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。     

Transparency in complex dynamic food supply chains

Food supply chains are increasingly complex and dynamic due to (i) increasing product proliferation to serve ever diversifying and globalising markets as a form of mass customisation with resulting global flows of raw materials, ingredients and products, and (ii) the need to satisfy changing and variable consumer and governmental demands with respect to food safety, animal welfare, and environmental impact. Transparency in the food supply chain is essential to guarantee food quality and provenance to all users of food and food products. Intensified information exchange and integrated information systems involving all chain actors are needed to achieve transparency with respect to a multitude of food properties.In this paper, specific challenges of food supply chains are highlighted. Major elements are addressed that support transparency to consumers, the government and food companies, which are considered the claimants of transparency. Elements considered to be enablers of transparency are governance mechanisms, quality and safety standards and information exchange. The paper specifies these transparency claimants and enablers for food supply chains and identifies major information system functions and information technology applications needed to comply with transparency demands. It thereby provides a framework for transparency analysis in food supply chains.     

Regulatory Light Chains in Cardiac Development and Disease

The role of regulatory light chains (RLCs) in cardiac muscle function has been elucidated progressively over the past decade. The RLCs are among the earliest expressed markers during cardiogenesis and persist through adulthood. Failing hearts have shown reduced RLC phosphorylation levels and that restoring baseline levels of RLC phosphorylation is necessary for generating optimal force of muscle contraction. The signalling mechanisms triggering changes in RLC phosphorylation levels during disease progression remain elusive. Uncovering this information may provide insights for better management of heart failure patients. Given the cardiac chamber-specific expression of RLC isoforms, ventricular RLCs have facilitated the identification of mature ventricular cardiomyocytes, opening up possibilities of regenerative medicine. This review consolidates the standing of RLCs in cardiac development and disease and highlights knowledge gaps and potential therapeutic advancements in targeting RLCs.     

Preparation of High Strength and Toughness Aramid Fiber by Introducing Flexible Asymmetric Monomer to Construct Misplaced-Nunchaku Structure

High performance fibers with high strength and toughness have great potential in composites, but contradiction between tensile strength and elongation at break makes the preparation to become a current challenge. Herein, an asymmetric structure of more flexible diamine, 3,4′-diaminodiphenyl ether (3,4′-ODA), is introduced into heterocyclic aramid (PBIA) fibers to replace rigid symmetric p-phenylenediamine (PDA). By studying the properties of copolymer (mPEBA) fibers with different ratios of diamine, it is found that the mPEBA fiber reached the optimal mechanical properties with the 30% content of 3,4′-ODA. Compared with homopolymerized heterocyclic aramid fibers, the tensile strength and elongation at break of mPEBA fiber are improved by 26.2% and 38.7%, respectively. Results of X-ray diffraction show that the introduction of 3,4′-ODA structure can increase stretchability of mPEBA fibers, improving the orientation degree during hot-drawing. Molecular dynamics simulations confirm that 3,4′-ODA structure undergoes a conformation transformation to form a straightened chain during hot-drawing, while symmetrical 4,4′-diaminodiphenyl ether (4,4′-ODA) cannot form the same conformation. The misplaced-nunchaku structure is formed based on the special meta-para position of 3,4′-ODA, achieving the synergy of high strength and high toughness.     

甲型肝炎病毒(L-A-1株)基因型分析

目的 分析甲肝病毒基因型,为确定我国甲肝的分子流行病学及疫苗的安全性和免疫原性奠定基础。方法 采用抗原捕获聚合酶链反应（AC/PCR）,依据国际上甲肝病毒分型标准,扩增VP1/2A结合处的168个核苦酸（nt2909～3264）。结果 经生物信息学软件分析,得出L-A-1株病毒属于甲肝病毒基因IB亚型。结论 在我国有IA和IB两个亚型甲肝病毒流行。     

聚酯酰胺热熔胶的合成及其性能研究

研究了以聚酯胶和聚酰胺胶为原料在催化剂作用下加热共熔,通过大分子链交换反应制备织物用聚酯酰胺热熔胶的方法。用聚酯胶的溶剂对所得产品进行溶取试验并且通过红外光谱分析都证明了链交换反应的存在。用该法所得产品粘接强度大,既耐水洗又耐干洗,适用于粘合衬生产。