| 1. |
- A., Trubetskaya, et al.
(författare)
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The Effect of Wood Composition and Supercritical CO2 Extraction on the Charcoal Production
- 2019
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Ingår i: 2019 AIChE Annual Meeting proceedings. - : American Institute of Chemical Engineers.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- This work demonstrated that the coupling of supercritical carbon dioxide extraction with slow pyrolysis is effective to remove over half of extractives from low quality wood and to generate biochar from remaining solid wood fractions. The high yields of extractives from supercritical carbon dioxide extraction illustrates the potential utilizing of low quality wood as an alternative feedstock for the sustainable production of value-added chemicals. Results showed that supercritical carbon dioxide extraction has neither a strong impact on the physical properties of original wood nor on the yield of solid biochar. These results are promising as they show that the biochar obtained for this renewable feedstock could be used as an alternative to fossil-based coke in applications including ferroalloy industries. Moreover, the heat treatment temperature and supercritical carbon dioxide extraction had a significant impact on the tar yields, leading to the increase in naphthalene, polycyclic aromatic hydrocarbons, aromatic and phenolic fractions with the greater temperature. The differences in gasification reactivity and dielectric properties of solid biochars, composition and yields of liquid products of non-treated pinewood and extracted wood fraction emphasize the impact of supercritical carbon dioxide extraction on the pyrolysis process.
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| 2. |
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| 3. |
- Abbas, Nahla, et al.
(författare)
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Flow Variation of the Major Tributaries of Tigris River Due to Climate Change
- 2019
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Ingår i: Engineering. - : Scientific Research Publishing. - 1947-3931 .- 1947-394X. ; 11:8, s. 437-442
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Tidskriftsartikel (refereegranskat)abstract
- Iraq relies greatly on the flow of the Euphrates and Tigris Rivers and their tributaries. Five tributaries namely Khabour, Greater Zab, Lesser Zab, AlAd- hiam and Daylia, which are the major tributaries of Tigris River, sustain Northern Iraq Region, a semi-arid, mainly a pastureland. These tributaries contribute about 24 km3 of water annually. The discharge in the tributaries, in recent times, has been suffering increasing variability contributing to more severe droughts and floods apparently due to climate change. This is because there were no dams constructed outside Iraq previously. For an appropriate appreciation, Soil Water Assessment Tool (SWAT) model was used to evaluate the impact of climate change on their discharge for a half-centennial lead time to 2046-2064 and a centennial lead time to 2080-2100. The suitability of the model was first evaluated, and then, outputs from six GCMs were incorporated to evaluate the impacts of climate change on water resources under three emission scenarios: A1B, A2 and B1. The results showed that wa-ter resources are expected to decrease with time.
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| 4. |
- Abbas, Zainab Dekan, et al.
(författare)
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Locating Dam Sites For Water Harvesting : Case Study Of Najaf Province, Iraq
- 2019
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Ingår i: Journal of Environmental Hydrology. - Canada : The International Association of Environmental Hydrology. - 1058-3912 .- 1996-7918. ; 27, s. 1-8
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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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| 5. |
- Abd-Ellah, Mahmoud Khaled, et al.
(författare)
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A Review on Brain Tumor Diagnosis from MRI Images : Practical Implications, Key Achievements, and Lessons Learned
- 2019
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Ingår i: Magnetic Resonance Imaging. - : Elsevier. - 0730-725X .- 1873-5894. ; 61, s. 300-318
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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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| 6. |
- Abd-Ellah, Mahmoud Khaled, et al.
(författare)
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Parallel Deep CNN Structure for Glioma Detection and Classification via Brain MRI Images
- 2019
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Ingår i: IEEE-ICM 2019 CAIRO-EGYPT. - : IEEE. ; , s. 304-307
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Although most brain tumor diagnosis studies have focused on tumor segmentation and localization operations, few studies have focused on tumor detection as a time- and effort-saving process. This study introduces a new network structure for accurate glioma tumor detection and classification using two parallel deep convolutional neural networks (PDCNNs). The proposed structure is designed to identify the presence and absence of a brain tumor in MRI images and classify the type of tumor images as high-grade gliomas (HGGs, i.e., glioblastomas) or low-grade gliomas (LGGs). The introduced PDCNNs structure takes advantage of both global and local features extracted from the two parallel stages. The proposed structure is not only accurate but also efficient, as the convolutional layers are more accurate because they learn spatial features, and they are efficient in the testing phase since they reduce the number of weights, which reduces the memory usage and runtime. Simulation experiments were accomplished using an MRI dataset extracted from the BraTS 2017 database. The obtained results show that the proposed parallel network structure outperforms other detection and classification methods in the literature.
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| 7. |
- Abd-Ellah, Mahmoud Khaled, et al.
(författare)
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TPUAR-Net : Two Parallel U-Net with Asymmetric Residual-Based Deep Convolutional Neural Network for Brain Tumor Segmentation
- 2019
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Ingår i: Image Analysis and Recognition. - Cham : Springer. ; , s. 106-116
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Konferensbidrag (refereegranskat)abstract
- The utilization of different types of brain images has been expanding, which makes manually examining each image a labor-intensive task. This study introduces a brain tumor segmentation method that uses two parallel U-Net with an asymmetric residual-based deep convolutional neural network (TPUAR-Net). The proposed method is customized to segment high and low grade glioblastomas identified from magnetic resonance imaging (MRI) data. Varieties of these tumors can appear anywhere in the brain and may have practically any shape, contrast, or size. Thus, this study used deep learning techniques based on adaptive, high-efficiency neural networks in the proposed model structure. In this paper, several high-performance models based on convolutional neural networks (CNNs) have been examined. The proposed TPUAR-Net capitalizes on different levels of global and local features in the upper and lower paths of the proposed model structure. In addition, the proposed method is configured to use the skip connection between layers and residual units to accelerate the training and testing processes. The TPUAR-Net model provides promising segmentation accuracy using MRI images from the BRATS 2017 database, while its parallelized architecture considerably improves the execution speed. The results obtained in terms of Dice, sensitivity, and specificity metrics demonstrate that TPUAR-Net outperforms other methods and achieves the state-of-the-art performance for brain tumor segmentation.
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| 8. |
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| 9. |
- Abdullah, Mukhalad, et al.
(författare)
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Water Resources Projects : Large Storage Dams
- 2019
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Ingår i: Journal of Earth Sciences and Geotechnical Engineering. - UK : Scientific Press International Limited. - 1792-9040 .- 1792-9660. ; 9:4, s. 109-135
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Tidskriftsartikel (refereegranskat)abstract
- Several dams were built on Tigris, Euphrates, and Tigris tributaries in Iraq. The construction of dams had been done in the second half of 20th century. Of the most critical issues confronting the large storage dams in Iraq are the liquefactions in Mosul Dam foundations, land sliding and earthquake effects in Darbandikhan Dam, and the essential maintenance and rehabilitation requirements almost for all the dams. Absolutely, large storage dams made Iraq surviving from thirst in several occasions. Unfortunately, after 2003, the attention or will are not exist pertaining the building of new or partially built large dams.
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| 10. |
- Abdullah, Mukhalad, et al.
(författare)
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Water Resources Projects in Iraq : Irrigation Projects on Euphrates
- 2019
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Ingår i: Journal of Earth Sciences and Geotechnical Engineering. - UK : Scientific Press International Limited. - 1792-9040 .- 1792-9660. ; 9:4, s. 169-199
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Tidskriftsartikel (refereegranskat)abstract
- Euphrates River is distinguished with long existing irrigation projects, which had been developed in the 20th century after centuries of deterioration. One of the major projects a long Euphrates inside Iraq is Great Abu Ghraib Project, which is the largest reclaimed area. Also, Great Musayab Project, Kifl-Shinafiyah Project and Shinafiyah-Nasiriya Project are other major projects. The most important for which Hindiyah Barrage had been built is Hilla Branch that supply many projects on both sides of this branch. Euphrates irrigation projects need a lot of investments to develop the status of the projects and confront the continuous decrease in water quality of the river.
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