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In this paper, an experimental validation of a numerical procedure for estimating the structure-borne Underwater Radiated Noise (URN) Transfer Function (TF) of a marine structure based on the SEA theory has been performed. For the purpose, the structure-borne URN TF of a central point-excited one-side fluid-loaded four-edge stiffened plate in a reverberant water tank has been measured and compared with the SEA result. Additionally, the practical applicability of the procedure for a real ship structure has been demonstrated by comparing the URN analysis result based on the transfer function method and the measurement result for a Korean research vessel, ‘Cheong-Hae’. From the results, it is confirmed that the presented procedure can be used to estimate the structure-borne URN level emitted from the vibrating fluid-loaded side shells of a ship structure.

Purpose: The Radiofrequency (RF)‐induced heating for an active implantable medical device (AIMD) with dual parallel leads is evaluated in this paper. The coupling effects between dual parallel leads are studied via simulations and experiments methods. The global transfer function technique is used to assess the RF‐induced heating for dual‐lead AIMDs inside four human body models. Methods: RF‐induced heating for spinal cord stimulator systems with 60 and 90 cm length leads are studied at three parallel dual‐lead configurations (closely spaced, 8 mm spaced, and 40 mm spaced) and a single‐lead configuration. The global transfer function method is used to develop the AIMD models of different configurations and is used for lead‐tip heating assessments inside human body models. Results: In simulation studies, the peak 1g specific absorption rate/temperatrue rises of dual parallel leads systems is lower than those from the single‐lead system. In experimental American Society for Testing and Materials phantom studies, the temperature rises for the single‐lead AIMD system can be 2.4 times higher than that from dual‐lead AIMD systems. For the spinal cord stimulator systems used in the study, the statistical analysis shows the RF‐induced heating of dual‐lead configurations are also lower than those from the single‐lead configuration inside all four human body models. Conclusion: For the AIMD system in this study, it shows that the coupling effects between the dual parallel leads of AIMD systems can reduce RF‐induced heating. The global transfer function for different spatial distance dual‐lead configurations can potentially provide a method for the RF‐induced heating evaluation for dual‐lead AIMD systems. [ABSTRACT FROM AUTHOR]

To speed up the process for designing finite thinned arrays, an efficient artificial neural network (ANN) model considering mutual coupling effects is proposed in this communication. Array elements are divided into three categories based on the active element pattern (AEP) technique, and subarrays are constructed to extract the AEP of each category of elements as training samples. The proposed model including parallel ANN branches takes into account the mutual coupling between elements and avoids the calculation of the radiation pattern of the entire array. To improve modeling performance, furthermore, a prior knowledge input technique is used to reduce the complexity of the input–output relationship that an ANN has to learn. The existing knowledge is obtained by back propagation (BP) ANN modeling. Once the knowledge-based model is well trained, it is repeatedly called by the genetic algorithm (GA) for the optimal solution as a substitute for the full-wave simulation. Numerical examples of a U-shaped slot thinned array and a dual-layer patch thinned array are utilized to verify the efficiency of the proposed scheme. [ABSTRACT FROM AUTHOR]

The Fourier series is introduced as a transfer function (TF) in the artificial neural network (ANN) for parametric modeling of microwave filters in this letter. The reported pole-residue-based TF leads to an order-changing problem of input samples from vector fitting, which is usually solved with an order-tracking technique or data classification. The proposed Fourier series-based TF does not have to carry out the time-consuming operation because the only coefficient order can be determined for all input samples in an iterative process. Compared with the pole-residue-based TF, moreover, the ANN training involves a small number of TF coefficients in the proposed method. The predicted electromagnetic (EM) response is obtained from the coefficients of the ANN output. An example of the ultrawideband (UWB) filter is employed to verify the effectiveness of the Fourier series-based TF. [ABSTRACT FROM AUTHOR]

Purpose: During MR scans, abandoned leads from active implantable medical devices (AIMDs) can experience excessive heating at the lead tip, depending on the type of termination applied to the proximal contacts (proximal end treatment). The influence of different proximal end treatments (ie, [1] freely exposed in the tissue, [2] terminated with metal in contact with the tissue, or [3] capped with plastic, and thereby fully insulated, on the RF‐induced lead‐tip heating) are studied. A technique to ensure that MR Conditional AIMD leads remain MR Conditional even when abandoned is recommended. Methods: Abandoned leads from three MR Conditional AIMDs ([1] a sacral neuromodulation system, [2] a cardiac rhythm management pacemaker system, and [3] a deep brain stimulator system) were investigated in this study. The computational lead models (ie, the transfer functions) for different proximal end treatments were measured and used to assess the in vivo lead‐tip heating for four virtual human models (FATS, Duke, Ella, and Billie) and compared with the lead‐tip heating of the complete MR Conditional AIMD system. Result: The average and maximum lead‐tip heating for abandoned leads proximally capped with metal is always lower than that from the complete AIMD system. Abandoned leads proximally insulated could lead to an average in vivo temperature rise up to 3.5 times higher than that from the complete AIMD system. Conclusion: For the three investigated AIMDs under 1.5T MR scanning, our results indicate that RF‐induced lead‐tip heating of abandoned leads strongly depends on the proximal lead termination. A metallic cap applied to the proximal termination of the tested leads could significantly reduce the RF‐induced lead‐tip heating. [ABSTRACT FROM AUTHOR]

To improve the convenience and efficiency of antenna design, in this article, a novel inverse artificial neural network (ANN) model is proposed in which antenna performance indexes are set as the input and corresponding geometrical variables are set as the output. To solve the multiobjective problem of antenna modeling, the first part of the ANN model involves three parallel and independent branches for S-parameter, gain, and radiation pattern, and the second part outputs a final predicted result. Once the training is completed, the proposed inverse model can provide antenna geometries directly without being repetitively called by an optimization algorithm. Compared with the inverse extreme learning machine and five state-of-art forward models, the proposed model uses a small number of training samples and directly obtains the satisfying values of geometrical variables without any optimization process. [ABSTRACT FROM AUTHOR]

The present day industries are availing the use of modern digital power electronic devices which are more robust, noise free, reliable and flexible. Power DC-DC converters are used to control the output voltage of most of the electrical and electronics appliances, when they are employed for applications such as aircrafts, energy storage systems, electric vehicles, standalone, and grid connected photovoltaic (PV) system. The control of these converters has a wide scope for research and a number of control schemes have been introduced to efficiently control the output devices. This paper presents the design of model predictive controller (MPC) for boost converter. Boost converter is mathematically modelled and are implemented in MATLAB Simulink. Finally, they have tested various controller schemes and results obtained using these controllers are compared and analysed. The open loop response of the system has been used to find the transfer function (TF) of the system. The TF is used to design the MPC. The output voltage of converters is controlled by the designed controller and it has been observed that the output of converters is maintained at a constant value for different set points. The notable feature of the proposed design is to reduce the overshoot drastically. The empirical rules for tuning MPC parameters are reported based on desired response. Finally, the output voltage of the system with MPC based controller is compared with that of conventional controllers like PI, PID and it is found that MPC showed better control performance than conventional controllers. The efficacy of the designed controller is demonstrated through simulation using DCDCboost converters with R and RL load. [ABSTRACT FROM AUTHOR]

Propagation channel characterization and modeling is an important aspect in the wireless communication domain prior to the design and implementation of any RF system, especially in the millimeter-wave band for the 5G ecosystem. Several methods have been proposed in the literature for different environments where the antenna effects present inherently in the measured results caused by ambiguous channel characterization and model. The results are antenna specific and unreliable for other antennas. In this letter, the standalone channel response (frequency and time domain) excluding the antenna effects has been derived using a two-port network approach. Identical horn antennas operating in the C-band have been used to measure the channel transfer function and impulse response. A comparative investigation of the measured results with and without the antenna effects is presented. It is observed that measuring the channel characteristics without excluding the transmitting and receiving antenna effects adds additional time delays and reduced coherence bandwidth of the channel. [ABSTRACT FROM AUTHOR]

Over-track buildings have been increasingly favored in the construction of metro depots and freight depots in China in the last decade due to advantages of intensive utilization of land resources and high-profits. However, due to the relatively heavy transportation mass and high-operating frequency of bridge cranes, over-track buildings are often complained by occupants for annoying noise and vibrations. So far this issue is rarely concerned and the characteristics of noise and vibrations under bridge crane loading remain unclear. In this study, field measurements of two full-scale over-track buildings, including a seven-story building over a metro depot and a three-story building over a freight depot, were conducted. Vibration characteristics of both the structure and the bridge crane were obtained. The transmission of vibrations from bridge crane system to the over-track building was obtained by transfer function (TF) of vibration from the column bracket towards the outdoor platform or building floors. The structure-borne noise inside the building was also captured and evaluated. The effect of bridge crane operational parameters (loading capacity and running velocity) and structural dynamic properties (non-structural components) on system responses was further discussed. Results show that the bridge crane–induced vibrations are comparable to the levels of train-induced vibrations. Besides, both buildings tested in this study suffer from unacceptable structure-borne noise, although the building vibration is acceptable. We recommend to carefully examining design of new over-track buildings to avoid annoying indoor noise and improve the living or working environment of occupants. It is demonstrated that vibrations of over-track buildings are more sensitive to running velocity than load capacity of bridge crane. It could be expected that the future increase of velocity will worsen the noise and vibration environment of over-track buildings. Furthermore, it is seen that non-structural components would remarkably affect dynamic responses of the building. [ABSTRACT FROM AUTHOR]

This paper presents a novel, efficient, and simple method to characterize the transfer function (TF) of leads for active implantable medical devices. The method characterizes the TF using a set of base functions and can be obtained using a few voltage measurements. This procedure requires a few direct measurements of the radiofrequency (RF)-induced voltages on the leads during magnetic resonance imaging (MRI) exposure, and the simulated, or measured, electric field generated by MRI RF coil inside the American Society for Testing and Materials (ASTM) phantom. Consequently, the measurement time of the TF can be reduced and the overall process significantly simplified compared to existing TF measurement methods. The theory of the new method is presented and two examples are given to demonstrate the accuracy and efficiency. [ABSTRACT FROM AUTHOR]

Transfer function (TF) design is a central topic in direct volume rendering. The TF fundamentally translates data values into optical properties to reveal relevant features present in the volumetric data. We propose a semi-automatic TF design scheme which consists of two steps: First, we present a clustering process within 1D/2D TF domain based on the proximities of the respective volumetric features in the spatial domain. The presented approach provides an interactive tool that aids users in exploring clusters and identifying features of interest (FOI). Second, our method automatically generates a TF by iteratively refining the optical properties for the selected features using a novel feature visibility measurement. The proposed visibility measurement leverages the similarities of features to enhance their visibilities in DVR images. Compared to the conventional visibility measurement, the proposed feature visibility is able to efficiently sense opacity changes and precisely evaluate the impact of selected features on resulting visualizations. Our experiments validate the effectiveness of the proposed approach by demonstrating the advantages of integrating feature similarity into the visibility computations. We examine a number of datasets to establish the utility of our approach for semi-automatic TF design. [ABSTRACT FROM AUTHOR]

In this paper, a modified small signal state space average model is proposed to analyze the pulse width modulated converter operating in discontinuous conduction mode (DCM). It is based on a unique correction matrix (Mc) and new duty ratio constrain which is derived on the basic properties of inductor current. A 12 volt, 5 watt power supply based on Cuk converter is designed to demonstrate this proposed methodology. Transfer functions (input-to-output and control-tooutput) of this power supply are calculated theoretically with the help of proposed modelling procedure. Bode plots of those transfer function are achieved using MATLAB toolboxes. To validate the proposed model, a simulation is also performed in MATLAB and frequency response is captured at run time using linearization technique. Bode plots from proposed model are very much in line with simulation results and offer improved predictions for high frequency dynamics of converter operating in DCM. The validity of presented work is reconfirmed by experimental set-up. The presented work is also compared with conventional small signal modelling on the basis of frequency analysis. [ABSTRACT FROM AUTHOR]

In this paper, disk space variation, radial deformation, short circuit, and axial displacement as four common transformer winding faults, in different locations and with various extents, were practically applied to 20 kV winding of a 1.6 MVA distribution transformer. For classification of the fault type, its location, and extent, a new calculation method for transfer function (TF) comparison indices called windowed calculation was proposed. The whole frequency range of the TF is scanned in this method. It was shown that the presented method increases the visual fault detection ability even for fault-type detection and significantly enhances the accuracy of the classification winding faults type, location, and extent. In this study, Fisher discriminant analysis (FDA) was utilized for dimension reduction and feature extraction. The ability of the FDA for maximizing the between-class separability while minimizing their within-class variability was utilized for this application so as to decrease the dimension and extract appropriate features from a lot of calculated features by the proposed method. [ABSTRACT FROM PUBLISHER]

The scope of this paper is to evaluate the short-term predictive capacity of the stochastic models ARIMA, Transfer Function (TF) and Artificial Neural Networks for water parameters, specifically for 1, 2 and 3 steps forward (m = 1, 2 and 3). The comparison of statistical parameters indicated that ARIMA models could be proposed as short-term prediction models. In some cases that TF models resulted in better predictions, the difference with ARIMA was minimal and since the latter are simpler in their construction, they are proposed for short-term prediction. Artificial Neural Networks didn’t show a good short-term predictive capacity in comparison with the aforementioned models.

Baroreceptor reflex sensitivity (BRS) is an important prognostic factor because a reduced BRS has been associated with an adverse cardiovascular outcome. The threshold for a ‘reduced’ BRS was established by the ATRAMI study at BRS <3 ms/mmHg in patients with a previous myocardial infarction, and has been shown to improve risk assessment in many other cardiac dysfunctions. The successful application of this cut-off to other populations suggests that it may reflect an inherent property of baroreflex functioning, so our goal is to investigate whether it represents a ‘natural’ partition of BRS values. As reduced baroreflex responsiveness is also associated with ageing, we investigated whether a BRS estimate <3 ms/mmHg could be the result of a process of physiological senescence as well as a sign of BRS dysfunction. This study involved 228 chronic heart failure patients and 60 age-matched controls. Our novel method combined transfer function BRS estimation and automatic clustering of BRS probability distributions, to define indicative levels of different BRS activities. The analysis produced a fit clustering (cophenetic correlation coefficient 0.9 out of 1) and identified one group of homogeneous patients (well separated from the others by 3 ms/mmHg) with an increased BRS-based mortality risk [hazard ratio (HR): 3.19 (1.73, 5.89), P<0.001]. The age-dependent BRS cut-off, estimated by 5% quantile regression of log (BRS) with age (considering the age-matched controls), provides a similar mortality value [HR: 2.44 (1.37, 4.43), P=0.003]. In conclusion, the 3 ms/mmHg cut-off identifies two large clusters of homogeneous heart failure (HF) patients, thus supporting the hypothesis of a natural cut-off in the HF population. Furthermore, age was found to have no statistical impact on risk assessment, suggesting that there is no need to establish age-based cut-offs because 3 ms/mmHg optimally identifies patients at high mortality risk. [ABSTRACT FROM AUTHOR]

In this paper, a new method to discriminate between mechanical defects and electrical faults, as two major faults in power transformer windings, is proposed. In the first step, the detailed model of a real 1.2 MVA transformer winding is developed using geometrical dimensions and specifications. Thereafter, the frequency response characteristics are obtained for intact and defected cases using EMTP/ATP. In the next step, some features based on cross-correlation and other mathematical patterns are selected from the obtained signals. These features are then used to train an ANN classifier. The proposed method is able to precisely discriminate among disc-to-disc short circuit faults, radial deformation and axial displacement defects and determine their location or extent with a good accuracy. [ABSTRACT FROM AUTHOR]

A new artificial neural network (ANN) technique is described in this paper to detect and localize turn-to-turn short fault in power transformers by analyzing of transfer function (TF). The ANN is trained by using back propagation learning algorithm. Frequency and amplitude of TF in resonance points are used as ANN inputs and fault location is used as an output. An especially designed double-disk transformer winding with power rating 1.2 MVA is used as a test object to verify the proposed method. All disks of this winding were accessible via a tap in order to form a variety of turn-to-turn short faults. [ABSTRACT FROM AUTHOR]

The transfer function (TF) these days is a well-known method to detect different types of mechanical damage in power transformers. The most important mechanical faults mentioned by the authors and researchers, which are most likely to be detected using the TF and occur frequently in transformers, are disc-space variation, radial deformation, and axial displacement. These faults are investigated in this paper using three different similar-size test objects. Since the TF method is a comparative method and the measured results should be compared with the reference results, some mathematical methods are studied to compare different TFs. A complete fault detection, which means determining the type, location, and level of the faults by using TF analyses is the main aim of this paper. [ABSTRACT FROM PUBLISHER]

Abstract: In this paper, a variable advective time delay (ATD) is introduced to Transfer Function (TF) models. This element enables the TF model to follow the diversity in response of a catchment system much better than using a constant advective time delay value as heretofore. An investigation of different approaches to define the variation of the ATD of the catchment studied is presented here. The resulting variable ATD is dependent on the variations of the flow or rainfall, depending on which is used as input to the applied model in order to produce the flow forecast. The variable ATD is tested on both linear and nonlinear TF models; the latter being TF models with state dependent parameters. Both types have been widely used in real-time flow forecasting applications. The proposed methodology is assessed using rainfall and flow time series from the Pinios River in Greece. [Copyright &y& Elsevier]

The current ultra-wideband (UWB) channel models proposed by different research groups are generally based on measurements in which the effect of the antennas used are inevitably embedded. There is potentially significant waveform distortion by UWB antennas, and it is difficult to distinguish between antenna and real propagation path effects in many of the reported channel measurements. However, understanding these effects is important for overall system performance prediction. The discone antenna is known for its broadband characteristics and has been widely used for channel measurements. In this paper, we address the importance of the antenna and indoor propagation effects as applied to a UWB system analysis. This is achieved by use of a true time-domain three-dimensional ray-tracing propagation model coupled with accurate simulation of the time-domain performance of the discone antenna. A DS-UWB system approach was adopted for detailed study and its performance is evaluated under the channel model with and without considering the antenna pattern effect. Both line-of-sight and non-line-of-sight cases are considered. The antenna effect can be seen to be significant, leading to the conclusion that interpretation of practical system measurements must allow for the antennas being used in the measurement system. [ABSTRACT FROM PUBLISHER]

The central aortic blood pressure (cBP) waveform, which is different to that of peripheral locations, is a clinically important parameter for assessing cardiovascular function, however the gold standard for measuring cBP involves invasive catheter-based techniques. The difficulties associated with invasive measurements have given rise to the development of a variety of noninvasive methods. An increasingly applied method for the noninvasive derivation of cBP involves the application of transfer function (TF) techniques to a non-invasively measured radial blood pressure (BP) waveform. The purpose of the current study was to investigate the development of a general parametric model for determination of cBP from tonometrically transduced radial BP waveforms. The study utilized simultaneously measured invasive central aortic and noninvasive radial BP waveform measurements. Data sets were available from 92 subjects, a large cohort for a study of this nature. The output error (OE) model was empirically identified as the most appropriate model structure. A generalized model was developed using a pre-specified derivation cohort and then applied to a validation data set to estimate the recognized features of the cBP waveform. While our results showed that many relevant BP parameters could be derived within acceptable limits, the estimated augmentation index (AI) displayed only a weak correlation compared to the invasively measured value, indicating that any clinical diagnosis or interpretation based on estimated AI should be undertaken with caution., (Copyright © 2016 Elsevier Ltd. All rights reserved.)