作业评价系统的研究与设计

作业评价作为课程评价的一个重要方面,反映了学生在学习过程中的发展情况.本文在分析过程性评价、多元化评价以及个性化反馈理念的基础上,设计了基于Web的作业评价与反馈系统.将作业展示在学习平台中,通过自评、互评、教评层层递进的形式对学习过程进行多元化的全面评价,针对互动评价过程进行个性化反馈和指导,引导学生自我反思,调动学生积极性,促进学生全面发展.     

汽车电动助力转向系统的混杂控制与试验

汽车电动助力转向(EPS)系统以蓄电池为能源,以电动机为动力元件,汽车EPS控制系统的设计是提高EPS系统性能和电动机效率的关键.分析了汽车EPS系统的混杂特性,可分为助力工况、回正工况和阻尼工况.设计了汽车EPS混杂控制系统,助力工况采用由Bang-bang控制和变参数双模糊控制组成的双模态控制器;回正工况采用PID控制器;阻尼控制采用电动机制动转矩控制方式.设计了实车试验系统,进行了转向手感实车试验和回正控制实车试验.汽车EPS系统的混杂控制充分反映了汽车EPS系统的工作状况,优化了EPS系统的功能和控制效果,增强了转向操纵的安全性,提高了EPS电动机的工作效率和节能环保能力.     

Linear discriminant projection embedding based on patches alignment

Dimensionality reduction is often required as a preliminary stage in many data analysis applications. In this paper, we propose a novel supervised dimensionality reduction method, called linear discriminant projection embedding (LDPE), for pattern recognition. LDPE first chooses a set of overlapping patches which cover all data points using a minimum set cover algorithm with geodesic distance constraint. Then, principal component analysis (PCA) is applied on each patch to obtain the data's local representations. Finally, patches alignment technique combined with modified maximum margin criterion (MMC) is used to yield the discriminant global embedding. LDPE takes both label information and structure of manifold into account, thus it can maximize the dissimilarities between different classes and preserve data's intrinsic structures simultaneously. The efficiency of the proposed algorithm is demonstrated by extensive experiments using three standard face databases (ORL, YALE and CMU PIE). Experimental results show that LDPE outperforms other classical and state of art algorithms.     

简析服装流行色视觉评价指标体系的构建

服装流行色视觉评价指标体系在服装流行色预测、应用与研究中能够起到很好的作用。文章就服装流行色视觉评价指标体系中应包括的指标进行了论证。指标体系中的指标主要有两个方面,一是色彩自身多样形式的指标,二是色彩在不同载体上的多样形式指标。它们是色彩三要素配色形式、色彩数量、色彩三要素、色彩形状、色彩面积、色彩图地形式、色彩均衡形式、色彩装饰位置;色彩与材质结合的色彩肌理、色彩与材质经特殊加工的色彩肌理等。     

Chaotic self-adaptive particle swarm optimization algorithm for dynamic economic dispatch problem with valve-point effects

This paper presents a chaotic self-adaptive particle swarm optimization algorithm (CSAPSO) to solve dynamic economic dispatch problem (DED) with value-point effects. The proposed algorithm takes PSO as the main evolution method. The velocity, a sensitive parameter of PSO, is adjusted dynamically to increase the precision of PSO. To overcome the drawback of premature in PSO, chaotic local search is imported into proposed algorithm. Moreover, a new strategy is proposed to handle the various constraints of DED problem in this paper, the results solved by proposed strategy can satisfy the constraints of DED problem well. Finally, the high feasibility and effectiveness of proposed CSAPSO algorithm is validated by three test systems consisting of 10 and extended 30 generators while compared with the experimental results calculated by the other methods reported in this literature.     

Cryptanalysis and improvement of a threshold proxy signature scheme

A (t, n) threshold proxy signature scheme allows any t or more proxy signers to cooperatively sign messages on behalf of an original signer, but t ? 1 or fewer proxy signers cannot. In a recent work [C.H. Yang, S.F. Tzeng, M.S. Hwang, On the efficiency of nonrepudiable threshold proxy signature scheme with known signers, Systems and Software 73(3) (2004) 507–514], C.H. Yang, S.F. Tzeng and M.S. Hwang proposed a new threshold proxy signature scheme (called as YTH scheme), which is more efficient in algorithm and communication than Hsu et al.'s scheme proposed in 2001. However, YTH scheme still has some security weaknesses. In this paper, we show that YTH scheme cannot resist frame attack and public-key substitute attack. A new improvement with high safety and efficiency is proposed. The new scheme remedies the weaknesses of YTH scheme, especially, it can resist public-key substitute attack successfully by Zero-Knowledge Proof. Furthermore, the system doesn't need a security channel and computational complexity can be lowered.     

Supporting early pruning in top-k query processing on massive data

This paper analyzes the execution behavior of “No Random Accesses” (NRA) and determines the depths to which each sorted file is scanned in growing phase and shrinking phase of NRA respectively. The analysis shows that NRA needs to maintain a large quantity of candidate tuples in growing phase on massive data. Based on the analysis, this paper proposes a novel top-k algorithm Top-K with Early Pruning (TKEP) which performs early pruning in growing phase. General rule and mathematical analysis for early pruning are presented in this paper. The theoretical analysis shows that early pruning can prune most of the candidate tuples. Although TKEP is an approximate method to obtain the top-k result, the probability for correctness is extremely high. Extensive experiments show that TKEP has a significant advantage over NRA.     

A structure-preserved local matching approach for face recognition

In this paper, a novel local matching method called structure-preserved projections (SPP) is proposed for face recognition. Unlike most existing local matching methods which neglect the interactions of different sub-pattern sets during feature extraction, i.e., they assume different sub-pattern sets are independent; SPP takes the holistic context of the face into account and can preserve the configural structure of each face image in subspace. Moreover, the intrinsic manifold structure of the sub-pattern sets can also be preserved in our method. With SPP, all sub-patterns partitioned from the original face images are trained to obtain a unified subspace, in which recognition can be performed. The efficiency of the proposed algorithm is demonstrated by extensive experiments on three standard face databases (Yale, Extended YaleB and PIE). Experimental results show that SPP outperforms other holistic and local matching methods.     

基于DSP数字心电图机的设计

介绍12导联数字心电图机研制开发,采用双CPU架构,包括数字信号处理TMS320F206和微控制器AT89C55.该仪器利用数字信号处理器TMS320F206PZ实现实时对心电信号进行滤波和心电参数计算;热敏打印心电图形和检测结果;存储病人的心电数据,心电图形的回放打印,与PC机进行数据通主,建立病人的心电数据库,进一步研究分析.     

一种标签劣质XML数据上的twig查询处理的优化

XML数据中的不正确数据、不一致数据、不精确数据等劣质数据给XML.数据上的有效查询处理带来了挑战.专注于研究标签劣质的XML数据上twig查询处理的优化方法,文中分别给出了优化方法的原理、伪代码、正确性证明和复杂度分析,并通过例子加以解释.通过实验验证了优化方法的效率.