The next-generation smartphones should provide a signification improvement in terms of personalization. A major challenge in smartphone personalization is how to tackle the diversity in smartphone usage. This paper presents iLauncher, an intelligent quick launch that can adapt to individual usage patterns on the fly to change apps dynamically without user intervention. The rationale behind the development process is that we collected traces of real user activity and conducted statistical analysis to derive some observations that provide useful insights into the design of our algorithm. The results of experiments conducted to evaluate the proposed algorithm are encouraging in terms of prediction accuracy. We have implemented iLauncher based on the algorithm and released it in an Android marketplace for free usage.
It is not unusual that BOT firms are granted to develop or operate certain business/project beyond the main scope of a BOT project, such as the surrounding land development. By granting these BOT project associated business, government can improve the project expected return and financial viability, and encourage potential developers to participate in BOT projects. Nevertheless, for host government, it is very difficult and subjective to evaluate the motivating effects or policy effectiveness. For developers, inaccurate valuation of associated businesses may cause serious bias during BOT project bidding process. For fund providers, such as lenders, contract design depends on accurately evaluating the overall value and risk level of a BOT project. As a result, it is crucial to accurately price the associated business. In this paper, real options theory, a dynamic asset pricing approach, is used to evaluate the associated business. Theory of mechanism design based on game theory is incorporated with the real options to investigate the government policy effectiveness and optimal policy design. A computing algorithm for valuation and optimal debt contract is developed.
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