Time-Domain Energy Detection

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TEXTURE PATTERN IN ABNORMAL MAMMOGRAMS CLASSIFICATION USING SUPERVISED MACHINE 
LEARNING TECHNIQUES

TEXTURE PATTERN IN ABNORMAL MAMMOGRAMS CLASSIFICATION USING SUPERVISED MACHINE LEARNING TECHNIQUES

Voice activity detection (VAD) is a main process of speech recognition tasks in which every voice region is detected to extract acoustic feature parameters from the region. This paper proposes an efficient VAD approach for applying to real-time voice interface systems. Even though diverse VAD approaches have been successfully applied for speech applications, they may operate inefficiently according to environmental conditions. In this study, we attempt to enhance the conventional VAD method based on signal energy within time and spectral domain. In addition, an efficient end-point detection method is also proposed. We successfully verified the efficiency of the proposed approach via a set of VAD experiments, comparing with the performance of some conventional VAD methods including zero crossing rate.
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Newborn EEG Seizure Detection Based on Interspike Space Distribution in the Time-Frequency Domain

Newborn EEG Seizure Detection Based on Interspike Space Distribution in the Time-Frequency Domain

Abstract This paper presents a new time-frequency based EEG seizure detection method. This method uses the distribution of interspike intervals as a criterion for discriminating between seizure and nonseizure activities. To detect spikes in the EEG, the signal is mapped into the time-frequency domain. The high instantaneous energy of spikes is reflected as a localized energy in time-frequency domain. Histogram of successive spikes intervals is then used as a feature for seizure detection. In the presented technique the EEG data are segmented into 4-second epochs. A k-nearest neighbor algorithm is employed to classify the EEG epochs into seizure and nonseizure groups. The performance of the presented technique is evaluated using the EEG data of five neonates. The results indicate that the proposed technique is superior to the other existing methods with 92.4 % good detection rate and 4.9 % false detection rate.
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Grain Size Measurement in Steel by Laser Ultrasonics Based on Time Domain Energy

Grain Size Measurement in Steel by Laser Ultrasonics Based on Time Domain Energy

Laser ultrasonics, a technique based on the generation of ultrasonic waves by a pulsed laser and on their detection by a laser interferometer, can be used to determine grain sizes in steels. The absolute values of the average grain size can be calculated directly from the attenuation measurements of ultrasonic longitudinal bulk waves. The general methods of attenuation measurements are computed based on the amplitude of longitudinal waves. In fact, the amplitude as only one value is infected by the noise. Besides, the attenuation should be considered as the energy reduction. The method of time domain energy is proposed to compute the attenuation. The results indicate that time domain energy can improve the accuracy of the grain size prediction. The laser ultrasonic technique may be incorporated online for direct measurements of grain size during steel production. [doi:10.2320 / matertrans.M2014445]
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Real Time Power Monitoring Detection  Based on Sequence Time Domain Reflectometry Approach

Real Time Power Monitoring Detection Based on Sequence Time Domain Reflectometry Approach

In order to transfer data between sender and receiver, it should be more than one message transmitting from sender and receiving by receiver. Simple method is by sending a pure impulse signal and measuring the time delay of signal in the medium. But amount of total energy’s short pulse is limited and even by in- creasing the time duration to transmit more total energy, getting a sharp peak of time delay in correlation would be difficult. Therefore, by generating and apply- ing a proper coded signal, the duration can be increased while the total trans- mitted energy increasing as much as maintaining the sharp peak in correlation. Hence m-sequence is being used in STDR method [12].
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A time-domain control signal detection technique for OFDM

A time-domain control signal detection technique for OFDM

In addition, studies from, for example, [24] and [25] sug- gest that a time-domain approach is more robust against severe ISI compared with the frequency-domain method of channel equalization. This was partly due to the par- tial elimination of the channel tap with the most energy in the time-domain [26]. These principles form the basis behind the use of the time-domain estimation technique considered in this paper.

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INTERACTING THROUGH DISCLOSING: PEER INTERACTION PATTERNS BASED ON 
SELF DISCLOSURE LEVELS VIA FACEBOOK

INTERACTING THROUGH DISCLOSING: PEER INTERACTION PATTERNS BASED ON SELF DISCLOSURE LEVELS VIA FACEBOOK

A considerable amount of literature has reported the advantages of wavelet as transformation domain in automated seizure detection technique as it had superior resolution and high performance for visualization and representation of epilepsy activity [8], [16], apart it is suitable to analyse non-stationary signal [22]. Often, energy is extracted in each wavelet decomposition level as a feature due to high energy discharge during seizure caused by excessive neuronal activity [3] compared to non–seizure. Amplitude dispersion is another good feature to distinguish between seizure and non-seizure due to the dispersing of amplitude during seizure activity [23]. Approximate entropy (ApEn) has shown a good performance as feature in previous research to characterize the regularity of signal [24]. It is worth noting that, time-frequency analysis using discrete wavelet transformation (DWT) will increase the number of features depending on the wavelet decomposition level as the features need to be extracted in each level [24], [25]. This may increase the number of non-relevant features during this transformation, resulting in higher computational demands and poor performance [26].
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Improved local spectrum sensing for cognitive radio networks

Improved local spectrum sensing for cognitive radio networks

To improve the existing techniques, one-order cyclos- tationary detection in the time domain is proposed in [15], where the mean characteristic of the PU signal is exploited in order to improve the efficiency of channel sensing. Both real-time operation and low computational complexity can be achieved using this detection scheme. In [16], the energy detection technique is improved by replacing the squaring operation with arbitrary positive power operation. Power operation depends on the prob- ability of false alarms, the probability of detection, the average SNR, and the sample size. By choosing the value of the power operation, detection performance of a con- ventional energy detector can be improved. Advanced sensing techniques for energy detection, including mul- tiple antenna sensing and cooperative sensing, are dis- cussed in [17].
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Domain and Time Domain Approaches in Forecasting Techniques

Domain and Time Domain Approaches in Forecasting Techniques

[4] Atikinson, A.C. (1970), “A Method for Discriminating Between Models”, Journal of the Royal Statistical Society B, 32, 323-353. [5] Box, G.E.P., and Jenkins, G.M. (1976), “Time Series Analysis, Forecasting and Control”, Rev. ed. San Francisco: Holden-Day. [6] Davidson, R., and MacKinnon, J.G. (1993), “Estimation and Inference in Econometrics”, New York : Oxford University Press. [7] Eubank, R.L., and Hart, J.D. (1992), “Testing Goodness-of-Fit in Regression Via Order Selection Criteria”, Ann. Statist, 20, 1412-1425. [8] Fan, J. (1993), “Local Linear Regression smoothers and Their Minimax Efficiencies”, Annals of Statistics”, 21, 196-216.
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Stability Analysis of Wind/Diesel/Storage Renewable Energy System: Time Domain Simulation

Stability Analysis of Wind/Diesel/Storage Renewable Energy System: Time Domain Simulation

This kinetic energy formulation is based on the fact that the mass of the solid is constant. However, if we consider wind (air in motion) as a fluid, both density and velocity can change and hence no constant mass. For this reason [9] formulated the kinetic energy law with a factor of 2/3 instead of 1/2. In this work we shall assume that the density of air does not vary considerably even with variation in altitude or temperature and use the kinetic energy law in the form of equation (9). Hence the kinetic energy (in joules) in air of mass (m) moving with velocity V WS (wind) can be calculated from equation (9) above. The power (P)
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Point absorber wave energy converters in regular and irregular waves with time domain analysis

Point absorber wave energy converters in regular and irregular waves with time domain analysis

command has to be equal to its extremal values (0 or 1) in order to maximise Hamiltonian, has to be formulated by a weaker model to implement this theory with a good numerical efficiency. When absolute latching control is applied, a force is applied on the body that instantaneously cancels the acceleration of the motion in order to lock the system temporarily. In the weak modelling, this force is replaced by a very large (but not infinite) damping force. Thus, latching control is modelled by adding a large control force in the equation of motion. The main advantage of optimal command is that it can straightforwardly deal with random waves as well as regular waves and can be used with any kind of WEC. In addition, optimal command method can be used to assess the benefit that latching control can bring to the efficiency of WEC. A major interest of this method is that it can deal with WEC with more than one degree of freedom provided the equations of motion are written under a state form in regular and irregular waves in order to apply optimal control theory. In the time domain, non-linear components of forces (like hydraulic Power- Take-Off) can be introduced straightforwardly.
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Density Detection of Aligned Nanowire Arrays Using Terahertz Time Domain Spectroscopy

Density Detection of Aligned Nanowire Arrays Using Terahertz Time Domain Spectroscopy

A rapid technique is necessary to quantitatively detect the density of nanowire (NW) and nanotube arrays in one- dimensional devices which have been identified as useful building blocks for nanoelectronics, optoelectronics, biomedical devices, etc. Terahertz (THz) time-domain spectroscopy was employed in this research to detect the density of aligned Ni NW arrays. The transmitted amplitude of THz peaks and optical thickness of NW arrays was found to be the effective parameters to analyze the density change of NW arrays. Owing to the low multiple scattering and high order of Ni NW arrays, a linear relationship was observed for the transmitted amplitude and optical thickness regarding NW density, respectively. Therefore, THz technique may be used as a promising tool to characterize the density of one-dimensional structures in the large-scale integrated nanodevice fabrication.
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Time and the domain of consciousness

Time and the domain of consciousness

Applied to the passage from Weyl quoted above, the kind of thought Dummett has in mind runs as follows. In suggesting that the gaze of consciousness ‘crawls’ along the world-line of my body, Weyl himself seems committed to the idea that, just as the A-theorist maintains, there is something that is left out by simply representing me as such a world-line, because something about that world-line itself changes over time. More specifically, the particular change in question is a matter of passage: the successive becoming present of different

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Effective electrodynamics theory for the hyperbolic metamaterial consisting of metal-dielectric layers

Effective electrodynamics theory for the hyperbolic metamaterial consisting of metal-dielectric layers

Recently, hyperbolic metamaterials belonging to the category of anisotropic media have received more and more attention [31-35]. The hyperbolic dispersion of this kind of metamaterials are caused by the opposite signs of the two principal values of the permittivity tensor along and perpendicular to the optic axis. One of the most important applications of hyperbolic metamaterial is the hyperlens [35], which can image subwavelength objects in the far-field region, overcoming the shortcomings of the superlens [1,3] that can only image the same objects in the near-field region. The simplest example of a hyperbolic metamaterial is a dielectric-metal multilayer structure that operates under the long- wavelength limit [35]. Although it seems that such metamaterials are much simpler than the wire- SRR and chiral metamaterials, to the best of our knowledge, the energy density problem and the Lagrangian description for this kind of metamaterials have not yet been studied. This is the main motivation of our present study. In addition, a better understanding about the energy density, Lagrangian description, and Hamiltonain theory for the hyperbolic metamaterial can help researchers further explore the dynamical behaviors of EM waves in this kind of media without being restricted to the frequency domain phenomena. This may have practical importance in the future. The Lagrangian and Hamiltonian descriptions also provide a starting point for the development of quantum description of the electrodynamics in the metamaterials [30].
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Evaluation of spectral domain and time domain optical coherence tomography findings in toxoplasmic retinochoroiditis

Evaluation of spectral domain and time domain optical coherence tomography findings in toxoplasmic retinochoroiditis

Figure 3 Baseline fundus photography. green arrows show the scan acquisition protocol used by spectral domain optical coherence tomography. A, C, and e are from the volume scans at baseline, and g, a linear scan from the fovea to the lesion. B, D, F, and h correspond to the same points at follow up. Vitreoschisis (asterisk) can be noticed at baseline A) and after 6 weeks B). note the expanded vitreous detachment at follow up. Subretinal fluid at the lesion site (arrowhead) is seen at baseline E) with resolution after 6 weeks F). The triangle shows the retinochoroidal lesion increased thickness at baseline (C, G) and atrophy at follow up (D, H).
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Performance Analysis of Two-Stage Spectrum Sensing for Cognitive Radio Networks

Performance Analysis of Two-Stage Spectrum Sensing for Cognitive Radio Networks

Communication networks, either it is wired and wirelesses, plays a very important role in each aspect of modern life: social, economic, healthcare, and others. During the last two decades, there has been a huge demand for wireless communication services, due to increase in consumer electronics applications and personal high-data-rate networks. Due to the ever-growing demand for the radio spectrum and the exclusive access to licensed bands, it has become challenge for the Federal Communications Commission (FCC) and regulators of many countries to allocate radio spectrum for new wireless services [1]. However, studies shows that allocated licensed band frequencies are largely underutilized in specific regions. It is observed that at any location at any given time around 85-90% of the licensed radio spectrum is not in use. Cognitive radio has emerged as a solution [14] to the problem of low spectral occupancy and inefficient utilization of the licensed radio spectrum. It enables the unlicensed users to access the licensed band without violating the exclusive usage facility for the licensed user. It identifies the unused portions of the licensed spectrum known as spectrum holes and makes them available for unlicensed or secondary users. Cognitive Radio cycle has the following function [4] as shown:
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Adaptive Linear Prediction Filtering in DWT Domain for Real-Time Musical Onset Detection

Adaptive Linear Prediction Filtering in DWT Domain for Real-Time Musical Onset Detection

Onset detection is a typical digital signal processing task in acoustic signal analysis, with many applications as in the musical field. Many techniques have been proposed so far, which are typically reliable in terms of performances but often not suitable to real-time computing, for example, they require knowledge of the whole piece to perform optimally, or they are too computationally intensive for most embedded processors. Up to the authors’ knowledge, the real-time implementation problem for musical onset detection has been scarcely addressed within the literature, which has motivated them to propose a scalable and computationally efficient algorithm with good detection capabilities. Comparison with other techniques and porting to a real-time embedded processor are discussed as well: provided experimental results seem to confirm the effectiveness of the approach.
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Condition Monitoring of Ball Bearing Using Vibration Analysis and Feature Extraction

Condition Monitoring of Ball Bearing Using Vibration Analysis and Feature Extraction

The typical failure mode of ball bearing is fault or scratch on surface which is the result of surface fatigue, caused by the repeated loading of the shaft and it is difficult to avoid in operating conditions. Thus the main problem of malfunction detection of bearing is to examine whether there is a surface defect on the bearing. When a defective surface contacts with its matching surface it will produce a short pulse that may excite the resonances of the bearing assembly. If the bearing is rotating at a constant speed, the contact pulse will occur periodically with a frequency which is a function of a bearing geometry, the rotational speed and the crack location [4]. For on-line monitoring purposes, it is always desirable to reduce the large amount of information contained in the on-line vibration signal to a single index or small number of features that reflects the overall characteristics of the signal. This procedure, known as signal feature extraction [5].
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Energy Conservation In Commercial Places Based On Real Time Occupancy Detection

Energy Conservation In Commercial Places Based On Real Time Occupancy Detection

This paper aims at conserving energy by estimating the crowd density level at indoor environments such as auditoriums, showrooms, supermarkets and calculating the exact cooling capacity required as per the guidelines given by Energy Star [8] and Natural Resources Canada [11] for adjusting variable capacity air-conditioning systems that have the ability to vary their cooling capacity over a wide range from 35% to 100% [12]. A bi-directional people counter based on video image processing has been proposed for counting people in indoor environments. The system captures object information using CCTV camera, analyses the captured data using video processing and pattern recognition technology and computes crowd density. The exact tonnage required is calculated as per the guidelines of Energy Star [8]. Finally the system adjusts the tonnage of variable capacity air-conditioner to the exact tonnage required.
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Real Time Detection of Unstable Control Loop Behavior in a Feedback Active Noise Cancellation System for In Ear Headphones

Real Time Detection of Unstable Control Loop Behavior in a Feedback Active Noise Cancellation System for In Ear Headphones

structure is the risk of instability, which is expressed in an overdrive and eventual destruction of the speakers or even damage of the user’s inner ear. In [1] for example, this problem is overcome by limiting the controller gain. Additionally, practical applications in general limit the actual speaker output or at least deactivate the controller output in case of an overdrive. Thus, conventional solutions either act preemptively or in response to the already unstable state, still exposing the listener to a potential danger. This results in the need to continuously observe the behavior of the control loop during run-time, in order to detect the possibly occurring unstable state at an early stage. In this paper, various methods are compared, which yield an estimation of the control loop state on the basis of the microphone and speaker signals to realize a real-time analysis.
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Control of Wave Energy Converters for Maximum Power Absorption with Time Domain Analysis

Control of Wave Energy Converters for Maximum Power Absorption with Time Domain Analysis

WEC without control traps energy only from the wave components whose frequency lies in the band of the natural frequencies of the system. Nevertheless, this system is potentially able to catch energy in the wave spectrum outside this band provided it can be dynamically controlled to adapt its bandwidth in real time. In this way, the power output from WEC can be increased by controlling the oscillation in order to approach an optimum interaction between WEC and incident wave. Optimum control methods can be classified for WEC as reactive (continuous) and latching (discrete) controls. Applying reactive control to WEC allows absorption of the maximum power [12]. In reactive control, the applied force/moments are a continuous function of time, and generally include resistive and reactive components to approach resonance at wave frequencies lower than the natural frequency of WEC. In latching control [11] while the motion is locked, the wave exciting force continues to evolve. Latching control involves braking and releasing the oscillating body such that its velocity bears the desired phase relationship with the wave-applied exciting force.
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