First break refraction event picking using fuzzy logic systems

First break picking is a pattern recognition problem in seismic signal processing, one that requires much human effort and is difficult to automate. The authors' goal is to reduce the manual effort in the picking process and accurately perform the picking. Feedforward neural network first break pickers have been developed using backpropagation training algorithms applied either to an encoded version of the raw data or to derived seismic attributes which are extracted from the raw data. The authors summarize a study in which they applied a backpropagation fuzzy logic system (BPFLS) to first break picking. The authors use derived seismic attributes as features, and take lateral variations into account by using the distance to a piecewise linear guiding function as a new feature. Experimental results indicate that the BPFLS achieves about the same picking accuracy as a feedforward neural network that is also trained using a backpropagation algorithm; however, the BPFLS is trained in a much shorter time, because there is a systematic way in which the initial parameters of the BPFLS can be chosen, versus the random way in which the weights of the neural network are chosen     

A semantic modeling approach for image retrieval by content

We introduce a semantic data model to capture the hierarchical, spatial, temporal, and evolutionary semantics of images in pictorial databases. This model mimics the user's conceptual view of the image content, providing the framework and guidelines for preprocessing to extract image features. Based on the model constructs, a spatial evolutionary query language (SEQL), which provides direct image object manipulation capabilities, is presented. With semantic information captured in the model, spatial evolutionary queries are answered efficiently. Using an object-oriented platform, a prototype medical-image management system was implemented at UCLA to demonstrate the feasibility of the proposed approach.     

应用粒子动态分析仪研究水力旋流器流场

利用粒子动态分析仪(PDA),对水力旋流器内固相颗粒流场做了全面的测定,得出水力旋流器内固相颗粒的流态、浓度及粒度分布,为进一步查清水力旋流器的工作机理提供了重要理论依据。     

催化裂化汽油选择性加氢脱硫催化剂RSDS-1的开发

介绍了用于催化裂化汽油选择性加氢脱硫催化剂RSDS-1的研究开发，考察了载体、活性组元、金属原子比以及助剂对催化剂选择性的影响。研究结果表明，催化裂化汽油中烯烃的加氢饱和受扩散限制；Co—Mo组合对烯烃饱和的能力相对较弱；较高的Co／Mo原子比有利于提高催化剂选择性；助剂的加入对催化剂选择性有明显的影响；RSDS—1催化剂用于催化裂化汽油选择性脱硫，对不同原料油适应性好，脱硫率可达80％，RON损失小于2个单位，且可长周期稳定运转。     

电镀企业火警和爆鸣事故实例

列举了作者经历的18种火警和爆呜事故，为电镀企业敲响警钟，安全重于泰山。     

Technology for testing nondeterministic client/server database applications

The execution of a client/server application involving database access requires a sequence of database transaction events (or, T-events), called a transaction sequence (or, T-sequence). A client/server database application may have nondeterministic behavior in that multiple executions thereof with the same input may produce different T-sequences. We present a framework for testing all possible T-sequences of a client/server database application. We first show how to define a T-sequence in order to provide sufficient information to detect race conditions between T-events. Second, we design algorithms to change the outcomes of race conditions in order to derive race variants, which are prefixes of other T-sequences. Third, we develop a prefix-based replay technique for race variants derived from T-sequences. We prove that our framework can derive all the possible T-sequences in cases where every execution of the application terminates. A formal proof and an analysis of the proposed framework are given. We describe a prototype implementation of the framework and present experimental results obtained from it.     

基于DSP+CPLD的高精度信号发生器

介绍了基于直接数字式频率合成(DDS)原理的全数字信号发生器(DSP),利用DSP芯片快速、高精度的运算优势以及CPLD芯片灵活的编程逻辑、大容量存储功能的特点,采用通用可编程芯片以及数字波形合成技术,形成高稳定、高精度、高动态的数字合成信号.该信号发生器可产生0～25 kHz的正弦波、三角波和方波,输出电压峰峰值为0～5 V,频率步进1 Hz,幅度步进0.001 V.     

基于PCI总线的高速多路数据传输卡设计

介绍了一套基于外部设备互连(PCI)总线的高速多路数据传输卡的设计,采用基于PCI内核与PCI用户逻辑相结合的新型设计方案,在顶层通过仿真来验证PCI接口以及用户逻辑设计正确与否.降低了设计的复杂程度,提高了电路的集成度和系统的性能,并根据PCI卡对外部设备驱动能力较弱的特点,在传输卡中加入了长线驱动功能,采用低电压差分信号(LVDS)技术,既降低了系统功耗,又实现长距离的计算机双向通信.