Optimal Scaling Factor Research Articles

Analytical layout optimization of printed planar coil with variable trace width for inductive wireless power transfer

In the inductive wireless power transmission (WPT) designs of consumer electronics and implantable devices, the printed planar coil in standard manufacture is commonly used. Layout optimization of the coils is one of the important ways to make the power transmission system more efficient. Varying the trace width and turn-to-turn spacing together for the coils is proposed to optimize the maximum achievable power transfer efficiency (𝜂max). An accurate analytical model for the printed square coils is also established as well to speed up the design process. By virtue of this model, an optimal scaling factor of the trace width and the optimal frequency can be quickly estimated. The proposed model is validated by both the simulations (ANSYS HFSS) and experiments. A WPT link of two planar coils with size of 50 mm × 50 mm × 1 mm, operating at 23 MHz, is optimized by using this methodology. After optimization, the measured 𝜂max of the WPT system is increased from 22.60% to 32.74% at a 100-mm transmission distance.

Cyclic Shift Based Tone Reservation PAPR Reduction Scheme with Embedding Side Information for FBMC-OQAM Systems

The tone reservation (TR) scheme is an attractive method to reduce peak-to-average power ratio (PAPR) in the filter bank multicarrier with offset quadrature amplitude modulation (FBMC-OQAM) systems. However, the high PAPR of FBMC signal will severely degrades system performance. To address this issue, a cyclic shift based TR (CS-TR) scheme with embedding side information (SI) is proposed to reduce the PAPR of FBMC signals. At the transmitter, four candidate signals are first generated based on cyclic shift of the output of inverse discrete Fourier transform (IDFT), and the SI of the selected signal with minimum peak power among the four candidate signals is embedded in sparse symbols with quadrature phase-shift keying constellation. Then, the TR weighted by optimal scaling factor is employed to further reduce PAPR of the selected signal. At the receiver, a reliable SI detector is presented by determining the phase rotation of SI embedding symbols, and the transmitted data blocks can be correctly demodulated according to the detected SI. Simulation results show that the proposed scheme significantly outperforms the existing TR schemes in both PAPR reduction and bit error rate (BER) performances. In addition, the proposed scheme with detected SI can achieve the same BER performance compared to the one with perfect SI.

Energy harvesting using a clamped–clamped piezoelectric–flexoelectric beam

In this article, the nonlinear vibration problem of a clamped–clamped monolithic piezoelectric flexoelectric beam is investigated when considering the device as an energy harvester. A scalable model of the beam is derived based on Euler–Bernoulli theory and takes into account geometric nonlinearity resulting from relatively large displacements and restrictive boundary conditions. The Galerkin method is used to discretize the nonlinear reduced-order model which is solved numerically using a continuation technique. The analysis of the dynamic response of the device at the micro and nano-scales demonstrate that such structure can be used to harvest energy despite its symmetry. This result was generally ignored in the literature for clamped–clamped single layered structures. The generated energy was demonstrated to be particularly attributed to the introduction of the longitudinal potential variation and the mid-plane stretching into the beam’s model. It was also found that the transverse piezoelectric coefficient is mainly responsible for the harvested energy. A 3D finite element model is developed providing the validation of the assumed assumptions, including the adopted analytical potential distribution particularly for the piezoelectric case. The nonlinear dynamic behavior of the beam is analyzed by varying the geometric dimensions of the device from the micro to the nano-scale. It is found that a better power density is obtained when larger scaling factors are used. However, a better performance can be achieved for an optimal scale factor at specific narrow frequency bandwidth nearby the fundamental frequency.

Low-Overhead Adaptive Brightness Scaling for Energy Reduction in OLED Displays

Organic Light Emitting Diode (OLED) is rapidly emerging as the mainstream mobile display technology. This is posing new challenges on the design of energy-saving solutions for OLED displays, specifically intended for interactive devices such as smartphones, smartwatches and tablets. To this date, the standard solution is brightness scaling. However, the amount of the scaling is typically set statically (either by the user, through a setting knob, or by the system in response to predefined events such as low-battery status) and independently of the displayed image. In this work we describe a smart computing technique called Low-Overhead Adaptive Brightness Scaling (LABS), that overcomes these limitations. In LABS, the optimal content-dependent brightness scaling factor is determined automatically for each displayed image, on a frame-by-frame basis, with a low computational cost that allows real-time usage. The basic form of LABS achieves more than 35 percent power reduction on average, when applied to different image datasets, while maintaining the Mean Structural Similarity Index (MSSIM) between the original and transformed images above 97 percent.

A novel digital watermarking scheme using dragonfly optimizer in transform domain

In today’s technologically-wise advanced environment, it is very significant for the entrepreneurs and business people to secure or protect the digital content. Their digital content can be protected legally using the copyright information such as copyrights embedded into the data. Bio-inspired computing algorithms will help find the optimal scale factor(s) by developing an appropriate fitness function and parameter selection. This article proposes a novel robust and blind watermarking method for digital images using a dragonfly optimizer. This article provides a solution for a false-positive problem using third party protection code. The proposed watermarking system outperforms the competing methods both on efficiency and efficacy measures such as experimental time, Bit Error Rate, Peak Signal to Noise Ratio, Normalized Correlation in the standard databases (Signal and Image Processing Institute (SIPI), Break Our Watermarking System (BOWS)) and also found to be robust to various image processing attacks.

Digital Watermarking using Grasshopper Optimization Algorithm

Abstract The advancement in computer science technology has led to some serious concerns about the piracy and copyright of digital content. Digital watermarking technique is widely used for copyright protection and other similar applications. In this paper, a technique for digital watermarking based on Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), and Grasshopper Optimization Algorithm (GOA) is proposed. The method computes the DWT of the cover image to obtain the sub-components of the image. The subcomponent is converted to frequency domain using DCT. The challenge is to find the optimal scaling factor to be used for watermarking. The authors have designed a GOA based technique that finds the optimized scaling factor and the coefficient for embedding the watermark. GOA makes the watermark undetectable and is invisible in the cover image. The watermark image is embedded in the cover image using these coefficients. The extraction of watermark from the cover image is done by using inverse DCT and DWT. The proposed method is compared with the other state of the art methods. The effectiveness of the proposed method is computed using Peak Signal to Noise Ratio (PSNR), Normalized Cross Correlation (NCC) and Image Fidelity (IF). The proposed method outperforms the other methods and can be effectively used for practical digital watermarking.

Abundance and Associated Variations of Cytochrome P450 Drug-Metabolizing Enzymes in the Liver of East Asian Adults: A Meta-Analysis.

Cytochrome P450 (CYP) enzymes are one of the main sources of variability in drug metabolic clearance. Information on their abundance levels is therefore crucial to optimize scaling factors for in vitro-in vivo extrapolation (IVIVE) to predict metabolic clearance. This study aims to quantify the abundance data of hepatic drug-metabolizing CYP enzymes in East Asian subjects reported from various sources in the literature using meta-analysis. We conducted a meta-analysis on the abundance of drug-metabolizingCYP enzymes in the liver of East Asian adults. Eligible reports were identified based on predefined criteria-(1) individual liver microsomal samples, and (2) absolute protein abundance data from normal tissues of East Asian adult subjects. Subgroup and sensitivity analyses were also performed. Among the 11 CYP isoforms analyzed in East Asian subjects, CYP3A5 and CYP3A4 had the highest protein levels. In particular, the number of studies and the liver sample used to quantify the abundance of CYP3A4 were the largest. Of the isoforms involved, CYP2J2 and CYP2B6 had the lowest abundance level, i.e., <5 pmol/ mg of microsomal protein. For enzymes with abundance values available in both Chinese and Japanese subjects (CYP1A2, CYP2C9, CYP3A4, and CYP3A5), the abundance level of each CYP isoform appeared to be higher in Chinese than in Japanese subjects. The most distinct difference was observed in CYP3A5 abundance. The current meta-analysis shows that the abundance levels of CYP enzymes appear to vary greatly among different East Asian individuals who have similar ethnic backgrounds and food habits. The pooled data of CYP abundance can be used as preliminary reference values along with the associated variations for the projections of pharmacokinetics through physiologically based pharmacokinetic (PBPK)approaches.

Spatial Sharpening of KOMPSAT-3A MIR Images Using Optimal Scaling Factor

This paper present efficient methods for merging KOMPSAT-3A (Korea Multi-Purpose Satellite) medium wave Infrared (MIR) and panchromatic (PAN) images. Spatial sharpening techniques have been developed to create an image with both high spatial and high spectral resolution by combining the desired qualities of a PAN image with high spatial and low spectral resolution and an MS/MIR image with low spatial and high spectral resolution. The proposed methods can extract an optimal scaling factor, and uses the tactics of appropriately controlling the balance between the spatial and spectral resolutions. KOMPSAT-3A PAN and MIR images were used to test and evaluate the performance of the proposed methods. A qualitative assessment were performed using the image quality index (Q4), the cross correlation index (CC) and the relative global dimensional synthesis error (Spectral/Spatial ERGAS). These tests indicate that the proposed methods preserve the spectral and spatial characteristics of the original MIR and PAN images. Visual analysis reveals that the spectral and spatial information derived from the proposed methods were well retained in the test images. A comparison of the results of the proposed methods with those obtained from applying existing ones such as the Multi Sensor Fusion (MSF) technique or the Guide Filter Based Fusion (GF) show the efficiency of the new fusion process to be superior to the one of the others. The results showed a significant improvement in fusion capability for KOMPSAT-3A MIR imagery.

A multi-scale image watermarking based on integer wavelet transform and singular value decomposition

Image watermarking technique is one of effective solutions to protect copyright, and it is applied to a variety of information security application domains. It needs to meet four requirements of imperceptibility, robustness, capacity and security. A multi-scale and secure image watermarking method is proposed in this work, which is based on the Integer Wavelet Transform (IWT) and Singular Value Decomposition (SVD). Four IWT sub-bands are firstly obtained after 1-level IWT on the host image, and the corresponding singular diagonal matrices of four sub-bands can be obtained using SVD. Then, each singular diagonal matrix is divided into four non-overlapping sections in terms of the size of embedding watermark. Particularly, the size of upper left part is same as the size of watermark. The watermark can be directly embedded into four upper left parts afterwards by multiplying different scaling factors to complete the final watermarking operation. Especially, a novel optimized authentication mechanism is designed to resolve the false positive problem, which exists in the SVD-based watermarking algorithms. In addition, three-dimensional optimal mapping algorithm is proposed to search the optimal scaling factors through a novel objective evaluation function, and it can significantly improve the imperceptibility and robustness. The experimental test and comparison analysis illustrate that the proposed watermark scheme demonstrates a high imperceptibility with peak signal to noise ratio values of 45 dB and strong robustness with average normalized correlation values of 0.92.

High-SNR steganography for digital audio signal in the wavelet domain

Imperceptible, robust, and embedding capacity are three main requirements for the steganography of digital audio signal. To enhance them, this study presents a novel steganography for digital audio signal in the wavelet domain. Since the performance of imperceptible and robust are usually in term of signal-to-noise ratio (SNR) and bit-error-rate (BER), we propose a quantization-based optimization model to maximize SNR and reduce BER in embedding secret message. In the proposed model, quantization technique with unknow coefficients of discrete wavelet transform (DWT) is rewritten as the first constraint. The adjustment of scaling DWT coefficients is considered as the second constraint. At the same time, signal-to-noise ratio (SNR) is converted into a performance index. In solving this model, we use matrix operations and Lagrange multiplier to obtain optimal DWT coefficients and scaling factors. Moreover, the invariant feature of the scaling factors against amplitude scaling attack is proved. In extraction, secret message can be detected without original audio signal. Experimental results show that the proposed steganography has high SNR and strong robustness against many malicious attacks when comparing to some exiting methods.

Digital audio watermarking using minimum-amplitude scaling on optimized DWT low-frequency coefficients

This work presents an audio watermarking scheme using minimum-amplitude scaling on the optimized lowest-frequency coefficients in the wavelet domain. Signal-to-noise ratio (SNR), bit-error-rate (BER) and Perceptual Evaluation of Audio Quality (PEAQ) are commonly utilized performance indexes in measuring the fidelity, robustness and quality of watermarking algorithms. However, there is a tradeoff relationship between audio quality and robustness. To overcome the drawback, this paper aims in proposing an optimization-based scaling scheme using optimal modification of low-frequency amplitude in the wavelet domain. A function connecting the multi-coefficients, composed of arbitrary scaling on the lowest DWT coefficients, and the group SNR of these coefficient is derived. Karush-Kuhn-Tucker (KKT) theorem and minimum length play two essential roles to obtain the optimal modification of low-frequency amplitude with optimal scaling factors. Furthermore, the almost invariant feature of these optimized scaling factors hold demonstrates resistance to amplitude modification manipulation. To practically evaluate the watermarked audio quality, an objective measurement using the PEAQ is also performed as well. Experimental results confirm that the embedded audio in the proposed method has high SNR, low BER, and good PEAQ, indicating strong robustness against various attacks, such as re-sampling, amplitude modification, and mp3 compression.

Atmospheric inverse estimates of CO emissions from Zhengzhou, China

Carbon monoxide (CO) is an important gas that affects human health and causes air pollution. However, the estimates of CO emissions in China are still subject to large uncertainties. Based on the CO mass concentration and the coupled Weather Research and Forecast (WRF) and Stochastic Time-Inverted Lagrangian Transport (STILT) model (WRF-STILT), this study estimates the CO emissions over Zhengzhou, China. The results show that the mean CO mass concentration was 1.17 mg m−3 from November 2017 to February 2018, with a clear diurnal variation. There were two periods of rapidly increasing CO concentration in the diurnal variation, which are 06:00–09:00 and 16:00–20:00 local time. The footprint analysis shows that the observation site is highly influenced by local emissions. The most influential regions to the site observations are northeast and northwest Zhengzhou, which are associated with the geographical barrier of the Taihang Mountains in the north and narrow Fenwei Plain in the west. The inversion result shows that the actual emissions are lower than the inventory estimates. Using the optimal scaling factors, the WRF-STILT simulations of CO concentration agree closely with the CO measurements with the linear fitting regression equation y = 0.87x + 0.15. The slopes of the linear fitting regressions between the WRF-STILT-simulated CO concentrations determined using the optimal emissions and the observations range from 0.72 to 0.89 for four months, and all the fitting results passed the significance test (P < 0.001). These results indicate that the new optimal emissions derived with the scaling factors could better represent the real emission conditions than the a priori emissions if the WRF-STILT model is assumed to be reliable.

Damping spectra for estimating inelastic deformations from modal response spectrum analysis

SummaryThe focus of this study is estimating inelastic deformations of building frames by conducting response spectrum analysis. Damping spectra (Rμ–ξ–T spectra) are derived first for SDOF systems defined with their initial period or initial stiffness, in order to attain equal maximum displacements of the companion inelastic systems. Mean spectral relations and their standard deviations are calculated for 566 horizontal pairs of near‐fault ground motions. They are further classified with respect to ductility reduction factor Rμ as well as the earthquake magnitude and soil type, which are found to have notable influence on the effect of damping in reducing maximum displacement. Optimal damping scaling factors are then calculated for converting the standard 5% damped linear elastic spectra to inelastic spectra. Finally, maximum deformations of MDOF building frames are estimated by using the optimal spectral factors through mode superposition analysis. The results are compared with the results obtained from nonlinear response history analysis under different sets of strong ground motions. Mean inelastic deformations are predicted with reasonable accuracy with the proposed procedure. Hence, damping spectra furnishing optimal damping ratios are suggested as a practical tool for assessing the seismic performance of newly designed, code conforming structures.

Optimizing Multiscale Entropy Approach for Rotor Core Identification using Simulated Intracardiac Electrograms.

Atrial Fibrillation (AF) is most common sustained cardiac arrhythmia and a precursor to many fatal cardiac conditions. Catheter ablation, which is a minimally invasive treatment, is associated with limited success rates in patients with persistent AF. Rotors are believed to maintain AF and core of rotors are considered to be robust targets for ablation. Recently, multiscale entropy (MSE) was proposed to identify the core of rotors in ex-vivo rabbit hearts. However, MSE technique is sensitive to intrinsic parameters, such as scale factor and template dimension, that may lead to an imprecise estimation of entropy measures. The purpose of this research is optimize MSE approach to improve its accuracy and sensitivity in rotor core identification using simulated EGMs from human atrial model. Specifically, we have identified the optimal time scale factor (τopt) and optimal template dimension (Τopt) that are needed for efficient rotor core identification. The τopt was identified to be 10, using a convergence graph, and the Τopt (~20 ms) remained the same at different sampling rates, indicating that optimized MSE will be efficient in identifying core of the rotor irrespective of the signal acquisition system.

Optimizing the Performance of MOS Stacks

CMOS stack circuits find applications in multi-input exclusive-OR gates and barrel-shifters. Specifically, in wide fan-in CMOS NAND/NOR gates, the need arises to connect a relatively large number of NMOS/PMOS transistors in series in the pull-down network (PDN)/pull-up network (PUN). The resulting time delay is relatively high and the power consumption accordingly increases due to the need to deal with the various internal capacitances. The problem gets worse with increasing the number of inputs. In this paper, the performance of conventional static CMOS stack circuits is investigated quantitatively and a figure of merit expressing the performance is defined. The word “performance” includes the following three metrics; the average propagation delay, the power consumption, and the area. The optimum scaling factor corresponding to the best performance is determined. It is found that under the worst-case low-to-high transition at the output (that is, the input combination that results in the longest time delay in case of logic “1” at the output), there is an optimum value for the sizing of the PDN in order to minimize the average propagation delay. The proposed figure of merit is evaluated for different cases with the results discussed. The adopted models and the drawn conclusions are verified by comparison with simulation results adopting the 45 nm CMOS technology.

New approach to the generation of orthogonal body-fitted meshes and its application to non-steady plane-strain ideal plastic flow

For rigid-perfect plastic solids, ideal plastic flow happens when all material elements follow minimum work paths and the two principal stretch lines are materially embedded. To describe its kinematics effectively, Lagrange convective orthogonal curvilinear system has to be constructed. Therefore, a numerical procedure for generating orthogonal body-fitted meshes has been developed and applied to non-steady plane-strain ideal plastic flow. The mapping between the Cartesian system and the orthogonal system is based on Laplace equations and Cauchy–Riemann condition. The numerical procedure takes into consideration of all the prescribed boundary curves instead of one as the boundary conditions, which has been adopted in earlier studies when using conventional characteristic line method. After each iteration step, the obtained boundary points are adjusted towards the orthogonality conditions until error tolerance requirement is met. For demonstration purpose, the numerical procedure is applied to the optimization of a bulk part under forging. The obtained orthogonal body-fitted meshes are in good agreement with previous methods. Then the optimal initial scale factor is also calculated based on this method and compared with earlier studies. Finally, the evolution of the intermediate shapes and frictional external boundary conditions is also calculated when there are no elastic dead zones.

Physiological Correlates to In-race Paratriathlon Cycling Performance.

The purpose was to determine the physiological correlates to cycling performance within a competitive paratriathlon. Five wheelchair user and ten ambulant paratriathletes undertook laboratory-based testing to determine their: peak rate of oxygen uptake; blood lactate- and ventilatory-derived physiological thresholds; and, their maximal aerobic power. These variables were subsequently expressed in absolute (l∙min -1 or W), relative (ml∙kg-1∙min -1 or W∙kg -1) and scaled relative (or ml∙kg - 0.82 ∙min -1, ml∙kg - 0.32 ∙min -1 or W∙kg -0.32) terms. All athletes undertook a paratriathlon race with 20 km cycle. Pearson's correlation test and linear regression analyses were produced between laboratory-derived variables and cycle performance to generate correlation coefficients (r), standard error of estimates and 95% confidence intervals. For wheelchair users, performance was most strongly correlated to relative aerobic lactate threshold (W∙kg -1) (r=-0.99; confidence intervals: -0.99 to -0.99; standard error of estimate=22 s). For ambulant paratriathletes, the greatest correlation was with maximal aerobic power (W∙kg -0.32) (r=-0.91; -0.99 to -0.69; standard error of estimate=88 s). Race-category-specificity exits regarding physiological correlates to cycling performance in a paratriathlon race with further differences between optimal scaling factors between paratriathletes. This suggests aerobic lactate threshold and maximal aerobic power are the pertinent variables to infer cycling performance for wheelchair users and ambulant paratriathletes, respectively.

Using Space-Based Observations and Lagrangian Modeling to Evaluate Urban Carbon Dioxide Emissions in the Middle East.

Improved observational understanding of urban CO2 emissions, a large and dynamic global source of fossil CO2, can provide essential insights for both carbon cycle science and mitigation decision making. Here we compare three distinct global CO2 emissions inventory representations of urban CO2 emissions for five Middle Eastern cities (Riyadh, Mecca, Tabuk, Jeddah, and Baghdad) and use independent satellite observations from the Orbiting Carbon Observatory‐2 (OCO‐2) satellite to evaluate the inventory representations of afternoon emissions. We use the column version of the Stochastic Time‐Inverted Lagrangian Transport (X‐STILT) model to account for atmospheric transport and link emissions to observations. We compare XCO2 simulations with observations to determine optimum inventory scaling factors. Applying these factors, we find that the average summed emissions for all five cities are 100 MtC year−1 (50–151, 90% CI), which is 2.0 (1.0, 3.0) times the average prior inventory magnitudes. The total adjustment of the emissions of these cities comes out to ~7% (0%, 14%) of total Middle Eastern emissions (~700 MtC year−1). We find our results to be insensitive to the prior spatial distributions in inventories of the cities' emissions, facilitating robust quantitative assessments of urban emission magnitudes without accurate high‐resolution gridded inventories.

Adaptive scaling factors based on the impact of selected DCT coefficients for image watermarking

Image watermarking technique aims at high imperceptibility of the embedded watermark with minimal distortion in the watermarked images. In frequency-domain, block-based Discrete Cosine Transform (DCT) is a popular method which can be improved by different scaling factors. This paper presents an adaptive scaling factor for selected DCT coefficients in image watermarking. The image blocks that have lowest pixel variances are chosen as the embedding locations. The optimal scaling factors for selected DCT coefficients on the middle frequencies are obtained by finding the best quality of images. The embedding process is performed using the obtained scaling factors. The proposed technique was investigated to verify the robustness and imperceptibility against various image-processing attacks. It is proved that our technique achieves higher robustness against noise addition, filter and compression than the existing schemes in most cases. Our technique produces greater imperceptibility than the existing schemes.

Accurate Fault Location Method of the Mechanical Transmission System of Shearer Ranging Arm

In the process of coal mine production, the fault of the mechanical transmission system of the shearer ranging arm directly affects safety production. Therefore, it is very important to achieve the accurate fault location of the shearer ranging arm. The combination method of optimized continuous complex Morlet wavelet envelope demodulation spectrum analysis and spectrum analysis is proposed. Firstly, the spectrum contrast analysis of vibration signals between the normal state and fault state is performed, which can obtain the fault characteristics frequency and preliminary fault location. Then, the optimized continuous complex Morlet wavelet envelope demodulation algorithm is proposed to extract the side-bands characteristics of vibration signals, which can obtain the rotation frequency of fault location by the contrast analysis of side-bands characteristics in normal and fault state. In the algorithm, the center frequency and bandwidth of Morlet wavelet are optimized by wavelet Shannon entropy, and the optimal scale factor can be accurately determined by spectrum contrast analysis of vibration signals in normal and fault state. Finally, the accurate gear fault location is achieved by comprehensive analysis results of optimized continuous complex Morlet wavelet envelope demodulation spectrum and spectrum contrast. The simulation signals and practical vibration signals are applied to verify the proposed accurate gear fault location method. The experiment results indicate that the center frequency and bandwidth determined by wavelet Shannon entropy make the wavelet waveform best match the fault impact signal, and the optimal scale factor can be accurately determined by spectrum contrast analysis of vibration signals in normal and fault state, and the proposed method can achieve the precise fault location of the mechanical transmission system of shearer ranging arm. It provides the method for the on-site rapid accurate fault location of the mechanical transmission system. It is of great significance to the safe and efficient production of the coal mine.