In order to make strategic decision on firms’ sharing reward program( SRP), a nested Stackelberg game is developed. The sharing behavior among users and the rewarding strategy of firms are modeled. The optimal sharin...In order to make strategic decision on firms’ sharing reward program( SRP), a nested Stackelberg game is developed. The sharing behavior among users and the rewarding strategy of firms are modeled. The optimal sharing bonus is worked out and the impact of social relationships among customers is discussed. The results show that the higher the bonus,the more efforts the inductor is willing to make to persuade the inductee into buying. In addition,the firms should take the social relationship into consideration when setting the optimal sharing bonus. If the social relationship is weak,there is no need to adopt the SRP. Otherwise,there are two ways to reward the inductors. Also,the stronger the social relationship,the fewer the sharing bonuses that should be offered to the inductors,and the higher the expected profits. As a result,it is reasonable for the firms to implement SRPs on the social media where users are familiar with each other.展开更多
This paper studies a high-speed text-independent Automatic Speaker Recognition(ASR)algorithm based on a multicore system's Gaussian Mixture Model(GMM).The high speech is achieved using parallel implementation of t...This paper studies a high-speed text-independent Automatic Speaker Recognition(ASR)algorithm based on a multicore system's Gaussian Mixture Model(GMM).The high speech is achieved using parallel implementation of the feature's extraction and aggregation methods during training and testing procedures.Shared memory parallel programming techniques using both OpenMP and PThreads libraries are developed to accelerate the code and improve the performance of the ASR algorithm.The experimental results show speed-up improvements of around 3.2 on a personal laptop with Intel i5-6300HQ(2.3 GHz,four cores without hyper-threading,and 8 GB of RAM).In addition,a remarkable 100%speaker recognition accuracy is achieved.展开更多
基金The National Social Science Foundation of China(No.17BGL196)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.KYLX15_0193)
文摘In order to make strategic decision on firms’ sharing reward program( SRP), a nested Stackelberg game is developed. The sharing behavior among users and the rewarding strategy of firms are modeled. The optimal sharing bonus is worked out and the impact of social relationships among customers is discussed. The results show that the higher the bonus,the more efforts the inductor is willing to make to persuade the inductee into buying. In addition,the firms should take the social relationship into consideration when setting the optimal sharing bonus. If the social relationship is weak,there is no need to adopt the SRP. Otherwise,there are two ways to reward the inductors. Also,the stronger the social relationship,the fewer the sharing bonuses that should be offered to the inductors,and the higher the expected profits. As a result,it is reasonable for the firms to implement SRPs on the social media where users are familiar with each other.
文摘This paper studies a high-speed text-independent Automatic Speaker Recognition(ASR)algorithm based on a multicore system's Gaussian Mixture Model(GMM).The high speech is achieved using parallel implementation of the feature's extraction and aggregation methods during training and testing procedures.Shared memory parallel programming techniques using both OpenMP and PThreads libraries are developed to accelerate the code and improve the performance of the ASR algorithm.The experimental results show speed-up improvements of around 3.2 on a personal laptop with Intel i5-6300HQ(2.3 GHz,four cores without hyper-threading,and 8 GB of RAM).In addition,a remarkable 100%speaker recognition accuracy is achieved.
