Smart Society and Artificial Intelligence:Big Data Scheduling and the Global Standard Method Applied to Smart Maintenance

The implementation of artificial intelligence(AI)in a smart society,in which the analysis of human habits is mandatory,requires automated data scheduling and analysis using smart applications,a smart infrastructure,smart systems,and a smart network.In this context,which is characterized by a large gap between training and operative processes,a dedicated method is required to manage and extract the massive amount of data and the related information mining.The method presented in this work aims to reduce this gap with near-zero-failure advanced diagnostics(AD)for smart management,which is exploitable in any context of Society 5.0,thus reducing the risk factors at all management levels and ensuring quality and sustainability.We have also developed innovative applications for a humancentered management system to support scheduling in the maintenance of operative processes,for reducing training costs,for improving production yield,and for creating a human–machine cyberspace for smart infrastructure design.The results obtained in 12 international companies demonstrate a possible global standardization of operative processes,leading to the design of a near-zero-failure intelligent system that is able to learn and upgrade itself.Our new method provides guidance for selecting the new generation of intelligent manufacturing and smart systems in order to optimize human–machine interactions,with the related smart maintenance and education.

The Value Insistence of the Cultural Production in the Big Data Era

The ultimate value of cultural production should be realizing human's comprehensive and free development,and deconstructing the ultimate value would result in human alienation.In the era of big data,every domain of human's social life,even the mode of thinking,has been transformed significantly.However,when the big data technology entirely penetrates the field of cultural production especially inducts the cultural production depending on the demand forecasting techniques,it would inevitably lead to a worry about value of the cultural production.This paper formulates that the cultural production's essence in the era of big data remains for the purpose of maximizing profit of commercial manipulation based on the modeling analysis of cultural production mechanism in the big data times.If the tendency is not corrected,the two main factors of cultural consumerism prevalence and the instrumental reason dictatorship will gradually deconstruct the ultimate value of cultural production and bring about the alienation of human being.For the sake of avoiding the trend,we should cope with two relationships:one is the people as a means and as a purpose;the other is the instrumental reason and the value rationality,finally giving rise to human's comprehensive and free development rather than human alienation.

Fifty-Six Big Data V’s Characteristics and Proposed Strategies to Overcome Security and Privacy Challenges (BD2)

The amount of data that is traveling across the internet today, including very large and complex set of raw facts that are not only large, but also, complex, noisy, heterogeneous, and longitudinal data as well. Companies, institutions, healthcare system, mobile application capturing devices and sensors, traffic management, banking, retail, education etc., use piles of data which are further used for creating reports in order to ensure continuity regarding the services that they have to offer. Recently, Big data is one of the most important topics in IT industry. Managing Big data needs new techniques because traditional security and privacy mechanisms are inadequate and unable to manage complex distributed computing for different types of data. New types of data have different and new challenges also. A lot of researches treat with big data challenges starting from Doug Laney’s landmark paper, during the previous two decades;the big challenge is how to operate a huge volume of data that has to be securely delivered through the internet and reach its destination intact. The present paper highlights important concepts of Fifty-six Big Data V’s characteristics. This paper also highlights the security and privacy Challenges that Big Data faces and solving this problem by proposed technological solutions that help us avoiding these challenging problems.

中美人工智能技术创新的动态比较——基于人工智能技术创新大数据的多S曲线模型分析

基于基础研究、技术创新、科技布局、产业规模与技术进步5个维度人工智能技术创新大数据,创新性地构建了人工智能技术创新发展水平多指标测度体系及技术创新综合发展指数;根据技术创新综合发展指数,拟合绘制出人工智能技术创新周期S演化曲线,较为准确定位了中美人工智能技术创新发展所处位置;由5个维度在技术不同发展阶段的权重分布动态,比较出中美新技术之间的创新发展差距,分析影响中国人工智能新技术创新发展的主要因素。研究发现,美国日本等世界主要发达国家的人工智能技术已步入创新成熟期,中国正处于创新成长期后期,技术创新十分活跃;借助于后发优势,中国人工智能技术创新逐年综合发展指数已超过美国,展现出非常强劲的增长态势。为赢得未来人工智能技术创新竞争的胜利,中国应在人工智能技术创新体制和技术创新资源配置机制等方面不断完善,确保中国人工智能技术创新中长期的领先地位。

Government Management Innovation in the Age of Big Data

Both opportunities and challenges are currently faced by government management innovation in the age of ＂big data＂. Traditionally, relative studies view the management of governments as the effective means to improve governmental services, without really understanding the structural influence of big data and network technology on governmental mode of thinking. Against such backdrop, this paper tries to conduct critical analysis based upon traditional outcomes in this regard, trying to make full use of the function of big data technology. With these efforts, this paper contributes to the building of an interaction theory that could promote transparency of information and customization and segmentation of the policies. By constructing a mode in which management could be carried out based on the law of big data, by building an information management system in which balance could be achieved between responsibility and freedom, by promoting the rebalancing among public power, online civil society and civil rights, the innovation of governmental management would be achieved.

Reconstructing the Data Crime Governance Model from the Perspective of Criminal Compliance

With the advent of the risk society and the era of big data,criminal law must respond to data crime in a more proactive manner.The traditional way of conviction and sentencing adopted by the current criminal law for data crime can no longer meet the requirements of the times.Compliance should be introduced into criminal law to improve the governance system of data crime.There are three ways to incorporate compliance into criminal law:(1)as the exemption cause of enterprise crime;(2)as the general circumstances of sentencing in the General Provisions of Criminal Law of the People’s Republic of China;(3)as the special circumstances of sentencing in the Specific Provisions of Criminal Law of the People’s Republic of China.The latter two approaches are more suited to China’s national conditions.

The Symbiotic Relationship Unraveling the Interplay between Technology and Artificial Intelligence(An Intelligent Dynamic Relationship)

This article investigates the dynamic relationship between technology and AI(artificial intelligence)and the role that societal requirements play in pushing AI research and adoption.Technology has advanced dramatically throughout the years,providing the groundwork for the rise of AI.AI systems have achieved incredible feats in various disciplines thanks to advancements in computer power,data availability,and complex algorithms.On the other hand,society’s needs for efficiency,enhanced healthcare,environmental sustainability,and personalized experiences have worked as powerful accelerators for AI’s progress.This article digs into how technology empowers AI and how societal needs dictate its progress,emphasizing their symbiotic relationship.The findings underline the significance of responsible AI research,which considers both technological prowess and ethical issues,to ensure that AI continues to serve the greater good.

基于SAIC方法的纵向数据模型平均

传统的SAIC模型平均所需运行时间随数据维数而呈现出阶乘级的增长,其预测精度也随之下降.本文基于传统SAIC模型平均法进行了改进,提出一类基于SAIC加权法的纵向数据模型平均法,使运算效率大幅提升,并且使预测效果拥有良好的稳定性.模拟实验结果表明,与传统方法相比,在预测残差平方和层面,本文提出的新模型在稳定性、精准性和运行速度方面均优于传统方法.

大数据背景下社交平台伪健康信息传播影响因素研究

探究大数据背景下社交平台伪健康信息传播影响因素,为有关部门更好地制定伪健康信息管理策略提供参考与借鉴。整合S-O-R模型和MOA理论,引入个性化推荐这一新变量,构建社交平台伪健康信息传播影响因素模型,利用问卷调查和结构方程模型验证模型和假设的合理性。研究表明信息交换、健康关注度、信息质量、信息新颖和个性化推荐正向影响用户感知,进而正向影响用户伪健康信息传播行为,而健康信息素养负向影响用户伪健康信息传播行为,并据此提出管理社交平台伪健康信息传播的可行性建议。

新文科背景下大数据管理与应用专业人才培养体系构建探索

本研究遵循“专业优化、课程提质、模式创新”的新文科建设要求,从课程体系建设、实践教学体系建设、项目驱动培养机制、多元化教学模式、教学师资队伍建设、教学资源建设等六个方面探索大数据管理与应用人才培养体系。通过对本体系的研究,迎合数字经济发展的需求,培养具备理解管理数据、研究数据和应用数据的综合能力的数据人才,掌握高效数据处理,数据隐私和安全等方面的相关理论和方法。

网络购物的优选神器设计

顺应时代发展,我们推出了“森源优选”网络购物平台。本文从研究背景、理论基础技术支撑需求分析、系统设计实现、数据库设计、系统测试等方面进行论述研究。我们使用UML建模语言对系统进行建模设计,并构建了一个B/S架构的网络购物平台,包括数据分析、用户管理、信息发布管理、运营商管理、网络管理、广告管理等核心模块。在数据库方面,采用了关系型数据库My Sql进行管理和储存。系统测试主要聚焦于性能、功能及安全等方面。展望未来,我们对平台的发展提出了一些建设性建议,以推动其持续进步。

基于HDFS优化传统信息化架构的数据存储模式

首先,分析了企业传统信息化架构下数据存储现状;然后,结合Hadoop技术特点,提出了运用Hadoop分布式文件系统(HDFS)提升企业数据存储能力的思路和系统架构;最后,通过经济、效率和可靠性等方面的分析,说明其可行性。

基于B/S架构的智慧窑炉远程监控系统的研究

为改进传统工业窑炉生产的监控手段,基于"互联网+",融合无线传感技术、通信技术、网络技术、云平台和大数据等技术,设计实现了一套智慧窑炉远程监控系统。该系统使窑炉在运行时具有在线自诊断功能,让管理人员及时掌握炉体的温度场分布变化、废弃排放是否达标以及窑炉故障前兆,云端的大数据挖掘为窑炉寿命的预测等提供决策依据,对安全生产、提高生产效率、节约能源以及环保监测等关键技术经济指标起着至关重要的作用。因此,该设计对实际生产具有重大的实际意义。

应用D-S证据理论评估增量配电项目投资风险的方法

针对增量配电项目存在配电施工难度大、投资项目长、周期不稳定等诸多高风险性问题,提出新型的评估模型。该模型在D-S证据理论模型的基础上融合了模糊综合评价模型,能够将影响增量项目投资风险数据的多个因素化为不同的层次和子集,使得用户能够直观地从不同的层次、子集以及阶层读取数据信息,通过确定指标权重、计算指标权重系数和一致性检验实现增量配电项目投资风险评估。试验表明,这个研究方法的平均正确率大于90%。

基于B/S的信息调查反馈系统的设计与实现

在对统计信息的调查反馈中受到信息随机性的干扰,导致反馈的准确性不好,提出一种基于大数据融合和B/S构架的信息调查反馈系统设计方案,在嵌入式Linux内核和B/S构架下进行信息调查反馈系统的软件开发设计,系统的设计分为信息大数据处理算法设计和软件设计两大部分.采用大数据挖掘和模糊聚类分析方法进行信息调查反馈的算法设计.软件设计包括AD模块、底层信息交互模块、数据库模块、人机交互模块和集成信息处理模块等组成,在B/S结构体系下进行信息调查反馈系统的底层数据库构造,采用交叉编译方法进行程序加载和自动编译设计,在总线控制和嵌入式环境下实现软件系统的软件开发.测试结果表明,采用该方法进行信息调查反馈的信息集成处理能力较强,数据融合和挖掘性能较好,反馈结果稳定可靠.

The Use of Curriculum Integration in ELT within Secondary Schools in China

CTMRC - Curriculum and Teaching Materials Reform Commission; CTMRI - Curriculum and Teaching Materials Research Institute; ELT - English Language Teaching; MOE - Ministry of Education;

基于BS架构的梯级水电站大数据服务平台设计

为提升水电站服务平台实际应用过程中的执行响应时间,文章基于B/S架构,接入PCI Express连接器,构建ADC核心电路,在B/S架构下编制集控互备服务指令,建立分布式B/S服务数据库,完成了梯级水电站大数据服务平台的设计。测试结果表明,该服务平台测试组的服务响应时间相对较短,对水电站日常任务的执行以及数据的汇总处理效果更佳,具有实际的应用价值。

Web和大数据模型在农机虚拟设计中的研究

介绍了农机虚拟设计的基本概念及其关键技术,基于Web和大数据模型建立了虚拟设计模型,并基于B/S模型结构实现了农机虚拟设计系统。仿真结果表明:仿真设计的拖拉机在传动比、速度、功耗和振动比多方面都满足理论计算值,符合设计预期。

大数据伦理研究进展、理论框架及其启示

[研究目的]掌握国内学者在大数据伦理研究领域的研究现状特点和问题,为未来该领域的研究提供参考和启示。[研究方法]通过文献分析,以中国知网(CNKI)平台近8年发布的CSSCI论文为样本数据,分别从背景、问题、原因、内容和路径5个视角来分析大数据伦理研究进展。[研究结论]国内关于大数据伦理研究处于新兴阶段,理论体系尚未建成。大数据伦理的研究视角仍需开拓,需进一步加强对大数据伦理的本体论追问,借鉴已有研究探索性地构建大数据伦理研究的建构假设框架图,并根据文献分析结果对其各构成部分进行研析,从而发现进一步完善的思路,提出未来研究展望。

人民陪审:全过程人民民主的司法路径——基于司法大数据的实证考察

人民陪审员制度作为人民司法、司法民主的重要制度表达形式,是新时代实现人民民主权利的司法路径。本文从“全过程人民民主”的理论视角出发,以人民陪审员制度作为研究对象,基于司法大数据实证追踪公民参与司法的程度、组织、范围和效能。研究发现,人民陪审能够为“全过程人民民主”提供宽广的施行空间;人民陪审所包含的“全过程人民民主”能够深刻影响司法决策;人民陪审所生发的“全过程人民民主”活力有待进一步释放。“全过程人民民主”之于人民司法,不仅拟合着“让人民群众在每一个司法案件中感受到公平正义”的本质要求,也预示着一种全新的司法治理技术的诞生。