基于ANP-PP-SPA的区域洪灾风险评价模型研究

针对现有洪灾风险评价模型的缺陷与不足,从致灾因子、孕灾因子、承灾因子和减灾因子4个方面,通过对14项评价指标的分析与计算,构建洪灾风险评价体系。洪灾风险评价体系以网络层次分析法(ANP)求解主观权重,投影寻踪法(PP)求解客观权重,主客观综合权重与集对分析理论(SPA)耦合,构建基于ANP-PP-SPA的洪灾风险评价模型。以广东省英德市为例,验证洪灾风险评价模型的适用性。计算结果表明,英德市2016年的洪灾风险属于中等级别,符合英德市2016年的实际情况。洪灾风险评价模型不仅综合考虑了评价指标间的相互关系,还较好地体现了洪灾风险的模糊性和随机性,能够为区域洪灾风险决策和洪水管理提供科学依据。     

Parking futures: An international review of trends and speculation

The explosion of low-cost, on-demand taxi services and the anticipation of an autonomous vehicle future has made transportation the center of debate and discussion for the first time since the massive expansion of the US highway system in the 1950s. Yet the realm of parking boasts innovations and developments far beyond the high-profile issues of TNCs and AVs. Rather, innovation in parking is happening in many cases quietly on a wide variety of fronts, including technology, public policy, and design. This paper serves an overview of emerging trends in parking, primarily within the US context. We identify and outline five developments and the pertinent technologies helping to catalyze change: unbundling parking costs, reducing parking minimums, pricing and allocating curb space dynamically, designing hybrid parking structures, and preparing for the autonomous era and “mobility as a service.” This paper presents these trends with illustrative examples highlighting current practices, governance challenges, and possible future scenarios.     

Beyond the community in participatory forest management: A governance network perspective

Governance of the environment and natural resources involves interests of multiple stakeholders at different scales. In community-based forest management, organisations outside of communities play important roles in achieving multiple social and ecological objectives. How and when these organisations play a role in the community-based forest management process remains a key question. We applied social network analysis to a case study in Indonesian Borneo to better understand the evolution of interactions between organisational actors, and with communities. NGOs featured most prominently in initiating the permit process, implementing management, and providing other support activities, while also being well-connected to donors and government actors. The network configurations indicated significant cooperation among organisations when initiating the community forest process, while bridging between village and organisational levels characterised all stages of the community forest process. While community-based forest management often evokes images of grassroots efforts and broad local capacity to manage forests, reality shows a more dynamic and heterogeneous picture and broader involvement of different actor types and motivations in Indonesia. These findings can be applied to other countries implementing and expanding their decentralised forest policies.     

深度学习技术在海关风险甄别中的应用研究

随着互联网的高速发展和人工智能时代的到来,越来越多从前必须由人脑完成的工作能够利用计算机技术来完成,而深度学习的出现更解决了传统机器学习算法在计算机视觉领域、自然语言处理领域表现不佳的问题,使机器也能够拥有准确感知图像和语音的能力。人脸识别是深度学习网络最常见的应用场景之一,具有自然、直接、方便的特点,且不需要检测对象配合,因此非常适合用于公共安全领域的风险检测。研究充分结合海关实际需求,搭建基于深度学习技术的人脸识别模型,提供对通关旅客进行实时风险甄别的解决方案,以及海关通关风险防控场景的理论参考,为后续深度学习技术在海关业务的研究提供支撑。     

上海合作组织命运共同体:一项研究议题

构建上海合作组织命运共同体是中国政府提出的关于促进上海合作组织长远发展的重大倡议。由于上海合作组织命运共同体理念的提出时日尚短,学术界关于该理念的研究尚未全面启动。要使上海合作组织命运共同体理念成为一个有效的研究议题,不仅需要明晰上海合作组织命运共同体的具体内涵,而且需要将其纳入国际共同体、国际组织和大国外交等议题的研究,提炼出一些具有普遍性的理论命题。就攸关上海合作组织命运共同体构建的重大问题而言,至少需要回答上海合作组织命运共同体提出的理论与实践意义、上海合作组织命运共同体构建应遵循的基本路径、上海合作组织命运共同体构建的基础和条件、上海合作组织命运共同体构建面临的挑战与障碍、学术界能为上海合作组织命运共同体构建提供的对策建议等重大问题。在此过程中,学术界还需将其与周边命运共同体、人类命运共同体等家族相似性的概念纳入同一研究视域,以澄清上海合作组织命运共同体的内涵与外延,辨识上海合作组织命运共同体演变的动力与机制,并从理论层面提炼上海合作组织发展经验的特殊性与普遍性。     

Systemic financial risk early warning of financial market in China using Attention-LSTM model

We propose an Attention-LSTM neural network model to study the systemic risk early warning of China. Based on text mining, the network public opinion index is constructed and used as a training set to be incorporated into the early warning model to test the early warning effect. The results show that: (i) the network public opinion is the non-linear Granger causality of systemic risk. (ii) The Attention-LSTM neural network has strong generalization ability. Early warning effects have been significantly improved. (iii) Compared with the BP neural network model, the SVR model and the ARIMA model, the LSTM neural network early warning model has a higher accuracy rate, and its average prediction accuracy for systemic risk indicators has been improved over short, medium and long terms. When the attention mechanism is included in the LSTM, the Attention-LSTM neural network model is even more accurate in all the cases.     

黄浦江两岸地区公共空间可达性研究 ——基于社会网络分析的公共交通评价与 优化策略

黄浦江两岸地区正在打造世界级的滨江公共空间， 如何便捷、多样地抵达滨江公共空间是其规划设计和建设实施 的重要评价指标。将该评价指标定义为滨江公共空间可达性， 指居民利用滨江公共交通系统(常规公交)抵达滨江公共空间的 便捷性和多样性程度。利用社会网络分析方法，以虹口区和徐 汇区的滨江公共空间为例，构建了滨江公共空间可达性模型， 借助地理信息系统(ArcGIS)与计算机编程语言(Python)对现 状可达性进行量化分析评价，并提出优化滨江公共空间可达性 的算法和策略，以期更好地提升滨江公共空间可达性。     

Metafrontier efficiency analysis for hospital pharmacy services using dynamic network DEA framework

Medication management is a complex but critical process within the healthcare delivery system. The pharmacy department in healthcare facilities is responsible for acquisition, distribution and dispensing of medication to patients that involves a series of network process. This process can be categorized into two main subprocesses: i) pharmacy store and ii) patient services (i.e., ambulatory and inpatient pharmacy). The objective of this study was to investigate the relative efficiency level of the two subprocesses of pharmacy services in Malaysia's public hospitals. We used a nonconvex metafrontier technology to estimate technical efficiency of hospital pharmacies between specialist and nonspecialist hospital categories under the dynamic network data envelopment analysis (DNDEA) framework. For overall efficiency, both specialist and nonspecialist categories had similar mean efficiency scores. However, when measuring the efficiency level according to pharmacy store and patient services separately, the nonspecialist category had a higher mean efficiency score in pharmacy store, whereas for patient service efficiency, both categories had similar results. The patient service efficiency level was lower consistently over time, suggesting that the overall inefficiency of hospital pharmacy is greatly influenced by the inefficiency of the patient service. This suggests that systematic improvements in patient service efficiency should be a higher priority than pharmacy store efficiency to further increase the overall efficiency level. We believe that our findings will provide valuable information to policymakers towards achieving an efficient public healthcare service.     

一种基于量子加密的软件定义网络南向安全防护策略

提出一种以量子加密技术为核心的软件定义网络（Software-defined Network，SDN）的南向安全防护策略，建立了基于量子密钥分发的SDN网络模型并分析了该模型下的身份认证、量子密钥分发和自适应免疫窃听流程。推导出了本策略下窃听攻击强度、用于检测窃听的量子态数目的比例α、系统发现窃听者的概率、密钥分发效率之间的定量关系。通过动态仿真分析确立了不同攻击强度下系统参数α的最优选值区间。SDN控制器可根据该仿真结果，动态地决策系统中α的取值进行自适应免疫密钥分发，实施更为精准的窃听免疫方案。     

基于深度学习的跳频信号识别

针对跳频信号分选存在人工提取参数特征具有复杂性的问题，提出了一种基于深度学习的识别方法。首先对跳频信号进行短时傅里叶变换，得到二维的时频矩阵；接着提取信号的轮廓特征，构造三维矩阵作等高线图，并对等高线图进行预处理；最后把预处理后的等高线图输入到卷积神经网络中进行训练、测试，进而实现分类识别。仿真结果表明，在不需要复杂的人工提取参数特征的基础上，在分选率为100〖WT《Times New Roman》〗%〖WTBZ〗时，所提方法经裁剪处理下的信噪比为-15 dB，比支持向量机和传统K-Means聚类算法都低10 dB。实测数据的算法验证表明，所提方法能够将大疆精灵4Pro、hm无人机、司马航模X8HW以及大疆悟2这四类无人机正确分类。