bluuebunny/crossref_metadata_2025 huggingface dataset:
Impact of Approach Angle of an Impinging Cyclone on Generation of Storm Surges and Its Interaction with Tides and Wind Waves
Authors: Pandey Smita , Rao A. D.
Published: October 2019

Detailed investigation is made on the effect of cyclone's approach angle on generation of storm surges and its nonlinear interaction with tides and wind waves using a standalone 2DDI ADCIRC and a coupled ADCIRC+SWAN model. Numerical experiments are executed using 17 idealized straight cyclone tracks of same intensity moving at constant forward speed. The study domain considers an idealized bathymetry with straight coastline and uniform shelf width. All cyclones make landfall at the same location with angles approaching from 10° to 170° with an increment of 10°. The simulations show that the maximum storm surge is computed for tracks land falling with 60o–90o. Increase in the peak storm surge is seen about 15% from 10o–60o, while it decreases by about 13% from 90o–170o. Surge‐wave interaction modifies the maximum water level by about 21–26%. The maximum wave contribution is seen for track with 90o followed by 160o and 20o. During different phases of tide, surge‐tide interaction modifies peak surge, its occurrence, and location as cyclone makes landfall at different angles. The extent of affected coastal stretch is maximum on either side of the landfall for the tracks moving close to the coast, while it is minimum for the perpendicular track (90o), confined only to the right of the landfall. The peak surge‐tide‐wind wave interaction along the coast at both high and low tide is seen about 2–4 hr after the landfall. The interaction along the coast depends on approach angles of the cyclone; however, the total water level is mainly modified by both tidal phase and approach angle.
Five‐Year Measurements of Net Ecosystem CO2 Exchange at a Fen in the Zoige Peatlands on the Qinghai‐Tibetan Plateau
Authors: Liu Xinwei , Zhu Dan , Zhan Wei , Chen Huai , Zhu Qiuan , Hao Yanbin , Liu Wenjun , He Yixin
Published: October 2019

Little is known about the relationship between carbon sequestration and environment in some alpine peatland ecosystems, especially in remote areas such as the Qinghai‐Tibetan Plateau. In the present study, net ecosystem CO2 exchange (NEE) flux was measured from 2013 to 2017 at the Riganqiao fen in the Zoige peatlands on the eastern Qinghai‐Tibetan Plateau using the eddy covariance technique. In the growing season, diurnal CO2 uptake peaks occurred between 12:00 and 14:00, while emission peaks occurred between 21:00 and 22:00. Carbon uptake peak occurred mainly from June to July in the growing season, and the maximum daily net CO2 uptake of −8.4 g C m−2 d−1 was observed in mid‐June 2016. The Riganqiao peatland was a net CO2 sink, with uptake (g C m−2 yr−1) of average −171.4 ± 38.1 during the five years. Photosynthetically active radiation (PAR) and soil temperature (Ts) were significantly correlated with diurnal net CO2 uptake. In growing seasons, PAR was significantly correlated with daytime CO2 uptake, and Ts was a major determinant of ecosystem respiration during growing and nongrowing seasons, although the fitting functions differed between the two seasons. Rainfall influenced interannual variability of cumulative NEE and water table depth (WTD) and volumetric water content (VWC) were both significantly correlated with interannual NEE. Our results suggest that in the long term, peatland NEE is affected mainly by the water regime, which is influenced by soil temperature and water condition.
Hypervelocity Impact Experiments in Iron‐Nickel Ingots and Iron Meteorites: Implications for the NASA Psyche Mission
Authors: Marchi S. , Durda D.D. , Polanskey C.A. , Asphaug E. , Bottke W.F. , Elkins‐Tanton L.T. , Garvie L.A.J. , Ray S. , Chocron S. , Williams D.A.
Published: October 2019

The National Aeronautics and Space Administration (NASA) Psyche mission will visit the 226‐km diameter main belt asteroid (16) Psyche, our first opportunity to visit a metal‐rich object at close range. The unique and poorly understood nature of Psyche offers a challenge to the mission as we have little understanding of the surface morphology and composition. It is commonly accepted that the main evolutionary process for asteroid surfaces is impact cratering. While a considerable body of literature is available on collisions on rocky/icy objects, less work is available for metallic targets with compositions relevant to Psyche. Here we present a suite of impact experiments performed at the NASA Ames Vertical Gun Range facility on several types of iron meteorites and foundry‐cast ingots that have similar Fe‐Ni compositions as the iron meteorites. Our experiments were designed to better understand crater formation (e.g., size, depth), over a range of impact conditions, including target temperature and composition. We find that the target strength, as inferred from crater sizes, ranges from 700 to 1,300 MPa. Target temperature has measurable effects on strength, with cooled targets typically 10–20% stronger. Crater morphologies are characterized by sharp, raised rims and deep cavities. Further, we derive broad implications for Psyche's collisional evolution, in light of available low resolution shape models. We find that the number of large craters (>50 km) is particularly diagnostic for the overall bulk strength of Psyche. If confirmed, the number of putative large craters may indicate that Psyche's bulk strength is significantly reduced compared to that of intact iron meteorites.
Anomalous Phyllosilicate‐Bearing Outcrops South of Coprates Chasma: A Study of Possible Emplacement Mechanisms
Authors: Buczkowski Debra L. , Seelos Kimberly D. , Viviano Christina E. , Murchie Scott L. , Seelos Frank P. , Malaret Erick , Hash Christopher
Published: October 2019

The formation of widespread phyllosilicate‐bearing near‐surface layers on Mars has often been attributed to pedogenesis, a process of weathering basaltic soils by continued exposure to meteoric water percolating down from the surface, which can result in layers of aluminum phyllosilicates forming over layers of iron‐magnesium phyllosilicates. We present evidence of an Fe/Mg‐smectite bearing layer stratigraphically above Al‐phyllosilicates in three circular features to the south of Coprates Chasma, suggesting that some process other than, or in addition to, a single pedogenic sequence must have been involved. A review of several formation mechanisms shows that all models require multiple episodes of aqueous alteration. In addition, only by invoking groundwater alteration in conjunction with pedogenesis can we reconcile the stratigraphic pattern of altered material exposed by these features.
Recovery of Soils From Acidic Deposition May Exacerbate Nitrogen Export From Forested Watersheds
Authors: Lawrence Gregory B. , Scanga Sara E. , Sabo Robert D.
Published: October 2019

Effects of ambient decreases in N deposition on forest N cycling remain unclear as soils recover from acidic deposition. To investigate, repeated soil sampling data were related to deposition, vegetation, and stream data, for 2000–2015 in North and South Buck Creek watersheds, in the Adirondack region of New York, USA. In 63 other Adirondack streams, NO3− concentrations were also compared between 2004–2005 and 2014–2015, and a link between soil calcium and stream NO3− was investigated using data from 387 Adirondack streams that were sampled in either 2003–2005 or 2010–2011. No trends in N export or NO3− concentrations were observed in either Buck watershed despite a 45% decrease in N deposition, although South Buck N export was 2 to 3 times higher than in North Buck, where 48% of deposited N was accounted for by accumulation in the upper soil. In marked contrast, the upper profile in South Buck showed a net loss of N. Increased decomposition appeared likely in South Buck as those soils are adjusted to lower levels of acidifying S deposition, whereas decomposition increases in North Buck were likely suppressed by high levels of natural organic acidity. Stream NO3− concentrations in Buck watersheds bracketed regional results and were consistent with the regional streams that showed no overall change in NO3− concentrations between 2004 and 2014. A negative correlation observed between NO3− concentration and watershed buffering capacity expressed as the ratio of Ca2+ to SO42− also suggested that stream NO3− concentrations were elevated where soil Ca depletion had occurred.
Marked changes in diversity and relative activity of picoeukaryotes with depth in the world ocean
Authors: Giner Caterina R , Pernice Massimo C , Balagué Vanessa , Duarte Carlos M , Gasol Josep M , Logares Ramiro , Massana Ramon
Published: October 2019

Microbial eukaryotes are key components of the ocean plankton. Yet, our understanding of their community composition and activity in different water layers of the ocean is limited, particularly for picoeukaryotes (0.2–3 µm cell size). Here, we examined the picoeukaryotic communities inhabiting different vertical zones of the tropical and subtropical global ocean: surface, deep chlorophyll maximum, mesopelagic (including the deep scattering layer and oxygen minimum zones), and bathypelagic. Communities were analysed by high-tthroughput sequencing of the 18S rRNA gene (V4 region) as represented by DNA (community structure) and RNA (metabolism), followed by delineation of Operational Taxonomic Units (OTUs) at 99% similarity. We found a stratification of the picoeukaryotic communities along the water column, with assemblages corresponding to the sunlit and dark ocean. Specific taxonomic groups either increased (e.g., Chrysophyceae or Bicosoecida) or decreased (e.g., Dinoflagellata or MAST-3) in abundance with depth. We used the rRNA:rDNA ratio of each OTU as a proxy of metabolic activity. The highest relative activity was found in the mesopelagic layer for most taxonomic groups, and the lowest in the bathypelagic. Altogether, we characterize the change in community structure and metabolic activity of picoeukaryotes with depth in the global ocean, suggesting a hotspot of activity in the mesopelagic.
Precise quantitation and sensitive detection of copy number within genetic variations using ligation-mediated droplet digital PCR in plasma
Authors: Tian Hui , Duan Mingyue , Wei Pingping , Hu Fei , Zhao Shuhao , Zhang Zengming , Peng Niancai
Published: October 2019

The analysis of cancer-associated genetic copy number variations (CNVs) has been employed for cancer diagnostics, treatment, and prognostic assessments.
Virus-derived materials: bury the hatchet with old foes
Authors: Wu Jiahe , Wu Honghui , Nakagawa Shinsaku , Gao Jianqing
Published: October 2019

Viruses, with special architecture and unique biological nature, can be utilized for various biomedical applications.
First-principles calculation of the electronic and optical properties of a new two-dimensional carbon allotrope: tetra-penta-octagonal graphene
Authors: Bhattacharya Debaprem , Jana Debnarayan
Published: October 2019

A novel sp2 hybridized planar 2D carbon allotrope consisting of tetra, penta and octagonal (TPO) rings is proposed in this work.
Constant chemical potential cycles for capacitive deionization
Authors: Moreno Daniel , Hatzell Marta C.
Published: October 2019

The thermodynamic path followed during an electrosorption, desorption and solution-switching process, influences the energy consumed per ion removed.
Torsional artificial muscles
Authors: Aziz Shazed , Spinks Geoffrey M.
Published: October 2019

Torsional actuators are of potential application in areas that include smart textiles, exoskeletons, microfluidic mixing, microsensors, photonic displays, and energy-harvesting devices.
Understanding the role of alcohols in the growth behaviour of ZnO nanostructures prepared by solution based synthesis and their application in solar cells
Authors: M. Ramya , T. K. Nideep , V. P. N. Nampoori , M. Kailasnath
Published: October 2019

We report the successful control of the ZnO nanostructures by a simple solution method using alcohols such as methanol, ethanol, butanol, hexanol, octanol and decanol as solvents.
Simple hydrothermal synthesis of defective CeMoSe2 dendrites as an effective electrocatalyst for the electrochemical sensing of 4-nitrophenol in water samples
Authors: Ramki Settu , Sukanya Ramaraj , Chen Shen-Ming , Sakthivel Mani , Wang Jun Yu
Published: October 2019

This work reports the fabrication of a highly selective and novel electrocatalyst for electrochemical sensing applications.
Development of a nickel oxide/oxyhydroxide-modified printed carbon electrode as an all solid-state sensor for potentiometric phosphate detection
Authors: Sedaghat Sotoudeh , Jeong Sookyoung , Zareei Amin , Peana Samuel , Glassmaker Nicholas , Rahimi Rahim
Published: October 2019

This work describes the preparation, characterization and use of a nickel oxide/oxyhydroxide-printed carbon electrode as an efficient potentiometric phosphate sensor.
Sub-60 mV per decade switching in ion-gel-gated In–Sn–O transistors with a nano-thick charge trapping layer
Authors: Liu Wanrong , Sun Jia , Qiu Weijie , Chen Yang , Huang Yulong , Wang Juxiang , Yang Junliang
Published: October 2019

A sub-60 mV per decade switching at room temperature was demonstrated in ion-gel-gated In–Sn–O transistors with a nano-thick charge trapping layer.
Thiamine hydrochloride as a recyclable organocatalyst for the synthesis of bis(indolyl)methanes, tris(indolyl)methanes, 3,3-di(indol-3-yl)indolin-2-ones and biscoumarins
Authors: Mathavan Sivagami , Kannan Keerthana , Yamajala Rajesh B. R. D.
Published: October 2019

Thiamine hydrochloride was identified as an eco-friendly organocatalyst for the synthesis of a broad range of bis(indolyl)methanes, tris(indolyl)methanes, 3,3-di(indol-3-yl)indolin-2-ones and biscoumarin derivatives in good to excellent yields.
An ultra-sensitive label-free electrochemiluminescence CKMB immunosensor using a novel nanocomposite-modified printed electrode
Authors: Adhikari Juthi , Keasberry Natasha Ann , Mahadi Abdul Hanif , Yoshikawa Hiroyuki , Tamiya Eiichi , Ahmed Minhaz Uddin
Published: October 2019

This study presents a novel and ultrasensitive electrochemiluminescence approach for the quantitative assessment of creatine kinase MB (CK-MB).
Droplet-based in situ X-ray absorption spectroscopy cell for studying crystallization processes at the tender X-ray energy range
Authors: Xto Jacinta , Wetter Reto , Borca Camelia N. , Frieh Christophe , van Bokhoven Jeroen A. , Huthwelker Thomas
Published: October 2019

We introduce a new in situ cell for time-resolved reactions involving aerosols/droplets using tender X-ray absorption spectroscopy and related methods.
Electrocoalescence of water in oil emulsions: a DPD simulation study and a novel application of electroporation theory
Authors: Skartlien Roar , Simon Sebastien , Sjöblom Johan
Published: October 2019

Electrocoalescence of water in oil emulsions can be described by electroporation theory and predictions compared well to DPD molecular simulations.
An aptasensor based on the microscopic enumeration of encoding gold nanoparticles for the detection of C-reactive protein
Authors: Zhao Yuanfang , Zhao Jingru , Jin Tian , Sun Shuqing , Liu Wenlan , Tan Ying
Published: October 2019

An aptasensor based on the displacement of encoding AuNPs by analyte molecules was presented. Combined with magnetic separation and DFM imaging, the number of displaced AuNPs was counted, which was correlated to the concentration of the CRP.
A novel method for total chlorine detection using machine learning with electrode arrays
Authors: Li Zhe , Huang Shunhao , Chen Juan
Published: October 2019

Establish soft measurement model of total chlorine: cyclic voltammetry curves, principal component analysis and support vector regression.
Performance of metal–organic frameworks for the adsorptive removal of potentially toxic elements in a water system: a critical review
Authors: Ramanayaka Sammani , Vithanage Meththika , Sarmah Ajit , An Taicheng , Kim Ki-Hyun , Ok Yong Sik
Published: October 2019

This review examines the performance of metal–organic frameworks based on partition coefficient data over the classic maximum adsorption capacities.
Thermodynamic analysis of multivalent binding of functionalized nanoparticles to membrane surface reveals the importance of membrane entropy and nanoparticle entropy in adhesion of flexible nanoparticles
Authors: Farokhirad Samaneh , Bradley Ryan P. , Radhakrishnan Ravi
Published: October 2019

We present a quantitative model for multivalent binding of ligand-coated flexible polymeric nanoparticles (NPs) to a flexible membrane expressing receptors.
Approach of 2D direction of arrival estimation of FMCW traffic radar by utilising 1D array
Authors: Zhang Wei , He Ningyu , He Zishu , Han Minghua
Published: October 2019

The frequency‐modulated continuous wave (FMCW) radar will play a more important role in future intelligent traffic systems due to low cost and high adaptability to complex environments. Generally, a 2D array is utilised to measure range, speed and azimuth and elevation angles (4D) for multiple vehicles simultaneously. However, a traffic radar utilising a 2D array will enhance its system complexity; therefore, the increased cost would make it less superior to LiDAR. In this Letter, an azimuth and elevation angles estimation method of FMCW radar utilising only 1D array is proposed. Thus, it can provide 4D parameters to multiple vehicles simultaneously. The feasibility of the proposed approach is verified by on‐road measurement data.
Cold load pickup model parameters based on measurements in distribution systems
Authors: Hachmann Christian , Lammert Gustav , Hamann Lucas , Braun Martin
Published: October 2019

The electric power demand after an outage can be significantly different from normal values. A major cause of this is the loss of statistic diversity in load devices that interact with some kind of storage. Examples are heating and cooling appliances as well as some applications of pumps and devices with integrated batteries. This phenomenon is known as cold load pickup (CLPU). Changes in load after an outage are of high relevance for investigations of power system restoration, especially active power control and balancing of generation and load. Besides the very fast inrush effects relevant for fast acting protection and short‐term stability, long‐term dynamics, thermal overload of equipment and active power balancing in the presence of uncontrolled distributed generation consider a time frame of minutes to hours. To predict CLPU from physical models, a lot of knowledge is required. Since this information is rarely available in the real‐world applications, the authors investigate typical ranges of CLPU behaviour. The authors analyse measurement data from reconnections after real outages of medium voltage feeders in Germany and provide parameters for the exponential decay model of CLPU. The relevance of the application of the presented model for long‐term stability studies is demonstrated by an example.
Optimal power routing scheme between and within interlinking converters in unbalanced hybrid AC–DC microgrids
Authors: Mahmoudian Esfahani Mohammad , Habib Hany F. , Mohammed Osama A.
Published: October 2019

An optimal power routing (OPR) scheme between and within interlinking converters (ICs) in unbalanced hybrid AC–DC microgrids to minimise the power imbalance factor at the point of common coupling, active power losses, and voltage deviation indices for microgrids in grid‐connected operating mode is proposed in this study. These goals are achieved through a multi‐objective optimisation model by optimal distributing of mobile loads between available charging stations and at the same time, OPR within three phases of three‐phase four‐lag AC/DC converters. Numerical results obtained from implementing the proposed method on the modified IEEE 13‐bus system, as an unbalanced hybrid microgrid, and IEEE 34‐bus test system, as an unbalanced distribution system, demonstrate that proposed OPR algorithm is successful to satisfy the optimisation goals. For this purpose, four case studies are defined and studied to demonstrate the unique features of the proposed OPR comparing with other power routing schemes. In addition to simulation results, the OPR scheme between ICs is realistically implemented at Florida International University smart grid testbed to show the effect of the power routing on energy losses reduction.
Optimisation electric field inverse solving algorithm for non‐destructive detection of voltage on transmission lines
Authors: Wang Ru , Tian Jin , Wu Fei , Zhang Zhenhua , Liu Haishan , Gong Li
Published: October 2019

Electromagnetic field inverse calculation plays a crucial role in solving the problem arising from the design and non‐destructive testing of electromagnetic devices in engineering. In this study, an optimisation algorithm for electric field inverse calculation is proposed, which enables non‐destructive detection of voltage on overhead transmission lines, enhances the robustness of the algorithm and improves the accuracy of calculation. Firstly, 2D and 3D calculation models of electric field are established. A multimedium calculation model with the operating environment of transmission lines considered is proposed. Based on the multimedium calculation method, the calculation environment is categorised into soil, vegetation, geology, and other media, and the correctness of the optimisation method is verified by the finite‐element method‐based model. Secondly, in order to eliminate the measurement noise and electric field distortion to the electric field measurement data, a modified model based on Kalman filter is constructed. Both multimedium calculation method and Kalman filter are applied to the inverse calculation of electric field as an optimisation electric field inverse solving algorithm. Finally, the inverse optimisation method is applied to 220 kV transmission lines and practical 500 kV ultra‐high voltage transmission lines, respectively, to improve the accuracy and robustness of calculation.
Electricity–gas‐integrated energy planning based on reward and penalty ladder‐type carbon trading cost
Authors: Xiaohui Zhang , Xiaoyan Liu , Jiaqing Zhong , Wenbo Gao
Published: October 2019

Given the background of energy Internet and low‐carbon electricity, the integrated energy system has become an important carrier of energy conservation and emission reduction. This study establishes an electric–gas‐integrated energy system planning model that considers carbon trading. First, carbon trading is introduced into the planning model. A reward and punishment ladder‐type carbon trading cost model is proposed, and its restriction on carbon emission is analysed. On this basis, a planning model is established, to minimise the total costs including the investment cost, operation cost, and carbon trading cost. Finally, the discrete bacterial colony chemotaxis algorithm is applied to solve this model. The simulation results of the three planning models are compared and analysed by simulation examples, which verify the effectiveness of the proposed model in balancing the low carbon and economic efficiency of the system. The impact of carbon trading price on system planning and operation is analysed.
Control of superconducting magnetic energy storage systems in grid‐connected microgrids via memetic salp swarm algorithm: An optimal passive fractional‐order PID approach
Authors: Yang Bo , Yu Lei , Zhang Xiaoshun , Wang Junting , Shu Hongchun , Li Shengnan , He Tingyi , Yang Lei , Yu Tao
Published: October 2019

This study proposes an optimal passive fractional‐order proportional‐integral derivative (PFOPID) control for a superconducting magnetic energy storage (SMES) system. First, a storage function is constructed for the SMES system. Moreover, it has carefully reserved favourable terms for purpose of making full use of the physical properties of the SMES systems, while a fractional‐order PID (FOPID) structure is adopted as the attached input for purpose of further improving its dynamical responses. In addition, a memetic salp swarm algorithm is adopted to optimise and tune the control gains of the proposed method, which can achieve a suitable trade‐off between global exploration and local exploitation, so as to realise the optimal control performance. Case studies, e.g. (i) active and reactive power supply, (ii) system recovery capability under power grid fault, (iii) power support under the infiltration of random renewable energy and (iv) robustness of system parameter uncertainty is studied, and the availabilities and benefits of POFPID control over PID control, FOPID control and passive control based on interconnection and damping assignment passivity‐based control are comprehensively investigated. Lastly, the feasibility of PFOPID control is checked by hardware‐in‐the‐loop experiment based on a dSpace.
Automatic cloud segmentation from INSAT‐3D satellite image via IKM and IFCM clustering
Authors: A Pugazhenthi , Kumar Lakshmi Sutha
Published: October 2019

Cloud extraction and classification from satellite imagery is important for many applications in remote sensing. Satellite images are segmented based on distance, intensity and texture of the images. The popular segmentation algorithms, k‐means (KM) and fuzzy c‐means (FCM) clustering algorithms, face some problems such as unknown number of groups, unknown initialization and dead centers. In this paper, an unsupervised pixel classification by the KM and FCM algorithms is improved and the selection of centroids is made automatic. The proposed improved k‐means (IKM) and improved fuzzy c‐means (IFCM) clustering algorithms segment the INSAT‐3D satellite's thermal infrared image into low‐level, middle‐level, high‐level clouds and non‐cloudy region. As human beings can easily find the clouds in the satellite images, visible image is used to differentiate the clouds from the background. A threshold is found from the histogram of the visible image to separate the cloudy and non‐cloudy pixels. The other three thresholds to divide the clouds into three types are found from the thermal infrared image's histogram. The segmentation results of IKM and IFCM algorithms are compared with the existing segmentation algorithms. The comparison shows that IFCM algorithm matches well with original image followed by IKM algorithm as compared with existing algorithms.
Reversible contrast enhancement for medical images with background segmentation
Authors: Wu Hao‐Tian , Huang Qi , Cheung Yiu‐ming , Xu Lingling , Tang Shaohua
Published: October 2019

Contrast enhancement (CE) of medical images is helpful to bring out the unclear content in the interested regions. Recently, reversible CE has been proposed so that the original version of a contrast‐changed image can be exactly recovered. This property can be used to save storage space or facilitate the archiving system. To enhance the regions of interest (ROI) without introducing visual distortions, the technique of image segmentation (e.g. using Otsu's method) has been used to obtain the background before conducting the CE process. To segment the ROI more accurately, an interactive algorithm called GrabCut is employed in the proposed scheme. In addition, a new preprocessing strategy is adopted to preserve the image quality through the CE process. Consequently, the content in the selected regions can be better brought out while the reversibility of the CE process is achieved. The experimental results on 30 chest radiograph images and 20 magnetic resonance images have demonstrated the efficacy of the proposed scheme for reversible CE. The evaluation results are provided to show the better performances of the proposed method in achieving CE effects and preserving image quality.
Effect of pooling strategy on convolutional neural network for classification of hyperspectral remote sensing images
Authors: Bera Somenath , Shrivastava Vimal K.
Published: October 2019

The deep convolutional neural network (CNN) has recently attracted the researchers for classification of hyperspectral remote sensing images. The CNN mainly consists of convolution layer, pooling layer and fully connected layer. The pooling is a regularisation technique and improves the performance of CNN while reducing the computation time. Various pooling strategies have been developed in literature. This study shows the effect of pooling strategy on the performance of deep CNN for classification of hyperspectral remote sensing images. The authors have compared the performance of various pooling strategies such as max pooling, average pooling, stochastic pooling, rank‐based average pooling and rank‐based weighted pooling. The experiments were performed on three well‐known hyperspectral remote sensing datasets: Indian Pines, University of Pavia and Kennedy Space Center. The proposed experimental results show that max pooling has produced better results for all the three considered datasets.
Correction of complex purple fringing by green‐channel compensation and local luminance adaptation
Authors: Malik Parveen , Karthik Kannan
Published: October 2019

In natural photography, defects in camera imaging pipeline often result in some form of colour noise or distortion. Nature of this distortion is generally intertwined with scene dependent variables such as positioning, intensity and composition of light source and local object colour reflectivity. One such defect is called purple fringing aberration (PFA). PFA problems are of two types, one of which corresponds to a localised fringing effect near high contrast zones (termed as Isolated PFA or IS‐PFA) and the second which corresponds to a widespread semi‐transparent purple haze over a large part of natural scene (termed as complex PFA or C‐PFA). Much of the PFA‐correction solutions have been driven towards IS‐PFA and very little towards C‐PFA. Based on a premise that in C‐PFA, green channel is heavily suppressed and noisy, while colour information in red and blue channels are largely conserved, authors propose a green‐channel compensation algorithm for restoring true natural colours in fringe affected region. To correct white‐tuft produced by proposed compensation algorithm, they also devise a suitable localised luminance adaptation procedure to equalise perceived changes in luminance profile. Comparisons with state‐of‐the‐art methods devised to combat this purple haze effect yield promising results for a majority of test cases.
Hyperspectral image restoration by subspace representation with low‐rank constraint and spatial‐spectral total variation
Authors: Ye Jun , Zhang Xian
Published: October 2019

Hyperspectral images (HSIs) restoration is an important preprocessing step. The spectral vectors in HSI can be separated into different classification based on the land‐covers, which means the spectral space can be regarded as the union of several low‐rank subspaces. Subspace low‐rank representation (SLRR) is powerful in exploring the inner low‐rank structure and has been applied for HSI restoration. However, the traditional SLRR only seek for the rank‐minimum representation under a given dictionary, which may treat the structured sparse noise as inherent low‐rank components. In addition, the SLRR framework cannot make full use of the spatial information. In this study, a framework named subspace representation with low‐rank constraint and spatial‐spectral total variation is proposed for HSI restoration. In which, an artificial rank constraint is introduced to control the rank of the representation result, which can improve the removal of the structured sparse noise and exploit the intrinsic structure of spectral space more effectively. Meanwhile, the spatial‐spectral total variation regularisation is applied to enhance the spatial and spectral smoothness. Several experiments conducted in simulated and real HSI datasets demonstrate that the proposed method can achieve a state‐of‐the‐art performance both in visual quality and quantitative assessments.
Backlit images enhancement using global tone mappings and image fusion
Authors: Buades Antoni , Lisani Jose‐Luis , Petro Ana Belen , Sbert Catalina
Published: October 2019

The authors present a method for the enhancement of backlit images, i.e. images in which the main source of light is behind the photography subject. These images contain, simultaneously, very dark and very bright regions. In this situation, a single tone mapping function is unable to enhance the whole image. They propose the use of several such tone mappings, some of them enhancing the dark regions while others enhancing the bright regions, and then the combination of all these results using an image fusion algorithm. Qualitative and quantitative results confirm the validity of the proposed method.
Enhanced copy–paste forgery detection in digital images using scale‐invariant feature transform
Authors: Selvaraj Priyadharsini , Karuppiah Muneeswaran
Published: October 2019

Image forgery detection and localisation is one of the principal problems in digital forensics. Copy–paste forgery in digital images is a type of forgery in which an image region is copied and pasted at another location within the same image. In this work, the authors propose a methodology to detect and localise copy‐pasted regions in images based on scale‐invariant feature transform (SIFT). Existing copy‐paste forgery detection in images using SIFT and clustering techniques such as hierarchical agglomerative and density‐based spatial clustering of applications with noise resulted many false pixel detections. They have introduced sensitivity‐based clustering along with SIFT features to identify copy–pasted pixels and disregard the false pixels. Experimental evaluation on public image datasets MICC‐F220, MICC‐F2000 and MICC‐F8 multi shows that the proposed method is showing improved performance in detecting and localising copy‐paste forgeries in images than the existing works. Also the proposed work detects multiple copy–pasted regions in the images and is robust to attacks such as geometrical transformation of copied regions such as scaling and rotation.
Improving 3D reconstruction accuracy in wavelet transform profilometry by reducing shadow effects
Authors: López‐Torres Claudia‐Victoria , Salazar Colores Sebastián , Kells Kevin , Pedraza‐Ortega Jesús‐Carlos , Ramos‐Arreguin Juan‐Manuel
Published: October 2019

Wavelet transform profilometry is a three‐dimensional (3D) reconstruction method based on the structured light technique of fringe pattern projection, widely used because it is a non‐invasive, high‐performance 3D reconstruction method. The presence of shadows created by the object in the image capture process is an obstacle in obtaining accurate 3D reconstructions, as they add noise to the phase data, leading to artefacts in object reconstruction, even when using robust phase‐unwrapping algorithms. Since shadows present diverse intensities and shapes, detecting and eliminating their effects are challenging tasks. This work presents a novel method to detect shadow regions and reduce their effects in 3D reconstruction. The proposed method uses coloured fringe patterns to detect the shadows and mathematical morphology to condition the outlines of the shadow regions. The shadow outline information is used to interpolate the background‐plane fringe pattern onto the captured scene, where the shadows are detected. The mean squared error (MSE) of the reconstructed objects is reduced to 25% of the MSE without shadow removal, on an average, when using the Bioucas phase‐unwrapping method. When using the Ghiglia phase‐unwrapping method, the MSE reduction is to 8.3%, on an average, of the MSE in the shadow case.
Miniaturised tri‐band rhombus‐shaped metamaterial‐inspired antenna with gain enhancement using complementary closed ring resonators
Authors: Gupta Ashish , Bansal Bajrang , Kumar Mishra Vimal , Agrawal Anand
Published: October 2019

In this study, a rhombus‐shaped patch antenna is proposed using metamaterial transmission line. The motivation of this work is to overcome the problem of low gain while designing miniaturised antennas. The proposed design is based on coplanar waveguide feeding technique. A rhombus‐shaped patch is chosen in this structure in which striplines are provided to connect the ground planes and to obtain the shunt inductance. Asymmetric meandered line inductors are integrated with the striplines for miniaturising the electrical size of the antenna. Further to improve the gain of the antenna in the lower bands, asymmetric ground plane and complementary closed ring resonator have been employed in the proposed structure. The electrical size of the proposed antenna is 0.168λ0 × 0.151λ0 corresponding to the physical size of 25 mm × 22.5 mm, where λ0 = free space wavelength at 2.02 GHz. Considering below −10 dB input reflection coefficient, this antenna operates in three bands covering 1.96–2.07, 4.06–4.72, and 6.43–7.79 GHz. In addition, the proposed antenna exhibits gain of 1.49, 2.68, 2.19, and 4.31 dB at 2.02, 4.48, 6.72, and 7.43 GHz, respectively, in the maximum direction of radiation.
Minimum phase bipolar converter for DC microgrid applications
Authors: Kumar Pawan , Singh Rajeev Kumar , Mahanty Ranjit
Published: October 2019

This study proposes a minimum phase bipolar converter for dc microgrid applications, which is derived from the combination of and Sepic converters with some modifications in both of them in order to get a minimum phase system. In the proposed bipolar converter (PBC), the equivalent series resistance of transfer capacitors of both and Sepic converters is increased by adding resistances and introducing magnetic coupling between the filter inductors of the Sepic converter with a series RC network. These circuit modifications eliminate right half plane zero from the PBC and thereby make it a minimum phase, unlike the conventional –Sepic bipolar converter. Due to the minimum phase behaviour, the proposed converter can deliver high load current, achieves high bandwidth and facilitates simpler controller design in contrast to the conventional –Sepic bipolar converter. Detailed steady state and dynamic modelling of the PBC has been carried out in order to show its advantages. A 500 W laboratory prototype has been developed and implemented using field programmable gate array‐based system to verify the operation of the proposed converter.
Adaptive maintain power signature scheme for power over ethernet system
Authors: Li Yongyuan , Zhu Zhangming
Published: October 2019

Power over Ethernet (PoE) technology has been widely used in networking market for its space‐saving, flexibility and low cost. As the PoE system needs to meet maintain power signature (MPS) requirements specified by the IEEE standard, it is important for powered device (PD) to draw a predetermined minimum current. If the PD current goes below the minimum current, the power sourcing equipment (PSE) assumes the PD has been disconnected and terminates operating voltage. If a fixed current is added to exceed the minimum current, a phenomenon of power wasting will be caused during standby or ultra‐low power mode. This study proposes an adaptive MPS scheme to achieve power‐saving and meet the MPS requirements. It consists of current comparator and MPS circuit to extract the periodic pulsed current for MPS requirements. The proposed scheme has been fabricated in 0.18 μm 100 V Bipolar‐CMOS‐DMOS process adding no extra pin and an area is 1.45 × 2.23 mm2. Test results show that the proposed interface sources a periodic pulsed current with a period of 318 ms and 25% duty cycle to tackle the issue of MPS absence in very low power condition.
Recognition method of voltage sag causes based on two‐dimensional transform and deep learning hybrid model
Authors: Zheng Zhicong , Qi Linhai , Wang Hong , Pan Aiqiang , Zhou Jian
Published: October 2019

The voltage sags’ caused recognition is the basis for formulating governance plans and clarifying liabilities for accidents. The diversification of smart grid equipment, the grid‐connected power generation of new energy sources and the regional differentiation of power consumption modes pose new challenges to the traditional methods. In this study, a method based on deep learning hybrid model is proposed. The convolutional neural network is used to flexibly receive the voltage after two‐dimensional transformation, so as to automatically obtain the time series and spatial characteristics of the voltage sag signals. The deep belief network is used to replace the fully connected layers in convolutional neural network, thereby enhancing the multi‐label classification ability of the model. The parameters obtained by the unsupervised training of the stacked sparse denoising auto‐encoder are used to initialise the weight of deep belief network, thereby improving the convergence speed and the anti‐noise performance of the model. Iterative training and repeated testing of the network using pre‐processed simulation data and actual recorded data verify the high recognition accuracy and strong anti‐noise performance of the hybrid model. Compared with the traditional methods, the hybrid model also has good generalisation ability and can be effectively applied in practical engineering.
Three‐dimensional rotatable omnidirectional MCR WPT systems
Authors: Li Wanlu , Wang Quandi , Wang Yingcong , Kang Jianwei
Published: October 2019

Recently, Wi‐Fi wireless power transfer (WPT) has attracted increasing attention. In this study, a rotatable three‐dimensional (3D) transmitter (Tx) is first designed which only needs to be powered by a single source without current amplitude or phase control. Mutual inductance formulas of the Tx and a receiver (Rx) during the Tx's 3D rotation are derived based on Biot‐Savart law and rotating matrix, and the maximum coupling areas are obtained. A method of achieving equal coupling of Rxs with the Tx which simultaneously charges two Rxs is proposed. A real rotatable 3D Tx and an omnidirectional magnetically coupled resonant (MCR) WPT prototype are fabricated, and the theoretical analysis is verified by simulation and experiment. Experiment displays that the maximum or desired coupling of single or two Rxs in 3D space can be obtained by calculated rotation combinations. The maximum power transfer efficiency (PTE) of the system can reach 90.2% with the transmission distance of 1.5 times the radius of Tx. Finally, the PTE can be maintained at 73% with the transmission distance varying from 18 to 27 cm by a novel method. The proposed 3D technique could be applied to many fields including Wi‐Fi WPT home devices, remote sensing and some mechanical systems.
Dynamic model to predict the characteristics of the electric arc around a polluted insulator
Authors: Ouchen Lyamine , Bayadi Abdelhafid , Boudissa Rabah
Published: October 2019

This study presents a dynamic arc model of a polluted insulator based on the formulation of the Obenaus model and the Hampton criterion for discharge propagation. An experiment was conducted on a practical glass insulator installed in the Algerian network for the purpose of measuring the flashover voltage and estimating the arc parameters (A and N) using a genetic optimisation algorithm. The parameters used in the dynamic model were the arc current, arc length, and arc resistance calculated using MATLAB. Moreover, an attempt was made with finite element software to calculate the voltage and electric‐field throughout the insulator surface with and without the presence of contaminants. Finally, the obtained simulation and experimental results showed high performances under operational conditions and respect IEC 60060‐1 standard recommendations.
Evaluation of statistical methods used in the estimation of breakdown voltage distribution
Authors: Andrade Arthur Francisco , Costa Edson G. , Oliveira Neto Antonio B. , Lira George R.S. , Ferreira Tarso V.
Published: October 2019

Multiple‐level and up‐and‐down test methods are commonly employed in laboratories to obtain the breakdown voltage distribution of self‐restoring insulation, which is applied for equipment evaluation and for risk calculation in insulation coordination studies. This study investigates the reliability of the methods and proposes a methodology for evaluating their performance. The accuracy and precision of the estimated distribution parameters were analysed considering the variation of the test parameters. Algorithms that simulate the random nature of the tests were developed and applied in simulations. Then, a case study of risk calculation was carried out. The results indicated that both methods estimate the critical flashover voltage with acceptable accuracy and precision, even for the minimum parameters defined by standards. However, estimating the standard deviation is the critical step of the tests. The proposed methodology allows parameter definition for a given reliability requirement in the case of the constant voltage method. In the case of the up‐and‐down method, however, high dispersion was observed for all analysed cases, which indicates that this method presents low reliability for calculating flashover risk and, therefore, its use for insulation coordination studies is not recommended.
Deciphering the expression dynamics of ANGPTL8 associated regulatory network in insulin resistance using formal modelling approaches
Authors: Siddiqa Amnah , Ahmad Jamil , Ali Amjad , Khan Sharifullah
Published: October 2019

ANGPTL8 is a recently identified novel hormone which regulates both glucose and lipid metabolism. The increase in ANGPTL8 during compensatory insulin resistance has been recently reported to improve glucose tolerance and a part of cytoprotective metabolic circuit. However, the exact signalling entities and dynamics involved in this process have remained elusive. Therefore, the current study was conducted with a specific aim to model the regulation of ANGPTL8 with emphasis on its role in improving glucose tolerance during insulin resistance. The main contribution of this study is the construction of a discrete model (based on kinetic logic of René Thomas) and its equivalent Stochastic Petri Net model of ANGPTL8 associated Biological Regulatory Network (BRN) which can predict its dynamic behaviours. The predicted results of these models are in‐line with the previous experimental observations and provide comprehensive insights into the signalling dynamics of ANGPTL8 associated BRN. The authors’ results support the hypothesis that ANGPTL8 plays an important role in supplementing the insulin signalling pathway during insulin resistance and its loss can aggravate the pathogenic process by quickly leading towards Diabetes Mellitus. The results of this study have potential therapeutic implications for treatment of Diabetes Mellitus and are suggestive of its potential as a glucose‐lowering agent.
Real‐time energy storage management system of a nanogrid integrating photovoltaics and V2G operation
Authors: Bampoulas Adamantios , Karlis Athanasios
Published: October 2019

The widespread penetration of electric vehicles (EVs) in the automotive market will create not only concerns about additional energy burden on power grids but also incentives to further encourage vehicle to grid (V2G) functionalities. The integration of EVs with intermittent renewables requires complex control systems due to the need to predict and manage data related to user behaviour and climate. In this study, a real‐time energy storage management system was developed to accommodate V2G technology integration in a residential nanogrid considering no prior knowledge about the future system's state. The rule‐based algorithm developed maximises the direct use of solar energy, ensures a user‐determined driving range and provides ancillary services to the utility grid in real‐time through an autonomous distributed control. The considered residential nanogrid set up was modelled via Matlab/Simulink and the corresponding results are demonstrated and discussed. From simulations, it is shown that the smart house designed integrates the V2G technology so that the nanogrid provides ancillary services to the bulk power system causing the least possible energy burden on the utility.