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Development of Spatial Data Infrastructure based on Free Data Integration
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In recent years, the performance of Spatial Data Infrastructures for governments and companies is a task that has gained ample attention. Different categories of geospatial data such as digital maps, coordinates, web maps, aerial and satellite images, etc., are required to realize the geospatial data components of Spatial Data Infrastructures. In general, there are two distinct types of geospatial data sources exist over the Internet: formal and informal data sources. Despite the growth of informal geospatial data sources, the integration between different free sources is not being achieved effectively. The adoption of this task can be considered the main advantage of this research. This article addresses the research question of how the integration of free geospatial data can be beneficial within domains such as Spatial Data Infrastructures. This was carried out by suggesting a common methodology that uses road networks information such as lengths, centeroids, start and end points, number of nodes and directions to integrate free and open source geospatial datasets. The methodology has been proposed for a particular case study: the use of geospatial data from OpenStreetMap and Google Earth datasets as examples of free data sources. The results revealed possible matching between the roads of OpenStreetMap and Google Earth datasets to serve the development of Spatial Data Infrastructures.

 

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Publication Date
Sun Jun 23 2024
Journal Name
Asee Annual Conference And Exposition
Undergraduate Research Impact on Students' Retention and Academic Development Based on Their Study Field and the Mentoring Approach
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The impact of undergraduate research experiences on students' academic development and retention in STEM fields is significant. Students' success in STEM fields is based on developing strong research and critical thinking skills that make it essential for students to engage in research activities throughout their academic programs. This work evaluates the effectiveness of undergraduate research experiences with respect to its influence on student retention and academic development. The cases presented are based on years of experience implementing undergraduate research programs in various STEM fields at Colorado State University Pueblo (CSU Pueblo) funded by HSI STEM Grants. The study seeks to establish a correlation between students' reten

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Scopus
Publication Date
Wed May 10 2023
Journal Name
Journal Of Engineering
Free Head Shear Test on Decomposed Granite Soil
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The study presents the test results of Completely Decomposed Granite (CDG) soil tested under drained triaxial compression, direct shear and simple shear tests. Special attention was focused on the modification of the upper halve of conventional Direct Shear Test (DST) to behave as free
head in movement along with vertical strain control during shear stage by using Geotechnical Digital System (GDS). The results show that Free Direct Shear Test (FDST) has clear effect on the measured shear stress and vertical strain during the test. It has been found that shear strength
parameters measured from FDST were closer to those measured from simple shear and drained triaxial compression test. This study also provides an independent check on

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Publication Date
Sat Mar 31 2018
Journal Name
Journal Of Engineering
Integration of Transportation Stations as Intermodal Stations
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Ease of transfer between different modes of public transportation within the stations is a significant contribution to the movement that can be provided by transportation industries to develop solutions of integrated transportation. It is future integrated multimodal transportation, to make public transportation more enjoyable and interesting, in addition to passenger transportation and future movement of goods are also depend on multimodal transportation The importance of interchange promotion between multimodal as a basic feature of passengers buildings in modern Railway Stations the Research problem:" con

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Publication Date
Tue Sep 01 2020
Journal Name
Al-khwarizmi Engineering Journal
Arduino-Based Controller for Sequence Development of Automated Manufacturing System
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It has become necessary to change from a traditional system to an automated system in production processes, because it has high advantages. The most important of them is improving and increasing production. But there is still a need to improve and develop the work of these systems. The objective of this work is to study time reduction by combining multiple sequences of operations into one process. To carry out this work, the pneumatic system is designed to decrease\ increase the time of the sequence that performs a pick and place process through optimizing the sequences based on the obstacle dimensions. Three axes are represented using pneumatic cylinders that move according to the sequence used. The system is implemented and

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Publication Date
Tue Sep 01 2020
Journal Name
Al-khwarizmi Engineering Journal
Arduino-Based Controller for Sequence Development of Automated Manufacturing System
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It has become necessary to change from a traditional system to an automated system in production processes, because it has high advantages. The most important of them is improving and increasing production. But there is still a need to improve and develop the work of these systems.

The objective of this work is to study time reduction by combining multiple sequences of operations into one process. To carry out this work, the pneumatic system is designed to decrease\ increase the time of the sequence that performs a pick and place process through optimizing the sequences based on the obstacle dimensions. Three axes are represented using pneumatic cylinders that move according to the sequence used. The system is implemented and con

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Publication Date
Fri Oct 26 2018
Journal Name
Journal Of Planner And Development
Alternative Methods for Decreasing Infrastructure Deficiencies in Iraq
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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
Tue Oct 01 2013
Journal Name
Proceedings Of The International Astronomical Union
The infrared <i>K</i>-band identification of the DSO/G2 source from VLT and Keck data
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Abstract<p>A fast moving infrared excess source (G2) which is widely interpreted as a core-less gas and dust cloud approaches Sagittarius A* (Sgr A*) on a presumably elliptical orbit. VLT <italic>K<sub>s</sub></italic>-band and Keck <italic>K</italic>′-band data result in clear continuum identifications and proper motions of this ∼19<sup><italic>m</italic></sup> Dusty S-cluster Object (DSO). In 2002-2007 it is confused with the star S63, but free of confusion again since 2007. Its near-infrared (NIR) colors and a comparison to other sources in the field speak in favor of the DSO being an IR excess star with photospheric continuum emission at 2 microns than a</p> ... Show More
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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
A Comparison between Ericson's Formulae Results and Experimental Data Using New Formulae of Single Particle Level Density
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The partial level density PLD of pre-equilibrium reactions that are described by Ericson’s formula has been studied using different formulae of single particle level density . The parameter  was used from the equidistant spacing model (ESM) model and the non- equidistant spacing model (non-ESM) and another formula of  are derived from the relation between  and level density parameter . The formulae used to derive  are the Roher formula, Egidy formula, Yukawa formula, and Thomas –Fermi formula. The partial level density results that depend on  from the Thomas-Fermi formula show a good agreement with the experimental data.

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Scopus Crossref
Publication Date
Mon Mar 31 2025
Journal Name
The Iraqi Geological Journal
Evaluation of Machine Learning Techniques for Missing Well Log Data in Buzurgan Oil Field: A Case Study
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The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti

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