OpenCL: A Parallel Programming Standard for Heterogeneous Computing Systems

We provide an overview of the key architectural features of recent microprocessor designs and describe the programming model and abstractions provided by OpenCL, a new parallel programming standard targeting these architectures.     

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.     

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...     

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.     

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     

基于矢量模型的语音线性预测研究

研究语音参数线性预测的并行处理问题。通过把语音源序列的相邻样本分组能够构成一个均方差平稳的语音向量自回归序列,在Hilbert空间中运用正交投影原理导出具有高度并行处理能力的一预测编码策略,由此可推出参数线性预测的并行处理自适应算法。同传统格型算法相比,这种算法的计算复杂度及存贮量有明显改善。最后通过仿真运算检测了算法的性能。     

Blind Source Extraction for Noisy Mixtures by Combining Gaussian Moments and Generalized Autocorrelations

In the blind source extraction problem, the concept of generalized autocorrelations has been successfully used when the desired signal has special temporal structures. However, their applications are only limited to noise-free mixtures, which is not realistic. Therefore, this paper addresses the extraction of the noisy model based on these temporal characteristics of sources. An objective function, which combines Gaussian moments and generalized autocorrelations, is proposed. Maximizing this objective function, we present a blind source extraction algorithm for noisy mixtures. Simulations on synthesized signals, images, artificial electrocardiogram (ECG) data and the real-world ECG data show the better performance of the proposed algorithm. Moreover, comparisons with the existing algorithms further indicate its validity and also show its robustness to the estimated error of time delay.