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The purpose of this paper is to investigate the possibility to replace radio equipment compliance requirements based on equipment parameters with a set of simple metrics that accurately reflects spectrum utilization and spectrum-sharing efficiency.

The approach taken is to go back to the basic factors that determine radio system behavior in a shared spectrum environment: radio frequency power, duty cycle and frequency occupation. By normalizing these parameters, device specificity is avoided and a statistical perspective on spectrum utilization and sharing becomes possible.

The analysis shows that two technology-neutral metrics would be adequate to govern spectrum utilization and sharing: a spectrum utilization metric and a spectrum-sharing efficiency metric. These metrics form the core of regulatory requirements for shared frequency bands. Each shared frequency band could be assigned criteria based on these metrics that take into account the types of applications for which that band will be used.

This work is a first step that identifies the main factors that affect shared spectrum usage from a statistical point of view. More work is needed on the relationship between real-world interference and its abstraction in the spectrum-sharing rules.

The metrics proposed could be considered as the basis for a new approach to the regulation of the license-exempt spectrum, and, by extension, as the basis for generic compliance criteria. Their use would facilitate the compliance assessment of software-defined radio technology.

This work has no direct social implications.

This paper combines new work on spectrum utilization criteria with extensions of previous work on spectrum-sharing efficiency into a comprehensive proposal for a new approach to the regulation of the license-exempt spectrum.

In order to meet the different quality of service (QoS) requirements of vehicle-to-infrastructure (V2I) and multiple vehicle-to-vehicle (V2V) links in vehicle networks, an efficient V2V spectrum access mechanism is proposed in this paper.

A long-short-term-memory-based multi-agent hybrid proximal policy optimization (LSTM-H-PPO) algorithm is proposed, through which the distributed spectrum access and continuous power control of V2V link are realized.

Simulation results show that compared with the baseline algorithm, the proposed algorithm has significant advantages in terms of total system capacity, payload delivery success rate of V2V link and convergence speed.

The LSTM layer uses the time sequence information to estimate the accurate system state, which ensures the choice of V2V spectrum access based on local observation effective. The hybrid PPO framework shares training parameters among agents which speeds up the entire training process. The proposed algorithm adopts the mode of centralized training and distributed execution, so that the agent can achieve the optimal spectrum access based on local observation information with less signaling overhead.

New technologies challenge the traditional view that the radio spectrum must be tightly controlled and the new orthodoxy that a market‐based approach is the most efficient way to manage the spectrum. This article aims to make the case for collective use of the spectrum.

The paper draws on a range of literature, both technical and economic, as well as the authors' opinions to describe the economic context, market and other models for spectrum allocation, technological advances in signal processing, and the way forward for assessing future spectrum management policy, with particular reference to Europe.

Technical advances, from research in the commercial domain and from release of military research, combined with the increasingly important economic need to facilitate innovation in new radio technologies, demand a debate on a new approach to spectrum management policy.

The paper brings together the economic and technical arguments in favour of collective use of the radio spectrum and will be of value to academics, business and policy makers.

Mathematical bios and heartbeat series show an inverse relation between frequency and power; the time series of differences between successive terms of cardiac and mathematical chaos shows a direct relation between frequency and power. Other statistical analyses differentiate these biotic series from stochastically generated 1/f noise. The time series of complex biological and economic processes as well as mathematical bios show asymmetry, positive autocorrelation, and extended partial autocorrelation. Random, chaotic and stochastic models show symmetric statistical distributions, and no partial autocorrelation. The percentage of continuous proportions is high in cardiac, economic, and mathematical biotic series, and scarce in pink noise and chaos. These findings differentiate creative biotic processes from chaotic and stochastic series. We propose that the widespread 1/f power spectrum found in natural processes represents the integration of the fundamental relation between frequency and energy stated in Planck's law. Natural creativity emerges from determined interactions rather than from the accumulation of accidental random changes.

The pressure exerted on the body by clothes is one important factor affecting the comfort of clothing, it is an effective method to evaluate pressure comfort by physiology and psychology. The purpose of this paper is to measure, electroencephalography (EEG), an index of brain activity in order to examine the effect on brain activity conditions caused by oppression exerted by clothing on the body.

EEG power spectrum analysis was conduct to verify the electrophysiological characteristic of brain caused by pressure on the body by girdle.

Experimental results showed that the intensity of α waves in the pressure condition is decreased compared to the non-pressure condition, and the somatosensory activated by pressure of girdle mainly in occipital, frontal and parietal region of brain.

It was clarified that it is impossible to evaluate the clothes pressure by physiological technique of EEG, this study has enriched methods of evaluation pressure comfort.

Detection of deformation of devices in high voltage electricity transmission line systems is an important issue in terms of economy and reuse. This study is aimed to detect devices that are deformed or thought to have suffered due to environmental and electrical reasons.

In this experimental study, it was ensured that the sound and deformed insulators used in energy transmission lines were determined by the analysis of the sounds obtained by using the impact method. Equal intensity impact was applied to the isolator using the pendulum and the resulting sound noise signal analyses were made using power spectral density (PSD), magnitude scalogram (MS), multitape power spectrum density (MPSD) and continuous wavelet transform (CWT) methods in the study. In the analysis results, the isolators that are not visible to the eye and have certain damage were successfully separated from the intact insulators. Especially, MPSD and CWT analysis results are quite satisfactory.

Damage analysis of insulators used in electricity transmission lines has been made. A total of 40 insulators were examined in two categories in their group, both damaged and not damaged. Data collection system was established. The data obtained from the data collection system were analysed and compared using four analysis methods. PSD, MS, MPSD and CWT analyses were made in the study. All the analyses carried out generally contain features that distinguish damaged and undamaged insulators from each other, the most successful results are MS and CWT results. CWT results are very successful in terms of time and amplitude, and it has been proposed as a method that can be used to separate damaged and undamaged insulators.

It can be suggested as a result of experimental tests that the results of CWT analysis can be used in the pulse noise method in isolators to be tested for reuse in electrical power transmission lines.

The purpose of this paper is to propose applications of advanced signal-processing techniques for the diagnosis and detection of rotor fault in an induction machine. Two techniques are used: spectral analysis techniques and time frequency techniques for the diagnosis of an electrical machine. One is based on the power spectral density estimation techniques, such as periodogram and Welch periodogram. The second method is based on Hilbert transform (HT) to extract the envelope for the stator current. Then, this signal is processed via discrete wavelet transform (DWT) for determining the faulty components in the spectrum of the stator current envelope and identifying the eigenvalues of energies (HDWT).

First, this paper focused on theoretical development and a comparative study of these signal-processing techniques, which are based on the periodogram, Welch periodogram, HT and the DWT to extract the envelope for the stator current; it is used to compute the energy stored in each decomposition level obtained by the stator current envelope (HDWT). Moreover, the Welch periodogram is applied to obtain the envelope spectrum.

The simulation obtained and the experimental validation results of the proposed methods through MATLAB environment show the effectiveness of the proposed approaches with a good accuracy by power spectral density estimation techniques (periodogram and Welch periodogram). Moreover, the faults are manifested through the appearance of new frequencies components, as well as the envelope for the stator current (HT and DWT). This approach is effective for non-stationary and stationary signal to extract useful information for the detection of broken bar fault.

The current paper proposes a new diagnosis method for the detection and characterization of broken rotor bars defects early; it is founded primarily on theoretical development, and the comparison is based on the power spectral density technique (periodogram and Welch periodogram) and the computation of the energy stored in each decomposition level (precisely the HT and DWT). Moreover, the Welch periodogram is applied to obtain the envelope spectrum. The main advantages of the proposed techniques increase their reliability and availability.

The wind speed is very fluctuant and contains a significant energy. Taking into account the turbulent component in the energy management would increase the profitability of the wind‐diesel hybrid system. Sometimes, a diesel generator is used to compensate the requested energy but the storage devices are required to prevent disturbances induced by the wind generator current on the DC‐bus. The purpose of this paper is to show how the battery and flywheel (or ultracapacitors (UCs)) are used to mitigate the fluctuations of the wind generator current. The proposed method is based on the filtering of the wind generator current. The high power density sources (flywheel and UCs) are used in aims to improve the batteries' lifetime, which is estimated, in this paper, by using the rainflow cycles counting method. Spectral studies are made and the simulation and experimental results are analyzed.

This study is organized according to the following main and sub‐topics: wind speed characteristics, hybrid system energy management, behavioral simulations results, spectral analysis and batteries' lifetime estimation and experimental setup and results.

The simulations results highlight the interest in using a second‐order filter. The experimental results show that the fluctuations induced by the wind generator current are effectively mitigated by the storage devices.

The spectral analysis of the current for different filters parameters is realized and the application of the rainflow cycles counting method, in this context, is presented. This paper is interesting for the experimental hybrid system design according to the method proposed to control the DC‐DC converters.

This study aims to analyze the dynamic relationship between the Bitcoin market and the conventional asset classes in India

This paper aims to cast light on the dynamic linkages between Bitcoin prices and other conventional asset classes in India by using the wavelet transform frameworks, which can allow us to analyze components of time series without losing the information. To do that, the techniques used with the data set include wavelet-based covariance, correlation, coherence spectrum, continuous power spectrum and Granger causality test.

The findings of the study suggest that interrelationships between Bitcoin and the key financial asset returns are statistically significant at low, medium and high frequencies. This study also finds the existence of the unidirectional connectedness between Bitcoin the other assets in India.

The outcome of the analysis calls for substantial policy implications for investors, portfolio management in India. This research on the existence of the interconnectedness between Bitcoin and other conventional asset classes in a specific country context, India can, therefore, make a significant contribution to the contemporary debate about the speculative nature of the cryptocurrencies. It casts light on whether Bitcoin provides any diversification and risk management benefits for Indian, as well as global investors.

To the best of the author’s knowledge, this is the first paper investigating the interrelatedness between Bitcoin and key conventional asset classes in India. This research makes methodological advancements by using the wavelet coherence transform. The findings provide empirical bases from which to deal with issues regarding hedging purposes and optimal portfolio allocation for an increasing number of investors in the Indian context. Therefore, the main contribution of this study to related literature in this field is significant.

At the current stage of electrical technology development, it is relevant to take into account the quality of electrical energy. It can be implemented if an assessed energy quality indicator is available. The amount of electrical energy is determined by active power, which is transmitted over a certain time period. In some cases, reactive power is included in the metering system. The distortion power is justifiably criticized and is not taken into account. The purpose of this paper consists in the substantiation of the indicator of the distortion of the periodic polyharmonic current electrical energy power, by separating from the instantaneous power such harmonics, which formed by same frequencies current and voltage harmonics.

Using the method of calculating linear polyharmonic current circuits, the following quantities are identified in instantaneous power: active, reactive and apparent powers of each harmonic. These components are known from references as canonical.

By the method of instantaneous power harmonic analysis, the components formed by current and voltage harmonics of the same frequency and different frequencies are distinguished.

The RMS value of the instantaneous power due to current and voltage harmonics of different frequencies is justified in the work. This quantity allows you to distinguish the instantaneous power distortion level in comparison with the existing quantity.

The results can be used to assess the level of instantaneous power distortion level in commercial and technical metering systems.

The definition of instantaneous power distortion by extracting the canonical components from it and determining the root mean square value of the remainder is proposed.