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Optimizing Application of UAV-Based SfM Photogrammetric 3D Mapping in Urban Areas
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In recent years, the extensive need for high-quality acquisition platforms for various 3D mapping applications has rapidly increased, especially in sensor performance, portability, and low cost. Image-based UAV sensors have overwhelming merits over alternative solutions for their high timeline and resilience data acquisition systems and the high-resolution spatial data they can provide through extensive Computer Vision (CV) data processing approaches. However, applying this technique, including the appropriate selection of flight mission and image acquisition parameters, ground settings and targeting, and Structure from Motion- Multi-View Stereo (SfM-MVS) post-processing, must be optimized to the type of study site and feature characteristics. This research focuses on optimizing the application of UAV-SfM photogrammetry in an urban area on the east bank of the Tigris River in the north region of Iraq following optimized data capturing plan and SfM-MVS photogrammetric workflow. The research presented the practical application of optimized flight planning, data acquisition, image processing, accuracy analysis, and evaluation based on ground truth targets designed for the proposed optimal routine. This includes investigating the influence of the number and distribution of GCPs, flying heights, and processing parameters on the quality of the produced 3D data. The research showed the potential of low-budget and affordable UAV devices to deliver robust 3D products in a relatively short period by demonstrating the value of UAV-based image techniques when contributed to CV algorithms. The results showed powerful outcomes with validation errors reaching a centimeter-level from 100 m flying height when applying the optimized flight plan settings and the appropriate selection of the number and distribution of GCPs. The study established a streamlined UAV mapping procedure, demonstrated the viability of UAV use for 3D mapping applications, offered suggestions for enhancing future applications, and offered clues as to whether or not UAVs could serve as a viable alternative to conventional ground-based surveying techniques in accurate applications.

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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
Sun Jan 01 2017
Journal Name
Statistical Applications In Genetics And Molecular Biology
Mixture model-based association analysis with case-control data in genome wide association studies
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Abstract<p>Multilocus haplotype analysis of candidate variants with genome wide association studies (GWAS) data may provide evidence of association with disease, even when the individual loci themselves do not. Unfortunately, when a large number of candidate variants are investigated, identifying risk haplotypes can be very difficult. To meet the challenge, a number of approaches have been put forward in recent years. However, most of them are not directly linked to the disease-penetrances of haplotypes and thus may not be efficient. To fill this gap, we propose a mixture model-based approach for detecting risk haplotypes. Under the mixture model, haplotypes are clustered directly according to their estimated d</p> ... Show More
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Publication Date
Wed Sep 20 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Modified Radial Based Neural Network for Clustering and Routing Optimal Path in Wireless Network
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Several methods have been developed for routing problem in MANETs wireless network, because it considered very important problem in this network ,we suggested proposed method based on modified radial basis function networks RBFN and Kmean++ algorithm. The modification in RBFN for routing operation in order to find the optimal path between source and destination in MANETs clusters. Modified Radial Based Neural Network is very simple, adaptable and efficient method to increase the life time of nodes, packet delivery ratio and the throughput of the network will increase and connection become more useful because the optimal path has the best parameters from other paths including the best bitrate and best life link with minimum delays. The re

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Microwave Nondestructive Testing for Defect Detection in Composites Based on K-Means Clustering Algorithm
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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
A Word Cloud Model based on Hate Speech in an Online Social Media Environment
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Social media is known as detectors platform that are used to measure the activities of the users in the real world. However, the huge and unfiltered feed of messages posted on social media trigger social warnings, particularly when these messages contain hate speech towards specific individual or community. The negative effect of these messages on individuals or the society at large is of great concern to governments and non-governmental organizations. Word clouds provide a simple and efficient means of visually transferring the most common words from text documents. This research aims to develop a word cloud model based on hateful words on online social media environment such as Google News. Several steps are involved including data acq

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Publication Date
Thu Dec 01 2022
Journal Name
Environmental Nanotechnology, Monitoring & Management
Synthesis of nano-magnetite and magnetite/synthetic geopolymer nano-porous composite for application as a novel adsorbent
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In this work magnetite/geopolymer composite (MGP) were synthesized using a chemical co-precipitation technique. The synthesized materials were characterized using several techniques such as: “X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), vibrating sample-magnetometer (VSM), field-emission scanning electron microscopy (FE-SEM), energy dispersive X-ray spectroscopy (EDS), Brunauer–Emmett–Teller (BET) and Barrentt-Joyner-Halenda (BJH)” to determine the structure and morphology of the obtained material. The analysis indicated that metal oxide predominantly appeared at the shape of the spinel structure of magnetite, and that the presence of nano-magnetite had a substantial impact on the surface area and pore st

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Publication Date
Thu Jan 21 2021
Journal Name
Iop Conf. Series: Materials Science And Engineering
Synthesis, spectroscopic study, biological activity and dyeing application of curcumin - Schiff base with various metal ions complexes
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A tetradentate (N2O2) Schiff base (H2Ldfm) was successfully synthesized via condensation of curcumin / diferuloylmethane (dfm) and L-leucine amino acid (HL). There were three different methods that used for synthesizing H2Ldfm; (refluxing, grading, and fusion). Ten different metal complexes were also successfully synthesized by combination of the Schiff base (H2Ldfm) and 1,10-phenanthroline (phen) ligand to form a hexadentate (N4O2) mixed ligands (Ldfm , phen) with ten different metal salts (M) where{ M= Al(III), Mn(II), Fe(III), Co(II), Ni(II), Cu(II), Ag(I), Cd(II), Hg(II), and Pb(II)}. The molar ratio of reactants was (1:1:1) (M: H2Ldfm : phen). The new Schiff base and its new complexes were characterized by different physicochemical tec

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Publication Date
Sat Sep 30 2023
Journal Name
Journal Of The College Of Education For Women
The Prophetic Speeches (Hadith) on Sciences and Scientists: Application of the "Text from Text and D+" Theory
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This study aims to apply the theory of "Text from Text and the Plus Dimension" in the analysis of the Prophetic discourse found in the section on the virtues of knowledge and scholars from Imam Sahih al-Bukhari's book. This section covers several topics, including the virtue of gathering for the sake of learning, the superiority of a scholar over a worshipper, the excellence of jurisprudence in the religion of Allah, the acquisition of knowledge through the passing away of scholars, the merit of inviting people to Allah, the continuing benefit of beneficial knowledge after a scholar's demise, the warning against seeking knowledge for purposes other than Allah, and the Prophet seeking refuge from knowledge tha

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Publication Date
Mon Apr 01 2019
Journal Name
Journal Of Materials In Civil Engineering
Moisture Susceptibility and Fatigue Performance of Hydrated Lime–Modified Asphalt Concrete: Experiment and Design Application Case Study
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Hydrated lime has been recognized as an effective additive used to improve asphalt concrete properties in pavement applications. However, further work is still needed to quantify the effect of hydrated lime on asphaltic concrete performance under varied weather, temperature, and environmental conditions and in the application of different pavement courses. A research project was conducted using hydrated lime to modify the asphalt concretes used for the applications of wearing (surface), leveling (binder), and base courses. A previous publication reported the experimental study on the resistance to Marshall stability and the volumetric properties, the resilient modulus, and permanent deformation at three different weather temperatures. This

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Publication Date
Sat Apr 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Application the generalized estimating equation Method (GEE) to estimate of conditional logistic regression model for repeated measurements
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Conditional logistic regression is often used to study the relationship between event outcomes and specific prognostic factors in order to application of logistic regression and utilizing its predictive capabilities into environmental studies. This research seeks to demonstrate a novel approach of implementing conditional logistic regression in environmental research through inference methods predicated on longitudinal data. Thus, statistical analysis of longitudinal data requires methods that can properly take into account the interdependence within-subjects for the response measurements. If this correlation ignored then inferences such as statistical tests and confidence intervals can be invalid largely.

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