Diagnosis of rotor fault using neuro-fuzzy inference system

The three-phase induction machines (IM) is large importance and are being widely used as electromechanical system device regarding for their robustness, reliability, and simple design with well developed technologies. This work presents a reliable method for diagnosis and detection of rotor broken bars faults in induction machine. The detection faults are based on monitoring of the current signal. Also the calculation of the value of relative energy for each level of signal decomposition using package wavelet, which will be useful as data input of adaptive Neuro-Fuzzy inference system (ANFIS). In this method, fuzzy logic is used to make decisions about the machine state. The adaptive Neuro-Fuzzy inference system is able to identify the IM bearing state with high precision. This technique is applied under the MATLAB®.Keywords: Induction Machine; Diagnosis; Detection; Neuro-Fuzzy inference system

Prosociality in business: a human empowerment framework

This study introduces a human empowerment framework to better understand why some businesses are more socially oriented than others in their policies and activities. Building on Welzel’s theory of emancipation, we argue that human empowerment—comprised of four components: action resources, emancipative values, social movement activity, and civic entitlements—enables, motivates, and entitles individuals to pursue social goals for their businesses. Using a sample of over 15,000 entrepreneurs from 43 countries, we report strong empirical evidence for two ecological effects of the framework components on prosociality. We find that human empowerment (1) lifts entrepreneurs’ willingness to choose a social orientation for their business, and (2) reinforces the gender effect on prosociality in business activity. We discuss the human empowerment framework’s added value in understanding how modernization processes fully leverage the potential of social business activities for societies