Brain computer interface (BCI) systems have been regarded as a new way of communication for humans. In this research, common methods such as wavelet transform are applied in order to extract features. However, genetic algorithm (GA), as an evolutionary method, is used to select features. Finally, classification was done using the two approaches support vector machine (SVM) and Bayesian method. Five features were selected and the accuracy of Bayesian classification was measured to be 80% with dimension reduction. Ultimately, the classification accuracy reached 90.4% using SVM classifier. The results of the study indicate a better feature selection and the effective dimension reduction of these features, as well as a higher percentage of classification accuracy in comparison with other studies.
According to different nature of work in various companies, the essential step in implementation of optimal customer relationship management is identifying factors affecting CRM performance and indicators related to each factor. Therefore in this study, in order to assess the maturity of organization in the implementation of CRM, the main factors affecting CRM performance in the baby accessories industry were identified. Then the indicators explaining each factor were extracted and using Analytical Hierarchy Process (AHP) factors and identified indicators were ranked, and then the maturity status of the studied organization were analyzed in relation to CRM implementation. According to new and valid ideas, the main factors affecting the assessment of organizational maturity in CRM implementation are defined by three factors of processes, human resources and technology. The main factors affecting the CRM implementation were prioritized and also indicators related to the three main factors in line with the successful implementation of CRM were ranked. In order to assess the maturity of organization in CRM implementation, the binominal test was used. Except for the indicator of information technology and knowledge management which is lower than the given value for maturity level of the organization (12.5), other indicators such as strategy, organizational processes, organizational culture, human resources and change management, the studied organization in baby accessories industry has matured in CRM implementation.
In recent years, brain-computer communication systems have been regarded as a new way of communication for humans. One of the applications of brain-computer communication is the development of systems which facilitates communication. To this end, it is necessary to extract the visually evoked signals from the EEG signal and classify it. In this research, common methods such as wavelet transform are applied in order to extract features. However, genetic algorithm, as an evolutionary method, is used to select features. Finally, after selecting features, the classification was done using the two approaches support vector machine and Bayesian method. Five features were selected and the accuracy of Bayesian classification was measured to be 80% with dimension reduction, and 78% without dimension reduction. Ultimately, the classification accuracy reached 90.4% using SVM classifier. The results of the study indicate a better feature selection and the effective dimension reduction of these features, as well as a higher percentage of classification accuracy in comparison with other studies.
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