Mixed ligands reaction of [2-[(3-hydroxyphenyl)diazinyl]-1,2-benzothiazol-3(2H)-one-1,1-dioxide] (H2L, primary ligand) and bipyridyl (secondary ligand) with salts of Cr(III), Mn(II), Fe(III), Co(II) and Ni(II) was performed. A series of air-stable complexes with distinctive octahedral moieties was created by equal molar ratio (1:1:1). The formation of these compounds was verified using detecting analysis techniques incorporating mass spectra, which validated the achieved geometries. Fourier transform infrared (FTIR) analysis demonstrated how the ligands (H2L and bipyridyl) are chelated as tridentate (ONO) and bidentate (NN) groups, respectively and the coordination with the metal ions. Thermal decomposition studies using pyrolysis (

ECG is an important tool for the primary diagnosis of heart diseases, which shows the electrophysiology of the heart. In our method, a single maternal abdominal ECG signal is taken as an input signal and the maternal P-QRS-T complexes of original signal is averaged and repeated and taken as a reference signal. LMS and RLS adaptive filters algorithms are applied. The results showed that the fetal ECGs have been successfully detected. The accuracy of Daisy database was up to 84% of LMS and 88% of RLS while PhysioNet was up to 98% and 96% for LMS and RLS respectively.

Digital change detection is the process that helps in determining the changes associated with land use and land cover properties with reference to geo-registered multi temporal remote sensing data. In this research change detection techniques have been employed to detect the changes in marshes in south of Iraq for two period the first one from 1973 to 1984 and the other from 1973 to 2014 three satellite images had been captured by land sat in different period. Preprocessing such as geo-registered, rectification and mosaic process have been done to prepare the satellite images for monitoring process. supervised classification techniques such maximum likelihood classification has been used to classify the studied area, change detection aft

      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu

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

Due to the large population of motorway users in the country of Iraq, various approaches have been adopted to manage queues such as implementation of traffic lights, avoidance of illegal parking, amongst others. However, defaulters are recorded daily, hence the need to develop a mean of identifying these defaulters and bring them to book. This article discusses the development of an approach of recognizing Iraqi licence plates such that defaulters of queue management systems are identified. Multiple agencies worldwide have quickly and widely adopted the recognition of a vehicle license plate technology to expand their ability in investigative and security matters. License plate helps detect the vehicle's information automatically ra

The buildup factor was measured after irradiating Iraq carbon black powder using each of and sources respectively, using mixing ratios 40% & 50% for thickness range . The results showed that the buildup factor depends on energy and has limited dependence on the mixing ratio. The QIFT program succeeded accenting for the experimental results even for expected values more than 4 m.f.p outside the thickness range.

The buildup factor of cylindrical samples (shields) for Brass, Copper & lead (Brass, Cu, Pb (was studied, where buildup factor were calculated with thickness between (0-12) m.f.p. for Co60 and Cs137sources with activities (30) & (41) MBq respectively , using scintillation detector NaI(T?) with (3"×3")volume .The results shows increases of buildup factor for low atomic number(Z) samples where the energy of radiation source was constant, also shows increases of buildup factor with decreases the energy of radiation source. An empirical equation was obtained using Matlab7 program this equation have agreements with most obtained data for 96%.