bluuebunny/crossref_metadata_2025_split huggingface dataset:
Weight‐based colour constancy using contrast stretching
Authors: Abedini Zeinab , Jamzad Mansour 
Published: April 2021

AbstractOne of the main issues in colour image processing is changing objects' colour due to colour of illumination source. Colour constancy methods tend to modify overall image colour as if it was captured under natural light illumination. Without colour constancy, the colour would be an unreliable cue to object identity. Till now, many methods in colour constancy domain are presented. They are in two categories; statistical methods and learning‐based methods. This paper presents a new statistical weighted algorithm for illuminant estimation. Weights are adjusted to highlight two key factors in the image for illuminant estimation, that is contrast and brightness. The focus was on the convex part of the contrast stretching function to create the weights. Moreover, a novel partitioning mechanism in the colour domain that leads to improvement in efficiency is proposed. The proposed algorithm is evaluated on two benchmark linear image databases according to two evaluation metrics. The experimental results showed that it is competitive to the statistical state of the art methods. In addition to its low computational cost, it has the advantage of improving the efficiency of statistics‐based algorithms for dark images and images with low brightness contrast. Moreover, it is robust to camera change types.
Investigation on the partial discharge characteristics of eco‐friendly nanofluid insulation of corn oil nanofluid
Authors: M Shantha Kumar , P Kasi Viswanathan , H Shree Kumar 
Published: April 2021

AbstractThe suitability of corn oil nanofluid as an insulation material is studied herein by analysing the partial discharge characteristics. Experiments are conducted on nano‐silica modified corn oil at 0.01, 0.05, and 0.1 wt.% mass fractions. Electrode configurations are used to generate partial discharge (PD) sources such as corona discharge, internal discharge, and surface discharge. Partial discharge inception voltage dependency on electrode geometry is studied. Phase‐resolved partial discharge analysis (PRPD) at various test conditions is done to understand the influence of live element geometry that causes PD in real‐time operations, Weibull statistical analysis of PD parameters like scale parameter, shape parameter, skewness, and repetition rate is evaluated to understand the influence of nanofiller mass fraction in corn oil. The results illustrate that the addition of silica nanoparticles to corn oil has a significant influence on PD characteristics. The PRPD pattern analysis reveals information about the PD dependency on electrode configuration of the test condition. The addition of nanofillers in optimal concentrations without agglomeration can influence the PD characteristics to a certain degree. The test results may be inferred to suggest corn oil‐based silica nanofluids as an alternative biodegradable liquid insulation.
Analysis and robust passivity‐based control of zero‐voltage switching quasi‐resonant Cuk converter
Authors: Ayubirad Mostafa Ali , Yazdanpanah Mohammad Javad 
Published: April 2021

AbstractHere, a general state‐space average model of the half‐wave zero‐voltage switching quasi‐resonant Cuk converter (HW‐ZVS‐QRCC) is derived and validated. The development of an extended Lyapunov‐function‐based robust passivity‐based control strategy for HW‐ZVS‐QRCC is carried out using the derived model. The first feature of the proposed controller is that that the resulted closed‐loop HW‐ZVS‐QRCC is globally asymptotically stabilized even if the physical constraint on the magnitude of the control signal is taken into account. Also, to deal with the uncertainties in the conventional passivity‐based control (PBC) design, an integral function of the output voltage error is incorporated in PBC structure such that zero‐voltage regulation error is assured. Lastly, it shows which variables are most suitable for feedback purposes over a wide range of controller gains. Simulation and experimental results are also provided to validate the theoretical conclusions.
Tracing spinning reserve inadequacy risk via hybrid importance sampling with an optimised partially collapsed Gibbs sampler
Authors: Wang Yue 
Published: April 2021

AbstractFrom the simulation perspective, spinning reserve risk evaluation of power system is commonly a rare‐event assessing issue, for which importance sampling is an appealing solution technique. This paper proposes a hybrid importance sampling method for tracing spinning reserve inadequacy risk of power system integrating with renewables. The proposed method is oriented towards a generic high‐dimensional integral calculus, which allows for continuous and discrete random variables mixed together for casting kinds of risk indices. To improve the robustness in high‐dimensional applications, a partially collapsed Gibbs sampler is devised to help in exploring adaptive training samples which feature typical rare outage events. Interestingly, the originators engendering extreme spinning reserve inadequacy events can be traced using the sampling information of the proposed method. The performance of the proposed method is tested in an updated RTS‐79 system vis‐à‐vis several existing methods. Spinning reserve inadequacy risk tracing is explained by uncovering a scenario frequency distribution concerning the short‐term expected energy not supplied.
Online inertia estimation for power systems with high penetration of RES using recursive parameters estimation
Authors: Makolo Peter , Zamora Ramon , Lie Tek‐Tjing 
Published: April 2021

AbstractLow and time‐changing inertia values due to the high percentage of renewable energy sources (RESs) can cause stability problems in power systems due to rapid frequency instabilities. Inertia monitoring will assist operators to apply suitable actions and more proper control methods to alleviate stability issues. Therefore, this paper proposes an online method to estimate the total inertia of a network using a recursive least‐squares approach. The proposed method uses network measurements with a non‐recursive system identification approach to initially estimate the network hypothesis model. Then, the recursive method is used together with time changing measurements to recursively estimate model parameters and extract online inertia estimates of the network. During the estimation, the method does not need to store previous data after each sample step; therefore, the computation burden is significantly reduced. More importantly, the technique incorporates the use of available electromechanical oscillation modes in the system, which are linked with system parameters, to determine the network inertia estimates. The applicability of the proposed method has been validated by numerical simulations of the IEEE 39‐bus network and the aggregated New Zealand network with its actual inertia data.
Research on sub/super‐synchronous oscillation suppression method for direct‐drive wind turbine based on energy compensation
Authors: Ma Jing , Zhang Min , Phadke A. G. 
Published: April 2021

AbstractA method to suppress sub/super‐synchronous oscillation of direct‐drive wind turbines based on energy compensation is proposed. First, the transient energy model of direct‐drive wind turbine is built, and the negative damping energy terms that lead the oscillation of direct‐drive wind turbine are extracted. On this basis, the expressions of voltage compensation terms corresponding to negative damping energy terms are derived by backward deduction, thus supplementary energy branches are constructed, and their impact on fundamental frequency characteristics of wind turbine is analyzed. And then, with the compensation energy of supplementary branches reaching the maximum and the increment of fundamental‐frequency voltage being the minimum as the objective, and with the frequency‐domain characteristic and fundamental‐frequency voltage characteristic of control links being satisfied as constraints, a scheme to optimize the compensation coefficients of multiple branches is established. Finally, the model of direct‐drive wind turbine is built in RT‐LAB for hardware‐in‐the‐loop tests. Simulation results verify that, the method can realize fast frequency‐dependent suppression of sub/super‐synchronous oscillation in different frequency bands concerning different grid strengths.
Polarisation variation of linear polarised Bi‐ISAR system in space targets imaging
Authors: Bu Linsheng , Wang Junling 
Published: April 2021

AbstractA bistatic inverse synthetic aperture radar (Bi‐ISAR) system is used to observe space targets through different viewing angles via a bistatic radar configuration. It is seen that the receiver of a linear polarised Bi‐ISAR system with a long baseline will encounter energy variation and high‐order phase deviation in ISAR imaging due to the polarisation variation of this system. Here, the authors quantitatively analyse the energy variation caused by polarisation mismatch in a linearly polarised Bi‐ISAR system by investigating the time‐varying bistatic angle and intrinsic variable polarisation effect of targets via the combination of observation geometry and computational electromagnetic. The high‐order phase deviation in long‐term coherent processing is also presented through the same strategy. The authors conducted simulations for a bistatic system, which is configured with different baseline vectors, to analyse the impact of polarisation variation of the linear polarised Bi‐ISAR system on the energy loss and high‐order phase terms.
Multi‐carrier and multi‐polarimetric model based adaptive target detector for passive radar systems
Authors: Filippini Francesca , Colone Fabiola 
Published: April 2021

AbstractA new adaptive detection strategy for passive radar systems that fruitfully capitalizes on signals, simultaneously emitted by the same transmitter of opportunity at different carrier frequencies and collected by a set of differently polarized surveillance antennas is derived. Based on recent results that demonstrated the benefits provided by proper strategies to exploit polarimetric diversity, the authors aim at further improving the target detection performance by combining polarimetric and frequency diversity. Real data collected through an FM radio‐based passive radar prototype is used to extensively demonstrate the effectiveness of the derived strategy with respect to state‐of‐the‐art approaches. The conceived solution is proved to successfully enhance the capability to discriminate targets, thanks to an effective disturbance rejection performed at each frequency channel as well as a target echo enhancement and an increased robustness to the time‐varying characteristics of the exploited source of opportunity.
Deep learning for aircraft classification from VHF radar signatures
Authors: Fix Jérémy , Ren Chengfang , Costa Lopes Arthur , Morice Guillaume , Kobayashi Shuwa , Leterte Thierry , Hinostroza Sáenz Israel D. 
Published: April 2021

AbstractRadio sources in the Very High Frequency (VHF) band can be seized as opportunity donors in a passive radar configuration such as FM radio stations and VHF omnidirectional range (VOR). A full‐wave simulation of three size classes of aeroplanes shows that their bistatic radar cross‐section (RCS) are statistically comparable, albeit perform differently in time while the plane is flying. This difference can be exploited to recognize the size of the aeroplanes with respect to these classes. Measurements confirm this possible differentiation between the aeroplanes within the same class. Encouraging initial results were obtained using convolutional or recurrent neural networks to classify aircraft classes, combining simulated bistatic RCS results and real trajectories (collected from automatic dependent surveillance‐broadcast data).
WG2AN: Synthetic wound image generation using generative adversarial network
Authors: Sarp Salih , Kuzlu Murat , Wilson Emmanuel , Guler Ozgur 
Published: April 2021

AbstractIn part due to its ability to mimic any data distribution, Generative Adversarial Network (GAN) algorithms have been successfully applied to many applications, such as data augmentation, text‐to‐image translation, image‐to‐image translation, and image inpainting. Learning from data without crafting loss functions for each application provides broader applicability of the GAN algorithm. Medical image synthesis is also another field that the GAN algorithm has great potential to assist clinician training. This paper proposes a synthetic wound image generation model based on GAN architecture to increase the quality of clinical training. The proposed model is trained on chronic wound datasets with various sizes taken from real hospital environments. Hyperparameters such as epoch count and dataset size for training tasks are studied to find optimum training conditions as well. The performance of the developed model was evaluated through a mean squared error (MSE) metric to determine the similarity between generated and actual wounds. Visual inspection is performed to examine generated wound images. The results show that the proposed synthetic wound image generation (WG2AN) model has great potential to be used in medical training and performs well in producing synthetic wound images with a 1000‐image training dataset and 200 epochs of training.
Design and implementation of fast and hardware‐efficient parallel processing elements to set full and partial permutations in Beneš networks
Authors: Koloko Labson , Matsumoto Takahiro , Obara Hitoshi 
Published: April 2021

AbstractA new design for parallel and distributed processing elements (PEs) is proposed to configure Beneš networks based on a novel parallel algorithm that can realise full and partial permutations in a unified manner with very little overhead time and extra hardware. The proposed design reduces the hardware complexity of PEs from to due to a distributed architecture. In the proposed design, asynchronous operation was introduced in parts to reduce the time complexity per PE stage down to O(1) within a certain N, while it takes time per PE stage in conventional algorithms. A prototype parallel was constructed and PEs were distributed in a field programmable gate array to investigate performance for the switch size of N = 4 to 32. The experimental results demonstrate that the proposed design outperforms a recent method by at least several times in terms of hardware and processing time complexities.
The GOGREEN survey: Internal dynamics of clusters of galaxies at redshift 0.9–1.4
Authors: Biviano A. , van der Burg R. F. J. , Balogh M. L. , Munari E. , Cooper M. C. , De Lucia G. , Demarco R. , Jablonka P. , Muzzin A. , Nantais J. , Old L. J. , Rudnick G. , Vulcani B. , Wilson G. , Yee H. K. C. , Zaritsky D. , Cerulo P. , Chan J. , Finoguenov A. , Gilbank D. , Lidman C. , Pintos-Castro I. , Shipley H. 
Published: April 2021

Context.The study of galaxy cluster mass profiles (M(r)) provides constraints on the nature of dark matter and on physical processes affecting the mass distribution. The study of galaxy cluster velocity anisotropy profiles (β(r)) informs the orbits of galaxies in clusters, which are related to their evolution. The combination of mass profiles and velocity anisotropy profiles allows us to determine the pseudo phase-space density profiles (Q(r)); numerical simulations predict that these profiles follow a simple power law in cluster-centric distance.Aims.We determine the mass, velocity anisotropy, and pseudo phase-space density profiles of clusters of galaxies at the highest redshifts investigated in detail to date.Methods.We exploited the combination of the GOGREEN and GCLASS spectroscopic data-sets for 14 clusters with massM200 ≥ 1014 M⊙at redshifts 0.9 ≤ z ≤ 1.4. We constructed anensemblecluster by stacking 581 spectroscopically identified cluster members with stellar massM⋆ ≥ 109.5 M⊙. We used the MAMPOSSt method to constrain severalM(r) andβ(r) models, and we then inverted the Jeans equation to determine theensembleclusterβ(r) in a non-parametric way. Finally, we combined the results of theM(r) andβ(r) analysis to determineQ(r) for theensemblecluster.Results.The concentrationc200of theensemblecluster mass profile is in excellent agreement with predictions from Λ cold dark matter (ΛCDM) cosmological numerical simulations, and with previous determinations for clusters of similar mass and at similar redshifts, obtained from gravitational lensing and X-ray data. We see no significant difference between the total mass density and either the galaxy number density distributions or the stellar mass distribution. Star-forming galaxies are spatially significantly less concentrated than quiescent galaxies. The orbits of cluster galaxies are isotropic near the center and more radial outside. Star-forming galaxies and galaxies of low stellar mass tend to move on more radially elongated orbits than quiescent galaxies and galaxies of high stellar mass. The profileQ(r), determined using either the total mass or the number density profile, is very close to the power-law behavior predicted by numerical simulations.Conclusions.The internal dynamics of clusters at the highest redshift probed in detail to date are very similar to those of lower-redshift clusters, and in excellent agreement with predictions of numerical simulations. The clusters in our sample have already reached a high degree of dynamical relaxation.
Lung MRI in Children: The Road Less Travelled
Authors: Sodhi Kushaljit Singh 
Published: April 2021

AbstractMagnetic resonance imaging (MRI) of the lungs is one of the most underutilized imaging modality when it comes to imaging of thoracic diseases in children. This is largely due to less-than-optimal image quality and multiple technical challenges involved with MRI of the lungs. Advances in MRI technology along with increased awareness about optimization of MR protocol have led to it being viewed as a feasible option for evaluation of various chest diseases in children. This short review article takes the reader to the road less travelled to explore newer horizons for applications of this rapidly evolving magnetic resonance technique in the field of thoracic diseases in children.
How soccer scouts identify talented players
Authors: Bergkamp Tom L. G. , Frencken Wouter G. P. , Niessen A. Susan M. , Meijer Rob R. , den Hartigh Ruud. J. R. 
Published: April 2021

ABSTRACTScouts of soccer clubs are often the first to identify talented players. However, there is a lack of research on how these scouts assess and predict overall soccer performance. Therefore, we conducted a large‐scaled study to examine the process of talent identification among 125 soccer scouts. Through an online self‐report questionnaire, scouts were asked about (1) the players’ age at which they can predict players’ soccer performance, (2) the attributes they consider relevant, and (3) the extent to which they predict performance in a structured manner. The most important results are as follows. First, scouts who observed 12‐year‐old and younger players perceived they could predict at older ages (13.6 years old, on average) whether a player has the potential to become a professional soccer player. This suggests that scouts are aware of the idea that early indicators of later performance are often lacking, yet do advise on selection of players at younger ages. Second, when identifying talented players, scouts considered more easily observable attributes, such as technical attributes. However, scouts described these often in a broad sense rather than in terms of specific predictors of future performance. Finally, scouts reported that they assess attributes of players in a structured manner. Yet, they ultimately based their prediction (i.e. final score) on an intuitive integration of different performance attributes, which is a suboptimal strategy according to existing literature. Taken together, these outcomes provide specific clues to improve the reliability and validity of the scouting process.

Highlights
Based on a large sample of soccer scouts, we examine three issues that are important in the process of identifying talented soccer players: The age at which good performance predictions can be made, which attributes are relevant predictors, and how performance predictions are formed.
Scouts who observe players in young age cohorts believe that the age at which they can predict performance is older than the players they typically scout, suggesting that they are aware that early indicators of performance are often lacking.
Technical performance attributes are considered as most important performance predictors by scouts, but these are often described in a broad ‐ rather than specific ‐ sense.
Scouts indicate that they predict performance in a structured manner, but form their overall performance prediction on an intuitive integration of different performance attributes, which can be a suboptimal approach.
The effect of fatiguing lower‐body exercise on punch forces in highly‐trained boxers
Authors: Dunn Emily C. , Humberstone Clare E. , Franchini Emerson , Iredale Fiona K. , Blazevich Anthony J. 
Published: April 2021

ABSTRACTThis study aimed to examine the effect of intense intermittent lower‐body and trunk exercise (rowing) on punching performance in 28 highly‐trained male amateur boxers. Straight‐ and bent‐arm punch performances were assessed with a custom‐built punch integrator using a 3‐min maximal‐effort punch test, completed in both non‐fatigued (ROWpre) and fatigued (ROWpost) states. A within‐subject repeated measures design was implemented; subjects completed ROWpre, then 9 × 1‐min bouts of rowing (1‐min rest intervals), followed by ROWpost. Peak punch force and force‐time variables, including impulse and rate of force development (RFD; calculated to five time points), were assessed. Differences between ROWpre and ROWpost for each punch type (jab, cross, lead‐ and rear‐hand hook) were tested with a linear mixed model, and effect sizes (Cohen's d) were calculated. Results showed significant (p < 0.05) reductions in punch force in ROWpost compared to ROWpre for all punch types as well as significant delays in the time to reach specific force levels, and relative percentages of peak force (RFD) in all punches except the jab. It is likely that fatigue of the lower body and trunk muscles impaired ground reaction force, and thus punch force, production. This effect was larger in punches that involved a greater degree of trunk rotation, crosses and hooks, than in the jab which relies predominantly on arm extension. These findings reveal the negative effect of fatigue on punch force production, and provide evidence that lower‐body and trunk force are important for generating punch force.

Highlights
The ability of the lower body to generate force affects the magnitude of punch force produced in trained boxers.
A bout of intense rowing exercise significantly reduces punch force, and rate of force development. This should be carefully considered when programming and scheduling boxing specific training sessions and strength and conditioning sessions.
While non‐specific fatigue affected the punch performance of boxers, the authors call for further research to examine the effects of fatigue sustained during a boxing bout in comparison to non‐boxing muscular fatigue and a non‐exercise control.