This research aims at studying each of the cold and hot thermal wavelengths affecting
Iraq for a minimum climatic course of 11 years beginning from 1992 till 2002. Three stations
were selected including the parts of Iraq surface: Mosul, Baghdad and Basrah.
The wave days were also connected with the related climatic elements represented by
the wind direction and speeds and the relative humidity. It was shown that Iraq is affected by
the rates of hot thermal wave lengths greatly compared to the rates of cold wavelengths. The
results suggested that the highest rate of hot and cold wavelengths recorded over Basra station
was (3.5) days for the cold and (5) days for the hot. While the lowest rates was at Mosul
station

Anticyclone of synoptic studies that influence weather and climate of Iraq, The aim of
the study is to clarify the effect variation of repetition of Anticyclone and effect on thermal
characteristic in Iraq were pressure level has been analyzed (1000) millibars and that because
of pressure level is the closet to the earth surface and the clarity of climatic phenomenon
based on a systematic analysis of synoptic seeking maps and observation and (12:00)
according to timing GMT for five climatic stations which is (Mosul, Kirkuk, Baghdad, Rutba,
and Basra) and so far three consecutive climatic cycles which is first climatic cycle for period
(1986-1976). and second climatic cycle for period (1997-1987) and third climatic cy

In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

In this article, the high accuracy and effectiveness of forecasting global gold prices are verified using a hybrid machine learning algorithm incorporating an Adaptive Neuro-Fuzzy Inference System (ANFIS) model with Particle Swarm Optimization (PSO) and Gray Wolf Optimizer (GWO). The hybrid approach had successes that enabled it to be a good strategy for practical use. The ARIMA-ANFIS hybrid methodology was used to forecast global gold prices. The ARIMA model is implemented on real data, and then its nonlinear residuals are predicted by ANFIS, ANFIS-PSO, and ANFIS-GWO. The results indicate that hybrid models improve the accuracy of single ARIMA and ANFIS models in forecasting. Finally, a comparison was made between the hybrid foreca

Image retrieval is used in searching for images from images database. In this paper, content – based image retrieval (CBIR) using four feature extraction techniques has been achieved. The four techniques are colored histogram features technique, properties features technique, gray level co- occurrence matrix (GLCM) statistical features technique and hybrid technique. The features are extracted from the data base images and query (test) images in order to find the similarity measure. The similarity-based matching is very important in CBIR, so, three types of similarity measure are used, normalized Mahalanobis distance, Euclidean distance and Manhattan distance. A comparison between them has been implemented. From the results, it is conclud

Air pollution evaluation of the operational processes in the East Baghdad oil field was carried out. The analysis was carried out by ICP-MS technique. Total Suspended Particles (TSP) air load was higher than Iraqi Standards and world international allowable limits of World Health Organization. The mean concentrations of gases carbon monoxide, carbon dioxide, sulfur dioxide, in the air were within national and world standards, while the mean concentration of nitrogen dioxide was higher than standard limits. The air of the study area is considered a good quality for CO, CO2 and NO2 with no health effect, while it is hazardous for TSP that have serious risk for people with respiratory disease. The mean concentrations of Cd, Cr, Cu and