| 1. |
- Ahsan, Amimul, et al.
(författare)
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Modeling of a new triangular shape solar distillation system integrated with solar PV panel and DC water heater
- 2023
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Ingår i: Case Studies in Thermal Engineering. - : Elsevier. - 2214-157X. ; 44
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Tidskriftsartikel (refereegranskat)abstract
- A new triangular shape solar distillation system is fabricated using locally available materials by integrating with solar PV panel connected to DC water heater. It is designed for the first time to distill saline water or seawater using solar heat energy directly (to heat sample water) and indirectly (through water heater to heat sample water). The trough is made of Plexiglass and painted in black color which is placed inside the triangular frame made of UPVC pipe. The performance of the still is experimented in field. The diurnal variations of solar heat energy, distillate output, various temperatures and relative humidity are observed. A few linear proportional relationships are obtained between the sunlight heat energy and the productivity, between the ambient temperature and the productivity, and between the productivity and water-cover temperature difference. The production rate of the still is higher than the conventional one. An improved simulation model is proposed to estimate the productivity of the still as some previous simulation models cannot estimate the productivity of the solar still precisely. A few new factors are incorporated in the new model as these factors affect the distillate output of the solar still.
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| 2. |
- Ehsan, Muhsan, et al.
(författare)
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Groundwater delineation for sustainable improvement and development aided by GIS, AHP, and MIF techniques
- 2024
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Ingår i: Applied water science. - : Springer Science and Business Media Deutschland GmbH. - 2190-5487 .- 2190-5495. ; 14:2
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Tidskriftsartikel (refereegranskat)abstract
- Exploration of groundwater is an integral part of viable resource growth for society, economy, and irrigation. However, uncontrolled utilization is mainly reported in urban and industries due to the increasing demand for water in semi-arid and arid regions of the world. In the background, groundwater demarcation for potential areas is vital in meeting necessary demand. The current study applied an integrated method comprising the analytical hierarchy process (AHP), multiple influence factors (MIF), combined with a linear regression curve and observatory well data for groundwater prospects mapping. Thematic maps such as flow direction, flow accumulation, elevation map, land use land cover, slope, soil texture, hill shade, geomorphology, normalized vegetation index, and groundwater depth map were generated utilizing remote sensing techniques. The relative weight of each parameter was estimated and then assigned to major and minor parameters. Potential zones for groundwater were classified into five classes, namely very good, good, moderate, poor, and very poor, based on AHP and MIF methods. A spatially explicit sensitivity and uncertainty analysis method to a GIS-based multi-criteria groundwater potential zone model is presented in this research. The study addressed a flaw in the way groundwater potential mapping results are typically presented in GIS-based multi-criteria decision analysis studies, where discrete class outputs are used without any assessment of their certainty with respect to variations in criteria weighting, which is one of the main contributors to output uncertainty. The study region is categorized based on inferred results as very poor, poor, marginal, and very good in potential ground quality 3.04 km2 is considered extremely poor, 3.33 km2 is considered poor, 64.42 km2 is considered very good, and 85.84 km2 is considered marginal zones, which shows reliable and potential implementation. The outcomes of AHP and MIF were validated by linear regression curve and actual water table in a study area. The study results help to formulate the potential demarcation of groundwater zones for future sustainable planning and development of groundwater sources. This study may be helpful to provide a cost-effective solution to water resources crises. The current study finding may be helpful for decision-makers and administrative professionals for sustainable management of groundwater resources for present and future demands.
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| 3. |
- Shahabi, Himan, et al.
(författare)
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Flood Detection and Susceptibility Mapping Using Sentinel-1 Remote Sensing Data and a Machine Learning Approach : Hybrid Intelligence of Bagging Ensemble Based on K-Nearest Neighbor Classifier
- 2020
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Ingår i: Remote Sensing. - Switzerland : MDPI. - 2072-4292. ; 12:2, s. 1-30
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Tidskriftsartikel (refereegranskat)abstract
- Mapping flood-prone areas is a key activity in flood disaster management. In this paper, we propose a new flood susceptibility mapping technique. We employ new ensemble models based on bagging as a meta-classifier and K-Nearest Neighbor (KNN) coarse, cosine, cubic, and weighted base classifiers to spatially forecast flooding in the Haraz watershed in northern Iran. We identified flood-prone areas using data from Sentinel-1 sensor. We then selected 10 conditioning factors to spatially predict floods and assess their predictive power using the Relief Attribute Evaluation (RFAE) method. Model validation was performed using two statistical error indices and the area under the curve (AUC). Our results show that the Bagging–Cubic–KNN ensemble model outperformed other ensemble models. It decreased the overfitting and variance problems in the training dataset and enhanced the prediction accuracy of the Cubic–KNN model (AUC=0.660). We therefore recommend that the Bagging–Cubic–KNN model be more widely applied for the sustainable management of flood-prone areas.
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| 4. |
- Abdullah, Gamil M. S., et al.
(författare)
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Boosting-based ensemble machine learning models for predicting unconfined compressive strength of geopolymer stabilized clayey soil
- 2024
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Ingår i: Scientific Reports. - : Springer Nature. - 2045-2322. ; 14:1
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Tidskriftsartikel (refereegranskat)abstract
- The present research employs new boosting-based ensemble machine learning models i.e., gradient boosting (GB) and adaptive boosting (AdaBoost) to predict the unconfined compressive strength (UCS) of geopolymer stabilized clayey soil. The GB and AdaBoost models were developed and validated using 270 clayey soil samples stabilized with geopolymer, with ground-granulated blast-furnace slag and fly ash as source materials and sodium hydroxide solution as alkali activator. The database was randomly divided into training (80%) and testing (20%) sets for model development and validation. Several performance metrics, including coefficient of determination (R2), mean absolute error (MAE), root mean square error (RMSE), and mean squared error (MSE), were utilized to assess the accuracy and reliability of the developed models. The statistical results of this research showed that the GB and AdaBoost are reliable models based on the obtained values of R2 (= 0.980, 0.975), MAE (= 0.585, 0.655), RMSE (= 0.969, 1.088), and MSE (= 0.940, 1.185) for the testing dataset, respectively compared to the widely used artificial neural network, random forest, extreme gradient boosting, multivariable regression, and multi-gen genetic programming based models. Furthermore, the sensitivity analysis result shows that ground-granulated blast-furnace slag content was the key parameter affecting the UCS.
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| 5. |
- Ahmad, Hafed Qasem, et al.
(författare)
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Assessment of Spatiotemporal Variability of Meteorological Droughts in Northern Iraq Using Satellite Rainfall Data
- 2021
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Ingår i: KSCE Journal of Civil Engineering. - : Korean Society Of Civil Engineers-KSCE. - 1226-7988 .- 1976-3808. ; 25:11, s. 4481-4493
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Tidskriftsartikel (refereegranskat)abstract
- The absence of a dense rainfall monitoring network and longer period data are the major hindrances of hydroclimatic study in arid and semi-arid regions. An attempt has been made for the evaluation of spatiotemporal changes in droughts at the northern semi-arid region of Iraq for the period 1981-2018 using high-resolution (0.05 degrees) precipitation data of Climate Hazards Group Infrared Precipitation with Stations (CHIRPS). The performance of CHIRPS in replicating rainfall and Standard Precipitation Index (SPI) for different timescales at eleven locations for the available period of observation data (2000-2014) was evaluated. The SPI was also used to estimate drought frequency and evaluate drought trends at all the CHIRPS grid points. A modified version of the non-parametric Mann-Kendall (MK) test was employed for a robust evaluation of the spatial distribution of temporal trends in droughts. The results showed a good ability of CHIRPS in reconstructing observed SPI with a correlation coefficient ranged from 0.64 to 0.87, BIAS between 1.05 and 1.81, Nash-Sutcliff efficiency from 0.39 to 0.55, and Willmott Index between 0.67 and 0.79. The CHIRPS also able to reconstruct the time series and probability distribution of observed SPI reasonably. Spatial distribution of droughts revealed a higher frequency of droughts of all categories and timescales in the east and north of Northern Iraq, mainly due to high rainfall variance. The MK test revealed a reduction in 6- and 12-month droughts in the northwest and an intensification at a few northeastern grids. It indicates droughts became more recurrent in the already drought-prone region and lessened in a less drought-prone region.
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| 6. |
- Ghadhban Al-Maliki, Hadi Naser, et al.
(författare)
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Nonlinear Simulation Analysis of Tapered Reinforced Concrete Column (Solid and Hollow) Behavior Under Axial Load
- 2021
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Ingår i: International Journal of GEOMATE. - : The Geomate International Society. - 2186-2982 .- 2186-2990. ; 21:86, s. 131-146
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Tidskriftsartikel (refereegranskat)abstract
- Tapered columns are a type of column that is used for different purposes, including architectural purposes or structural needs to take into account the changes that occur to moments along with the height of the column. For example, in highway bridges, tapered columns are used to reduce the number of moments transmitted to the base of the columns and from there to the foundation. This research studied the analysis of short reinforced concrete columns with variable cross-sections along the column in a linear manner by using the ANSYS V.15 software package. The variables that were studied included the type of section, solid or hollow, the ratio of longitudinal and transverse reinforcement, the ratio of the hollowness, and the comparison of numerical results with those obtained from the previous study. The results we obtained from the simulation of the numerical analysis of the models showed a very good agreement with the results of the experimental studies for them. This agreement can also be observed through statistical analysis using the arithmetic mean and standard deviation when compared. Thus, the proposed model by numerical analysis and hypotheses is suitable for formulating the behavior of these reinforced concrete tapered column models under the effect of axially applied load and other variables. The behavior of column models is based on applied loads, load-displacement curves, crack patterns, and failure modes. The results showed that increasing the ratio of longitudinal and transverse reinforcement increases the resistance of the R.C. column models and the ductility index with a decrease in the corresponding lateral displacement. This behavior is observed when changing the section from hollow to solid. Finally cracks pattern is represented in the concrete crushing and concrete spalling out of some parts at the end of the tapered and diagonal cracks in different places, especially at the end of the tapered.
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| 7. |
- Moulavi, M. Amir, et al.
(författare)
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State-Space Feedback Control for Elastic Distributed Storage in a Cloud Environment
- 2012
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Ingår i: ICAS 2012. - St. Maarten, Netherlands Antilles. - 9781612081878 ; , s. 589-596
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Konferensbidrag (refereegranskat)abstract
- Elasticity in Cloud computing is an ability of asystem to scale up and down (request and release resources) in response to changes in its environment and workload. Elasticity can be achieved manually or automatically. Efforts arebeing made to automate elasticity in order to improve system performance under dynamic workloads. In this paper, we reportour experience in designing an elasticity controller for a key-value storage service deployed in a Cloud environment. To design our controller, we have adopted a control theoretic approach. Automation of elasticity is achieved by providing a feedback controller that automatically increases and decreases the number of nodes in order to meet service level objectives under high load and to reduce costs under low load. Every step in the building of a controller for elastic storage, includingsystem identification and controller design, is discussed. We have evaluated our approach by using simulation. We have developed a simulation framework EStoreSim in order to simulate anelastic key-value store in a Cloud environment and be able to experiment with different controllers. We have examined the implemented controller against specific service level objectives and evaluated the controller behavior in different scenarios. Our simulation experiments have shown the feasibility of our approach to automate elasticity of storage services using state-space feedback control.
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