Identifying mislabeled training data with the aid of unlabeled data

This paper presents a new approach for identifying and eliminating mislabeled training instances for supervised learning algorithms. The novelty of this approach lies in the using of unlabeled instances to aid the detection of mislabeled training instances. This is in contrast with existing methods which rely upon only the labeled training instances. Our approach is straightforward and can be applied to many existing noise detection methods with only marginal modifications on them as required. To assess the benefit of our approach, we choose two popular noise detection methods: majority filtering (MF) and consensus filtering (CF). MFAUD/CFAUD is the new proposed variant of MF/CF which relies on our approach and denotes majority/consensus filtering with the aid of unlabeled data. Empirical study validates the superiority of our approach and shows that MFAUD and CFAUD can significantly improve the performances of MF and CF under different noise ratios and labeled ratios. In addition, the improvement is more remarkable when the noise ratio is greater.     

水稻指纹图谱的计算机检索方法

为了解决人工鉴别水稻指纹图谱效率低下的问题,提出一种计算机辅助鉴别方法。提取用SSR分子标记技术构建的水稻DNA图谱条带轮廓,计算各条带区域的质心,将条带质心转换形成特征向量,并利用支持向量机构造出品种分类器,从而实现对未知样品的自动分类。该方法利用支持向量机较强的泛化能力,解决特征提取后不同品种样本之间细微差别所带来的识别困难。实验结果表明,该方法识别率总体上比欧几里得距离分类要高,可以辅助提高水稻品种鉴别效率。     

基于TS201系列DSP的PGA算法实现

相位梯度自聚焦(PGA)算法被广泛用于机载合成孔径雷达(SAR)成像中.由于其过程复杂,数据处理量大,为满足机载SAR实时处理的要求,选用具有强大处理能力的TS201 DSP.为了充分发挥TS201的性能,利用PGA原理和TS201处理器的特点,对算法流程进行优化,并且对最耗时的FFT采用了汇编语言实现,使得运算量和处...     

八通道可变增益高速数据采集系统

针对多通道超声波应用提出了一种USB+FPGA+DSP的架构,模拟前端可实现8通道高速数据采集,并可实现线性增益和可变采样率。FPGA为系统的控制核心,同时进行信号预处理方面的工作,而DSP着重于复杂算法的应用。最后通过已知信号对整个系统进行测试,验证了该系统性能良好,具有很高的实用价值。     

高分辨率遥感卫星数据传输中信道编码技术分析与研究

根据RS编译码原理,结合高分辨率遥感卫星在轨影像实际数据压缩情况,提出将RS(255,243)和RS(34,26)两种编码算法进行联合使用的方案,以解决数据传输中误码问题,仿真试验证明该方法在解决有干扰条件下的星地数据传输时,可有效防止和减少误码扩散。     

磁力机械式和激光气体分析仪的应用

论述2种氧分析仪表的测量原理和异同点,介绍二者在应用中存在的问题.     

Deadline division-based heuristic for cost optimization in workflow scheduling

Cost optimization for workflow applications described by Directed Acyclic Graph (DAG) with deadline constraints is a fundamental and intractable problem on Grids. In this paper, an effective and efficient heuristic called DET (Deadline Early Tree) is proposed. An early feasible schedule for a workflow application is defined as an Early Tree. According to the Early Tree, all tasks are grouped and the Critical Path is given. For critical activities, the optimal cost solution under the deadline constraint can be obtained by a dynamic programming strategy, and the whole deadline is segmented into time windows according to the slack time float. For non-critical activities, an iterative procedure is proposed to maximize time windows while maintaining the precedence constraints among activities. In terms of the time window allocations, a local optimization method is developed to minimize execution costs. The two local cost optimization methods can lead to a global near-optimal solution. Experimental results show that DET outperforms two other recent leveling algorithms. Moreover, the deadline division strategy adopted by DET can be applied to all feasible deadlines.     

Grid resource management policies for load-balancing and energy-saving by vacation queuing theory

The resource management is the central component of grid system. The analysis of the workload log file of LCG including the job arrival and the resource utilization daily cycle shows that the idle sites in the Grid are the source of load imbalance and energy waste. Here we focus on these two issues: balancing the workload by transferring jobs to idle sites at prime time to minimize the response time and maximize the resource utilization; power management by switch the idle sites to sleeping mode at non-prime time to minimize the energy consume. We form the M/G/1 queue model with server vacations, startup and closedown to analysis the performance metrics to instruct the design of load-balancing and energy-saving policies. We provide our Adaptive Receiver Initiated (ARI) load-balancing strategy and power-management policy for energy-saving. The simulation experiments prove the accuracy of our analysis and the comparisons results indicate our policies are largely suitable for large-scale heterogeneous grid environment.