基于Proteus和Keil的单片机演奏乐曲的仿真

针对乐曲演奏在单片机实践教学中实现的不足,介绍了基于Proteus和Keil联调的单片机演奏乐曲的设计方法,通过对乐谱的音符和节拍进行编码,实现了乐曲演奏的功能。仿真结果表明：该方法电路简单、调试方便,只需简单的修改程序就可实现其它歌曲的演奏。     

An efficient t‐out‐of‐n oblivious transfer for information security and privacy protection

In t‐out‐of‐n oblivious transfer (OT), the receiver can only receive t messages out of n messages sent by the sender, and the sender has no idea about which ones have been received. Majority of the existence of previous efficient OT schemes require t calls of 1‐out‐of‐n OT to construct the t‐out‐of‐n OT. Its computational requirements and bandwidth consumption are quite demanding. On the basis of the elliptic curves cryptography, we propose a new t‐out‐of‐n OT protocol for private information retrieval in this article. It is more suitable for the smart cards or mobile units. Copyright © 2013 John Wiley & Sons, Ltd.     

Content-based image retrieval using local visual attention feature

Content-based image retrieval (CBIR) has been an active research topic in the last decade. As one of the promising approaches, salient point based image retrieval has attracted many researchers. However, the related work is usually very time consuming, and some salient points always may not represent the most interesting subset of points for image indexing. Based on fast and performant salient point detector, and the salient point expansion, a novel content-based image retrieval using local visual attention feature is proposed in this paper. Firstly, the salient image points are extracted by using the fast and performant SURF (Speeded-Up Robust Features) detector. Then, the visually significant image points around salient points can be obtained according to the salient point expansion. Finally, the local visual attention feature of visually significant image points, including the weighted color histogram and spatial distribution entropy, are extracted, and the similarity between color images is computed by using the local visual attention feature. Experimental results, including comparisons with the state-of-the-art retrieval systems, demonstrate the effectiveness of our proposal.     

Content-based image retrieval using H.264 intra coding features

Efficient multimedia retrieval has become a vital issue because more audio and video data are now available. This paper focuses on content-based image retrieval (CBIR) in the compression domain (CPD). The retrieval features are extracted based on I-frame coding information in H.264. This paper proposes using a local mode histogram as the texture feature to match images and applying the residual coefficients to filter non-confident modes. The geometrical correspondence between two images is also considered. The experimental results show that the proposed method can substantially reduce computational and memory resource consumption, and provides similar performance compared with methods that extract features from decompressed images.     

Multiple kernel-based multi-instance learning algorithm for image classification

In this paper, a novel multi-instance learning (MIL) algorithm based on multiple-kernels (MK) framework has been proposed for image classification. This newly developed algorithm defines each image as a bag, and the low-level visual features extracted from its segmented regions as instances. This algorithm is started from constructing a “word-space” from instances based on a collection of “visual-words” generated by affinity propagation (AP) clustering method. After calculating the distance between a “visual-word” and the bag (image), a nonlinear mapping mechanism is introduced for registering each bag as a coordinate point in the “word-space”. In this case, the MIL problem is transformed into a standard supervised learning problem, which allows multiple-kernels support vector machine (MKSVM) classifiers to be trained for the image categorization. Compared with many popular MIL algorithms, the proposed method, named as MKSVM-MIL, shows its satisfactorily experimental results on the COREL dataset, which highlights the robustness and effectiveness for image classification applications.     

利用相位恢复波前传感技术检测球面镜面形

为了验证相位恢复波前传感器系统波前检测的能力,搭建了基于相位恢复测量方法的波前传感器检测球面镜面形的实验平台。该平台结构简单,抗震动,可以在对光路不进行任何改变的前提下,利用成像系统上已有的相机对整个光学系统进行在位检测。为了验证相位恢复波前传感器测量方法的准确性,将相位恢复波前传感器测量结果与ZYGO干涉仪测量结果进行比较,实验结果表明在面形误差分布及误差的峰谷值(PV)和方均根值(RMS)上,两者具有极大的相似性,所以利用相位恢复波前传感器技术能有效地检测出球面镜的面形误差。     

Architecture Takes Time

Though condensed between the stages of design and completion, the conventional process of designing a building is time consuming, involving various stakeholders, planning processes and a wide team of consultants and contractors. What happens, though, if the time period of an architect's involvement is expanded? How might a more process-orientated approach shift the role of the architect? Tobias Armborst, Daniel D'Oca and Georgeen Theodore , principals of Interboro Partners in New York, describe how they have developed projects that have sought opportunities in expanding the timescale and remit of traditional practice.     

一种基于精细化稀疏自适应匹配追踪算法的图像检索方法研究

基于压缩感知理论,研究了一种精细化稀疏自适应匹配追踪（Meticulous Sparsity Adaptive Matching Pur-suit,MSAMP）算法,在此基础上提出了一种新的数字图像检索方法。首先对图像的RGB颜色、灰度共生矩阵按照列优先次序形成颜色及纹理的原始信号,然后对这两类信号采用分块压缩感知测量方法对图像进行分块测量,得到代表颜色特征和纹理特征的分块测量向量。其次利用MSAMP算法进行分块重构,计算出分块原始信号差量及其稀疏值。最后在图像检索时,通过计算图像的整体相似度,重点对差量的稀疏性进行估计,不需要精确恢复原始信号,从而减少迭代次数,加快检索速度。仿真实验表明,应用MSAMP算法的图像检索方法在检索速度和查准率等指标上具有较高的性能。     

基于分级显著信息的空间编码方法

传统的Bag of Words模型检索方法并不具备局部特征间的空间关系,因此影响检索性能.本文提出了基于分级显著信息的空间编码方法.通过分层次的提取显著区域并对每个显著区域内的特征点进行空间编码.目的是探索特征间的空间关系,并根据分级显著信息提高特征间的相关性.在几何验证过程中,本文通过任意三点间的角度编码和位移编码构成的空间编码方法完成图像对之间的空间关系匹配,同时根据图像各个区域间的显著程度赋予该区域空间关系匹配得分相应权重,得到最终的几何得分,重新排列检索结果.实验结果表明本文提出的方法既改善了最终检索结果的精确度又降低了几何验证阶段的计算时间.