基于网络的智能辅导模式研究与系统设计

针对目前辅导行业的现状,为解决课后辅导的自动化、实时化的问题,分析了学生课后学习掌握知识的过程,提出了一个基于学生课后学习规律的辅导模型,建立了面向问题的多层面知识辅导新模式,构建了基于此模式的网络智能家教系统的框架结构。该系统采用基于知识的自动推理技术使得推理过程得以完整保存来分析后续的多层面辅导信息,采用资源模型分解知识粒度保证抽象度,采用网络服务模式满足用户的实时使用。以学生提出的几何问题为实例,展示了多层面辅导过程,实验结果表明了该模式和系统设计的可行性。     

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.     

Automatic detection of breast cancers in mammograms using structured support vector machines

Breast cancer is one of the most common cancers diagnosed in women. Large margin classifiers like the support vector machine (SVM) have been reported effective in computer-assisted diagnosis systems for breast cancers. However, since the separating hyperplane determination exclusively relies on support vectors, the SVM is essentially a local classifier and its performance can be further improved. In this work, we introduce a structured SVM model to determine if each mammographic region is normal or cancerous by considering the cluster structures in the training set. The optimization problem in this new model can be solved efficiently by being formulated as one second order cone programming problem. Experimental evaluation is performed on the Digital Database for Screening Mammography (DDSM) dataset. Various types of features, including curvilinear features, texture features, Gabor features, and multi-resolution features, are extracted from the sample images. We then select the salient features using the recursive feature elimination algorithm. The structured SVM achieves better detection performance compared with a well-tested SVM classifier in terms of the area under the ROC curve.     

Analysis of application patterns of Z-type MEMS microspring

In this paper, we design a Z-type microspring, which consists of several “Z” type micromechanical beams within mutual connection. With good mechanical performance and mature LIGA fabrication technology, Ni is chosen as the material of Z-type MEMS microspring. The mechanical properties of electroformed Ni have been tested by the Micro Hardness Tester, and the Young’s modulus is 219 GPa. Different from traditional springs, microsprings can be divided into three application patterns in direction x, y, and z to study. Applying the Castigliano second theorem of energy method in macro theory, the formulas used to calculate the spring constant of Z-type microspring in the directions of the three application patterns were derived, and verified by the ANSYS finite element method. Using the Tytron250 micro force test machine, the experiments of the Z-type microspring deformation properties were carried out. The spring constant, rupture force and rupture strength of Z-type microspring in direction y are 3821 N/m, 1.64 N and 1.61 GPa, respectively. The experimental results agree with the theoretical analysis. Based on the analysis above, the change laws of the spring constant of microspring in the three application patterns are summarized.     

Picture or it didn’t happen: catch the truth for events

Multimedia Tools and Applications - Pictures spreading on the Internet are essential for the authenticity of events. Each day, huge amounts of data are published on social media, and many of them...     

Continuous-variable quantum homomorphic signature

Quantum cryptography is believed to be unconditionally secure because its security is ensured by physical laws rather than computational complexity. According to spectrum characteristic, quantum information can be classified into two categories, namely discrete variables and continuous variables. Continuous-variable quantum protocols have gained much attention for their ability to transmit more information with lower cost. To verify the identities of different data sources in a quantum network, we propose a continuous-variable quantum homomorphic signature scheme. It is based on continuous-variable entanglement swapping and provides additive and subtractive homomorphism. Security analysis shows the proposed scheme is secure against replay, forgery and repudiation. Even under nonideal conditions, it supports effective verification within a certain verification threshold.     

基于跳频和同步捕获技术的水下无线通信技术研究

本文所阐述的水下无线技术即基于跳频技术和同步捕获技术的水声通信,由于声波在海水中的传播特性显著优越于电磁波和可见光,使得水声技术成为海洋高技术的主要研究领域之一 ,在国防领域也具有十分重要的研究意义.本文主要论述了水声通信中跳频技术和同步捕获技术的原理、具体算法的实现方案以及部分硬件设施的使用简述,并通过展示实验结果验证算法的可行性.     

医院超声图象管理系统的设计与实现

介绍了医院超声图象管理系统的功能和特点,并阐述了其关键技术。     

蒙特卡罗法及其在射弹散布仿真中的应用

作战仿真的真实性需要对抗双方火力射击效果的真实体现。文中提出了一种利用蒙特卡罗法进行射弹散布仿真的方法 ,并将结果与实际情况进行了比较。该方法已用于装甲兵数字化作战仿真实验室的作战仿真中