Fast microwave detection system for coherent synchrotron radiation study at KEK: Accelerator test facility

A fast room temperature microwave detection system based on the Schottky Barrier-diode detector was created at the KEK ATF (Accelerator Test Facility). It was tested using Coherent Synchrotron Radiation (CSR) generated by the 1.28 GeV electron beam in the damping ring. The speed performance of the detection system was checked by observing the CSR from a multi-bunch (2.8 ns bunch separation time) beam. The theoretical estimations of CSR power yield from an edge of bending magnet as well as new injection tuning method are presented. A very high sensitivity of CSR power yield to the longitudinal electron distribution in a bunch is discussed.     

A VLSI architecture for a half-edge-based corner detector

Corner detection is a low-level feature detection operator that is of great use in image processing applications, for example, optical flow and structure from motion by image correspondence. The detection of corners is a computationally intensive operation. Past implementations of corner detection techniques have been restricted to software. In this paper we propose an efficient very large-scale integration (VLSI) architecture for detection of corners in images. The corner detection technique is based on the half-edge concept and the first directional derivative of Gaussian. Apart from the location of the corner points, the algorithm also computes the corner orientation and the corner angle and outputs the edge map of the image. The symmetrical properties of the masks are utilized to reduce the number of convolutions effectively, from eight to two. Therefore, the number of multiplications required per pixel is reduced from 1800 to 392. Thus, the proposed architecture yields a speed-up factor of 4.6 over conventional convolution architectures. The architecture uses the principles of pipelining and parallelism and can be implemented in VLSI.     

Conceptual damage-sensitive features for structural health monitoring: Laboratory and field demonstrations

The use of damage-sensitive features to evaluate structural condition or health is a very critical aspect of structural health monitoring. The purpose of this paper is to investigate the potential of two different damage-sensitive features for detecting damage. Different damage scenarios are simulated on a large-scale laboratory structure and a three-span highway bridge for demonstration. The features presented in this paper are the modal flexibility-based deflection and curvature both of which are obtained directly from dynamic properties. In the literature, flexibility associated with mode shapes and mode shapes curvatures have been mostly explored. In this study, multi-input–multi-output dynamic data are used to obtain modal flexibility, which is a close approximation to the actual flexibility. A main novelty is that the curvature is calculated from the deflected shapes using the modal flexibility as opposed to using modal vectors. In this paper, the theory of the methodology is explained and then experimental studies and results are presented. For the experimental studies, the laboratory specimen and the three-span bridge were gradually damaged. It is shown that both deflection and curvature are conceptual and physically meaningful features for damage detection and localization. The issues and the requirements for these features to perform successfully are also presented.     

Investigation of Centreline Segregation and Centreline Porosity in CC ‐ Slabs

Improvements of solidification processing in conventional or near net shape casting depend on sophisticated methods of macroscopic examination of central unsoundness and inhomogeneity of the cast material. As long as remarkable deviations referring to the quality features exist between the slab centre and the bulk material such methods should be looked after. Two semi‐macroscopic methods of segregation analysis are discussed in this paper: firstly, the potential of the emission spectral analysis combined with sectioning of a sample and secondly, the computer aided micro‐probe analysis. Both methods are restricted to small local areas. The proneness of elements and steel grades with respect to micro‐ and macrosegregation as well as distribution‐ and segregation coefficients are determined. The effect of a diffusion anneal on homogenisation of segregation is studied. Last not least the precipitation of sulphides, phosphides or carbonitrides is estimated. Ultrasonic detection of the central unsoundness of conventional slabs or thin slabs is a new approach towards a quantitative macroscopic examination. The sample size is 400 mm x 300 mm x 30 mm. To achieve a low ultrasonic noise using a 5 MHz‐transducer the samples are heat treated for grain refinement. “Dog bone porosity”, macroscopic topographical misfit between the upper and lower solidifying shells, periodical corner cracks or systematic transverse centre cracks are detected. Obviously, segregations do not reflect the ultrasonic beam. However, it can be presumed that an interrelation exists between porosity and segregation, although these might be locally apart from each other. This new ultrasonic test of the central unsoundness of continuous cast (c.c.) slabs gives valuable arguments to machine builders and maintenance people to decide on the right concepts for strand guidance, support rollers and secondary cooling. Soft reduction can be optimized and variations in casting speed counteracted by dynamic means. R&D service of this kind can help steelmakers when decisions are impending to build new casting machines or revamp old ones.     

Effect of sampling density on the measurement of stream condition indicators in two lowland Australian streams

There is widespread application of indicators to the assessment of environmental condition of streams. These indicators are intended for use by managers in making various comparative and absolute assessments and often have a role in resource allocation and performance assessment. Therefore, the problem of formally defining confidence in the results is important but difficult because the sampling strategies used are commonly based on a compromise between the requirements of statistical rigour and the pragmatic issues of access and resources. It is rare to see this compromise explicitly considered and consequently there is seldom quantification of the uncertainty that could affect the confidence a manager has in an indicator. In this paper, we present a method for quantitatively assessing the tradeoffs between sampling density and uncertainty in meeting various monitoring objectives. Assessments using judgement‐based representative reaches are shown to be unreliable; instead a sampling approach is recommended based on the random selection of measuring sites. A detailed dataset was collected along two streams in Victoria, Australia, and the effect of sampling density was assessed by subsampling from this dataset with precision related to the number of sites assessed per reach length and the intensity of the sampling at each site. The sampling scheme to achieve a given precision is shown to depend on the monitoring objective. In particular, three objectives were considered: (1) making a baseline assessment of current condition; (2) change detection; and (3) detection of a critical threshold in condition. Change detection is shown to be more demanding than assessing baseline condition with additional sampling effort required to achieve the same precision. Sampling to detect a critical threshold depends on nominating acceptable values of Type I and II error and the size of the effect to be detected. Copyright © 2006 John Wiley & Sons, Ltd.     

Grouped Approach for the Design of H.264/AVC Motion Estimation Architectures

This letter presents a novel approach for organizing computational resources into groups within H.264/AVC motion estimation architectures, leading to reductions of up to 75% in the equivalent gate count with respect to state‐of‐the‐art designs.     

高分辨率合成孔径雷达图像舰船检测方法

寻找针对高分辨率SAR图像的舰船目标检测算法。利用KSW双阈值分割技术，其效果比传统检测方法好，有利于进一步的目标分类和识别。且必须根据SAR图像分辨率来选择舰船检测算法。     

Efficient similarity-based operations for data integration

Dealing with discrepancies in data is still a big challenge in data integration systems. The problem occurs both during eliminating duplicates from semantic overlapping sources as well as during combining complementary data from different sources. Though using SQL operations like grouping and join seems to be a viable way, they fail if the attribute values of the potential duplicates or related tuples are not equal but only similar by certain criteria. As a solution to this problem, we present in this paper similarity-based variants of grouping and join operators. The extended grouping operator produces groups of similar tuples, the extended join combines tuples satisfying a given similarity condition. We describe the semantics of this operator, discuss efficient implementations for the edit distance similarity and present evaluation results. Finally, we give examples of application from the context of a data reconciliation project for looted art.     

Cycle detection using a stack

We present an algorithm for detecting periodicity in sequences produced by repeated application of a given function. Our algorithm uses logarithmic memory with high probability, runs in linear time, and is guaranteed to stop within the second loop through the cycle. We also present a partitioning technique that offers a time/memory tradeoff. Our algorithm is especially well suited for sequences where the cycle length is typically small compared to the length of the acyclic prefix.     

Pedestrian detection and tracking at crossroads

This paper presents a system that can perform pedestrian detection and tracking using vision-based techniques. A very important issue in the field of intelligent transportation system is to prevent pedestrians from being hit by vehicles. Recently, a great number of vision-based techniques have been proposed for this purpose. In this paper, we propose a vision-based method, which combines the use of a pedestrian model as well as the walking rhythm of pedestrians to detect and track walking pedestrians. Through integrating some spatial and temporal information grabbed by a vision system, we are able to develop a reliable system that can be used to prevent traffic accidents happened at crossroads. In addition, the proposed system can deal with the occlusion problem. Experimental results obtained by executing some real world cases have demonstrated that the proposed system is indeed superb.