bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dynamic optimized cooperation in multi‐source multi‐relay wireless networks with random linear network coding
Authors: Benamira E. , Merazka F. , Kurt G. K. 
Published: January 2021

AbstractThe authors present a strategy that improves the reliability of data transmission from multiple sources towards a destination D via multiple relays over wireless channels. After the broadcast phase, the destination selects the best cooperative direct link sources with the highest instantaneous signal‐to‐noise ratio , then generates and sends the random linear network coding coefficient matrix to the relays. After receiving the random linear network coding–coded symbols (packets) from the relays, D completes the reception and decoding of all source nodes packets. Monte Carlo simulations are conducted with Galois field (GF) () symbols ( = 2, 4 and 8) and the results are compared with the scenario of static cooperative direct links. An important decrease of symbol error rate (SER) is achieved. Furthermore, the efficiency of this approach is confirmed for the whole range of possible values of path loss exponent on direct links, that is, all types of environment between source nodes and destination D.
Critical frequency of metasurfaces on dielectric half‐space
Authors: Liu Xiaobo , Chen Xiaoming , Zhang Anxue , Kishk Ahmed A. 
Published: January 2021

AbstractIn this letter, the critical frequency of the periodic metasurface in a dielectric half‐space is studied. First, according to the mode expansion theory, the wave of the periodic metallic elements can be decomposed into different eigen‐modes. Then, as the frequency increases, partial high‐order modes are excited by the periodic metallic elements that may propagate into the substrates as spics. Finally, the critical frequency is analytically derived for a homogenized surface without spics. This study shows that the reflected and transmitted spics can co‐exist, but there is a distinct difference between their corresponding critical frequencies. Thus, the actual critical frequency of homogenized metasurface in a dielectric half‐space is not only related to the periodicity and incident angle, but also to the substrates.
Electrocardiogram estimation using Lagrange interpolation
Authors: Yadav Om Prakash , Sahu Anil Kumar 
Published: January 2021

AbstractAn electrocardiogram records activity of cardiac which is collected through the electrodes positioned on specific locations on the human body. These signals are required for cardiac‐related issues. Electrocardiogram signals are quasi‐stable signals and are often contaminated by artefacts. The magnitude and frequency of these artefacts are different, and thus their effect on electrocardiogram is also variable. These artefacts must reduce to a significantly optimum level to make them interpretable. This paper proposes an algorithm to estimate electrocardiogram signals from the MIT‐BIH database signal using Lagrange interpolation through Chebyshev nodes. The performance evaluation of the proposed method has been assessed through standard estimation tools. Performance parameters revealed that the algorithm is suitable for signal estimation irrespective of the characteristic of artefact introduced to the signal.
Efficient and robust bitstream processing in binarised neural networks
Authors: Aygun Sercan , Gunes Ece Olcay , De Vleeschouwer Christophe 
Published: January 2021

AbstractIn the neural network context, used in a variety of applications, binarised networks, which describe both weights and activations as single‐bit binary values, provide computationally attractive solutions. A lightweight binarised neural network system can be constructed using only logic gates and counters together with a two‐valued activation function unit. However, binarised neural networks represent the weights and the neuron outputs with only one bit, making them sensitive to bit‐flipping errors. Binarised weights and neurons are manipulated by the utilisation of bitstream processing with regard to stochastic computing to cope with this error sensitivity. Stochastic computing is shown to provide robustness for bit errors on data while being built on a hardware structure, whose implementation is simplified by a novel subtraction‐free implementation of the neuron activation.
Millimetre‐wave high–low IMPATT source development: First on‐chip experimental verification
Authors: Mukherjee Moumita , Chatterjee Sulagna 
Published: January 2021

AbstractThis paper reports design and development of high–low type Si/SiC‐based Impact Ionisation Avalanche Transit Time device and its on‐chip characterisation. The design has been performed with indigenously developed strain engineered non‐linear self‐consistent large‐signal simulator. On‐chip hetero‐structure SiC Impact Ionisation Avalanche Transit Time at 94 GHz has been successfully fabricated and on‐chip DC testing (forward and reverse) results are reported for the first time. The device breaks down at 185 V (simulated result: 188 V) and breakdown current is ∼12.5 mA. If the diode chip is mounted properly with W‐band waveguide, it is expected to generate ∼2 W of Radio Frequency (RF) power at W‐band window frequency (∼94 GHz). The experimental verification of newly developed in‐house strain‐corrected mixed quantum tunnelling drift diffusion simulator is done successfully.
Deep learning‐based massive multiple‐input multiple‐output channel state information feedback with data normalisation using clipping
Authors: Jo Sanguk , Lee Jaehee , So Jaewoo 
Published: January 2021

AbstractMassive multiple‐input multiple‐output (MIMO) can provide real‐time high‐capacity data transmission service to the user equipment (UE). However, the use of massive MIMO exponentially increases the channel state information (CSI) feedback overhead. Deep learning‐based approaches have been proposed to reduce CSI feedback overhead with significant CSI accuracy. Data normalisation is a very important part of deep learning, because the performance of the deep learning highly depends on the data normalisation. In this letter, an efficient data normalisation method for deep learning‐based CSI feedback in a massive MIMO system is proposed, where the proposed method uses a clipping technique based on the received signal strength. Simulation results show that the proposed normalisation with the clipping decreases the CSI feedback error and increases the accuracy of the beamforming vector in deep learning‐based CSI feedback.
Ultra‐wideband and large‐range incident angles radar cross‐section reduction by quasi‐fractal polarisation conversion metasurfaces
Authors: Shakouri Amir Hossein , Ameri Edris , Sedighy Seyed Hassan 
Published: January 2021

AbstractThis study proposes a quasi‐fractal polarisation conversion metasurface (PCM) for ultra‐wideband radar cross‐section reduction (RCSR). The simple and proposed metasurface is composed of double‐heads arrowed‐like unit cell benefited from the second iteration Koch fractal in its arm and cut‐line to broaden the bandwidth. Consequently, this PCM unit cell and its 90, 180 and 270 degrees rotated counterparts obtain destructive interference cancellation between their reflected waves and RCSR. The proposed metasurface demonstrates 10‐dB RCSR from 7.68 to 40.87 GHz (136.73%) for normal incident waves, and more than 96.7% up to 40 degrees incident angle that verifies the large range incident angle RCSR of the surface. The experimental measurement results at the normal incident angle and their comparison with simulation ones prove the idea.
Towards fully domain‐independent gesture recognition using COTS WiFi device
Authors: Yin Yuqing , Zhang Zixin , Yang Xu , Yan Faren , Niu Qiang 
Published: January 2021

AbstractThis letter proposes a fully domain‐independent WiFi‐based gesture recognition system based on the multi‐label adversarial network. Unlike pioneer machine learning works, our system does not require retraining in the target domain, which benefits from our key idea of eliminating fully domain information such as orientations, locations, environment information. The system proposed by us includes three parts: Feature extractor, domain discriminator, and gesture recogniser. The feature extractor attempts to deceive the domain discriminator based on the adversarial network structure so that it is difficult to judge the input domain label, thereby obtaining domain‐independent features and realising fully domain‐independent gesture recognition. Extensive experiments are conducted on the Widar 3.0 dataset and our dataset to evaluate system performance. The results show that our system can achieve an in‐domain recognition accuracy of 93.2% and a cross‐domain recognition accuracy of 87.1%, which is superior to other state‐of‐the‐art works.
Performance analysis of a novel outer rotor flux‐switching permanent magnet machine as motor/generator for vehicular and aircraft applications
Authors: Sharouni Sahar , Naderi Peyman , Hedayati Mahdi , Hajihosseini Payman 
Published: January 2021

AbstractHerein, a novel study on outer rotor flux‐switching permanent magnet (OR‐FSPM) machines for motor/generator applications is presented. An improved magnetic equivalent circuit (MEC) is used for saturable machine model, and the performance analysis is presented in both dynamic and steady‐state cases. A flexible MEC‐based method is used, where the machines with arbitrary properties can be analysed. Moreover, the model accuracy can be tuned by selective parameters in the proposed method. It is shown that the machine can be used as a high efficiency 400 Hz Ground Power Unit (GPU) for aircraft application. Furthermore, the machine usage for in‐wheel application in the hybrid and electric vehicles (HVs and EVs) is analysed. Comparison with 2D and 3D finite‐element‐method (FEM) shows the effectiveness and accuracy of the proposed MEC method, where shorter processing time is obtained compared with FEM.
Modelling of magnetostrictive vibration and acoustics in converter transformer
Authors: Yadav Suman , Mehta Ram Krishna 
Published: January 2021

AbstractThe converter transformers are susceptible to more noise and vibration when compared to power transformers due to the presence of DC bias in the DC transmission line. DC bias occurs mostly due to inaccuracies in valve firing resulting in a small residual DC oscillating around zero. Measurement of magnetostriction becomes significant as it influences the vibration and noise from the core. Hence, a magnetostrictive model of a high‐voltage DC converter transformer has been developed. This work analyses the vibration and noise acoustics under such an occurrence. First, the core of the transformer model is designed in the stepped configuration for 240 MVA; then, magnetostrictive vibration is analysed by using suitable modules of COMSOL Multiphysics at different magnitudes of DC bias. The physics of noise has been interfaced using the Acoustics Module, and the results are recorded. Finally, artificial neural network model is developed for the prediction of vibration and noise characteristics of the model. The fitting process of neural network was then remodelled using various optimisation techniques, namely teaching–learning‐based optimisation, particle swarm optimisation, biogeography‐based optimisation, simulated annealing and binary coded genetic algorithm, and their results were compared to obtain the best‐suited method using % mean‐squared‐error evaluation.
Utilising LiDAR for fall detection
Authors: Frøvik Nikolai , Malekzai Bashir A. , Øvsthus Knut 
Published: January 2021

AbstractAutonomous driving generates several low‐cost technologies, such as light detection and ranging (LiDAR). Due to this, the LiDAR technology has experienced impressive performance improvements. Our ambition is to capitalise on this development, where LiDAR is considered as the enabling technology for a non‐invasive monitoring system for securing elder persons in their home. A motivation for technology‐based securing of elder persons is that many countries experience a demographic change. Traditional personal care by care worker or re‐location to special homes of elder persons does not scale due to the shrinking fraction of the working population. Technology can reduce some of the burden. This article proposes and assesses technology for securing a person's home. However, securing a person, based on monitoring, requires careful design because the technology should be non‐invasive, reliable and low cost. LiDAR technology offers several crucial qualities that meet these system requirements. This article provides a proof of concept for a low‐cost, non‐invasive LiDAR‐based monitoring system. Our proposed system can detect if a person has fallen, and it can trigger an alarm to the care services when required. We emphasise especially that our monitoring solution can operate in the bathroom and even in the shower.
Robustness evaluation of an inkjet‐printed epidermal ultra‐high‐frequency radio frequency identification tag
Authors: Oyeka Dumtoochukwu Obiora , Batchelor John C. 
Published: January 2021

AbstractThis paper examines the impact of daily activities on the performance of a body‐mounted radio frequency identification (RFID) tag inkjet printed onto tattoo transfer paper. This paper aims to assess how robust RFID tags of this nature are when mounted on the skin while the user undergoes various daily activities. The factors considered for these robustness tests are the effect of sweat and wear and tear on these tags during everyday use and also how it stands up to being exposed to water and soap during showering. Performance assessment was carried out using parameters such as point‐to‐point surface DC resistance as well as read range. Results show marginal effects on the tag performance and the tag continued to function during a normal day's activities, which lasted for 8 h, and rigorous activities like exercising but stopped functioning when there was severe damage to tag.
A mild route for the preparation of calcium carbonate rod bundles in large scale from carbide slag
Authors: Yang Baojun , Shao Zongqi , Zhang Dongxue , Wang Bainian 
Published: January 2021

AbstractIn this article, a powerful method to synthesize uniform CaCO3 rod bundles with a high mass fraction of aragonite from carbide slag in large‐scale production via a two‐step leaching‐precipitation process is reported. The effects of the addition of ethylene glycol and reaction temperature on the structure and morphology of the prepared CaCO3 samples were investigated and then demonstrated by the experimental results. It is beneficial to increase the mass fraction of aragonite in CaCO3 samples and ensure the formation of regular rod bundles in morphology when the addition of ethylene glycol is 30 mL and the reaction temperature is 80 °C. The formation mechanism of the CaCO3 rod bundles was preliminarily discussed according to the Muffins–Sekerka theory.
Concurrent photocatalytic degradation and filtration with bi‐plasmonic TiO2 for wastewater treatment
Authors: Anvari Abbas , Amoli‐Diva Mitra , Sadighi‐Bonabi Rasoul 
Published: January 2021

AbstractA new photocatalytic filtration membrane was prepared by grafting of Ag–Au bi‐plasmonic shell‐on TiO2@Fe3O4 nanoparticles as a magnetically‐separable heterogeneous photocatalyst to a poly acrylic acid‐modified cellulose acetate membrane for decomposition and removal of methyl orange as a model pollutant from textile wastewater samples. Eight photocatalysts including five Au NPs‐modified TiO2@Fe3O4 NPs and three Ag‐Au bi‐plasmonic NPs‐decorated TiO2@Fe3O4 NPs with different shell thickness were synthesized and characterized by TEM, UV–vis, and SEM techniques and their photocatalytic activity was assessed using two radiation sources. After selection of optimum photocatalyst and modification of cellulose acetate membrane, the photodegradation of methyl orange was evaluated in a dead‐end membrane reactor using the prepared membrane. The flux performance, antifouling property and pollutant removal efficiency of the membrane were evaluated using textile wastewater samples. It was demonstrated that the prepared membrane reactor is able to produce cleaner water with more stable flux performance and good antifouling property.
Nanomechanical characterisation of single‐crystal Bi2Se3 topological insulator
Authors: Uzun Utku , Yetmez Mehmet , Akıncı Nurgül 
Published: January 2021

AbstractTopological insulators (TIs) are recently discovered high‐tech materials where their potential use in nanoelectronic devices such as spintronics and quantum computers, due to their unique electronic features, can be a solution to the emerging need for high‐bit data processing. Yet their mechanical properties are not well understood for their use in practical applications. With the objective of exploiting the nanomechanical behaviour of TIs, bulk single‐crystal Bi2Se3 TI is grown by using the Bridgeman–Stockbarger method and mechanically characterised by the nanoindentation method. The Young's modulus and hardness were extracted from the load‐displacement data by using Oliver and Pharr's standard method. Further, fracture toughness of the material was reported for the first time after comprehensive research of indentation crack length (ICL) methods. The grown Bi2Se3 exhibits hardness and Young's modulus as 323 MPa and 6.018 GPa at nanoscale, respectively. Fracture toughness of the TI was evaluated at 0.034 MPa m1/2 and elastic recovery was around 60% after the full unloading process.
A molecular dynamics study of the effect of nanoparticles coating on thermal conductivity of nanofluids
Authors: Roni Md. Rakibul Hasan , Shahadat Muhammad Rubayat Bin , Morshed A.K.M. Monjur Monjur 
Published: January 2021

AbstractNanofluids have become the subject of theoretical and experimental researches over the last few decades due to their enhanced heat transfer performance. In this study, thermal conductivity of copper argon nanofluids containing coated and non‐coated copper particles is determined through MD simulation. Coating over the nanoparticles is applied to provide long‐term stable dispersion and also to enhance the heat transfer performance. Thermal conductivity of nanofluids depends on the types of coating applied over the nanoparticles. The role of surface coating over the nanoparticles in enhancing thermal properties of the nanofluids is discussed and compared to that of non‐coated particles. The silver coating is applied over the copper nanoparticles. Green Kubo method is employed to determine the thermal conductivity of the nanofluids. Result shows that, for volume fraction 3% and 86 K system temperature, thermal conductivity enhancement of nanofluid containing coated particle is 17% compared to that of base fluid and without coating, thermal conductivity enhancement is 12%. The mechanism of increased heat transfer performance for surface coating over the nanoparticles is discussed in this paper.
Design and analysis of piezoelectric MEMS micro‐speaker based on scandium‐doped AlN thin film
Authors: Fawzy Ahmed , Lang Yiming , Zhang Menglun 
Published: January 2021

AbstractPiezoelectric MEMS microspeakers are promising candidates for miniaturized speakers, such as for in‐ear applications. Using lead‐free scandium doped aluminium nitride (ScAlN) thin film instead of lead zirconium titanate helps these speakers to be environmental friendly, CMOS compatible and potentially more linear. The piezoelectric coefficient of ScAlN is higher than undoped AlN, which leads to improved performance of MEMS actuators including speaker chips. The design of piezoelectric MEMS ScAlN speaker based on four triangular cantilevers is proposed. The design in this work has been verified by finite element method simulation. The displacement and sound pressure level are 39 μm and 56 dB, respectively. This MEMS loudspeaker has small size and simple structure. The model opens the door also to further optimization for higher energy efficiency and higher acoustic performance based on lead‐free ScAlN thin film.
Effect of TiO2 grain size on performance of Ba0.5Sr0.5TiO3 based capacitors for energy storage application
Authors: P. S. Smitha , S. Jayan Jitha , Appukuttan Saritha , V. Suresh Babu , G. Shiny 
Published: January 2021

AbstractPerformance of energy storage devices, particularly metal‐insulator‐metal capacitors are evaluated mainly by leakage current and specific capacitance. The insulator material BaSrTiO shows high specific capacitance owing to its high relative permittivity. In this work, BaSrTiO nanopowder is synthesized using commercially available TiO nanopowder (ACS reagent grade) as well as using synthesized TiO nanopowder from Ti isopropoxide. The crystallinity and grain sizes of commercially available and synthesized TiO nanopowder differ. The effects of crystallinity and grain size of TiO nanopowder on specific capacitance and leakage current density of BaSrTiO ceramic based metal‐insulator‐metal capacitors are investigated in this paper. An 88 % reduction in grain size is achieved in TiO nanopowder synthesized from Ti isopropoxide compared to commercially available TiO nanopowder. A 45 % enhancement in specific capacitance and 57 % enhancement in leakage current are achieved in BaSrTiO ceramic based metal‐insulator‐metal capacitor synthesized using TiO nanopowder with lower grain size. The lower leakage current of metal‐insulator‐metal capacitor with BaSrTiO ceramic of low grain size is investigated with its structure using X‐ray powder diffraction pattern analysis as well. The BaSrTiO ceramics synthesized using TiO nanopowder with lower grain size is a suitable candidate for insulator material in metal‐insulator‐metal capacitors for energy storage application.
Study of the magnetic properties of Mn‐doped iron titanate nanoparticles fabricated using natural mineral
Authors: Senthil Sutha , Nattanmai Raman Dhineshbabu , Sundaramoorthy Arunmetha 
Published: January 2021

AbstractIn this study, iron titanate (FT) and manganese‐doped iron titanate (MFT) nanoparticles were synthesised from a natural mineral, ilmenite ore, using a simple and effective method. X‐ray diffraction analysis confirmed the reduction of crystallite size from 56 to 29 nm with an increase in Mn doping concentration from 0% to 2%. Doping of Mn transformed the agglomerated fine particles into nanosphere‐like morphology with dimensions less than 200 nm. Magnetization studies revealed that FT and MFT were hard ferrimagnetic materials, and beyond 0.8% Mn dopant concentration, reduction in magnetic saturation value of 1.46–1.41 emu g−1 was observed. Resistivity of FT decreased from ≈19 to ≈2 K Ω‐cm with doping Mn and tuning of such electrical property through doping concentration can lead to their application in fabricating spintronic devices. This work suggests a new pathway to synthesise magnetic–semiconducting nanostructures at large scale and in an environment friendly manner from ilmenite ore.