Interacting Socially with the Internet of Things (IoT): Effects of Source Attribution and Specialization in Human–IoT Interaction

This study investigates the theoretical mechanisms by which the variations in source attribution (multiple sources vs. single source) and specialization (multifunctionality vs. single functionality) of Internet of Things (IoT) devices influence the quality of human–IoT interaction. Results from a between‐subjects experiment (N = 100) indicate that IoT devices that elicit the sense of multiple agencies and are specialized in a single function induce greater social presence and perceived expertise, which, in turn, lead individuals to show a more positive attitude toward the devices and to ascribe greater quality to the information transmitted by them. The results also reveal that the effect of multiple source attribution is more pronounced for individuals for whom the content of the information has low personal relevance.     

Who creates Trends in Online Social Media: The Crowd or Opinion Leaders?

Internet slang words can very quickly become ubiquitous because of social memes and viral online content. Weibo, a Twitter‐like service in China, demonstrates that the adoption of popular Internet slang undergoes 2 distinct peaks in its temporal evolution, in which the former is relatively much lower than the latter. An in‐depth comparison of the diffusion of these different peaks suggests that popular attention in the early stage of propagation results in large‐scale coverage, while the participation of opinion leaders at the early stage only leads to minor popularity. Our empirical results question the conventional influentials hypothesis and provide some insights for marketing practice and influence maximization in social networks.     

面向频谱大数据处理的机器学习方法

随着移动互联网与物联网的迅猛发展,个人无线设备的数 量呈现指数级增长,随之产生的海量频谱数据与日俱增,频谱大数据的存在已成事实。同时 ,频谱赤字也日益严峻。为提高频谱利用率,有效的频谱大数据处理显得十分重要。本文从 无线通信的角度,首先给出了频谱大数据的定义并分析了它的基本特征;然后总结了一些 对于频谱大数据分析与利用颇具前景的机器学习方法,如分布式和并行式学习、极速学习、 核学习、深度学习、强化学习、博弈学习和迁移学习;最后给出了几个开放性话题和研究 趋势。     

基于物联网的移动通信信号定位模型仿真分析

在城市小区或在物联网中,因受非视距传播、多径传播等多种不利因素的综合影响,导致其定位性能显著下降,造成移动通信的信号定位识别出现较大的偏差,严重时甚至导致定位识别器瘫痪,无法定位.为此提出基于物联网的移动通信信号定位模型仿真分析,通过对移动通信环境下产生的通信信号频率进行定位识别分析,经由物联网环境下移动通信信号进行定位识别检测,建立信号定位模型来完成通信信号准确定位的过程.仿真结果表明,提出的方法能够有效的提高移动通信信号设备在物联网中的定位准确性、抗干扰能力强并且在长时间运行过程识别定位速度快,可靠性强.有效的为移动通信安全高效运行提供更好的保障,也为基于物联网的电信业务提供了更好的技术手段.     

移动互联网中一种移动学习方案的设计与原型实现

以移动教育方面的三方应用场景为例,设计并实现了一个面向精品课程和开放课程的移动学习系统原型,实现了网络教学资源整合。根据现行主流移动智能终端的特点,针对触摸屏移动智能终端因误操作引起的计算资源和通信资源浪费现象,给出了一个有三方参与的应用系统场景中,可行的减少误操作的应用方法。通过使用确定型有限自动机的方法验证了系统的正确性。测试表明,该方法可以有效降低应用场景中代理服务模块和资源服务模块的工作压力,提高用户体验度。     

网络环境下的信息技术课程整合教学

基于信息技术的课程整合作为小学信息技术教学的发展方向之一,越来越受到信息技术科任老师的关注。本文对基于网络环境的信息技术课程整合优势、网络环境在课程整合中的利用策略、网络环境下的信息技术课程整合的核心活动等方面进行了分析,探讨了如何利用网络技术促进信息技术课与其它学科的整合。     

Cortex-A8和ZigBee构成的智能餐厅系统

本文提出一种基于Cortex-A8和ZigBee的智能餐厅系统设计方案,构建了无人餐厅模型,系统通过ZigBee无线网络连接自助点菜终端、PC主机端、网关端、厨房端、送餐车、清洁车等模块,最终实现了通过Web服务器、CGI接口、云计算平台等方式提供远程订餐服务。经测试,本方案可实现包括自助点菜、送餐、清洁、结算、网页微信订餐等功能。     

未来互联网体系结构中的内生安全研究

未来互联网体系结构试图通过其内生安全特性解决目前互联网中的安全问题。新型的未来互联网体系结构命名空间普遍使用了具备自认证能力的网络标识支持网络的内生安全,但目前的方案不能将用户标识符、网络标识符、公钥三者在脱离PKI的情况下实现同时绑定。本文提出了基于组合公钥密码体制的自认证标识(SCI-CPK)命名方案,可用于未来互联网体系结构命名空间中标识安全绑定,并给出了在未来互联网体系结构XIA、MobilityFirst和NDN中支持实体鉴别的应用方法。分析表明,SCI-CPK方案能够支持未来互联网中泛在互联和泛在移动场景下的大规模实体身份和地址鉴别。     

How to maneuver in the world of negative online reviews,the important ethical considerations for attorneys,and changes needed to protect the legal profession

The advent of the Internet and social media has revolutionized the way society communicates, the speed in which news is disseminated, and the approach that people take in their daily decision-making. Online reviews are now common place on nearly every consumer-related website. Consequently, attorneys are also being publicly scrutinized by their clients on a range of topics from price, competence, satisfaction, personality, communication, and effectiveness. On one side of the coin, this new phenomenon can be very rewarding since attorneys were previously limited to receiving a small number of referrals from the word-of-mouth promotion before the creation of online reviews. However, the exact opposite is true. Negative online reviews, whether accurate or not, may deter potential clients from even giving the attorney a second thought. As a result, a firm's business can feel the immediate impact of negative reviews. Attorneys, who legitimately need and want to protect their business and reputation, cannot speak freely online to defend their honor. Rather, an attorney must be mindful of not disclosing confidential client information or crossing other ethical lines that may then expose the attorney to potential discipline. There are several interests that must be considered such as allowing attorneys to exercise their First Amendment right to free speech, respect and adherence to the ethical rules of non-disclosure of confidential information, allowing attorneys to preserve their reputation, and protecting an attorney's marketability and means of generating income. This article explores the trend in offering reviews online in a variety of industries, including legal services, the statistical findings regarding the prevalence of this information and consumers' reliance on the information while making a purchasing decision. This article also considers the positive and negative implications of the reviews being so widely spread, while highlighting unique considerations as it relates to the practice of law and factors that may greatly skew a reviewer and reader's perceptions. Next, this article outlines the ethical considerations of attorneys if they want to respond to negative online feedback, such as disclosure of confidential information. Then, this article analyzes the American Bar Association (ABA) and several US states' ethics opinions for guidance for attorneys who wish to respond negative reviews. Finally, this article details the author's recommendations for attorneys, the ABA, and the US states and propose the areas where additional ethics opinions, rules and guidelines should be focused to establish a proper balance between the valuable insights discovered from a client's review and attorneys' legitimate interests in protecting their reputation and livelihood from inaccurate, malicious, or erroneous postings.