基于语料库数据的近义词语义韵调查——以rather,fairly为例

运用基于数据的方法,通过对本族语语料库LOB中rather和fairly两个近义词的语义韵的实例研究,揭示了二者的语义韵特征,证明了语料库作为语言研究工具的强大生命力。建议学习者和语言教师在语言的学与教中广泛使用语料库工具,提高语义韵感知能力,促进语言学习和交际的顺利进行。

程度副词fairly，quite，rather和pretty

一、fairly，quite，rather和pretty的用法 这四个词都含有“相当”的意思，都可以用作程度副词，用来修饰形容词或副词，但它们所表达的语气和程度并不完全一样。

略谈rather和fairly的用法

本文从八个方面具体探讨了“rather/和“fairly”的词义差别,以及不同用法。

浅谈程度副词fairly,quite,rather,pretty和very的用法及差异

fairly,quite,rather,pretty和very这五个副词都表示程度,一般英汉词典的释义都是"相当"或"颇"。用来修饰形容词或副词,这几个词单凭其汉语释义是看不出它们的差异的,而在英语中这几个副词表示的"程度"相差很大,十分容易混淆。它们的词义从fairly开始到very为止,是逐渐加强的。大致可描述如下(后面的词比前面的语气强):fairly→quite→rather/pretty→very。

fairly,quite,rather及very的用法区别

这四个词同时都是表程度的副词,且语义含糊,灵活多变。使用时常带有一定的主观色彩。所以,要十分确切地区分这四个词是很不客易的。笔者拟从以下几个方面加以区别: 一、程度不同:

rather和fairly用法辨析

rather和fairly都有“非常”、“很”之意，但一旦出现，有些同学就分不清选择哪一个，致使选择错误。现从以下几个方面来加以浅析：

Hierarchical medical diagnosis approach for COVID-19 based on picture fuzzy fairly aggregation operators

In Pakistan, a hierarchical healthcare system is an efficient way of addressing the issueof limited and insufficient healthcare services. Identifying the various degrees of diseasebased on the doctor's diagnosis is an important step in developing the hierarchical healthcaretreatment structure. This research presents a framework for dealing with the issueof diagnosis values presented as "picture fuzzy numbers (PFNs)". Specifically, the goal ofthis study is to establish some innovative operational laws and "aggregation operators"(AOs) in a picture fuzzy environment. In this regard, we proposed some new neutral orfair operational laws that incorporate the concept of proportional distribution in orderto achieve a neutral or fair remedy to the positive, neutral and negative aspects ofPFNs. Based on the developed operational laws, we proposed the "picture fuzzy fairlyweighted average operator" and the "picture fuzzy fairly ordered weighted averagingoperator". Compared to previous techniques, the proposed AOs provide more generalizedand reliable. Furthermore, using proposed AOs with multiple decision-makers andpartial weight information under PFNs, a "multi-criteria decision-making" algorithmis developed. Finally, we provide an example to show how the novel approach can aidhierarchical treatment systems. This is essential for merging the healthcare capabilitiesof the general public and optimizing the medical care system's service performance.

政府开放数据平台FAIR原则评估指标体系及实证研究

[目的/意义]评估政府开放数据平台FAIR原则的实施效果有助于平台规范标识符、统一元数据标准等,增强政府数据的发现、共享和重用。[方法/过程]采用网络调研法,借鉴国际代表性评估框架,结合调研构建面向政府开放数据平台的FAIR原则评估指标体系,并选取国内外8个样本平台作为案例,从可发现、可访问等4个维度展开评估分析,比较FAIR原则实施状况和差异。[结果/结论]从永久性标识符方案、元数据标准规范、数据使用许可等方面提出相应改进策略,完善国内政府开放数据平台数据管理规范,为后续相关平台的建设与利用提供理论指导和实践借鉴。

国际数据管理计划工具比较研究

采纳一定的标准,特别是以主流、用户量大的数据管理计划(DMP)工具作为代表,遴选出6种研究数据管理计划工具作为研究对象,结合实际试用、前人研究和专家访谈,从科研人员使用和体验视角采用综合性研究方法,厘清工具比较评估的核心要素,构建工具比较评估的三级指标体系,就基本功能、DMP模板内容、用户体验开展比较分析,研究结果呈现通用DMP工具的典型特性和未来发展趋势,供我国出台相关政策和研发工具借鉴参考。

基于FAIR原则的数据期刊开放共享与关联模型研究

[目的/意义]为揭示数据论文与期刊论文关联出版的新形态,对目前数据期刊的开放共享、数据论文与期刊论文之间的关联进行研究,有助于推动科学数据的开放共享发展,促进科学数据的高效流通,使科学数据在多层维度释放数据价值。[方法/过程]基于FAIR原则,从元数据元素、文献服务等角度出发,构建数据流向视角下数据论文与期刊论文之间的互关联模型,分析数据论文与期刊论文之间的关联过程,并选取代表性数据期刊Data in Brief的数据论文为实例展开模型验证与实践参照。[结果/结论]本文基于“可访问”“可发现”对“开放共享”展开研究;基于“可互操作”和“可重用”对“关联”展开研究。通过构建理论模型、实例验证,厘清数据论文与期刊论文之间的关联模式以及验证理论模型的可行性与合理性。

期刊论文支撑数据FAIR原则的应用评估与案例分析

[目的/意义]FAIR原则在科技期刊的应用有助于增强期刊论文支撑数据的可发现、交互、共享与重用。评估FAIR实施情况有利于其推广实施,以期为我国期刊论文的支撑数据共享与重用提供有益参考。[方法/过程]本文在国外FAIR原则评估模型的基础上,综合考虑各模型的优势和指标设计特点,结合《数据分析与知识发现》期刊论文相关的科学数据特征,构建FAIR原则指标评价体系,基于该体系从4个维度分析调研结果,最后对中文期刊论文的支撑数据FAIR应用提出合理化建议与优化策略。[结果/结论]FAIR原则在期刊论文支撑数据的应用仍需进一步完善,科研人员的数据共享意识及对于FAIR原则的认知度远远不够,建议从宏观和微观两个层面推广FAIR原则及其实施,推动数据更加开放和可重用。

政策文本视角下我国国家科学数据中心FAIR化特征初探

[目的/意义]对我国国家科学数据中心数据政策的FAIR化特征进行探索,为我国数据中心的数据管理政策制定和工作优化提供初步参考。[方法/过程]综合运用网络调研和文本挖掘的方法,使用KH Coder内容挖掘软件对20家数据中心的79部数据政策进行量化文本分析。通过对FAIR原则在政策文本中的出现频次和高相似词汇的分析,揭示FAIR原则在各个数据中心、不同类型政策文本中表现出的关注度差异与语义特征。[结果/结论]数据中心的数据政策已体现了一定的FAIR原则理念,但对每项FAIR原则的关注度不均衡;不同类型的数据政策关注FAIR原则的不同方面,共性在于对可发现原则和可互操作原则比较关注;对元数据给予了重点关注。[创新/价值]建议数据中心在数据政策制定中突出“元数据”在数据全生命周期管理中的作用,推动“数据增值驱动”的数据政策体系构建,并立足我国科学数据管理实际,适度引入FAIR原则。

免疫学数据库和分析门户ImmPort建设经验与启示

目的/意义总结免疫学数据库和分析门户ImmPort的建设经验,为我国建设大型免疫学数据库提供经验和参考。方法/过程全面分析ImmPort的整体架构,讨论各模块功能,同时梳理其数据收集、组织、共享和分析复用的标准化数据流,总结ImmPort平台实践成果。结果/结论我国在大型免疫学数据库建设过程中应重视数据标准化组织和建模;积极引用标准化术语提供语义支持;在分类分级管理中共享数据,同时开发配套工具体系,保障免疫学数据安全有效地共享和利用。

A Formal Model for Analyzing Fair Exchange Protocols Based on Event Logic

Fair exchange protocols play a critical role in enabling two distrustful entities to conduct electronic data exchanges in a fair and secure manner.These protocols are widely used in electronic payment systems and electronic contract signing,ensuring the reliability and security of network transactions.In order to address the limitations of current research methods and enhance the analytical capabilities for fair exchange protocols,this paper proposes a formal model for analyzing such protocols.The proposed model begins with a thorough analysis of fair exchange protocols,followed by the formal definition of fairness.This definition accurately captures the inherent requirements of fair exchange protocols.Building upon event logic,the model incorporates the time factor into predicates and introduces knowledge set axioms.This enhancement empowers the improved logic to effectively describe the state and knowledge of protocol participants at different time points,facilitating reasoning about their acquired knowledge.To maximize the intruder’s capabilities,channel errors are translated into the behaviors of the intruder.The participants are further categorized into honest participants and malicious participants,enabling a comprehensive evaluation of the intruder’s potential impact.By employing a typical fair exchange protocol as an illustrative example,this paper demonstrates the detailed steps of utilizing the proposed model for protocol analysis.The entire process of protocol execution under attack scenarios is presented,shedding light on the underlying reasons for the attacks and proposing corresponding countermeasures.The developedmodel enhances the ability to reason about and evaluate the security properties of fair exchange protocols,thereby contributing to the advancement of secure network transactions.

Ada-FFL:Adaptive computing fairness federated learning

As the scale of federated learning expands,solving the Non-IID data problem of federated learning has become a key challenge of interest.Most existing solutions generally aim to solve the overall performance improvement of all clients;however,the overall performance improvement often sacrifices the performance of certain clients,such as clients with less data.Ignoring fairness may greatly reduce the willingness of some clients to participate in federated learning.In order to solve the above problem,the authors propose Ada-FFL,an adaptive fairness federated aggregation learning algorithm,which can dynamically adjust the fairness coefficient according to the update of the local models,ensuring the convergence performance of the global model and the fairness between federated learning clients.By integrating coarse-grained and fine-grained equity solutions,the authors evaluate the deviation of local models by considering both global equity and individual equity,then the weight ratio will be dynamically allocated for each client based on the evaluated deviation value,which can ensure that the update differences of local models are fully considered in each round of training.Finally,by combining a regularisation term to limit the local model update to be closer to the global model,the sensitivity of the model to input perturbations can be reduced,and the generalisation ability of the global model can be improved.Through numerous experiments on several federal data sets,the authors show that our method has more advantages in convergence effect and fairness than the existing baselines.

Aerodynamic Analysis and Optimization of Pantograph Streamline Fairing for High-Speed Trains

A pantograph serves as a vital device for the collection of electricity in trains.However,its aerodynamic resistance can limit the train’s running speed.As installing fairings around the pantograph is known to effectively reduce the resistance,in this study,different fairing lengths are considered and the related aerodynamic performances of pantograph are assessed.In particular,this is accomplished through numerical simulations based on the k-ωShear Stress Transport(SST)two-equation turbulence model.The results indicate that the fairing diminishes the direct impact of high-speed airflow on the pantograph,thereby reducing its aerodynamic resistance.However,it also induces interferences in the flow field around the train,leading to variations in the aerodynamic resistance and lift of train components.It is shown that a maximum reduction of 56.52%in pantograph aerodynamic resistance and a peak decrease of 3.38%in total train aerodynamic resistance can be achieved.

Resource Allocation in Multi-User Cellular Networks:A Transformer-Based Deep Reinforcement Learning Approach

To meet the communication services with diverse requirements,dynamic resource allocation has shown increasing importance.In this paper,we consider the multi-slot and multi-user resource allocation(MSMU-RA)in a downlink cellular scenario with the aim of maximizing system spectral efficiency while guaranteeing user fairness.We first model the MSMURA problem as a dual-sequence decision-making process,and then solve it by a novel Transformerbased deep reinforcement learning(TDRL)approach.Specifically,the proposed TDRL approach can be achieved based on two aspects:1)To adapt to the dynamic wireless environment,the proximal policy optimization(PPO)algorithm is used to optimize the multi-slot RA strategy.2)To avoid co-channel interference,the Transformer-based PPO algorithm is presented to obtain the optimal multi-user RA scheme by exploring the mapping between user sequence and resource sequence.Experimental results show that:i)the proposed approach outperforms both the traditional and DRL methods in spectral efficiency and user fairness,ii)the proposed algorithm is superior to DRL approaches in terms of convergence speed and generalization performance.

Convergence over AI Governance Amid Differences

As the EU passes the first AI law,the U.S.grapples with bipartisanship,and China proactively advances the issue-based approach and advocates the Global AI Governance Initiative,will AI become“a force for good,ensuring safety,and promoting fairness”?

Dilemmas and Optimization of Third-Party Assessment System in Chinese Fair Competition Review

The current predominant self-review mechanism by policy-making bodies suffers from deficiencies such as insufficient motivations, limited review capabilities, and weak external supervision. Third-party assessment, characterized by independence and specialization, is designed to mitigate these shortcomings. However, the implementation of third-party assessment faces challenges too. This paper intends to improve the third-party assessment system and to realize the legislative purpose of the system. Based on social research, discussions and exchanges with relevant parties, and the existing research results, this paper analyzes the challenges and possible optimization measures for the third-party assessment. The challenges include repulsion from policy-making bodies, insufficient independence of assessment bodies, disparity of assessment quality, and limited application of assessment outcomes. Possible optimization measures include promoting fair competition culture, increasing the acceptance of third-party assessment from policy-making bodies, enhancing the quality of third-party assessment, clarifying the relationship between policy-making bodies and assessment bodies, ensuring the independence of third-party assessments, and promoting the application of assessment results.