Preferred Language
Articles
/
3hhVW5QBVTCNdQwCjxLS
Supervised Classification Accuracy Assessment Using Remote Sensing and Geographic Information System
...Show More Authors

Assessing the accuracy of classification algorithms is paramount as it provides insights into reliability and effectiveness in solving real-world problems. Accuracy examination is essential in any remote sensing-based classification practice, given that classification maps consistently include misclassified pixels and classification misconceptions. In this study, two imaginary satellites for Duhok province, Iraq, were captured at regular intervals, and the photos were analyzed using spatial analysis tools to provide supervised classifications. Some processes were conducted to enhance the categorization, like smoothing. The classification results indicate that Duhok province is divided into four classes: vegetation cover, buildings, water bodies, and bare lands. During 2013-2022, vegetation cover increased from 63% in 2013 to 66% in 2022; buildings roughly increased by 1% to 3% yearly; water bodies showed a decrease of 2% to 1%; the amount of unoccupied land showed a decrease from 34% to 30%. Therefore, the classification accuracy was assessed using the approach of comparison with field data; the classification accuracy was about 85%.

Scopus Clarivate Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Thu Apr 21 2016
Journal Name
Australian Journal Of Basic And Applied Sciences
Sensing Properties of (In2O3:Eu) Thin Films
...Show More Authors

Thin films of iridium doped indium oxide (In2O3:Eu)with different doping ratio(0,3,5,7,and 9%) are prepared on glass and single crystal silicon wafer substrates using spray pyrolysis method. The goal of this research is to investigate the effect of doping ratio on of the structural, optical and sensing properties . The structure of the prepared thin films was characterized at room temperature using X-ray diffraction. The results showed that all the undoped and doped (In2O3:Eu)samples are polycrystalline in structure and nearly stoichiometric. UV-visible spectrophotometer in the wavelength range (200-1100nm)was used to determine the optical energy gap and optical constants. The optical transmittance of 83% and the optical band gap of 5.2eV

... Show More
Publication Date
Fri Jan 11 2019
Journal Name
Iraqi Journal Of Physics
Bulk heterojunction blend (NiPcTs:PEDOT:PSS) in gas sensing
...Show More Authors

Thin films of bulk heterojunction blend Ni-Phthalocyanine
Tetrasulfonic acid tetrasodium salt and dpoly
(3, 4-ethylenedioxythiophene) poly (styrenesulfonate) (NiPcTs:
PEDOT: PSS) with different (PEDOT:PSS) concentrations (0.5, 1, 2)
are prepared using spin coating technique with thickness 100 nm on
glass and Si substrate. The X-Ray diffraction pattern of NiPcTs
powder was studied and compared with NiPc powder, the pattern
showed that the structure is a polycrystalline with monoclinic phase.
XRD analysis of as-deposited (NiPcTs/PEDOT:PSS) thin films
blends in dicated that the film appeared at(100), (102) in
concentrations (0.5, 1) and (100) in concentration (2). The grain size
is increased with increasing

... Show More
View Publication Preview PDF
Crossref
Publication Date
Mon Jun 01 2009
Journal Name
2009 Etp International Conference On Future Computer And Communication
Signal Processing Techniques for Robust Spectrum Sensing
...Show More Authors

Cognitive radios have the potential to greatly improve spectral efficiency in wireless networks. Cognitive radios are considered lower priority or secondary users of spectrum allocated to a primary user. Their fundamental requirement is to avoid interference to potential primary users in their vicinity. Spectrum sensing has been identified as a key enabling functionality to ensure that cognitive radios would not interfere with primary users, by reliably detecting primary user signals. In addition, reliable sensing creates spectrum opportunities for capacity increase of cognitive networks. One of the key challenges in spectrum sensing is the robust detection of primary signals in highly negative signal-to-noise regimes (SNR).In this paper ,

... Show More
View Publication
Scopus (4)
Crossref (2)
Scopus Clarivate Crossref
Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Development of an ANN Model for RGB Color Classification using the Dataset Extracted from a Fabricated Colorimeter
...Show More Authors

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

... Show More
Preview PDF
Scopus Crossref
Publication Date
Sat Dec 01 2018
Journal Name
Indian Journal Of Ecology
Classification of al-hammar marshes satellite images in Iraq using artificial neural network based on coding representation
...Show More Authors

Scopus (2)
Scopus
Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Development of an ANN Model for RGB Color Classification using the Dataset Extracted from a Fabricated Colorimeter
...Show More Authors

 

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

... Show More
View Publication Preview PDF
Scopus Crossref
Publication Date
Mon Jan 29 2024
Journal Name
2024 3rd International Conference On Digital Transformation And Applications (icdxa)
The Mediating Role of Cobit 2019 in Managing the Relationship Between Qualitative Characteristics of Accounting Information and Information Asymmetry
...Show More Authors

The Mediating Role of Cobit 2019 in Managing the Relationship Between Qualitative Characteristics of Accounting Information and Information Asymmetry

View Publication
Scopus Crossref
Publication Date
Sun Sep 05 2010
Journal Name
Baghdad Science Journal
Design and Implementation for optical fiber communication system using frequency shift coding
...Show More Authors

In this research, optical communication coding systems are designed and constructed by utilizing Frequency Shift Code (FSC) technique. Calculations of the system quality represented by signal to noise ratio (S/N), Bit Error Rate (BER),and Power budget are done. In FSC system, the data of Nonreturn- to–zero (NRZ ) with bit rate at 190 kb/s was entered into FSC encoder circuit in transmitter unit. This data modulates the laser source HFCT-5205 with wavelength at 1310 nm by Intensity Modulation (IM) method, then this data is transferred through Single Mode (SM) optical fiber. The recovery of the NRZ is achieved using decoder circuit in receiver unit. The calculations of BER and S/N for FSC system a

... Show More
View Publication Preview PDF
Crossref
Publication Date
Sat Jul 01 2023
Journal Name
Int. J. Advance Soft Compu. Appl,
Arabic and English Texts Encryption Using Proposed Method Based on Coordinates System
...Show More Authors

Preview PDF
Publication Date
Mon Nov 11 2019
Journal Name
Spe
Modeling Rate of Penetration using Artificial Intelligent System and Multiple Regression Analysis
...Show More Authors
Abstract<p>Over the years, the prediction of penetration rate (ROP) has played a key rule for drilling engineers due it is effect on the optimization of various parameters that related to substantial cost saving. Many researchers have continually worked to optimize penetration rate. A major issue with most published studies is that there is no simple model currently available to guarantee the ROP prediction.</p><p>The main objective of this study is to further improve ROP prediction using two predictive methods, multiple regression analysis (MRA) and artificial neural networks (ANNs). A field case in SE Iraq was conducted to predict the ROP from a large number of parame</p> ... Show More
View Publication Preview PDF
Crossref (7)
Crossref