考虑边信息的多层贝叶斯需求预测模型

随着工业互联网经济的发展,需求的不确定性日益增大,为提高需求预测的准确性,提出一个考虑边信息的多层贝叶斯需求预测模型(DFSI)。DFSI模型通过构造隐层的网络结构以实现对客户需求更加精确的刻画,该隐层结构主要包含两组参数:一组用于描述客户需求在时间上固有的连续性特征,另一组则用于融合相关的边信息特征。进一步,以贝叶斯推断为理论基础,以最大化后验概率为目标,推导出了DFSI的优化目标,并基于梯度下降方法设计了相应的求解算法。使用京东商城及某制造企业的真实销售数据对提出的模型进行了检验。结果显示,与常用的需求预测模型相比,DFSI能获得更好的预测结果。     

基于测绘地理信息技术的涉地税源风险识别模式应用研究

为解决沧州市涉地税源管理手段单一等问题,文中提出以测绘地理信息技术为支撑,通过对多源数据组织管理,建立风险分析指标,采用多种GIS空间分析方法构建了涉地风险税源识别模式并在沧州进行应用。结果表明:该模式能有效识别多种涉地风险,为涉地税源管理提供了支撑。     

Determinants of consumers’ continuance intention to use social recommender systems: A self-regulation perspective

Social recommender systems have transformed how consumers seek product- or service-related information. Based on Bagozzi's self-regulation framework, this study examines the determinants of consumers' continuance intention to use social recommender systems. We found that appraisal factors (perceived information quality and perceived system quality) are strong predictors of emotional reaction (recommendation satisfaction and trust in recommendation). Particularly, perceived information quality has a significant effect on both recommendation satisfaction and trust in recommendation. However, the positive effect of perceived system quality is only on recommendation satisfaction. Both recommendation satisfaction and trust in recommendation positively affect consumers' continuance intention to use social recommender systems.     

Formal Approach to Workflow Application Fragmentations Over Cloud Deployment Models

Workflow management technologies have been dramatically improving their deployment architectures and systems along with the evolution and proliferation of cloud distributed computing environments. Especially, such cloud computing environments ought to be providing a suitable distributed computing paradigm to deploy very large-scale workflow processes and applications with scalable on-demand services. In this paper, we focus on the distribution paradigm and its deployment formalism for such very large-scale workflow applications being deployed and enacted across the multiple and heterogeneous cloud computing environments. We propose a formal approach to vertically as well as horizontally fragment very large-scale workflow processes and their applications and to deploy the workflow process and application fragments over three types of cloud deployment models and architectures. To concretize the formal approach, we firstly devise a series of operational situations fragmenting into cloud workflow process and application components and deploying onto three different types of cloud deployment models and architectures. These concrete approaches are called the deployment-driven fragmentation mechanism to be applied to such very large-scale workflow process and applications as an implementing component for cloud workflow management systems. Finally, we strongly believe that our approach with the fragmentation formalisms becomes a theoretical basis of designing and implementing very large-scale and maximally distributed workflow processes and applications to be deployed on cloud deployment models and architectural computing environments as well.     

基于BIM+GIS的大坝安全监测信息可视化展示技术研究

为了解决传统大坝监测信息三维可视化程度低,展示不够直观、形象等问题,采用BIM+GIS技术,将监测信息展示从传统二维空间拓展到三维空间。对BIM建模、模型轻量化、三维可视化展示以及系统功能设计进行了研究,通过在桃源水电站的应用实例表明,BIM+GIS技术能够实现大坝安全监测信息三维可视化展示,展示效果更为形象、生动,具有广泛应用前景。     

致密砂岩气藏多层试井解释方法研究

致密砂岩油气藏储层多套小层叠置发育，为实现产能及经济效益最大化，通常采用一套井网分层压裂多层合采的开发方式，受非均质性影响，开发过程中层间干扰严重，各小层产能贡献比例、能量衰减速度差异大，限制了产能有效发挥。在应用试井分析结果评价生产井储层动态参数、压力水平的过程中，常规试井解释模型只能反映各生产子层数据的平均值，无法准确评价各层段数据，实际指导意义存在局限性。综合运用单层、多层试井解释模型对试井数据开展精细解释，以生产测井的分层产量作为拟合计算的新增约束条件，并以此建立多层渗流试井模型，拟合结果符合率高，在降低单层试井解释模型多解性的同时，实现多层参数定量评价，对于多层合采井在开发过程中技术政策调整以及增产措施制定等工作提供强力支撑。     

Unconditionally Secure Oblivious Polynomial Evaluation: A Survey and New Results

Oblivious polynomial evaluation (OPE) is a two-party protocol that allows a receiver, R to learn an evaluation f(α), of a sender, S's polynomial f(x), whilst keeping both α and f(x) private. This protocol has attracted a lot of attention recently, as it has wide ranging applications in the field of cryptography. In this article we review some of these applications and, additionally, take an in-depth look at the special case of information theoretic OPE. Specifically, we provide a current and critical review of the existing information theoretic OPE protocols in the literature. We divide these protocols into two distinct cases (three-party and distributed OPE) allowing for the easy distinction and classification of future information theoretic OPE protocols. In addition to this work, we also develop several modifications and extensions to existing schemes, resulting in increased security, flexibility and efficiency. Lastly, we also identify a security flaw in a previously published OPE scheme.     

Recovery planning of industrial robots based on semantic information of failures and time-dependent utility

Industrial robots are required to recover from temporary errors and continue operations under a changing environment. In this paper, we propose a recovery planning system that considers the semantic information behind errors during robotic actions. In order to establish general repair strategies for feasible recovery plans under uncertainties, the proposed system uses a conceptual graph based on case grammar and a Bayesian network that is dynamically constructed according to the semantic information. In addition, we tackle the problem that the wealth of the recovery plan depends on the uncertainty of execution costs against the deadline at the production site. The proposed system controls the decision model by using a time-dependent utility. We demonstrate the effectiveness of the proposed system through simulations of assembly tasks by multiple robots.     

一种无线传感器网络中的信息驱动节点选择机制

提出了一种信息驱动的节点选择机制,应用于无线传感器网络中的目标估值。其方法是,以传感器节点的测量值与目标状态的估计分布之间的互信息作为信息效用函数,度量节点的测量值对目标状态估计的信息贡献,选择信息贡献值大的节点参与卡尔曼滤波过程进行迭代;应用基于地理位置信息的路由算法顺序访问选中的节点,并建立与Sink节点之间的路由,路径上的节点依次进行卡尔曼迭代以修正估计的状态值。仿真结果表明,该机制涉及的节点数目较少,总的通信距离较短,但目标估值的性能很好。