bluuebunny/crossref_metadata_2025_split huggingface dataset:
Robustification of fault detection algorithm in a three‐phase induction motor using MCSA for various single and multiple faults
Authors: Kompella K. C. Deekshit , Rongala Naga Sreenivasu , Rayapudi Srinivasa Rao , Mannam Venu Gopala Rao 
Published: March 2021

AbstractFault diagnosis in induction machines, particularly at a premature stage, has become necessary to avoid unexpected interruption of the industrial process. Moreover, a reliable and cost‐effective fault detection process is highly essential to avoid inappropriate shut down of the machine. Thus, a critical comparison is done between two popular pre‐fault component cancellation techniques and a reliability test is performed to develop a robust algorithm for fault diagnosis in three‐phase induction motor. To achieve this, various single and multiple faults experienced by induction motor are created and tested to examine the effectiveness of developed algorithm. Evaluation of the proposed topology based on motor current signature analysis is done by repeating the process for several times and tested for consistency. As a part of this, various feature extraction parameters are computed and compared to identify the best estimate of fault and its seriousness. The proposed technique is examined in MATLAB and LabVIEW environment and experiments on a three‐phase, 1.5‐kW induction motor.
Open‐circuit fault‐tolerant operation of permanent magnet synchronous generator drives for wind turbine systems using a computationally efficient model predictive current control
Authors: Jlassi Imed , Marques Cardoso Antonio J. 
Published: March 2021

AbstractModel predictive fault‐tolerant current control (MPFTCC) of permanent magnet synchronous generator (PMSG) drives can make a valuable contribution to improving the reliability and availability levels of wind turbines, because back‐to‐back (BTB) converters are prone to failure. However, MPFTCC suffers from excessive computational burden, because the BTB converter is treated as one system where all feasible voltage vectors (VVs) are used for prediction and evaluation. Accordingly, a computationally efficient MPFTCC algorithm for a PMSG drive is developed and proposed with the ability to handle insulated‐gate bipolar transistor open‐circuit faults. The candidate VVs of both machine‐ and grid‐side converters are separately predicted and evaluated, which significantly reduces calculation effort. The proposed reconfigurable converter is a five‐leg power converter with a common leg that connects the generator first phase to the grid three‐phase, ensuring proper postfault reconfiguration of the grid‐side inverter. Moreover, a three‐switch rectifier is adopted to achieve fault tolerance of the PMSG‐side rectifier. Performance of the considered MPFTCC strategies is evaluated by experimental means.
Regularised dynamic optimal transportation of electric vehicles over networks considering strategic charging pricing
Authors: Feng Rui , Czarkowski Dariusz 
Published: March 2021

AbstractA dynamic optimal transport problem of electric vehicles (EVs) over a network is investigated. The EVs are considered to be transported from their initial locations to the destination nodes for charging purposes. In our framework, the operators of charging stations are strategic, and each of them designs their charging pricing optimally to maximise the revenue. Since EVs play an essential role as power loads at the charging stations, the designed transport strategy by the EV operator has an impact on the market energy price which in turn influences the charging prices. Therefore, to design an efficient transport plan, the EV operator needs to take into account its influence on the charging pricing and the market energy price due to their complex interplay. To achieve this goal, a unified framework is proposed for optimal EV transportation by considering factors including the delay, charging cost, and real‐time social demand of EVs over a finite‐time horizon. The balanced dynamic optimal transport strategy is enabled through a combined quadratic and entropic regularisation. To compute the equilibrium pricing for all charging stations, an iterative particle‐swarm optimisation scheme is designed which addresses a high‐dimensional nonlinear optimisation problem. Finally, case studies are used to illustrate and corroborate the obtained results.
Delayed mobile data offloading scheme for quality of service traffic: Design and analysis
Authors: Ajith Anusree , Venkatesh Tiruchirai Gopalakrishnan 
Published: March 2021

AbstractAs the world is entering the era of 5G, we are witnessing exponential growth in the volume of data traffic generated and consumed by mobile devices. Mobile data offloading handles the surge in mobile data traffic by offloading part of the traffic onto the Wi‐Fi network. In this context, we design and analyse a quality of service (QoS) enhancement scheme for delayed mobile data offloading. We first consider prioritised queuing of traffic as a scheme for QoS provisioning. Using the concepts of virtual waiting time, renewal process, and level crossing arguments, we derive the average transmission delay of the offloaded and reneged packets of high priority. Next, we mathematically validate the benefit of balking all such packets whose expected virtual waiting time exceeds their deadline. Using a three‐dimensional Markov chain model, we derive the required balking probability. Moreover, we merge the technique of balking with prioritisation for improving QoS in delayed offloading. Through an extensive simulation, we validate our analysis and demonstrate how the proposed scheme reduces the transmission delay without sacrificing offloading efficiency. Our investigation has the potential to be adopted in future mobile data offloading standards for improving QoS.
Mobile Cloud Computing and Wireless Sensor Networks: A review, integration architecture, and future directions
Authors: Panigrahi Chhabi Rani , Sarkar Joy Lal , Pati Bibudhendu , Buyya Rajkumar , Mohapatra Prasant , Majumder Abhishek 
Published: March 2021

AbstractIn today's fast advancing world, sensors are used in various applications to provide complete data about different objects present around us. The sensor data when integrated with Mobile Cloud Computing (MCC) is used for further computation to provide useful results advanced warning, forecasting, planning, and plethora of other applications in this uncertain world. Few works have been proposed where sensor nodes are integrated with Wireless Sensor Networks (WSNs) which give a new direction in modern research for developing new technologies which help the users for fast access of sensory data over mobile devices. Herein, a systematic literature review of both MCC and WSNs are conducted and subsequently assimilated them via an architecture which is efficient and achievable within short time‐span for a variety of applications. The MCC applications are reviewed from two main perspectives that are energy and information management. The communication aspect in MCC and WSNs has been discussed and the need for integration between the two has been justified in this work. The work done on mobility management in MCC and WSNs is reviewed. Also, the challenges in MCC‐WSNs integration along with the comprehensive analysis and findings of the review are identified. Finally, the conclusion and specific future direction of research in this area are provided.
Outage probability analysis of overlay cognitive two‐way relaying scheme with opportunistic relay selection
Authors: Ma Long , Li Enyu , Wang Xinjie , Gu Meng , Yang Qianqian 
Published: March 2021

AbstractThe authors investigate an overlay cognitive two‐way relaying system where max‐min (MM) relay selection scheme is employed for improving the reliability of the considered system. Furthermore, they design the process of the data forwarding and relay selection in the overlay cognitive two‐way relaying system. Based on the MM relay selection criterion, the exact close‐form expression of outage probability is derived. From numerical simulations, it is observed that there is an outage probability floor appearing in the high signal‐to‐noise ratio (SNR) region, and the reason for its occurrence is stated. Besides, the approximate result of outage probability in high SNR is provided, which shows that the ratio of interference channel' transmit power and main channel' transmit power will not affect the outage probability in low SNR region, but it will significantly affect it in the high SNR region. Although each individual channel state information (CSI) will not be able to control the outage performance of this considered system in the high SNR region, the ratio of each channel's CSI will be able to do the same.
Energy‐efficient reporting scheme for cognitive radio networks
Authors: Chilakala Sudhamani , Saxena Ashutosh , Vunnava Aswini 
Published: March 2021

AbstractCooperative spectrum sensing in cognitive radio network consumes a large amount of energy during spectrum sensing and reporting. An energy‐efficient reporting scheme called the reduced energy consumption scheme for reporting has been proposed to reduce energy consumption. In this scheme, all secondary users will sense the channel and make a local decision about the spectrum. All these local decisions are forwarded to a common node known as the fusion centre. This counts the presence or absence of the primary user based on the secondary user's local decisions. Whenever the counters count is greater than or equal to the threshold then the fusion centre sends a stop reporting feedback signal to the secondary users. In this way the energy consumption is reduced by diminishing the reporting secondary users and the energy efficiency is improved. The simulation and numerical results show a notable improvement in the energy efficiency of a reduced spectrum sensing scheme compared to the conventional spectrum sensing method.
DNN‐based distributed sequential uplink processing in cell‐free massive MIMO based on radio stripes
Authors: Mishra Aman Kumar , Ponnusamy Vijayakumar 
Published: March 2021

AbstractCell‐free massive MIMO (mMIMO) has two distinctive advantages: first is, macrodiversity from large numbers of distributed access points and second, interference cancellation from cellular mMIMO is envisioned to be next‐generation wireless technology for beyond 5G. However, its practical deployment is extremely challenging due to large numbers of long cables (economic perspective) and network synchronisation. Cell‐free mMIMO system based on radio stripe (CFMMRS) network is one such architecture of cell‐free mMIMO suitable for practical deployment. This study proposes DNN‐based distributed sequential uplink processing for detecting symbols in the uplink of CFMMRS network architecture. Simulation results show that the proposed algorithm outperforms the traditional iterative soft interference cancellation‐based detection method.
Learning and Stroke Recovery: Parallelism of Biological Substrates
Authors: Joy Mary Teena , Carmichael S. Thomas 
Published: March 2021

AbstractStroke is a debilitating disease. Current effective therapies for stroke recovery are limited to neurorehabilitation. Most stroke recovery occurs in a limited and early time window. Many of the mechanisms of spontaneous recovery after stroke parallel mechanisms of normal learning and memory. While various efforts are in place to identify potential drug targets, an emerging approach is to understand biological correlates between learning and stroke recovery. This review assesses parallels between biological changes at the molecular, structural, and functional levels during learning and recovery after stroke, with a focus on drug and cellular targets for therapeutics.
Governance of Eswatini Apparel Regional Value Chains and the Implications of Covid-19
Authors: Pasquali Giovanni , Godfrey Shane 
Published: March 2021

AbstractThere is a growing literature on the impact of Covid-19 on commercial and labour conditions at suppliers in apparel global value chains (GVCs). Yet much less is known about the implications for suppliers operating in regional value chains (RVCs) in the global South. In this article, we focus on Eswatini, which has grown to become the largest African manufacturer and exporter of apparel to the region. We draw on a combination of firm-level export data and interviews with stakeholders before and after the Covid-19 lockdown to shed light on the influence of private and public governance on suppliers’ economic and social upgrading and downgrading. We point to the coexistence of two separate private governance structures: the first characterised by direct contracts between South African retailers and large manufacturers (direct suppliers); the second operating through indirect purchasing via intermediaries from relatively smaller producers (indirect suppliers). While direct suppliers enjoyed higher levels of economic and social upgrading than indirect suppliers before Covid-19, the pandemic reinforced this division, with severe price cuts for indirect suppliers. Furthermore, while retailers provided some direct suppliers with support throughout the crisis, this was not the case for indirect suppliers, who remain comparatively more vulnerable. In terms of public governance, the negative consequences of the lockdown on firms’ income and workers’ livelihoods have been compounded by the state’s ineffective response. Our paper contributes to the research on RVCs in the global South, enhancing our understanding of how different governance structures and external shocks affect firms’ and workers’ upgrading and downgrading prospects.
Measuring the phase noise of Raman lasers with an atom-based method
Authors: Wang Yaning , Yan Shuhua , Xu Dongyang , Hu Mei , Li Qixue , Zhang Xu , Zhang Huankai , Lv Mengjie , Jia Aiai , Wang Guochao , Zhu Lingxiao , Yang Jun 
Published: March 2021

Phase noise of Raman lasers is a major source of noise for a Raman-type cold atom interferometer, which is traditionally measured using the signal source analyzer. We report here an atom-based method to measure the phase noise performance between two Raman lasers. By analyzing and calibrating the system noise sources, we can characterize the contribution of phase noise from the total deviation of the relative atom population at the middle of the interference fringe. Knowing the transfer function specified by the operation sequence of the interferometer, we can obtain the transfer function and power spectrum density of the phase noise term. By varying the time sequences of the interferometer, we can measure the white phase noise floor and the phase noise performance over a large range of Fourier frequencies from 1 to 100 000 Hz with a minor difference of 1 dB compared with results from the traditional method using a signal analyzer, which proves the validity of the atom-based method. Compared with the traditional measurement method, the atom-based method can have higher accuracy and have the ability of self-calibrating.
Upgrades and redesign of the National Ignition Facility’s soft x-ray opacity spectrometer (OpSpec)
Authors: Wallace M. S. , Heeter R. F. , Knight R. A. , Durand A. M. , Heinmiller J. M. , Lara R. B. , Max D. A. , Dutra E. C. , Huffman E. J. , Ayers J. , Emig J. A. , Archuleta T. N. , Urbatsch T. J. , Perry T. S. 
Published: March 2021

The soft x-ray Opacity Spectrometer (OpSpec) used on the National Ignition Facility (NIF) has recently incorporated an elliptically shaped crystal. The original OpSpec used two convex cylindrical crystals for time-integrated measurements of point-projection spectra from 540 to 2100 eV. However, with the convex geometry, the low-energy portion of the spectrum suffered from high backgrounds due to scattered x-rays as well as reflections from alternate crystal planes. An elliptically shaped crystal allows an acceptance aperture at the crossover focus between the crystal and the detector, which reduces background and eliminates nearly all reflections from alternate crystal planes. The current elliptical design is an improvement from the convex cylindrical design but has a usable energy range from 900 to 2100 eV. In addition, OpSpec is currently used on 18 NIF shots/year, in which both crystals are typically damaged beyond reuse, so efficient production of 36 crystals/year is required. Design efforts to improve the existing system focus on mounting reliability, reducing crystal strain to increase survivability between mounting and shot time, and extending the energy range of the instrument down to 520 eV. The elliptical design, results, and future options are presented.
Spatio-temporal heterogeneity in hippocampal metabolism in control and epilepsy conditions
Authors: Brancati Giulio E. , Rawas Chahinaz , Ghestem Antoine , Bernard Christophe , Ivanov Anton I. 
Published: March 2021

Significance
The dorsal part of the hippocampus is involved in spatial learning and memory processes, while the ventral is implicated in motivational and emotional behavior. These functions change during the night and day cycle, and they are altered in epilepsy. Here, we show that energy production (glycolysis versus oxidative phosphorylation) varies along the dorsoventral axis in a circadian manner ex vivo in control mice. These rules are altered in experimental epilepsy. Thus, energy production may be tailored to the function performed by hippocampal subdivisions and to the time of the day. Alterations in epilepsy may contribute to seizure generation and cognitive deficits.
Statistical evidence for the Proto-Indo-European-Euskarian hypothesis
Authors: Blevins Juliette , Sproat Richard 
Published: March 2021

AbstractBased on a new reconstruction of Proto-Basque, and regular sound correspondences between this Proto-Basque and Proto-Indo-European as standardly reconstructed,Blevins (2018)argues that Proto-Basque and Proto-Indo-European have a common ancestor that pre-dates the two proto-languages. Part of this argument is based on proposed Proto-Indo-European/Proto-Basque cognate sets that include basic vocabulary items. In this study we offer statistical support for Blevins’ conclusions by using a Monte Carlo simulation that allows us to estimate the probability that the proposed lexical correspondences could have arisen by chance. The method makes use of phonotactic language models to generate possible words in a pair of languages, and then attempts to discover consistent correspondences between the words, producing a list of possible “cognates”. The method differs from some previous approaches by considering matches between all segments in the word pairs. By running such a simulation a large number of times, we can estimate the probability that two languages with the given phonotactics could have produced the number of cognate pairs observed in the actual data. The method is independently assessed by comparing wordlists from 100 pairs of languages, related and unrelated, where relations are known. Our conclusion is that the proposed correspondences are unlikely to have arisen by chance, supporting a distant relationship between Proto-Basque as reconstructed byBlevins (2018)and Proto-Indo-European.
Welfare implications for dairy bull calves
Authors: Alley Mark L. , Smith Geof W. , Pairis-Garcia Monique D. , Wagner Brooklyn , Cramer Mary Caitlin 
Published: March 2021

AbstractDairy bull calves may experience compromised welfare as a result of production practices and management techniques implemented on farm. This includes high disease incidence due to poor ventilation, pain experienced as a by-product of processing procedures, social isolation, and hunger from inappropriate nutrition. Although dairy heifer calves may experience similar issues, these conditions are often exacerbated for dairy bull calves due to the low economic value of the individual animal. In addition, given the bull calf will likely not remain on the farm, this group of animals are more likely to receive less adequate care in the first weeks of life. Welfare issues such as increased rates of dystocia, failure of passive transport, dehorning, castration, and long transportation distances are all critical and will be discussed in this review. Therefore, the objectives of this article are to (1) evaluate current welfare concerns specific to dairy bull calves, (2) identify areas for improvement to mitigate poor welfare outcomes, and (3) review proper euthanasia techniques and protocols specific for calves. Ultimately there is still much to learn about specific areas for improvement relating to the welfare of dairy bull calves and future studies are needed. However, the industry should properly manage the welfare challenges of bull calves, identify opportunities within the industry to increase their value, and uphold our ethical responsibility to these animals.
Root pruning - a growth regulation practice in fruit crops
Authors: Mathiyazhagan Kavino , Subash Mani , Bose Chandra 
Published: March 2021

Abstract
Root pruning is a horticultural practice from ages ago that has potential benefits on tree crop growth regulation and production. It is followed in orchards as a growth control mechanism of vigorously growing fruit trees. The growth regulation in trees is brought about by many physiological mechanisms involving water stress and assimilates partitioning to maintain the root: shoot equilibrium. Root pruning of structural roots increases the function and efficiency of functional roots in trees. It is widely practiced in transplanting of saplings which ensures better establishment. Time and selection of the distance from the trunk by root pruning may play an important role not only on vigour control but also on vegetative response and flower induction, fruit set; hence, they should be addressed as well. However, it will require additional experience, horticultural insight and better understanding of the physiological basis of the technique. It favours the large-scale adoption of root pruning in perennial fruit crops under high-density planting system in order to regulate the canopy size and regular bearing.
Tobacco dependence and motivation to quit smoking: an identity-based framework (Adicción al tabaco y motivación para dejar de fumar: una perspectiva identitaria)
Authors: Blondé Jérôme , Falomir-Pichastor Juan-Manuel 
Published: March 2021

Literature has extensively shown that tobacco dependence is negatively associated with motivation to quit smoking. In this research, we aimed to account for this negative relationship by adopting an identity-based framework. More specifically, we hypothesized that tobacco dependence constitutes an identity threat that smokers seek to manage by diminishing their motivation to quit. To assess whether such a mechanism is at work, we used a self-affirmation manipulation across two independent studies that were pooled into one ( N = 308). More specifically, we asked daily smokers to report their tobacco dependence prior to manipulating self-affirmation. Then, we assessed their motivation to quit. Results demonstrated that, among high-dependent smokers, those who were self-affirmed reported higher motivation to quit than those who were not. Self-affirmation had no effect among low-dependent smokers. These findings illuminate the idea that an interpretation in terms of identity processes can offer new insights into understanding tobacco dependence and its consequences on smokers’ motivation to quit.