journal Of Engineering And Applied Sciences
SURVEY ON VANET TECHNOLOGIES AND SIMULATION MODELS
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Vehicular ad hoc network (VANET) is a distinctive form of Mobile Ad hoc Network (MANET) that has attracted increasing research attention recently. The purpose of this study is to comprehensively investigate the elements constituting a VANET system and to address several challenges that have to be overcome to enable a reliable wireless communications within a vehicular environment. Furthermore, the study undertakes a survey of the taxonomy of existing VANET routing protocols, with particular emphasis on the strengths and limitations of these protocols in order to help solve VANET routing issues. Moreover, as mobile users demand constant network access regardless of their location, this study seeks to evaluate various mobility models for vehi

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Publication Date
Sun Apr 22 2018
Journal Name
Acs Biomaterials Science & Engineering
Engineered coatings for titanium implants to present ultra-low doses of BMP-7
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The ongoing research to improve the clinical outcome of titanium implants has resulted in the implementation of multiple approaches to deliver osteogenic growth factors accelerating and sustaining osseointegration. Here we show the presentation of human bone morphogenetic protein 7 (BMP-7) adsorbed to titanium discs coated with poly(ethyl acrylate) (PEA). We have previously shown that PEA promotes fibronectin organization into nanonetworks exposing integrin- and growth-factor-binding domains, allowing a synergistic interaction at the integrin/growth factor receptor level. Here, titanium discs were coated with PEA and fibronectin and then decorated with ng/mL doses of BMP-7. Human mesenchymal stem cells were used to investigate cellular resp

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Publication Date
Tue Jan 12 2016
Journal Name
Wireless Networks
Low communication cost (LCC) scheme for localizing mobile wireless sensor networks
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In recent years, the number of applications utilizing mobile wireless sensor networks (WSNs) has increased, with the intent of localization for the purposes of monitoring and obtaining data from hazardous areas. Location of the event is very critical in WSN, as sensing data is almost meaningless without the location information. In this paper, two Monte Carlo based localization schemes termed MCL and MSL* are studied. MCL obtains its location through anchor nodes whereas MSL* uses both anchor nodes and normal nodes. The use of normal nodes would increase accuracy and reduce dependency on anchor nodes, but increases communication costs. For this reason, we introduce a new approach called low communication cost schemes to reduce communication

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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Engineering And Sustainable Development
Improving Performance Classification in Wireless Body Area Sensor Networks Based on Machine Learning Techniques
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Wireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s

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Publication Date
Wed Oct 15 2014
Journal Name
International Journal Of Advanced Research
A survey/ Development of Passive Optical Access Networks Technologies
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The bandwidth requirements of telecommunication network users increased rapidly during the last decades. Optical access technologies must provide the bandwidth demand for each user. The passive optical access networks (PONs) support a maximum data rate of 100 Gbps by using the Orthogonal Frequency Division Multiplexing (OFDM) technique in the optical access network. In this paper, the optical broadband access networks with many techniques from Time Division Multiplexing Passive Optical Networks (TDM PON) to Orthogonal Frequency Division Multiplex Passive Optical Networks (OFDM PON) are presented. The architectures, advantages, disadvantages, and main parameters of these optical access networks are discussed and reported which have many ad

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
An Improved Cuckoo Search Algorithm for Maximizing the Coverage Range of Wireless Sensor Networks
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The issue of increasing the range covered by a wireless sensor network with restricted sensors is addressed utilizing improved CS employing the PSO algorithm and opposition-based learning (ICS-PSO-OBL). At first, the iteration is carried out by updating the old solution dimension by dimension to achieve independent updating across the dimensions in the high-dimensional optimization problem. The PSO operator is then incorporated to lessen the preference random walk stage's imbalance between exploration and exploitation ability. Exceptional individuals are selected from the population using OBL to boost the chance of finding the optimal solution based on the fitness value. The ICS-PSO-OBL is used to maximize coverage in WSN by converting r

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