In this work, different soil samples were brought to study and analyse the element concentrations from different middle regions of Iraq (such as, Habbaniah, Garmah, Fallujah, and Tarmiah cities). Using laser-induced breakdown spectroscopy (LIBS) has been documented as an atomic emission spectroscopy (AES) technique.  Laser-induced plasma utilized to analyse elements in materials (gases, liquids, and solids) in order to analyse elements in materials (gases, liquids and solid). The Nd:YAG laser excitation source at 1064nm with pulse width and pulse duration of 9ns is used to generate power density of 5.5 x 10¹² MW/mm², with optical spectrum in the range 320 -740 nm.

The soils of Habbaniyah and Garmah citi

An eco-epidemiological system incorporating a vertically transmitted infectious disease is proposed and investigated. Micheal-Mentence type of harvesting is utilized to study the harvesting effort imposed on the predator. All the properties of the solution of the system are discussed. The dynamical behaviour of the system, involving local stability, global stability, and local bifurcation, is investigated. The work is finalized with the numerical simulation to observe the global behaviour of the solution.

A total of 352 freshwater fishes, belonging to three species of the family Cyprinidae were collected from the Greater Zab river in north of Iraq during the period from November 2000 to the end of November 2001. The inspection of their gills revealed the infection of these fishes with three species of monogenetic trematodes belonging to the genus Dogielius. These species included D. mokhayeri from Aspius vorax with a percentage incidence of 37.5%; D. molnari from Cyprinion macrostomum (33.3%) and D. persicus from Barbus luteus (41.2%). The record of this genus and its three above-named species of the present study are considered as the first record on fishes of Iraq.

This paper presents a proposed method for (CBIR) from using Discrete Cosine Transform with Kekre Wavelet Transform (DCT/KWT), and Daubechies Wavelet Transform with Kekre Wavelet Transform (D4/KWT) to extract features for Distributed Database system where clients/server as a Star topology, client send the query image and server (which has the database) make all the work and then send the retrieval images to the client. A comparison between these two approaches: first DCT compare with DCT/KWT and second D4 compare with D4/KWT are made. The work experimented over the image database of 200 images of 4 categories and the performance of image retrieval with respect to two similarity measures namely Euclidian distance (ED) and sum of absolute diff

Most of the propositions and researches that dealt with fashions in the Middle East, specifically this region from the world, from a historical perspective have not been sufficient, and were characterized by many aspects of immature thinking, in addition, they have been varied in quality. This can be attributed to many factors including: the focus in the field of researches and Middle East studies is on languages, arts, history, and political thinking of the region. Other factors are the information asymmetry, the differences in sources and references, in addition to differences in the scientific value of these sources added to the difficulty of gathering them at the same time especially that these sources are scattered in many places wh

In this paper, two new simple, fast and efficient block matching algorithms are introduced, both methods begins blocks matching process from the image center block and moves across the blocks toward image boundaries. With each block, its motion vector is initialized using linear prediction that depending on the motion vectors of its neighbor blocks that are already scanned and their motion vectors are assessed. Also, a hybrid mechanism is introduced, it depends on mixing the proposed two predictive mechanisms with Exhaustive Search (ES) mechanism in order to gain matching accuracy near or similar to ES but with Search Time ST less than 80% of the ES. Also, it offers more control capability to reduce the search errors. The experimental tests

With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect

This paper proposes a collaborative system called Recycle Rewarding System (RRS), and focuses on the aspect of using information communication technology (ICT) as a tool to promote greening. The idea behind RRS is to encourage recycling collectors by paying them for earning points. In doing so, both the industries and individuals reap the economical benefits of such system. Finally, and more importantly, the system intends to achieve a green environment for the Earth. This paper discusses the design and implementation of the RRS, involves: the architectural design, selection of components, and implementation issues. Five modules are used to construct the system, namely: database, data entry, points collecting and recording, points reward

In this paper an accurate Indian handwritten digits recognition system is
proposed. The system used three proposed method for extracting the most effecting
features to represent the characteristic of each digit. Discrete Wavelet Transform
(DWT) at level one and Fast Cosine Transform (FCT) is used for features extraction
from the thinned image. Besides that, the system used a standard database which is
ADBase database for evaluation. The extracted features were classified with KNearest
Neighbor (KNN) classifier based on cityblock distance function and the
experimental results show that the proposed system achieved 98.2% recognition
rate.