bluuebunny/crossref_metadata_2025 huggingface dataset:
Footprint of Tropical Mesoscale Convective System Variability on Stratospheric Water Vapor
Authors: Dong W. H. , Lin Y. L. , Zhang M. H. , Huang X. M.
Published: February 2020

Mesoscale convective systems (MCSs) play a dominant role in tropical climate. However, the variabilities of their occurrences on a tropical‐wide scale remain elusive, and the way they impact the tropical stratospheric moisture remains under debate. Based on a comprehensive global MCS data set during 1985–2008, we detect distinct transitions in tropical MCS activities, with the occurrence frequency of MCS during 1995–2002 being significantly lower than those before and after this period by over 10%. The stepwise transition of tropical MCSs has a significant impact on stratospheric water vapor: Active MCS occurrences result in an overall drier stratosphere, and vice versa. We demonstrate that these changes are closely related to the sea surface temperature pattern in the tropical central Pacific and the associated Walker circulation shift on convective systems. Our results suggest that the sea surface temperature variability in tropical central Pacific may exert an important forcing on the stratospheric water vapor.
Observational Evidence of State‐Dependent Positive and Negative Land Surface Feedback on Afternoon Deep Convection Over the Southern Great Plains
Authors: Qiu Shaoyue , Williams Ian N.
Published: February 2020

The detection of soil moisture‐precipitation feedback is complicated by the dependence of feedback sign on atmospheric state and cloud types. We evaluated responses of convective clouds to changes in surface evaporative fraction (EF) from satellite and ground‐based measurements over the Southern Great Plains in summer months. Strong responses to EF were inferred only after accounting for tropospheric states supporting systematically positive or negative responses. State dependence (inferred from controlled model experiments) explains the weak response found in previous studies. The probability of transitions from shallow to deep cumulus, and subsequent precipitation onset, increases by 58% over drier surfaces in weakly stratified environments having deeper boundary layers. Boundary layer dynamics play a more important role than low‐level relative humidity in these environments. Wetter surfaces yield increased deep convection in moist and thermally stratified environments. The distinct pathways of convective initiation over dry and wet land surfaces can play important roles in drought onset and termination.
Local‐Time Variabilities of March Equinox Daytime SABER CO2 in the Upper Mesosphere and Lower Thermosphere Region
Authors: Salinas Cornelius Csar Jude H. , Chang Loren C. , Liang Mao‐Chang , Yue Jia , Qian Liying , Gan Quan , Chiu Yi‐Chung , Russell James , Mlynczak Martin
Published: February 2020

This work reports the analysis of the local‐time variations of daytime CO2 in the Upper Mesosphere and Lower Thermosphere region as observed by the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument onboard the Thermosphere Ionosphere Mesosphere Energetics and Dynamics satellite. Results show that daytime SABER CO2 in the upper mesosphere between latitudes 30°S and 50°N is lower in the morning than in the afternoon. The same was found in the lower thermosphere but between latitudes 50°S and 50°N. The opposite was found in the upper mesosphere between 50°S and 30°S. These results are compared to simulations of CO2 by the Whole Atmosphere Community Climate Model–eXtended. It was found that the local‐time variations of Whole Atmosphere Community Climate Model–eXtended CO2 are weaker than SABER CO2. Model diagnostics indicated that these local‐time variations in the model are driven primarily (secondarily) by strong vertical (meridional) gradients in Upper Mesosphere and Lower Thermosphere CO2 volume mixing ratios and strong local‐time variations in vertical (meridional) winds. This work concludes that SABER CO2 shows significant local‐time variations that are not well simulated by Whole Atmosphere Community Climate Model–eXtended, and we suggest that this is likely because of weaker tidal forcing in the model.
Three‐Dimensional Hydrochemical Model for Dissolutional Growth of Fractures in Karst Aquifers
Authors: Li Sanbai , Kang Zhijiang , Feng Xia‐Ting , Pan Zhejun , Huang Xiaote , Zhang Dongxiao
Published: February 2020

This paper is intended to present a newly developed, comprehensive model to understand hydrochemical behaviors related to dissolutional growth of complex fractures underground. Under a fully implicit solution framework, the finite volume approach is employed to solve the reactive‐convective‐dispersive system. Based on the embedded discrete fracture model, a novel modeling approach is proposed to describe dissolutional fractures with various apertures in three dimensions (3‐D). This model is verified against preexisting numerical models. Then, a 3‐D field case study regarding hypogene speleogenesis in a deep‐seated, artesian setting is carried out, based on field data concerning karst terrain compiled from Western Ukraine. Finally, we perform a case study to elucidate the finger‐like dissolution process related to a synthetic 3‐D fracture network in gypsum and limestone with heterogeneous aperture fields. Simulation results suggest that (a) the combination of the kinetic trigger mechanism and the transverse speleogenesis concept favors the generation of hierarchical caves in homogeneous fractures; (b) the mechanism of reactive infiltration instabilities determines dissolutional propagation in gypsum with rough fractures; and (c) in limestone, nonlinear kinetics matters for both uniform‐ and variable‐aperture fractures.
Rh(iii)-Catalyzed diastereoselective transfer hydrogenation: an efficient entry to key intermediates of HIV protease inhibitors
Authors: Wang Fangyuan , Zheng Long-Sheng , Lang Qi-Wei , Yin Congcong , Wu Ting , Phansavath Phannarath , Chen Gen-Qiang , Ratovelomanana-Vidal Virginie , Zhang Xumu
Published: February 2020

A highly efficient diastereoselective transfer hydrogenation of α-aminoalkyl α′-chloromethyl ketones catalyzed by a tethered rhodium complex was developed and successfully utilized in the synthesis of the key intermediates of HIV protease inhibitors.
Synthesis and characterization of high affinity fluorogenic α-synuclein probes
Authors: Lengyel-Zhand Zsofia , Ferrie John J. , Janssen Bieneke , Hsieh Chia-Ju , Graham Thomas , Xu Kui-ying , Haney Conor M. , Lee Virginia M.-Y. , Trojanowski John Q. , Petersson E. James , Mach Robert H.
Published: February 2020

Fluorescent molecules are powerful tools for imaging α-synuclein pathology. Here, we demonstrate that benzofuranone derivatives have high affinity for α-synuclein and display different binding to α-synucleinopathies in post-mortem brain tissue.
In situ processed tungsten carbide/carbon black-supported platinum electrocatalysts for enhanced electrochemical stability and activity
Authors: Na Hyunwoong , Choi Hanshin , Oh Ji-Won , Kim Da Bin , Cho Yong Soo
Published: February 2020

An in situ synthesis technique of tungsten carbide on carbon black support via cathodic arc deposition is introduced to satisfy both the performance-efficiency and long-term durability of Pt-based electrocatalysts.
Surface modified cellulose nanomaterials: a source of non-spherical nanoparticles for drug delivery
Authors: Khine Yee Yee , Stenzel Martina H.
Published: February 2020

Cellulose nanomaterials, often called nanocellulose, have created a lot of buzz as a renewable building block for new materials. In this review, the steps necessary to generate soluble nanocellulose-based drug carriers are discussed, which includes surface modifications and toxicity.
Hollow-shell structured porous CoSe2 microspheres encapsulated by MXene nanosheets for advanced lithium storage
Authors: Hong Lin , Ju Shunlong , Yang Yunhe , Zheng Jiening , Xia Guanglin , Huang Zhenguo , Liu Xiaoyun , Yu Xuebin
Published: February 2020

Cobalt diselenide (CoSe2), a representative transition-metal chalcogenide (TMC), is attracting intensive interest as an anode material for lithium ion batteries (LIBs), in view of its high specific capacity based on the conversion reaction mechanism.
Dual channel ion imprinted fluorescent polymers for dual mode simultaneous chromium speciation analysis
Authors: Lu Hongzhi , Xu Shoufang
Published: February 2020

We report core shell structured ion imprinted fluorescent polymers structure for blue and red dual channel simultaneous chromium speciation analysis based on the inner filter effect and electron transfer dual mode.
Homoleptic versus heteroleptic trinuclear systems with mixed l-cysteinate and d-penicillaminate regulated by a diphosphine linker
Authors: Hanprasit Sasikarn , Yoshinari Nobuto , Saito Daisuke , Kato Masako , Konno Takumi
Published: February 2020

The generation of homoleptic versus heteroleptic coordination compounds was controlled by slight modification of the diphosphine linker in a digold(i) metalloligand.
Mono-functionalized derivatives and revised configurational assignment of amide naphthotubes
Authors: Yao Huan , Wang Xiaoping , Xie Mo , Wang Yu-Mei , Quan Mao , Yang Liu-Pan , Jiang Wei
Published: February 2020

A pair of mono-functionalized amide naphthotubes with one alkyne and three carboxylate groups has been synthesized, and they show different binding behavior from its parent naphthotubes, presumably due to the self-inclusion of the alkyne group.
A nonswellable gradient hydrogel with tunable mechanical properties
Authors: Xu Pingping , Xu Huaxiu , Yang Yang , Wang Xionglei , An Wenli , Hu Yan , Xu Shimei
Published: February 2020

A bone-like nonswellable gradient hydrogel with adjustable mechanical properties was prepared by an acid-heat treatment of polyamide-based hydrogels.
Classification method based on the deep structure and least squares support vector machine
Authors: Ma Wenlu , Liu Han
Published: February 2020

Support vector machines (SVMs) are one of the most representative shallow network models and have good generalisation abilities in small data sets. In this Letter, a new classification method based on the deep structure and least squares SVM (LSSVM) is proposed. For large‐scale data sets, the method builds the structures of a multi‐layer SVM. Using edge detection and the K‐means algorithm, the sample set is compressed into a smaller sample set, which is used to train the LSSVM model of each layer and the discriminant classification function is obtained. Finally, this method is applied to UCI data sets and compared with several density‐dependent quantised LSSVM methods and other methods. The experimental results show that the method has good performance in solving the large‐scale data set classification problem.
Micro‐Doppler effect removal in ISAR imaging based on Radon‐Laplace method
Authors: Li Hongzhi , Wang Xin , Wang Yong
Published: February 2020

In inverse synthetic aperture radar (ISAR) imaging, the high‐resolution images can be obtained by using Range‐Doppler algorithm. However, the rotational parts of the complex moving targets induce micro‐Doppler (m‐D) effects which influence the quality of ISAR imaging. In this Letter, a novel method of Radon‐Laplace based on the Radon transform (RT) and the Laplace operator is proposed to reduce the m‐D effect in ISAR imaging. For this method, the RT and Laplace operator are used to extract the rigid body parts in the short‐time Fourier transform domain. Then, the rigid body parts can be got through a corresponding filter on the basis of the extraction results. The simulation and measured data results demonstrate the effectiveness of the proposed method.
Dop‐NET: a micro‐Doppler radar data challenge
Authors: Ritchie M. , Capraru R. , Fioranelli F.
Published: February 2020

Radar sensors have a new growing application area of dynamic hand gesture recognition. Traditionally radar systems are considered to be very large, complex and focused on detecting targets at long ranges. With modern electronics and signal processing it is now possible to create small compact RF sensors that can sense subtle movements over short ranges. For such applications, access to comprehensive databases of signatures is critical to enable the effective training of classification algorithms and to provide a common baseline for benchmarking purposes. This Letter introduces the Dop‐NET radar micro‐Doppler database and data challenge to the radar and machine learning communities. Dop‐NET is a database of radar micro‐Doppler signatures that are shareable and distributed with the purpose of improving micro‐Doppler classification techniques. A continuous wave 24 GHz radar module is used to capture the first contributions to the Dop‐NET database and classification results based on discriminating these hand gestures as shown.
Implementation of energy‐efficient fast convolution algorithm for deep convolutional neural networks based on FPGA
Authors: Li W.‐J. , Ruan S.‐J. , Yang D.‐S.
Published: February 2020

The state‐of‐the‐art convolutional neural networks (CNNs) have been widely applied to many deep neural networks models. As the model becomes more accurate, both the number of computation and the data accesses are significantly increased. The proposed design uses the row stationary with network‐on‐chip and the fast convolution algorithm in process elements to reduce the number of computation and data accesses simultaneously. The experimental evaluation which using the CNN layers of VGG‐16 with a batch size of three shows that the proposed design is more energy‐efficient than the state‐of‐the‐art work. The proposed design improves the total GOPs of the algorithm by 1.497 times and reduces the on‐chip memory and off‐chip memory accesses by 1.07 and 1.46 times than prior work, respectively.
Reconstruction of C&C channel for P2P botnet
Authors: Jafari Dehkordi Mohammad , Sadeghiyan Babak
Published: February 2020

Breaking down botnets has always been a big challenge. The robustness of command and control (C&C) channels is increased, and the detection of botmaster is harder in peer‐to‐peer (P2P) botnets. In this study, the authors proposed a probabilistic method to reconstruct the topologies of the C&C channel for P2P botnets. Due to the geographic dispersion of P2P botnet members, it is not possible to supervise all members, and there does not exist all necessary data for applying other graph reconstruction methods. So far, no general method has been introduced to reconstruct C&C channel topology for all type of P2P botnet. In their method, the probability of connections between bots is estimated by using the inaccurate receiving times of several cascades, network model parameters of C&C channel, and end‐to‐end delay distribution of the Internet. The receiving times can be collected by observing the external reaction of bots to commands. The results of their simulations show that more than 90% of the edges in a 1000‐member network with node degree mean 50, have been accurately estimated by collecting the inaccurate receiving times of 22 cascades. In case the receiving times of just half of the bots are collected, this accuracy of estimation is obtained by using 95 cascades.
4‐ary 14/16 modulation code for reducing two‐dimensional inter‐symbol interference
Authors: Kim Juri , Jeong Seongkwon , Lee Jaejin
Published: February 2020

Holographic data storage (HDS) can access data in a short amount of time and can also quickly transmit data because HDS records and reads data in units of pages. Thus HDS is regarded as a promising candidate for future optical recording storage systems. Conventional storage systems such as CD, DVD, and HDD have one‐dimensional (1D) inter‐symbol interference (ISI). However, HDS has a 2D ISI that degrades performance. In this study, to avoid and overcome the 2D‐ISI problem, the authors propose a 14/16 modulation code for 4‐ary HDS systems which represents 2 bits on each pixel. The proposed 14/16 modulation code allows a bit of unwanted ISI cases in order to raise the code rate, but it has a higher code rate but similar performance compared to a 3/4 modulation code that has no unwanted ISI cases.
Adaptive modulation and frame length method based on Moore state machine in LTE‐R communication system
Authors: Chen Mengjia , Zhao Yisheng , Gao Jincheng , Chen Zhonghui
Published: February 2020

In this study, the problem of adaptive modulation and frame length (AMFL) is investigated in long‐term evolution for railway (LTE‐R) communication system. By considering the effect of frame length, a novel AMFL strategy based on Moore state machine (MSM) is proposed. The influence of the frame length on the goodput is discussed by theoretical analysis and simulation evaluation. According to modulation and frame length schemes (MFLSs) adopted in LTE‐R system, the finite state set of the MSM is designed. For different MFLSs, the frame error rate (FER) and signal‐to‐noise ratio (SNR) curve is obtained. By giving a target FER, the SNR thresholds corresponding to different MFLSs are achieved. From the perspectives of modulation priority and frame length priority, two different AMFL‐MSMs are designed to change MFLSs dynamically. Simulation results show that the proposed two AMFL‐MSMs have more stable goodput than the common modulation schemes and less symbol energy consumption than the high‐order modulation scheme. In addition, the AMFL‐MSM with modulation priority has better performance than the AMFL‐MSM with frame length priority in terms of goodput stability.
Multiple‐access ultrawideband communications using frequency modulation of quasi‐orthogonal impulse‐like waveforms
Authors: Shishter Yousef M.H. , Hussain Malek G.M.
Published: February 2020

This paper presents a detailed study of multiple access ultrawideband communications based on M‐ary frequency‐shift keying modulation of impulse‐like carrier waveforms. The proposed signal model is described using expressions of duty cycle, energy, and correlation coefficient analytically derived and analyzed in terms of signal parameters. The frequency sets for coherent as well as non coherent detection utilized in narrow band communications are extended to impulse communications, and the resultant signals' correlation properties are investigated. Analytic expression of the frequency spectrum for continuous transmission is obtained, and a parametric study of the spectrum is carried out to analyze its properties. System performance analysis in terms of error probability curves is given for different signal model parameters. For single user communications, error probability curves for M‐ary system are plotted using the union bound, while for multiple access communications, analytic expression of binary error probability in Rayleigh fading channel is given and plotted. The plots demonstrate the advantages of multiple access coding and signal design in improving system performance. Comparison between the bit error performance of impulse frequency shift keying, impulse phase shift keying, pulse position, and binary phase shift keying modulation schemes is presented too.
Incorporation of prior knowledge into sparse time dispersive OFDM channel estimation via weighted atomic norm minimisation
Authors: Hezaveh Hoomaan , Valiulahi Iman , Kahaei Mohammad Hossein
Published: February 2020

A new estimator for sparse time dispersive channels in pilot aided orthogonal frequency division multiplexing (OFDM) systems is developed by considering prior knowledge on channel time dispersions. The authors propose a weighted atomic norm minimisation (WANM) in order to incorporate the prior information into the estimator. The dual of the WANM is then converted to a tractable semidefinite programming using positive trigonometric polynomial theory. After solving the dual problem, the channel response is identified by solving a least squares approach. In this work, they assume that time dispersions associated delays can take any value with a mild minimum separation condition on the normalised interval . The performance of the new estimator is compared with conventional approaches. With respect to the pilot number and signal to noise ratio (SNR), simulation results reveal that the proposed estimator performs superior to that of traditional methods. It is shown that both a lower SNR and number of pilots are required to achieve the same mean square error reported in previous works.
Low complexity receiver of sparse code multiple access based on dynamic trellis
Authors: Peng Xiaohuan , Pan Zhipeng , Lai Ke , Wen Lei , Lei Jing
Published: February 2020

Sparse code multiple access (SCMA) is one of the non‐orthogonal multiple access schemes to meet the demands of massive connection and high spectral efficiency in the 5G communications. Since the sparsity of the codebook, the message passing algorithm (MPA) can be utilised for multi‐user detection. However, the high computational complexity of MPA hinders the practical application of SCMA. The extended Max‐Log MPA (EML‐MPA) and the channel‐adaptive extended Max‐Log MPA (CAD‐EML‐MPA) help to reduce the complexity of conventional Log‐MPA with trellis representation. On this basis, the authors propose a dynamic trellis based MPA (DT‐MPA) in this study. DT‐MPA selects symbols dynamically according to a specific threshold in each iteration of MPA. The impact of the threshold on the complexity and convergence behaviour is analysed. Simulation results show that the DT‐MPA with variable which is related to bit signal‐to‐noise can achieve better bit error rate performance and lower complexity than EML‐MPA and CAD‐EML‐MPA.
Discrete Fourier transform‐based block transmission for multi‐carrier faster‐than‐Nyquist signalling
Authors: Peng Yaqiu , Bian Xin , Li Mingqi
Published: February 2020

Multi‐carrier faster‐than‐Nyquist (MC‐FTN) signalling, which is a non‐orthogonal data transmission scheme, is broadly viewed as one of the potential candidates for the future high spectral‐efficient communications. In this study, a discrete time‐frequency packing scheme based on the discrete Fourier transform (DFT) block transmission for MC‐FTN signalling (DBT‐MC‐FTN) is proposed. Firstly, by transforming the blockwise MC‐FTN signalling into the frequency domain, an efficient implementation transceiver structure incorporating a bank of DFTs, circular expanding operation, and cyclic shift summation operation is obtained. Thus, flexible packing in both time and frequency domains can be achieved efficiently within a DBT‐MC‐FTN block. Secondly, to deal with the inter‐symbol interference (ISI) introduced by time packing and inter‐carrier interference (ICI) introduced by frequency packing in the proposed DBT‐MC‐FTN scheme, a subcarrier‐level equalisation combined with a soft interference cancellation scheme operated in the frequency domain is further proposed to detect the DBT‐MC‐FTN signals at the receiver. Simulation results show that the proposed DBT‐MC‐FTN scheme performs close to the corresponding orthogonal system with negligible bit error rate performance loss in the case of moderate ISI and ICI. Additionally, the post‐processing signal‐to‐interference‐plus‐noise ratio of the proposed scheme is also given in detail.
Performance evaluation and security analysis of ground‐to‐satellite FSO system with CV‐QKD protocol
Authors: Alshaer Nancy , Ismail Tawfik , Nasr Mohamed E.
Published: February 2020

This study evaluates the performance of a secure ground‐to‐satellite free‐space optical (FSO) system using a bipolar pulse amplitude modulation over modulated gamma fading channel. A closed‐form expression is derived for the joint probability of a satellite‐based continuous‐variable quantum key distribution (CV‐QKD) protocol that uses dual‐threshold detection. Furthermore, to study the system behaviour, closed‐form expressions for quantum bit‐error‐rate (QBER) and quantum bit‐discard rate (QBDR) are given. The accuracy of the proposed derivations is validated using Monte‐Carlo simulations and numerical analysis. The dual‐threshold range is optimised to satisfy design criteria in terms of QBER and QBDR. Finally, a sufficient selection of transmitter and receiver parameters ensures a guarantee of system security. Additionally, the information capacity is maximised by a scaling coefficient of .
Secure full duplex OFDM wireless communication based on phase relay between the legitimate nodes
Authors: Guo Yong , Zhang Lijie
Published: February 2020

This study proposes a scheme to realise secure orthogonal frequency‐division multiplexing (OFDM) wireless communication between two full duplex nodes—node A and node B. If node A wants to send secret messages to node B, node A and node B transmit the training signal to each other to acquire channel state information (CSI) in the first time frame. Node A acquires the phases of the received signal from node B (no need to decode). In the second time frame, node A then sends secret messages to node B with the phases of the modulated signal being added to the random phases of the signal from node B in the previous time frame, i.e node A relaying the phases of the signal from node B. Node B can recover the secret messages from node A, but eavesdroppers cannot because they do not know the CSI of the main channel. The secrecy capacity is irrelevant to the CSI of the eavesdropper channel, which is a big advantage over other schemes. The scheme can guarantee secrecy capacity to be positive in all circumstances and work well for single‐input single‐output systems. A computation efficient algorithm is presented to optimally allocate power over sub‐carriers for secrecy capacity maximisation.
Adaptive mesh size (AMS) algorithm for energy efficiency maximisation in underlay D2D communication
Authors: Saad Waleed , Refky Hajar , Shokair Mona
Published: February 2020

The need to maximise energy efficiency (EE) for device‐to‐device (D2D) communication has become an urgent necessity for the fifth‐generation wireless networks. In this study, the power allocation problem is considered for the cellular system underlaid with D2D users (DUs) to maximise the EE for the whole network. Firstly, the random distribution of DUs and cellular users (CUs) are described by utilising the homogeneous Poisson point process based on stochastic geometry. Secondly, successful transmission probabilities are deduced. Finally, the optimisation problem for maximising EE is formulated to determine the optimal power values for both D2D and CUs. An adaptive mesh size algorithm is suggested to solve the non‐convexity of the EE optimisation problem. Simulation results prove that the suggested technique has the ability to accomplish the near‐optimal EE. Furthermore, it has superior performance when compared with the related algorithms.
Regularising neural networks for future trajectory prediction via inverse reinforcement learning framework
Authors: Choi Dooseop , Min Kyoungwook , Choi Jeongdan
Published: February 2020

Predicting distant future trajectories of agents in a dynamic scene is challenging because the future trajectory of an agent is affected not only by their past trajectory but also the scene contexts. To tackle this problem, the authors propose a model based on recurrent neural networks, and a novel method for training this model. The proposed model is based on an encoder–decoder architecture where the encoder encodes inputs (past trajectory and scene context information), while the decoder produces a future trajectory from the context vector given by the encoder. To make the proposed model better utilise the scene context information, the authors let the encoder predict the positions in the past trajectory and a reward function evaluate the positions along with the scene context information generated by the positions. The reward function, which is simultaneously trained with the proposed model, plays the role of a regulariser for the model during the simultaneous training. The authors evaluate the proposed model on several public benchmark datasets. The experimental results show that the prediction performance of the proposed model is greatly improved by the proposed regularisation method, which outperforms the‐state‐of‐the‐art models in terms of accuracy.
Flexibility provision through enhanced synergies between electricity, gas and heat systems: a comparative analysis of market and regulatory frameworks in seven case study countries
Authors: Cauret Lionel , Belhomme Regine , Raux‐Defossez Pauline , Nösperger Stanislas , Steinbeisser Johannes , Pagán Carpe Juana
Published: February 2020

With the increased share of renewable energy sources, there is a growing need for more flexibility to ensure the efficient and reliable operation of the electricity system. Multi‐energy systems (MES) now appear as one possible means to provide such flexibility through increased synergies between electricity, gas, and heating/cooling systems. In this context, the main findings of the study carried out in the MAGNITUDE European project are described. The most relevant services that could be provided by MES to the electricity system are first presented. Then a methodology is proposed to characterise and compare the market organisations and mechanisms for their procurement. The results of its application in seven case study countries are summarised and illustrate the diversity met between countries. The gas and heat sectors are also investigated for the seven countries to characterise the main aspects relevant to the provision of the services by MES. A comparative analysis is then carried out between the three energy sectors in the seven countries and highlights the major similarities and differences. Finally, potential barriers for the provision of the services by MES are discussed regarding the market, regulatory, and cultural aspects.
Transient stability evaluation model based on SSDAE with imbalanced correction
Authors: Wang Huaiyuan , Ye Weitao
Published: February 2020

With the rapid development of machine learning technology, a new tool is provided for real‐time stability evaluation in power systems. The training of a machine learning‐based model is inseparable from a large number of training samples. However, compared with stable samples, unstable samples in power systems are infrequent. The results of the model evaluation are biased due to the imbalance of training samples. Faced with such a problem, a framework based on deep imbalanced learning is proposed. Firstly, for each sample, the samples nearby in the opposite class are applied to calculate its space information. Based on the space information of all samples, the spatial distribution characteristics of the training samples are obtained. And then, in order to obtain balanced training samples, unstable samples are generated according to their spatial distribution characteristics. Finally, stacked sparse denoising auto‐encoder (SSDAE) based model, which has the ability of anti‐noise, is established as the classifier. Simulation results in IEEE 39‐bus system show the high performance of the proposed imbalanced correction scheme and evaluation scheme.
Chua's diode and strange attractor: a three‐layer hardware–software co‐design for medical image confidentiality
Authors: Rajagopalan Sundararaman , Poori Siva , Narasimhan Mukund , Rethinam Sivaraman , Vallipalayam Kuppusamy Chandrasekar , Balasubramanian Ramalingam , Moorthi Paramasivam Annamalai Vijaya , Rengarajan Amirtharajan
Published: February 2020

Medical image security relies upon the arrival of improved techniques for enhancing the confusion as well as diffusion processes in the pixel level manipulations. Non‐linear circuits constructed with hardware components can be employed for hardware–software co‐design in medical image encryption. The proposed approach has adopted Chua diode circuit for the generation of 256 × 256 random synthetic image with the entropy of 7.9972. This synthetic image has been utilised to scramble the DICOM image for the second level of diffusion as the cellular automata provides the first level of scrambling and diffusion. The average correlation coefficients of encrypted pixels are 0.00204, −0.00298 and −0.00054 in three directions. The encrypted pixels pass the NIST SP 800‐22 test suite and offer resistance to statistical, differential and chosen plain text attacks.
Medical image segmentation using deep learning with feature enhancement
Authors: Huang Shaoqiong , Huang Mengxing , Zhang Yu , Chen Jing , Bhatti Uzair
Published: February 2020

Pre‐segmentation is known as a crucial step in medical image analysis. Many approaches have been proposed to make improvement to both the quality and efficiency of segmentation. However, existing methods are lacking in robustness to the variation in the edges and textures of the target. In order to address these drawbacks, a novel attention Gabor network (AGnet) based on deep learning for medical image segmentation that is capable of automatically paying more attention to the edge and consistently for improvement to the segmentation performance is proposed. The proposed model consists of two components. The first one is to determine the approximate location of the organs of interest in the image using convolution filters, and the other one is to highlight salient edge features intended for a specific segmentation task using Gabor filters. In order to facilitate collaboration in between the two parts, a region attention mechanism based on Gabor maps is suggested. The mechanism improved performance by learning to focus on the salient regions of the image that are useful for the authors' tasks. As indicated by the experimental results, the AGnet is capable of enhancing the prediction performance while maintaining the computational efficiency, which makes it comparable with other state‐of‐the‐art approaches.
Dynamic image reconstruction and synthesis framework using deep learning algorithm
Authors: Jeyaraj Pandia Rajan , Samuel Nadar Edward Rajan
Published: February 2020

This research study shows an effective deformable complex 3D image reconstruction and image synthesis technique by consolidating needed high‐level features from a deep convolutional neural network (CNN) system. By recognising the inherent deep features in image patches lead to information discovery in medicinal imaging. Utilising the ADNI and LONI imaging datasets, the performance of the proposed deep learning algorithm image reconstruction and synthesis performance was verified. For validation, various performance indices obtained with the proposed deep learning algorithm were compared with two conventional algorithms namely support vector machine and CNN. Likewise, to reveal the adaptability of the proposed image reconstruction and synthesis system, synthesis and reconstruction experiments were directed on the 7 T cerebrum magnetic resonance image. As presented in the study outcomes, the proposed method can accomplish predominant performance compared with other cutting‐edge techniques with either low‐ or high‐level features in terms of the synthesis and reconstruction rate. The proposed algorithm has a training time of 5 s with a structural similarity index of 0.97. In all investigations, the outcome shows that the proposed image reconstruction framework reliably exhibited progressively precise outcomes when contrasted with best in class. Hence, it can be used for possible precise image reconstruction and synthesis related applications.
Image multi‐encryption architecture based on hybrid keystream sequence interspersed with Haar discrete wavelet transform
Authors: Umoh Edwin A. , Iloanusi Ogechukwu N. , Nnolim Uche A.
Published: February 2020

A novel image multi‐encryption architecture based on hybrid keystream sequence generated by a single hyperchaotic system and Haar discrete wavelet transform (HDWT) is proposed. The architecture consists of a pre‐cipher stage, first encryption operation, Haar discrete wavelet decomposition stage and a second encryption operation. In the pre‐cipher stage, the algorithm applies two‐level pixel position permutation of the image. The first encryption operation is accomplished by diffusing the pixel's numbers with keystream sequence generated by a sequence generator SG‐1. The resulting cipher image is decomposed using two‐dimensional HDWT decomposition technique. The decomposed image is further encrypted through operation between keystream sequence generated by sequence generator SG‐2 and bytes of the decomposed image which are selected with the aid of a novel pseudo – 4 bit Boolean truth table‐based byte selection mechanism. SG‐1 and SG‐2 are special cases of the hyperchaotic system and are evolved online by separately nullifying selected parameters of the hyperchaotic system. The novelty of the proposed architecture lies in the possibility of increasing the number of sequence generators, which can result in exponentially huge key space and fast encryption speed. A comprehensive complexity analysis of performance, security and robustness to attacks, confirmed the feasibility of the architecture.
Tablet identification using support vector machine based text recognition and error correction by enhanced n‐grams algorithm
Authors: Dhivya A.B. , Sundaresan M.
Published: February 2020

Unidentified and/or misidentified tablets always present challenges to both patients and health care professionals alike. Consumption of these misidentified tablets often results in adverse drug reaction and sometimes may even cause ill health leading to death. Thus, identification of unknown tablets is an important task in the medical industry. This study proposes an algorithm that uses the text imprinted on the tablet images to identify unknown images. Text imprinted on pills often contains important information that can be used to identify tablets. In this study, multiple feature sets were extracted from tablet images. The proposed work first identifies the text region, from which the text is recognised using support vector machine classifier. A post processing algorithm based on the confusion model combined with n‐grams is used to correct the substitution, insertion and deletion errors in the text recognised. Finally, the corrected text is matched with a template tablet database to identify similar tablets. Experimental results showed that the proposed system is efficient with respect to accuracy and can be safely used by both common public and health care professionals to identify tablets.
Computational approach to body mass index estimation from dressed people in 3D space
Authors: Jiang Min , Shang Yuanyuan , Guo Guodong
Published: February 2020

Body mass index (BMI) defines as a person's weight divided by the square of height (BMI ), which is an important indicator of the health condition. The authors study BMI estimation from the three‐dimensional (3D) visual data by measuring the correlation between the estimated body volume and BMIs, and then develop an efficient BMI computation method. Their approach consists of body weight and height estimation from normally dressed people in 3D space. To address the influence of loose clothes on body volume estimation, two clothes models are developed to make the volume estimation more accurate. A new RGB‐D video dataset is collected for this study, and the reconstructed 3D data are provided by the KinectFusion on depth data. Experimental results show the effectiveness of the approach to work on normal conditions of dressed people. The mean absolute error of the estimated BMI can achieve 2.54 in their experiments.
Non‐linear calibration optimisation based on the Levenberg–Marquardt algorithm
Authors: Hu Guoliang , Zhou Zuofeng , Cao Jianzhong , Huang Huimin
Published: February 2020

An outstanding calibration algorithm is the most important factor that affects the precision of attitude measurement. This study proposes a non‐linear optimisation algorithm to refine the solutions of the initial guess obtained using the Zhang's technique, the Bouget's technique, or the Hartley's algorithm. Large sets of point correspondences were adopted to test the validity of the proposed method. Extensive practical experiments demonstrated that the proposed method can significantly improve the accuracy of calibration and ultimately obtains higher measurement precision. The error of the reprojection in the proposed method was <0.13 px. At a range of 1 m, the error rate was 0.5% for the length test and about 3% for the angle test. This study proposes a new method to calibrate the relationship between laser radar and the camera. Binocular vision was used to reconstruct the point cloud of the non‐cooperative target. At the same time, data was also obtained using laser radar. Finally, the two groups of systems were fused. Accurate and dense three‐dimensional information of the target was obtained. It could not only obtain the dense pose information of the target surface but also the texture and colour feature information of the target surface.
Improved water quality mapping based on cross‐fusion of Sentinel‐2 and Landsat‐8 imageries
Authors: Rangzan Kazem , Kabolizadeh Mostafa , Karimi Danya
Published: February 2020

This study proposed methods based on Sentinel‐2 and Landsat‐8 cross‐fusion for improving water quality mapping (WQM). Therefore, four traditional fusion methods including intensity–hue–saturation, Gram–Schmidt transform, wavelet transform and Brovey transform and different scenarios of cross‐fusion have been implemented. The proposed cross‐fusion methods highly improved the correlation coefficient (CR) between the images and the water quality parameter (WQP). Considering the higher CR values, the created WQP maps showed very good accuracy, in which the root‐mean‐square error values were 0.03, 0.59, 0.96, 0.26 and 279.76 for potential hydrogen (PH), dissolved oxygen (DO), chemical oxygen demand (COD), biological oxygen demand (BOD) and electrical conductivity (EC) maps, respectively. Also, the effect of considering 1 px value or the mean of a 3×3 window of the input images for calculating the regression models on the accuracy of the final maps was tested. Only the best outputs for mapping PH and DO parameters were based on applying the mean of a 3×3 window. The results also showed that increasing the window size could increase the computational complexity and decrease the WQM accuracy. Comparing the output maps with the traditional maps confirmed the higher accuracy of the proposed methods.
Efficient image noise estimation based on skewness invariance and adaptive noise injection
Authors: Ma Ben , Yao Jincao , Le Yanfen , Qin Chuan , Yao Heng
Published: February 2020

The precise estimation of the noise level is a crucial issue in image processing. In this study, the authors propose a new method for noise standard deviation (STD) estimation from natural images based on skewness‐scale invariance in the transform domain and an adaptive noise injection strategy. The method is divided into two steps. The first step assumes that the natural clean image has the property of constancy of skewness in the transform domain. Then, a preliminary noise estimation method based on skewness invariance is designed by solving a constrained non‐linear optimisation problem. The second step involves noise rectification via noise injection. According to the phenomenon that compared with the high‐noise circumstance, the error of preliminary estimation is more serious under a low amount of noise, the noise STD is re‐estimated by injecting another noise for which the STD is known. In addition, the threshold model with respect to image complexity is established to identify whether a second estimation is needed. The experimental results demonstrate the efficacy of the proposed method and performance is superior to other state‐of‐the‐art methods.
Compact coupled resonators for small size dual‐frequency wireless power transfer (DF‐WPT) systems
Authors: Atallah Hany A. , Hussein Rasha , Abdel‐Rahman Adel B.
Published: February 2020

This work introduces a novel design for high efficiency and compact size dual‐frequency wireless power transfer (DF‐WPT) systems. The proposed design is composed of two identical transmitting (Tx) and receiving (Rx) substrates. Each substrate has a microstrip feed line, a C‐shaped coupled resonator on the top layer and a spiral coupled defected ground structure on the bottom layer. The system is analysed using J‐inverters for the dual‐frequencies (DFs) operation. The measured results show that the proposed DF‐WPT system with a compact size of 20 × 20 mm2 is able to provide a stable WPT characteristic with total efficiencies of 91.2 and 79.4% at 0.28 and 0.49 GHz, respectively with a transmission distance of 6 mm. The proposed system achieved good agreements between the analytical design procedure, the circuit model, the electromagnetic simulations, and the measurements.
Measurement‐based geometrical characterisation of the vehicle‐to‐vulnerable‐road‐user communication channel
Authors: Rashdan Ibrahim , de Ponte Müller Fabian , Sand Stephan , Jost Thomas , Caire Giuseppe
Published: February 2020

Vehicle‐to‐vulnerable‐road‐user (V2VRU) communications have the ability to provide of awareness to both vehicles and vulnerable road users to prevent accidents. An accurate V2VRU channel model in critical accident scenarios is essential to develop a reliable communications system. Therefore, extensive wideband single‐input and single‐output channel measurement campaigns at 5.2 GHz were carried out in open‐field and urban environments. Accident prone scenarios between a vehicle and a cyclist as well as between a vehicle and a pedestrian are considered. In this study, locations of the scatterers in the propagation environment are estimated. The authors propose a method to extract specular multipath components (MPCs) from the estimated time‐variant channel impulse response based on the density of neighbouring MPCs. The specular MPCs are then tracked using a novel tracking algorithm based on the multipath component distance approach. Each path is then related to a physical scatterer in the propagation environment by employing a joint delay‐Doppler estimation. According to the results, single and double bounce reflections from buildings and parked vehicles are identified in line‐of‐sight (LoS) situation. In non‐LoS(NLoS) situation, scattering from nearby trees as well as reflections from traffic signs and lampposts beneath the trees canopy are identified.
Optimal phase‐shift control of three‐level dual‐active bridge DC–DC converter with minimum reflux power for wide voltage conversion ratio range application
Authors: Jin Li , Chen Chen
Published: February 2020

Three‐level dual‐active bridge (3L‐DAB) DC–DC converter under conventional phase‐shift (CPS) control would produce large reflux power and current stress, especially when the voltage conversion ratio is varied in a wider range, which will lead to high power loss and low system efficiency. An optimised phase‐shift (OPS) control strategy is proposed to control the 3L‐DAB operating at the point with minimum reflux power. The power characteristics of 3L‐DAB under CPS control are analysed. Then the mathematical model of the reflux power is established, and the relationship equations among the reflux power, phase‐shift (PS) ratios, and voltage conversion ratio are deduced. The minimum reflux power and optimal PS ratio are calculated by using the segmentation optimisation algorithm in different ranges of transmission power and voltage conversion ratio. Performance comparative analysis between CPS and OPS controls is carried out later. Adopting the proposed OPS control strategy, the reflux power of 3L‐DAB is minimised, as well as reducing the current stress and increasing the efficiency in a wide voltage conversion ratio range. An experimental prototype was developed to verify the effectiveness of the OPS control strategy and the correctness of the theoretical analysis.