bluuebunny/crossref_metadata_2025 huggingface dataset:
PANDAA intentionally violates conventional qPCR design to enable durable, mismatch-agnostic detection of highly polymorphic pathogens
Authors: MacLeod Iain J. , Rowley Christopher F. , Essex M.
Published: February 2021

Sensitive and reproducible diagnostics are fundamental to containing the spread of existing and emerging pathogens. Despite the reliance of clinical virology on qPCR, technical challenges persist that compromise their reliability for sustainable epidemic containment as sequence instability in probe-binding regions produces false-negative results. We systematically violated canonical qPCR design principles to develop a Pan-Degenerate Amplification and Adaptation (PANDAA), a point mutation assay that mitigates the impact of sequence variation on probe-based qPCR performance. Using HIV-1 as a model system, we optimized and validated PANDAA to detect HIV drug resistance mutations (DRMs). Ultra-degenerate primers with 3’ termini overlapping the probe-binding site adapt the target through site-directed mutagenesis during qPCR to replace DRM-proximal sequence variation. PANDAA-quantified DRMs present at frequency ≥5% (2 h from nucleic acid to result) with a sensitivity and specificity of 96.9% and 97.5%, respectively. PANDAA is an innovative advancement with applicability to any pathogen where target-proximal genetic variability hinders diagnostic development.
Rotaxane rings promote oblique packing and extended lifetimes in DNA-templated molecular dye aggregates
Authors: Barclay Matthew S. , Roy Simon K. , Huff Jonathan S. , Mass Olga A. , Turner Daniel B. , Wilson Christopher K. , Kellis Donald L. , Terpetschnig Ewald A. , Lee Jeunghoon , Davis Paul H. , Yurke Bernard , Knowlton William B. , Pensack Ryan D.
Published: February 2021

Molecular excitons play a central role in natural and artificial light harvesting, organic electronics, and nanoscale computing. The structure and dynamics of molecular excitons, critical to each application, are sensitively governed by molecular packing. Deoxyribonucleic acid (DNA) templating is a powerful approach that enables controlled aggregation via sub-nanometer positioning of molecular dyes. However, finer sub-Angstrom control of dye packing is needed to tailor excitonic properties for specific applications. Here, we show that adding rotaxane rings to squaraine dyes templated with DNA promotes an elusive oblique packing arrangement with highly desirable optical properties. Specifically, dimers of these squaraine:rotaxanes exhibit an absorption spectrum with near-equal intensity excitonically split absorption bands. Theoretical analysis indicates that the transitions are mostly electronic in nature and only have similar intensities over a narrow range of packing angles. Compared with squaraine dimers, squaraine:rotaxane dimers also exhibit extended excited-state lifetimes and less structural heterogeneity. The approach proposed here may be generally useful for optimizing excitonic materials for a variety of applications ranging from solar energy conversion to quantum information science.
Fossilized anaerobic and possibly methanogenesis-fueling fungi identified deep within the Siljan impact structure, Sweden
Authors: Drake Henrik , Ivarsson Magnus , Heim Christine , Snoeyenbos-West Oona , Bengtson Stefan , Belivanova Veneta , Whitehouse Martin
Published: February 2021

Recent discoveries of extant and fossilized communities indicate that eukaryotes, including fungi, inhabit energy-poor and anoxic environments deep within the fractured igneous crust. This subterranean biosphere may constitute the largest fungal habitat on our planet, but knowledge of abyssal fungi and their syntrophic interactions with prokaryotes and their concomitant metabolisms is scarce. Here we report findings of fossilized, chitin-bearing fungal hyphae at ~540 m depth in fractured bedrock of the Siljan impact structure, the largest crater in Europe. Strong 13C-enrichment of calcite precipitated with and on the fungi suggests formation following methanogenesis, and that the anaerobic fungi decomposed dispersed organic matter producing for example H2 that may have fueled autotrophic methanogens. An Eocene age determined for the calcite infers the first timing constraint of fossilized fungi in the continental igneous crust. Fungi may be widespread decomposers of organic matter and overlooked providers of H2 to autotrophs in the vast rock-hosted deep biosphere.
Graphene based electrochemical immunosensor for the ultra-sensitive label free detection of Alzheimer's beta amyloid peptides Aβ(1–42)
Authors: Abbasi Hina. Y. , Tehrani Zari , Devadoss Anitha , Ali Muhammad Munem , Moradi-Bachiller Soraya , Albani Diego , Guy Owen. J.
Published: February 2021

Development of ultra-thin polymer layer modified screen printed graphene electrodes with high conductivity for higher-sensitivity detection of Aβ(1–42) peptides with the lowest LOD of 1.4 pg mL−1is presented.
Armor-like passivated CsPbBr3 quantum dots: boosted stability with hand-in-hand ligands and enhanced performance of nuclear batteries
Authors: Yang Dandan , Xu Zhiheng , Gong Chunhui , Su Lin , Li Xiaoming , Tang Xiaobin , Geng Dongling , Meng Cuifang , Xu Feng , Zeng Haibo
Published: February 2021

An armor-like passivation strategy is developed to improve luminous efficiency, storage stability, water resistance and irradiation stability of PQDs. Moreover, PQDs as the transducer component are used in radioluminescent nuclear battery.
Oxidation of the inert sp3C–H bonds of tetrahydroisoquinolines through C–H activation relay (CHAR): construction of functionalized isoquinolin-1-ones
Authors: Yuan Yuan , Zhang Shuwei , Sun Zheng , Su Yichun , Ma Qiyuan , Yuan Yu , Jia Xiaodong
Published: February 2021

An unprecedented functionalization of the 3,4-C–H bonds of THIQs was realized byCHAR, accomplishing the shift of radical center from the active position to the inert position.
Removal of methylene blue and lead(ii) via PVA/SA double-cross-linked network gel beads loaded with Fe3O4@KHA nanoparticles
Authors: Niu Yuhua , Han Xingxing , Song Jie , Huang Liangxian
Published: February 2021

The adsorption of MB and Pb(ii) onto and regeneration of PVA/SA/Fe3O4@KHA magnetic gel beads.
How accurate are citations of frequently cited papers in biomedical literature?
Authors: Pavlovic Vedrana , Weissgerber Tracey , Stanisavljevic Dejana , Pekmezovic Tatjana , Milicevic Ognjen , Lazovic Jelena Milin , Cirkovic Andja , Savic Marko , Rajovic Nina , Piperac Pavle , Djuric Nemanja , Madzarevic Petar , Dimitrijevic Ana , Randjelovic Simona , Nestorovic Emilija , Akinyombo Remi , Pavlovic Andrija , Ghamrawi Ranine , Garovic Vesna , Milic Natasa
Published: February 2021

Citations are an important, but often overlooked, part of every scientific paper. They allow the reader to trace the flow of evidence, serving as a gateway to relevant literature. Most scientists are aware of citations’ errors, but few appreciate the prevalence of these problems. The purpose of the present study was to examine how often frequently cited papers in biomedical scientific literature are cited inaccurately. The study included an active participation of the first authors of included papers; to first-hand verify the citations accuracy. Findings from feasibility study, where we reviewed 1540 articles containing 2526 citations of 14 most cited articles in which the authors were affiliated with the Faculty of Medicine University of Belgrade, were further evaluated for external confirmation in an independent verification set of articles. Verification set included 4912 citations identified in 2995 articles that cited 13 most cited articles published by authors affiliated with the Mayo Clinic Division of Nephrology and Hypertension. A citation was defined as being accurate if the cited article supported or was in accordance with the statement by citing authors. At least one inaccurate citation was found in 11 and 15% of articles in the feasibility study and verification set, respectively, suggesting that inaccurate citations are common in biomedical literature. The most common problem was the citation of nonexistent findings (38.4%), followed by an incorrect interpretation of findings (15.4%). One-fifth of inaccurate citations were due to chains of inaccurate citations. Based on these findings, several actions to reduce citation inaccuracies have been proposed.
Plant growth-promoting microbes — an industry view
Authors: Breakfield Natalie W. , Collett Dayna , Frodyma Michael E.
Published: February 2021

Plant growth-promoting microbes can affect the plant microbiome, improving different properties of the plant such as yield and health. Many companies are commercializing these microbes as products called biologicals. Defining the product concept is one of the first and most important steps in making a biological product. Companies can use phenotyping and genotyping approaches to identify the microbe to make into a live bacterial product. Screening usually begins in the laboratory and often moves from high-throughput methods to more time and resource-intensive methods culminating in large scale field testing. Once the microbe is chosen, the fermentation process grows the bacteria to the necessary amounts, while the formulation process ensures a stable product in the desired form such as a liquid or powder. The products must show yield increases in the field over several seasons and conditions, but also must be easy to use and cost-effective to be adopted by farmers and other customers. Tying all these data together from the selection process to test results gives a customer a ‘reason to believe’ for the marketing and launch of a successful product.
Machine learning‐based scheduling: a bibliometric perspective
Authors: Li Shiyun , Yu Tianzong , Cao Xu , Pei Zhi , Yi Wenchao , Chen Yong , Lv Ruifeng
Published: February 2021

In recent years, the rapid development of artificial intelligence and data science has given rise to the study of data driven algorithms in highly volatile systems. The scheduling of complex shop floor resources falls into such a category, which is often non‐linear in nature, time varying, multi‐objective, and subject to interruptions. Ergo, the machine learning‐based scheduling, has become a research hotspot and attracted the attention of many scholars. In the literature, the research methods employed in solving scheduling problems are based on various perspectives, such as mathematical programming, combinatorial optimization, and heuristic rules. However, due to the inherent complexity of the problem, many issues remain to be addressed. In particular, with the availability of production data, the progress of computing power, and the breakthrough in intelligent algorithms, a novel branch of data driven algorithms present great potential, for example, the deep learning and reinforcement learning‐based algorithms. To reveal the value of machine learning‐based scheduling methods, bibliometric analysis was conducted to analyse the relevant articles and documents from the year 1980 to 2019. Finally, the future research trend in the domain of machine learning‐based scheduling is considered and tips are provided for researchers as well as practitioners to find leading scientists for collaborations.
Comparative study of stator consequent‐pole permanent magnet machines
Authors: Li Ya , Yang Hui , Lin Heyun
Published: February 2021

A comparative investigation is made of stator consequent‐pole (SCP) machines with different permanent magnet (PM) arrangements. Compared with conventional surface‐mounted PM (SPM) configurations, SCP configurations produce more orders of air‐gap field harmonics. Due to asymmetrical PM magnetomotive force (MMF) distributions and the double‐side slotting effect, SCP machines exhibit multiple air‐gap field harmonics, especially relatively enhanced low‐order field harmonics, for torque production. As a consequence, improved torque capability can be obtained over that of conventional SPM counterparts. Machine topologies and operating principles are described. The design parameters of four SCP machines with different magnet arrangements are globally optimised. The key electromagnetic performances, including open‐circuit performance, torque quality, field‐weakening capability, and efficiency, are comprehensively investigated and compared by the finite element (FE) method. Finally, some experimental measurements on an optimally selected SCP machine prototype are carried out to validate the theoretical and FE analyses.
ACAR: an ant colony algorithm‐based routing protocol for underwater acoustic sensor network
Authors: Su Yishan , Zhang Lin , Fu Xiaomei , Li Yun
Published: February 2021

Research on underwater acoustic sensor networks has become a compelling field in recent years since resources on land are being depleted. Therefore, robust and efficient routing protocols are needed to ensure the reliability of message gathering and transmitting in underwater sensor networks. In the process of biological foraging in nature, creatures such as insects can find paths while adapting to dynamic environmental conditions through group cooperation, which provides a new perspective for research on routing protocols. In this study, the authors proposed an ant colony algorithm‐based routing protocol (ACAR). In ACAR, the pheromone with a novel physical meaning and concentration changing mechanism is utilised to guide ants (path establishing packets) to the sink node. In addition, node depth information is used to decrease redundancy in the underwater environment. The routing process can be summarised in three parts: pheromone list setup, routing decision and damaged path repair. Simulation results, carried out on an underwater simulator based on NS‐2, showed that ACAR outperforms other schemes with regards to network lifetime with a relatively better delivery ratio and latency in the proposed network scenarios.
Hybrid deep learning‐based throughput analysis for UAV‐assisted cellular networks
Authors: Yayeh Munaye Yirga , Juang Rong‐Terng , Lin Hsin‐Piao , Berie Tarekegn Getaneh
Published: February 2021

Mobile users are interested in utilising high network capabilities without time and place constraints. However, with a high level of interest in the usage of mobile phones and internet facilities, the limited capacity of terrestrial base stations (BSs) is unbalanced. As a potential alternative to BSs, unmanned aerial vehicles (UAVs) are emerging as a means of transmitting wireless data to ground mobile users. As an air‐to‐ground communication network, the real UAVs deployed and collected communication data from ground mobile users. The main objective of this study is to analyse and evaluate user throughput, interference, and power transmission when the UAVs are at different heights. The parameters used include the locations of the UAVs and users, the altitudes and elevation angles from the users to UAVs, signal‐to‐noise‐ratio, throughput values, the categories of line‐of‐sight, and non‐line‐of‐sight links. Furthermore, K‐means used as a clustering method for class identification, long short‐term memory (LSTM), and gated recurrent unit (GRU) to analyse and evaluate system performance. The system's performance was compared with a multi‐layer perceptron approach. The evaluation results show that the proposed LSTM–GRU provides reliable and encouraging performance with low computational complexity, which is appropriate for heterogeneous networks.
Anisotropic layer model theory applied to synchronous machine analysis
Authors: Alvarenga Bernardo P. , Alves Renato S. , Paula Geyverson T. , Marra Enes G. , Chabu Ivan E. , Cardoso José R. , Mecrow Barrie C. , Smith Alexander C.
Published: February 2021

This study demonstrates the application of layer model theory to the analysis of synchronous machines. The derivation of the model from Maxwell's equations is briefly described. With the use of steady‐state equations and terminal operation information, a methodology is established, and the synchronous machine operation is modelled. Two case examples are then analysed. It is shown that the layer model methodology can be applied to synchronous machines with promising results.
Design optimisation and performance investigation of novel dual three‐phase permanent‐magnet linear synchronous machines for a ropeless elevator system
Authors: Jiang Qian , Lu Qinfen , Li Yanxin , Wu Bocheng
Published: February 2021

A novel dual three‐phase permanent‐magnet linear synchronous machine (DTP‐PMLSM) is proposed for the large capacity ropeless elevator, where two sets of windings have 30 electrical degrees phase shift in space. First, the topology of DTP‐PMLSM with 12‐slot/11‐pole (12 s/11p) combination is introduced. Second, the influence of each main parameter on thrust force performance is investigated by single variable sweeping method, and then DTP‐PMLSM is optimised by global optimisation method. Moreover, the electromagnetic performance is predicted and analysed by two‐dimensional (2D) finite element method (FEM) in detail. Compared with conventional single three‐phase PMLSM, the proposed DTP‐PMLSM shows better force performance. Furthermore, the analysis results are compared with 3D FEM which includes the transverse end effect. Finally, a 12 s/11p prototyped machine is built and tested to validate the theoretical analyses.
Improved position signal demodulation method for sensorless control based on HF sinusoidal pulsating voltage injection
Authors: Liu Jiali , Zhang Yongchang , Yang Haitao
Published: February 2021

High frequency (HF) sinusoidal pulsating voltage injection is a reliable method for position sensorless control in low speed range. For HF voltage injection based methods, position signal demodulation plays a key role. However, the conventional sinusoidal demodulation suffers from long settling time and limited bandwidth because of requirement of a low‐pass filter (LPF) to suppress HF harmonics in the estimated position. Additionally, the overall performance is deteriorated due to the characteristic of linear demodulation. To address these issues, the cube of q‐axis HF current instead of itself is used as the carrier of position estimation error. In this way, the input variable for phase‐locked loop (PLL) is the cube function with respect to the position deviation. During steady state, the equivalent gain in PLL is very small and thus the estimated position is non‐sensitive against high‐frequency harmonics, thereby the LPF is no longer required in the proposed method. While during dynamic process, the equivalent gain is increased leading to a fast converging rate when compared with the conventional method. The stability and dynamic performance are theoretically analysed by the magnitude–frequency diagram. The superiority of the proposed method was experimentally justified and the obtained results show that both steady‐state and dynamic performance are improved when compared with the prior art.
Multipurpose battery‐assisted solar water pumping system for off‐grid applications: design and development
Authors: Vamja Rajan Vinodray , Mulla Mahmadasraf A.
Published: February 2021

Providing basic human needs like water and household electricity is a challenging task at remote locations. To support both needs, this study presents the development of a multipurpose battery‐assisted solar water pumping system (SWPS). The system consists of only two power electronics converter, viz., bidirectional DC–DC converter, and three‐phase voltage source inverter (VSI). The detailed control system is presented, where the DC–DC converter controls the battery power and also ensures the maximum utilisation of stand‐alone solar photovoltaic source. In pumping operation, the VSI is operated as a variable frequency motor drive and rotates an induction motor (IM) at the rated power to deliver rated water discharge. In power supply operation, the household electrical load is connected between the mid‐point of DC‐bus and the star point of an IM winding. The VSI, along with motor inductance, realises the single‐phase inverter, which is controlled with synchronous sine pulse‐width modulation to deliver single‐phase output. The motor does not rotate during this operation and the motor winding acts as a current filter. This multipurpose SWPS assures rated water discharge during the irrigation period and availability of electrical power in the remaining period. A prototype is developed and extensive experiments are performed to investigate system performances.
Saturated VSD model of a six‐phase induction machine
Authors: Brkovic Bogdan Mihailo , Jecmenica Milos , Levi Emil , Lazarevic Zoran M.
Published: February 2021

In this study, a saturated model of an asymmetrical six‐phase induction machine is presented. The model is based on the vector space decomposition approach, and it includes main and leakage flux saturation, as well as the mutual coupling between orthogonal planes while using the Gamma equivalent circuit approach. The accuracy of the proposed model in unbalanced operating modes that are characteristic for multiphase machines, such as post‐fault and power‐sharing operation, makes it advantageous compared to existing models. The model is developed assuming that the machine operates in asymmetrical conditions and that, therefore, there is fundamental frequency excitation in both planes. The inter‐plane coupling effect is examined using finite element analysis and an experimental procedure for its quantification is developed. The model is verified by comparison with the experimental results obtained from a prototype asymmetrical six‐phase induction machine, and its advantages compared to existing models are emphasised.
Magnet array of planar motor using permanent magnets with different magnetisation intensity and height
Authors: Wang Yang , Chen Fuxiang , Zheng Zhiyi , Zeng Lizhan
Published: February 2021

Planar motor is used as an actuator to directly produce multi‐degree long stroke, high speed, and high precision movement. Its performance mainly depends on the topology and design of magnet array. In response to the rising trend of structural complexity, this study presents a novel easy‐to‐manufacture magnet array using permanent magnets with different magnetisation intensity and height. First, the flux density distribution of magnet array with different magnetisation intensity is derived by the Fourier analysis and the scalar magnetic potential equation. Then, the magnetic field model of magnet array using permanent magnets with different magnetisation intensity and height is obtained by the superposition method. Afterwards, the magnet array is raised and optimised based on the derived model. Calculations show that the high‐order harmonics are significantly reduced. At last, the proposed analytical modelling method and magnet array are verified with experiments.
Depth estimation for underwater images from single view image
Authors: Raihan A Jarina , Abas Pg Emeroylariffion , De Silva Liyanage C
Published: February 2021

Underwater images often undergo distortions from scattering, absorption, colour loss, diffraction, polarisation, and varying attenuation depending on the light frequency, due to the water medium. This study answers problems associated with the recovery of underwater images, by developing novel depth map estimation which may be used as an intermediary step for underwater image restoration. The depth map is an important factor for the recovery of the underwater image, as it has been shown that proper estimation of depth, results in better restoration of the underwater image. The proposed algorithm estimates a depth map from a single view image, using blurriness and lighting information, obtained using a simple background neutralisation method. Results from the algorithm on selected raw underwater image data set have been compared with other algorithms and it has been shown that the proposed method gives Pearson coefficients in the range of 0.75–0.95, which are considerably higher and better log root mean square value compared to other methods in the literature. This suggests a better estimation of depth by the proposed method.
Rotational invariant biologically inspired object recognition
Authors: Sufi karimi Hiwa , Mohammadi Karim
Published: February 2021

The biologically inspired hierarchical model and X (HMAX) has been one of the superior techniques for object recognition purposes. HMAX is a robust method in the presence of some image variations including illumination, different scales, and location changes. However, the performance of HMAX extremely deteriorates if the orientation of the applied images in training phase is different than the orientation of testing images. In this study, the authors propose rotational invariant HMAX (RIMAX) to overcome the existing issues in object recognition imposed by rotations in the images. To this end, they embed two new layers into the structure of the standard HMAX. In the first added layer, non‐accidental properties (e.g. corners and edges) are extracted as features that lead to obtaining a repeatable object recognition process. The second added layer provides robustness of RIMAX to image rotations by normalising the dominant orientation of the extracted features. Furthermore, they considerably reduce the imposed computational load by modifying template matching strategy as well as removing multiple scales of the Gabor filter. Simulation results employ Caltech101, TUD, Caltech5, and GRAZ‐02 databases that validate RIMAX outperforms the standard HMAX and the other mathematical approaches in terms of robustness, accuracy, repeatability, and speed.
Automatic production of synthetic labelled OCT images using an active shape model
Authors: Danesh Hajar , Maghooli Keivan , Dehghani Alireza , Kafieh Rahele
Published: February 2021

Limited labelled data is a challenge in the field of medical imaging and the need for a large number of them is paramount for the training of machine learning algorithms, as well as measuring the performance of image processing algorithms. The purpose of this study is to construct synthetic and labelled optical coherence tomography (OCT) data to solve the problems of having access to accurately labelled data and evaluating the processing algorithms. In this study, a modified active shape model is used which considers the anatomical features of available images such as the number and thickness of the layers as well as their associated brightness, the location of retinal blood vessels and shadow information with respect to speckle noise. The algorithm is also able to provide different data sets with the varying noise level. The validity of the proposed method for the synthesis of retinal images is measured by two methods (qualitative assessment and quantitative analysis).
Genetic‐based feature fusion in face recognition using arithmetic coded local binary patterns
Authors: Najafi Khanbebin Saeed , Mehrdad Vahid
Published: February 2021

Local binary patterns (LBPs) are one of the attempts for gathering local features with face recognition algorithms. Although the application of LBP's in many recognition contents is too apparent, these methods have limited accuracy because of their threshold value. One problem is earning one value for two different regions with a diverse pixel neighbourhood, which causes mistakes in feature vector and decreases the discriminative power. In this study, the authors proposed a modified LBP that covers the LBP's disadvantages. The proposed approach is arithmetic coded LBP (ACLBP) that uses arithmetic coding process during LBP calculation instead of applying original thresholds. The proposed policy addresses the problem of returning one similar LBP value for two different patches. Moreover, the proposed method modifies LBP by using a different threshold for calculating the pixels differences. Using this algorithm, the authors conducted a genetic‐based feature fusion method by combining LBP and histogram of oriented gradients and ACLBP. The proposed approach could work better on LFW dataset, and the ORL dataset and Yale face dataset that shows the improving role of ACLBP in comparison with the earlier version of LBP.
Wise optimisation: deep image embedding by informative pair weighting and ranked list learning
Authors: Fan Lili , Zhao Hongwei , Zhao Haoyu
Published: February 2021

Deep image embedding learns how to map images onto feature vectors. Image retrieval performance is often used to evaluate embedding quality. In this study, the authors proposed a wise deep image embedding optimisation (WDIEO) algorithm based on informative pair weighting and ranked list learning (IPWRLL) for network optimisation of fine‐grained image retrieval. First, a hard sample mining method Top‐k is proposed to select positive and negative samples. Then, for the selected query sample, a ranking list is obtained by comparing the similarity between samples in the data set and the query sample, and the sample is labelled according to the similarity. Finally, for positive samples, two optimisation rules with different functions are used, while ensuring two key issues of instance weighting and intra‐class data distribution. For negative samples, different from the widely adopted methods based on the weight of sample information, the authors’ algorithm's weights are set according to the ranking list, which keeps the inter‐class data distribution and the optimisation direction consistent with the loss reduction direction. The WDIEO‐IPWRLL model is an end‐to‐end optimisation that can share parameters in the testing process. Experiments show that their proposed model achieves the state‐of‐the‐art performance on the benchmark data set.
HU‐PageScan: a fully convolutional neural network for document page crop
Authors: das Neves Ricardo Batista , Lima Estanislau , Bezerra Byron L.D. , Zanchettin Cleber , Toselli Alejandro H.
Published: February 2021

November The offer of online, automated, and impersonal services demand users to upload scanned copies of their documents to the organisations. As a consequence of this decentralisation, the documents present more challenges to the already complex process of image processing and information extraction. To address this problem, the authors presented an optimised fully convolutional neural network model for document segmentation that works on mobile devices to detect the region of the document in the captured image. They performed experiments in three representative datasets comparing the proposed method with the Geodesic object Proposals, U‐net, Mask R‐CNN, and OctHU‐PageScan algorithms. They also compared the proposed model with all competitors of the ICDAR2015 Competition on smartphone document capture. Furthermore, they performed a qualitative and comparative analysis with the CamScanner software, a popular app for Android and iOS smartphones used for more than 100 million users in over 200 countries. The proposed approach achieved a significant performance compared with the current state‐of‐the‐art methods, providing a powerful approach for document segmentation in photos and scanned images.
Image enhancement using convolutional neural network to identify similar patterns
Authors: Lu Ching‐Ta , Chen Ruei‐Han , Wang Ling‐Ling , Lin Jia‐An
Published: February 2021

An image may be disturbed by impulse noise during transmission or acquisition. To effectively restore the disturbed image is important for the applications of image processing. This study aims at enhancing the disturbed images by using the convolutional neural network (CNN) to identify similar patterns for the restoration of noisy pixels. In the training phase, each noisy pixel is analysed and compared with the noise‐free image to find the closest neighbouring pixels. The pixels in a local window form a micro‐pattern. All the captured micro‐patterns, whose centre pixel is noisy, become a dataset for the training of a position CNN. The closest neighbouring pixel of a noisy image to the centre one of the noise‐free image at the same position of each micro‐pattern is selected to be the target. In the enhancement phase, a noisy micro‐pattern, where the centre pixel is noisy, is input into the trained position CNN. The top N pixels are recognised and averaged to replace the grey level of the centre pixel. An enhanced pixel is obtained. The experimental results show that the position CNN can well recognise the similar neighbouring pixels and effectively enhance the noisy pixels in an image disturbed by salt‐and‐pepper noise.
Direct synthesis and systematic design of a multi‐objective controller for grid‐connected inverters under weak grid conditions
Authors: Raja Parthiban , Bhaskaran Umamaheswari , Shanmugam Paramasivam
Published: February 2021

A systematic approach for synthesis and tuning of the controller for grid‐connected inverters with LCL‐filter is proposed in this study. The design objectives like current tracking, harmonics rejection, resonant damping and extended stability over wide grid variations are addressed. Controller structure is synthesised by direct synthesis approach which leads to a systematic design procedure and tuning method. Low‐frequency approximation of the system under worst grid condition is used for the synthesis of the current controller and the resonance component is handled separately. Tunable parameters are identified to investigate grid variations in the process of augmenting the synthesised controller for realisability. Complete design, stability analysis and tuning are dealt with directly in the discrete domain. Detailed simulation and experimental validation are carried out on a 1 kW prototype inverter. The method proposed in this study serves as a simplified design tool for effective design of a multi‐objective controller for grid‐connected inverters.
Enhancing the stability of active harmonic filter using artificial neural network‐based current control scheme
Authors: Vaidya Tushar , Chatterjee Kishore
Published: February 2021

A combination of shunt active harmonic filter (SAHF), and adjustable power factor correction (PFC) capacitors is generally employed in industrial applications to achieve cost effective solution for the load compensation. It has been experienced that SAHFs operating in conjunction with PFC capacitors may lose their stability while compensating certain harmonic components which are near the resonant frequency of the network. This resonant frequency is not known beforehand while designing the controller of the SAHF, and further it keeps on varying with time as the value of PFC capacitors vary based on the reactive power requirement of the load. Therefore, the conventional controllers having predetermined values for gains fail to stabilise the operation of the SAHF under varying operating conditions of the network. This necessitates the involvement of an adaptive control mechanism within the SAHF with which the SAHF exhibits stable operation even under varying network conditions. In order to accomplish this requirement an artificial neural network‐based control scheme is proposed in this study. The proposed scheme is verified by conducting thorough simulation studies. The viability of the proposed scheme is also confirmed by carrying out detailed experimental studies on a laboratory prototype.
Scalable architecture of DC microgrid implemented with multi‐input multi‐output converter
Authors: Anees Muhammad , Nasir Mashood , Ahmad Zaffar Nauman , Abbas Khan Hassan , Vasquez Juan C. , Guerrero Josep M.
Published: February 2021

In this study, modelling, implementation, and control of a hybrid renewables‐based, scalable DC microgrid using multi‐input multi‐output dual active half‐bridge (DAHB) converter is presented. The proposed microgrid architecture exhibits superiority and enhanced functionality in comparison to the existing conventional architectures in terms of the reduced number of converters for each resource integration, modularity, scalability, and bidirectional power flow capability, and local maximum power point tracking for each renewable resource. The proposed architecture is significant in terms that only a single converter is responsible for the whole operation of the DC microgrid. A dual half active bridge acts as a central hub for power processing while multiple renewable energy resources can be integrated through isolated input and output ports. The proposed microgrid is analysed for power flow, and the control scheme for different voltage and power‐sharing scenarios is designed. The proposed architecture of the microgrid is simulated on the Power‐SIM simulator, and a simplified hardware prototype is implemented in the laboratory with satisfactory results.
Modified SPWM technique for improved harmonic performance of single PV array fed grid‐tied five‐level converter
Authors: Yadav Shivam Kumar , Mishra Nidhi , Singh Bhim , Padmanaban Sanjeevikumar , Blaabjerg Frede
Published: February 2021

This study presents a performance assessment of a single photovoltaic (PV) array fed transformer‐based five‐level converter topology with optimal shift factor‐based modified sinusoidal pulse width modulation (OSF‐MSPWM) technique under a dynamic solar PV environment. The five‐level converter output is generated using H bridge cells and single‐phase transformers. A single PV array is fed to all cascaded H bridge cells and isolation is provided by cascading secondary windings of the transformers in the AC side. The separate DC sources requirement is eliminated and galvanic isolation is provided by single‐phase transformers. The decoupled controller with modified in‐phase disposition PWM technique is used for active power injection into the grid at unity power factor. This work uses a new carrier shape at the same input carrier frequency and modulation index mf for improving the harmonics performance of the five‐level converter. Hence, shift the dominant harmonics to the higher side for developed topology and performing optimal shift factor‐based modulation is compared with the conventional SPWM technique. The steady‐state and dynamic responses of the PV multilevel converter are observed in MATLAB simulation and tested in a real‐time platform.
Battery voltage equalisation using single‐phase cascaded H‐bridge converters
Authors: Pirooz Ashkan , Firouz Yousef , Berecibar Maitane , Van Mierlo Joeri
Published: February 2021

This research demonstrates modular battery storage systems' voltage balancing using cascaded H‐bridge (CHB) converters. The main principle is to maintain AC‐side high‐quality power absorption or injection, while on the DC‐side independent battery units' voltages get balanced. The CHB converter operates in inversion or rectification modes to discharge the storage system to an AC load/grid, or to charge it from an AC source, respectively. To achieve this goal, several challenges as high‐differential mode , and dealing with semiconductors voltage drop also arise which should get tackled through feasible controller design. Model predictive control (MPC), as a flexible technique capable of multi‐parameter controlling, is used to achieve the beforementioned system objectives in a simple, efficient, and scalable manner. The proposed MPC‐based algorithm is an AC current controller, which handles DC‐side voltage equalisation and introduces adjacent CHB voltage levels to reduce and performs switches voltage loss modelling all in a single control block. An additional linear controller based on multi‐carrier pulse width modulation is also implemented for comparison with the MPC‐based design. Experimental prototyping and simulation results validate the feasibility of this approach.
VSC plug‐and‐play operation using online grid parameter estimation for PI self‐tuning
Authors: Alves André G.P. , Rolim Luís G.B. , Dias Robson F.S. , Santos Paulo T.P.
Published: February 2021

This work presents a plug‐and‐play solution for voltage source converters controlled by proportional–integral controllers to automatically operate connected to a previously unknown grid. The methodology consists of an initial operation using hysteresis band current control in order to synthesise harmonic currents, which are used for online grid parameter estimation, allowing the proper analytical tuning of the controllers using the grid's equivalent model. The method is firstly simulated and then validated through experimental results using Texas Instruments TMS320F28377S Digital Signal Processor and BOOSTXLDRV8305‐EVM static converter.
Probabilistic evaluation of power converters as support in their design
Authors: Corti Fabio , Reatti Alberto , Patrizi Gabriele , Ciani Lorenzo , Catelani Marcantonio , Kazimierczuk Marian K.
Published: February 2021

In this study, a procedure to evaluate the performance of a power converter under different operating conditions is presented. The technique takes into account the effect of the environmental conditions and the tolerance on each component and it provides a probability estimation that the converter will reach certain performance under definite operating condition. This feature allows to better understand the operation of the converter even outside the nominal operating conditions. Furthermore, by appropriately modelling the performance of each component, it is possible to understand from the early design stages which component technology is more suitable according to the environment in which the converter will work. The steps of the procedure are explained in detail and a case study applied on a Class‐E inverter to provide a step‐by‐step explanation and to experimentally validate the accuracy of the probability estimation is presented.
Parametric transformer using PM‐inductors with saturation‐gap
Authors: Revilla Aguilar Andres , Rannestad Bjørn , Munk‐Nielsen Stig
Published: February 2021

Parametric transformers are magnetic components which employ a variable inductance to generate parametric oscillations in a secondary resonant tank. Power conversion with parametric transformer can provide constant output voltage regulation, short‐circuit protection, input over‐voltage and under‐voltage protection, and bidirectional filtering. In spite of these benefits, parametric transformers did only experience small scientific attention during the 1970s. Due to the low energy density and low efficiency of the topologies developed at the time, parametric transformers were discarded in favour of the more common power converters based on the magnetic amplifier. In spite of the great developments in power semiconductors, magnetic amplifier control still remains a competitive option in present‐day power electronic applications benefiting from its high robustness. This publication presents a new topology of parametric transformer based on permanent magnet (PM)‐inductors, presenting higher efficiency and higher energy density. Finite element method magnetics simulations are used to analyse the variable inductance mechanisms. A physical prototype is developed and tested empirically in an AC/DC power converter. The prototype verifies all the mentioned benefits of parametric power conversion, and presents an efficiency and energy density equivalent to presently employed solutions for voltage regulation, using power semiconductor magnetic amplifiers.
Mitigation of CM conducted EMI in flyback converter using balancing capacitors
Authors: Manjunath Ashritha , Sudheer M.L.
Published: February 2021

The offline Switched Mode Power Supply (SMPS) draw non‐sinusoidal line current from the utility power supply, thereby introducing unwanted harmonics and also generate significant electromagnetic interference (EMI). Power factor correction (PFC) converters can be used to improve the power factor. But they also generate EMI in both Differential Mode (DM) and Common Mode (CM). In this paper, the EMI generated by the flyback PFC converter is addressed. A lumped circuit model for CM conducted EMI generated in a flyback converter, including the HF transformer's parasitics and the components, is considered. The parasitics of the HF transformer are calculated and measured experimentally. Using them, the resonant frequencies of the flyback converter are calculated for validation. A technique for determining the required balancing capacitor to mitigate CM conducted EMI is presented. A novel technique by splitting this balancing capacitor with their mid‐point grounded for further reduction of this EMI is presented. This technique can eliminate the capacitors of the EMI line filter connected between line/neutral to the ground. Hence for the same amount of CM conducted EMI mitigation, the size and the cost of EMI line filters are reduced. Theoretical analysis, simulation results, and experimental verifications are presented.
Feature pyramid U‐Net for retinal vessel segmentation
Authors: Liu Yi‐Peng , Rui Xue , Li Zhanqing , Zeng Dongxu , Li Jing , Chen Peng , Liang Ronghua
Published: February 2021

The retinal vessel is the only microvascular network that can be directly and non‐invasively observed in humans. Cardiovascular and cerebrovascular diseases, such as diabetes, hypertension, can lead to structural changes of the retinal microvascular network. Therefore, it is of great significance to study effective retinal vessel segmentation methods and assist doctors in early diagnoses with quantitative results for vascular networks. In this study, we propose a novel convolutional neural network named feature pyramid U‐Net (FPU‐Net) that extracts multiscale representations by constructing two feature pyramids both on the encoder and the decoder of U‐Net. In this representation, objects features with different size like micro‐vessels and pathology will be fused for better vessel segmentation. The experimental results show that compared with state‐of‐the‐art methods, FPU‐Net is superior in terms of accuracy, sensitivity, F1‐score, and area under the curve and capable of stronger domain generalisation across different datasets.
Low‐profile millimetre‐wave wideband microstrip antenna with parasitic patch arrays
Authors: Xue Mei , Wan Weikang , Wang Qidong , Cao Liqiang
Published: February 2021

A millimetre‐wave low‐profile wideband microstrip antenna is proposed. To widen impedance bandwidth and achieve stable large gain simultaneously, coplanar parasitic patch arrays are arranged on both sides of a microstrip patch fed by a coaxial probe. Double slots are etched on the microstrip patch to reduce H‐plane cross‐polarization levels. Zero‐phase‐reflection analysis with Floquet‐port model is proposed to predict resonant frequency of the parasitic patch arrays. Resonance modes excited is verified according to input impedance with an ideal probe. Two adjacent broadside resonances respectively dominated by the quasi‐TM10 mode of the microstrip patch and quasi‐TM30 of the parasitic patch array are excited in turn. The proposed antenna with a dimension of 1.06 × 1.06 × 0.024 λ03 (λ0 is the wavelength of 29 GHz in free space) realizes 15% (27–31.35 GHz) impedance bandwidth for |S11| ≤ −10 dB. Realized peak gain is up to 9.26 dBi and 2‐dB gain bandwidth is 15.7%. H‐plane cross‐polarization levels within 3‐dB beamwidth are less than −14 dB, and back radiation levels are less than −17.9 dB.