网络视角下智慧城市外部智慧性作用机制探究

经济全球化快速发展使得城市之间的各类联系日益增多,要实现城市的智慧发展,不能仅关注城市内部的创新,也要重视其在整体网络中的表现。在城市网络理论视域下,采用社会网络分析法,将智慧城市在城市网络中的位置与作用定义为其外部智慧性,并以2016年中国193个试点智能城市为样本,利用主要企业总部-分公司布址数据构建智慧城市网络,探究智慧城市的外部智慧性对其内部智慧性绩效评估的影响与作用机理。研究发现,智慧城市在网络中的点入度、点出度、结构洞与互惠性等属性均对其内部智慧性的评估结果有显著的影响作用。新兴智慧城市要提升综合竞争力,应该识别自身的网络定位,增强与其他城市的联系与合作,形成内外联动,实现智慧城市发展的各项目标。     

Creating value from Social Big Data: Implications for Smart Tourism Destinations

This paper aims to demonstrate how the huge amount of Social Big Data available from tourists can nurture the value creation process for a Smart Tourism Destination. Applying a multiple-case study analysis, the paper explores a set of regional tourist experiences related to a Southern European region and destination, to derive patterns and opportunities of value creation generated by Big Data in tourism. Findings present and discuss evidence in terms of improving decision-making, creating marketing strategies with more personalized offerings, transparency and trust in dialogue with customers and stakeholders, and emergence of new business models. Finally, implications are presented for researchers and practitioners interested in the managerial exploitation of Big Data in the context of information-intensive industries and mainly in Tourism.     

Committee standards battles in the era of convergence: Implications for smart systems

By now, there have been many standards battles fought within the same industry or by multiple industries in the market-based standardization. In these battles, incompatible standards compete to win market dominance. While there is some research on standards battles found within a single committee, competitions in the committee-based standardization between standards from different committees or SDOs are underexplored. This paper categorizes the types of standards battles by the mode of standardization and the heterogeneity of actors. A new type referred to as ‘committee standards battles for converging systems’ is introduced and the dynamics of such battles is explored with two cases. The battle between the electric vehicle charging and the smart meter communication standard and the battle between two different vehicle-to-everything (V2X) communication standards are analyzed. The failure in achieving compatibility between different committee standards on the same frequency bands results in communication interference that adversely affects the operation of smart systems. Social incompatibilities between actors and alliances from a mix of industries with vested interests towards a particular standard complicate the battling scene. The findings provide implications in terms of heterogeneity, actors, and government role in standards battles.     

SmartRolling: A human–machine interface for wheelchair control using EEG and smart sensing techniques

Smart wheelchairs based on brain–computer interface (BCI) have been widely utilized recently to address certain mobility problems for people with disability. In this paper, we present SmartRolling, an intuitive human–machine interaction approach for the direct control of robotic wheelchair that jointly leverages EEG signals and motion sensing techniques. Specifically, SmartRolling offers two wheelchair-actuation modes for users with different physical conditions: (1) head motion only — people who are severely disabled but able to do basic tasks using eyes and head, and (2) head and hands motion — in addition to type 1, people who can use functioning hands/arms for extra tasks. The system issues operation commands by recognizing different EEG patterns elicited by motor execution (ME) tasks including eye blink, jaw clench, and fist open/close, while at the same time estimates users’ steering intentions based on their facing direction by leveraging inertial measurements and computer vision techniques. The experiment results demonstrate that the proposed system is robust and effective to meets the individual’s needs and has great potential to promote better health.     

Machine learning based system for managing energy efficiency of public sector as an approach towards smart cities

Energy efficiency of public sector is an important issue in the context of smart cities due to the fact that buildings are the largest energy consumers, especially public buildings such as educational, health, government and other public institutions that have a large usage frequency. However, recent developments of machine learning within Big Data environment have not been exploited enough in this domain. This paper aims to answer the question of how to incorporate Big Data platform and machine learning into an intelligent system for managing energy efficiency of public sector as a substantial part of the smart city concept. Deep neural networks, Rpart regression tree and Random forest with variable reduction procedures were used to create prediction models of specific energy consumption of Croatian public sector buildings. The most accurate model was produced by Random forest method, and a comparison of important predictors extracted by all three methods has been conducted. The models could be implemented in the suggested intelligent system named MERIDA which integrates Big Data collection and predictive models of energy consumption for each energy source in public buildings, and enables their synergy into a managing platform for improving energy efficiency of the public sector within Big Data environment. The paper also discusses technological requirements for developing such a platform that could be used by public administration to plan reconstruction measures of public buildings, to reduce energy consumption and cost, as well as to connect such smart public buildings as part of smart cities. Such digital transformation of energy management can increase energy efficiency of public administration, its higher quality of service and healthier environment.     

Who are We?

This article scrutinises the usage of the words “we”, “us” and “our” by BBC radio journalists when reporting and discussing news and current affairs. By analysing reports and discussions on the “flagship” Radio 4 Today, a daily news programme whose centrality to political and public debate is widely recognised, the article raises substantive questions about clarity, accuracy and impartiality in senior broadcast journalists’ choice of language. In exploring the assumptions which may underlie the invocation, via such language choices, of an implied community, and against the backdrop of the BBC's commitment to impartiality in its Editorial Guidelines, the article identifies numerous recent examples where the choice of words and identifiers can be seen as undermining the BBC's impartiality and which show several of its senior journalists adopting the first-person plural “we” when reporting on matters of public policy. The findings therefore indicate a general need to codify norms which are seen to integrate the need for accuracy as well as impartiality, and for these norms to take into account issues which might at first glance seem to be inconsequential, micro-level features of the journalists’ language. The evidence suggests that more fine-grained guidelines on permissible circumstances for BBC journalists’ usage of “we” and “our” need revising and disseminating in the light of these findings.     

MATLAB在说话人识别算法中的应用

Matlab作为目前最流行的功能强大的软件,可用于说话人识别。在介绍说话人识别基本概念和原理的基础上,通过一个具体实例,说明如何用matlab的simulink工具箱提取特征参数、通过编程来进行对说话人识别的过程。最后给出了识别结果。     

燕燕和小千户非乳兄妹辩——读太田辰夫《元刊本〈调风月〉考》的一点思考

太田辰夫先生根据情理推测元刊杂剧《诈妮子调风月》男女主人公的关系,认为他们是乳兄妹。本文通过对相关论据和作品文本的分析,认为在没有其他资料佐证的情况下,这一论断难以成立。     

指向教学空间优化的小学智慧教室的校本研究

智慧教室的设立和运用,将大大改善学生枯燥的学习氛围,优化学生的学习形式,进一步加强学生在课堂学习中的主体地位。因此,本文结合智慧教室的教学特点,对小学信息技术学科的校本开发展开研究。