Efficiently Disassemble-and-Pack for Mechanism

In this paper, we present a disassemble-and-pack approach for a mechanism to seek a box which contains total mechanical parts with high space utilization. Its key feature is that mechanism contains not only geometric shapes but also internal motion structures which can be calculated to adjust geometric shapes of the mechanical parts. Our system consists of two steps: disassemble mechanical object into a group set and pack them within a box efficiently. The first step is to create a hierarchy of possible group set of parts which is generated by disconnecting the selected joints and adjust motion structures of parts in groups. The aim of this step is seeking total minimum volume of each group. The second step is to exploit the hierarchy based on breadth-first-search to obtain a group set. Every group in the set is inserted into specified box from maximum volume to minimum based on our packing strategy. Until an approximated result with satisfied efficiency is accepted, our approach finish exploiting the hierarchy.Comment: 2 pages, 2 figure

Understanding the determinants of self-service technology (SST) adoption in fast-food chain setting

In today’s business environment, the way that people interact with service providers has been witnessed a dramatic change. Service encounter has been gradually substituted by technology-based self service. Self checkout system, as one of the most important type of SST, has been widely adopted in different industries, such as hotel, supermarket, oil pump station, etc. However, limited success has been witnessed in a fast-food restaurant setting. In particular, the success of SST adoption from a customer perspective is unclear. Thus, the main purpose of this study is to examine a customer evaluation model including attitude, satisfaction and re-use intention of SST by identifying key antecedents. Besides, this study further delivered managerial implications to practitioners who run fast-food business aiming to address the practical issues. A quantitative method was used to investigate these issues by generating solid and insightful findings though SPSS analysis. The findings suggest that various antecedents offer different levels of explanatory power toward consequences (attitude, satisfaction and intention). The explanatory power also varies from different demographic factors (e.g. age group, education level). From this perspective, this study offered directions that marketing practitioners should focus on and put effort in, and helped them to understand the evaluation process of SST from a customer perspective. Finally, the limitation of this research was also discussed in the end of study

An Optimization Approach for Pricing Analysis on a Bank Wealth-Management Equity Structured Product

This paper researches on the pricing and design of a certain stock-type structured product. Firstly, a semi-analytic pricing model is deduced by discounting the payoff function of the product. Secondly, the difference between publishers\u27 and investors\u27 required rate of return is explained with market segmentation theory when estimating the pricing model’s parameters, which defines the cost and sale price of a product. Finally, with sensitivity analysis, it is concluded that publishers can increase their profits by extending the due date of the product or publishing it with relatively large asset volatility. The study aims to help publishers make reasonable product design and pricing decisions

An Optimization Approach for pricing of Discrete European Call options Based on the Preference of Investors

Firstly, a method for measuring the risk aversion of investors was proposed based on the prospect theory. Secondly, under a sole hypothetical condition in which the risk aversion degree for different assets is the same in a market, the pricing of discrete European options was given based on the objective probability. Thirdly, it was proven that the European option price obtained was a non-arbitrate price. And then, both for the binomial tree, which is a complete market, and for the trinomial tree, which is an incomplete market, pricing European options were discussed by implementing the method provided in this paper. Lastly, an illustration is used to demonstrate how to estimate preference parameters from market data and how to calculate options prices. The result states that the method in this paper is the same as the traditional risk-neutral methods in a complete market, but it is different from the traditional risk-neutral methods in an incomplete market, and more, the price obtained in this paper is affected by the objective probability and also contains the risk attitude of the investors

Defining and identifying the optimal embedding dimension of networks

Network embedding is a general-purpose machine learning technique that encodes network structure in vector spaces with tunable dimension. Choosing an appropriate embedding dimension -- small enough to be efficient and large enough to be effective -- is challenging but necessary to generate embeddings applicable to a multitude of tasks. Unlike most existing strategies that rely on performance maximization in downstream tasks, here we propose a principled method for the identification of an optimal dimension such that all structural information of a network is parsimoniously encoded. The method is validated on various embedding algorithms and a large corpus of real-world networks. Estimated values of the optimal dimension in real-world networks suggest that efficient encoding in low-dimensional spaces is usually possible.Comment: 9 pages, 5 figures + Suppl. Ma

Re-Expression of AKAP12 Inhibits Progression and Metastasis Potential of Colorectal Carcinoma In Vivo and In Vitro

Background: AKAP12/Gravin (A kinase anchor protein 12) is one of the A-kinase scaffold proteins and a potential tumor suppressor gene in human primary cancers. Our recent study demonstrated the highly recurrent loss of AKAP12 in colorectal cancer and AKAP12 reexpression inhibited proliferation and anchorage-independent growth in colorectal cancer cells, implicating AKAP12 in colorectal cancer pathogenesis. Methods: To evaluate the effect of this gene on the progression and metastasis of colorectal cancer, we examined the impact of overexpressing AKAP12 in the AKAP12-negative human colorectal cancer cell line LoVo, the single clone (LoVo-AKAP12) compared to mock-transfected cells (LoVo-CON). Results: pCMV6-AKAP12-mediated AKAP12 re-expression induced apoptosis (3 % to 12.7%, p,0.01), migration (89.667.5 cells to 31.064.1 cells, p,0.01) and invasion (82.765.2 cells to 24.763.3 cells, p,0.01) of LoVo cells in vitro compared to control cells. Nude mice injected with LoVo-AKAP12 cells had both significantly reduced tumor volume (p,0.01) and increased apoptosis compared to mice given AKAP12-CON. The quantitative human-specific Alu PCR analysis showed overexpression of AKAP12 suppressed the number of intravasated cells in vivo (p,0.01). Conclusion: These results demonstrate that AKAP12 may play an important role in tumor growth suppression and the survival of human colorectal cancer