Many economies in the world are undergoing changes as a result of the shocks caused by globalization in the local labor force. These changes must answer orderly government, and as the national mechanism will "wake up" Earlier, this country less affected in the rapid globalization which taking place all over the world. This article presents the advantages and disadvantages of this, and gives a brief picture about the state of Israel

This paper focus on the performance of an industrial boiler using fuzzy logic controller. The parameter of the various industrial boilers are subjected to the change due to change in the environment or atmosphere. These parameter may be categorized as steam, pressure and temperature of the industrial boiler in use. In this paper work, a strategy of fuzzy logic controller called fuzzy supervisory is used which generates set points for the conventional controllers. This work also compared the performance of a boiler evaporator system when the system is controlled by a traditional proportional integral derivatives type strategy and when the system is controlled using fuzzy logic blocs to provide set point for it. The main change consists of representing only the behaviour of the drum evaporator system having a partial model of the combustion process with a simplified combustion control system and a three element boiler feed water receives a supervisory signal that comes from fuzzy logic to improve the performance of the overall control system.

The present study aims at evaluating effects of dietary fibers of Mango peels (MP) and Date seeds (DS) on the quality of Arabic bread (AB). MP was added at two levels (2% and 4%) and DS were at 4% and 6%, based on flour weight. Results showed that DS is considered as a good source of dietary fiber compared to MP. Also, it was found that MP at different levels improved the overall quality of AB. An adaptive neuro-fuzzy inference system (ANFIS) is used to study the properties AB with the different proportions of mango peel (M) and dates seed (D) as inputs, and two output properties (crust color CC and crumb texture CT). Experimental validation runs were conducted to compare the measured values and the predicted ones. The comparison shows that the adoption of this neuro- modeling technique (i.e., ANFIS) achieved a satisfactory prediction accuracy of about 85%

Power electronic converters are periodical variable structure system owing to their switching operations, being a simple in structure, lot of researchers are working on power electronic converters. As they have been found practically more efficient and cheapest. That’s why they are being used vastly. The Switch Mode DC DC Converters being a highly underdamped produces oscillations and nonlinearities in the output voltage. Lot of controlling techniques have been used to mitigate the oscillations but those controllers/ controlling techniques have certain drawbacks. In this research paper PI controller is being compared with Artificial Neural network controller based on Switch Mode DC DC converter at higher switching frequency under Steady state as well as dynamic state (line and load variations). Although Artificial Neural network controller is being used in problems involving nonlinearities and uncertainties but here it is used/applied to Step down chopper converter to control voltage under steady state as well as dynamic state. Here Neural Network is trained by using Levenberg Marquardt (trainlm) Algorithm. It is executed and operated in Matlab/Simulink, and Simulation results are shown here.

Failure of boiler tubes in a thermal power plant is a very common phenomenon. So run the plant safely it is imperative for every plant owners to investigate the reason of failure and find out the remedies to prevent frequent plant shut downs. This paper, therefore, aims to provide the failure analysis report of boiler tubes at Lakhra Power Generation Company limited LPGCL (Khanote). The investigation is comprised on visual examination, fractography analysis, microstructural investigations and chemical analysis of the tube material. Optical microscope, Scanning electron microscope (SEM), X-Ray diffraction (XRD) and electron dispersion spectroscopy (EDS) techniques were used. Results indicated that the major cause of failure was localized short-term overheating of the tube due to improper material used for manufacturing of boiler tube. The fracture appearance is called fish mouth opening.

Power electronic converters are periodical variable structure system owing to their switching operations, being a simple in structure, lot of researchers are working on power electronic converters. As they have been found practically more efficient and cheapest. That’s why they are being used vastly. The Switch Mode DC DC Converters being a highly underdamped produces oscillations and nonlinearities in the output voltage. Lot of controlling techniques have been used to mitigate the oscillations but those controllers/ controlling techniques have certain drawbacks. In this research paper PI controller is being compared with Artificial Neural network controller based on Switch Mode DC DC converter at higher switching frequency under Steady state as well as dynamic state (line and load variations). Although Artificial Neural network controller is being used in problems involving nonlinearities and uncertainties but here it is used/applied to Step down chopper converter to control voltage under steady state as well as dynamic state. Here Neural Network is trained by using Levenberg Marquardt (trainlm) Algorithm. It is executed and operated in Matlab/Simulink, and Simulation results are shown here.

Power electronic converters are periodical variable structure system owing to their switching operations, being a simple in structure, lot of researchers are working on power electronic converters. As they have been found practically more efficient and cheapest. That’s why they are being used vastly. The Switch Mode DC DC Converters being a highly underdamped produces oscillations and nonlinearities in the output voltage. Lot of controlling techniques have been used to mitigate the oscillations but those controllers/ controlling techniques have certain drawbacks. In this research paper PI controller is being compared with Artificial Neural network controller based on Switch Mode DC DC converter at higher switching frequency under Steady state as well as dynamic state (line and load variations). Although Artificial Neural network controller is being used in problems involving nonlinearities and uncertainties but here it is used/applied to Step down chopper converter to control voltage under steady state as well as dynamic state. Here Neural Network is trained by using Levenberg Marquardt (trainlm) Algorithm. It is executed and operated in Matlab/Simulink, and Simulation results are shown here.