机器翻译译文质量估计综述

机器翻译译文质量估计(Quality Estimation,QE)是指在不需要人工参考译文的条件下,估计机器翻译系统产生的译文的质量,对机器翻译研究和应用具有很重要的价值。机器翻译译文质量估计经过最近几年的发展,取得了丰富的研究成果。该文首先介绍了机器翻译译文质量估计的背景与意义;然后详细介绍了句子级QE、单词级QE、文档级QE的具体任务目标、评价指标等内容,进一步概括了QE方法发展的三个阶段: 基于特征工程和机器学习的QE方法阶段,基于深度学习的QE方法阶段,融入预训练模型的QE方法阶段,并介绍了每一阶段中的代表性研究工作;最后分析了目前的研究现状及不足,并对未来QE方法的研究及发展方向进行了展望。     

The roles of conceptual modelling in improving construction simulation studies: A comprehensive review

The conceptual modelling phase of simulation studies has proven to be effective in enhancing the impact of simulation modelling in different domains. However, this simulation phase did not receive much attention in the construction simulation domain. The objective of this paper is to identify the roles that conceptual modelling can play in advancing the engagement, accuracy, and adoption (among other things) of discrete-event simulation studies in construction. In this paper, a Systematic Literature Review (SLR) is conducted, which involves a comprehensive search of databases and researchers’ profiles to identify journal papers, conference articles, books, and theses that have reported the benefits of conceptual modelling for discrete-event simulation studies. The review resulted in 82 documents that were published from 2000 to 2020. Results indicate that the benefits of conceptual modelling include facilitating communications between stakeholders, capturing sufficient information for the simulation model, improving the quality of simulation models, guiding other simulation modelling activities, and facilitating verification and validation of simulation models. By linking these benefits to the current research agenda in construction simulation, this paper shows the significance and potential of the conceptual modelling phase to enhance the impact of discrete-event simulation studies in construction.     

A systematic literature review to explore traceability and lifecycle relationship

Traceability is the ability to follow a product along its lifecycle. It ensures product safety and quality along the supply chain, managing information generated by several players. Even though regulations establish the information that has to be traced, each player generates much more product (and process) information, which could be used to add value to products, with respect to, not only traceability, but also the lifecycle approach. However, the concepts do not appear to be immediately related in scientific panorama. This paper aims to explore the relationship between traceability and lifecycle through a systematic literature review. Six industries (Software, Manufacturing, Automotive, Automation, Aircraft, and Aerospace) and seven subject areas (Software engineering; System engineering; Industry 4.0; New product development; Process management; Data Management; and Environmental sustainability) were identified through bibliometric analysis. To better explore this relationship in the context of the food industry, a content analysis on lead papers’ sample was performed to identify traceability and lifecycle definitions, methodologies and technologies and their relation. The results of the work, synthetised in a proposed research map, will be of interest to those who are approaching the subject for the first time, and for companies involved in product lifecycle management and food traceability.     

Hybrid make-to-stock and make-to-order systems: a taxonomic review

Production planning and control (PPC) systems that employ aspects from both make-to-order (MTO) and make-to-stock (MTS) production control are known as hybrid MTS/MTO systems. While both MTO and MTS separately have been studied extensively, their combined use has received less attention. However, the literature on this topic is growing and this paper shows that the review performed in this paper is an important addition to the field. We categorise relevant literature according to a novel taxonomy and show that hybrid MTS/MTO production control can be used in different contexts. In addition, an overview of the modelling techniques and methods used in these papers is provided. Based on the reviewed literature, relevant research questions and directions for future research are identified. Finally, it is shown that hybrid MTS/MTO production control is prevalent in practice by discussing research with industrial applications. The paper contains an overview of research on hybrid MTS/MTO production control to be used as reference for researchers active in the field, and provides managerial insights and directions for future research on this topic.     

新型冠状病毒肺炎综述文献的网络结构分析

对新型冠状病毒肺炎综述文献进行网络结构分析可为新冠疫情的应对提供有效的理论支持。采用可视化软件CiteSpace对Web of Science数据库中新型冠状病毒肺炎综述文献的引文数据进行共被引网络分析，经统计发现文献共被引网络的度分布呈幂律分布，网络连通性较强且存在小世界现象。运用团渗流算法对其进行重叠社团挖掘，检测到7篇同时跨3个社团的核心文献，结合被引频次对网络重叠节点的功能进行验证。借助网络重叠节点的ID符号、介数中心性指标发现相应研究主题间联系紧密。通过不同特征的重要网络节点，能够有效挖掘到相关的研究主题。     

Scientific mapping to identify competencies required by industry 4.0

The objective of this study was to identify what competencies are identified in the literature as necessary for Industry 4.0 by conducting a survey of the literature and a scientific mapping of the evolution of the issues related to the qualification of professionals for Industry 4.0 and possible paths for research and education. A search was conducted on the Scopus, Web of Science and Science Direct databases for the interval from 2010 to 2018. This systematic review revealed topics and authors currently specialized in the field and allowed mapping the field of study. The identification of journals and keywords useful in future studies was also an object of this study. SciMAT software was used for the systematic literature review. The results are highlighted by the set of competencies (knowledge and skills) that must be developed in professional education to accompany the new industrial revolution, as well as the importance of integrating efforts by companies, governments and universities. These efforts should focus on creating “learning factories”, which are understood to be environments that provide practical experiences to these professionals, preparing them in the best way possible for the requirements of Industry 4.0. This conceptual map showed that the main competencies needed include skills: (leadership, strategic vision of knowledge, self-organization, giving and receiving feedback, pro-activity, creativity, problem solving, interdisciplinarity, teamwork, collaborative work, initiative, communication, innovation, adaptability, flexibility and self-management) and knowledge of contemporary fields (information and communication technology, algorithms, automation, software development and security, data analysis, general systems theory and sustainable development theory).     

An Advanced Analysis of Cloud Computing Concepts Based on the Computer Science Ontology

Our primary research hypothesis stands on a simple idea: The evolution of top-rated publications on a particular theme depends heavily on the progress and maturity of related topics. And this even when there are no clear relations or some concepts appear to cease to exist and leave place for newer ones starting many years ago. We implemented our model based on Computer Science Ontology (CSO) and analyzed 44 years of publications. Then we derived the most important concepts related to Cloud Computing (CC) from the scientific collection offered by Clarivate Analytics. Our methodology includes data extraction using advanced web crawling techniques, data preparation, statistical data analysis, and graphical representations. We obtained related concepts after aggregating the scores using the Jaccard coefficient and CSO Ontology. Our article reveals the contribution of Cloud Computing topics in research papers in leading scientific journals and the relationships between the field of Cloud Computing and the interdependent subdivisions identified in the broader framework of Computer Science.     

Reliability-based fault analysis models with industrial applications: A systematic literature review

Effective and early fault detection and diagnosis techniques have tremendously enhanced over the years to ensure continuous operations of contemporary complex systems, control cost, and enhance safety in assets-intensive industries, including oil and gas, process, and power generation. The objective of this work is to understand the development of different fault detection and diagnosis methods, their applications, and benefits to the industry. This paper presents a contemporary state-of-the-art systematic literature survey focusing on a comprehensive review of the models for fault detection and their industrial applications. This study uses advanced tools from bibliometric analysis to systematically analyze over 500 peer-reviewed articles on focus areas published since 2010. We first present an exploratory analysis and identify the influential contributions to the field, authors, and countries, among other key indicators.  A network analysis is presented to unveil and visualize the clusters of the distinguishable areas using a co-citation network analysis. Later, a detailed content analysis of the top-100 most-cited papers is carried out to understand the progression of fault detection and artificial intelligence–based algorithms in different industrial applications. The findings of this paper allow us to comprehend the development of reliability-based fault analysis techniques over time, and the use of smart algorithms and their success. This work helps to make a unique contribution toward revealing the future avenues and setting up a prospective research road map for asset-intensive industry, researchers, and policymakers.     

Immersive virtual reality applications for design reviews: Systematic literature review and classification scheme for functionalities

The development of immersive virtual reality (IVR) applications for design reviews is a major trend in the design field. While many different applications have been developed, there is little consensus on the functionalities necessary for these applications. This paper proposes a classification scheme for IVR functionalities related to design reviews (DRs), combining conceptual-to-empirical and empirical-to-conceptual strategies. The classification scheme consists of eight class categories (Input, Representation, Navigation, Manipulation, Collaboration, Edit, Creation, and Output), 22 class subcategories, and 55 classes. The classification scheme has been validated by analysing several commercial IVR applications for DRs. As part of the classification scheme development, Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) was utilised to review 70 articles that develop IVR applications for DRs. The results from systematic literature reviews suggest the development of solutions that integrate several class categories, are better connected to current design workflows, include various design information, support a DR planning cycle, and support distributed work. The proposed classification scheme helps to orient the future development of IVR applications for DRs and provides a framework to systematically accumulate evidence on the effect of such applications on DRs.