A novel series of mixed-ligand complexes of the type, [ML 1 (L 2 ) 3 ]Cl x [M = Cr(III), Fe(III), Co(II),Ni(II), Cu(II), Cd(II) and Hg(II), n = 2, 3], was synthesized using Schiffbase (HL 1 ) as main ligand, nicotinamide (L 2 ) as secondary ligand, and the corresponding metal ions in 1:3:1 molar ratio. The main ligand, HL 1 was prepared by the interaction of ampicillin drug and 4-chlorobenzophenone. The synthesized mixed ligand complexes were characterized by elemental analysis, UV-Vis, FT-IR, 1 H-NMR, 13 C-NMR and TG/DTG studies. In the mixed-ligand complexes, the Schiffbase ligand, HL 1 showed coordination to the central metal ion in tridentate manner via azomethine nitrogen, β-lactam ring oxygen and deprotonated carboxylic oxy- gen atom

This study was conducted to evaluate the efficiency of some chemicals and biological agents to induce systemic resistance (ISR) against to wheat common bunt disease caused by the two species of fungus Tilletia tritici (Bjerk.) Wint (T. caries (Dac.) Tul.) and T. laevis Kuhn (T. foetida (Wall.) Liro. Trails in the efforts to find an alternative, safe and environmentally friendly means to control the disease. Results of this study which carried out during two consecutive seasons for the years 2012 - 2013 and 2013 - 2014 at two different environmental locations. Seed treatment by (SA 100 and 200 mg/L, 500 ?–aminobutyric acid (BABA) and 1000 mg/L, Effective Microorganisms (EM1) 40 and 150 ml/kg seeds) have led to high significant redu

فقدان الزوج يعد حدثًا يغير حياة النساء، مما يضطرهن إلى السباحة في عالم جديد مليء بالحزن والوحدة والشكوك. مع الوقت، تطورت طريقة تصوير الأرامل بشكل كبير تعكس التغييرات في الآراء والقيم الثقافية. تُمثل الأرامل تقليديًا بأنهن ضعيفات ومعتمدات في الأدب، مستندة إلى افتراض أنهن يفتقدن الدعم المالي بعد وفاة شركائهن. ومع ذلك، فإن هذا التصوير لا يعترف بتأثير الأرملة على الرفاهية والهوية الشخصية. يسعى هذا النص إلى

Tourism plays an important role in Malaysia’s economic development as it can boost business opportunity in its surrounding economic. By apply data mining on tourism data for predicting the area of business opportunity is a good choice. Data mining is the process that takes data as input and produces outputs knowledge. Due to the population of travelling in Asia country has increased in these few years. Many entrepreneurs start their owns business but there are some problems such as wrongly invest in the business fields and bad services quality which affected their business income. The objective of this paper is to use data mining technology to meet the business needs and customer needs of tourism enterprises and find the most effective

  The great scientific progress has led to widespread Information as information accumulates in large databases is important in trying to revise and compile this vast amount of data and, where its purpose to extract hidden information or classified data under their relations with each other in order to take advantage of them for technical purposes.

      And work with data mining (DM) is appropriate in this area because of the importance of research in the (K-Means) algorithm for clustering data in fact applied with effect can be observed in variables by changing the sample size (n) and the number of clusters (K)

One wide-ranging category of open source data is that referring to geospatial information web sites. Despite the advantages of such open source data, including ease of access and cost free data, there is a potential issue of its quality. This article tests the horizontal positional accuracy and possible integration of four web-derived geospatial datasets: OpenStreetMap (OSM), Google Map, Google Earth and Wikimapia. The evaluation was achieved by combining the tested information with reference field survey data for fifty road intersections in Baghdad, Iraq. The results indicate that the free geospatial data can be used to enhance authoritative maps especially small scale maps.

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob