Federated learning (FL) relies on a sufficient number of clients to utilize their local data for model training, making the incentive mechanism a crucial component for its success. Given the significant impact of the training dataset on FL performance, we introduce two key metrics: the scale and diversity of the training data. These factors are vital for improving model accuracy. However, designing an incentive mechanism that accounts for both the scale and diversity of data in FL is a challenge task. To address this, we propose an auction-based method for multi-dimensional objectives, called the diversity-aware incentive mechanism (DAIM). We prove that the DAIM satisfies three important properties: truthfulness, individual rationality and budget feasibility. Under this mechanism, clients are incentivized to truthfully report the size, distribution and cost of their local datasets, with selected clients contributing all or part of their data to federated model training. Experimental results show that, especially when the budget is limited, DAIM outperforms existing methods that ignore data diversity, particularly when there is significant variation in dataset distributions across clients.

In Internet of Things (IoT) systems, the vast amounts of personal data generated by IoT devices offer significant opportunities for enhancing personalized services but also introduce substantial risks of privacy leakage. Taking into account personalized privacy concerns of users, in this work we design an machine learning-based optimal data transaction mechanism that incentivizes users to share their data based on their truthful privacy valuation. We treat data with varying privacy protection levels (PPLs) as distinct sale items. By offering multiple privacy options for users to choose from, the mechanism improves data utility and encourages users to select options that reflect their true privacy valuations. By integrating machine learning into the option design in mechanism, our approach achieves optimal data utility without prior knowledge of the privacy valuation distribution. Experimental results demonstrate that even with an unknown distribution of user privacy valuations, the proposed mechanism enables users to select the optimal PPL according to their preferences, while data buyers can maximize the utility of procured data.

设计了一个安全监护终端设备和综合服务网站。终端设备通过GPS模块接收地理位置信息,通过GPRS模块的TCP/IP协议发送给Internet上的服务器。服务器实现教育功能及终端位置查询功能,并通过谷歌地图显示。

文章从工科大学生的技能需求出发,提出了基本技能、实践技能和创新技能三大技能的需求,并就如何使学生获得这些技能进行了深入的探讨和研究。

FPGA partial dynamic reconfiguration is an innovative progress of the FPGA configuration methods,and will be widely applied.Accordingly,the FPGA structure,design process and solutions will all change dramatically.In this paper,the structural analysis is made of the FPGA which can be partially and dynamically reconfigured,and the methods of partial dynamic reconfiguration as well as the application solutions are proposed.

介绍了应用在大型仓库管理中拣货环节的一种电子装置称为电子标签或电脑辅助拣货系统的概念以及实现的方法。

传统的拣货方式由于速度慢、正确率低等原因已不能满足物流产业的飞速发展,本文提出一种用于辅助拣货的电子标签系统的设计方法,实现了计算机对整个拣货过程进行实时监控管理,提高了物流中心拣货的速度,且正确率可达99%以上.

主要介绍了由微机单片机单片机构成的一种主从分布式系统模型及其多机串口通信程序的实现过程.