This work comprises the synthesis of new thioxanthone derivatives containing C-substituted thioxanthone. To obtain these derivatives, the o-mercapto benzoic acid was chosen as the starting material, which was reacted with dry benzene in sulfuric acid (98 %) to produce the thioxanthone (1). The 2,7-(disulfonyl phosphine imine) thioxanthone (4-8) were prepared from reaction of compound (1) with chlorosulfonic acid gave 2,7-(disulfonyl chloride) thioxanthone (2). Treatment of (2) with sodium azide to produce 2,7-(disulfonyl azide) thioxanthone (3). Condensation of (3) with phosphorus compounds afforded compounds (4-8). The 2,7-(disulfonamide) thioxanthone (9-21) was obtained when co

Nurse scheduling problem is one of combinatorial optimization problems and it is one of NP-Hard problems which is difficult to be solved as optimal solution. In this paper, we had created an proposed algorithm which it is hybrid simulated annealing algorithm to solve nurse scheduling problem, developed the simulated annealing algorithm and Genetic algorithm. We can note that the proposed algorithm (Hybrid simulated Annealing Algorithm(GS-h)) is the best method among other methods which it is used in this paper because it satisfied minimum average of the total cost and maximum number of Solved , Best and Optimal problems. So we can note that the ratios of the optimal solution are 77% for the proposed algorithm(GS-h), 28.75% for Si

The rise in the general level of prices in Iraq makes the local commodity less able to compete with other commodities, which leads to an increase in the amount of imports and a decrease in the amount of exports, since it raises demand for foreign currencies while decreasing demand for the local currency, which leads to a decrease in the exchange rate of the local currency in exchange for an increase in the exchange rate of currencies. This is one of the most important factors affecting the determination of the exchange rate and its fluctuations. This research deals with the currency of the European Euro and its impact against the Iraqi dinar. To make an accurate prediction for any process, modern methods can be used through which

Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi