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The total/partial oil change treatment can affect the furfural partitioning in oil-paper-pressboard insulation, resulting in poor accuracy of furfural analysis. Moreover, due to the high cost of total oil change, partial oil change is more practical during transformer operation. This paper investigates the furfural partitioning in the oil-paper-pressboard insulation under partial oil change conditions. First, the initial furfural partitioning equation with non-oil change is proposed based on the obtained furfural content in oil, paper, and pressboard. Then, the modified furfural partitioning model under partial oil change condition is established by introducing a correction factor. Moreover, a preliminary correction scheme for the furfural partitioning model considering the influence of moisture and acid is provided. Finally, furfural content in oil-Kraft paper and oil-thermally upgraded Kraft (TUK) paper insulation are discussed, and results indicate that the proposed modified furfural partitioning model is not suitable for the oil-TUK paper insulation. This work can provide theoretical support for furfural analysis of oil-immersed transformers. [ABSTRACT FROM AUTHOR]

Promoting a wider range of contribution types can facilitate healthy growth of the visualization community, while increasing the intellectual diversity of visualization research papers. In this paper, we discuss the importance of contribution types and summarize contribution types that can be meaningful in visualization research. We also propose several concrete next steps we can and should take to ensure a successful launch of the contribution types. [ABSTRACT FROM AUTHOR]

Thermal aging of insulation paper occurs during transformer operation, with the water produced during aging accelerating the thermal aging process. Insulation paper aging largely determines the operational life of a transformer pressboard; accordingly, research pertaining to insulation paper enhancement is significant with respect to the functional safety of transformers. Within molecular research, particularly that focusing on molecular simulation, appropriate force field selection is paramount in order to acquire accurate results, in addition to appropriately reflecting cellulose thermal stability and associated degradation mechanisms. In the current study, two diverse cellulose models (water only; water, dicyandiamide, melamine and polyacrylamide) are developed and analyzed. Numerous model variables, including the diffusion coefficient of water and cellulose chain distance, are collated, in order to examine the effects of amines on the thermal stability of cellulose. Additionally, a novel insulation paper is formulated by combining traditional insulation paper with three diverse amines; an accelerated aging experiment is thus undertaken, comparing traditional and modified insulation paper samples at 110 °C, together with periodic assessment of both microwater content and the degree of polymerization (DP). Results indicate that during transformer operation, a higher degree of elasticity is associated with the modified insulation paper, thus significantly increasing its toughness and extensibility, in parallel with decreasing it brittleness. Results also show that the DP associated with cellulose comprising the modified insulation paper decreases at a reduced rate, with measured water content significantly less than that of traditional insulation paper. Simulation results are consistent with experimental findings. Therefore, it may be concluded that the thermal aging properties of cellulose significantly improve upon addition of dicyandiamide, melamine, and polyacrylamide as thermal stabilizers. [ABSTRACT FROM AUTHOR]

This paper presents a modeling practical works project of electrical engineering, proposed to the first-year students of the University Institute of Technology in France, during the COVID-19 pandemic. The objective of this paper is twofold. The first objective is to present to the students the opportunities of modeling and calculation development of a spreadsheet software in their professional lives. The second objective is to create a file that automatically calculates all the current and voltage values at each point of any alternative electrical circuit. The aim of this paper, geared toward students, is to bring them to build their own numerical remote lab, autonomously. Therefore, pedagogical keys are given along the reading of this document to help them to progress, both on electrical circuits conceptual understanding with series and parallel RLC circuits and on their computation in a spreadsheet software. As a conclusion, this paper can be used as a base to develop remote modeling practical works of many and different devices, as well as a database starting point of such analytical models. [ABSTRACT FROM AUTHOR]

Transformer oil and insulation paper are subject to the combined effects of the electric field and temperature operations, which significantly impact insulation deterioration. This article designs a comparative test of the electro-thermal combined aging to obtain several characteristic parameters for the aging degree of oil-pressboard insulation. Molecular dynamics are used to establish a mixed molecular model of oil-pressboard insulation to simulate the pyrolysis reactions at high temperatures using the ReaxFF force field. The microscopic effects of the electric field on the aging of oil-pressboard insulation are studied. The rationale of the simulation model is verified from experimental results, and the trend of the reactants and products in the reaction process was considered to determine the influence mechanism of electric–thermal coupling on oil-pressboard insulation. The experimental results show that thermal stress remains the most important factor toward cracking in insulation paper. The acid value and furfural formation rate in oil increase, and the polymerization degree of the insulation paper decreases rapidly after the combined electric and thermal aging. In addition, the molecular dynamics simulations show that pyrolysis increases the bond energy, promotes repulsion between atoms, and leads to fractured bonds. The addition of the electric field increases the susceptibility of the chemical bonds in cellulose molecules to breakage. The morphology of the cellulose chain then changes, and the diffusion of small molecules intensifies. This study reveals the mechanism of insulation aging under electro-thermal coupling through combined macroscopic testing and molecular dynamics simulations. [ABSTRACT FROM AUTHOR]

In recent years, multilayer networks have served as effective models for addressing and analyzing real-world systems with multiple relationships. Among these scenarios, the community detection (CD) problem is one of the most prominent research hotspots. Although some research on multilayer network CD (MCD) has been proposed to address this problem, most studies focus only on topological structures. Therefore, their algorithms cannot extract the most out of complementary network information, such as node similarities and low-rank features, which may lead to unsatisfactory accuracy. To tackle this problem, this paper proposes a novel multi-objective evolutionary algorithm based on consensus prior information (MOEA-CPI). The proposed algorithm takes full advantage of prior information to guide the MOEA with respect to topological structures, initializations, and the optimization process. More specifically, this paper first extracts two kinds of prior information, i.e., graph-level and node-level information, based on Node2vec and Jaccard similarity, respectively. Then, the prior layer and a high-quality initial population are constructed on the basis of the graph-level information. During the optimization process, the genetic operator, which integrates the weighting strategy and node-level information, is applied to guide the algorithm to distribute similar nodes into the same community. Extensive experiments are implemented to prove the superior performance of MOEA-CPI over the state-of-the-art methods. [ABSTRACT FROM AUTHOR]

This paper offers a comprehensive overview of the IEEE Transactions on Engineering Management (IEEE TEM) from 1985 to 2017. This paper employs a mixed-method examination based on an in-depth interview with the new editor-in-chief regarding the challenges for the future of IEEE TEM, along with a bibliometric analysis of the journal. By using Web of Science Core Collection data, the analysis maps the knowledge produced and disseminated by IEEE TEM, revealing the most cited papers, the most frequently occurring keywords and the interconnection between them, the most prolific authors and their coauthorship network, and the most prolific countries for published articles. This paper also shows the main avenues of research covered by IEEE TEM and their evolution through the analysis of the correlation of keywords. This paper offers an example application of a mixed-method bibliometric analysis, seeking to extend the quantitative findings by including other sources of data. [ABSTRACT FROM AUTHOR]

In a series of papers by Pawlikowski and his team, they warned about a deep crisis of credibility in simulation studies for the performance evaluation of telecommunication networks. The goal of this article is to revisit the investigation on simulation credibility and to extend the previous research in this area by presenting the results of a comprehensive survey of over 8370 IEEE publications (2007?2009) on telecommunication networks which appeared in the proceedings of IEEE Transactions on Communications (TC), IEEE/ACM Transactions on Networking (TN), IEEE Infocom, IEEE ICC, and IEEE Globecom. These proceedings were selected based on their popularity and relevance to our study. Besides simulation credibility, we also report on the commonly used simulation tools and performance analysis methodology adopted by the authors of the surveyed papers. Our findings show that a significant number of authors did not provide information of the simulation tools used or, even when they did, there was not enough information about the CI or SE of simulation results presented in the surveyed papers. Thus, there is no significant change with respect to quality and credibility of the simulation studies revised and the deep crisis of credibility still remains. The research design most authors prefer is a hybrid one where both simulation and analytic methods are being used for network performance analysis. Finally, we provide guidelines for the best practice of using simulation tools for the performance evaluation of telecommunication networks. [ABSTRACT FROM PUBLISHER]

The papers in this special section focus on modeling and simulation in disaster and emergency management. The COVID-19 pandemic of 2020 has wrought damage globally to a degree that is totally unprecedented in human history.Within three months that the first known death from the illness caused by the so-called novel Coronavirus was reported by state media in China on the 11th of January 2020, close to 1.8 million people worldwide had tested positive, with more than 100,000 deaths reported. By the time the pandemic will have been declared to be under control, millions more are expected to have been infected and tens (possibly hundreds) of thousands more will have perished as a result of the disease. Not only are the numbers of COVID-19 infected people and deaths staggering. Economies throughout the world have suffered tremendously, with many companies forced to shut down, or at the very least significantly scale down, their production of goods and services as a result of the need for social distancing and self-isolation required to prevent the unmitigated transmission of the disease. All this has led to hundreds of millions worldwide losing their employment or other sources of livelihood. Governments of all nations, large and small, developed and underdeveloped, have needed to pump into their economy and onto their struggling citizens whatever financial resources they could manage to generate. [ABSTRACT FROM AUTHOR]

The first part of this paper presented mymargin the device-level comparison of emerging materials (In0.53Ga0.47As and 2-D materials) and device architecture (NW FETs) with s-Si FinFETs. In order to further understand the performance and energy efficiency of these device options for future technology nodes, it is required to go beyond the device-level comparison by accounting for not only intrinsic but also the extrinsic parasitic elements. In this paper, we present the comparison of s-Si, In0.53Ga0.47As, and 2-D material-based n-type MOSFETs using the circuit-level figure of merits across three successive future technology nodes. The analysis incorporates both device characteristics obtained from an advanced quantum mechanical simulation tool and circuit-level comparison, which accounts for device parasitic elements and wiring load. The results show that 2-D material DG MOSFETs present a more energy-efficient device option than s-Si and In0.53Ga0.47As FinFETs in sub-0.7-V supply voltage regime and In0.53Ga0.47As nanowire (NW) FETs can outperform s-Si multi-gate (MuG) FETs and 2-D material FETs, but when considering non-idealities, s-Si NW FETs remain both faster and more energy-efficient device option. [ABSTRACT FROM AUTHOR]

The impedance expansion method (IEM), which has been previously proposed by the authors of this paper, is a circuit modeling technique for electrically very small devices. This paper describes a circuit modeling procedure that utilizes the IEM and eigenmode analysis for a wireless power transfer system. First, a multimode circuit model that can represent the higher order resonances in a broadband frequency range is presented. Subsequently, a single-mode circuit model—consisting only of passive elements—that can represent both the radiated and conduction loss powers at approximately its operating frequency band is presented. [ABSTRACT FROM AUTHOR]

This paper presents a systematic literature review of learning analytics dashboards (LADs) research that reports empirical findings to assess the impact on learning and teaching. Several previous literature reviews identified self-regulated learning as a primary focus of LADs. However, there has been much less understanding how learning analytics are grounded in the literature on self-regulated learning and how self-regulated learning is supported. To address this limitation, this review analyzed the existing empirical studies on LADs based on the well-known model of self-regulated learning proposed by Winne and Hadwin. The results show that existing LADs are rarely grounded in learning theory, cannot be suggested to support metacognition, do not offer any information about effective learning tactics and strategies, and have significant limitations in how their evaluation is conducted and reported. Based on the findings of the study and through the synthesis of the literature, the paper proposes that future research and development should not make any a priori design decisions about representation of data and analytic results in learning analytics systems such as LADs. To formalize this proposal, the paper defines the model for user-centered learning analytics systems (MULAS). The MULAS consists of the four dimensions that are cyclically and recursively interconnected including: theory, design, feedback, and evaluation. [ABSTRACT FROM AUTHOR]

Enhancing power electronics (PE) converter reliability is crucial for ensuring a reliable operation of current and future operating Wind Turbines (WTs). Achieving high reliability of variable speed WT PE systems requires careful consideration of their operation, and particularly their thermal cycling. This paper presents a methodology for evaluating and reconsidering operational strategies of WTs with relation to the thermal loading and lifetime consumption of the converter. The methodology is applied to compare control strategies for the WT generator and evaluate their impact on the converter reliability by observation of the thermal cycles and by calculating the resultant lifetime consumption of those stress cycles. The thermal stress on both the Machine Side Converter (MSC) and the Grid Side Converter (GSC) is examined and compared. It is shown that the least reliable of the three evaluated control strategies is the one that tracks the power curve below rated speed most closely. This paper suggests that dynamic transients associated with the WT control largely influence the IGBT module wear-out and their modelling needs to be prioritized for lifetime studies. These dynamic transients are captured by the improved model whose value is confirmed for the comparisons in the case study of the paper. [ABSTRACT FROM AUTHOR]

Cross-laminated timber (CLT) buildings are constructed by connecting CLT panels with dowel-type fasteners and mechanical anchors, which govern the lateral behavior of these structures. Although these connections are mostly distributed along the perimeter of the CLT panels, creating highly redundant structures, previous research on the lateral behavior of CLT structures has mainly focused on the behavior of the connections placed at the base of the CLT shear walls, such as hold downs and angle brackets, while limited attention has been paid to the connections between perpendicular walls and their effect on the lateral response of CLT shear walls. This paper presents a comprehensive experimental study aimed at investigating the effects of the interaction between perpendicular walls on the lateral response of CLT shear walls. CLT shear walls with three different aspect ratios were analyzed by means of monotonic and cyclic tests, both in single wall configuration and connected to perpendicular walls. The experimental findings demonstrate that the structural interaction due to the perpendicular walls significantly affects the lateral response of a CLT shear wall, resulting in increased lateral stiffness, lateral capacity, and deformation capacity. In addition, the study presents two analytical models for the prediction of the lateral stiffness and the lateral capacity of CLT shear walls connected to perpendicular walls. The analytical models were validated based on the experimental results, showing reasonable agreement. [ABSTRACT FROM AUTHOR]

This paper analytically examines how the condition of weak grid connection affects the torsional sub-synchronous oscillations (SSOs) induced by a grid-connected DFIG in a power system. The examination focuses on the SSO mode of grid-connected DFIG, which is dominated by the phase locked loop (PLL) or DC voltage control. Theoretical analysis is carried out to prove that the condition of weak grid connection amplifies the impact of modal resonance between the DFIG and torsional dynamics of synchronous generators. The amplifying effect of weak grid connection exhibits as the decrease of damping of SSO mode of DFIG and increase of the associated residue when the grid connection weakens. Consequently, the DFIG is more likely to induce torsional SSOs under the condition of weak grid connection, leading to system instability in the worst case. Analytical examination presented in the paper reveals the mechanism about how the condition of weak grid connection plays a key role for the DFIG to induce the torsional SSOs. An example multi-machine power system with the grid-connected DFIG is presented. Results of modal analysis and non-linear simulation using detailed model of DFIG validate the analysis and conclusions made in the paper. [ABSTRACT FROM AUTHOR]

This paper proposes an approach to determine the participation of algebraic variables in power system modes. The approach is based on a new interpretation of the classical participation factors, as well as on the definition of adequate output variables of the system's state-space representation. The paper considers both the linear and generalized eigenvalue problems for the calculation of the participation factors and presents a theorem to cope with eigenvalue multiplicities. An illustrative example on the two-area system, as well as a study on a 1479-bus dynamic model of the all-Irish transmission system are carried out to support the theory and illustrate the features of the proposed approach. [ABSTRACT FROM AUTHOR]

An increasing need for fast and reliable models has led to a continuous development of Fourier-based (FB) analytical modeling. This paper presents an overview of the techniques that are currently available in FB modeling for electric machines. By coupling that overview to the most relevant literature related to the subject, an interesting starting point is provided for anyone who wants to use or improve FB models. The following seven aspects of FB models are discussed in detail: 1) the magnetic potential (scalar or vector potential); 2) the coordinate system and the solution of the partial-differential equations for each magnetic potential and for each coordinate system; 3) the way in which time dependence is accounted for; 4) the implementation of the source terms; 5) the possibilities to account for slotted structures; 6) the modeling of eccentricity; and 7) the post-processing computation of physical quantities, such as flux density, electromotive force, torque, losses, and eddy currents in conductive objects. Furthermore, this paper gives the closed form solution of the Laplace, Poisson, and Helmholtz equations in each coordinate system. In addition, this paper tackles other important features of FB models such as computational time reduction and coupling the machine model to an electric circuit. [ABSTRACT FROM AUTHOR]

Background: The accurate prediction of where faults are likely to occur in code can help direct test effort, reduce costs, and improve the quality of software. Objective: We investigate how the context of models, the independent variables used, and the modeling techniques applied influence the performance of fault prediction models. Method: We used a systematic literature review to identify 208 fault prediction studies published from January 2000 to December 2010. We synthesize the quantitative and qualitative results of 36 studies which report sufficient contextual and methodological information according to the criteria we develop and apply. Results: The models that perform well tend to be based on simple modeling techniques such as Naive Bayes or Logistic Regression. Combinations of independent variables have been used by models that perform well. Feature selection has been applied to these combinations when models are performing particularly well. Conclusion: The methodology used to build models seems to be influential to predictive performance. Although there are a set of fault prediction studies in which confidence is possible, more studies are needed that use a reliable methodology and which report their context, methodology, and performance comprehensively. [ABSTRACT FROM AUTHOR]

Multimodal sentiment analysis aims to extract and integrate information from different modalities to accurately identify the sentiment expressed in multimodal data. How to effectively capture the relevant information within a specific modality and how to fully exploit the complementary information among multiple modalities are two major challenges in multimodal sentiment analysis. Traditional approaches fail to obtain the global contextual information of long time-series data when extracting unimodal temporal features, and they usually fuse the features from multiple modalities with the same method and ignore the correlation between different modalities when modeling inter-modal interactions. In this paper, we first propose an Attentional Temporal Convolutional Network (ATCN) to extract unimodal temporal features for enhancing the feature representation ability, then introduce a Multi-layer Feature Fusion (MFF) model to improve the effectiveness of multimodal fusion, which fuses the different-level features by different methods according to the correlation coefficient between the features, and cross-modal multi-head attention is used to fully explore the potential relationship between the low-level features. The experimental results on SIMS and CMU-MOSI datasets show that the proposed model achieves superior performance on sentiment analysis tasks compared to state-of-the-art baselines. [ABSTRACT FROM AUTHOR]

Emotion recognition is a key attribute for artificial intelligence systems that need to naturally interact with humans. However, the task definition is still an open problem due to the inherent ambiguity of emotions. In this paper, a novel Bayesian training loss based on per-utterance Dirichlet prior distributions is proposed for verbal emotion recognition, which models the uncertainty in one-hot labels created when human annotators assign the same utterance to different emotion classes. An additional metric is used to evaluate the performance by detecting test utterances with high labelling uncertainty. This removes a major limitation that emotion classification systems only consider utterances with labels where the majority of annotators agree on the emotion class. Furthermore, a frequentist approach is studied to leverage the continuous-valued “soft” labels obtained by averaging the one-hot labels. We propose a two-branch model structure for emotion classification on a per-utterance basis, which achieves state-of-the-art classification results on the widely used IEMOCAP dataset. Based on this, uncertainty estimation experiments were performed. The best performance in terms of the area under the precision-recall curve when detecting utterances with high uncertainty was achieved by interpolating the Bayesian training loss with the Kullback-Leibler divergence training loss for the soft labels. The generality of the proposed approach was verified using the MSP-Podcast dataset which yielded the same pattern of results. [ABSTRACT FROM AUTHOR]

As the inverter-based generation replaces the conventional synchronous generators, it may also need to fill in the missing ancillary service support. One of these ancillary services is dynamic reactive power provision and voltage control. This paper analyzes optimal strategy of reactive and active fault-current support of the inverter-based generation leading to fast voltage recovery of the system. For the purpose of the analysis, new ramping active current controller able to emulate different behavior of active current injection is proposed. By optimizing its parameters for different case studies of the system, the conclusions about optimal behavior of the inverter based generation with respect to system parameters and operating conditions are drawn. It is observed that the optimal combination of active and reactive fault-current is the most sensitive to the dynamic load component penetration levels in the system. With the increasing penetration levels, the significance of active fault-current injection increases. The results show that with higher penetration levels of dynamic load component in the heavy load areas, the ramping down of the inverter-based generation active fault-current results in slower voltage recovery of the system. Following this conclusion, a recommendation on update of current European grid codes is proposed. [ABSTRACT FROM AUTHOR]

In wideband radar system testing and performance evaluation, target echo simulation should simultaneously meet real-time and high-precision requirements. In this paper, we focus on the wideband linear frequency modulated (LFM) radar signal, derive the echo signal time-domain analytical expression based on the multiscattering center model and propose a high-precision real-time echo simulation calculation method. Regarding the low model reliability and poor versatility problems in the current wideband radar target calculation, the analytical model proposed here truly reflects the inner-pulse modulation characteristics of the radar transmit signal and the wideband electromagnetic scattering characteristics of the target. Current wideband radar target signal calculation accuracy and real-time performance are also difficult to balance. Considering this problem, the wideband radar target echo analytical model proposed in this paper avoids the large amount of calculations required for the full numerical calculation and effectively improves the calculation accuracy and real-time performance of wideband radar target echo signal calculations without reducing calculation accuracy. The real-time calculation method involves elaborate amplitude-phase control. Simulation analysis and experimental verification confirmed the reliability and validity of these results. These research results have important theoretical significance and practical application value in the field of hardware-in-the-loop simulation. [ABSTRACT FROM AUTHOR]

This paper addresses the frequency oscillation problem in a parallel-inverter-based grid-connected system. Angular frequency interactions between inverters and the grid exhibit various numbers of complicated characteristics that seriously threaten the connected power system's stable operation. This paper proposes a unified frequency oscillation method analysis to investigate the oscillation problem in a multi-VSG grid-connected system. In this method, the power control model of each grid-connected inverter is equivalent to a two-terminal network by analogy method, which can be described as a “current source” connected in parallel with a reciprocal of “admittance” and then joined in series with a joint of “admittance.” Next, considering the influence of grid impedance, the model of the whole grid-connected system is established to reveal the mechanism of multi-VSG angular frequency oscillation. Subsequently, the influence factors of frequency oscillation and its variation law are analyzed through transfer functions, which provide an essential theoretical method for solving the frequency oscillation problem in the current multi-inverter grid-connected engineering application. Finally, we validate the effectiveness and correctness of the small-signal model and the frequency oscillation characteristics by building the MATLAB/Simulink simulation. [ABSTRACT FROM AUTHOR]

The Cox proportional hazards model is a popular semi-parametric model for survival analysis. In this paper, we aim at developing a federated algorithm for the Cox proportional hazards model over vertically partitioned data (i.e., data from the same patient are stored at different institutions). We propose a novel algorithm, namely VERTICOX, to obtain the global model parameters in a distributed fashion based on the Alternating Direction Method of Multipliers (ADMM) framework. The proposed model computes intermediary statistics and exchanges them to calculate the global model without collecting individual patient-level data. We demonstrate that our algorithm achieves equivalent accuracy for the estimation of model parameters and statistics to that of its centralized realization. The proposed algorithm converges linearly under the ADMM framework. Its computational complexity and communication costs are polynomially and linearly associated with the number of subjects, respectively. Experimental results show that VERTICOX can achieve accurate model parameter estimation to support federated survival analysis over vertically distributed data by saving bandwidth and avoiding exchange of information about individual patients. The source code for VERTICOX is available at: https://github.com/daiwenrui/VERTICOX. [ABSTRACT FROM AUTHOR]

To research the impact of temperature-dependent characteristics of windings and magnets on the electromagnetic power loss and thermal properties of high-speed (HS) interior permanent magnet synchronous machines (PMSMs), an electromagnetic-thermal bi-directional coupling method (BDCM) is proposed for water-cooled HS PMSMs considering the assembling gaps between the motor components in this paper. The electromagnetic power loss is calculated by 3-D transient finite-element method and loaded into the 3-D temperature field according to the actual loss distribution, and the materials’ properties are in turn updated according to the temperature distributions. The loss and temperature calculation results of a 15kW HS amorphous metal PMSM are calculated by two different coupling methods in the conditions of the rated-load sinusoidal supply and converter supply, and compared with the measured results in the case of converter supply. The results obtained by the BDCM are more consistent with the experiment results, verifying the superiority of the proposed analyzing method in improving the calculation accuracy of motor loss and temperature rise. In addition, the applicable conditions of the proposed method are also summarized in the paper. [ABSTRACT FROM AUTHOR]

Sentiment Quantification aims to detect the overall sentiment polarity of users from a set of reviews corresponding to a target. Existing methods equally treat and aggregate individual reviews’ sentiment to judge the overall sentiment polarity. However, the confidence of each review is not equal in sentiment quantification where sentiment perturbation arising from high- and low-confidence reviews may degrade the accuracy of Sentiment Quantification. Specifically, fake reviews with deceptive sentiments are low confidence, which perturbs the overall sentiment prediction. Whereas, some reviews generated by responsible users are high confidence. They contain authoritative suggestions so they should be emphasized in Sentiment Quantification. In this paper, we design and build COSE, a confidence-aware sentiment quantification framework, which can measure the confidence of individual reviews to eliminate sentiment perturbation and facilitate sentiment quantification. We design a Review Graph that achieves review confidence modeling in an unsupervised manner and obtains review confidence representations. Moreover, we develop a dynamic fusion attention mechanism, which produces sentiment “de-perturbation” vectors to eliminate the sentiment perturbation based on the confidence representations. Extensive experiments on large-scale review datasets validate the significant superiority of COSE over the state-of-the-art. [ABSTRACT FROM AUTHOR]

The mining method that is still often used in salt deposits is the room-and-pillar mining method, in which the dimensioning of the most requested element in the system is followed. The pillars are the elements subjected to the greatest loads. Knowing the size and distribution mode of the secondary state of stress—deformation—is a necessity that can lead to the design and realization of stable, reliable underground excavations. This paper proposes an analytical assessment model of the secondary stress state in the pillars between the operating rooms, as well as in the whole system room–pillar–floor, based on the results obtained from laboratory research through modeling and in situ research. For this purpose, the evaluation of the secondary stress state was carried out considering the following methods: (1) the dimensioning method based on the theory of limit equilibrium, taking into account the effective stress in the pillars; and (2) the mechanics of the continuous environment based on the design of some analytical models for evaluating the secondary stress-deformation state in the pillar and floor. The exploitation of one of the largest salt deposits in Romania is used as a case study, and the stability of the exploitation system with rooms and pillars is evaluated by analytical methods. The secondary state of tension was calculated at different points on the height of the pillar. Through the proposed algorithm, the value of the axial component of the secondary stress state at different points along the axis of a pillar located at a depth of 100 m varies between 1.498 and 1.657 MPa, compared to the value obtained by the finite element method and in situ measurements, which was 1.64 MPa. The comparison revealed a high degree of agreement between the results obtained for the depth of 100 m using both the FEM and laboratory and in situ measurements. This suggests that the proposed algorithm is a reliable method for predicting the secondary stress state. The presented algorithm can be extended in the field of mining deposits, where mining methods with rooms and pillars are used. [ABSTRACT FROM AUTHOR]

A group of geographically dispersed and logically collaborated emergency organizations are involved when emergency occurs. Two challenging issues are a reasonable emergency resource allocation mechanism and an efficient resource conflict checking and resolution control mechanism to ensure the conflict-free execution of global cross-organization emergency response processes. To address them, this paper proposes an approach to support emergency resource management including both intraorganization private resource management and cross-organization public resource management. The former has been fully discussed in our previous work using E-net. To cope with the latter, this paper presents a novel type of Petri net that is extended with both time and resource factors to model cross-organization emergency response processes. Then, according to the resource requirement analysis, their worst, delayed, and best cases are obtained. Next, emergency resource conflict checking and four conflict resolution strategies are proposed to resolve the detected resource conflicts for the delayed execution case. This paper shows how to use different resolution strategies to construct the conflict-free model by designing corresponding resolution controllers. Finally, their performance is evaluated by a fire emergency response example. [ABSTRACT FROM AUTHOR]

This paper presents insights into the tradeoffs that exist when balancing charge and temperature within a lithium-ion battery pack. Both charge imbalance and temperature imbalance can harm battery pack performance—the former limits the charge/discharge capabilities of the pack, and the latter is known to accelerate battery pack aging. The literature proposes the manipulation of balancing current, normally reserved for charge or voltage balancing, to additionally reduce temperature heterogeneity. The goal is to limit both charge and temperature imbalance simultaneously, as balancing one may increase imbalance of the other. A noticeable gap in the literature, one this paper seeks to address, is the lack of a more formal understanding of the tradeoffs between charge and temperature imbalance. This paper uses a formal framework to obtain insights regarding the cases of balancing neither charge nor temperature, balancing charge, and balancing temperature. This allows for the determination of different factors that describe how balancing one state impacts the other, as well as the discovery that temperature balancing can be improved through the control of the average pack current. A model predictive control scheme is used to determine balancing current and validate these insights for a variety of scenarios. [ABSTRACT FROM AUTHOR]

In this paper, an analytical model has been developed to observe the recombination losses involved in a tunnel oxide passivated contact solar cell with a carrier-selective layer constituting polycrystalline silicon (poly-Si). The main focus of this paper is to observe the contribution of each component of recombination current density and its effect on open-circuit voltage, Voc. The effect of emitter saturation current density (Joe), surface recombination velocity, substrate thickness, and doping density of carrier-selective layer on Voc has been presented. The analysis indicates that Voc = 766 mV can be achieved for Joe = 2 fA/cm2, and a doping density of poly-Si > 1021cm−3 in a c-Si/SiO2/poly-Si contact for a 50- $\mu \text{m}$ -thick substrate in case of ideal surface passivation. For identical conditions, Voc attains a lower value of 750mV for a 180- $\mu \text{m}$ -thick substrate. The dependence of Voc on bandgap of tunnel layers has also been observed by considering other materials like Si3N4 and SiC. These results from the analyticalmodel have been compared with results froma simulation using automat FOR simulation of HETerostructures v2.5 and have been found to be in good agreement with each other. [ABSTRACT FROM AUTHOR]

Ranking and selection (R&S) procedures are powerful tools to enhance the efficiency of simulation-based optimization. In this paper, we consider the R&S problem subject to stochastic constraints and seek to improve the selection efficiency by incorporating the information from across the domain into quadratic regression metamodels. To better fulfill the quadratic assumption of the regression metamodel used in this paper, we divide the solution space into adjacent partitions such that the underlying functions of both the objective and constraint measures in each partition are approximately quadratic with homogeneous noise. Using the large deviations theory, we characterize the asymptotically optimal allocation rule by maximizing the rate at which the probability of false selection tends to zero. Numerical experiments demonstrate that our approach dramatically improves the selection efficiency by 50%–90% on some typical selection examples compared with the existing approaches. Note to Practitioners—Simulation is widely used for designing and analyzing complex discrete-event systems such as manufacturing production systems, transportation systems, and supply chain operations. However, efficiency is still a significant concern when using simulation for stochastic optimization problems, especially in the presence of stochastic constraints. This paper was motivated by the problem of selecting the best feasible design (solution) from a finite set of alternatives given anobjective and stochastic constraints, where the performances of the objective and constraint measures can be estimated via simulation. Different from the existing approaches in the literature, in this paper, we propose a new R&S procedure using regression metamodels. Given a fixed amount of computing budget, our approach determines the asymptotic optimal number of simulation replications for each design. It can be shown through numerical experiments that the proposed approach can significantly improve the selection efficiency by more than 50% over the existing methods on some typical benchmark examples. [ABSTRACT FROM AUTHOR]

Modern complexities associated with an arterial traffic makes existing safety prediction methods insufficient to meet desired standards required by recent developmental needs. This paper proposes an enhanced active safety prediction method based on big-data approach and Stacked AutoEncoder-Gated Recurrent Unit. Firstly, the big-data technology is used to construct a dynamic identification model to recognize real-time operation state and risk state. Secondly, the Stacked AutoEncoder-Gated Recurrent Unit is used to predict a level of safety based on associated recognition results. This paper uses data from working days of Sunset Boulevard, California, from January $1^{\mathrm{st}}$ , 2020, to February $28^{\mathrm{th}}$ , 2020. The results of analysis show that the accuracy of the proposed dynamic recognition model reaches 98.92%, which is better than existing models such as random forest, K-nearest neighbor, and naïve Bayes models. In addition, it is found that the Stacked AutoEncoder-Gated Recurrent Unit can achieve a prediction accuracy of 95.157% and has significant advantages in terms of efficiency. The proposed methods will provide feasible solutions for actively monitoring safety levels. [ABSTRACT FROM AUTHOR]

Bridges play an important role in transportation infrastructure systems. Intelligent and digital management of bridges group is an essential part of the future intelligent transportation infrastructure system. This paper proposes a digital twin system for bridges group in the regional transportation infrastructure network, which is interconnected by measured traffic loads. In physical space, a full-bridge traffic load monitoring system based on information fusion of weigh-in-motion (WIM) and multi-source heterogeneous machine vision is set up on the target bridge to measure traffic loads, also lightweight sensors are employed on the bridges group for structural response information. Furthermore, by establishing mechanical analysis models in the corresponding digital space and using the measured traffic loads as links, the working condition perception and safety warning of all bridges in the regional transportation network is achieved, forming an important support for further intelligent transportation infrastructure system. The proposed digital twin system has been preliminarily implemented in a bridges group around Shanghai, China, demonstrating the feasibility of the technical framework proposed in this paper and the bright prospects. [ABSTRACT FROM AUTHOR]

To achieve higher throughputs in cellular networks, 3GPP proposes to use unlicensed frequency bands and develops technologies — the latest one is NR-U — allowing a cellular base station to transmit in unlicensed bands, which are already occupied by Wi-Fi networks. To enable fair channel sharing between two technologies, the base station uses a sort of CSMA/CA with binary exponential backoff similar to Wi-Fi. However, the base station can start data transmission only at strictly periodic time moments. Many papers propose sending a reservation signal between the end of the backoff procedure and such a moment to prevent nearby devices from accessing the channel. However, this approach significantly reduces Wi-Fi performance. The paper proposes a novel method CR-LBT of transmitting a reservation signal that greatly decreases channel resource waste caused by collisions and improves channel resource sharing fairness. With developed analytical models and simulations, it is shown that CR-LBT may simultaneously increase the throughput of both NR-U and Wi-Fi networks. The effect is more noticeable for the Wi-Fi network, the throughput of which may rise three times compared with the traditional method of sending the reservation signal. Finally, the influence of various factors on CR-LBT performance is studied. [ABSTRACT FROM AUTHOR]

In this paper, the boundary discretization method is used to improve the traditional subdomain model. The improved model can be used to calculate the magnetic field distribution in the region containing non-orthogonal boundary, avoiding the influence of the simplified stator slot or permanent magnet shape on the results in calculating the motor magnetic field using the traditional subdomain model. In addition, the improved subdomain model can also be used to calculate the air-gap flux density when the rotor is eccentric, instead of segmenting the air-gap to an equivalent state without eccentricity. The calculation object of this paper is a surface-mount permanent magnet motor with a rectangular stator slot. The air-gap flux density under no-load and load conditions is calculated, respectively. Since the improved subdomain model does not need to simplify the stator slot shape, the magnetic potential in the stator slot is also calculated. Finally, the air-gap flux density under rotor eccentricity is calculated, and the influence of the calculating parameters on the results of the improved subdomain model is discussed. All the calculated results are compared with those obtained by the finite element method, which verifies the accuracy of the improved calculation model. [ABSTRACT FROM AUTHOR]

This paper proposes a way to represent the anisotropic nonlinear superconducting properties using a discrete model for magnetization with the corresponding critical parameters, equivalent to the Power Law model for currents. This simplified model makes it possible to analyze magnetic systems with superconducting elements in a stationary mode, which reduces the calculation time. Using of proposed model is demonstrated by the calculation of force interactions between high-temperature superconducting (HTS) samples and permanent magnet in zero-field-cooling (ZFC) and field-cooling (FC) modes. HTS bulks in the form of a prism and stack made of HTS tape are considered. The calculation of the electromagnetic field was carried out using the method of integral equations for field sources. The data of calculations are compared with the results of experimental studies. [ABSTRACT FROM AUTHOR]

Millimeter-wave rotary-wing (RW) unmanned aerial vehicle (UAV) air-to-ground (A2G) links face unpredictable Doppler effect arising from the inevitable wobbling of RW UAV. Moreover, the time-varying channel characteristics during transmission lead to inaccurate channel estimation, which in turn results in the deteriorated bit error probability performance of the UAV A2G link. This paper studies the impact of mechanical wobbling on the Doppler effect of the millimeter-wave wireless channel between a hovering RW UAV and a ground node. Our contributions of this paper lie in: i) modeling the wobbling process of a hovering RW UAV; ii) developing an analytical model to derive the temporal autocorrelation function (ACF) for the millimeter-wave RW UAV A2G link in a closed-form expression; and iii) investigating how RW UAV wobbling impacts the Doppler effect on the millimeter-wave RW UAV A2G link. Numerical results show that different RW UAV wobbling patterns impact the amplitude and the frequency of ACF oscillation in the millimeter-wave RW UAV A2G link. For UAV wobbling, the temporal ACF decreases quickly and the impact of the Doppler effect is significant on the millimeter-wave A2G link. [ABSTRACT FROM AUTHOR]

This report analyzes the reproducibility of the article “Computing Planetary Interior Normal Modes with A Highly Parallel Polynomial Filtering Eigensolver” by Jia Shi et al. (Shi, 2018). To reproduce the results we perform different weak and strong scaling studies using a series of Mars models. All experimental runs were performed during the SC19 Student Cluster Competition on a four node Intel Skylake cluster. We show that the findings of the original article can be reproduced in a different environment. [ABSTRACT FROM AUTHOR]