Newspaper coverage of artificial intelligence: A perspective of emerging technologies

The focus of the study is on how newspapers have covered artificial intelligence (AI) over the past decades. Analyzing 1776 news articles culled from four mainstream newspapers (i.e., the New York Times, Washington Post, the Guardian, and USA Today), the study examined the general landscape of media coverage as well as media framing of the topic through a mixed methodology (i.e., automatic content analysis and manual coding). Fourteen major topics (e.g., regulation & policy, risk & weapon) emerged from the accumulated articles. Furthermore, the study found that journalists have used different framing devices, including lexical compounds and argumentation patterns, to frame AI as a sophisticated, powerful, and value-laden issue. Also, different actors (e.g., research communities, governments, business sectors) combined to constitute a complex network in the media discourses.     

人工智能技术在应用中的安全风险与管控研究

作为新型通用技术之一,人工智能正与实体经济逐步融合,推动社会经济各领域向智能化转型,但围绕人工智能技术的安全性威胁问题也日益凸显。本文对人工智能技术在应用中面临的主要安全风险进行梳理分析,并对现有管控政策和措施进行梳理概括,在此基础上,针对基础电信企业应对人工智能安全风险提出初步建议。     

电力系统自动化中人工智能的应用

人工智能应用于电力系统自动化中,既是电力系统自动化相关产业发展的一种趋势,也是我国电力系统自动化在时代发展中的一种进步的标志。本论文首先对人工智能在电力系统自动化中的应用趋势进行探讨,主要包括人工智能运用的普遍化、人工智能技术更新的快速性两种。此外,本论文也对人工智能在电力系统自动化中的应用优势进行探讨,包括提高电电力系统设备效率、降低操作误差、提高对设备的控制效果以及对相关参数调节的便利性。最后,本论文对人工智能在电力系统自动化中的应用进行总结,包括在电力设备中的应用、电力控制中的应用、电力保护中的应用以及在电力系统中的应用四个方面。     

电力系统自动化中人工智能的应用

人工智能应用于电力系统自动化中,既是电力系统自动化相关产业发展的一种趋势,也是我国电力系统自动化在时代发展中的一种进步的标志。本论文首先对人工智能在电力系统自动化中的应用趋势进行探讨,主要包括人工智能运用的普遍化、人工智能技术更新的快速性两种。此外,本论文也对人工智能在电力系统自动化中的应用优势进行探讨,包括提高电电力系统设备效率、降低操作误差、提高对设备的控制效果以及对相关参数调节的便利性。最后,本论文对人工智能在电力系统自动化中的应用进行总结,包括在电力设备中的应用、电力控制中的应用、电力保护中的应用以及在电力系统中的应用四个方面。     

On recommendation-aware content caching for 6G: An artificial intelligence and optimization empowered paradigm

Recommendation-aware Content Caching (RCC) at the edge enables a significant reduction of the network latency and the backhaul load, thereby invigorating ubiquitous latency-sensitive innovative services. However, the effectiveness of RCC strategies is highly dependent on explicit information as regards subscribers’ content request patterns, the sophisticated caching placement policy, and the personalized recommendation tactics. In this article, we investigate how the potentials of Artificial Intelligence (AI) and optimization techniques can be harnessed to address those core issues and facilitate the full implementation of RCC for the upcoming intelligent 6G era. Towards this end, we first elaborate on the hierarchical RCC network architecture. Then, the devised AI and optimization empowered paradigm is introduced, whereas AI and optimization techniques are leveraged to predict the users’ content preferences in real-time situations with the assistance of their historical behavior data and determine the cache pushing and recommendation decision, respectively. Through extensive case studies, we validate the effectiveness of AI-based predictors in estimating users’ content preference and the superiority of optimized RCC policies over the conventional benchmarks. At last, we shed light on the opportunities and challenges in the future.     

人工智能与经济发展探究

人工智能经过50多年的发展,已经从最开始的理论研究走向了市场,对社会、经济、科技的发展产生了极大的推动作用,人工智能应用于经济发展已然成为21世纪的核心.文章主要围绕人工智能与经济发展、劳动就业、国际分工展开,探讨人工智能在时代发展下的价值体现.     

大数据和人工智能时代的情报分析和技术探索

在深入梳理现代情报分析六大关键问题和理想状态的基础上,结合大数据和人工智能技术近10年的跨越式发展,针对目前大数据和人工智能技术应用于情报分析的主要认识误区,详细分析了其用于情报分析领域的六大挑战和所需7项关键支撑技术,并提出了大数据和人工智能基础上的新型情报分析技术体系架构模型和情报生产使用流程。最后,对未来情报界相关系统和工作流程建设提出了四个方面的建议。     

人工智能在广播电视行业中的应用

目前人工智能已经在广播电视行业有所应用并取得了实效,据此采取综合分析、文献分析等方法,对人工智能的具体应用展开了分析,基本明确了人工智能在内容采编、生产、存储、分发、运行维护等方面的价值作用以及具体应用方法,仅供参考.     

Application of artificial intelligence in mobile communication:challenge and practice

The research and application progress in mobile communication,and points out its obstacle for improving the performance of mobile communication system were summarized.A new approach for reducing the gap between the practical and the ideal network performance was put forward creatively,which included the artificial intelligence reconstruction for performance outer loop part,the traditional adaptation or optimization for performance inner loop part,and the optimal cooperation between the two parts.The effectiveness of this approach was proved by the several successful applications.Finally,it pointed out that in order to meet the severe demands of mobile communication system for the “stable” “accurate” and “fast” artificial intelligence solution,and make the mobile network automatic,intelligent and wise,in addition to the excellent performance of the artificial intelligence reconstruction scheme itself,there must also be a feedback closed-loop system architecture based on the big data analysis and analog system,which is the key path to achieve this target.     

浅谈人工智能与机器人的发展趋势

近几十年来,随着时代的飞速发展,人工智能作为计算机学科的一个分支,已经得到了很广泛的应用.人工智能与机器人的技能发展逐渐渗入高中生学习范围之中.本文拟从人工智能的起源与发展经历的几个阶段,对人工智能在机器人中的应用进行分析与阐述.     

计算机网络中大数据与人工智能技术的应用

新时期计算机网络中的大数据与人工智能技术,广泛运用于生活工作中,在为社会大众提供便利的同时也成为一把双刃剑,带来了诸多弊端,比如信息泄露、数据资源造假等问题,如何在计算机网络中合理运用大数据与人工智能技术,成为相关工作人员的研究重点.互联网走进千家万户,在一定程度上拉近了民众距离,使其打开看见新世界的窗户,大数据与人工...     

人工智能在电视人机交互中的应用及相关分析

本文分析了人工智能电视中人机语音交互的基本优势,研究了语音对话、远场语音等语音交互的重要技术,探讨了人工智能语音交互应用在噪声抑制、远距离交互的识别准确率、回声消除能力、全方位感知定位精度等方面的不足.同时对基于语音交互的内容提供、智能化和个性化内容推荐等人机内容交互进行分析,思考人工智能在电视人机交互中的发展前景,希...     

人工智能技术研究及未来智能化信息服务体系的思考

人工智能、认知计算、决策支持技术的概念及研究已经跨出实验室,进入真正的实用阶段,其现实价值超过了技术研究者最初的认识,其本质是对信息、数据进行加工生产的技术,而这种生产加工不但可以给人们提供更加便捷的生活,还将对未来人们的生产、生活方式产生根本性的影响,对未来国家经济生活的运行方式、未来社会的组织结构产生深远的影响.首先介绍了人工智能技术的基本概念,然后研究了人工智能技术对未来经济生活的重要意义,人工智能技术开发、积累、复用、平台化的特征及其所面临的问题,最后初步分析了运营商接应人工智能技术研究及应用策略的思考.     

构建WebGIS和人工智能技术的防震综合管理系统

作为对人类人身和财产危害最严重的自然灾害,地震灾害的预防和管理越来越受到重视。伴随着科技的不断发展和进步,处在互联网时代的人们利用各种先进技术来应对地震灾害,其中地理信息系统发展也趋向于结合网络技术的Web空间数据浏览、查询及分析等功能,从而逐渐形成了基于网络技术的地理信息系统(WebGIS)。WebGIS平台的出现将空间数据的共享变为现实,对防震减灾工作提供了非常大的帮助。     

Fusion of artificial intelligence and game theory for resource allocation in non-orthogonal multiple access-assisted device-to-device cooperative communication

Device-to-device (D2D) communication offers a low-cost paradigm where two devices in close proximity can communicate without needing a base station (BS). It significantly improves radio resource allocation, channel gain, communication latency, and energy efficiency and offers cooperative communication to enhance the weak user's network coverage. The cellular mobile users (CMUs) share the spectral resources (e.g., power, channel, and spectrum) with D2D mobile users (DMUs), improving spectral efficiency. However, the reuse of radio resources causes various interferences, such as intercell and intracell interference, that degrade the performance of overall D2D communication. To overcome the aforementioned issues, this paper presents a fusion of AI and coalition game for secure resource allocation in non-orthogonal multiple access (NOMA)-based cooperative D2D communication. Here, NOMA uses the successive interference cancellation (SIC) technique to reduce the severe impact of interference from the D2D systems. Further, we utilized a coalition game theoretic model that efficiently and securely allocates the resources between CMUs and DMUs. However, in the coalition game, all DMUs participate in obtaining resources from CMUs, which increases the computational overhead of the overall system. For that, we employ artificial intelligence (AI) classifiers that bifurcate the DMUs based on their channel quality parameters, such as reference signal received power (RSRP), received signal strength indicator (RSSI), signal-to-noise ratio (SNR), and channel quality indicator (CQI). It only forwards the DMUs that have better channel quality parameters into the coalition game, thus reducing the computational overhead of the overall D2D communication. The performance of the proposed scheme is evaluated using various statistical metrics, for example, precision score, accuracy, recall, F1 score, overall sum rate, and secrecy capacity, where an accuracy of 99.38% is achieved while selecting DMUs for D2D communication.     

人工智能在无人作战飞机上的应用与展望

在未来高对抗环境下,夺取空中优势至关重要,无人作战飞机（UCAV）的参战将实现飞行员零伤亡。人工智能（AI）作为无人作战飞机未来发展的颠覆性技术之首,将从力量倍增器或作战支持转变为真正的人类替代者。从AI对UCAV的作用与意义出发,介绍了国外UCAV相关的人工智能项目的研究进展,总结了UCAV相关的AI智能算法,分析了UCAV的发展趋势。随着人工智能技术、机载处理技术以及传感器技术的进步,UCAV将在未来战争中实现智能协同、智能任务与智能飞行,成为空战的主力。     

Public perceptions on artificial intelligence driven disaster management: Evidence from Sydney,Melbourne and Brisbane

In recent years, artificial intelligence (AI) is being increasingly utilised in disaster management activities. The public is engaged with AI in various ways in these activities. For instance, crowdsourcing applications developed for disaster management to handle the tasks of collecting data through social media platforms, and increasing disaster awareness through serious gaming applications. Nonetheless, there are limited empirical investigations and understanding on public perceptions concerning AI for disaster management. Bridging this knowledge gap is the justification for this paper. The methodological approach adopted involved: Initially, collecting data through an online survey from residents (n = 605) of three major Australian cities; Then, analysis of the data using statistical modelling. The analysis results revealed that: (a) Younger generations have a greater appreciation of opportunities created by AI-driven applications for disaster management; (b) People with tertiary education have a greater understanding of the benefits of AI in managing the pre- and post-disaster phases, and; (c) Public sector administrative and safety workers, who play a vital role in managing disasters, place a greater value on the contributions by AI in disaster management. The study advocates relevant authorities to consider public perceptions in their efforts in integrating AI in disaster management.     

基于物联网和人工智能技术的智能行李安检系统研究

无论是机场还是车站,安全检查工作面向的都是全体的乘客,而采用传统的检测方式,无法满足现代乘机人、乘车人的流动需求。物联网和人工智能技术的应用能实现智能安检,有助于提升我国的整体检测质量。文章提出一种基于物联网和人工智能技术的智能行李安检系统,希望可促进我国安检工作的质量,提高通行效率,促进行业发展。     

边缘智能在轨道交通中的应用：前景与展望

边缘智能作为一项新兴技术,正受到国内外学者的广泛关注,其作为人工智能技术与边缘计算技术的结合,有望促进人工智能技术在各行业的部署,加速产业智能化进程。该文首先介绍了边缘智能技术的基本原理、系统架构及其比较优势,梳理了边缘智能技术的国内外研究现状;分析了边缘智能在轨道交通建设工程、运维调度、智能控制、改造升级的全生命周期应用前景,详述了边缘智能技术在轨道交通过程管理控制、建设现场数据采集分析、信息共享、智能运维、智能调度、自动驾驶系统、列车协同控制及改造升级等全生命周期中的赋能作用。该文随后设计与实现了轨道交通智能运行控制为背景下的边缘智能平台,测试基于深度学习和强化学习的边缘智能应用的功能及性能。最后,归纳了边缘智能技术在轨道交通领域应用的问题与挑战。该文的研究期望为轨道交通领域的边缘智能应用提供有益的借鉴和实践基础。     

人工智能视域下哈尔滨远东理工学院机器人通识课程的改革探索与实践

受到相关技术发展的影响,机器人技术逐渐在各个行业内得到了广泛的应用,机器人学科本身就是一个交叉性质的学科,其中包含了电子、机械、计算机等等多个领域内的专业知识,欧美发达国家早在上个世纪的90年代就已经开设了综合性的机器人课程。目前,诸多高校都已经开设了机器人方面的专业课程。本文基于哈尔滨远东理工学院的机器人通识课程问题,在分析人工智能学科特征的基础上,提出了具体的课程改革措施,以便为今后机器人通识课程的改革提供一些参考。