盘类零件内型腔尺寸检测

航空发动机中,盘类、机匣类零件是航空发动机的重要零件,对航空发动机安全可靠性与使用寿命有很大影响。盘类零件结构复杂、刚性差,精度要求高,该测具解决了盘类、机匣类环形零件内腔型面直径尺寸大于零件开口直径尺寸测量的问题。采用测量销可旋转式新结构,解决测具用标准件对表后无法进入零件内检测的问题。测具通用性强,可检测不同高度、不同型面尺寸各种盘类零件,提高了盘类环形零件的测量精度和合格率。

以花键分度圆为基准的孔位置度测具设计

针对以花键分度圆为基准的待检测件孔位置度是否合格的问题,设计了一种孔位置度检测装置,并提出其检测方法。采取花键跨棒距固定不变、滚棒与花键的齿槽相配合,通过调节滚棒尺寸来消除齿槽宽公差间隙的定位方式,配合测量销能否通过测量孔来判断孔的位置度是否合格,解决了检测以花键分度圆为基准的待检测件孔位置度是否合格的难题。

凸轮轴键槽与凸轮间相位角的快捷通用检测夹具

本文介绍了一种快捷通用检测夹具,该夹具在凸轮轴批量生产中可快速检测凸轮轴键槽与凸轮间的相位角,保证产品的一致性。在测量不同型线、不同型号的凸轮轴时,可根据产品的不同要求更换该夹具中的定位块或调整该夹具后顶尖支座位移量,从而满足测量的需求。

Study of the Influence of Parent-brand Similarity,Association,and Complimentary Fit on Co-brand Attributes

In this paper,it investigates the factors affecting successive brand alliance in which two brands from different product categories are featured together to introduce a co-brand.Based on the brand alliance theories,the degree of association,similarity,and complimentary fit between parents brands are important factors in determining successive brand alliance.By using the 5P's,which are premium price,perceived quality,product features,performance,and perceived image,as the measuring scale in brand attributes for each brand,it has reflected the change of brand attributes of the brands before and after brand alliance.400 subjects participate in the research,and 360 of which are valid.From this study,we conclude that when association between parents turns from "-" to "+" and similarity from "-" to "0",there is a trend of descending of co-brand attributes.When fit between parents turns from "-" to "0",there is also a trend of descending of co-brand attributes.While fit between parents turns from "+" to "0",there is a trend of increasing of co-brand attributes.The results show an interesting pattern of interactions among factors,which has important implications for managers in co-brand marketing.These also provide researchers with promising avenues for further study in brand alliance.

Optimal design for split-and-recombine-type flow distributors of microreactors based on blockage detection

In order to increase the productivity of microreactors, the parallelization of the microreactors is required. The performances of flow distributors can affect the product yield and fault detection ability when blockage happens.In this research, an optimal design method to calculate the channel diameters and to determine the flow sensor location is derived based on mass balance and pressure balance models of split-and-recombine-type flow distributors(SRFDs). The model accuracy is verified by experiment data. The proposed method is applied to optimal design of SRFDs under constant flow rate operation conditions. The maximum angle difference between normal and blockage conditions at one sensor to those at the other sensors is set to be the objective function and the uniformity of flow distribution in microreactors under normal condition is also required. The diameters of each pipe in SRFDs are selected as the design variables. Simulated annealing algorithm is used to solve the optimization problem. The effectiveness of the optimal design results is demonstrated by fluid dynamics simulations. The results show that using the optimal channel diameters of SRFDs, the pressure drop in SRFD section is lower than that of the microreactor section. Meanwhile, in the case studies, only a few sensors that are located inside the SRFDs can easily detect the blockage abnormal condition in the parallelized microreactor system.

Market orientation for the hotel segment： The Portuguese case

In view of the importance of the hotel segment for the tourism and for the economy of countries such as Portugal, the objective of this study was to measure the level of orientation for the market of the largest hotel groups of Portugal. This investigation initially emphasized the importance of the marketing for the organizations, mainly the orientation for the market. After a brief explanation on the hotel segment in Portugal, an empirical study was presented, of quantitative, exploratory and traversal character, performed with the largest groups of 20 hotels of Portugal, using as an instrument of collection data, the traditional Markor scale （market orientation） adapted to the hotel sector. After analyzing the data, it was found in the investigated organizations that a good capacity to generate market information and response to the market, which formed two of the three constructs of Markor scale. However the results obtained with the construct of the dissemination of market information were below the expectations. It was possible to conclude that marketing professionals of the large hotel groups in Portugal are well oriented to the market, something not shared by other investigated departments of the hotels. So the current challenge for the main networks of hotels in Portugal is to improve the internal dissemination of information that marketing professionals gathered at the market.

Research on the High Robustness JavaEE Enterprise Development Mode based on Hadoop and Cloud Servers

In this paper, we conduct research on the high robustness JavaEE enterprise development mode based on Hadoop and cloud servers. The current virtual machine real-time migration can only achieve manual migration, and cannot achieve full-automatic migration. In other words, when the server overload requires the administrator to artificially select a low-load host, and then hit migration command to implement the migration. In recent years, the Hadoop is becoming popular, and the read performance of the data is measured in terms of the time overhead for reading the required data. The key to reducing read time is to optimize that Hadoop cloud data read time and the RDBMS data query time. This paper integrates the mentioned techniques to construct the novel JavaEE enterprise development pattern that will promote the further development of the related techniques.

E-commerce business model mining and prediction

We study the problem of business model mining and prediction in the e-commerce context. Unlike most existing approaches where this is typically formulated as a regression problem or a time-series prediction problem, we take a different formulation to this problem by noting that these existing approaches fail to consider the potential relationships both among the consumers （consumer influence） and among the shops （competitions or collaborations）. Taking this observation into consideration, we propose a new method for e-commerce business model mining and prediction, called EBMM, which combines regression with community analysis. The challenge is that the links in the network are typically not directly observed, which is addressed by applying information diffusion theory through the consumer-shop network. Extensive evaluations using Alibaba Group e-commerce data demonstrate the promise and superiority of EBMM to the state-of-the-art methods in terms of business model mining and prediction.

Multiple Multi-Qubit Quantum States Sharing

A multiple multi-qubit quantum states sharing scheme is proposed,in which the dealer can share multiple multi-qubit quantum states among the participants through only one distribution and one recovery.The dealer encodes the secret quantum states into a special entangled state,and then distributes the particles of the entangled state to the participants.The participants perform the single-particle measurements on their particles,and can cooperate to recover the multiple multi-qubit quantum states.Compared to the existing schemes,our scheme is more efficient and more flexible in practice.