Urban expansion and its environmental and safety effects are one of the critical information needed for future development planning, safety considerations and environmental management. This work used two methods to monitor urban expansion and it's environmental and safety effects, the first is based on Google Maps for the years 2002 and 2010, and the second was the usage of spatial videos for the year 2013. Although the usage of satellite images is critical to know and investigate the general situation and the total effects of the expansion on a large piece of area, but the Spatial videos do a very detailed fine scale investigation, site conditions regarding both environmental and safety cannot be easily distinguished fr

      The Matching and Mosaic of the satellite imagery play an essential role in many remote sensing and image processing projects. These techniques must be required in a particular step in the project, such as remotely change detection applications and the study of large regions of interest. The matching and mosaic methods depend on many image parameters such as pixel values in the two or more images, projection system associated with the header files, and spatial resolutions, where many of these methods construct the matching and mosaic manually. In this research, georeference techniques were used to overcome the image matching task in semi automotive method. The decision about the quality of the technique can be considered i

Kidney tumors are of different types having different characteristics and also remain challenging in the field of biomedicine. It becomes very important to detect the tumor and classify it at the early stage so that appropriate treatment can be planned. Accurate estimation of kidney tumor volume is essential for clinical diagnoses and therapeutic decisions related to renal diseases. The main objective of this research is to use the Computer-Aided Diagnosis (CAD) algorithms to help the early detection of kidney tumors that addresses the challenges of accurate kidney tumor volume estimation caused by extensive variations in kidney shape, size and orientation across subjects.
In this paper, have tried to implement an automated segmentati

Heavy metal (HM) pollution has long been a significant source of environmental deterioration and a problem for the safety of food. Iraqis prefer rice over any other food, and since heavy metals have a direct impact on health, their traces in rice have drawn particular attention. Before cooking rice, it is usual in Iraq to wash and soak it. Some 55 varieties of imported and local rice were sampled from Erbil city markets in 2022 with the aim of determining the concentration of As, Cd, Cr, Ni and Pb before and after soaking. Standard procedure of acid digestions was applied on the raw and soaked samples. The solutions were analyzed using ICPE-9820 Shimadzu. The mean concentrations of As, Cd, Cr, Ni and Pb (in mg/kg) in the rice samples bef

Given the importance of possessing the digital competence (DC) required by the technological age, whether for teachers or students and even communities and governments, educational institutions in most countries have sought to benefit from modern technologies brought about by the technological revolution in developing learning and teaching and using modern technologies in providing educational services to learners. Since university students will have the doors to work opened in all fields, the research aims to know their level of DC in artificial intelligence (AI) applications and systems utilizing machine learning (ML) techniques. The descriptive approach was used, as the research community consisted of students from the University

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

Thep resent study was conducted for monitoring of the evaporative cooling tower in methanol production plant using digital computer' visuql Basic computer program was used for the monitoring of the performance of the cooling tower. The structure program consists of sub programs and forms to show all the related variabltes such as temperature, flow rate, pressure ...etc, that affect the cooling tower operation and give alarms and important function informition regarding these variables.