5D Spectrum Database

PurposePenetration state is one of the most important factors for judging the quality of a gas tungsten arc welding (GTAW) joint. The purpose of this paper is to identify and classify the penetration state and welding quality through the features of arc sound signal during robotic GTAW process.Design/methodology/approachThis paper tried to make a foundation work to achieve on‐line monitoring of penetration state to weld pool through arc sound signal. The statistic features of arc sound under different penetration states like partial penetration, full penetration and excessive penetration were extracted and analysed, and wavelet packet analysis was used to extract frequency energy at different frequency bands. The prediction models were established by artificial neural networks based on different features combination.FindingsThe experiment results demonstrated that each feature in time and frequency domain could react the penetration behaviour, arc sound in different frequency band had different performance at different penetration states and the prediction model established by 23 features in time domain and frequency domain got the best prediction effect to recognize different penetration states and welding quality through arc sound signal.Originality/valueThis paper tried to make a foundation work to achieve identifying penetration state and welding quality through the features of arc sound signal during robotic GTAW process. A total of 23 features in time domain and frequency domain were extracted at different penetration states. And energy at different frequency bands was proved to be an effective factor for identifying different penetration states. Finally, a prediction model built by 23 features was proved to have the best prediction effect of welding quality.

The essential task of a Brain-Computer Interface (BCI) is to extract the motor imagery features from Electro-Encephalogram (EEG) signals for classifying the thought process. It is necessary to analyse these obtained signals in both the time domain and frequency domains. It is observed that the combination of multiple algorithms increases the performance of the feature extraction process. This paper identifies combinations that have not been attempted previously and improves the accuracy of the overall process, although other authors implemented different combinations of the techniques. The focus is given more on the feature extraction process and frequency bands, which are user-specific and subject-specific frequency bands. In both time and frequency domains, after analysing EEG signals with the time domain parameter, we select the frequency band and the timing while using the Fisher ratio of the time domain parameter (TDP). We used Fisher discriminant analysis (FDA)-type F-score to simultaneously select the frequency band and time segment for multi-class classification. We extracted subject-specific TDP features from the training trials to train the classifier when optimal time-frequency areas were selected for each subject. In this paper, various methods are explored for obtaining the features, which are Time Domain Parameters (TDP), Fast Fourier Transform (FFT), Principal Component Analysis (PCA), R2, Fast Correlation Based Filter (FCBF), Empirical Mode Decomposition (EMD), and Intrinsic time-scale decomposition (ITD). After the extraction process, PCA is used for dimensionality reduction. An efficient result was obtained with the combination of TDP, FFT, and PCA. We used the multi-class Fisher’s linear discriminant analysis (LDA) as the classifier, which was in line with the FDA-type F-score. It is observed that the combination of feature extraction techniques to the frequency bands that were selected by the Fisher ratio and FDA type F-score along with Fisher’s LDA classifier had higher accuracy than the results obtained other researches. A kappa coefficient accuracy of 0.64 is obtained for the proposed technique. Our method leads to better classification performance when compared to state-of-the-art methods. The novelty of the approach is based on the combination of frequency bands and two feature extraction methods.

In recent years, as more devices are connected to wireless communication systems, the demand for spectrum has increased. As conventional spectrum resources are limited, the THz band becomes an interesting option of more spectrum for wireless communication. However, the channel in THz band has different characteristics compared to the channels in typical frequency bands, and therefore, it is necessary to perform more research to understand the THz channel propagation. In this paper, we focus on the time domain THz channel model under line of sight (LoS) propagation conditions and investigate the channel propagation characteristics in time domain. Firstly, in the full frequency band (FFB) scenario, the time domain impulse responses, which correspond to the time domain THz channel model, are presented for different distances. In the impulse responses, there are significantly delayed paths due to the molecular absorption which causes significant frequency selectivity. Secondly, we extend the model to the limited frequency band (LFB) scenario by applying the root raised cosine filters. The results indicate that the richness of the delayed paths in the impulse response depends on the selected frequency band. In addition, the results indicate that the time delay and total energy strongly depend on the distance whereas the delay spread varies as a function of frequency.

This study examines international synchronization of growth rate cycles using spectral techniques in the frequency domain. In particular, we look at synchronization of growth rate cycles between bilateral country pairs, US, UK, Germany, Japan and India over the period from January 1974 to December 2018. We examine two aspects of the synchronization process—one, strength of co-movement across countries’ growth rate cycles, and two, sequencing in terms of leads and lags of these cycles vis-à-vis each other. The strength of co-movements is analyzed using coherences of growth rate cycles between bilateral country pairs across frequency bands and over time. The lead–lag structure between growth rate cycles of countries is obtained from the spectral phase shift parameter. This is evaluated against the lead–lag structure in the time domain, as inferred from the reference chronology given by the Economic Cycle Research Institute (ECRI). Based on the growth rate of the coincident index obtained from ECRI, we infer the sequencing of growth rate cycles in one country vis-à-vis the other in terms of the relative timing of their peaks and troughs. This comparative analysis across the time and frequency domains highlights both the pattern of lead–lag in terms of timing of peaks and troughs (time domain) as well as the lead–lag in terms of all phases of the cycle (frequency domain). For analyzing these patterns over time, we undertake the exercise over two subsamples: January 1974–December 1990 and January 1991–December 2018. We find that the coherence between developed country pairs is, in general, higher than that between developed–emerging economy pairs. We also find evidence of greater co-movement of country cycles post-1990, as compared with that in 1974–1990. The magnitude of leads–lags shows that the synchronization process is faster in the latter time period. The leads–lags obtained from the spectral phase shift estimates are found to be in line with those inferred from economic indicator analysis (EIA).

Heart period variability has been considered for clinical assessment of autonomic function, determining the presence of haemorrhage or disease states, and for predicting mortality from traumatic injury. However, for heart period variability to be clinically useful, a number of important methodological issues should be addressed, including the minimum number of R-R intervals (RRI) required for accurate derivation, and the reproducibility of these metrics. ECGs were recorded for > or =10 min in 18 resting, supine subjects (12 M/6 F; 19-55 years). Heart period variability analyses included 21 time, frequency and complexity domain metrics. For assessment of minimum RRIs required, measurements were made from ECG recordings of 5 min down to 30 s for time and frequency domain metrics, and from 800 RRIs down to 100 RRIs for complexity metrics, by methodical truncation of the data set. Inter-subject variability was assessed by calculating the range and co-efficient of variation (%CV) across all subjects. Two independent 30 s or 100 RRI ECG segments were used to assess intra-subject variability via calculation of %CV in each subject. Six time and frequency domain metrics were robust down to 30 s of data, while five complexity metrics were robust down to 100 RRIs. All time and frequency domain metrics (except for RRI) exhibited high inter-subject variability (CVs > or = 30.0%), while five of eleven complexity metrics displayed low inter-subject variability (CVs < or = 8.5%). In the assessment of intra-subject variability in metrics valid with 30 s or 100 RRIs of ECG, only one time domain and four complexity metrics had CVs < 10%. Metrics that are highly reproducible and require few RRIs are advantageous for patient monitoring as less time is required to assess physiological status and initiate early interventions. Based on our analyses from healthy, resting humans, we have identified a select cohort of heart period variability metrics that performed well in regards to these two criteria.

ACOUSTIC liners are widely used in industry for noise reduction. They are indispensable noise-suppression devices for jet engines. Acoustic liners are effective over a wide band of frequencies. To account for such characteristics, broadband impedance models are used for time-domain computation. The acoustic impedance of a surface, Z ! , is originally defined in the frequency domain. Problems involving noise propagation over impedance surfaces may be solved in the time domain. Time-domain methods have obvious advantages over frequency-domain methods for broadband and nonlinear problems. However, because an impedance boundary condition is set up for use in the frequency domain, an equivalent time-domain impedance boundary condition is needed. Mathematically, the time-domain equivalent may be derived by taking its inverse Fourier transform. For the equivalent time-domain impedance condition to be physical, the impedance function must be causal, real, and passive [1]. In general, the inverse Fourier transform of a frequency-domain impedance boundary condition would lead to a convolution integral. Computation of the convolution integral is time consuming. However, if the impedance can be represented by a sum of certain special functions, the evaluation of the convolution may be carried out in a simple systematic manner. Tam and Auriault [2] introduced a three-parameter time-domain impedancemodel. Thismodel can provide accurate representation of liner impedance for single discrete frequency problems. But the three-parameter model cannot offer a general representation of liner impedance over awide band of frequencies. Rienstra [1] proposed an extended Helmholtz resonator model. The free parameters of the model are the geometrical dimensions of the resonator. The impedance of the model is derived by the response of the Helmholtz resonator to periodic acoustic input. A comparison study by Richter et al. [3] indicated that a numerical instability could occur in some cases. A filtering technique has to be applied for avoiding this problem. Recently, Reymen et al. [4] developed a new and efficient time-domain impedance boundary condition based on the use of recursive convolution. The key to their method is the representation of the impedance by a series of simple poles in the complex plane. For the method to work efficiently, the value of the function in the convolution integral within a time step must be approximated by a linear or quadratic function. This impedance model has been proven to be physical, causal, and real. The primary objective of this paper is to develop an improved multipole broadband time-domain impedance boundary condition. A secondary objective is to derive an analytical solution for problems involving damping of broadband acoustic input by liners with broadband impedance characteristics. These solutions may serve for benchmarking numerical computations involving broadband sound. This paper is organized as follows. Section II discusses the improved multipole broadband impedance model. The implementation of the time-domain impedance boundary condition is presented in Sec. III. Section IV presents analytical solutions of twodimensional problems with broadband incident acoustic waves. These solutions are then used to validate numerical results with a liner having broadband impedance properties. Section IV concludes this work.

With the advancement of information and communication technologies (ICTs), the way we live and communicate with each other is changing rapidly. As urban environments continue to evolve, the smart sustainable city (SSC) has sparked considerable attention. We are hoping for a new era in which numerous devices and machines including vehicles, sensors, and robots are all connected to communicate, respond, and operate in real time. The next-generation communication system, the sixth generation (6G), is expected to play a crucial role in improving the efficiency of urban operations and services. In this paper, we first provide the recent trends and key features of standardization in the SSC. To make the future SSC, we highlight key candidate technologies of 6G such as non-terrestrial networks, advanced mobile edge computing, vision-aided wireless communication, artificial intelligence (AI)-based wireless communication, and integrated sensing and communication. We put forth the main technical challenges given to each prime technology along with the potential benefits to pave the way for 6G-enabled SSC. We further address how the potential benefits of prime technologies enable various urban practice cases for 6G-enabled SSC.

This paper presents the latest achievements with respect to 3GPP Release-17 adjacent band coexistence simulation work on 5G New Radio Non-Terrestrial Networks (NTNs) for satellite communications. For the first time, 3GPP considered the introduction of Mobile Satellite Service (MSS) frequency bands for 3GPP User Equipment (UE) direct connectivity with satellites and had to consider the coexistence in adjacent bands with Terrestrial Networks (TNs). This paper will further explain the most challenging and the main surprising outcomes of this work, which opened new market opportunities for both terrestrial and non-terrestrial stakeholders. The main conclusions can be summarized as (1) NTN UE can reuse the current requirements of the TN UE, (2) the satellite connectivity does not require a dedicated satellite waveform, and (3) TN can co-exist with NTN on adjacent channels with relaxed ACIR requirements for the tested simulation scenario.

Summary This paper presents the latest achievements concerning 3GPP Release‐17 adjacent band coexistence simulation work on 5G new radio non‐terrestrial networks (NTNs) for satellite communications. For the first time, 3GPP considered the introduction of mobile satellite service (MSS) frequency bands for 3GPP user equipment (UE) direct connectivity with satellites and had to consider the coexistence in adjacent bands with terrestrial networks (TNs). This paper will further explain the most challenging and the main surprising outcomes of this work, which opened new market opportunities for both terrestrial and non‐terrestrial stakeholders. The main conclusions can be summarized as follows: (1) NTN UE can reuse the current requirements of the TN UE, (2) the satellite connectivity does not require a dedicated satellite waveform, and (3) TN can co‐exist with NTN on adjacent channels with relaxed ACIR requirements for the tested simulation scenario.

Third order time and frequency analysis has exhibited great potential for correlation analysis of multi-sensor datasets, but is usually presented as separate time domain and frequency domain approaches. A combined framework of both frequency domain and time domain has rarely been used. This paper proposes a non-parametric third order time and frequency domain framework which used two dimensional Fourier transforms to bridge the gap between time domain and frequency domain. A unified framework offers flexibility and efficiency to apply to data. In this paper we study neural spike train data treated as stochastic point processes. In time domain direct analysis, third order cumulant densities of spike trains are applied, which need all first-, secondand third order product densities to be calculated before constructing the third order cumulant density, which brings additional challenges. The novelty in this study is that a new framework is proposed which can offer an alternative approach without calculating lower order quantities and can reveal nonlinear relationship between neural recordings. The results show that the present framework provides a novel non-parametric method to estimate both time and frequency domain measurements which is applicable to neural spike trains.

A fundamental problem for signal processing in wireless communications is the separation multiple signals/users from their mixture. The problem would be simpler if they are non-overlapping in either time domain or frequency domain. Two signals may be overlapping in both time and frequency, but they still can be easily separated if they are uncorrelated (orthogonal), like in Code Division Multiple Access system (CDMA). It may be interesting to know that two signals may be overlapping in both the frequency and time domain and also are not orthogonal to each other, but they can still be separated if each autocorrelation function at the receiver is separable in the domain of time-lags. In this paper, we will show how the Noise-Loop (NL) modulation, originally thought to produce security at physical layer, can be used to effectively separate uncoordinated/unorthogonal users sharing the same time and frequency band. In order to show the potential of noise-loop multiple access (NLMA) scheme, the theoretical solution is derived as well as numerical semi-analytical simulations. It can be shown that the NLMA is able to distinguish the bit stream of the users. This feature together with the intrinsic security make the NL an interesting scheme for wireless technology.

We describe the main properties of the EQUATOR airborne geophysical system and how the system can be employed to solve some engineering and environmental problems. To date, the EQUATOR system has been used for groundwater search in 2014 and 2015 in Siberia. The name “EQUATOR” originates from the intention to EQUATE, or to balance time and frequency domain approaches in airborne electromagnetics, which is why the system was originally designed. To the best of our knowledge, EQUATOR is the only system to collect electromagnetic data both in time and in frequency domains. We further explain the difference between the two methods on some numerical and field examples. Also we describe some advantages of their coupling. In particular, by virtue of our approach, a numerically more robust solution of the one-dimensional electromagnetic inverse problem may be achieved. The recorded full-time measurements are further converted to in-phase, quadrature and off-time responses, as opposed to standard frequency or time domain solutions, which have been widely adapted within the industry. When inverting the data, our main focus is within the top 100 m of the Earth, which are the most relevant for engineering and environmental studies. We emphasize that a combined use of frequency and time domain data gives more detailed information about geological structures in the near-surface. As an example, we present some case studies obtained over a platform (Siberia) and a crystalline shield (Western Africa) setting. We further suggest using these results in such near-surface studies as sediment thickness estimation, soil state analysis, groundwater search, and geological structural analysis.

Prediction of countershock success using single features from multiple ventricular fibrillation frequency bands and feature combinations using neural networks

IntroductionThe popularity of mobile communication systems has increased remarkably during the last decade and the market demand still continues to increase.As a fundamental part of these systems, antenna is one of the most important design issues in modern mobile communication units.Although there are several similar definitions, an antenna can be mainly described as a device, which transforms the electromagnetic waves in an antenna to radiating waves in an unbounded medium such as air in transmitting mode and vice versa in receiving mode.Because antennas are dependent on frequency, they are designed to operate for certain frequency bands.The rapid growth of mobile communication systems has forced to the use of novel antennas for base and mobile station applications (mobile phone, notebook computer, personal digital assistants (PDA), etc.).Earlier, mobile systems were designed to operate for one of the frequency bands of 2G (second generation) systems, which are Digital Cellular System (DCS), Personal Communications Service (PCS) and Global System for Mobile Communications (GSM) networks.Currently, many mobile communication systems use several frequency bands such as GSM 900/1800/1900 bands (890-960 MHz and 1710-1990 MHz); Universal Mobile Telecommunication Systems (UMTS) and UMTS 3G expansion bands (1900-2200 MHz and 2500-2700 MHz); and Wi-Fi (Wireless Fidelity)/Wireless Local Area Networks (WLAN) bands (2400-2500 MHz and 5100-5800 MHz) where the list of frequently used frequency bands is given in Table 1 ( Best, 2008).Conventionally, because a single antenna can not operate at all of these frequency bands of mobile communication, multiple different antennas covering these bands separately should be used.However, usage of many antennas is usually limited by the volume and cost constraints of the applications.Therefore, multiband and wideband antennas are essential to provide multifunctional operations for mobile communication.A multiband antenna in a mobile communication system can be defined as the antenna operating at distinct frequency bands, but not at the intermediate frequencies between bands.For example, a triple band antenna for GSM 900/1800/1900 bands can cover the frequency bands 890-960 MHz and 1710-1990 MHz (Ali et al., 2003); however, it does not operate properly at the frequencies such as 1200 MHz or 2500 MHz.On the other hand, a wideband antenna operates at every frequency points within a given frequency band.For example, a wideband antenna covering UMTS, extended UMTS and WLAN 2400 bands functions at every frequency points www.intechopen.com

Multi-window spectrum analysis of Búzios oil field PSDM seismic data applied to frequency attenuation study