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joe-2227
Optimized Zero and First Order Design of Micro Geodetic Networks
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Precision is one of the main elements that control the quality of a geodetic network, which defines as the measure of the network efficiency in propagation of random errors. This research aims to solve ZOD and FOD problems for a geodetic network using Rosenbrock Method to optimize the geodetic networks by using MATLAB programming language, to find the optimal design of geodetic network with high precision. ZOD problem was applied to a case study network consists of 19 points and 58 designed distances with a priori deviation equal to 5mm, to determine the best points in the network to consider as control points. The results showed that P55 and P73 having the minimum ellipse of error and considered as control points. FOD problem was applied to three cases of selected network to analyzed using the objective function of A-Optimality and D-Optimality, with selected range of movement of 300m to each point in each direction. The first case was a free network, the second case was with P55 and P73 as control points, and the third case was with P42 and P44 as control points. The results showed that the third case was the optimal design with high precision

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Publication Date
Thu Jun 02 2016
Journal Name
مجلة العلوم التربوية والنفسية
The effect of the K.W.L.Plus strategy in developing the mental skills and reflective thinking of first-year middle school female students
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Publication Date
Sun Jul 02 2017
Journal Name
Journal Of Educational And Psychological Researches
The Effect of Carin Model in The Achievement of The First Intermediate Grade Students and Their Reflective Thinking in Physics Subject.
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The Current research aims to identify ( the effect of Carin model in the achievement of the first intermediate Grade Students and their Reflective Thinking in physics Subject ) the researcher selected the experimental design with a partial adjust , The research sample consisted of ( 47 ) Students with ( 23 ) Students in the experimental group and ( 24 ) Students in the control group , The two groups rewarded in the variables chronological age in months , Reflective Thinking and the degrees in physics in the first course. The researcher coined the purposes of behavioral which belong to chapter fifth, sixth, and seventh of physics books scheduled of the school year ( 2015-2016 ) and prepared appropriate lesson plans for the two experimenta

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Publication Date
Sat Sep 27 2014
Journal Name
Soft Computing
Multi-objective evolutionary routing protocol for efficient coverage in mobile sensor networks
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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Data Aggregation in Wireless Sensor Networks Using Modified Voronoi Fuzzy Clustering Algorithm
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Data centric techniques, like data aggregation via modified algorithm based on fuzzy clustering algorithm with voronoi diagram which is called modified Voronoi Fuzzy Clustering Algorithm (VFCA) is presented in this paper. In the modified algorithm, the sensed area divided into number of voronoi cells by applying voronoi diagram, these cells are clustered by a fuzzy C-means method (FCM) to reduce the transmission distance. Then an appropriate cluster head (CH) for each cluster is elected. Three parameters are used for this election process, the energy, distance between CH and its neighbor sensors and packet loss values. Furthermore, data aggregation is employed in each CH to reduce the amount of data transmission which le

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Publication Date
Tue Jan 30 2024
Journal Name
Iraqi Journal Of Science
Parallel Particle Swarm Optimization Algorithm for Identifying Complex Communities in Biological Networks
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    Identification of complex communities in biological networks is a critical and ongoing challenge since lots of network-related problems correspond to the subgraph isomorphism problem known in the literature as NP-hard. Several optimization algorithms have been dedicated and applied to solve this problem. The main challenge regarding the application of optimization algorithms, specifically to handle large-scale complex networks, is their relatively long execution time. Thus, this paper proposes a parallel extension of the PSO algorithm to detect communities in complex biological networks. The main contribution of this study is summarized in three- fold; Firstly, a modified PSO algorithm with a local search operator is proposed

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Publication Date
Sun Jul 01 2012
Journal Name
Applied Soft Computing
A new evolutionary based routing protocol for clustered heterogeneous wireless sensor networks
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Publication Date
Sat Dec 31 2022
Journal Name
International Journal Of Intelligent Engineering And Systems
Dynamic Virtual Network Embedding with Latency Constraint in Flex-Grid Optical Networks
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Publication Date
Sun Jul 01 2018
Journal Name
Ieee Transactions On Intelligent Transportation Systems
Real-Time Intersection-Based Segment Aware Routing Algorithm for Urban Vehicular Networks
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High vehicular mobility causes frequent changes in the density of vehicles, discontinuity in inter-vehicle communication, and constraints for routing protocols in vehicular ad hoc networks (VANETs). The routing must avoid forwarding packets through segments with low network density and high scale of network disconnections that may result in packet loss, delays, and increased communication overhead in route recovery. Therefore, both traffic and segment status must be considered. This paper presents real-time intersection-based segment aware routing (RTISAR), an intersection-based segment aware algorithm for geographic routing in VANETs. This routing algorithm provides an optimal route for forwarding the data packets toward their destination

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Computational Intelligence Systems
Evolutionary Feature Optimization for Plant Leaf Disease Detection by Deep Neural Networks
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Publication Date
Sun Jan 01 2017
Journal Name
Journal Of Sensors
Sequential Monte Carlo Localization Methods in Mobile Wireless Sensor Networks: A Review
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The advancement of digital technology has increased the deployment of wireless sensor networks (WSNs) in our daily life. However, locating sensor nodes is a challenging task in WSNs. Sensing data without an accurate location is worthless, especially in critical applications. The pioneering technique in range-free localization schemes is a sequential Monte Carlo (SMC) method, which utilizes network connectivity to estimate sensor location without additional hardware. This study presents a comprehensive survey of state-of-the-art SMC localization schemes. We present the schemes as a thematic taxonomy of localization operation in SMC. Moreover, the critical characteristics of each existing scheme are analyzed to identify its advantages

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