Yaseen T Mustafa | University of Zakho (original) (raw)

Papers by Yaseen T Mustafa

Journal of applied science and technology trends, Jul 30, 2022

The concept of ecosystem service (ES) was originally developed to illustrate the benefits that na... more The concept of ecosystem service (ES) was originally developed to illustrate the benefits that natural ecosystems generate for society and to raise awareness for biodiversity and ecosystem conservation. In recent years, geographical information systems (GIS) have become a powerful tool for mapping (ES) within a landscape, which visualizes spatial and temporal patterns and changes in ecosystems and their services. Mapping (ES) is necessary for the progress of strategies that will guarantee their future supply and to support the policies in a more effective way. The comprehensive literature review was conducted using international databases such as Elsevier, Springer, Wiley, and Google Scholar. We used key terms including 'mapping', 'maps', 'ES or ecosystem service, 'ecosystem functions', 'landscape functions', 'evaluation of ES', and 'assessment of services'. To identify mapping ecosystem services and their challenges and opportunities. In total, 65 research papers were found first, of which 34 were selected for review. The most important challenges are insufficient generation of ES in the context of managed systems, the need to estimate associations among indicators of (ES) incomplete understanding of the nature of associations among services, and the lack of a general numerical outline to address these relations.

IEEE Access

The accurate quantification of surface soil moisture (SSM) and vegetation cover using remote sens... more The accurate quantification of surface soil moisture (SSM) and vegetation cover using remote sensing techniques is essential for effective environmental management. This study investigated the spatial variations in SSM and vegetation cover in the Batifa region of the Kurdistan Region of Iraq. Landsat-8 images of the study area were classified using a support vector machine (SVM), and the soil land type was subsequently extracted. A random forest (RF) algorithm was developed to retrieve SSM using Landsat data in conjunction with in situ measurements. The results demonstrated that the RF algorithm achieved a high coefficient of determination (R 2 = 0.80) for the SSM retrieval. The study area exhibited distinct distributions of SSM and normalized difference vegetation index (NDVI) values across different ranges. The low range of SSM (2.21%-3.34%) and NDVI (−0.020-0.172) values occupied approximately 25% of the soil area, whereas the moderate range of SSM (3.34%-4.05%) and NDVI (0.172-0.238) values covered approximately 50% of the soil area. A high range of SSM (4.05%-6.49%) and NDVI (0.238-0.935) values was found in approximately 25% of the region. The southern part of Batifa experienced drought conditions, whereas the northern part exhibited higher SSM levels. Anthropogenic resources caused a decrease in vegetation and SSM in Batifa. These findings have significant implications for sustainable management of water and soil resources in the Batifa area.

Iraqi geological journal, Sep 30, 2022

The temperature rise has become a serious environmental concern affected by both human and natura... more The temperature rise has become a serious environmental concern affected by both human and natural factors. Worldwide, rising land surface temperatures have emerged as the most pressing issue facing the twenty-first century. In the last two decades, a curious change was realized in temperature in the Duhok district of Iraq. Hence, this study examined the spatiotemporal land surface temperature distribution and Modified Soil Adjusted Vegetation Index (MSAVI2) and the correlation between them in the Duhok district in three different years 2001, 2011, and 2021 using Landsat satellite images. Air temperature data from seven weather stations were used to validate the land surface temperature results. The study's findings revealed that the Duhok district's LST has risen during the study period. In general, the average land surface temperature has been increasing at a rate of 0.15 °C per year. Other findings showed that the vegetation cover of the Duhok district has changed dynamically. In all three years of study, the regression analysis results indicated that there was a negative correlation between LST and MSAVI2. This method of evaluation will be useful in guiding future urban management work and local government strategies.

Journal of applied science and technology trends, Apr 2, 2022

The resection in 3D space is a common problem in surveying engineering and photogrammetry based o... more The resection in 3D space is a common problem in surveying engineering and photogrammetry based on observed distances, angles, and coordinates. This resection problem is nonlinear and comprises redundant observations which is normally solved using the least-squares method in an iterative approach. In this paper, we introduce a vigorous angular based resection method that converges to the global minimum even with very challenging starting values of the unknowns. The method is based on deriving oblique angles from the measured horizontal and vertical angles by solving spherical triangles. The derived oblique angles tightly connected the rays enclosed between the resection point and the reference points. Both techniques of the nonlinear least square adjustment either using the Gauss-Newton or Levenberg-Marquardt are applied in two 3D resection experiments. In both numerical methods, the results converged steadily to the global minimum using the proposed angular resection even with improper starting values. However, applying the Levenberg-Marquardt method proved to reach the global minimum solution in all the challenging situations and outperformed the Gauss-Newton method.

Applied Sciences

Soil organic matter (SOM) is an essential component of soil fertility that plays a vital role in ... more Soil organic matter (SOM) is an essential component of soil fertility that plays a vital role in the preservation of healthy ecosystems. This study aimed to produce an SOM-level map of the Batifa region in northern Iraq. Random forest (RF) and extreme gradient boosting (XGBoost) models were used to predict the SOM spatial distribution. A total of 96 soil samples were collected from the surface layer (0–30 cm) of both cropland and soil areas in Batifa. In addition, remote sensing data were obtained from Landsat 8, including bands 1–7, 10, and 11. Supplementary variables such as the normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), brightness index (BI), and digital elevation model (DEM) were employed as tools to predict SOM levels across the region. To evaluate the accuracy of the RF and XGBoost models in predicting SOM levels, statistical metrics, including mean absolute error (MAE), root mean square error (RMSE), and determination coefficient (R2...

Earth

Groundwater availability in the Zakho Basin faces significant challenges due to political issues,... more Groundwater availability in the Zakho Basin faces significant challenges due to political issues, border stream control, climate change, urbanization, land use changes, and poor administration, leading to declining groundwater quantity and quality. To address these issues, this study utilized the Analytic Hierarchy Process (AHP) and geospatial techniques to identify potential groundwater sites in Zakho. The study assigned weights normalized through the AHP eigenvector and created a final index using the weighted overlay method and specific criteria such as slope, flow accumulation, drainage density, lineament density, geology, well data, rainfall, and soil type. Validation through the receiver operating characteristic (ROC) curve (AUC = 0.849) and coefficient of determination (R2 = 0.81) demonstrated the model’s accuracy. The results showed that 17% of the area had the highest potential as a reliable groundwater source, 46% represented high-to-moderate potential zones, and 37% had l...

Earth and Environmental Sciences Library, 2022

Journal of Geoinformatics & Environmental Research, 2021

The concept of ecosystem service (ES) was originally developed to illustrate the benefits that na... more The concept of ecosystem service (ES) was originally developed to illustrate the benefits that natural ecosystems generate for society and to raise awareness for biodiversity and ecosystem conservation. In recent years, geographical information system (GIS) has become a powerful tool for mapping (ES) within a landscape, which visualizes spatial and temporal patterns and changes in ecosystems and their services.Mapping (ES) is necessary for the progress of strategies that will guarantee their future supply and to support the policies in a more effective way. The comprehensive literature review were conducted from international databases such as Elsevier, Springer, Wiley, and Google Scholar. We used the key terms including ‘mapping’, ‘maps’, ‘ES or ecosystem service, ‘ecosystem functions’, ‘landscape functions’, ‘evaluation of ES’, and ‘assessment of services’. in order to identify mapping ecosystem services and their challenges and opportunities. In total, 65 research papers were fou...

Applied Sciences

Convolutional neural networks (CNNs) have become a popular choice for various image classificatio... more Convolutional neural networks (CNNs) have become a popular choice for various image classification applications. However, the multi-layer perceptron mixer (MLP-Mixer) architecture has been proposed as a promising alternative, particularly for large datasets. Despite its advantages in handling large datasets and models, MLP-Mixer models have limitations when dealing with small datasets. This study aimed to quantify and evaluate the uncertainty associated with MLP-Mixer models for small datasets using Bayesian deep learning (BDL) methods to quantify uncertainty and compare the results to existing CNN models. In particular, we examined the use of variational inference and Monte Carlo dropout methods. The results indicated that BDL can improve the performance of MLP-Mixer models by 9.2 to 17.4% in term of accuracy across different mixer models. On the other hand, the results suggest that CNN models tend to have limited improvement or even decreased performance in some cases when using B...

Earth Science Informatics

Surveying and Geospatial Engineering Journal

The resection in 3D space is a common problem in surveying engineering and photogrammetry based o... more The resection in 3D space is a common problem in surveying engineering and photogrammetry based on observed distances, angles, and coordinates. This resection problem is nonlinear and comprises redundant observations which is normally solved using the least-squares method in an iterative approach. In this paper, we introduce a vigorous angular based resection method that converges to the global minimum even with very challenging starting values of the unknowns. The method is based on deriving oblique angles from the measured horizontal and vertical angles by solving spherical triangles. The derived oblique angles tightly connected the rays enclosed between the resection point and the reference points. Both techniques of the nonlinear least square adjustment either using the Gauss-Newton or Levenberg – Marquardt are applied in two 3D resection experiments. In both numerical methods, the results converged steadily to the global minimum using the proposed angular resection even with im...

Journal of Applied Science and Technology Trends, Mar 10, 2020

The rapidly and wide use of remote sensing and accurately obtain information on the spatiotempora... more The rapidly and wide use of remote sensing and accurately obtain information on the spatiotemporal distribution of large-scale vegetation is of great significance for improving and managing the Environment. To assess and analyze the spatiotemporal variation of vegetation status in Kurdistan Region of Iraq (KRGI), we used time series NDVI-based vegetation that are extracted from MOD13Q1 MODIS product over 20 years (2000-2019). The results showed that vegetation was mainly distributed in the northeast to southeast of the KRGI, while west region has less distributed and almost no vegetation. This is clearly remarkable in the southwest part of the region (Garmian administration). While, the most dominated vegetation province was Duhok province in KRGI during study period. There is a noticeable temporal variation in vegetation over a period of 20-year in the KRGI. The lower vegetated cover area is observed in the years 2000, 2008, and 2009. The increase/decrease of vegetated cover area is not only effected by climate conditions. The anthropogenic resource is also one of the main resources that has a major influence on the increase/decrease of vegetation.

AL-Rafidain Journal of Computer Sciences and Mathematics

In this paper, we provide a solution to the system of non-integer differential equation of order ... more In this paper, we provide a solution to the system of non-integer differential equation of order 0  q  1, by the technique of Laplace transformation and with interest to property of Mittag-Leffler function, with the help of the programming technique of Maple.

IOP Conference Series: Materials Science and Engineering

IOP Conference Series: Materials Science and Engineering

In recent years, advance oxidation processes (AOPs) have been widely interested for treatment of ... more In recent years, advance oxidation processes (AOPs) have been widely interested for treatment of industrial wastewater and organic matter. At among, Electrofenton has been proposed as a strong oxidative method. So, the aim of this work was purification of colored aqueous containing crystal violet by electrofenton process and steel mesh electrodes. All regents and methods were prepared from analytical grad and standard methods. The amounts of crystal violet were determined by colorimetric using a spectrophotometer at a maximum wavelength about 586 nm. The main parameters such as pH, applied current, dye concentration, reaction time and supporting electrolyte dose were investigated. Experimental data analysis was also performed using excel software. The results of this study showed that the better dye degradation is occurred in acidic pH (pH3), contact time of 5 minutes, initial concentration of crystal violet 50 mg/l, applied current 0.8 A and an electrolyte level about 0.1 g/L of Na...

PLOS ONE

Modern societies are exposed to a myriad of risks ranging from disease to natural hazards and tec... more Modern societies are exposed to a myriad of risks ranging from disease to natural hazards and technological disruptions. Exploring how the awareness of risk spreads and how it triggers a diffusion of coping strategies is prominent in the research agenda of various domains. It requires a deep understanding of how individuals perceive risks and communicate about the effectiveness of protective measures, highlighting learning and social interaction as the core mechanisms driving such processes. Methodological approaches that range from purely physics-based diffusion models to data-driven environmental methods rely on agentbased modeling to accommodate context-dependent learning and social interactions in a diffusion process. Mixing agent-based modeling with data-driven machine learning has become popularity. However, little attention has been paid to the role of intelligent learning in risk appraisal and protective decisions, whether used in an individual or a collective process. The differences between collective learning and individual learning have not been sufficiently explored in diffusion modeling in general and in agent-based models of socioenvironmental systems in particular. To address this research gap, we explored the implications of intelligent learning on the gradient from individual to collective learning, using an agent-based model enhanced by machine learning. Our simulation experiments showed that individual intelligent judgement about risks and the selection of coping strategies by groups with majority votes were outperformed by leader-based groups and even individuals deciding alone. Social interactions appeared essential for both individual learning and group learning. The choice of how to represent social learning in an agent-based model could be driven by existing cultural and social norms prevalent in a modeled society.

GeoInformatica

Machine learning (ML) algorithms steer agent decisions in agent-based models (ABMs), serving as a... more Machine learning (ML) algorithms steer agent decisions in agent-based models (ABMs), serving as a vehicle for implementing behaviour changes during simulation runs. However, when training an ML algorithm, obtaining large sets of micro-level human behaviour data is often problematic. Information on human behaviour is often collected via surveys of relatively small sample sizes. This paper presents a methodology for training a learning algorithm to guide agent behaviour in a spatial ABM using a limited survey data sample. We apply different implementation strategies using survey data and Bayesian networks (BNs). By being grounded in probabilistic directed graphical models, BNs stand out among other learning algorithms in that they can be based on expert knowledge and/or known datasets. This paper presents four alternative implementations of data-driven BNs to support agent decisions in a spatial ABM. We differentiate between training BNs prior to, or during the simulation runs, using only survey data or a combination of survey data and expert knowledge. The four different implementations are then illustrated using a spatial ABM of cholera diffusion for Kumasi, Ghana. The results indicate that a balance between expert knowledge and survey data provides the best control over the learning process of the agents and produces the most realistic agent behaviour.

International journal of health geographics, Mar 20, 2018

Millions of people worldwide are exposed to deadly infectious diseases on a regular basis. Breaki... more Millions of people worldwide are exposed to deadly infectious diseases on a regular basis. Breaking news of the Zika outbreak for instance, made it to the main media titles internationally. Perceiving disease risks motivate people to adapt their behavior toward a safer and more protective lifestyle. Computational science is instrumental in exploring patterns of disease spread emerging from many individual decisions and interactions among agents and their environment by means of agent-based models. Yet, current disease models rarely consider simulating dynamics in risk perception and its impact on the adaptive protective behavior. Social sciences offer insights into individual risk perception and corresponding protective actions, while machine learning provides algorithms and methods to capture these learning processes. This article presents an innovative approach to extend agent-based disease models by capturing behavioral aspects of decision-making in a risky context using machine ...

Biophysical parameter values such as LAI have proved useful in a number of environmental applicat... more Biophysical parameter values such as LAI have proved useful in a number of environmental applications. An approach is presented for producing the spatio-temporal estimation of leaf area index (LAI) of a heterogeneous forest using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images. This is performed by decomposing MODIS LAI for a heterogeneous forest using the Linear Mixture Model (LMM) and the information about the class fraction from an aerial image. Results showed that the decomposed MODIS LAI values were estimated well with maximum and minimum RMSE of 0.37, and 0.17, respectively. We concluded that our approach can be used to decompose MODIS LAI successfully for any heterogeneous forest.

Monitoring and analyzing forests and trees are required task to manage and establish a good plan ... more Monitoring and analyzing forests and trees are required task to manage and establish a good plan for the forest sustainability. To achieve such a task, information and data collection of the trees are requested. The fastest way and relatively low cost technique is by using satellite remote sensing. In this study, we proposed an approach to identify and map 15 tree species in the Mangish sub - district, Kurdistan region-Iraq. Image-objects (IOs) were used as the tree species mapping unit. This is achieved using the shadow index, normalized difference vegetation index and texture measurements. Four classification methods (Maximum Likelihood, Mahalanobis Distance, Neural Network, and Spectral Angel Mapper) were used to classify IOs using selected IO features derived from WV-2 imagery. Results showed that overall accuracy was increased 5-8% using the Neural Network method compared with other methods with a Kappa coefficient of 69%. This technique gives reasonable results of various tree...

Journal of applied science and technology trends, Jul 30, 2022

The concept of ecosystem service (ES) was originally developed to illustrate the benefits that na... more The concept of ecosystem service (ES) was originally developed to illustrate the benefits that natural ecosystems generate for society and to raise awareness for biodiversity and ecosystem conservation. In recent years, geographical information systems (GIS) have become a powerful tool for mapping (ES) within a landscape, which visualizes spatial and temporal patterns and changes in ecosystems and their services. Mapping (ES) is necessary for the progress of strategies that will guarantee their future supply and to support the policies in a more effective way. The comprehensive literature review was conducted using international databases such as Elsevier, Springer, Wiley, and Google Scholar. We used key terms including 'mapping', 'maps', 'ES or ecosystem service, 'ecosystem functions', 'landscape functions', 'evaluation of ES', and 'assessment of services'. To identify mapping ecosystem services and their challenges and opportunities. In total, 65 research papers were found first, of which 34 were selected for review. The most important challenges are insufficient generation of ES in the context of managed systems, the need to estimate associations among indicators of (ES) incomplete understanding of the nature of associations among services, and the lack of a general numerical outline to address these relations.

IEEE Access

The accurate quantification of surface soil moisture (SSM) and vegetation cover using remote sens... more The accurate quantification of surface soil moisture (SSM) and vegetation cover using remote sensing techniques is essential for effective environmental management. This study investigated the spatial variations in SSM and vegetation cover in the Batifa region of the Kurdistan Region of Iraq. Landsat-8 images of the study area were classified using a support vector machine (SVM), and the soil land type was subsequently extracted. A random forest (RF) algorithm was developed to retrieve SSM using Landsat data in conjunction with in situ measurements. The results demonstrated that the RF algorithm achieved a high coefficient of determination (R 2 = 0.80) for the SSM retrieval. The study area exhibited distinct distributions of SSM and normalized difference vegetation index (NDVI) values across different ranges. The low range of SSM (2.21%-3.34%) and NDVI (−0.020-0.172) values occupied approximately 25% of the soil area, whereas the moderate range of SSM (3.34%-4.05%) and NDVI (0.172-0.238) values covered approximately 50% of the soil area. A high range of SSM (4.05%-6.49%) and NDVI (0.238-0.935) values was found in approximately 25% of the region. The southern part of Batifa experienced drought conditions, whereas the northern part exhibited higher SSM levels. Anthropogenic resources caused a decrease in vegetation and SSM in Batifa. These findings have significant implications for sustainable management of water and soil resources in the Batifa area.

Iraqi geological journal, Sep 30, 2022

The temperature rise has become a serious environmental concern affected by both human and natura... more The temperature rise has become a serious environmental concern affected by both human and natural factors. Worldwide, rising land surface temperatures have emerged as the most pressing issue facing the twenty-first century. In the last two decades, a curious change was realized in temperature in the Duhok district of Iraq. Hence, this study examined the spatiotemporal land surface temperature distribution and Modified Soil Adjusted Vegetation Index (MSAVI2) and the correlation between them in the Duhok district in three different years 2001, 2011, and 2021 using Landsat satellite images. Air temperature data from seven weather stations were used to validate the land surface temperature results. The study's findings revealed that the Duhok district's LST has risen during the study period. In general, the average land surface temperature has been increasing at a rate of 0.15 °C per year. Other findings showed that the vegetation cover of the Duhok district has changed dynamically. In all three years of study, the regression analysis results indicated that there was a negative correlation between LST and MSAVI2. This method of evaluation will be useful in guiding future urban management work and local government strategies.

Journal of applied science and technology trends, Apr 2, 2022

The resection in 3D space is a common problem in surveying engineering and photogrammetry based o... more The resection in 3D space is a common problem in surveying engineering and photogrammetry based on observed distances, angles, and coordinates. This resection problem is nonlinear and comprises redundant observations which is normally solved using the least-squares method in an iterative approach. In this paper, we introduce a vigorous angular based resection method that converges to the global minimum even with very challenging starting values of the unknowns. The method is based on deriving oblique angles from the measured horizontal and vertical angles by solving spherical triangles. The derived oblique angles tightly connected the rays enclosed between the resection point and the reference points. Both techniques of the nonlinear least square adjustment either using the Gauss-Newton or Levenberg-Marquardt are applied in two 3D resection experiments. In both numerical methods, the results converged steadily to the global minimum using the proposed angular resection even with improper starting values. However, applying the Levenberg-Marquardt method proved to reach the global minimum solution in all the challenging situations and outperformed the Gauss-Newton method.

Applied Sciences

Soil organic matter (SOM) is an essential component of soil fertility that plays a vital role in ... more Soil organic matter (SOM) is an essential component of soil fertility that plays a vital role in the preservation of healthy ecosystems. This study aimed to produce an SOM-level map of the Batifa region in northern Iraq. Random forest (RF) and extreme gradient boosting (XGBoost) models were used to predict the SOM spatial distribution. A total of 96 soil samples were collected from the surface layer (0–30 cm) of both cropland and soil areas in Batifa. In addition, remote sensing data were obtained from Landsat 8, including bands 1–7, 10, and 11. Supplementary variables such as the normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), brightness index (BI), and digital elevation model (DEM) were employed as tools to predict SOM levels across the region. To evaluate the accuracy of the RF and XGBoost models in predicting SOM levels, statistical metrics, including mean absolute error (MAE), root mean square error (RMSE), and determination coefficient (R2...

Earth

Groundwater availability in the Zakho Basin faces significant challenges due to political issues,... more Groundwater availability in the Zakho Basin faces significant challenges due to political issues, border stream control, climate change, urbanization, land use changes, and poor administration, leading to declining groundwater quantity and quality. To address these issues, this study utilized the Analytic Hierarchy Process (AHP) and geospatial techniques to identify potential groundwater sites in Zakho. The study assigned weights normalized through the AHP eigenvector and created a final index using the weighted overlay method and specific criteria such as slope, flow accumulation, drainage density, lineament density, geology, well data, rainfall, and soil type. Validation through the receiver operating characteristic (ROC) curve (AUC = 0.849) and coefficient of determination (R2 = 0.81) demonstrated the model’s accuracy. The results showed that 17% of the area had the highest potential as a reliable groundwater source, 46% represented high-to-moderate potential zones, and 37% had l...

Earth and Environmental Sciences Library, 2022

Journal of Geoinformatics & Environmental Research, 2021

The concept of ecosystem service (ES) was originally developed to illustrate the benefits that na... more The concept of ecosystem service (ES) was originally developed to illustrate the benefits that natural ecosystems generate for society and to raise awareness for biodiversity and ecosystem conservation. In recent years, geographical information system (GIS) has become a powerful tool for mapping (ES) within a landscape, which visualizes spatial and temporal patterns and changes in ecosystems and their services.Mapping (ES) is necessary for the progress of strategies that will guarantee their future supply and to support the policies in a more effective way. The comprehensive literature review were conducted from international databases such as Elsevier, Springer, Wiley, and Google Scholar. We used the key terms including ‘mapping’, ‘maps’, ‘ES or ecosystem service, ‘ecosystem functions’, ‘landscape functions’, ‘evaluation of ES’, and ‘assessment of services’. in order to identify mapping ecosystem services and their challenges and opportunities. In total, 65 research papers were fou...

Applied Sciences

Convolutional neural networks (CNNs) have become a popular choice for various image classificatio... more Convolutional neural networks (CNNs) have become a popular choice for various image classification applications. However, the multi-layer perceptron mixer (MLP-Mixer) architecture has been proposed as a promising alternative, particularly for large datasets. Despite its advantages in handling large datasets and models, MLP-Mixer models have limitations when dealing with small datasets. This study aimed to quantify and evaluate the uncertainty associated with MLP-Mixer models for small datasets using Bayesian deep learning (BDL) methods to quantify uncertainty and compare the results to existing CNN models. In particular, we examined the use of variational inference and Monte Carlo dropout methods. The results indicated that BDL can improve the performance of MLP-Mixer models by 9.2 to 17.4% in term of accuracy across different mixer models. On the other hand, the results suggest that CNN models tend to have limited improvement or even decreased performance in some cases when using B...

Earth Science Informatics

Surveying and Geospatial Engineering Journal

The resection in 3D space is a common problem in surveying engineering and photogrammetry based o... more The resection in 3D space is a common problem in surveying engineering and photogrammetry based on observed distances, angles, and coordinates. This resection problem is nonlinear and comprises redundant observations which is normally solved using the least-squares method in an iterative approach. In this paper, we introduce a vigorous angular based resection method that converges to the global minimum even with very challenging starting values of the unknowns. The method is based on deriving oblique angles from the measured horizontal and vertical angles by solving spherical triangles. The derived oblique angles tightly connected the rays enclosed between the resection point and the reference points. Both techniques of the nonlinear least square adjustment either using the Gauss-Newton or Levenberg – Marquardt are applied in two 3D resection experiments. In both numerical methods, the results converged steadily to the global minimum using the proposed angular resection even with im...

Journal of Applied Science and Technology Trends, Mar 10, 2020

The rapidly and wide use of remote sensing and accurately obtain information on the spatiotempora... more The rapidly and wide use of remote sensing and accurately obtain information on the spatiotemporal distribution of large-scale vegetation is of great significance for improving and managing the Environment. To assess and analyze the spatiotemporal variation of vegetation status in Kurdistan Region of Iraq (KRGI), we used time series NDVI-based vegetation that are extracted from MOD13Q1 MODIS product over 20 years (2000-2019). The results showed that vegetation was mainly distributed in the northeast to southeast of the KRGI, while west region has less distributed and almost no vegetation. This is clearly remarkable in the southwest part of the region (Garmian administration). While, the most dominated vegetation province was Duhok province in KRGI during study period. There is a noticeable temporal variation in vegetation over a period of 20-year in the KRGI. The lower vegetated cover area is observed in the years 2000, 2008, and 2009. The increase/decrease of vegetated cover area is not only effected by climate conditions. The anthropogenic resource is also one of the main resources that has a major influence on the increase/decrease of vegetation.

AL-Rafidain Journal of Computer Sciences and Mathematics

In this paper, we provide a solution to the system of non-integer differential equation of order ... more In this paper, we provide a solution to the system of non-integer differential equation of order 0  q  1, by the technique of Laplace transformation and with interest to property of Mittag-Leffler function, with the help of the programming technique of Maple.

IOP Conference Series: Materials Science and Engineering

IOP Conference Series: Materials Science and Engineering

In recent years, advance oxidation processes (AOPs) have been widely interested for treatment of ... more In recent years, advance oxidation processes (AOPs) have been widely interested for treatment of industrial wastewater and organic matter. At among, Electrofenton has been proposed as a strong oxidative method. So, the aim of this work was purification of colored aqueous containing crystal violet by electrofenton process and steel mesh electrodes. All regents and methods were prepared from analytical grad and standard methods. The amounts of crystal violet were determined by colorimetric using a spectrophotometer at a maximum wavelength about 586 nm. The main parameters such as pH, applied current, dye concentration, reaction time and supporting electrolyte dose were investigated. Experimental data analysis was also performed using excel software. The results of this study showed that the better dye degradation is occurred in acidic pH (pH3), contact time of 5 minutes, initial concentration of crystal violet 50 mg/l, applied current 0.8 A and an electrolyte level about 0.1 g/L of Na...

PLOS ONE

Modern societies are exposed to a myriad of risks ranging from disease to natural hazards and tec... more Modern societies are exposed to a myriad of risks ranging from disease to natural hazards and technological disruptions. Exploring how the awareness of risk spreads and how it triggers a diffusion of coping strategies is prominent in the research agenda of various domains. It requires a deep understanding of how individuals perceive risks and communicate about the effectiveness of protective measures, highlighting learning and social interaction as the core mechanisms driving such processes. Methodological approaches that range from purely physics-based diffusion models to data-driven environmental methods rely on agentbased modeling to accommodate context-dependent learning and social interactions in a diffusion process. Mixing agent-based modeling with data-driven machine learning has become popularity. However, little attention has been paid to the role of intelligent learning in risk appraisal and protective decisions, whether used in an individual or a collective process. The differences between collective learning and individual learning have not been sufficiently explored in diffusion modeling in general and in agent-based models of socioenvironmental systems in particular. To address this research gap, we explored the implications of intelligent learning on the gradient from individual to collective learning, using an agent-based model enhanced by machine learning. Our simulation experiments showed that individual intelligent judgement about risks and the selection of coping strategies by groups with majority votes were outperformed by leader-based groups and even individuals deciding alone. Social interactions appeared essential for both individual learning and group learning. The choice of how to represent social learning in an agent-based model could be driven by existing cultural and social norms prevalent in a modeled society.

GeoInformatica

Machine learning (ML) algorithms steer agent decisions in agent-based models (ABMs), serving as a... more Machine learning (ML) algorithms steer agent decisions in agent-based models (ABMs), serving as a vehicle for implementing behaviour changes during simulation runs. However, when training an ML algorithm, obtaining large sets of micro-level human behaviour data is often problematic. Information on human behaviour is often collected via surveys of relatively small sample sizes. This paper presents a methodology for training a learning algorithm to guide agent behaviour in a spatial ABM using a limited survey data sample. We apply different implementation strategies using survey data and Bayesian networks (BNs). By being grounded in probabilistic directed graphical models, BNs stand out among other learning algorithms in that they can be based on expert knowledge and/or known datasets. This paper presents four alternative implementations of data-driven BNs to support agent decisions in a spatial ABM. We differentiate between training BNs prior to, or during the simulation runs, using only survey data or a combination of survey data and expert knowledge. The four different implementations are then illustrated using a spatial ABM of cholera diffusion for Kumasi, Ghana. The results indicate that a balance between expert knowledge and survey data provides the best control over the learning process of the agents and produces the most realistic agent behaviour.

International journal of health geographics, Mar 20, 2018

Millions of people worldwide are exposed to deadly infectious diseases on a regular basis. Breaki... more Millions of people worldwide are exposed to deadly infectious diseases on a regular basis. Breaking news of the Zika outbreak for instance, made it to the main media titles internationally. Perceiving disease risks motivate people to adapt their behavior toward a safer and more protective lifestyle. Computational science is instrumental in exploring patterns of disease spread emerging from many individual decisions and interactions among agents and their environment by means of agent-based models. Yet, current disease models rarely consider simulating dynamics in risk perception and its impact on the adaptive protective behavior. Social sciences offer insights into individual risk perception and corresponding protective actions, while machine learning provides algorithms and methods to capture these learning processes. This article presents an innovative approach to extend agent-based disease models by capturing behavioral aspects of decision-making in a risky context using machine ...

Biophysical parameter values such as LAI have proved useful in a number of environmental applicat... more Biophysical parameter values such as LAI have proved useful in a number of environmental applications. An approach is presented for producing the spatio-temporal estimation of leaf area index (LAI) of a heterogeneous forest using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images. This is performed by decomposing MODIS LAI for a heterogeneous forest using the Linear Mixture Model (LMM) and the information about the class fraction from an aerial image. Results showed that the decomposed MODIS LAI values were estimated well with maximum and minimum RMSE of 0.37, and 0.17, respectively. We concluded that our approach can be used to decompose MODIS LAI successfully for any heterogeneous forest.

Monitoring and analyzing forests and trees are required task to manage and establish a good plan ... more Monitoring and analyzing forests and trees are required task to manage and establish a good plan for the forest sustainability. To achieve such a task, information and data collection of the trees are requested. The fastest way and relatively low cost technique is by using satellite remote sensing. In this study, we proposed an approach to identify and map 15 tree species in the Mangish sub - district, Kurdistan region-Iraq. Image-objects (IOs) were used as the tree species mapping unit. This is achieved using the shadow index, normalized difference vegetation index and texture measurements. Four classification methods (Maximum Likelihood, Mahalanobis Distance, Neural Network, and Spectral Angel Mapper) were used to classify IOs using selected IO features derived from WV-2 imagery. Results showed that overall accuracy was increased 5-8% using the Neural Network method compared with other methods with a Kappa coefficient of 69%. This technique gives reasonable results of various tree...