Seeing things through a negentropic lens won’t solve a bad relationship or help you love a job you hate – those are complicated issues. The best way to apply the idea of negentropy to social systems is to not only improve the small processes, but also look at the big picture and see if the status quo itself promotes energy loss. Spending time improving an orientation to introduce new workers to a company culture may not be very useful if the culture itself needs to change. As you try to implement negentropic ideas, keep track of what works, how much effort it took and ideas you come up with for future negentropic actions.Īs you work to reverse energy losses, you may find that at times you are actually maintaining a social system that isn’t beneficial no matter how smoothly it works. Put the ideas into action, but stay focused on energy gains and losses. You could start by fixing the leaky faucet or picking up your socks if pre-pre-planning meetings are causing your organization a lot of trouble, analyze the problem and figure out how to fix it. Identify actions that will reverse the energy losses you noted and plan ways to address the highest priorities first. Fixing it might make room in your mind to consider other improvements to your kitchen that would make it more functional. For example, perhaps that leaky kitchen faucet drives you crazy. Identify the largest or most annoying losses and those that draw your attention most often. A badly designed new employee onboarding system can lead to serious legal problems later. A poorly organized kitchen makes things hard to find. It’s helpful to think of it like a thermal map of the outside of your house that highlights where heat – or energy – is lost. Identify places where energy is lost in the social systems in your daily life. Passivhaus Institut, CC BY-SA 5 steps for negentropic successįrom my colleagues’ and my research into negentropy, we have come up with five steps to reverse energy loss in in daily life. Yuan ZH, Yong Q, Zongyi X, Limin J, Xiaoqing CH (2013) Safety region estimation and state identification of rolling bearing based on statistical feature extraction.Energy loss in your daily life is just like heat leaking out of a badly sealed house. Lingli J (2011) Fault diagnosis and pattern analysis for rotating machinery based on kemel methods. Yu Y, Dejie Y, Junsheng CH (2007) A fault diagnosis approach for roller bearing based on IMF envelope spectrum and SVM. Xueguang SH, Wensheng C (1999) A novel algorithm of the wavelet packets transform and its application to DE-Noising of analytical signal. IEEE Trans Neural Net Learn Syst 99(1):10 Zhigang L, Zhiwei H, Yang ZH, Qiaoge ZH (2014) Multi-wavelet packet entropy and its application in transmission line fault recognition and classification. He Z, Ling F, Lin S, Bo Z (2010) Fault detection and classification in EHV transmission line based on wavelet singular entropy bispectrum entropy feature extraction and its application for fault diagnosis of gearbox. National University of Defense Technology, Changsha Qinghu Z (2010) Fault prognostics technologies research for key parts and components of mechanical transmission systems. In: Proceedings of 13th International Congress on COMADEM, Houston, USA, pp12–20 Yang BS, Lim DS, An JL (2000) Vibration diagnostic system of rotating machinery using artificial neural network and wavelet transform. Elsevier Advanced Technology Publications, UK Measurement 55:343–352īarber A (1992) Handbook of noise and vibration control, 6th edn. Purarjomandlangrudi A, Ghapanchi AH, Esmalifalak M (2014) A data mining approach for fault diagnosis: an application of anomaly detection algorithm. Yang S, Shi T, Ding H (1992) The theory, Technique and method for mechanical device diagnosis. Jinsong H (2003) The rotating machinery faults diagnosis oriented empirical mode decomposition time-frequency analysis method and experiment study. Lim GM, Bae DM, Kim JH (2014) Fault diagnosis of rotating machine by thermography method on support vector machine. In: Signal Processing and their Applications IEEE 10th International Conference on Information Science, pp 21–24 Al-Badourl F, Chedect L, Suna M (1993) Non-stationary vibration signal analysis of rotating machinery via time–frequency and wavelet techniques.
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