应用型计算机本科教育课程体系的研究与探索

本文阐述应用型计算机教育的产生背景以及课程体系研究的必要性,分析应用型教育的特点及其课程体系建立应考虑的因素,并在此基础上给出具有地方特色的应用型计算机教育课程体系及该课程体系中的每个环节的具体构成,最后讨论该课程体系具体实施过程中可能遇到的问题。     

计算机上机实验课程质量保障方式探讨

计算机实验教学是深化理论教学、培养学生动手能力和提高学生素质的重要环节。本文对当前计算机实验教学中存在的问题进行了分析,提出建立文件存储服务器、上机实时监控软件和实验成绩评定数据库系统的方法,以此提高保障上机实验课程教学质量的能力。     

广西壮族干栏建筑对现代展示空间设计的应用探究

壮族干栏建筑是一种具有鲜明地方民族特色的民居类型,壮族干栏建筑以其独特的空间规划和结构独树一帜,现代的许多设计案例从中深受其启发,展示设计也不例外。空间规划是展示设计中的重要要素之一,壮族干栏建筑的空间结构形式对于展示空间规划很有启发作用。本文从壮族干栏建筑中的空间规划和结构特点分析,结合现代展示设计对空间的处理中强调空间层次的体验感,进行探讨干栏建筑对展示设计空间规划的可行性启示。     

基于SLAM的虚实配准方法研究

研究和实现了一种基于SLAM技术的虚实配准方法,通过将SLAM分离为定位和构图,分别利用改进的pf做位姿估计和ukf进行位置估计,进而实现整个场景内目标的位姿计算,最终完成虚实配准。一定程度上解决了传统方法中存在的视域受限问题,并同时支持户内和户外应用,提高了增强现实系统的可用性。     

基于贝叶斯网的抗肺结核诊疗数据分析

将贝叶斯网络方法应用于临床抗肺结核诊疗数据分析,挖掘筛选出有价值的信息,建立一个能够为以后的治疗提供有价值的参考作用的医院医疗方案以及模型.     

Data-driven testing methodology for RFID systems

A radio-frequency identification (RFID) system including hardware and software may be updated from time to time after first time deployment. To ensure the reliability of the system, extensive tests are required. However, enumerating all test cases is infeasible, especially when the tests involve time-consuming hardware operations. To solve this problem, we propose a testing methodology for RFID systems which does not enumerate all test cases but rather those which are representative. A clustering method is adopted in selecting representative test cases. Although a small number of selected test cases are run, we can still obtain a relatively high bug detection rate compared with running the enumerated test cases. Our extensive experiments show the efficiency and effectiveness of our testing methodology.     

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.     

A novel color image watermarking scheme in nonsampled contourlet-domain

Geometric distortion is known as one of the most difficult attacks to resist, for it can desynchronize the location of the watermark and hence causes incorrect watermark detection. It is a challenging work to design a robust color image watermarking scheme against geometric distortions. Based on the support vector regression (SVR) and nonsubsampled contourlet transform (NSCT), we propose a new color image watermarking algorithm with good visual quality and reasonable resistance toward geometric distortions in this paper. Firstly, the geometrically invariant space is constructed by using color image normalization, and a significant region is obtained from the normalized color image by utilizing the invariant centroid theory. Then, the NSCT is performed on the green channel of the significant region. Finally, the digital watermark is embedded into host color image by modifying the low frequency NSCT coefficients, in which the HVS masking is used to control the watermark embedding strength. In watermark detection, according to the high correlation among different channels of the color image, the digital watermark can be recovered by using SVR technique. Experimental results show that the proposed color image watermarking is not only invisible and robust against common image processing operations such as filtering, noise adding, and JPEG compression etc., but also robust against the geometrical distortions.     

Neighborhood rough set and SVM based hybrid credit scoring classifier

The credit scoring model development has become a very important issue, as the credit industry is highly competitive. Therefore, considerable credit scoring models have been widely studied in the areas of statistics to improve the accuracy of credit scoring during the past few years. This study constructs a hybrid SVM-based credit scoring models to evaluate the applicant’s credit score according to the applicant’s input features: (1) using neighborhood rough set to select input features; (2) using grid search to optimize RBF kernel parameters; (3) using the hybrid optimal input features and model parameters to solve the credit scoring problem with 10-fold cross validation; (4) comparing the accuracy of the proposed method with other methods. Experiment results demonstrate that the neighborhood rough set and SVM based hybrid classifier has the best credit scoring capability compared with other hybrid classifiers. It also outperforms linear discriminant analysis, logistic regression and neural networks.     

降低协同设计虚拟机启动开销的译码后指令缓存技术

协同设计虚拟机采用动态二进制翻译实现不同体系结构间的二进制兼容,对源指令的翻译和处理影响了协同设计虚拟机的启动性能.研究发现,在一个采用解释执行和翻译相结合的协同设计虚拟机中,处理非热点代码的解释执行是虚拟机启动开销的主要来源.发现了协同设计虚拟机中的解释例程局部性,并提出了一种硬件译码后指令缓存结构DICache(d...