Assessing Energy Efficiency for Economic and Sustainable Development in the Region of European Union Countries

The objective of this research is to estimate the energy-saving intensities of nations within the European Union, applying varied equations of the DEA analysis, such as the DEA, modified radial equation, Russel dynamic envelope analysis, and the adjusted Russel Dynamic envelope Analysis, throughout the period of 2010–2018. Unlike other studies, this analysis seeks to unravel whether European nations are effective in increasing the EE finance of their respective economies. Because the European Union not only has geographical ties between regions, it is also a collection of interests of various sovereign states, its energy exhibits efficiency changes under the relationship of competition and cooperation under that economic effect. Regarding this circumstance, different dynamic envelope evaluations were formulated. One primary finding is that nations such as Germany, Sweden, or Austria attain robust ecological safeguard performance, seem to be using less energy, and are ecologically efficient relative to other nations such as Denmark, Belgium, Spain, France, or Ireland. Furthermore, a group of Eastern EU nations attained reduced efficiency marks, which could be categorized as anticipated, as a result of reduced technological implementation within the principal manufacturing sectors. The main result of this study is that few nations are performing in terms of efficiency. Additionally, RE (Renewable Energy) power production expands as nations’ dynamic envelope analysis marks and creates inefficient governments nearer to the efficiency frontline. Inversely, the presence of peak-time power consumption reduced the dynamic envelope analysis marks and increased the distance from the Frontier of efficiency (the optimal value of efficiency).

Measuring the Relative Efficiency of Government Banks Using Data Envelope Analysis (DEA) For The Period (2010-2019)

The research aims to apply the data envelope analysis method to measure the efficiency of Iraqi government banks for the period (2010-2019) and to implement the objectives of the research, the method of data envelope analysis was chosen on (7) government banks for the period (2010-2019), this research means measuring the efficiency of the Iraqi banking system The research reached a main conclusion that (6) banks did not achieve efficiency, namely (Al-Rafidain Bank, Al-Rasheed Bank, Agricultural Bank, Industrial Bank, Real Estate Bank, Trade Bank of Iraq) and one bank that achieved efficiency during the period 2010-2019, which is (Al-Nahrain Bank Islamic(. Therefore, the research recommends Iraqi government banks to work to raise their efficiency by modernizing banks to strengthen their financial positions, and to provide new banking services to face intense competition in light of the liberalization of banking services trade, and the research recommends the necessity of financing provided by government banks to achieve economic development.

Toward an online strategy for mechanical failures diagnostics inside the wind turbine generators based on spectral analysis

Mechanical faults in wind turbine generators lead to a huge problems of breaking electricity production, increase the maintenance cost and can damage the wind turbine generator, which caught fire in the nacelle. Gearbox installed in the nacelle is the important component in wind turbine, it composed by shafts bearings and gearings. Always bearings and gearings failures are related together. Therefore, to control these rotating components we need to analysis their vibration signature. This work was done with Tunisian Electricity and Gas Company (STEG) it’s about mechanical failures diagnostics which are based on three temporal vibration signals which are made by three sensors installed also in three positions axial, vertical, and horizontal. In this work we present a Fast Fourier Transform which is applied on raw mechanical vibration signals by the vibration department of STEG, which are compared with a new strategy of envelope analysis is commonly used to obtain the mechanical faults harmonics from the envelope signal spectrum analysis and has shown a more suitable results of diagnostics which is applied on the same data sets from Fast Fourier Transform. In this work, we illustrate a squared envelope based on spectral kurtosis approach to determine optimum envelope analysis parameters including the filtering band and center frequency through a short time Fourier transform. This method proves a better diagnosis results using real vibration data set from vibration department of STEG.

Time–Frequency Envelope Analysis for Fault Detection of Rotating Machinery Signals with Impulsive Noise

Envelope analysis is a widely used tool for fault detection in rotating machines. In envelope analysis, impulsive noise contaminates the measured signal, making it difficult to extract the features of defects. This paper proposes a time–frequency envelope analysis that overcomes the effects of impulsive noises. Envelope analysis is performed by dividing the signal into several sections through a time window. The effect of impulsive noises is eliminated by using the frequency characteristics of the short time rectangular wave. The proposed method was verified through simulation and experimental data. The simulation was conducted by mathematically modeling a cyclo-stationary process that characterizes rotating machinery signals. In addition, the effectiveness of the method was verified by the measured data of normal and defective air-conditioners produced on the actual assembly line. This simple proposed method is effective enough to detect the faults. In the future, the approaches of big data and deep learning will be required for the development of the prognostic health-management framework.

Envelope analysis of the human alpha rhythm

The origin of the human alpha rhythm has been a matter of debate since Lord Adrian attributed it to synchronous neural populations in the occipital cortex. While some authors have pointed out the Gaussian characteristics of the alpha rhythm, their results have been repeatedly disregarded in favor of Adrian′s interpretation; even though the first EEG Gaussianity reports can be traced back to the origins of EEG. Here we revisit this problem using the envelope analysis — a method that relies on the fact that the coefficient of variation of the envelope (CVE) for continuous-time zero-mean Gaussian white noise (as well as for any filteredsub-band) is equal to √(4−π)/π≈0.523, thus making the CVE a fingerprint for Gaussianity. As a consequence, any significant deviation from Gaussianity is linked to synchronous neural dynamics. Low-CVE signals come from phase-locking dynamics, while mid-CVE signals constitute Gaussian noise. High-CVE signals have been linked to unsteady dynamics in populations of nonlinear oscillators. We analyzed occipital EEG and iEEG data from massive public databases and the order parameter of a population of weakly coupled oscillators using the envelope analysis. Our results showed that the human alpha rhythm can be characterized as a rhythmic, Gaussian, or pulsating signal due to intra- and inter-subject variability. Furthermore, Fourier analysis showed that the canonical spectral peak at≈10[Hz] is present in all three CVE classes, thus demonstrating that this same peak can be produced by rhythms, Gaussian noise, and pulsating ripples. Alpha-like signals obtained from a population of non-linear oscillators showed a different CVE depending only on the coupling constant, suggesting that the same neural population can produce the amplitude modulation patterns observed in experimental data. iEEG data, however, was found to be mostly Gaussian, specially the signals recorded from the calcarine cortex. These results suggest that a new interpretation for EEG event-related synchronization/desynchronization (ERS/ERD) may be needed. Envelope analysis constitutes a novel complement to traditional Fourier-based methods for neural signal analysis relating amplitude modulations (CVE) to signal energy.