Content Centric Networking: A New Approach to Big Data Distribution

In this paper, we explore network architecture anal key technologies for content-centric networking （CCN）, an emerging networking technology in the big-data era. We descrihe the structure anti operation mechanism of tl CCN node. Then we discuss mobility management, routing strategy, and caching policy in CCN. For better network performance, we propose a probability cache replacement policy that is based on cotent popularity. We also propose and evaluate a probability cache with evicted copy-up decision policy.

Using an Ontology to Help Reason about the Information Content of Data

We explore how an ontology may be used with a database to support reasoning about the “information content” of data whereby to reveal hidden information that would otherwise not derivable by using conventional database query languages. Our basic ideas rest with “ontology” and the notions of “information content”. A public ontology, if available, would be the best choice for reliable domain knowledge. To enable an ontology to work with a database would involve, among others, certain mechanism thereby the two systems can form a coherent whole. This is achieved by means of the notion of “information content inclusion relation”, IIR for short. We present what an IIR is, and how IIR can be identified from both an ontology and a database, and then reasoning about them.

Monitoring Soil Salt Content Using HJ-1A Hyperspectral Data: A Case Study of Coastal Areas in Rudong County, Eastern China

Hyperspectral data are an important source for monitoring soil salt content on a large scale. However, in previous studies, barriers such as interference due to the presence of vegetation restricted the precision of mapping soil salt content. This study tested a new method for predicting soil salt content with improved precision by using Chinese hyperspectral data, Huan Jing-Hyper Spectral Imager(HJ-HSI), in the coastal area of Rudong County, Eastern China. The vegetation-covered area and coastal bare flat area were distinguished by using the normalized differential vegetation index at the band length of 705 nm(NDVI705). The soil salt content of each area was predicted by various algorithms. A Normal Soil Salt Content Response Index(NSSRI) was constructed from continuum-removed reflectance(CR-reflectance) at wavelengths of 908.95 nm and 687.41 nm to predict the soil salt content in the coastal bare flat area(NDVI705 < 0.2). The soil adjusted salinity index(SAVI) was applied to predict the soil salt content in the vegetation-covered area(NDVI705 ≥ 0.2). The results demonstrate that 1) the new method significantly improves the accuracy of soil salt content mapping(R2 = 0.6396, RMSE = 0.3591), and 2) HJ-HSI data can be used to map soil salt content precisely and are suitable for monitoring soil salt content on a large scale.

Stratal Carbonate Content Inversion Using Seismic Data and Its Applications to the Northern South China Sea

On the basis of the relationship between the carbonate content and the stratal velocity and density, an exercise has been attempted using an artificial neural network on high-resolution seismic data for inversion of carbonate content with limited well measarements as a control. The method was applied to the slope area of the northern South China Sea near ODP Sites 1146 and 1148, and the results are satisfaetory. Before inversion calculation, a stepwise regression method was applied to obtain six properties related most closely to the carbonate content variations among the various properties on the seismic profiles across or near the wells. These include the average frequency, the integrated absolute amplitude, the dominant frequency, the reflection time, the derivative instantaneous amplitude, and the instantaneous frequency. The results, with carbonate content errors of mostly ±5 % relative to those measured from sediment samples, show a relatively accurate picture of carbonate distribution along the slope profile. This method pioneers a new quantitative model to acquire carbonate content variations directly from high-resolution seismic data. It will provide a new approach toward obtaining substitutive high-resolution sediment data for earth system studies related to basin evolution, especially in discussing the coupling between regional sedimentation and climate change.

面向5G mMTC的data-only竞争式免调度接入

基于参考信号的竞争式免调度接入,参考信号的碰撞会限制其性能。考虑了一种基于纯数据(data-only)的竞争式免调度接入方案,其盲检测接收机充分利用数据本身的特点来实现多用户检测,避免了参考信号的碰撞难题以及资源开销,因而可取得高得多的业务负载。另一方面,高负载接入性能还受限于小区间干扰。data-only接入信号不包含小区级处理,每个小区基站的盲检测接收机会对所有接收到的用户信号,包括靠近本区的邻区用户信号,进行解调译码和干扰消除。这实质上实施了小区间干扰消除,因而能明显减少邻区的强干扰,进而提升系统的负载。而且data-only盲检测接收机实现小区间干扰消除并不用增加很多额外的复杂度,这是传统小区间干扰消除方法所不具备的优点。

引用位置视角下数据论文引用行为特征分析——以Scientific Data为例

为探究数据论文的引用行为特征,本研究以Scientific Data期刊中1 473篇数据论文为例,基于引用位置视角,抓取数据论文全文数据,提取引用行为相关信息进行分析。经研究并与一般学术论文对比,发现数据论文引用位置呈“头重脚轻”特征,且不同引用位置上的被引年龄与引用强度均存在明显差异。

A Novel Metadata Based Multi-Label Document Classification Technique

From the beginning,the process of research and its publication is an ever-growing phenomenon and with the emergence of web technologies,its growth rate is overwhelming.On a rough estimate,more than thirty thousand research journals have been issuing around four million papers annually on average.Search engines,indexing services,and digital libraries have been searching for such publications over the web.Nevertheless,getting the most relevant articles against the user requests is yet a fantasy.It is mainly because the articles are not appropriately indexed based on the hierarchies of granular subject classification.To overcome this issue,researchers are striving to investigate new techniques for the classification of the research articles especially,when the complete article text is not available(a case of nonopen access articles).The proposed study aims to investigate the multilabel classification over the available metadata in the best possible way and to assess,“to what extent metadata-based features can perform in contrast to content-based approaches.”In this regard,novel techniques for investigating multilabel classification have been proposed,developed,and evaluated on metadata such as the Title and Keywords of the articles.The proposed technique has been assessed for two diverse datasets,namely,from the Journal of universal computer science(J.UCS)and the benchmark dataset comprises of the articles published by the Association for computing machinery(ACM).The proposed technique yields encouraging results in contrast to the state-ofthe-art techniques in the literature.

New reconstruction and forecasting algorithm for TEC data

To reconstruct the missing data of the total electron content （TEC） observations, a new method is proposed, which is based on the empirical orthogonal functions （EOF） decomposition and the value of eigenvalue itself. It is a self-adaptive EOF decomposition without any prior information needed, and the error of reconstructed data can be estimated. The interval quartering algorithm and cross-validation algorithm are used to compute the optimal number of EOFs for reconstruction. The interval quartering algorithm can reduce the computation time. The application of the data interpolating empirical orthogonal functions （DINEOF） method to the real data have demonstrated that the method can reconstruct the TEC map with high accuracy, which can be employed on the real-time system in the future work.

A UNIFIED EXTENDING METHOD FOR CONTENT-IGNORANT WEB PAGE CLUSTERING

The content-ignorant clustering method takes advantages in time complexity and space complexity than the content based methods.In this paper,the authors introduce a unified expanding method for content-ignorant web page clustering by mining the "click-through" log,which tries to solve the problem that the "click-through" log is sparse.The relationship between two nodes which have been expanded is also defined and optimized.Analysis and experiment show that the performance of the new method has improved,by the comparison with the standard content-ignorant method.The new method can also work without iterative clustering.

如何走出AIGC的“科林格里奇困境”:全流程动态数据合规治理

[目的/意义]AIGC的快速发展带来了安全风险与规制问题,遵循AIGC的发展趋势构建全流程动态数据合规治理机制,能够帮助AIGC走出“科林格里奇困境”。[研究设计/方法]通过梳理AIGC与数据治理之间的赋能与保障关系,结合AIGC规制的国际实践经验进行“科林格里奇困境”规制博弈分析,探析AIGC创新发展与规制的路径。[结论/发现]无论是欧盟的强硬规制、中国的谨慎监管还是美国的行业自律,都在不同维度显现出规制的局限性,可以通过全流程动态化规制手段适配AIGC的动态化发展趋势,构建基于数据合规治理的AIGC全流程动态规制机制,帮助AIGC走出困境。[创新/价值]基于数据合规治理的AIGC动态规制机制能够不断改进规制体制和工具,为AIGC相关技术落地具体应用领域提供思路。

人工智能生成内容确权模式的嬗变与数据财产权的确立

人工智能生成内容已深入应用到社会生产生活当中。在数据确权制度诞生之前,各国立法、司法和理论界大多主张以著作权法保护人工智能生成的数据。由于狭义著作权确权模式饱受“独创性”诟病,转而走向邻接权确权模式。然而,透过人工智能生成内容的技术和法律本质可以看出,该客体和邻接权的保护客体以及设立目的并无相关之处,盲目扩大邻接权的保护范围不仅会遭到理论与制度的挑战,而且在司法实践中也会捉襟见肘。因此,必须走出著作权保护模式的藩篱和迷雾,直面人工智能生成内容的本质,构建具有合理性的新型财产权制度。从数据视野来看,人工智能生成内容的技术本质为数据,法律本质为数据财产。随着数据时代的到来以及数据立法的展开,人工智能生成内容的数据财产权确权模式必然浮出水面。数据财产权确权模式是依托于数据法律制度的出现与发展提出的,是立足于人工智能生成内容的数据本质形成的,是基于人工智能生成内容的数据财产法律属性揭示的确权模式选择。在综合考量产业目的、盈利模式、风险成本、商业实践以及使用者目的来看,人工智能生成内容的权利主体应当为服务使用者而不是服务提供者,权利保护应适用“财产规则”和“禁易规则”。

A Survey of Applications Research on Content-Centric Networking

As a named data-based clean-slate future Internet architecture,Content-Centric Networking(CCN)uses entirely different protocols and communication patterns from the host-to-host IP network.In CCN,communication is wholly driven by the data consumer.Consumers must send Interest packets with the content name and not by the host’s network address.Its nature of in-network caching,Interest packets aggregation and hop-byhop communication poses unique challenges to provision of Internet applications,where traditional IP network no long works well.This paper presents a comprehensive survey of state-of-the-art application research activities related to CCN architecture.Our main aims in this survey are(a)to identify the advantages and drawbacks of CCN architectures for application provisioning;(b)to discuss the challenges and opportunities regarding service provisioning in CCN architectures;and(c)to further encourage deeper thinking about design principles for future Internet architectures from the perspective of upper-layer applications.

美欧数据跨境流动治理政策共性内容要素分析与中国启示研究

[目的/意义]通过对美欧数据跨境流动治理政策进行深入调研和内容分析,旨在为我国数据跨境流动治理政策制定和管理实践提供启示与借鉴。[方法/过程]采用文献调研、网络调查和质性文本分析法,基于数据生命周期理论,梳理并分析美欧数据跨境流动治理政策内容,通过构建政策文本分析类目体系,提炼政策共性内容要素。[结果/结论]研究发现,美欧已将数据生命周期思想融入数据跨境流动治理政策,且二者存在诸多共性,体现出数据跨境流动政策制定的总体遵循。基于此,文章结合美欧政策内容共性要素,立足我国国情,围绕数据跨境流动中的“三难选择”问题,分别从保障个人数据权利、平衡数据跨境流动与数据安全、维护数据主权等方面提出对策建议,为我国数据跨境流动治理政策的制定与完善提供思路。

A Quality Assurance Reference Framework for Assessing Educational Data

Digital educational content is gaining importance as an incubator of pedagogical methodologies in formal and informal online educational settings. Its educational efficiency is directly dependent on its quality, however educational content is more than information and data. This paper presents a new data quality framework for assessing digital educational content used for teaching in distance learning environments. The model relies on the ISO2500 series quality standard and beside providing the mechanisms for multi-facet quality assessment it also supports organizations that design, create, manage and use educational content with the quality tools (expressed as quality metrics and measurement methods) to provide a more efficient distance education experience. The model describes the quality characteristics of the educational material content using data and software quality characteristics.

基于数据生命周期的煤泥浮选智能控制技术研究进展

随着国家政策和新一代人工智能技术的持续牵引,矿山智能化研究取得突破,其中,选煤厂智能化建设受到高度关注,煤泥浮选智能控制技术一直是阻碍选煤厂智能化建设的关键瓶颈之一。以煤泥浮选数据生命周期为主线,从浮选精煤/尾煤灰分在线预测、浮选药剂智能添加和煤泥浮选系统智能决策3个角度综述了煤泥浮选智能控制技术的研究进展,并展望未来煤泥浮选智能控制技术发展趋势。浮选精煤灰分在线预测困难重重,单一视觉特征信息并不可靠,尾矿灰分的预测技术相对更加成熟可靠;浮选药剂添加量受多个过程变量同时制约,模型性能在整个工况区间的自适应性和泛化能力还需进一步提升;当前浮选工业系统智能控制技术的进一步发展严重受限于浮选精煤/尾煤灰分等指标的预测精度、传感器检测精度、药剂添加精度等因素。浮选过程数据集维度更高,难以建立可靠的知识库,以深度学习为代表的新一代人工智能技术能适应这类数据结构。此外,已有浮选监测系统只针对特定矿物,唯一性较高。未来浮选智能控制系统应集中攻克指标预测、传感器检测精度等方面限制,建立多煤种、模板化的煤泥浮选智能控制资料大数据集和大模型。

命名数据网络中基于分级的数据缓存方法

针对NDN固有数据缓存机制存在数据内容多样性低、频繁替换等问题,提出了一种数据分级缓存方法.该方法将传输路径上的路由器进行等级划分,根据数据内容热度,将其缓存在相应等级的路由器中,以减少用户获取数据内容的时间.实验结果表明:该方法能够有效提高缓存命中率,减少平均路由跳数,降低平均请求时延.

环境工程专业学位硕士试验设计与数据处理课程教学优化——基于国内外三所高校案例

文章比较了清华大学试验设计与分析线上课程和昆士兰大学试验设计线下课程在教学内容和教学方法方面的差异,并分析了各自的特点;在此基础上,介绍了中国矿业大学环境工程专业学位硕士试验设计与数据处理课程结合人才培养目标,进行教学内容和教学方法优化,并实施线上线下混合式教学模式的实践。中国矿业大学的试验设计与数据处理课程教学达到了使学生“懂理论、会应用、能实践”的目标。

政策工具和政策特性视角下《数据安全法》内容解析

数据安全是数据经济健康快速发展的重要保障。本研究以《中华人民共和国数据安全法》的政策文本为对象,运用内容分析法和共词分析法分别从政策工具和政策特性的视角进行分析。在政策工具视角下,环境型政策工具占比最大,供给型政策工具次之,而需求型政策工具则相对缺乏;从政策特性角度看,具有数据保护的义务性、数据获取的规范性、数据应用的需求性、数据责任的具体化四个特性。

基于“教赛协同”的数据挖掘课程教学改革研究

数据挖掘课程是大数据和人工智能方向重要的核心课程,主要培养学生在数据驱动的范式下结合问题场景和社会需求,具备利用数据挖掘方法和技术分析、解决实际问题的能力。针对数据挖掘课程教学过程中存在的“痛点”问题,以培养工程型创新性人才为导向,从课程内容体系、学科竞赛体系和课程队伍体系三个维度,探索并构建基于“教赛协同”的数据挖掘课程教学改革的策略和方法,为地方高等院校大数据和人工智能相关专业的发展提供思路。