元宇宙的发展

元宇宙近几年来骤然火爆起来,各个行业争先恐后加入元宇宙的发展浪潮中来。元宇宙由于5G、VR、AR、AI、区块链等技术发展扩展了人们对现实与未来空间的渴望,同时“元宇宙概念”带来的投资机会,使人们对元宇宙巨大的机遇和革命性的作用都非常期待。从目前来看,元宇宙初步体现在游戏娱乐行业、社交、消费、数字孪生等方面。国内外的学者尝试对元宇宙进行定义,并从多个方面对元宇宙发展方式进行阐述。元宇宙近两年开始在各个行业快速崛起,但各个行业并没有一个清晰的发展方向,那么什么是元宇宙?元宇宙会走向哪里?会带来什么?这里从客观角度科技发展的趋势,从主观角度人类自我发展的内在驱动,提出新的元宇宙定义,在此基础上,提出元宇宙需要经过三个发展阶段,即虚拟阶段、物机互融阶段、N平行宇宙阶段。同时对各阶段需要支撑的科学技术要求进行阐述,举例并给出结论,希望能为元宇宙的发展带来一些启示。     

元宇宙下的控制与决策综述

“元宇宙”概念现已得到学者的广泛关注.文中首先分析并介绍元宇宙的相关概念,并将其与虚拟世界、数字孪生等相似概念进行区分,梳理和阐述元宇宙及其建立所需技术的发展历程,对未来元宇宙的构建层次提出假设并给出各个构建层次的各种技术支撑.然后,从控制科学与工程学科的角度,梳理总结控制与决策理论的发展历程,并展望在元宇宙背景下结合云计算、人工智能2.0、工业元宇宙、区块链等技术的控制与决策理论的发展与应用.最后,讨论并展望控制与决策理论以及元宇宙构建中可能遇到的关键挑战与开放性问题,为未来元宇宙相关研究和产业应用提供启发与参考.     

基于ARM的智能仪器人机交互系统设计

针对电力行业智能仪器设计了一种通用的人机交互系统,基于ARM平台对系统硬件进行了模块化设计,详细阐述了系统软件设计程序流程和显示结构,实际使用证明在该ARM硬件平台和软件结构基础上,仅对显示和通信子程序做适当修改,便能运用到各种智能仪器上,节省开发周期,降低开发成本,性能稳定,对智能仪器仪表产品开发具有重要借鉴意义.     

元宇宙及其应用概述

元宇宙可以被视为虚拟现实的一个更高级别的概念,它是模拟的三维虚拟世界,用户可以在其中以真实的方式交互并创建内容。元宇宙的应用非常广泛,可以被用来进行虚拟购物、学习、社交、游戏等各种活动,甚至能够扩展到虚拟现实交互式电影和其他娱乐形式中。总体而言,元宇宙被认为将会成为未来互联网的一个重要方向,弥合虚拟与现实之间的鸿沟,使人们能够以全新的方式进行数字体验。本文讲述了元宇宙的内涵、概念及技术方法,多角度分析其应用和发展。     

工业元宇宙—现实世界与虚拟世界互通的桥梁北大核心

2022年两会上,元宇宙再度成为热词。当前,在各行各业中,不断出现“XX元宇宙”的词汇,诸如:金融元宇宙、城市元宇宙、教育元宇宙、战场元宇宙、工业元宇宙、商贸元宇宙、大健康元宇宙……等等。在工业领域,元宇宙则是摇身一变,成为现实世界与虚拟世界互通的桥梁。工业元宇宙的概念成为继工业互联网之后,影响企业数字化转型的新动能。从初识元宇宙轮廓,再识工业元宇宙,工业元宇宙推动智能制造,元宇宙带来的变化与工业元宇宙应用实例等就工业元宇宙作一阐述。     

元宇宙赋能在线教学模式新形态探究

元宇宙赋能在线教育以虚实融合、数智融合、人机融合的技术优势实现沉浸交互式学习、智能个性化教学和开放共享式教学。针对元宇宙虚实相生、镜像连接、可持续发展、开放共享等特点,提出通过情境化教学模式的营造实现具身教学认知,并以混合式教学模式构筑线上线下深度融合,实现全方位、多元化、数字化人才培养,有效解决现阶段以互联网为媒介载体的远程在线教学中时空割裂、不利于监管、学习孤独感强等弊病。     

计算和智能

大约一年多以前,作者发表了拙作《智能机理和软计算》(l),曾引起不少同行的兴趣,希望进一步推     

基于“站线台户”数据基座的配电网元宇宙探究

深挖电力企业数据价值,延长各类业务数据的使用寿命,是电力企业数字化转型的重要环节。但是在开展过程中,面临着跨专业数据融合难、海量数据接入后检索与应用难、人工智能盲盒效应带来不确定性的问题。为解决以上问题,本文提出了将配电网元宇宙应用于日常运维管理实践的观点。借助元宇宙的直观可视和多元化操作优势,将多维数据接入虚拟现实形成数字孪生,添加工作人员日常监管校验环节,形成具备有数据汇总、监管和成果输出的配电网元宇宙。通过不断完善可溯源的人机协作模式,让新技术与人的社会活动紧密连接,在完成数据的融合和价值挖掘的同时,提供了一种人员参与监管,实现溯源矫正的新方法。最后通过站线台户数据基座的应用实践,完成配电网元宇宙应用的探究工作。     

新信息环境下的在线教育元宇宙建模探索

针对在线教育的时空隔离障碍及自主成长性缺失等问题,分析总结在线教育当前的热点领域自适应学习域的研究成果,勾勒出自适应学习域中的相关对象模型,依据MDA工业标准给出对象模型相应的UML类图实现,令其有向下依据实时数据自我调节成长、向上可被封装为云服务的能力,最终将其嵌入交互性逼近真实、闭环且能随着技术进步不断成长的新信息环境形成在线教育元宇宙。     

基于机器学习的人工智能语义分析方法

针对中国移动河南公司对敏感数据的金库管控现状,设计采用机器学习的框架数据,结合挖掘算法和贝叶斯算法,并运用中文分词的原理形成人工智能语义分析方法,在对敏感操作源头进行操作时,可以有效地规范和约束行为,增强对人为访问敏感数据时的甄别及管控能力,进而为各类敏感数据提供保护措施和精准的前提要素。     

A human-computer interactive method for projected clustering

Clustering is a central task in data mining applications such as customer segmentation. High-dimensional data has always been a challenge for clustering algorithms because of the inherent sparsity of the points. Therefore, techniques have recently been proposed to find clusters in hidden subspaces of the data. However, since the behavior of the data can vary considerably in different subspaces, it is often difficult to define the notion of a cluster with the use of simple mathematical formalizations. The widely used practice of treating clustering as the exact problem of optimizing an arbitrarily chosen objective function can often lead to misleading results. In fact, the proper clustering definition may vary not only with the application and data set but also with the perceptions of the end user. This makes it difficult to separate the definition of the clustering problem from the perception of an end-user. We propose a system, which performs high-dimensional clustering by cooperation between the human and the computer. The complex task of cluster creation is accomplished through a combination of human intuition and the computational support provided by the computer. The result is a system, which leverages the best abilities of both the human and the computer for solving the clustering problem.     

Machine learning in artificial intelligence

Among several forms of learning, learning concepts from examples is the most common and best understood. In this paper some approaches to learning concepts from examples are reviewed. In particular those approaches that are currently most important with respect to practical applications (learning decision trees and if-then rules), or likely to become very important in the near future (Inductive Logic Programming as a form of relational learning) are discussed.     

Application of artificial intelligence based on deep learning in breast cancer screening and imaging diagnosis

Neural Computing and Applications - In recent years, with the change of lifestyle in Europe and America, the incidence of breast cancer in Chinese women is increasing. In order to find the model of...     

Functional motion detection based on artificial intelligence

The Journal of Supercomputing - Sports injuries can be a major problem for athletes. Therefore, sports injury protection has become a key focus of attention in sports and medical circles. With...     

Hybrid artificial intelligence approach based on metaheuristic and machine learning for slope stability assessment: A multinational data analysis

Slope stability assessment is a critical research area in civil engineering. Disastrous consequences of slope collapse necessitate better tools for predicting their occurrences. This research proposes a hybrid Artificial Intelligence (AI) for slope stability assessment based on metaheuristic and machine learning. The contribution of this study to the body of knowledge is multifold. First, advantages of the Firefly Algorithm (FA) and the Least Squares Support Vector Classification (LS-SVC) are combined to establish an integrated slope prediction model. Second, an inner cross-validation with the operating characteristic curve computation is embedded in the training process to reliably construct the machine learning model. Third, the FA, an effective and easily implemented metaheuristic, is employed to optimize the model construction process by appropriately selecting the LS-SVM's hyper-parameters. Finally, a dataset that contains 168 real cases of slope evaluation, recorded in various countries, is used to establish and confirm the proposed hybrid approach. Experimental results demonstrate that the new hybrid AI model has achieved roughly 4% improvement in classification accuracy compared with other benchmark methods.     

A lightweight automatic sleep staging method for children using single-channel EEG based on edge artificial intelligence

World Wide Web - With the development of telemedicine and edge computing, edge artificial intelligence (AI) will become a new development trend for smart medicine. On the other hand, nearly...     

Automated,interactive, and traceable domain modelling empowered by artificial intelligence

Software and Systems Modeling - Model-Based Software Engineering provides various modelling formalisms for capturing the structural, behavioral, configuration, and intentional aspects of software...     

路径约束下基于人工智能的智慧航空旅游动态寻径方法

为了提高智慧航空旅游动态寻优控制能力,提出一种基于人工智能的路径约束下智慧航空旅游动态寻径方法。采用多目标进化方法进行智慧航空旅游动态寻径的路径约束控制,结合粒子群方法进行智慧航空旅游动态寻径的路径优化选择,采用多目标Pareto映射方法进行智慧航空旅游的路径规划设计,结合信息素导引方法进行智慧航空旅游动态寻径的自适应控制,构建智慧航空旅游动态寻径的蚁群滤波模型,根据蚁群路径约束寻优方法构建智慧航空旅游动态寻径的人工智能算法,实现智慧航空旅游动态寻径的人工智能控制和自适应寻优。仿真结果表明,采用该方法进行智慧航空旅游动态寻径的自适应性能较好,路径优化控制能力较强。