双约束下智慧供应链精准化质量需求资源配置模型

互联网的发展不仅影响顾客购买行为和需求模式,还带来了供应链解耦点的前移。为提高顾客满意度,各节点企业需支付额外的成本。围绕顾客和企业效用,考虑智慧供应链整体最优,延伸资源配置理论,设计新的运算规则,建立双约束下质量需求资源配置模型。利用大数据情感分析技术获取精准化质量需求重要度,设计“加”取值规则求得顾客满意约束下质量需求权向量,形成模型输入信息。通过逐级循环运算求解,得到精准化质量需求优先级决策结果,为智慧供应链资源配置提供依据,优化企业质量行为。以某品牌新能源汽车智慧供应链为例,获取真实的评论数据,验证模型的有效性。     

互联网背景下制造业创新体系建设研究

以互联网和大数据为特征的新一代信息技术深刻影响着制造业创新体系建设。本文分析了互联网背景下,制造业创新体系在共性技术供给、技术供给方式和产学研创新体系建设方面的建设需求,提出了建设共性技术研发基地、提供多元化技术供给平台以促进创新网络建设和创新生态培育。     

智慧园区建设探索与实践

随着5G、物联网、大数据等技术的发展,传统的园区建设已经不能满足现有园区的发展,数字园区、知识园区、生态园区、创新园区等理念的新型园区,更是这种形式下衍生出来的科技园区发展的新形态,需要有更创新、更可靠的园区建设架构及新的技术来引领更智慧的发展,这就需要智慧园区从信息化朝着数字化、智能化迈进。该文以建设感知园区为目标,实现对园区内的人、车、财、物的位置、流向、状态以及环境参数、生产信息的全面掌握、智能预警和敏捷控制,从而真正实现物联网在园区内的普及应用,为园区智慧化打下坚实的基础[1]。该文通过智慧园区建设理念、技术架构、构建模式、标准化接口等方面,进而阐述如何采用大数据、物联网技术使智慧化应用更好地服务于园区。     

“互联网文化创新”陕西文化软实力提升理论研究

文章分析了陕西省在"互联网+文化创新"现状下的困境,以及现状下的机遇和挑战;从政策与理论的角度阐述了如何提升陕西省的文化软实力;并提出了销售创新、协作创新、设计创新和传承创新来实现"互联网+文化创新"陕西文化产业发展模式,为陕西建设互联网时代文化大省提供理论支持。     

基于“互联网+”的计量检测记录电子采集与证书系统

<正>随着互联网+这种互联网新形态、新业态的产生,互联网+计量创新思维应运而生,互联网+计量创新生产力对现在国内计量检测行业普遍存在的纸张化录入检测数据的方式提出了挑战。只有实现计量检测原始记录电子化运作方式,才能有数据、网络等互联网基础资源实现互联网+计量检测行业的融合,才能够运用互联网思维和互联网技术充分发挥这种创新生     

浅谈互联网+背景下的事业单位人力资源管理

21世纪以来,互联网的发展日新月异,也衍生出了诸多大数据工具,对提高办公效率和提升办公环境有着重大作用.在事业单位的人力资源管理中,一向使用的纸质载体化办公模式已经逐渐不能满足办公需求,面对挑战,事业单位的人力资源管理需要进行与互联网+接轨的积极应对.本文针对互联网+背景下事业单位人力资源管理进行探讨,力求为事业单位人力资源管理的改进提供有效依据.     

基于互联网大数据的检测服务平台的实现

在互联网技术井喷的时代,依托互联网技术创新服务模式,实现转型升级甚至颠覆式发展的案例数不胜数。作为传统的检验检测服务行业,建设基于互联网思维和技术的检验检测服务平台,是加快政府职能转变、促进检验检测机构转型升级、精准便捷服务检验客户的客观需求。本文首先分析了传统检验检测服务行业存在的诸多弊端,以及基于互联网技术实现检验检验服务模式创新的必要性,之后阐述了平台的功能架构和建设内容。     

“互联网+”语境下养老护理产品设计研究

基于国家"互联网+居家养老"行动计划,催生更丰富的养老护理产品,全面、智能、健康的护理产品为老年人养老提供了方便。在"互联网+"时代下养老护理产品设计在需求功能、设计原则、技术规范等方面有了全新定义和价值。通过理论与调研分析在"互联网+"时代下养老护理产品设计的全方位、具体化、有效性的战略构想,为养老产品设计提供定性分析基础。对"互联网+"时代下的养老护理产品设计的全面研究,真正实现养老护理产品设计的创新生态、跨界融合,为老年人提供精准、快捷、全方位的产品体验服务。     

设计质量创新--QFD、TRIZ和田口方法的集成应用

 产品竞争归根到底是设计与制造水平的竞争,只有在设计中运用新的思想,采用新的理论、方法和原理,才能提高产品的设计质量,实现创新,从而构筑竞争优势．QFD方法以顾客需求为导向,从顾客出发寻找影响产品质量的关键技术．TRIZ理论提供了一种全新的解决创新问题的思想,实现技术创新．田口方法为创新成果转化成物美价廉的产品提供了切实可行的应用工具．在比较和分析3种方法各自特点的基础上,提出了QFD、TRIZ和田口方法的集成应用的设计思想,它将最大限度地发挥各自的优势,弥补不足,从而实现设计质量创新．     

互联网+先进计量——综述与展望

<正>一、引言互联网+是面向蓬勃发展的互联网信息技术与传统产业深度融合的新型经济形态。互联网+从"互联网+传统行业"这一基本出发点不断延拓,依托互联网信息技术在大数据、物联网、人工智能等前沿领域取得的最新进展,优化或重构传统行业体系与模式,从而帮助实现产业转型升级与社会生产力提升。在经济全球化背景下,我国为了进一步提升国际经济地位,优化所处国际经济利益分配链条的位置,互联网+成为国家重点支     

A Novel Ensemble Learning Algorithm Based on D-S Evidence Theory for IoT Security

In the last decade, IoT has been widely used in smart cities, autonomous driving and Industry 4.0, which lead to improve efficiency, reliability, security and economic benefits. However, with the rapid development of new technologies, such as cognitive communication, cloud computing, quantum computing and big data, the IoT security is being confronted with a series of new threats and challenges. IoT device identification via Radio Frequency Fingerprinting (RFF) extracting from radio signals is a physical-layer method for IoT security. In physical-layer, RFF is a unique characteristic of IoT device themselves, which can difficultly be tampered. Just as people’s unique fingerprinting, different IoT devices exhibit different RFF which can be used for identification and authentication. In this paper, the structure of IoT device identification is proposed, the key technologies such as signal detection, RFF extraction, and classification model is discussed. Especially, based on the random forest and Dempster-Shafer evidence algorithm, a novel ensemble learning algorithm is proposed. Through theoretical modeling and experimental verification, the reliability and differentiability of RFF are extracted and verified, the classification result is shown under the real IoT device environments.     

智慧能源体系信息通信技术构架及实施方案

基于社会经济发展、环境保护需求、产业政策引导等多方因素,智慧能源将为传统能源结构带来新一轮的巨变。现代信息通信技术(information communications technology,ICT)的飞速发展,为传统能源向智慧能源转型升级提供了强有力的技术支撑。整个智慧能源体系将以创新型的场景需求为导向,以跨界科技力量的深度加持为支撑,驱动整个能源及相关产业链的结构性升级。结合云计算、大数据、物联网(internet of things,IoT)、移动通信、人工智能、区块链等新兴技术,赋能传统能源体系,提出一种适用于智慧能源应用场景下的能源体系ICT构架,贯通能源体系的底层至顶层,实现智慧能源体系能量流、信息流和价值流的全面融合。     

大连“智慧海洋”示范工程启动

大连"智慧海洋"示范工程充分利用了沿海的便利条件，将现代化智能技术、信息处理技术与海洋装备、海洋活动相结合，以完善的海洋信息采集与传输体系为基础，运用工业大数据和互联网大数据技术，实现海洋资源共享、海洋活动协同，挖掘新需求，创造新价值。     

大数据时代移动终端界面设计创新趋势研究

目的研究移动终端界面设计创新趋势。方法通过分析大数据技术在移动终端界面设计中,对设计理念与设计方法的广泛影响,提出移动终端用户整合化、情感化、个性化的新需求。结论大数据时代的移动终端界面设计需具备创新的设计特征,包括简洁、有效的视觉呈现,自由、愉悦的情感体验以及个性化、多元化的定制体验,只有运用以上特征才能满足设计的创新需求。     

Knowledge-driven digital twin manufacturing cell towards intelligent manufacturing

Rapid advances in new generation information technologies, such as big data analytics, internet of things (IoT), edge computing and artificial intelligence, have nowadays driven traditional manufacturing all the way to intelligent manufacturing. Intelligent manufacturing is characterised by autonomy and self-optimisation, which proposes new demands such as learning and cognitive capacities for manufacturing cell, known as the minimum implementation unit for intelligent manufacturing. Consequently, this paper proposes a general framework for knowledge-driven digital twin manufacturing cell (KDTMC) towards intelligent manufacturing, which could support autonomous manufacturing by an intelligent perceiving, simulating, understanding, predicting, optimising and controlling strategy. Three key enabling technologies including digital twin model, dynamic knowledge bases and knowledge-based intelligent skills for supporting the above strategy are analysed, which equip KDTMC with the capacities of self-thinking, self-decision-making, self-execution and self-improving. The implementing methods of KDTMC are also introduced by a thus constructed test bed. Three application examples about intelligent process planning, intelligent production scheduling and production process analysis and dynamic regulation demonstrate the feasibility of KDTMC, which provides a practical insight into the intelligent manufacturing paradigm.     

大数据驱动的新零售博弈与品牌价值创新策略

目的 研究大数据驱动的新零售博弈中品牌价值创新的实践、策略与趋势.方法 通过对零售业数字化转型的国际趋势、阿里与京腾生态系之间的新零售格局进行梳理和总结,以体验经济时代的特征、品牌研究的理论与工具为线索,研究和分析我国大数据驱动下的品牌价值创新策略,以及变革和未来的发展趋势.结论 品牌内涵发展至"品牌即体验"阶段,数据成为了重要的战略资源,新的工具不断被开发,用以支持大数据驱动的品牌价值创新.企业逐步完成数字化转型,通过数据洞察新的商业机会,构建新的品牌战略,推动组织变革,创造新的品牌体验,从而成为新时代的强势品牌.     

Controller Placement in Software Defined Internet of Things Using Optimization Algorithm

The current and future status of the internet is represented by the upcoming Internet of Things (IoT). The internet can connect the huge amount of data, which contains lot of processing operations and efforts to transfer the pieces of information. The emerging IoT technology in which the smart ecosystem is enabled by the physical object fixed with software electronics, sensors and network connectivity. Nowadays, there are two trending technologies that take the platform i.e., Software Defined Network (SDN) and IoT (SD-IoT). The main aim of the IoT network is to connect and organize different objects with the internet, which is managed with the control panel and data panel in the SD network. The main issue and the challenging factors in this network are the increase in the delay and latency problem between the controllers. It is more significant for wide area networks, because of the large packet propagation latency and the controller placement problem is more important in every network. In the proposed work, IoT is implementing with adaptive fuzzy controller placement using the enhanced sunflower optimization (ESFO) algorithm and Pareto Optimal Controller placement tool (POCO) for the placement problem of the controller. In order to prove the efficiency of the proposed system, it is compared with other existing methods like PASIN, hybrid SD and PSO in terms of load balance, reduced number of controllers and average latency and delay. With 2 controllers, the proposed method obtains 400 miles as average latency, which is 22.2% smaller than PSO, 76.9% lesser than hybrid SD and 91.89% lesser than PASIN.     

Secure Multifactor Remote Access User Authentication Framework for IoT Networks

The term IoT refers to the interconnection and exchange of data among devices/sensors. IoT devices are often small, low cost, and have limited resources. The IoT issues and challenges are growing increasingly. Security and privacy issues are among the most important concerns in IoT applications, such as smart buildings. Remote cybersecurity attacks are the attacks which do not require physical access to the IoT networks, where the attacker can remotely access and communicate with the IoT devices through a wireless communication channel. Thus, remote cybersecurity attacks are a significant threat. Emerging applications in smart environments such as smart buildings require remote access for both users and resources. Since the user/building communication channel is insecure, a lightweight and secure authentication protocol is required. In this paper, we propose a new secure remote user mutual authentication protocol based on transitory identities and multi-factor authentication for IoT smart building environment. The protocol ensures that only legitimate users can authenticate with smart building controllers in an anonymous, unlinkable, and untraceable manner. The protocol also avoids clock synchronization problem and can resist quantum computing attacks. The security of the protocol is evaluated using two different methods: (1) informal analysis; (2) model check using the automated validation of internet security protocols and applications (AVISPA) toolkit. The communication overhead and computational cost of the proposed are analyzed. The security and performance analysis show that our protocol is secure and efficient.     

Intrusion Detection Based on Bidirectional Long Short-Term Memory with Attention Mechanism

With the recent developments in the Internet of Things (IoT), the amount of data collected has expanded tremendously, resulting in a higher demand for data storage, computational capacity, and real-time processing capabilities. Cloud computing has traditionally played an important role in establishing IoT. However, fog computing has recently emerged as a new field complementing cloud computing due to its enhanced mobility, location awareness, heterogeneity, scalability, low latency, and geographic distribution. However, IoT networks are vulnerable to unwanted assaults because of their open and shared nature. As a result, various fog computing-based security models that protect IoT networks have been developed. A distributed architecture based on an intrusion detection system (IDS) ensures that a dynamic, scalable IoT environment with the ability to disperse centralized tasks to local fog nodes and which successfully detects advanced malicious threats is available. In this study, we examined the time-related aspects of network traffic data. We presented an intrusion detection model based on a two-layered bidirectional long short-term memory (Bi-LSTM) with an attention mechanism for traffic data classification verified on the UNSW-NB15 benchmark dataset. We showed that the suggested model outperformed numerous leading-edge Network IDS that used machine learning models in terms of accuracy, precision, recall and F1 score.     

工业系统的智能交互模式及人因工效研究综述

随着物联网、CPS、大数据等技术的出现和发展,生产制造、航空驾驶、安全监控等工业系统已进入第四次工业革命的智能转型升级。目的 工业系统的智能交互模式与人因工效是人机协同共生的关键核心问题。方法 从工业制造的智能化转型、航空航天的人机协同、核电安全智能监控等多个重大行业背景出发,分析人—信息—物理系统智能交互的发展趋势;剖析工业智能背景下国内外人因工效测评技术、评价模型及多源指标关联性研究进展;梳理智能化工业系统的信息表征发展趋势及多通道交互研究方法。结论 从国内外研究综述表明,需要从多学科交叉融通的角度构建智能化工业系统的人机交互研究体系,这将极大地改善系统中的人（任务执行者）获取信息、知识推理、判断决策的认知绩效,达成智能交互的人机物闭环,实现人（自然人、机器人）、信息系统、物理系统的充分感知融合,即人机协同共生模式。