The objective of the present investigation is to analyze the strategies that the companies implement and the changes that originate in the retail trade and the retail trade and in the commercial establishments in the developed countries. Based on a literary review, it identifies the framework of the current situation, encompassing all the social products and services that cause the new mechanisms of sale of products and services by the firms and the different ways of buying products and services by Los Consumers Concluding that this variation is mainly present due to the technological level, the culture of the purchase and the strategies of sale, that owns and develops the consumers and the companies.

The purpose of this research is to analyze the degree of effectiveness of TQM in SMEs in Mexico as a function of Business Performance, considering that Business Performance is related to Total Quality Management. This research is analytical and descriptive, since no statistical method is used, only the variables and the research problem are analyzed in detail and in a detailed manner, and descriptive because tables and tables can be found to help facilitate understanding of these important concepts. This research will analyze the impact of both variables, and with this, the entrepreneurs can make the necessary changes in their production line or in their employees to obtain better and greater positive results.

Electricity is natural but not a storable resource and has a vital role in modern life. Balancing between consumption and production of the electricity is highly important for power plants and production facilities. Researches show that electricity load consumption characteristic is highly related to exogenous factors such as weather condition, day type (weekdays, weekends and holidays etc.), seasonal effects, economic and politic changes (crisis, elections etc.). In this study, we propose a short-term load forecasting models using artificial intelligence based optimization technique. Proposed 5 different empirical models were optimized using flower pollination algorithm (FPA). Training and testing phase of the proposed models held with historical load and weather temperature dataset for the years between 2011-2014. Forecasting accuracy of the models was measured with Mean Absolute Percentage Error (MAPE) and monthly minimum approximately %1,79 for February 2013. Results showed that proposed load forecasting model is very competent for short-term load forecasting

Accelerators are systems where high-tech experiments are conducted today and contain high-tech constructions. Construction and operation of accelerators require multidisciplinary studies. Each accelerator structure has its own characteristics as well as similar features of accelerator structures. Control systems come to the forefront as one of the most important structures that make up accelerators. Since control systems have critical importance for accelerators, in such systems when a problem occurs, there is a danger of environmental and human safety as well as machine system. For that reason interlock systems are being developed in different structures. In the literature, FPGAs and PLCs in such interlock systems have been shown to be suitable for use in accelerators [1,7]. In this work, we describe an interlock system that evaluates the operation and protection modes of devices used in an electron accelerator. In order to ensure that this system can operate at minimum cost and maximum safety, the defined system is divided into 3 subsystems. The error messages from the control devices in the accelerator control systems are the input to the interlock system. The purpose of the interlock system that evaluates error messages is to ensure that the accelerator closes safely. The purpose of this study is to specify which of the 3 interlock subsystems which are defined for minimum cost and maximum security should be connected to the fault outputs from the control devices. As an evaluation criterion, 6 features are defined for the control devices and each control device is weighted according to the importance of the task. In the solution of the problem, genetic algorithms were used for assigning 74 controller outputs to 3 interlock subsystems. Thanks to the Genetic Algorithm used in the study, 94.3% success rate was obtained in terms of cost and safe system.

In this study, which is a source of renewable energy required to take advantage of solar energy to the maximum duration of sunshine was estimated. In the study, values were used of the city of Amasya. Artificial neural networks (ANN) backpropagation gradient-descent(GD) learn algorithm and genetic algorithm(GA) were used. Three hidden layer network model was designed with two inputs for ANN and GA. Between 2000 and 2010 values were used as input data monthly sunshine duration and humidity values. Output data was obtained monthly sunshine duration of 2010. The values obtained were compared with the actual values and the root mean square error (RMSE) was calculated. Result of the study, GA was used to calculate the values that are needed for solar energy.

This paper has presented the basis of a compound multiphase waveform design with additional amplitude modulation, capable of controlling a waveform pick-factor, suitable for use with marine radar. The waveform shows good Doppler tolerance, with the low side-lobes performance maintained over the central zone of an ambiguity function. A clear waveform design procedure has been presented that does not require the implementation of numerical optimization procedures. It has been shown that a compromise between side-lobes suppression and the value of pick-factor can be found. These waveforms allow achieving better results as compared to compound multiphase waveforms without additional amplitude modulation under mismatched weighting filtering. In this article we considered periodic mode of Radar.