This research aims to distinguish the reef environment from the non-reef environment. The Oligocene-Miocene-succussion in western Iraq was selected as a case study, represented by the reefal limestone facies of the Anah Formation (Late Oligocene) deposited in reef-back reef environments, dolomitic limestone of the Euphrates Formation (Early Miocene) deposited in open sea environments, and gypsiferous marly limestone of the Fatha Formation (Middle Miocene) deposited in a lagoonal environment. The content of the rare earth elements (REEs) (La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Er, Ho, Tm, Yb, Lu, and Y) in reef facies appear to be much lower than of those in the non-reef facies. The open sea facies have a low content of REEs due to bein

Accurate emotion categorization is an important and challenging task in computer vision and image processing fields. Facial emotion recognition system implies three important stages: Prep-processing and face area allocation, feature extraction and classification. In this study a new system based on geometric features (distances and angles) set derived from the basic facial components such as eyes, eyebrows and mouth using analytical geometry calculations. For classification stage feed forward neural network classifier is used. For evaluation purpose the Standard database "JAFFE" have been used as test material; it holds face samples for seven basic emotions. The results of conducted tests indicate that the use of suggested distances, angles

In this paper we present a method to analyze five types with fifteen wavelet families for eighteen different EMG signals. A comparison study is also given to show performance of various families after modifying the results with back propagation Neural Network. This is actually will help the researchers with the first step of EMG analysis. Huge sets of results (more than 100 sets) are proposed and then classified to be discussed and reach the final.

The objective of all planning research is to plan for human comfort and safety, and one of the most significant natural dangers to which humans are exposed is earthquake risk; therefore, earthquake risks must be anticipated, and with the advancement of global technology, it is possible to obtain information on earthquake hazards. GIS has been utilized extensively in the field of environmental assessment research due to its high potential, and GIS is a crucial application in seismic risk assessment. This paper examines the methodologies used in recent GIS-based seismic risk studies, their primary environmental impacts on urban areas, and the complexity of the relationship between the applied methodological approaches and the resulting env

This study was focused on biotreatment of soil which polluted by petroleum compounds (Diesel) which caused serious environmental problems. One of the most effective and promising ways to treat diesel-contaminated soil is bioremediation. It is a choice that offers the potential to destroy harmful pollutants using biological activity. The capability of mixed bacterial culture was examined to remediate the diesel-contaminated soil in bio piling system. For fast ex-situ treatment of diesel-contaminated soils, the bio pile system was selected. Two pilot scale bio piles (25 kg soil each) were constructed containing soils contaminated with approximately 2140 mg/kg total petroleum hydrocarbons (TPHs). The amended soil:

Most of the known cases of strong gravitational lensing involve multiple imaging of an active galactic nucleus. The properties of lensed active galactic nuclei make them promising systems for astrophysical applications of gravitational lensing. So we present a simple model for strong lensing in the gravitational lensed systems to calculate the age of four lensed galaxies, in the present work we take the freedman models with (k curvature index =0) Euclidian case, and the result show a good agreement with the other models.

In the present work, pattern recognition is carried out by the contrast and relative variance of clouds. The K-mean clustering process is then applied to classify the cloud type; also, texture analysis being adopted to extract the textural features and using them in cloud classification process. The test image used in the classification process is the Meteosat-7 image for the D3 region.The K-mean method is adopted as an unsupervised classification. This method depends on the initial chosen seeds of cluster. Since, the initial seeds are chosen randomly, the user supply a set of means, or cluster centers in the n-dimensional space.The K-mean cluster has been applied on two bands (IR2 band) and (water vapour band).The textural analysis is used