电话防盗报警器

详细介绍了电话通讯技术以及安全报警技术的应用，二者如何有效地结合起来形成综合联网报警系统。分析了HT9200A和MT8870DC的电路结构，及与AT89C51的接口电路。     

An approach for minimizing a quadratically constrained fractional quadratic problem with application to the communications over wireless channels

Studies for the cognitive model are relatively new in the literature; however there is a growing interest in the communication field nowadays. This paper considers the cognitive model in the communication field as the problem of minimizing a fractional quadratic problem, subject to two or more quadratic constraints in complex field. Although both denominator and numerator in the fractional problem are convex, this problem is not so simple since the quotient of convex functions is not convex in most cases. We first change the fractional problem into a non-fractional one. Second, we consider the semi-definite programming (SDP) method. For the problem with m (m≤2) constraints, we use the SDP relaxation and obtain the exact optimal solution. However, for the problem with m (m>2) constraints, we choose the randomization method to gain an approximation solution in the complex case. At last, we apply this method to practical communications over wireless channels with good results.     

基于OLPP符号表示的时间序列分类算法

基于符号表示的时间序列分类方法是时间序列数据挖掘的关键技术。大部分现有方法主要针对单个时间序列样本进行符号表示,没有考虑样本间的近邻关系对符号化分类的影响。对此提出一种基于正交局部保持映射(Orthogonal Locality Preserving Projection,OLPP)的时间序列符号表示方法。使用OLPP对原始数据集进行维数约减,利用信息增益寻找维数约减后数据的最佳符号投影区间,采用多重系数分箱技术(Multiple Coefficient Binning,MCB)将降维后数据表示成符号序列。该算法在20个时间序列数据集上的分类效果好于已有方法,有效利用样本间的近邻关系能够显著提高算法的分类性能。     

基于模糊兴趣模型与多Agent的个性化推荐系统

提出了基于模糊兴趣模型与多Agent的个性化推荐系统框架,通过引入用户模糊兴趣模型,使以Agent为基础的推荐系统无法通过隐式收集用户对商品属性评价的问题得到解决,并且在客户端收集并挖掘用户的私有信息,然后从服务器中获取用户感兴趣的信息,最后生成并更新UserProfile。     

联邦学习中的隐私保护技术研究综述

近年来,联邦学习成为解决机器学习中数据孤岛与隐私泄露问题的新思路。联邦学习架构不需要多方共享数据资源,只要参与方在本地数据上训练局部模型,并周期性地将参数上传至服务器来更新全局模型,就可以获得在大规模全局数据上建立的机器学习模型。联邦学习架构具有数据隐私保护的特质,是未来大规模数据机器学习的新方案。然而,该架构的参数交互方式可能导致数据隐私泄露。目前,研究如何加强联邦学习架构中的隐私保护机制已经成为新的热点。从联邦学习中存在的隐私泄露问题出发,探讨了联邦学习中的攻击模型与敏感信息泄露途径,并重点综述了联邦学习中的几类隐私保护技术：以差分隐私为基础的隐私保护技术、以同态加密为基础的隐私保护技术、以安全多方计算（SMC）为基础的隐私保护技术。最后,探讨了联邦学习中隐私保护中的若干关键问题,并展望了未来研究方向。     

Fuzzy induced generalized aggregation operators and its application in multi-person decision making

We present a wide range of fuzzy induced generalized aggregation operators such as the fuzzy induced generalized ordered weighted averaging (FIGOWA) and the fuzzy induced quasi-arithmetic OWA (Quasi-FIOWA) operator. They are aggregation operators that use the main characteristics of the fuzzy OWA (FOWA) operator, the induced OWA (IOWA) operator and the generalized (or quasi-arithmetic) OWA operator. Therefore, they use uncertain information represented in the form of fuzzy numbers, generalized (or quasi-arithmetic) means and order inducing variables. The main advantage of these operators is that they include a wide range of mean operators such as the FOWA, the IOWA, the induced Quasi-OWA, the fuzzy IOWA, the fuzzy generalized mean and the fuzzy weighted quasi-arithmetic average (Quasi-FWA). We further generalize this approach by using Choquet integrals, obtaining the fuzzy induced quasi-arithmetic Choquet integral aggregation (Quasi-FICIA) operator. We also develop an application of the new approach in a strategic multi-person decision making problem.     

Fire detection model in Tibet based on grey-fuzzy neural network algorithm

The fire signals are much weaker in low oxygen concentration and low pressure environment such as Tibet. Fire detectors which were calibrated in correlating standard conditions cannot work well in such condition. This paper presents a synthesis method of GM(1, 1) grey prediction model and adaptive neuro-fuzzy inference system (ANFIS) in advance to detect fire and to make it work in the environment. The theoretical analysis of the algorithm and experimental evaluation in Tibet are presented. In this process, the grey GM(1, 1) predict model can anticipate the development of fire signals without any assumption, thus allowing earlier fire alarm than traditional fire detection equipments, meanwhile, ANFIS can make sure the data processing more accurate to avoid false alarms. This work will supply useful suggestions with the fire detectors design in low ambient pressure and low oxygen concentration such as Tibet, etc.     

针对AES分组密码S盒的差分故障分析

研究了AES分组密码对差分故障攻击的安全性,攻击采用面向字节的随机故障模型,结合差分分析技术,通过在AES第8轮列混淆操作前导入随机单字节故障,一次故障导入可将AES密钥搜索空间由2128降低到232.3,在93.6%的概率下,两次故障导入无需暴力破解可直接恢复128位AES密钥.数学分析和实验结果表明:分组密码差分S盒取值的不完全覆盖性为差分故障分析提供了可能性,而AES密码列混淆操作良好的扩散特性极大的提高了密钥恢复效率,另外,本文提出的故障分析模型可适用于其它使用S盒的分组密码算法.     

基于小波分解和鉴别共同矢量的人耳识别

针对高维、小样本的情况下使用Fisher线形鉴别分析进行特征提取存在的病态奇异问题,提出一种新的特征提取方法,即先对人耳样本图像进行二维离散小波分解,再利用DCV算法对小波分解后的低频信息分量作进一步的降维处理。不仅克服了小样本问题,也解决了直接使用DCV算法对人耳图像降维所引起的计算量大和计算速度过慢的问题。实验证明,该方法具有较好的识别率,是一种有效的特征提取算法。     

基于WLAN的手机移动视频监控系统设计

介绍WLAN下手机移动视频监控的应用场景,详细描述该系统的设计,采用Android手机作为视频采集端和视频客户端,使用JPEG2000的无损压缩方式对采集的视频进行压缩编码,使得客户端能获取到清晰的视频图像。