Prospective issues for error detection

From the literature on error detection, the authors select several concepts relating error detection mechanisms and prospective memory features. They emphasize the central role of intention in the classification of the errors into slips/lapses/mistakes, in the error handling process and in the usual distinction between action-based and outcome-based detection. Intention is again a core concept in their investigation of prospective memory theory, where they point out the contribution of intention retrievals, intention persistence and output monitoring in the individual's possibilities for detecting their errors. The involvement of the frontal lobes in prospective memory and in error detection is also analysed. From the chronology of a prospective memory task, the authors finally suggest a model for error detection also accounting for neural mechanisms highlighted by studies on error-related brain activity.     

Development of 2D computer program to determine geometry of rock mass blocks简

Due to various geological processes such as tectonic activities fractures might be created in rock mass body which causes creation of blocks with different shapes and sizes in the rock body. Exact understanding of these blocks geometry is an essential issue concerned in different domains of rock engineering such as support system of underground spaces built in jointed rock masses, design of blasting pattern, optimization of fragmentation, determination of cube blocks in quarry mines, blocks stability, etc. The aim of this paper is to develop a computer program to determine geometry of rock mass blocks in two dimensional spaces. In this article, the geometry of jointed rock mass is programmed in MATLAB™.     

Image edge detection based on multi-fractal spectrum analysis

In this paper, an image edge detection method based on multi-fractal spectrum analysis is presented. The coarse grain H?lder exponent of the image pixels is first computed. then, its multi-fractal spectrum is estimated by the kernel estimation method. Finally, the image edge detection is done by means of different multi-fractal spectrum values. Simulation results show that this method is efficient and has better locality compared with the traditional edge detection methods such as the Sobel method. __________ Translated from Journal of Hunan University (Natural Sciences), 2004, 31(4): 28–33     

Preparation of a sensor substrate using functionalized mesoporous silica on a gold film for surface plasmon resonance (SPR) spectroscopy

The use of surface plasmon resonance (SPR) spectroscopy has been applied to a wide variety of fields such as biosensors and surface analysis instruments. In general, a SPR substrate is prepared using self-assembled monolayer (SAM) method of organic molecules as receptor for the target on a layer of gold or silver. However, mesoporous inorganic materials such as SBA-15 have benefits as sensor substrate for SPR. Mesoporous silica has a large surface area which receptor molecule can be attached and has a rigid body which has an excellent stability in the extreme condition compared to organic sensing layer. We prepared an organic modified mesoporous silica and successfully immobilized it on a gold surface, in an attempt to use as a substrate for SPR spectroscopy. For the comparison of sensitivity of prepared substrate, Pt²⁺ detection was selected as a model system. Substrate prepared in this study exhibited the capability of selective sensing for Pt²⁺ ions.     

改进分块支持向量聚类在入侵检测中的应用

支持向量聚类(SVC)是在支持向量机的思想上发展而来一种聚类方法,针对其处理大规模数据集速度缓慢的缺点,提出了一种改进的分块支持向量聚类算法。改进的算法分为三个阶段:前期的预处理,中期的分块算法,后期的改进标类算法。提出的方法显著加快了SVC的速度,在保持原来SVC算法的优点的基础上,对大规模数据集以及非均匀分布数据集等具有良好的效果。将其应用到网络入侵检测,实验结果表明改进的算法行之有效。     

一种晶闸管整流器全关断检测电路

本文提出并介绍了欧姆逻辑无环流检测的一种方案——晶闸管流器全关断检测，并与软件检测和电流互联器检测进行比较分析，最终得出晶闸管全关断检测方案准确可行的结论。全关断的输出信号与上述两种信号进行综合利用，从而准确可靠地实现了欧姆的逻辑无环流控制。     

Associative Learning Improves Visual Working Memory Performance.

The ability to remember visual stimuli over a short delay period is limited by the small capacity of visual working memory (VWM). Here the authors investigate the role of learning in enhancing VWM. Participants saw 2 spatial arrays separated by a 1-s interval. The 2 arrays were identical except for 1 location. Participants had to detect the difference. Unknown to the participants, some spatial arrays would repeat once every dozen trials or so for up to 32 repetitions. Spatial VWM performance increased significantly when the same location changed across display repetitions, but not at all when different locations changed from one display repetition to another. The authors suggest that a major role of learning in VWM is to mediate which information gets retained, rather than to directly increase VWM capacity. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Fuzzy logic for signal prediction in nuclear systems

In this paper, we present a fuzzy logic-based algorithm which allows to build a predictive model of an evolving signal. The if-then rules are inferred from the available input-output data. The errors of the model predictions with respect to the measured plant signals can then be used to detect, in real-time, any deviation of the process due either to a component's failure or to an operator's action. Applications of the approach are presented with respect to a chaotic time series of literature and to the water level in the steam generator of a PWR.     

GM计数管脉冲供电电压对计数率的影响

本文重点介绍了ＧＭ计数管脉冲供电电压对计数率的影响。经测试分析研究，结果表明脉冲供电比固定电压供电电压变化对ＧＭ管计数率的影响较大，应对脉冲电源提出更高的要求，