An improved two-vector model predictive torque control based on RMS duty ratio optimization for pmsm

This paper proposes an improved two-vector model-predictive torque control (MPTC) strategy to reduce the average torque ripple and improve the flux tracking performance. When determining the duty ratio of vector combination, this method aims at restricting the root mean square (RMS) error of both torque and flux during the whole control period. Every vector combination and corresponding time duration are evaluated in the cost function, which leads to global restriction of torque ripple and flux ripple. In order to avoid increasing switching frequency and computational burden, a restriction is added on the second vector. The three candidates of the second vector are the two adjacent vectors of the first one and zero vector. Simulation results are provided to show the effectiveness of the proposed strategy

Current boundary based model predictive torque control of PMSM

In this paper, a current boundary based model predictive torque control is proposed to improve torque and flux control performance of permanent magnet synchronous motor (PMSM). To reduce torque and flux ripple, two voltage vectors are applied in one control period. Based on the current variations under the two vectors, torque is forced to reach a preset boundary at the end of a control period and can be limited to a band during the whole period. In addition, according to the predictive switching instants and the predictive current, some vector combinations can be excluded from the control set, which significantly reduces the computational burden of cost function evaluation. Simulation results reveal the effectiveness of the proposed strategy

Reference voltage vector based model predictive torque control with RMS solution for PMSM

To reduce the computational burden of a conventional model predictive torque controller (MPTC), a reference voltage vector based MPTC strategy is proposed. The reference voltage vector is obtained from the reference stator flux vector and the reference torque. According to the location of the reference voltage vector, a first optimal vector can be determined in a quite straightforward way, improving the system dynamic performance. Furthermore, in order to decrease the torque and flux ripple, a root mean square (RMS) based solution is employed to generate the reference voltage vector and calculate the duty ratio. This method aims at minimizing the RMS error of flux and torque during the whole control period. Then, the steady state performance is improved. Besides, since the new cost function contains only the reference voltage vector, the weighting factor in conventional MPTC is eliminated. In addition, to keep a balance between the steady state performance and switching frequency, the candidates for the second optimal vector are restricted to a certain scope. Simulations were carried out and the results verified the validation of the proposed MPTC strategy

Co-contributorship Network and Division of Labor in Individual Scientific Collaborations

Collaborations are pervasive in current science. Collaborations have been studied and encouraged in many disciplines. However, little is known how a team really functions from the detailed division of labor within. In this research, we investigate the patterns of scientific collaboration and division of labor within individual scholarly articles by analyzing their co-contributorship networks. Co-contributorship networks are constructed by performing the one-mode projection of the author-task bipartite networks obtained from 138,787 papers published in PLoS journals. Given a paper, we define three types of contributors: Specialists, Team-players, and Versatiles. Specialists are those who contribute to all their tasks alone; team-players are those who contribute to every task with other collaborators; and versatiles are those who do both. We find that team-players are the majority and they tend to contribute to the five most common tasks as expected, such as "data analysis" and "performing experiments". The specialists and versatiles are more prevalent than expected by a random-graph null model. Versatiles tend to be senior authors associated with funding and supervisions. Specialists are associated with two contrasting roles: the supervising role as team leaders or marginal and specialized contributions.Comment: accepted by JASIS

Examining the Influence of Media System Dependency Relations on User Satisfaction, and Continuance Intention in Social Networking Services

Social Networking Services (SNS) exert a substantial influence in the digital realm. For marketers and entrepreneurs, comprehending the nuances of potential consumer interaction with SNS is pivotal to craft optimal communication strategies. Consequently, deciphering the determinants that either encourage or hinder individual SNS usage behaviors becomes imperative, as it fosters deeper insights into users' continuance intentions and facilitates the building of robust relationships. Drawing upon the Media System Dependency (MSD) theory, this research addresses two main questions: 1) How do individuals' MSD relations, encompassing Understanding Dependency (UD), Orientation Dependency (OD), and Play Dependency (PD), satisfaction (ST) within the SNS context? 2) Does satisfaction subsequently enhance their continuance intention (CI) towards the SNS? To address these queries, we scrutinized data amassed from 393 online Weibo users in China. Participants, all of whom possessed prior Weibo experience, were invited to partake in a comprehensive survey. The proposed hypotheses were rigorously examined using Partial Least Squares Structural Equation Modeling (PLS-SEM). The analysis revealed that the three delineated MSD relations significantly bolstered participants' ST, which in turn robustly influenced their CI. This study's findings shed invaluable light on the nexus between MSD relations and SNS engagement, offering meaningful implications for both academics and SNS practitioners. Future research endeavors are encouraged to expand upon these insights and further fortify our understanding of the topic

Multi-Grained Named Entity Recognition

This paper presents a novel framework, MGNER, for Multi-Grained Named Entity Recognition where multiple entities or entity mentions in a sentence could be non-overlapping or totally nested. Different from traditional approaches regarding NER as a sequential labeling task and annotate entities consecutively, MGNER detects and recognizes entities on multiple granularities: it is able to recognize named entities without explicitly assuming non-overlapping or totally nested structures. MGNER consists of a Detector that examines all possible word segments and a Classifier that categorizes entities. In addition, contextual information and a self-attention mechanism are utilized throughout the framework to improve the NER performance. Experimental results show that MGNER outperforms current state-of-the-art baselines up to 4.4% in terms of the F1 score among nested/non-overlapping NER tasks.Comment: In ACL 2019 as a long pape

Examining the effect of dependency relations on Weibo female users' media anxiety

Social media's rapidly expanding influence has transformed modern communication paradigms and reshaped user experiences, bringing particular repercussions for psychological well-being. Against this backdrop, the psychological impact of social media usage, especially among female users, is emerging as a significant area of both academic interest and societal concern. Grounded in the Media System Dependency (MSD) theory, this study delved into the complex dynamics of users' dependence on social media. Within this theoretical framework, three primary dependency dimensions—understanding, orientation, and play—were identified. These were further delineated across personal and societal dimensions, yielding six distinct dependency factors: Self-understanding (SeU), Social Understanding (SoU), Action Orientation (AO), Interaction Orientation (IO), Solitary Play (SiP), and Social Play (ScP). The primary aim of this research was to discern the impact of these dependency relations on media-induced anxiety. To achieve this, a meticulously designed cross-sectional study was conducted, surveying 400 female users of Weibo, a leading social media platform. By employing the robust PLS-SEM methodology for data analysis, the study formulated and tested a set of hypotheses. The empirical findings clearly demonstrated that dependency relations significantly influence media anxiety. This research not only enriches the academic discourse on MSD in varied digital contexts but also sheds light on the intricate relationship between media dependency and the mental well-being of female Weibo users

Examining the influence of media system dependency relations on user satisfaction, and continuance intention in social networking services

Social Networking Services (SNS) exert a substantial influence in the digital realm. For marketers and entrepreneurs, comprehending the nuances of potential consumer interaction with SNS is pivotal to craft optimal communication strategies. Consequently, deciphering the determinants that either encourage or hinder individual SNS usage behaviors becomes imperative, as it fosters deeper insights into users' continuance intentions and facilitates the building of robust relationships. Drawing upon the Media System Dependency (MSD) theory, this research addresses two main questions: 1) How do individuals' MSD relations, encompassing Understanding Dependency (UD), Orientation Dependency (OD), and Play Dependency (PD), satisfaction (ST) within the SNS context? 2) Does satisfaction subsequently enhance their continuance intention (CI) towards the SNS? To address these queries, we scrutinized data amassed from 393 online Weibo users in China. Participants, all of whom possessed prior Weibo experience, were invited to partake in a comprehensive survey. The proposed hypotheses were rigorously examined using Partial Least Squares Structural Equation Modeling (PLS-SEM). The analysis revealed that the three delineated MSD relations significantly bolstered participants' ST, which in turn robustly influenced their CI. This study's findings shed invaluable light on the nexus between MSD relations and SNS engagement, offering meaningful implications for both academics and SNS practitioners. Future research endeavors are encouraged to expand upon these insights and further fortify our understanding of the topic