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31.
  • Abbas, Nahla, et al. (författare)
  • Model-Based Assessment of Climate Change Impact on Isaac River Catchment, Queensland
  • 2016
  • Ingår i: Engineering. - 1947-3931 .- 1947-394X. ; 8:7, s. 460-470
  • Tidskriftsartikel (refereegranskat)abstract
    • Isaac River catchment, which is located within Fitzroy basin in Central Queensland, Australia is mostly a semi-arid region, sparsely populated, but rife with economic activities such as mining, grazing, cropping and production forestry. Hydro-meteorological data over the past several decades reveal that the catchment is experiencing increasing variability in precipitation and streamflow contributing to more severe droughts and floods supposedly due to climate change. The exposure of the economic activities in the catchment to the vagaries of nature and the possible impacts of climate change on the stream flow regime are to be analyzed. For the purpose, SWAT model was adopted to capture the dynamics of the catchment. During calibration of the model 12parameters were found to be significant which yielded a R2 value of 0.73 for calibration and 0.66 for validation. In the next stage, six GCMs from CMIP3 namely, CGCM3.1/T47, CNRM-CM3, GFDLCM2.1, IPSLCM4, MIROC3.2 (medres) and MRI CGCM2.3.2 were selected for climate change projections in the Fitzroy basin under a very high emissions scenario (A2), a medium emissions scenario(A1B) and a low emissions scenario (B1) for two future periods (2046-2064) and (2080-2100). All GCMs showed consistent increases in temperature, and as expected, highest rate for A2 and lowest rate for B1. Precipitation predictions were mixed-reductions in A2 and increases in A1B and B1, and more variations in distant future compared to near future. When the projected temperaturesand precipitation were inputted into the SWAT model, and the model outputs were compared with the baseline period (1980-2010), the picture that emerged depicted worsening water resources variability.
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32.
  • Abbas, Nahlah, et al. (författare)
  • Recent Trends and Long-Range Forecasts of Water Resources of Northeast Iraq and Climate Change Adaptation Measures
  • 2018
  • Ingår i: Water. - Switzerland : MDPI. - 2073-4441. ; 10:11, s. 1-19
  • Tidskriftsartikel (refereegranskat)abstract
    • Iraq has been experiencing water resources scarcity, and is vulnerable to climate change. Analysis of historical data revealed that the region is experiencing climate change to a degree higher than generally reported elsewhere. The relationship between climate change and its effect on water resources of a region has been sparsely addressed in published literature. To fill that gap this research work first investigates if there has been a significant change in climate in the region, which has been found to be true. In the next stage, the research projects future climatic scenarios of the region based on six oft-used General CirculationModel (GCM) ensembles, namely CCSM4, CSIRO-Mk3.6.0, GFDL-ESM2M, MEROC5, HadGEM2-ES, and IPSL-CM5A-LR. The relationship between climate change and its impact on water resources is explored through the application of the popular, widely used SWAT model. The model depicts the availability of water resources, classified separately as blue and green waters, for near and distant futures for the region. Some of the findings are foreboding and warrants urgent attention of planners and decision makers. According to model outputs, the region may experience precipitation reduction of about 12.6% and 21% in near (2049–2069) and distant (2080–2099) futures, respectively under RCP8.5. Those figures under RCP4.5 are 15% and 23.4%, respectively and under RCP2.6 are 12.2% and 18.4%, respectively. As a consequence, the blue water may experience decreases of about 22.6% and 40% under RCP8.5, 25.8% and 46% under RCP4.5, and 34.4% and 31% under RCP2.6 during the periods 2049–2069 and 2080–2099, respectively. Green water, by contrast, may reduce by about 10.6% and 19.6% under RCP8.5, by about 14.8% and 19.4% under RCP4.5, and by about 15.8% and 14.2% under RCP2.6 during the periods 2049–2069 and 2080–2099, respectively. The research further investigates how the population are adapting to already changed climates and how they are expected to cope in the future when the shift in climate is expected to be much greater.
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33.
  • Abbas, Nahla, et al. (författare)
  • The Impacts of Climate Change on Fitzroy River Basin, Queensland, Australia : The Impacts of Climate Change on Fitzroy River Basin, Queensland, Australia
  • 2017
  • Ingår i: Journal of Civil Engineering and Architecture. - USA : David Publishing Company. - 1934-7359 .- 1934-7367. ; 11:1, s. 38-47
  • Tidskriftsartikel (refereegranskat)abstract
    • An analysis of historical data of Fitzroy River, which lies in the east coast of Australia, reveals that there is an increasingtrend in extreme floods and droughts apparently attributable to increased variability of blue and green waters which could be due toclimate change. In order to get a better understanding of the impacts of climate change on the water resources of the study area for nearfuture as well as distant future, SWAT (soil and water assessment tool) model was applied. The model is first tested for its suitability incapturing the basin characteristics with available data, and then, forecasts from six GCMs (general circulation model) with abouthalf-a-century lead time to 2046~2064 and about one-century lead time to 2080~2100 are incorporated to evaluate the impacts ofclimate change under three marker emission scenarios: A2, A1B and B1. The results showed worsening water resources regime into thefuture.
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34.
  • Abbas, Nahla, et al. (författare)
  • Water resources problems of Iraq : Climate change adaptation and mitigation
  • 2018
  • Ingår i: Journal of Environmental Hydrology. - : International Association for Environmental Hydrology. - 1058-3912 .- 1996-7918. ; 26
  • Tidskriftsartikel (refereegranskat)abstract
    • Iraq is suffering from water scarcity, and future predictions indicate that it could get worse due to changing climate. Arguably, climate change is one of the greatest challenges onfronting this region it could have significant adverse effects on water resources and hence the environment and economy, particularly in the agricultural sector. This study considers possible adaptation and mitigation measures that could be undertaken in response to climate change. To overcome this problem,adaptation measures at farm and government level were conferred. Farm-level adaptation comprises adopting crop modification, soil conservation, irrigation, changing crop calendar and planting of trees. The government role is to ensure success of these adaptation measures. The government should get involved and support the farmers financially and technologically.
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35.
  • Abbas, Syed Adeel, et al. (författare)
  • Spinel-type Na2MoO4 and Na2WO4 as promising optoelectronic materials : First-principle DFT calculations
  • 2020
  • Ingår i: Chemical Physics. - : Elsevier. - 0301-0104 .- 1873-4421. ; 538
  • Tidskriftsartikel (refereegranskat)abstract
    • The mechanical, thermodynamic, electronic, and optical properties of Na2MoO4 (NMO) and Na2WO4 (NWO) spinels are elaborated by density functional theory (DFT) based full potential augmented plane wave method (FP-LAPW + lo). Our optimized lattice constants for the studied spinels are in good agreement with that obtained experimentally. The enthalpy of formation ensures the thermodynamic stability of NMO and NWO in the cubic phase. The Born mechanical stability criteria guarantees their mechanical stability, while Poisson ratio (ν) and Pugh's ratio (B/G) infer their brittle behavior. The Debye temperature (θD) is significant for NMO than NWO. The wide bandgap of 3.5 eV for NMO and 4.4 eV for NWO show the maximum absorption in the ultraviolet region that increases their importance for optoelectronic applications. The optical properties are explained in term of dielectric constant, refractive index, absorption of light, reflection, and optical loss factor.
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36.
  • Abbas, Zainab Dekan, et al. (författare)
  • Locating Dam Sites For Water Harvesting : Case Study Of Najaf Province, Iraq
  • 2019
  • Ingår i: Journal of Environmental Hydrology. - Canada : The International Association of Environmental Hydrology. - 1058-3912 .- 1996-7918. ; 27, s. 1-8
  • Tidskriftsartikel (refereegranskat)abstract
    • The Middle East is considered as an arid area. Iraq was an exception due to the presence of the Tigris  and  Euphrates  Rivers. After  1970,  the  flow  of  these  rivers  started  to  decrease  due  to  climate change  and  building  of  dams  in  the  upper  parts  of  the  catchments  of  the  rivers.  Now,  Iraq  is experiencing  water  shortage  problems.  Rain  water  harvesting  will  definitely  minimize  the  effect  of water shortage problems. In this research an arid area was selected (al Najaf) to find out the best sites for water harvesting using GIS techniques. The good agreement between the results from a simple GIS model  and  observations  in  cases  such  as  al  Najaf  Sea  is  indicating  a  promising  future  for  GIS application  in  hydrological  modeling.  The  present  study  proposed  a  function  formula  of  estimating suitable dam site using existing geographic information map such as the digital elevation maps. It is expected that it will save time, cost and work force. Finally, through the contour map of the study area, the lowest three elevation values at the governorate level were observed (20, 40, 60m). Based on these values, three possibilities were suggested to select the dam sites.
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37.
  • Abd-Ellah, Mahmoud Khaled, et al. (författare)
  • A Review on Brain Tumor Diagnosis from MRI Images : Practical Implications, Key Achievements, and Lessons Learned
  • 2019
  • Ingår i: Magnetic Resonance Imaging. - : Elsevier. - 0730-725X .- 1873-5894. ; 61, s. 300-318
  • Tidskriftsartikel (refereegranskat)abstract
    • The successful early diagnosis of brain tumors plays a major role in improving the treatment outcomes and thus improving patient survival. Manually evaluating the numerous magnetic resonance imaging (MRI) images produced routinely in the clinic is a difficult process. Thus, there is a crucial need for computer-aided methods with better accuracy for early tumor diagnosis. Computer-aided brain tumor diagnosis from MRI images consists of tumor detection, segmentation, and classification processes. Over the past few years, many studies have focused on traditional or classical machine learning techniques for brain tumor diagnosis. Recently, interest has developed in using deep learning techniques for diagnosing brain tumors with better accuracy and robustness. This study presents a comprehensive review of traditional machine learning techniques and evolving deep learning techniques for brain tumor diagnosis. This review paper identifies the key achievements reflected in the performance measurement metrics of the applied algorithms in the three diagnosis processes. In addition, this study discusses the key findings and draws attention to the lessons learned as a roadmap for future research.
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38.
  • Abd-Ellah, Mahmoud Khaled, et al. (författare)
  • Classification of Brain Tumor MRIs Using a Kernel Support Vector Machine
  • 2016
  • Ingår i: Building Sustainable Health Ecosystems. - : Springer International Publishing. - 9783319446714 - 9783319446721 ; , s. 151-160
  • Konferensbidrag (refereegranskat)abstract
    • The use of medical images has been continuously increasing, which makes manual investigations of every image a difficult task. This study focuses on classifying brain magnetic resonance images (MRIs) as normal, where a brain tumor is absent, or as abnormal, where a brain tumor is present. A hybrid intelligent system for automatic brain tumor detection and MRI classification is proposed. This system assists radiologists in interpreting the MRIs, improves the brain tumor diagnostic accuracy, and directs the focus toward the abnormal images only. The proposed computer-aided diagnosis (CAD) system consists of five steps: MRI preprocessing to remove the background noise, image segmentation by combining Otsu binarization and K-means clustering, feature extraction using the discrete wavelet transform (DWT) approach, and dimensionality reduction of the features by applying the principal component analysis (PCA) method. The major features were submitted to a kernel support vector machine (KSVM) for performing the MRI classification. The performance evaluation of the proposed system measured a maximum classification accuracy of 100 % using an available MRIs database. The processing time for all processes was recorded as 1.23 seconds. The obtained results have demonstrated the superiority of the proposed system.
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39.
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40.
  • Abd-Ellah, Mahmoud Khaled, et al. (författare)
  • Design and implementation of a computer-aided diagnosis system for brain tumor classification
  • 2017
  • Ingår i: 2016 28th International Conference on Microelectronics (ICM). - 9781509057214 ; , s. 73-76
  • Konferensbidrag (refereegranskat)abstract
    • Computer-aided diagnosis (CAD) systems have become very important for the medical diagnosis of brain tumors. The systems improve the diagnostic accuracy and reduce the required time. In this paper, a two-stage CAD system has been developed for automatic detection and classification of brain tumor through magnetic resonance images (MRIs). In the first stage, the system classifies brain tumor MRI into normal and abnormal images. In the second stage, the type of tumor is classified as benign (Noncancerous) or malignant (Cancerous) from the abnormal MRIs. The proposed CAD ensembles the following computational methods: MRI image segmentation by K-means clustering, feature extraction using discrete wavelet transform (DWT), feature reduction by applying principal component analysis (PCA). The two-stage classification has been conducted using a support vector machine (SVM). Performance evaluation of the proposed CAD has achieved promising results using a non-standard MRIs database.
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