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Assessing the performance of commercial Agisoft PhotoScan software to deliver reliable data for accurate3D modelling
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3D models delivered from digital photogrammetric techniques have massively increased and developed to meet the requirements of many applications. The reliability of these models is basically dependent on the data processing cycle and the adopted tool solution in addition to data quality. Agisoft PhotoScan is a professional image-based 3D modelling software, which seeks to create orderly, precise n 3D content from fixed images. It works with arbitrary images those qualified in both controlled and uncontrolled conditions. Following the recommendations of many users all around the globe, Agisoft PhotoScan, has become an important source to generate precise 3D data for different applications. How reliable is this data for accurate 3D modelling applications is the current question that needs an answer. Therefore; in this paper, the performance of the Agisoft PhotoScan software was assessed and analyzed to show the potential of the software for accurate 3D modelling applications. To investigate this, a study was carried out in the University of Baghdad / Al-Jaderia campus using data collected from airborne metric camera with 457m flying height. The Agisoft results show potential according to the research objective and the dataset quality following statistical and validation shape analysis.

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Publication Date
Thu Nov 01 2018
Journal Name
Computers & Fluids
Assessing moment-based boundary conditions for the lattice Boltzmann equation: A study of dipole-wall collisions
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Publication Date
Wed Dec 01 2021
Journal Name
Journal Of Economics And Administrative Sciences
Mathematical Modelling of Gene Regulatory Networks
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    This research includes the use of an artificial intelligence algorithm, which is one of the algorithms of biological systems which is the algorithm of genetic regulatory networks (GRNs), which is a dynamic system for a group of variables representing space within time. To construct this biological system, we use (ODEs) and to analyze the stationarity of the model we use Euler's method. And through the factors that affect the process of gene expression in terms of inhibition and activation of the transcription process on DNA, we will use TF transcription factors. The current research aims to use the latest methods of the artificial intelligence algorithm. To apply Gene Regulation Networks (GRNs), we used a progr

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Publication Date
Fri Jul 01 2011
Journal Name
25th International Cartographic Conference
User generated content and formal data sources for integrating geospatial data
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Today, problems of spatial data integration have been further complicated by the rapid development in communication technologies and the increasing amount of available data sources on the World Wide Web. Thus, web-based geospatial data sources can be managed by different communities and the data themselves can vary in respect to quality, coverage, and purpose. Integrating such multiple geospatial datasets remains a challenge for geospatial data consumers. This paper concentrates on the integration of geometric and classification schemes for official data, such as Ordnance Survey (OS) national mapping data, with volunteered geographic information (VGI) data, such as the data derived from the OpenStreetMap (OSM) project. Useful descriptions o

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Publication Date
Mon Jan 01 2018
Journal Name
Lecture Notes Of The Institute For Computer Sciences, Social Informatics And Telecommunications Engineering
Sensor Data Classification for the Indication of Lameness in Sheep
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Publication Date
Thu Jul 01 2021
Journal Name
University Of Northampton Pue
Validating a Proposed Data Mining Approach (SLDM) for Motion Wearable Sensors to Detect the Early Signs of Lameness in Sheep
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Publication Date
Sun Jul 31 2022
Journal Name
Journal Of Computational Innovation And Analytics (jcia)
PERFORMANCE MEASURE OF MULTIPLE-CHANNEL QUEUEING SYSTEMS WITH IMPRECISE DATA USING GRADED MEAN INTEGRATION FOR TRAPEZOIDAL AND HEXAGONAL FUZZY NUMBERS
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In this paper, a procedure to establish the different performance measures in terms of crisp value is proposed for two classes of arrivals and multiple channel queueing models, where both arrival and service rate are fuzzy numbers. The main idea is to convert the arrival rates and service rates under fuzzy queues into crisp queues by using graded mean integration approach, which can be represented as median rule number. Hence, we apply the crisp values obtained to establish the performance measure of conventional multiple queueing models. This procedure has shown its effectiveness when incorporated with many types of membership functions in solving queuing problems. Two numerical illustrations are presented to determine the validity of the

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Publication Date
Sun Apr 07 2013
Journal Name
Journal Of Educational And Psychological Researches
Effectiveness of enrichment activities through using software program for second graders in Conversation article
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Today we are witnessing huge scientific and technical progress so we need more skills and methods of thinking that needs to be acquired by the teacher, as the importance of computers in education  there are  many teachers  suffering  of the difficulty in teaching for pupils . researchers tried to  find a good suitable way with the technological  interests for now which represent by  computer design software and the introduction of enrichment activities in the curriculum because it is one of a contemporary trends for the development of the Arabic language with various levels of education and knowing if this program has negative or positive impact.

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Publication Date
Mon Apr 01 2019
Journal Name
2019 International Conference On Automation, Computational And Technology Management (icactm)
Multi-Resolution Hierarchical Structure for Efficient Data Aggregation and Mining of Big Data
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Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an

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Publication Date
Mon Jan 01 2024
Journal Name
Explainable Artificial Intelligence In The Digital Sustainability Administration
Harnessing Technological Innovation and Artificial Intelligence in Iraqi Commercial Banks to Achieve Sustainability
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Publication Date
Fri Jan 01 2010
Journal Name
Positioning
Fluid Inclusions Usage for Assessing Oil Migration in Duhok, North Iraq
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