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 (

Obiovisly that the holy thresholds are directly related to Islam and Muslims and related to the general culture of the Islamic peoples. In terms of architecture, it is considered a distinctive architectural scene that reviews the history of this origin and its architectural styles. Recently, with the increase in the number of pilgrims and visitors to the holy shrines, there is a need to develop and expand the buildings and provide them with services and introduce modern technology. The building of the holy thresholds consists of a number of functional design indicators: The general problem of research is that there is no clear theoretical framework for the design indicators for the development of the holy shrines according to the functio

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.

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

      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

             It is the regression analysis is the foundation stone of knowledge of statistics , which mostly depends on the ordinary least square method , but as is well known that the way the above mentioned her several conditions to operate accurately and the results can be unreliable , add to that the lack of certain conditions make it impossible to complete the work and analysis method and among those conditions are the multi-co linearity problem , and we are in the process of detected that problem between the independent variables using farrar –glauber test , in addition to the requirement linearity data and the lack of the condition last has been resorting to the

After harvesting, Alfalfa plant was washed, dried and ground to get fine powder used in treatment water. We used alfalfa plant with ethanol to made alcoholic extract and characterized it applying (GC-Mass, FTIR, UV) spectroscopy to determine active compounds. Alcoholic extract was used to prepare zinc nanoparticle. We characterized Zinc nanoparticles by using FTIR, UV, SEM, EDX Zeta potential and AFM. Zinc nanoparticle with Alfalfa extract and alfalfa powder was used to treat pollutant water with pesticides and negative ions by two methods, namely Batch and continuous processing. Batch process was used two times firstly, with Alfalfa plant to treat water affected by pesticides and negative ions, after 1h pesticides (glyphosate 44.76%, sulfo

Pseudomonas aeruginosa has variety of virulence factors that contribute to its pathogenicity. Therefore, rapid detection with high accuracy and specificity is very important in the control of this pathogenic bacterium. To evaluate the accuracy and specificity of Polymerase Chain Reaction (PCR) assay, ETA and gyrB genes were targeted to detect pathogenic strains of P. aeruginosa. Seventy swab samples were taken from patients with infected wounds and burns in two hospitals in Erbil and Koya cities in Iraq. The isolates were traditionally identified using phenotypic methods, and DNA was extracted from the positive samples, to apply PCR using the species specific primers targeting ETA, the gene encoding for exotoxin A, and gyrB gene. The res

In this paper, a subspace identification method for bilinear systems is used . Wherein a " three-block " and " four-block " subspace algorithms are used. In this algorithms the input signal to the system does not have to be white . Simulation of these algorithms shows that the " four-block " gives fast convergence and the dimensions of the matrices involved are significantly smaller so that the computational complexity is lower as a comparison with " three-block " algorithm .

Human skin detection, which usually performed before image processing, is the method of discovering skin-colored pixels and regions that may be of human faces or limbs in videos or photos. Many computer vision approaches have been developed for skin detection. A skin detector usually transforms a given pixel into a suitable color space and then uses a skin classifier to mark the pixel as a skin or a non-skin pixel. A skin classifier explains the decision boundary of the class of a skin color in the color space based on skin-colored pixels. The purpose of this research is to build a skin detection system that will distinguish between skin and non-skin pixels in colored still pictures. This performed by introducing a metric that measu