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Land Use/Cover Change Analysis Using Remote Sensing Data: A Case Study, Zhengzhou Area, Henan Province, China
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In the last two decades, arid and semi-arid regions of China suffered rapid changes in the Land Use/Cover Change (LUCC) due to increasing demand on food, resulting from growing population. In the process of this study, we established the land use/cover classification in addition to remote sensing characteristics. This was done by analysis of the dynamics of (LUCC) in Zhengzhou area for the period 1988-2006. Interpretation of a laminar extraction technique was implied in the identification of typical attributes of land use/cover types. A prominent result of the study indicates a gradual development in urbanization giving a gradual reduction in crop field area, due to the progressive economy in Zhengzhou. The results also reflect degradation of land quality inferred from the decline in yield capacity and significant degeneration. Developing land types are Barren land and urban areas (8.02%, and 246.65%). Shrinking land types are water, forest, crop, and grass areas (5.98, 11.52%, 7.09%, and 20.02% respectively). Such changes are the results of physical and anthropogenic factors. The results are expected to provide very useful information for the local government in its future planning.

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Publication Date
Mon Dec 10 2018
Journal Name
Indian Journal Of Natural Sciences
Verification the Pollution of Tigris River in South of Baghdad using Remote Sensing Techniques
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This paper describes the use of remote sensing techniques in verification of the polluted area in Diyala River and Tigris River and the effected of AL-Rustamiyah wastewater treatment plant, which is located on Diyala River, one of the branches of Tigris River in south of Baghdad. SPOT-5 a French satellite image of Baghdad, Iraq was used with ground resolution of 2.5 m in May 2016. ENVI 5.1 software programming was utilized for Image processing to assess the water pollution of Diyala and Tigris River’s water. Five regions were selected from a study area and then classified using the unsupervised ISODATA method. The results indicated that four classes of water quality which are successful in assessing and mapping water pollution which confi

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Publication Date
Thu May 21 2015
Journal Name
Environmental Monitoring And Assessment
Water quality monitoring of Al-Habbaniyah Lake using remote sensing and in situ measurements
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Publication Date
Wed Mar 08 2023
Journal Name
Sensors
A Critical Review of Remote Sensing Approaches and Deep Learning Techniques in Archaeology
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To date, comprehensive reviews and discussions of the strengths and limitations of Remote Sensing (RS) standalone and combination approaches, and Deep Learning (DL)-based RS datasets in archaeology have been limited. The objective of this paper is, therefore, to review and critically discuss existing studies that have applied these advanced approaches in archaeology, with a specific focus on digital preservation and object detection. RS standalone approaches including range-based and image-based modelling (e.g., laser scanning and SfM photogrammetry) have several disadvantages in terms of spatial resolution, penetrations, textures, colours, and accuracy. These limitations have led some archaeological studies to fuse/integrate multip

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Publication Date
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
Tourism Companies Assessment via Social Media Using Sentiment Analysis
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In recent years, social media has been increasing widely and obviously as a media for users expressing their emotions and feelings through thousands of posts and comments related to tourism companies. As a consequence, it became difficult for tourists to read all the comments to determine whether these opinions are positive or negative to assess the success of a tourism company. In this paper, a modest model is proposed to assess e-tourism companies using Iraqi dialect reviews collected from Facebook. The reviews are analyzed using text mining techniques for sentiment classification. The generated sentiment words are classified into positive, negative and neutral comments by utilizing Rough Set Theory, Naïve Bayes and K-Nearest Neighbor

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Publication Date
Sat Dec 30 2023
Journal Name
Journal Of Economics And Administrative Sciences
The Cluster Analysis by Using Nonparametric Cubic B-Spline Modeling for Longitudinal Data
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Longitudinal data is becoming increasingly common, especially in the medical and economic fields, and various methods have been analyzed and developed to analyze this type of data.

In this research, the focus was on compiling and analyzing this data, as cluster analysis plays an important role in identifying and grouping co-expressed subfiles over time and employing them on the nonparametric smoothing cubic B-spline model, which is characterized by providing continuous first and second derivatives, resulting in a smoother curve with fewer abrupt changes in slope. It is also more flexible and can pick up on more complex patterns and fluctuations in the data.

The longitudinal balanced data profile was compiled into subgroup

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Publication Date
Thu Dec 13 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Causes of maternal death in Mizan Aman and Gebretsadik shawo general hospitals from 2011 – 2015: A case - control study using propensity score matching analysis
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Objective: To identify causes of maternal death in Mizan Aman and Gebretsadik shawo general hospitals
Methodology: A case control study on 595 charts, 119 cases and 476 controls was conducted in Mizan
Aman & Gebretsadik shawo general hospitals. Data was analyzed by STATA 13.1. Propensity score
matching analysis was used to see causes of maternal death.
Results: Hemorrhage were the main direct causes of maternal death which accounts 47.9% (β =0.58
(95% CI (0.28,0.87)) in hospital but when projected to population based the sample (β =0.26 (95% CI
(0.22,0.31)). Followed by infection 36 (25.21%) (β = 0.50 (95% CI (0.08, 0.92)). when projected to
population based the sample PIH 7.6%) is significant cause (β = 0.16

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Publication Date
Thu Jun 16 2022
Journal Name
Al-khwarizmi Engineering Journal
Comparative study of vibration analysis in rotary shafts between Rayleigh's and Dunkerley's methods
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The importance of vibrations in rotating rotors in engineering applications has been examined, as has the best approach to interpreting vibration data. The most extensively used analytical approaches for rotating shaft vibration analysis have been investigated. In this research, a detailed study was made of the Rayleigh and Dunkerley methods due to their importance in the special calculations to find the amplitude of vibrations in the rotation system. The multi-node method was used to calculate both Dunkerley's and Rayleigh's methods. An experimental platform was built to study the vibrations that occur in the rotating shafts, and the results were compared with theoretical calculations and with different distances of the bearings. It pro

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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Multispectral and Panchromatic used Enhancement Resolution and Study Effective Enhancement on Supervised and Unsupervised Classification Land – Cover
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Publication Date
Sat Jan 01 2022
Journal Name
Proceeding Of The 1st International Conference On Advanced Research In Pure And Applied Science (icarpas2021): Third Annual Conference Of Al-muthanna University/college Of Science
Climate change and its effect on water and vegetation cover over shary region using GIS techniques
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Publication Date
Fri Aug 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Efficiency Measurement Model for Postgraduate Programs and Undergraduate Programs by Using Data Envelopment Analysis
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Measuring the efficiency of postgraduate and undergraduate programs is one of the essential elements in educational process. In this study, colleges of Baghdad University and data for the academic year (2011-2012) have been chosen to measure the relative efficiencies of postgraduate and undergraduate programs in terms of their inputs and outputs. A relevant method to conduct the analysis of this data is Data Envelopment Analysis (DEA). The effect of academic staff to the number of enrolled and alumni students to the postgraduate and undergraduate programs are the main focus of the study.

 

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