From the Nation-State to a World Society: An Institutional Reading of Globalization

This article highlights the inadequacy of classical and neoclassical theories for understanding the set of changes experienced by economic systems in their process of development. The institutional dimension concerning the issue of well-defined rules (through the introduction of economic policies) and involving all stakeholders in the regulatory process (starting from the firm), seems to better interpret micro- and macro-economic aspects of the evolving capitalist model. This means questioning the complicated economic governance and society in the transition from the nation-state to a world society (or world state).     

时空大数据支持的土地储备智能决策体系与应用研究

研究目的:设计土地储备智能决策体系,将土地储备决策环节进行科学化、定量化和模型化,为政府合理开展土地储备提供决策依据。研究方法:遵循科学性、实用性、先进性、开放性原则,以数据为驱动,人工智能为核心,通过基于Hadoop/Spark的大数据处理技术、多源异构数据融合技术、智能决策模型集对多源时空大数据挖掘分析。研究结果:提出了土地储备智能决策体系,研究了一套面向土地储备的决策方法集,实现对现状条件的精准刻画,对土地储备规模、结构、时序等内容的科学决策;在此基础上,研发了智能决策支持平台,将数据资源共享、现状条件评估、智能决策专题等功能集成,构建土地储备智能决策"一张图",并实现平台的自我学习和更新。研究结论:应用于宁波市实例验证,该体系有效地促进了土地储备科学智慧决策,对优化土地资源配置具有参考意义。     

Reasserting Institutionalist Insights on the Good Society: 30 Years After Petr’s Call for a Mixed Economy

In this research note, I revisit the issues raised by Jerry Petr (1987) in “The Nature and Necessity of the Mixed Economy.” The institutionalist mixed economy is still a sound model for the good society. However, Western industrialized countries have been losing ground on the goals of the mixed economy. The struggle to defend pragmatism over ideological attachment to neoliberalism, has evolved into a distributional struggle that cannot be resolved without institutional change.     

基于车辆数据的k近邻联合概率数据关联算法

在交通场景中采用一些预警措施能够有效地减少交通事故发生。例如，对车辆轨迹进行跟踪并预测车辆的驾驶行为，就是一个常用的预警方法。在对车辆进行跟踪的过程中，数据关联是很重要的部分，它可以对车辆的观测点和轨迹进行关联，从而更新车辆的轨迹，完成跟踪过程。在此背景下，提出了一种新的数据关联算法，即k近邻联合概率数据关联算法(k Nearest Neighbor-Joint Probability Data Association,kNN-JPDA)。实验结果表明，该算法能够较好地解决在交通场景下车辆数据的数据关联问题，在精度以及运行效率方面都有所提高。     

一种基于微波雷达回波信号的车型分类方法

车辆类型识别方法是智能交通系统的关键技术之一。利用深度学习的高维特征泛化学习能力，将改进的LeNet-5卷积神经网络用于基于交通微波雷达的大小车型分类识别。首先，以雷达触发前的N帧信号为基础，对雷达的回波信号进行分析并构建数据集；然后，分析LeNet-5卷积神经网络的特点；最后提出一种改进的LeNet-5卷积神经网络。实验结果表明，与传统的支持向量机方法相比，所提方法能够智能学习大小车的雷达时频信号特征，大小车型识别准确率达到97%以上，可为交通场景下的车型识别研究提供新的技术途径。     

基于物联网技术的智能交通控制系统研究

作为物物相连的互联网,物联网通过信息传感设备,把互联网与任何物品相连接,为构建智能交通信号控制与采集的体系提供了可能。论文从基于物联网的智能交通系统整体框架入手,并着重分析其在交通控制和信号采集两个子系统中的运用,指出物联网技术将全面提升交通管理水平。     

人工智能技术辅助开发“智铸”系统

采用开源免费的深度学习平台,利用python二次开发了“智铸”系统,包括“识铸”“听铸”“盯铸”三个模块,铸造企业员工可以用手机或电脑自主学习,提升员工从业能力。在设备旁安装“听铸”软硬件一体化设备,可以实现对连续运行设备的在线自动监听侦测。“盯铸”模块实现连续生产铸件的自动检测、铸造缺陷分析与重点安全区域的监控。     

中国邮储银行大连分行网点转型下客户服务模式创新研究

随着社会大众对金融服务的要求不断增多,银行网点转型已经成为一个必然趋势。信息时代背景下,银行网点的转型大多向智能化的方向转变,而随着网点转型,其客户服务模式也在不断创新。论文以邮储银行大连分行为例,对银行网点智能化转型的影响进行了分析,探究了邮储银行大连分行网点智能化转型存在的问题,并且提出了相关的转型建议,最后对邮储银行大连分行智能化网点转型下客户服务模式的创新情况进行了研究,希望能够在银行网点智能化转型的背景下,促进其客户服务水平的不断提升。     

Examining relationships among perceived benefit,tourist experience and satisfaction: the context of intelligent sharing bicycle

Intelligent sharing bicycle has been a new fashion in China and appeals to more and more tourists. To better understand the experience of tourists traveling on sharing bicycle, this study explored the influence of perceived benefit of sharing bicycle on different perceived experiences, including escape, entertainment, esthetic and educational experiences. The relationships between these experiences and perceived satisfaction were also tested. An effective questionnaire survey was conducted for 296 tourists in Chengdu, China. The results of the study show that perceived benefit significantly relates to all the four dimensions of experience. However, only entertainment and esthetic experience seem to affect tourist satisfaction in this context. The relationship among educational experience, escape experience and tourist satisfaction are insignificant. Theoretical and practical implications of the study results are discussed for further research.