Building an Intelligent Home Space for Service Robot Based on Multi-Pattern Information Model and Wireless Sensor Networks

This paper is concerned with constructing a prototype intelligent home environment for home service robot. In this environment, multi-pattern information can be represented by some intelligent artificial marks. Light-packs service robots can provide reliable and intelligent service by interacting with the environment through the wireless sensor networks. The intelligent space consists the following main components: smart devices with intelligent artificial mark;home server that connects the smart device and maintains the information through wireless sensor network;and the service robot that perform tasks in collaboration with the environment. In this paper, the multi-pattern information model is built, the construction of wireless sensor networks is presented, the smart and agilely home service is introduced. Fi- nally, the future direction of intelligent space system is discussed.

The ZigBee Based Wireless Sensor and Actor Network in Intelligent Space Oriented to Home Service Robot

In the study of intelligent space oriented to home service robot, an important technology is how to construct an communication network which has the characters of high reliability and easy building. In this paper, based on the characteristics of ZigBee protocol, ZigBee technology is used to construct a wireless sensor and actor network. Several intelligent services based on ZigBee wireless sensor and actor network are shown to certify the reliability of this communication network. ZigBee wireless sensor and actor network builds an information bridge for the components in the intelligent space, the spatially distributed devices are connected together seamlessly. With this network, robot can share the mass information in the intelligent space and improve its performance with 'light-packs', devices in intelligent space, such as lamp, curtain can be controlled autonomously.

Zigbee Based Wireless Sensor and Actuator Network for Service Robot Intelligent Space

Wireless sensor and actuator network is the key technology of service robot intelligent space. This paper is concerned with design and implementation of a ZigBee based wireless sensor and actuator network (hereinafter referred to as ZWSAN), which has been applied in our service robot intelligent space successfully. Firstly, a simplified ZigBee stack applied to ZWSAN is proposed and the primitives of the stack are illustrated after a short overview of ZigBee protocols. Then the implementation of hardware module and software stack is introduced in detail as well as several representative devices integrated into ZWSAN, including environmental sensors for environmental perception, home devices controllers for device control, embedded speech recognition module for speech control, IMU module for abnormal behaviors detection and laser robot control for service robot navigation. An application example is described to demonstrate how the devices in ZWSAN to provide service cooperatively. Finally, we conclude this paper and discuss the future directions.

Implementation of Intelligent Network Service Logic

According to the features of Intelligent Network(IN)service logic,a method based ondata table to implement IN Service Logic is proposed.The method supports dynamic additionof IN service logic.

Novel Path Counting-Based Method for Fractal Dimension Estimation of the Ultra-Dense Networks

Next-generation networks,including the Internet of Things(IoT),fifth-generation cellular systems(5G),and sixth-generation cellular systems(6G),suf-fer from the dramatic increase of the number of deployed devices.This puts high constraints and challenges on the design of such networks.Structural changing of the network is one of such challenges that affect the network performance,includ-ing the required quality of service(QoS).The fractal dimension(FD)is consid-ered one of the main indicators used to represent the structure of the communication network.To this end,this work analyzes the FD of the network and its use for telecommunication networks investigation and planning.The clus-ter growing method for assessing the FD is introduced and analyzed.The article proposes a novel method for estimating the FD of a communication network,based on assessing the network’s connectivity,by searching for the shortest routes.Unlike the cluster growing method,the proposed method does not require multiple iterations,which reduces the number of calculations,and increases the stability of the results obtained.Thus,the proposed method requires less compu-tational cost than the cluster growing method and achieves higher stability.The method is quite simple to implement and can be used in the tasks of research and planning of modern and promising communication networks.The developed method is evaluated for two different network structures and compared with the cluster growing method.Results validate the developed method.

Service Customized Space-Air-Ground Integrated Network for Immersive Media: Architecture, Key Technologies, and Prospects

The space-air-ground integrated network(SAGIN) is regarded as the key approach to realize global coverage in future network and it reaches broad access for various services. Being the new paradigm of service, immersive media(IM) has attracted users’ attention for its virtualization, but it poses challenges to network performance, e.g. bandwidth, rate, latency. However, the SAGIN has limitations in supporting IM services, such as 4 K/8 K video, virtual reality, and interactive games. In this paper, a novel service customized SAGIN architecture for IM applications(SAG-IM) is proposed, which achieves content interactive and real-time communication among terminal users. State-of-the-art research is investigated in detail to facilitate the combination of SAGIN and service customized technology, which provides endto-end differentiated services for users. Besides, the functional components of SAG-IM contain the infrastructure layer, perception layer, intelligence layer, and application layer, reaching the capabilities of intelligent management of the network. Moreover, to provide IM content with ultra-high-definition and high frame rate for the optimal user experience, the promising key technologies on intelligent routing and delivery are discussed. The performance evaluation shows the superiority of SAG-IM in supporting IM service.Finally, the prospects in practical application are high-lighted.

Machine learning-based zero-touch network and service management:a survey

The exponential growth of mobile applications and services during the last years has challenged the existing network infrastructures.Consequently,the arrival of multiple management solutions to cope with this explosion along the end-to-end network chain has increased the complexity in the coordinated orchestration of different segments composing the whole infrastructure.The Zero-touch Network and Service Management(ZSM)concept has recently emerged to automatically orchestrate and manage network resources while assuring the Quality of Experience(QoE)demanded by users.Machine Learning(ML)is one of the key enabling technologies that many ZSM frameworks are adopting to bring intelligent decision making to the network management system.This paper presents a comprehensive survey of the state-of-the-art application of ML-based techniques to improve ZSM performance.To this end,the main related standardization activities and the aligned international projects and research efforts are deeply examined.From this dissection,the skyrocketing growth of the ZSM paradigm can be observed.Concretely,different standardization bodies have already designed reference architectures to set the foundations of novel automatic network management functions and resource orchestration.Aligned with these advances,diverse ML techniques are being currently exploited to build further ZSM developments in different aspects,including multi-tenancy management,traffic monitoring,and architecture coordination,among others.However,different challenges,such as the complexity,scalability,and security of ML mechanisms,are also identified,and future research guidelines are provided to accomplish a firm development of the ZSM ecosystem.

Intelligence service binding architecture for interoperability between home network devices

Existing home devices in home network provides only independent services limited on a homogeneous protocol and/or do not fully support an intelligent service provided by cooperating among heterogeneous protocol devices. This paper proposes an intelligent and integrated service binding architecture which allow the users to figure out the status of devices and to cooperate among home network devices regardless of supported protocols or operational characteristics.

Study on Cognitive Optical Network Structure and Self-optimization with the Application of Artificial Intelligence Technology

Cognitive optical network is the intermediate to combine artificial intelligence technology with network,and also the important network technology to promote network intelligence level constantly.In the paper,it analyzes the cognitive optical network structure with the application of artificial intelligence technology by starting from the basic conditions of cognitive network and cognitive optional network on the basis of fully understanding the connotation of cognitive network and cognitive optical network,and explores its self-governance functions,so as to better realize the self-optimization and self-configuration of network.

Mean Opinion Score Estimation for Mobile Broadband Networks Using Bayesian Networks

Mobile broadband(MBB)networks are expanding rapidly to deliver higher data speeds.The fifth-generation cellular network promises enhanced-MBB with high-speed data rates,low power connectivity,and ultralow latency video streaming.However,existing cellular networks are unable to perform well due to high latency and low bandwidth,which degrades the performance of various applications.As a result,monitoring and evaluation of the performance of these network-supported services is critical.Mobile network providers optimize and monitor their network performance to ensure the highest quality of service to their end-users.This paper proposes a Bayesian model to estimate the minimum opinion score(MOS)of video streaming services for any particular cellular network.The MOS is the most commonly used metric to assess the quality of experience.The proposed Bayesian model consists of several input data,namely,round-trip time,stalling load,and bite rates.It was examined and evaluated using several test data sizes with various performance metrics.Simulation results show the proposed Bayesian network achieved higher accuracy overall test data sizes than a neural network.The proposed Bayesian network obtained a remarkable overall accuracy of 90.36%and outperformed the neural network.

Three-Dimensional Dynamic Based Borrowing Scheme for Wireless Cellular Networks

Mobility metrics of wireless networks such as link availability, number of neighboring nodes, link duration, link state, and link stability make it difficult to provide a node with quality of services guarantee. In previous research on Quality of Service (QoS) for cellular networks especially for handling handoff connections, the design was based on a flat 2D hexagon cells. However, in reality Base Station antenna coverage is in a 3D space and there exists a blind spot;the area which is just above and bellow the radiated antenna. In this paper we introduce the concept of Blind Spot (BS) in which there is no signals to initiate a call or accepting a handoff one. In BS, the signal power equal zero. Even if there is enough bandwidth to initiate or accept a handoff call, it will be blocked or dropped respectively. We present an implementation of Static Borrowing Scheme (SBS) and we extend the dynamic-rate based borrowing scheme [1] into 3-Dimentional structure and call it 3-Dimensional Dynamic Based Borrowing Scheme (3D DBBS). The proposed new technique for resource sharing is to ensure the continuity for both originating and handoff connections in 3-D cellular networks based on Dynamic-Based Borrowing Scheme (3D BBS). This technique aims to minimize the blocking probability of the originating calls by minimizing the dropping probability of the handoff requests and maximizing the channel utilization. The results revealed that 3D DBBS outperformed the static based schemes by 5% on average even when the blind spot of the base station antenna is taken into consideration. When moving to a 3D space, the results of the simulation showed the 3D DBBS outperformed the static scheme by 2% on average. As a result, considering nodes in a 3D space will have better QoS guarantee as the blocking and dropping probabilities are decreased. Thus, the bandwidth utilization is increased.

Key Technologies and Development Trends in Advanced Intelligent Sawing Equipments

As a starting point in equipment manufacturing,sawing plays an important role in industrial production.Intelligent manufacturing equipment is an important carrier of intelligent manufacturing technologies.Due to the backwardness of intelligent technology,the comprehensive performance of sawing equipments in China is obviously different from that in foreign countries.State of the art of advanced sawing equipments is investigated along with the technical bottleneck of sawing machine tool manufacturing,and a new industrial scheme of replacing turning-milling by sawing is described.The key technologies of processing-measuring integrated control,multi-body dynamic optimization,the collaborative sawing network framework,the distributed cloud sawing platform,and the self-adapting service method are analyzed;with consideration of the problems of poor processing control stableness,low single machine intelligence level,no on-line processing data service and active flutter suppression of sawing with wide-width and heavy-load working conditions.Suggested directions for further research,industry implementation,and industry-research collaboration are provided.

THE STUDY OF SCP OVERLOAD CONTROL IN MULTI-SERVICE ENVIRONMENT

This paper first gives a SCP abstract model, then SCP’s overload detection and maximum processing capability are discussed quantitatively. Based upon dynamic adjustment, a new two-level SCP overload control algorithm is proposed. Theoretical analysis and simulation prove the algorithm’s effectiveness and fairness.

双目标优化与生成对抗网络结合的框架结构阻尼器布置方案智能设计方法

为实现框架结构的阻尼器智能化布置,结合减震设计原理和智能算法,采用双目标优化算法和生成对抗网络算法分别进行阻尼器竖向和水平智能布置研究,并将该方法应用到两个框架结构减震设计工程案例中。在框架结构减震设计中,采用双目标优化算法进行阻尼器竖向布置,并与逐层逼近法、工程师设计和非减震设计进行对比,结果表明,采用该优化算法得到的阻尼器竖向布置方案能有效降低层间位移角和楼层加速度,提高结构的抗震性能。在确定各楼层的阻尼器数量后,利用训练好的生成对抗网络生成模型,可快速、自动地选择和确定各楼层阻尼器的平面安装位置,生成的平面布置与工程师设计的平面布置在相似性差异度综合评价指标上小于临界值0.1,说明两者相似度较高,且有利于提高原结构的抗扭能力。将双目标优化算法与生成对抗网络相结合,不仅能满足框架结构的减震性能目标,而且可实现阻尼器布置方案的智能设计,提升减震工程设计效率。

智能算法的亚群优化策略综述

群智能算法的优化是提升群智能算法性能的一个主要途径,随着群智能算法越来越广泛地运用到各类模型优化、生产调度、路径规划等问题中,对智能算法性能的要求也越来越高。亚群策略作为一种优化群智能算法的重要手段,能够灵活地平衡算法的全局勘探能力和局部开发能力,已经成为群智能算法的研究热点之一。为了促进亚群优化策略的发展和应用,对动态亚群策略、基于主从范式的亚群策略和基于网络结构的亚群策略进行了详细调查,阐述了各类亚群策略的结构特点、改进方式和应用场景。最后,总结了亚群策略目前存在的问题以及未来的研究趋势和发展方向。

大模型融入云平台,信息化走向数智化

随着人工智能的快速发展,大模型已逐渐发挥其关键作用,成为驱动企业数字化转型的重要力量。主要探寻了大模型崛起引发的众多变革,回溯了人工智能的发展轨迹,分析了自建基础大模型所面临的挑战,强调引入基础大模型提供方需要与垂直行业企业联手,合作开发行业大模型。针对中小型企业在开发行业大模型时所面临的困扰,提出“模型即服务”及其相关工具链可以通过协助微调形成专有企业模型的观点;探讨了大模型兴起对云服务产生的变革;对云网协同、算网融合以及人工智能加速数智化发展进行了深入分析。在数字经济时代的背景下,进一步分析了人工智能如何赋能新一代信息技术创新。目前正处于国际经济发展调整期、信息化向数字化的演进期及网络技术创新的加速期,大宽带、大连接、大数据、大平台、大模型、大智能正在快速地融合发展。

基于生成对抗网络的自动框架结构设计

本文在结构设计中引入人工智能方法,通过提出建筑结构特征表达方法,构建以生成对抗网络为核心的框架结构自动设计方法。在数据前处理阶段,通过对建筑结构图纸分析,提出建筑特征表达方法与结构特征表达方法。在构建算法模型阶段,实现在有限的数据量下训练生成对抗算法学习框架结构布置,构建了依据建筑信息自动生成含有构件尺寸信息的框架结构自动布置模型,并提出了评价指标量化评价模型的结构设计能力。在案例中使用本文构建的框架结构自动布置模型完成一栋实际建筑的自动设计,验证了本文提出方法对结构设计效率的提高。