Untreated municipal solid waste (MSW) release onto land is prevalent in developing countries. To reduce the high levels of harmful components in polluted soils, a proper evaluation of heavy metal concentrations in Erbil's Kani Qrzhala dump between August 2021 and February 2022 is required. The purpose of this research was to examine the impact of improper solid waste disposal on soil properties within a landfill by assessing the risks of contamination for eight heavy elements in two separate layers of the soil by using geoaccumulation index (I-geo) and pollution load index (PLI) supported. The ArcGIS software was employed to map the spatial distribution of heavy element pollution and potential ecological risks. The I-geo values in summe

Spatial Intelligence is a mental ability to understand and solve real-world problems. These visual-spatial representations are fundamental in learning various "STEM" topics, like digital drawing, art presentations, creating graphical representations, 2D designs. Opportunity to interact with real and/or virtual objects. It is a good opportunity in applying new techniques such as the augmenter, which is able to clarify mathematical tables, concepts and generalizations greatly to the visualization, understanding and mastery of concepts mathematically. The purpose of the research is to investigate impact of using AR technology in developing spatial intelligence for secondary school students, Baghdad. The quasi-experimental design was us

Objectives Dental implant is a revolution in dentistry; some shortages are still a focus of research. This study use long duration of radiofrequency (RF)–magnetron sputtering to coat titanium (Ti) implant with hydroxyapatite (HA) to obtain a uniform, strongly adhered in a few micrometers in thickness. Materials and Methods Two types of substrates, discs and root form cylinders were prepared using a grade 1 commercially pure (CP) Ti rod. A RF–magnetron sputtering device was used to coat specimens with HA. Magnetron sputtering was set at 150 W for 22 hours at 100°C under continuous argon gas flow and substrate rotation at 10 rpm. Coat properties were evaluated via field emission scanning electron microscopy (FESEM), scanning electro

This search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as com

This search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as

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

The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm