基于KL散度的用户相似性协同过滤算法

大多数用户相似性算法在计算用户相似性时只考虑了用户间的共同评分项,而忽略了用户其他评分中可能隐藏的有价值信息.为了准确评估用户间的相似性,提出了一种基于KL散度的用户相似性协同过滤算法.该算法不仅利用了共同评分项,还考虑了其他非共同评分信息的影响.该算法充分利用了用户的所有评分信息,提高了用户相似性度量的可靠性和准确性.实验结果表明,该算法优于当前主流的用户相似性算法,且在没有共同评分信息的条件下,仍能有效地完成用户相似性度量,解决了对共同评分项的完全依赖问题,具有更好的适应性.     

纬编与经编织物线圈建模与仿真分析

分别探讨了纬编线圈和经编闭口线圈的结构,建立了相应的数学模型,在VC++平台下进行仿真分析,并在此基础上设计出较为复杂的织物效果。综合阐述了纬编和经编线圈的建模原理,为织物生产设计及进一步仿真提供了思路。实验表明:建立的模型曲线平滑,能形象地表达线圈的真实客观形态。     

基于散射光谱的材质分类识别研究

有效的甄别、掌握空间碎片的状态,是合理利用太空资源和在轨航天器规避风险的前提,为了安全、持续地开发和利用空间资源,基于散射光谱,使用夹角余弦和欧式距离嵌入K临近法(KNN-AC-ED),并与经典的朴素贝叶斯分类器作为对比,对实验室测得的空间碎片中常用的四种材质进行分类识别。分类识别的结果显示,KNN-AC-ED法比经典的朴素贝叶斯分类器总体分类精度高4%。研究表明:朴素贝叶斯分类器需要提取每个光谱曲线的三个特征,而特征提取费时费力;KNN-AC-ED法利用光谱线型和强度两种信息,不仅全面的反应了光谱的信息,且计算相对更快捷。通过对空间碎片常用材质的分类,为进一步研究空间碎片的尺寸、材质等信息提供一定的借鉴意义。     

基于锁相放大算法的微弱光谱分析

由于强噪声背景的影响,在进行光谱探测的过程中收集到的信号很微弱。为了能有效的去除噪声,提出了采用锁相放大算法去除噪声提取光谱特征信号的方法。研制编写锁相放大算法,对收集的光谱数据进行处理,分析处理后的结果,光谱特征获得了放大,进一步进行两种结果的中值归一化对比,该光谱曲线与原始光谱曲线线型基本一致,且具有平滑去噪效果。该成果对微弱光谱信号去除噪声的研究具有实际意义。     

直接乙醇燃料电池研究进展

直接乙醇燃料电池的研究受到广泛的关注,但是乙醇反应机理较为复杂,目前乙醇直接燃料电池的效率很低。乙醇催化效率的提高研究目前主要集中在催化剂的选择、使用和对渗透膜的改进上。结合报道和课题组对Pt基纳米线的相关研究,就乙醇直接燃料电池研究的现状、存在的问题以及未来的前景进行了综述。     

A neglected GABAergic astrocyte: Calcium dynamics and involvement in seizure activity

Gamma-aminobutyric acid (GABA) contributes substantially to neurocognitive function as an important inhibitory neurotransmitter in the human cerebral cortex. However, the pathophysiology of disorders such as epilepsy are not well understood, since GABA agonists are not quite effective in treating epilepsy. Knowledge of the mechanism of action of GABA would contribute to review previously proposed anti-epileptic processes by GABA agonists. In this study based on recent experiments on GABAergic astrocytes, we developed a modified GABAergic astrocyte model, and successfully simulated a long-lasting Ca²⁺ oscillation in astrocytes after 0.5-s stimulation of GABAergic transmission. We then incorporated this GABAergic astrocyte model into a classical Ullah-Schiff seizure model and surprisingly found that this GABAergic astrocyte model functions to hinder the anti-epileptic action of GABA agonists, thereby explaining their low efficiency in previous experiments. These results also update our knowledge of the mechanism of action of GABA and the effects of astrocytes on physiological and pathological functions of the brain.     

Damage localization for beams based on the wavelet correlation operator

The continuous wavelet transform (CWT) is one of the crucial damage identification tools in the vibration-based damage assessment. Because of the vanishing moment property, the CWT method is capable of featuring damage singularity in the higher scales, and separating the global trends and noise progressively. In the classical investigations about this issue, the localization property of the CWT is usually deemed as the most critical point. The abundant information provided by the scale-domain information and the corresponding effectiveness are, however, neglected to some extent. Ultimately, this neglect restricts the sufficient application of the CWT method in damage localization, especially in noisy conditions. In order to address this problem, the wavelet correlation operator is introduced into the CWT damage detection method as a post-processing. By means of the correlations among different scales, the proposed operator suppresses noise, cancels global trends, and intensifies the damage features for various mode shapes. The proposed method is demonstrated numerically with emphasis on characterizing damage in noisy environments, where the wavelet scale Teager-Kaiser energy operator is taken as the benchmark method for comparison. Experimental validations are conducted based on the benchmark data from composite beam specimens measured by a scanning laser vibrometer. Numerical and experimental validations/comparisons present that the introduction of wavelet correlation operator is effective for damage localization in noisy conditions.     

结合自适应稀疏表示和全变分约束的图像重建

In view of the limitation of fixed complete orthogonal transformation, represented by two-dimensional wavelet transform and discrete cosine transform in compressed sensing high-resolution image reconstruction, this paper proposes a new method for high-resolution image reconstruction based on adaptive redundant dictionary sparse representation with the total variation constraint.The algorithm takes the intermediate image in the process of iteration as the training sample to get a redundant dictionary suitable for sample characteristics by adaptive learning. It makes full use of the correlation between dictionary atoms and the image to get an ideal complete sparse representation, thus reducing the sampling rate and improving the quality of image reconstruction. Finally, the algorithm takes the total variation as a constraint and uses the split Bregman iterative method to solve the sparse optimization problem. Simulation shows that the proposed method can reconstruct high quality images under a low sampling rate.     

Analysis on the gear-shifting schedule of hydraulic automatic transmission

With an advanced foreign hydraulic automatic transmission as the objective, an analytical method for the gear-shifting schedule is proposed. First the demanded maximum gradient of test is estimated. Then a test scheme and analytical procedure is formulated by initial test and hypothetical shift parameters. Finally through gear-shifting tests under different road conditions, load, accelerator pedal position limitation, throttle opening and output shaft speed are found to be the gear-shifting parameters. Under a common road condition, the gear-shifting schedule is a double-parameter schedule. Based on the driver''s demands on braking and dynamic performance, different shift schedules are made under downhill, uphill and quick releasing acceleration pedal conditions. The operation criteria of down-shift schedule on abrupt grade are proposed.     

互文视角下“日瓦戈的诗作”解读

长篇小说《日瓦戈医生》创造性地将主人公日瓦戈所写的25首诗独立成章,置于篇尾,并与整部小说有机地融合.本文选取其中较有代表性的五首诗,运用互文理论对其进行阐释,揭示在这种网状的互文关系中,诗歌文本世界内涵的丰富性以及作家带有浓厚宗教哲学意味的艺术观.