Knowledge management can play a vital role in increasing the efficiency and effectiveness of organizations. The earnings from utilizing knowledge management has caused that most organizations try to execute this process. In this study, we aim to assess the ranking and weights of knowledge management enablers based on the academic members, staff and student in management schools of Qom province in Iran. The results showed that the organizational culture has the most important position while the organizational structure has the least important position in knowledge management in universities. Using a group AHP weighting method resulted in highest weight for organizational culture and lowest weight for organizational culture in developing knowledge management in educational organizations.
In order to optimize source allocation and decision making about marketing mix in flower and plant (F&P) industry field and in order to reach to benefit goals, this research estimate the effects of five elements included product, price, place, promotion and Sale Labor Traits on F&P sale volume. On this base, the effect of each of these elements on F&P sale volume is hyphenised and essential information is been collected from flower sellers' population in city Tehran by a questionnaire. We used random sample method and content of sample members has computed about 130 stores. The one sample t test in order to confirm or reject those hypothesizes has been used. All of hypothesizes was supported with 95 percent confidence interval, Then we ranked amount of effect of each element with Friedman's test.
Since various pseudo-random algorith ms and sequences are used for cryptography of data or as init ial values for starting a secure communicat ion, how these algorith ms are analyzed and selected is very important. In fact, given the g rowingly extensive types of pseudorandom sequences and block and stream cipher algorith ms, selection of an appropriate algorith m needs an accurate and thorough investigation. Also, in order to generate a pseudo-random sequence and generalize it to a cryptographer algorith m, a co mprehensive and regular framework is needed, so that we are enabled to evaluate the presented algorith m as quick as possible. The purpose of this study is to use a number of pseudo-random number generators as well as popular cryptography algorith ms, analyze them in a standard framework and observe the results obtained in each stage. The investigations are like a match between d ifferent algorith ms, such that in each stage, weak algorith ms are eliminated using a standard method and successful algorith ms enter the next stage so that the best algorith ms are chosen in the final stage. The main purpose of this paper is to certify the approved algorithm.
ABSTRACT. In the current competitive environment, companies will be able to adjust business strategies, they use market segmentation based on practical ways rather than using traditional approaches or incomplete and impractical mass marketing. In recent years, mining has gained attention and popularity in the business world. The goal of data mining projects is to convert the raw data into useful information. Clustering can also be used to explore differences in attitudes and intentions of the clients. In this study, we used fuzzy clustering on 1071 life insurance customers during March to October 2014. . Results show that the optimal number of clusters was 2 which were named as "investment" and "life safety". Some suggestions are presented to improve the performance of the insurance company.
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