HAZARD ASSESSMENT OF CURRENT STATE OF VEGETATION DEGRADATION USING GIS, A CASE STUDY: SADRA REGION, IRAN

Masoud Masoudi,E. AMIRI 한국생태학회 2013 Journal of Ecology and Environment Vol.36 No.1

The entire land of Southern Iran faces problems arising out of various types of land degradation of which vegetation degradation forms one of the major types. The present work introduces a model developed for assessing the current status of hazard of vegetation degradation using Geographic Information System (GIS). This kind of assessment differs from those assessments based on vulnerability or potential hazard assessments. The Sadra watershed which covers the upper reaches of Marharlu basin, Fars Province, has been chosen for a hazard assessment of this type of degradation. The different kinds of data for indicators of current status of vegetation degradation were gathered from collecting of field data and also records of the governmental offices of Iran. Taking into consideration three indicators of current status of vegetation degradation the model identifies areas with different hazard classes. By fixing the thresholds of severity classes of the three indicators including per cent of vegetation cover, biomass production and ratio of actual biomass to potential biomass production, a hazard map for each indicator was first prepared in GIS. The final hazard map of current status of vegetation degradation was prepared by intersecting three hazards in the GIS. Results show areas under severe hazard class have been found to be widespread (89 %) while areas under moderate and very severe hazard classes have been found less extensive in the Sadra watershed. The preparation of hazard maps based on the GIS analysis of these indicators will be helpful for prioritizing the areas to initiate remedial measures.

HAZARD ASSESSMENT OF CURRENT STATE OF VEGETATION DEGRADATION USING GIS, A CASE STUDY: SADRA REGION, IRAN

Masoudi, Masoud,Amiri, E. The Ecological Society of Korea 2013 Journal of Ecology and Environment Vol.36 No.1

The entire land of Southern Iran faces problems arising out of various types of land degradation of which vegetation degradation forms one of the major types. The present work introduces a model developed for assessing the current status of hazard of vegetation degradation using Geographic Information System (GIS). This kind of assessment differs from those assessments based on vulnerability or potential hazard assessments. The Sadra watershed which covers the upper reaches of Marharlu basin, Fars Province, has been chosen for a hazard assessment of this type of degradation. The different kinds of data for indicators of current status of vegetation degradation were gathered from collecting of field data and also records of the governmental offices of Iran. Taking into consideration three indicators of current status of vegetation degradation the model identifies areas with different hazard classes. By fixing the thresholds of severity classes of the three indicators including per cent of vegetation cover, biomass production and ratio of actual biomass to potential biomass production, a hazard map for each indicator was first prepared in GIS. The final hazard map of current status of vegetation degradation was prepared by intersecting three hazards in the GIS. Results show areas under severe hazard class have been found to be widespread (89 %) while areas under moderate and very severe hazard classes have been found less extensive in the Sadra watershed. The preparation of hazard maps based on the GIS analysis of these indicators will be helpful for prioritizing the areas to initiate remedial measures.

Computational fluid dynamics modeling of hydrogen production in an autothermal reactor: Effect of different thermal conditions

Sayed Reza Shabanian,Masoud Rahimi,Amin Amiri,Shahram Sharifnia,Ammar Abdulaziz Alsairafi,정재학,김우경 한국화학공학회 2012 Korean Journal of Chemical Engineering Vol.29 No.11

A numerical model was developed and validated to simulate and improve the reforming efficiency of methane to syngas (CO+H2) in an autothermal reactor. This work was undertaken in a 0.8 cm diameter and 30 cm length quartz tubular reactor. The exhaust gas from combustion at the bottom of reactor was passed over a Ru/γ-Al2O3 catalyst bed. The Eddy Dissipation Concept (EDC) model for turbulence-chemistry interaction in combination with a modified standard k-ε model for turbulence and a reaction mechanism with 23 species and 39 elementary reactions were considered in the combustion model. The pre-exponential factors and activation energy values for the catalyst (Ru) were obtained by using the experimental results. The percentage of difference between the predicted and measured mole fractions of the major species in the exhaust gas from combustion and catalyst bed zones was less than 5.02% and 7.73%,respectively. In addition, the results showed that the reforming efficiency, based on hydrogen yield, was increased with increase in catalyst bed’s thermal conductivity. Moreover, an enhancement of 4.34% in the reforming efficiency was obtained with increase in the catalyst bed wall heat flux from 0.5 to 2.0 kW/m2.

Optimizing Employment and Learning System Using Big Data and Knowledge Management Based on Deduction Graph

Behzad Maleki Vishkaei,Iraj Mahdavi,Nezam Mahdavi-Amiri,Masoud Askari 한국정보기술응용학회 2016 Journal of information technology applications & m Vol.23 No.3

In recent years, big data has usefully been deployed by organizations with the aim of getting a better prediction for the future. Moreover, knowledge management systems are being used by organizations to identify and create knowledge. Here, the output from analysis of big data and a knowledge management system are used to develop a new model with the goal of minimizing the cost of implementing new recognized processes including staff training, transferring and employment costs. Strategies are proposed from big data analysis and new processes are defined accordingly. The company requires various skills to execute the proposed processes. Organization’s current experts and their skills are known through a pre-established knowledge management system. After a gap analysis, managers can make decisions about the expert arrangement, training programs and employment to bridge the gap and accomplish their goals. Finally, deduction graph is used to analyze the model.

Converting of the 2D graphene to its 3D by chicken red blood cells as sheets separator for construction supercapacitor electrode

Jamshidi Fariba,Gholivand Mohammad-Bagher,Amiri Masoud 한국물리학회 2022 Current Applied Physics Vol.37 No.-

Here, we report on a facile green and scalable method for the fabrication of porous 3D graphene as a well-known carbon-based material used in many energy storage devices. Chicken red blood cells were used as sheets spacer and heteroatom sources in the construction of 3D graphene. First, the red blood cells were separated from the blood and mixed with graphene oxide. Then, the mixture was freeze-dried and carbonized at 700 ◦C. The resulted 3D graphene containing heteroatoms was used as a supercapacitor electrode modifier on a glassy carbon electrode and tested with various electrochemical techniques. The supercapacitor electrode showed a specific capacitance of 330 F g-1 at a current density of 1 A g-1, maximum power density of 1958 W kg-1, and maximum energy density of 85 Wh kg-1. Furthermore, the supercapacitive performances were tested in a two-electrode symmetrical system which exhibited a specific capacitance of 238 F g-1 for 1 A g-1. It also showed a power density of 2200 W kg-1 and an appreciable energy density of 160 Wh kg-1. The excellent electrochemical behavior of 3D graphene indicates the promising abilities of the composite for other applications such as biosensors, batteries, electrocatalysts, etc.

Optimizing Employment and Learning System Using Big Data and Knowledge Management Based on Deduction Graph

Vishkaei, Behzad Maleki,Mahdavi, Iraj,Mahdavi-Amiri, Nezam,Askari, Masoud Korea Data Strategy Society 2016 Journal of information technology applications & m Vol.23 No.3

In recent years, big data has usefully been deployed by organizations with the aim of getting a better prediction for the future. Moreover, knowledge management systems are being used by organizations to identify and create knowledge. Here, the output from analysis of big data and a knowledge management system are used to develop a new model with the goal of minimizing the cost of implementing new recognized processes including staff training, transferring and employment costs. Strategies are proposed from big data analysis and new processes are defined accordingly. The company requires various skills to execute the proposed processes. Organization's current experts and their skills are known through a pre-established knowledge management system. After a gap analysis, managers can make decisions about the expert arrangement, training programs and employment to bridge the gap and accomplish their goals. Finally, deduction graph is used to analyze the model.