基于区间犹豫模糊语言集的水资源多目标决策

以鄂北水资源配置工程为对象,研究大型调水工程背景下的多水源多目标优化配置。将鄂北地区水库分为充蓄水库、补偿水库与在线水库等3类,根据各类水库特点对鄂北水资源配置工程进行系统概化,建立以年缺水量最小和调水成本最低为目标函数的多水源多目标优化配置模型。采用权重系数法进行求解得到非劣解集。最后采用基于区间犹豫模糊语言与TOPSIS的多目标决策方法对各方案的缺水量与调水量作出评价并遴选出最优方案。研究结果表明:对鄂北水资源配置工程而言,缺水量与调水量的权重比为7∶3的方案综合评价最优,重视缺水的同时兼顾调水成本;基于区间犹豫模糊语言集与TOPSIS的水资源多目标决策方法经本文实例验证具有较高的稳定性与可行性。     

Computational personality recognition from Facebook text: psycholinguistic features,words and facets

ABSTRACT

Advances in the Natural Language Processing (NLP) and machine learning fields have led to the development of automated methods for the recognition of personality traits from text available from social media and similar sources. Systems of this kind exploit the close relation between lexical knowledge and personality models – such as the well-known Big Five model – to provide information about the author of an input text in a non-intrusive fashion, and at a low cost. Although now a well-established research topic in the field, the computational recognition of personality traits from text still leaves a number of research questions worth further exploration. In particular, this paper attempts to shed light on three main issues: (i) whether we may develop psycholinguistics-motivated models of personality recognition when such knowledge sources are not available for the target language under consideration; (ii) whether the use of psycholinguistic knowledge may be still superior to contemporary word vector representations; and (iii) whether we may infer certain personality facets from a corpus that does not explicitly convey this information. In this paper these issues are dealt with in a series of individual experiments of personality recognition from Facebook text, whose initial results should aid the future development of more robust systems of this kind.     

基于Python的油田生产资料预处理软件设计与应用

油田内部生产资料类型包括钻井、录井、测井、试油等多种类型。针对资料整理过程中存在的问题如:从原始资料库中下载的资料格式多样;不同石油软件所需加载的数据格式不同;已有资料预处理软件功能均较单一等,从编程语言优选、软件兼容性、软件功能集成化三个方面出发,选取Python语言进行软件设计,利用Python扩展性强的特点,设计出红番茄资料预处理软件,并在新疆油田进行试点,生产资料整理时间缩短至原耗时间的约33%。Python语言在油田生产中的应用可为具有相同问题的其他油田提供参考。     

基于语言模型的预训练技术研究综述

预训练技术当前在自然语言处理领域占有举足轻重的位置。尤其近两年提出的ELMo、GTP、BERT、XLNet、T5、GTP-3等预训练模型的成功,进一步将预训练技术推向了研究高潮。该文从语言模型、特征抽取器、上下文表征、词表征四个方面对现存的主要预训练技术进行了分析和分类,并分析了当前自然语言处理中的预训练技术面临的主要问题和发展趋势。     

Distributed Kalman filter for linear system with complex multi-channel stochastic uncertain parameter and decoupled local filters

This article considers a distributed Kalman filtering problem for linear system contaminated by complex multi-channel random uncertain parameter in which a number of nodes cooperative without central coordination to estimate a common state based on local measurements and data received from neighbors. We propose an approach to eliminate this error propagation. The proposed local filters are guaranteed to be stable under some mild conditions on certain global structural data, and their fusion yields the centralized Kalman estimate. Then, we extend this method to smoothing and deconvolution algorithm. Finally, simulation experiments demonstrate the validity of the proposed approach.     

The introduction strategy of the emerging online marketplace considering risk attitude and channel power

With the development of online retailing, traditional online platforms have begun to offer a novel online marketplace format that brings many advantages but also gives rise to problems such as operational risks and changes in channel power. This paper studies whether the e-tailer and manufacturer can reach a consensus on introducing the marketplace channel and obtains the following insights. First, the manufacturer always prefers to introduce the online marketplace in the model where she acts as the leader. The e-tailer has the same preference for the online marketplace when he moves later or simultaneously with the manufacturer. Second, as the participants become more risk-averse, the manufacturer and e-tailer would be less willing to introduce the online marketplace, and it would be more difficult to realize the equilibrium strategy under all power structure models. Third, by combining the cross-effect of the attitude towards risks and the power structure, we find that when the participants prefer risks and the e-tailer has strong channel power, it would be much easier for the two parties to reach a consensus about introducing the online marketplace.     

Augmented reality in language learning: A state-of-the-art review of 2014–2019

This systematic review study synthesizes research findings pertaining to the use of augmented reality (AR) in language learning. Published research from 2014 to 2019 has been explored and specific inclusion and exclusion criteria have been applied resulting in 54 relevant publications. Our findings determined: (a) devices and software employed for mastering AR; languages and contexts in which AR had been applied; theoretical perspectives adopted for guiding the use of AR; the number of participants in AR activities and benefits from using AR as an educational tool in the language classroom; (b) alignment of the affordances of Augmented Reality with the KSAVE (Knowledge, Skills, Attitudes, Values, Ethics) 21st-century skills framework; (c) future directions in AR research and practice. The main findings from this review demonstrate the popularity of mobile-based AR for supporting vocabulary (23.9%), reading (12.7%), speaking (9.9%) writing (8.5%) or generic language skills (9.9%). Our findings also uncovered areas that merit future attention in the application of AR in language learning – for instance learning theories were not often considered in the implementation of AR. The study concludes with suggestions for future research especially in the areas of instructional design and user experience.     

Comparing the expressiveness of downward fragments of the relation algebra with transitive closure on trees

Motivated by the continuing interest in the tree data model, we study the expressive power of downward navigational query languages on trees and chains. Basic navigational queries are built from the identity relation and edge relations using composition and union. We study the effects on relative expressiveness when we add transitive closure, projections, coprojections, intersection, and difference; this for Boolean queries and path queries on labeled and unlabeled structures. In all cases, we present the complete Hasse diagram. In particular, we establish, for each query language fragment that we study on trees, whether it is closed under difference and intersection.     

Adaptive control of unactuated dynamical systems through interconnections: Stability and performance guarantees

This article studies control and performance enforcement for a class of uncertain dynamical systems that consist of actuated and unactuated portions physically interconnected to each other. The proposed approach stabilizes the overall interconnected system in the presence of unknown physical interconnections as well as system uncertainties. Performance guarantees are enforced, individually, on the actuated as well as unactuated portions of the interconnected system via this approach. For enforcing these performance guarantees, a set-theoretic model reference adaptive control approach is used, in conjunction with linear matrix inequalities, to restrict the respective system error trajectories of the actuated and unactuated dynamics inside a priori, user-defined compact sets. The efficacy of the proposed approach is demonstrated using simulations.