虚拟企业中数字车间与供应链系统的集成与协调

数字车间和供应链系统是虚拟企业的两个重要的功能组织。数字车间与供应链系统的信息集成和功能协调是虚拟企业能够高效运作的基础。Agent技术是构建大型、分布式系统的有效方法。本文研究了基于Agent技术的虚拟企业集成技术和协调机制。     

从供应商受益角度研究国际供应链合作关系

首先指出从供应商受益角度对国际供应链合作关系进行研究的重要意义，接着对国际供应链合作关系的起源及其概念界定进行了综合分析；其次对国际供应链战略伙伴关系下的供应商受益进行了相关研究结论的综合，并对我国供应商参与国际供应链合作的实际受益进行分析，然后将两者进行了比较，最后综合全文探讨得出本文研究的结论。     

A note on the first-passage problem and VanMarcke’s approximation — short communication

Given a scalar, stationary, Markov process, this short communication presents a closed-form solution for the first-passage problem for a fixed threshold b. The derivation is based on binary processes and the general formula of Siegert [Siegert AJF. On the first-passage time probability problem. Physical Review 1951; 81:617–23]. The relation for the probability density function of the first-passage time is identical to the commonly used formula that was derived by VanMarcke [VanMarcke E. On the distribution of the first-passage time for normal stationary random processes. Journal of Applied Mechanics ASME 1975; 42:215–20] for Gaussian processes. The present derivation is based on more general conditions and reveals the criteria for the validity of the approximation. Properties of binary processes are also used to derive a hierarchy of upper bounds for any scalar process.     

Markov不等式与H(?)lder不等式的差异性

通过对(李亚普诺夫)不等式的证明,论证了Markov不等式及Holder不等式的差异性,同时讨论了2个不等式的适应范围。     

新岭大桥转体施工技术

新岭大桥采用有平衡重的平面转体法施工 ,这在我省尚属首例。施工中因地制宜采用拉链葫芦滑轮组进行牵引 ,仅用 3小时就使拱肋平稳、安全地转体就位 ,牵引施工获得成功 ,为我省的桥梁施工积累了经验 ,具有推广价值     

基于模糊修正熵权TOPSIS的战时装备供应链风险评估

针对战时装备供应链的特点,以远程精确打击、敌特后方袭扰和恶劣天气等三个因素为主要风险指标,运用修正的模糊信息熵权对TOPSIS法进行改进,提出了一种新的战时装备供应链风险评估方法。首先利用原始数据产生的模糊信息熵权进行客观赋权,并引入专家因素对权重进行主观修正,利用逼近理想解排序方法进行运算,最后通过实例计算与分析,验证该评估方法简便易行,结论合理,有效降低了指挥员决策的主观随意性。     

Transit smart card data mining for passenger origin information extraction

The automated fare collection(AFC) system,also known as the transit smart card(SC) system,has gained more and more popularity among transit agencies worldwide.Compared with the conventional manual fare collection system,an AFC system has its inherent advantages in low labor cost and high efficiency for fare collection and transaction data archival.Although it is possible to collect highly valuable data from transit SC transactions,substantial efforts and methodologies are needed for extracting such data because most AFC systems are not initially designed for data collection.This is true especially for the Beijing AFC system,where a passenger’s boarding stop(origin) on a flat-rate bus is not recorded on the check-in scan.To extract passengers’ origin data from recorded SC transaction information,a Markov chain based Bayesian decision tree algorithm is developed in this study.Using the time invariance property of the Markov chain,the algorithm is further optimized and simplified to have a linear computational complexity.This algorithm is verified with transit vehicles equipped with global positioning system(GPS) data loggers.Our verification results demonstrated that the proposed algorithm is effective in extracting transit passengers’ origin information from SC transactions with a relatively high accuracy.Such transit origin data are highly valuable for transit system planning and route optimization.     

基于动态时间规整的手势加速度信号识别

为了提高基于加速度传感器的动态手势识别算法的性能,本文采用了动态时间规整(DTW)识别算法。通过该算法计算测试模板和参考模板的相似度,从而得出识别结果。为了验证该方法,建立了一套手势加速度无线采集系统,并采集了41个志愿者的手势信息。实验结果表明,该方法手势平均识别率在97%以上。与HMM识别算法相比,DTW识别算法在识别的准确率上比HMM识别算法更具优势。     

Transformation of semantic knowledge into simulation-based decision support

Simulation is capable to cope with the uncertain and dynamic nature of industrial value chains. However, in-depth system expertise is inevitable for mapping objects and constraints from the real world to a virtual model. This knowledge-intensity leads to long development times of respective projects, which contradicts the need for timely decision support. Since more and more companies use industrial knowledge graphs and ontologies to foster their knowledge management, this paper proposes a framework on how to efficiently derive a simulation model from such semantic knowledge bases. As part of the approach, a novel Simulation Ontology provides a standardized meta-model for hybrid simulations. Its instantiation enables the user to come up with a fully parameterized formal simulation model. Newly developed Mapping Rules facilitate this process by providing guidance on how to turn knowledge from existing ontologies, which describe the system to be simulated, into instances of the Simulation Ontology. The framework is completed by a parsing procedure for an automated transformation of this conceptual model into an executable one. This novel modeling approach makes model development more efficient by reducing its complexity. It is validated in a use case implementation from semiconductor manufacturing, where cross-domain knowledge was required in order to model and simulate the impacts of the COVID-19 pandemic on a global supply chain network.     

井下人员定位系统读卡器存储算法分析与测试

从查找时间与存储容量2个方面分析了适用于井下人员定位系统读卡器的3种存储算法,即链式存储算法、哈希表存储算法和哈希二叉树存储算法,给出了该3种不同存储算法的使用效率与应用场合。测试结果表明,链式存储算法查找时间呈线性增长,哈希表存储算法明显优越于链式存储算法,如果测试数据增多,其优越性会更明显;当数据量较大时,哈希搜索二叉树存储算法又明显优于哈希表存储算法,当人数达到行业所要求的8 000人以上时,选择哈希搜索二叉树存储算法更为合理。