Landfill Site Selection for Solid Waste Using GIS-based Multi-Criteria Spatial Modeling: TaqTaq Sub-district in Iraqi Kurdistan Region as a Case

This study gains insight into landfill sites with the observance of all the political, economic and environmental difficulties for the implementing appropriate site measures by adopting a collection of geospatial technique and weighted linear combination (WLC) in TqaTaq sub-district. In the current study, there are several areas determined as appropriate sites for landfill location. In this study, the criteria of distance from the roads, the city center, rivers, surface water, and land use map were used. According to this analysis, only 25.21% of the TaqTaq sub district is suitable for a landfill. Thus, basing on the findings, 20.93% of the concerned sub-district is regarded as least adequate site for this mission, whereas only 3.25% of the area is regarded as moderate suitable. Thus, this study has found out that 1.03% area is the most suitable. The majority of suitable area was located in the North of the Town, where waste production is more than other locations. It should be noted that based on the outcome of this study, the amount of waste produced in the TaqTaq Town for the next 10 years, from 2022 to 2032, is predicted to be about 4080 tons. According to the density calculated for the waste of this area and considering the height of 4 m for the landfill center, in the next 10 years, about 3000 m2 of land is required for the landfill location. Since the suitable area found in this research is about 15 hectares

Performance Analysis Of Neural Network Model For Automated Visual Inspection With Robotic Arm Controller System

The concept of Automated Visual Inspection (AVI) have emerged as a powerful platform for industrial machine vision where it used to inspect a large number of products rapidly.However,a major problem with this kind of application is the quality produced by the recognition process.In this paper,a system with the capability of identifying and categorizing a product based on image processing has been implemented.The image was processed by using Radial Basis Function (RBF) based on output center and spread values optimization.Robotic arm controller developed for pick and place the product based on their categories.Two performance measures are used to validate the model classification range and the spread values.The results of this project indicate that the model used able to identify the product and classify it according to their shape