Several multi-criteria programming methods for classification

In this paper, we propose a general optimization-based model for classification. Then we show that some well-known optimization-based methods for classification, which were developed by Shi et al. [Data mining in credit card portfolio management: a multiple criteria decision making approac. In: Koksalan M, Zionts S, editors. Multiple criteria decision making in the new millennium. Berlin: Springer; 2001. p. 427–36] and Freed and Glover [A linear programming approach to the discriminant problem. Decision Sciences 1981; 12: 68–79; Simple but powerful goal programming models for discriminant problems. European Journal of Operational Research 1981; 7: 44–60], are special cases of our model. Moreover, three new models, MCQP (multi-criteria indefinite quadratic programming), MCCQP (multi-criteria concave quadratic programming) and MCVQP (multi-criteria convex programming), are developed based on the general model. We also propose algorithms for MCQP and MCCQP, respectively. Then we apply these models to three real-life problems: credit card accounts, VIP mail-box and social endowment insurance classification. Extensive experiments are done to compare the efficiency of these methods.     

Performance Analysis of Gradient Neural Network Exploited for Online Time-Varying Matrix Inversion

This technical note presents theoretical analysis and simulation results on the performance of a classic gradient neural network (GNN), which was designed originally for constant matrix inversion but is now exploited for time-varying matrix inversion. Compared to the constant matrix-inversion case, the gradient neural network inverting a time-varying matrix could only approximately approach its time-varying theoretical inverse, instead of converging exactly. In other words, the steady-state error between the GNN solution and the theoretical/exact inverse does not vanish to zero. In this technical note, the upper bound of such an error is estimated firstly. The global exponential convergence rate is then analyzed for such a Hopfield-type neural network when approaching the bound error. Computer-simulation results finally substantiate the performance analysis of this gradient neural network exploited to invert online time-varying matrices.     

一种基于W7100A的实验室仪器信息采集系统

针对实验室仪器信息统计中的准确性、完整性欠缺及低效率等问题,设计了一种全新的实验室仪器信息采集系统,以低功耗网络微处理器W7100A为系统的主控制器,通过SHT11温湿度传感模块和ZLG500AT射频IC模块直接采集仪器的环境参数等信息,通过用户与上位机客户端软件交互的方式采集仪器的工作内容等信息,相较于传统的手工记录方式,信息采集的及时性、完整性、可靠性方面都有了极大的提高.     

L1-norm based null space discriminant analysis

Multimedia Tools and Applications - Null space based linear discriminant analysis (NSLDA) is a well-known feature extraction method, which can make use of the most discriminant information in the...     

流体动密封压力接头的计算机辅助设计与选型

介绍在AutoCAD 2 0 0 0上 ,如何运用ObjectARX开发集流体动密封压力接头选型、设计绘图与客户信息查询于一体的CAD软件系统。     

A MEMS Thermal Biosensor for Metabolic Monitoring Applications

This paper presents a microelectromechanical systems (MEMS) differential thermal biosensor integrated with microfluidics for metabolite measurements in either flow-injection or flow-through mode. The MEMS device consists of two identical freestanding polymer diaphragms, resistive heaters, and a thermopile between the diaphragms. Integrated with polymer-based microfluidic measurement chambers, the device allows sensitive measurement of small volumes of liquid samples. Enzymes specific to a metabolic analyte system are immobilized on microbeads packed in the chambers. When a sample solution containing the analyte is introduced to the device, the heat released from the enzymatic reactions of the analyte is detected by the thermopile. The device has been tested with glucose solutions at physiologically relevant concentrations. In flow-injection mode, the device demonstrates a sensitivity of approximately 2.1 muV/mM and a resolution of about 0.025 mM. In flow-through mode with a perfusion flow rate of 0.5 mL/h, the sensitivity and resolution of the device are determined to be approximately 0.24 muV/mM and 0.4 mM, respectively. These results illustrate that the device, when integrated with subcutaneous sampling methods, can potentially allow for continuous monitoring of glucose and other metabolites.     

指纹图象预处理

采用块方向图滤波的方法实现了沿指纹纹线方向的图象增强及图象的二值化,用细化模板匹配的迭代方法实现了纹线的细化,解决了指纹纹线复杂难以提取的问题,具体实现了指纹图象的预处理。经过预处理后提取出了纹线,且保留了纹线的关键信息,有利于下一步的特征提取工作。