Replenishment policy for a purchase-to-order seller: a tradeoff between ordering cost and delay cost

We consider replenishment decisions on when and how many goods to purchase for a seller under a purchase-to-order mode where there is no inventory and the seller purchases goods to fulfil orders already placed. For each purchase, there is a constant ordering cost. For each order, delay cost will be incurred if it is not fulfilled timely. Generally, the more frequent the replenishment, the higher the ordering cost but the lower the delay cost. Consequently, there is a tradeoff between the ordering cost and the delay cost for the seller to make replenishment decisions minimising the total cost. In this paper, we study three cases of the problem and investigate both offline versions and online versions according to the seller's knowledge about information of future orders. For offline versions with perfect information, we either develop an optimal policy, or prove it is NP-hard and develop an approximation policy. For online versions without any information about future orders, from the perspective of competitive analysis we prove the lower bound of competitive ratio for any possible online policy and present a 10-competitive online policy for the general case and a 2-competitive online policy for each of two special cases.     

基于声源定位的高校在线巡课系统设计与研究

随着网络建设以及信息化教学方法在高校教学过程中的应用普及,越来越多的高校使用在线巡课系统对教师的教学过程进行跟踪和管理,以便发现课堂教学中的亮点、问题和不足。文章提出的在线巡课系统,基于声源定位的技术,对传统的在线巡课系统做出了改进,解决了已有巡课系统中“只闻其声,不见其人”的问题,能够更直观地跟踪到教师的教学过程,包括教学行为以及师生互动过程,有效提升教务人员巡课效果和体验感受。     

Collective reflection strategy for moderating conformity tendency and promoting reflective judgment performance

Reflective judgement is crucial for medical-related practitioners in dealing with controversial issues. However, the conformity phenomenon is likely to occur and interfere with reflective judgement learning during interactive activities. Effective strategies are required to moderate the conformity behaviour tendency (CBT) and improve reflective judgement performance (RJP). This study demonstrates two significant results: (a) Compared with the guided self-reflection learning strategy, the online collective reflection (OCR) learning strategy effectively weakened the learners' general CBT while dealing with professional controversial issues; and (b) a significantly negative correlation between the RJP achieved and the change of CBT in online environment was detected in the OCR group. The implications and potential applications in higher education were discussed. Further studies are needed to confirm the long-term effects and the extending application to other professional studies.     

基于大数据分析的分布式MOLAP技术研究

在计算机系统运行以及研究环节中,会存在大量的规模效应,此类状况难以避免,要想有效解决此类问题,就需要利用分布式的处理方式,开展对文件系统的分析。文章对分布式多维联机分析过程(MOLAP)的数据模型进行了分析,从维编码的算法、映射归约(MapReduce)算法的实现、分析维的遍历算法等方面作深入探讨。     

超低渗油藏在线分流酸化增注技术研究与应用

酸化是超低渗油藏最有效的增注措施之一，但由于储层物性差、非均质性强等问题，造成目前常规酸化措施普遍具有施工周期长、有效率低、有效作用距离短等不足，且酸化过程中存在指进现象和储层二次伤害。针对这一问题，选取鄂尔多斯盆地环江油田三叠系超低渗油藏为研究对象，提出了在线分流酸化技术，并配套研制了一种多元缓速螯合酸COA-1S和一种新型的水溶性分流剂COA-1P。通过室内评价实验和在线分流酸化模拟实验，发现该技术在缓速性、配伍性、水溶性、螯合能力和暂堵功能等方面均显著优于常规酸化；现场先导性实验结果表明，酸化后剖面吸水均匀程度从28.5%上升至50.9%，视吸水指数增加2倍左右，降压增注效果显著；同时，该技术还具有“不停井、不泄压、不动管柱、不返排”的特点，简化了常规分流酸化工序、降低了安全环保风险，是一种能够很好地适应超低渗油藏特征的酸化增注技术。     

MooseFS热备元数据节点设计与实现

针对MooseFS元数据节点的单点故障问题，对MooseFS源码进行改造，为其增加一个热备的备元数据节点，并通过主备之间同步元数据，备节点回放操作日志等技术使得备元数据节点内存中的元数据时刻跟主元数据节点保持一致。当主元数据节点发生故障切换到备元数据节点后，备元数据节点无需从本地加载元数据即可快速接替主元数据节点对外提供服务。测试结果表明，备元数据节点本地和内存中的元数据均与主元数据节点保持一致，且故障恢复时间小于1 s。     

TSL:predicting popularity of Facebook content based on tie strength

The rapid development of online social networks leads to an explosion of information,however,there are great differences in the popularity of different messages,and accurate prediction is always a great difficulty is the current study.Popularity prediction of online content aims to predict the popularity in the future based on its early diffusion status.Existing models for popularity prediction were mostly based on discovering network features or fitting the equation into a varying time function that the accuracy of current popularity prediction model was not high enough.Therefore,with the help of the weak ties theory in sociology,the concept of tie strength was introduced and a multilinear regression equation was constructed combined with the early popularity.A TSL model to predict the popularity of Facebook’s well-known pages was proposed.The main contribution of this article was to solve the problem and few or no work based on sociology.A high linear correlation between the proportion of faithful fans was existed in Facebook homepage with frequent shares in the early and the future popularity.Compared with other baseline models,an experimental study of Facebook (including 1.54 million shares) illustrates the effectiveness of the proposed TSL model,and the performance is better than the existing similar methods.     

An E-Business Event Stream Mechanism for Improving User Tracing Processes

With the rapid development in business transactions, especially in recent years, it has become necessary to develop different mechanisms to trace business user records in web server log in an efficient way. Online business transactions have increased, especially when the user or customer cannot obtain the required service. For example, with the spread of the epidemic Coronavirus (COVID-19) throughout the world, there is a dire need to rely more on online business processes. In order to improve the efficiency and performance of E-business structure, a web server log must be well utilized to have the ability to trace and record infinite user transactions. This paper proposes an event stream mechanism based on formula patterns to enhance business processes and record all user activities in a structured log file. Each user activity is recorded with a set of tracing parameters that can predict the behavior of the user in business operations. The experimental results are conducted by applying clustering-based classification algorithms on two different datasets; namely, Online Shoppers Purchasing Intention and Instacart Market Basket Analysis. The clustering process is used to group related objects into the same cluster, then the classification process measures the predicted classes of clustered objects. The experimental results record provable accuracy in predicting user preferences on both datasets.     

Creep life assessment method for online monitoring of steam turbine rotors

The principal objective of work was to develop fast and accurate method for online creep life monitoring of steam turbine rotors. For this purpose, a characteristic strain model of creep was investigated and validated using test data of 2%CrMoV rotor steel. The model was then used to determine creep damage functions which are introduced to compute creep damage at a constant temperature based on the Robinson time fraction rule. Finite element (FE) creep calculations of a turbine rotor were performed using the same creep model to obtain reference damage results for validating the proposed method. Comparisons of the results obtained using both methods showed a very good accuracy of the online creep damage predictions.     

Distributed ledger technology in supply chains: a transaction cost perspective

With the emergence of distributed ledger technology (DLT), numerous practitioners and researchers have proclaimed its beneficial impact on supply chain transactions in the future. However, the vast majority of DLT initiatives are discontinued after a short period. With the full potential of DLT laying far down the road, especially managers in supply chain management (SCM) seek for short-term cost-saving effects of DLT in order to achieve long-term benefits of DLT in the future. However, the extant research has bypassed grounding long-term as well as short-term effects of DLT on supply chain transaction with empirical data. We address this shortcoming, following an abductive research approach and combining empirical data from a multiple case study design with the corresponding literature. Our study reveals that the effects of DLT on supply chain transactions are two-sided. We found six effects of DLT solutions that have a cost-reducing or cost avoidance impact on supply chain transactions. In addition, we found two effects that change the power distribution between buyers and suppliers in transactions and a single effect that reduces the dependency of supply chain transactions on third parties. While cost-reducing and avoidance as well as dependency-reducing effects are positive effects, the change in power distribution might come with disadvantages. With these findings, the paper provides the first empirical evidence of the impact of DLT on supply chain transactions, which will enable managers to improve their assessment of DLT usage in supply chains.