2020-01

4th International Conference on Buildings, Construction and Environmental Engineering

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 NaCl. Higher electrical current and lower pHs were caused to generate the higher amount of oxidative radical and regeneration of Fe2+. Under optimal condition, crystal violet was removed around 99.72%. Referring to the results, it can be concluded that the electrofenton is a suitable in situ hydrogen peroxide generation technology for treatment of colored wastewater.

2020-01

4th International Conference on Buildings, Construction and Environmental Engineering

The aim of this systematic review study was to provide a precise estimation and awareness of the remaining organophosphorus pesticides in global soil and sediments. To do so, both international and national databases of PubMed, Scopus and the Institute for Scientific Information, Scientific Information Database, Iranmedex and Magiran scientific were searched/used to find studies published from 1968 to 2017. Next, the following keywords in English and Persian were used including: "organophosphorous" or "organo-phosphorous" or "organophosphate" with or without "pesticide" or "toxicity"; "soil" or "topsoil". Based on our systematic search, a total number of 15 articles were chosen and used to analysis. Most studies have been conducted in Asian countries and some part of Africa and commonly used organophosphorous pesticides included chloroprifous, dichlorvos, diazinon, fenitrothion, malathion and profenofos. On the other hand, personal interviews showed that chloroprifous, dicrotophos and profenofos are more used widely in the world. Random effects model to estimate the overall amounts of the residue organophosphorus pesticides in global soil was used. Accordingly, the overall concentration of organophosphorus pesticides was estimated to be 131.05 mg/kg (95%CI, 130.98–131.12).

2019-05

2019 International Conference on Advanced Science and Engineering (ICOASE)

Past and current status of the land is significant for productive environmental management. This can especially be observable in regions that are affected by climate variability and human activities such as Zakho district. The present study illustrates the spatio-temporal dynamics of land use/cover (LUC) in Zakho district, Kurdistan Region-Iraq. Moreover, an attempt is made to predict LUC of the study area for year 2050. Landsat satellite imageries of two different time periods, i.e., Landsat Thematic Mapper (TM) of 1989 and Landsat Operational Land Imager (OLI) of 2014 were acquired and the changes in Zakho over a period of 25 years were quantified. Maximum Likelihood Algorithm is used to classify the satellite image. The satellite images were classified into 8 classes namely dense forest, sparse forest, grass, rock, soil, crop, built-up and water body. The results showed that during the last 25 years, build-up land has been increased from 9 km2 (1989) to 47 km2 (2014). Crops, rocks and water body lands have been increased as well by about 97 km2 , 16 km2 , and 4 km2 respectively. In other hand, dense forest, spare forest, grass and soil lands have been decreased by 93 km 2 , 9 km2 , 52 km2 , and 1 km2 , respectively. In addition, the major transformed LUC for the year 2050 was soil by 0.9, and followed by the grass by 0.78. This study concluded that change in Zakho district land happened in a negative trend in regarding natural environment.

2018-12

2018 IEEE 14th International Conference on e-Science (e-Science)

Epidemics have always been a source of concern to people, both at the individual and government level. To fight outbreaks effectively, we need advanced tools that enable us to understand the factors that influence the spread of life-threatening diseases.

2018-10

2018 International Conference on Advanced Science and Engineering (ICOASE)

Surface Water area (SWA) extraction is an important part of water resource management and has been the hottest topic in the remote sensing of water resource sector for over two decades. An approach is presented to estimate the change of area of surface water over 15 year period (2003 - 2018) using a time series of Landsat images. Twelve Landsat scenes were used to spatially and temporally cover Duhok Governorate, Kurdistan region-Iraq. A modified normalized different water index (MNDWI) were employed to quantitatively estimate the SWA and coincidently analyzed with the temporal change of precipitation and temperature data. Results show that the considerable decrement of SWA is observed from 2003 to 2008 with reduction of 51%. This is also was confirmed by metrological used data. Moreover, an increment of SWA is noticed from 2008 to 2013. However, a slight increment was realized between 2013 and 2018. In addition, during the studied period a climate conditions (temperature and precipitation) in Duhok Governorate have been changed significantly. These changes could have affected the SWA, but so also could external human interference.

2018-10

2018 International Conference on Advanced Science and Engineering (ICOASE)

Biomass estimation is a tool for assessing the amount of carbon stores in trees. An approach is presented to estimate aboveground biomass (AGB) of the scattered individual Quercus aegilops using very high resolution satellite imagery, WorldView-3 (WV3). First, an in-situ allometric model at tree level was developed, and AGB was estimated using the Diameter at Breast Height (DBH). Next, the allometric relationship between Tree Crown Area (TCA) derived from WV3 data and estimated in-situ AGB was investigated and used in the resulting model to estimate AGB (remote sensing derived). As a result, the developed allometric model in-situ produced a correlation of R 2 = 0.99, and the developed allometric model remote sensing produced a correlation of R 2 = 0.94. Tree AGB estimated from WV3 data was a good technique with a 1.24 bias and a root mean square error (RMSE) of 80.17. This approach can be used to accurately estimate and map AGB of scattered individual trees.

2017-09

2017 International Conference on GeoComputation, GeoComputation 2017

An increasing number of spatial agent based models (ABMs) use artificial intelligence to enhance agents’ decisions. There is a difference between ABMs with pure social intelligence based on information exchange among agents and ABMs with integrated spatial intelligence. Spatial intelligence refers to the fact that agents sense their environment, perform a judgement on the condition of this environment, and change their behaviour based on this judgement. When spatial intelligence is used in ABMs, it often facilitates navigation (human or animal) or adaptation to land cover change. Less implementations are available for assessing risky situation engaging agents’ risk perception. In this paper, we present a model that uses a combination of spatial and social intelligence to simulate disease diffusion. Agents evaluate changes in floating plastic debris in a river combined with personal information and media attention on cholera to decide which water source to use. Cognition of agents with respect to perceiving risk and acting upon it is implemented via two Bayesian Networks. Modelling results are compared with data collected during a Massive Open Online Course. Results of the ABM show a strong decline of the number of disease cases after implementation of artificial intelligence. Results from the survey confirm the fact that people judge quality of water visually, but also show the strong influence of communication on risk perception.

2016-07

International Environmental Modelling and Software Society (iEMSs), 8th International Congress on Environmental Modelling and Software

Agent-­Based Models (ABMs) are indispensable to studying the aggregated impacts of individual actions of heterogeneous interacting adaptive agents. Concurrently, artificial intelligence has been employed for decades to simulate autonomous actions of individual entities that react, learn and exchange information with an environment and one another. There are obvious synergies between the two computational approaches. For example, artificial intelligence is often used to enhance agents’ behaviour in ABMs. Artificial intelligence learning algorithms (AILAs) allow for a richer agents’ architecture for operationalization of more realistic learning decisions beyond a simplistic treatment of agents’ cognitive and sensory capacities. Firstly, we review recent socio-­economic and spatial ABMs that employ different AILAs to create individually, socially and spatially intelligent agents. We provide a systematic structured analysis of the types of AILAs employed in various application domains, their specific operationalization in an agent’s decision-­making for various tasks, treatment of spatial and social environment in the design of AILAs, and the level of empirical information used in ABM. We highlights the trends in the current practice of AILAs used to enhance ABMs, which social simulation modellers may rely on when designing their ABM simulations. Secondly, we present an example of a spatial agent based model where agents rely on both information from their spatial landscape and water quality in the local watershed as well as on the comprehensive risk assessment. We compare the performance of the model using simplified decision making on the agent level vs. agents enhanced with an artificial intelligence learning.

2015-09

Social simulation 2015, Groningen, Netherlands

Over the years a range of spatial agent-based models (ABMs) have been developed to simulate a wide variety of disease diffusion processes. However, most models: (a) Are based on simple (rule-based) agent behaviour unable to capture the change of behaviour during a developing epidemic due to e.g. increasing risk awareness; (b) Do not model explicitly behaviour change as a result of media attention and increasing risk awareness; (c) Include individual decision making and social interaction but no group behaviour; (d) Only include social intelligence but lack the element of “spatial intelligence” by: exploring how the introduction of cognitively-rich agents perceiving risks (and potentially acting upon them) impacts the spread and prevention of a disease.

2014-09

SPIE 9239, Remote Sensing for Agriculture, Ecosystems, and Hydrology XVI, Amsterdam, Netherlands

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 WorldView-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 species classifications by means of applying the Neural Network method with IOs techniques on WorldView-2 imagery.

2014-05

First Geographic Conference, Duhok, Kurdistan region-Iraq

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2013-12

First International Symposium on Urban Development, Erbil, Kurdistan region-Iraq

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2012-11

2nd International conference on Climate Change & Social Issues, Kuala Lumpur, Malaysia

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2012-03

ASPRS 2012 annual conference: Imaging and geospatial technologies into the future, Sacramento, USA

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2011-05

ASPRS 2011 annual conference: Ride on the geospatial revolution, Milwaukee, USA

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2011-03

Spatial Statistics 2011 conference: Mapping Global Change, Enschede, The Netherlands

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