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The method of the learning of vague languages which represent distorted/ambiguous patterns is proposed in the paper. The goal of the method is to infer the quasi-context-sensitive string grammar which is used in our model as the generator of patterns. The method is an important component of the multi-derivational model of the parsing of vague languages used for syntactic pattern recognition. |
Let R be a finite commutative ring. The set F(R) of polynomial functions on R is a finite commutative ring with pointwise operations. Its group of units F(R)× is just the set of all unit-valued polynomial functions. We investigate polynomial permutations on R[x]/(x2)=R[α], the ring of dual numbers over R, and show that the group PR(R[α])
, consisting of those polynomial permutations of R[α] represented by polynomials in R[x], is embedded in a semidirect product of F(R)× by the group P(R) of polynomial permutations on R. In particular, when R=Fq
, we prove that PFq(Fq[α])≅P(Fq)⋉θF(Fq)×. Furthermore, we count unit-valued polynomial functions on the ring of integers modulo pn and obtain canonical representations for these functions. |
Some of the most critical competencies students need to acquire to become control engineers require performing practices under actual industrial conditions. This means that they must not only master the theoretical aspects of the discipline but also acquire skills and attitudes to face unpredictable real-world situations. Software tools such as Matlab/Simulink are widely used to train the design and validation of controllers, but they fail to provide real industrial contexts. Nowadays, there are 3D simulation tools that support recreating industrial environments to a remarkable extent, making them very attractive for university courses. Nevertheless, their application in engineering courses is scarce yet. This paper presents a methodological framework for seizing into competency-bas... |
A single network model can’t extract more complex and rich effective features. Meanwhile, the network structure is usually huge, and there are many parameters and consume more space resources, etc. Therefore, the combination of multiple network models to extract complementary features has attracted extensive attention. In order to solve the problems existing in the prior art that the network model can’t extract high spatial depth features, redundant network structure parameters, and weak generalization ability, this paper adopts two models of Xception module and inverted residual structure to build the neural network. Based on this, a face expression recognition method based on improved depthwise separable convolutional network is proposed in the paper. Firstly, Gaussian filtering i... |
Despite improvement in gender inequality in Australian science, the problem has not been fully addressed yet. To better understand the nature of gender inequality in Australian science, all gendered Australian first authored articles published between 2010 and 2020 and indexed in the Dimensions database were analysed. Field of Research (FoR) was used as the subject classification of articles and Field Citation Ratio (FCR) was used for citation comparison. Overall, the ratio of female to male first authored articles increased over the years, and this was true for all FoRs except for information and computing sciences. The ratio of single-authored articles by females was also improved over the study period. Females appeared to have a citation advantage, using Field Citation Ratio, ove... |
The success of blockchain technology in cryptocurrencies reveals its potential in the data management field. Recently, there is a trend in the database community to integrate blockchains and traditional databases to obtain security, efficiency, and privacy from the two distinctive but related systems. In this survey, we discuss the use of blockchain technology in the data management field and focus on the fusion system of blockchains and databases. We first classify existing blockchain-related data management technologies by their locations on the blockchain-database spectrum. |
Social networks have become an increasingly common abstraction to capture the interactions of individual users in a number of everyday activities and applications. As a result, the analysis of such networks has attracted lots of attention in the literature. Among the topics of interest, a key problem relates to identifying so-called influential users for a number of applications, which need to spread messages. Several approaches have been proposed to estimate users’ influence and identify sets of influential users in social networks. A common basis of these approaches is to consider links between users, that is, structural or topological properties of the network. To a lesser extent, some approaches take into account users’ behaviours or attitudes. |
As the number of online labor platforms and the diversity of jobs on these platforms increase, ensuring group fairness for workers needs to be the focus of job-matching services. Risk of discrimination against workers occurs in two different job-matching services: when someone is looking for a job (i.e., a job seeker) and when someone wants to deploy jobs (i.e., a job provider). To maximize their chances of getting hired, job seekers submit their profiles on different platforms. Similarly, job providers publish their job offers on multiple platforms with the goal of reaching a wide and diverse workforce. In this paper, we propose a theoretical framework to maximize group fairness for workers 1) when job seekers are looking for jobs on multiple platforms, and 2) when jobs are being d... |
Scholars, policymakers and organizations in the EU, especially at the level of the European Commission, have turned their attention to the ethics of (trustworthy and human-centric) Artificial Intelligence (AI). However, there has been little reflexivity on (1) the history of the ethics of AI as an institutionalized phenomenon and (2) the comparison to similar episodes of “ethification” in other fields, to highlight common (unresolved) challenges. |
Deep learning has been extensively researched in the field of document analysis and has shown excellent performance across a wide range of document-related tasks. As a result, a great deal of emphasis is now being placed on its practical deployment and integration into modern industrial document processing pipelines. It is well known, however, that deep learning models are data-hungry and often require huge volumes of annotated data in order to achieve competitive performances. And since data annotation is a costly and labor-intensive process, it remains one of the major hurdles to their practical deployment. This study investigates the possibility of using active learning to reduce the costs of data annotation in the context of document image classification, which is one of the cor... |
