A 3-D vision system model for automatic object surface sensing

The development of a noncontact light striping (structured light) based three-dimensional, six-degrees-of-freedom vision system for automatic object surface sensing is reported. The system modeling and world-point reconstruction methodology involve homogeneous-coordinate system transformations applied in two independent stages: the video imaging stage using three-dimensional perspective transformations and the mechanical scanning stage using three-dimensional affine transformations. Concatenation of the two independent matrix models leads to a robust four-by-four, six-degrees-of-freedom system model. The reconstructed sectional contours are registered automatically in real time with respect to a common world-coordinate system as a control net for Non-Uniform Rational B-spline (NURBS) surface approximation. The reconstruction process is demonstrated by measuring the surface of a 19.5×2 ft rowing shell. A detailed statistical accuracy and precision analysis shows an average error of 0.2% (0.002) of the camera's field-of-view. System sensitivity analysis reveals a nonlinear increase of sensitivity for angles higher than 45° between the normals of the image and laser planes.     

开放磁路式磁致伸缩导波传感器原理的实验研究

磁致伸缩导波技术具有单点激励即可实现长距离检测的优点,但在检测非铁磁性构件或端部外露构件时面临难题.在分析已有磁致伸缩导波传感器检测原理的基础上,提出首先利用磁致伸缩效应在铁磁性波导管中产生导波;然后通过端部将其传入构件实现检测的原理,构建了开放磁路式磁致伸缩导波传感器原理的研究实验平台.采用270 kHz的纵向模态导波,在长2800 mm,壁厚2.5mm的Φ25 mm低碳钢钢管上可检测出0.5mm深刻槽和Φ5 mm的通孔缺陷,且在长2800 mm,壁厚2.5mm的Φ25mm不锈钢钢管上可得到明显的端部回波信号,从而为该传感器进一步应用于非铁磁性或端部外露构件检测提供了依据.     

Verification of the peak time approach for detection of step initiation using the UTRCEXO

We were able to detect the step initiation for the Unmanned Technology Research Center Exoskeleton before visible movements occurred during the peak time approach. Detection of the step initiation is important for the rapid onset of assistance with the exoskeleton operator’s movement. Many previous studies have attempted to detect the step initiation more rapidly using the precedence walking assistance mechanism with electromyography, or the shadow walking assistance mechanism with the heel-off or toe-off time. In this paper, we detect the step initiation and implement the precedence walking assistance mechanism using the peak time approach. In particular, we detect the vertical ground reaction forces before visible movements occur, which is more reliable, simpler and faster than the previous approaches. We also present insole-type force sensing resistors based on the peak time approach that are used in force plates that can be applied to the Unmanned Technology Research Center Exoskeleton to detect similar events, such as the ground reaction force events, and the step initiation. With the insole-type force sensing resistors, the Unmanned Technology Research Center Exoskeleton can not only detect step initiation before visible movements occur, but can also implement the precedence walking assistance mechanism for step initiation without using any bio-signals.     

Watermarking with retrieval systems

We are interested in the problem of associating messages with multimedia content for the purpose of identifying them. This problem can be addressed by a watermarking system that embeds the associated messages into the multimedia content (also called Work). A drawback of watermarking is that the content will be distorted during embedding. On the other hand, if we assume that the database is available, the problem can be addressed by a retrieval system. Although no undesirable distortion is introduced when a retrieval system is used, the overhead of searching in large databases is fundamentally difficult (also known as the dimensionality curse). In this paper we present a novel framework that strikes a trade-off between watermarking and retrieval systems. Our framework avoids the dimensionality curse by introducing small distortions (watermark) into the multimedia content. From another perspective, the framework improves the watermarking performance, marked by significant reduction in distortion, by introducing searching ability in the message detection stage. To prove the concept, we give an algorithm based on the proposed notion of active clustering.     

Anti-forensics of JPEG compression detection schemes using approximation of DCT coefficients

Here we propose a unique anti-forensics method using the approximation of DCT coefficients for security analysis of forensics schemes that are dependent on the distortions produced by JPEG compression to detect forgery. Approximation process first builds a model of the AC component of DCT coefficients. Then it uses that model to restore the values of the DCT coefficients. The beauty of the proposed anti-forensics technique is that one can specify any distortion measure and it is capable of minimizing that distortion as long as the specified distortion is produced by JPEG compression or the distortion is measurable in the DCT domain. We specifically mount our anti-forensics technique on three leading JPEG compression detection schemes (Fan and de Queiroz, IEEE Trans Image Process 12(2):230–235, 2003; Lai and Böhme 2011) to highlight their weaknesses. Though these schemes are based on three different distortions metrics, still we could achieve \(100\%\) missed detection rate for JPEG images having quality factor more than equal to \(60\%\). Our analysis raises a serious question regarding the robustness and security of JPEG artifact based forgery detection schemes.     

Systems engineering for software engineers

This paper describes how we have modified a software engineering stream within a computer science course to include broader concepts of systems engineering. We justify this inclusion by showing how many reported problems with large systems are not just software problems but relate to system issues such as hardware and operational processes. We describe what we mean by systems engineering and go on to discuss the particular course structure which we have developed. We explain, in some detail, the contents of two specific systems engineering courses (Software Intensive Systems Engineering and Critical Systems Engineering) and discuss the problems and challenges we have faced in making these changes. In the appendix, we provide details of the case studies which are used as linking themes in our courses.     

Infinitesimal perturbation analysis of a queueing system with bursty traffic

We study aG/G/1 queueing system with a bursty arrival process. Based on a general model for such a bursty process, we derive infinitesimal perturbation analysis (IPA) derivative estimators of the mean system time with respect to various parameters of interest. The cases of both complete and partial state information are considered. To ensure unbiasedness and strong consistency of the estimators, different sample path representations are developed such that sample functions are continuous with respect to the particular parameter of interest. Some of these representations are applicable to a wider class of gradient estimation problems where sample path discontinuities arise. Simulation results are included to compare the convergence rates and variance properties of the different IPA estimators developed.     

A computational approach for corner and vertex detection

Corners and vertexes are strong and useful features in computer vision for scene analysis, stereo matching, and motion analysis. Here, we deal with the development of a computational approach to these important features. We consider first a corner model and study analytically its behavior once it has been smoothed using the well-known Gaussian filter. This allows us to clarify the behavior of some well-knowncornerness measure based approaches used to detect these points of interest. Most of these classical approaches appear to detect points that do not correspond to the exact position of the corner. A new scale-space based approach that combines useful properties from the Laplacian and Beaudet's measure (Beaudet 1978) is then proposed in order to correct and detect exactly the corner position. An extension of this approach is then developed to solve the problem of trihedral vertex characterization and detection. In particular, it is shown that a trihedral vertex has two elliptic maxima on extremal contrast surfaces if the contrast is sufficient, and this allows us to classify trihedral vertexes in 2 classes: vertex, and vertex as corner. The corner-detection approach developed is applied to accurately detect trihedral vertexes using an additional test in order to make a distinction between trihedral vertexes and corners. Many experiments have been carried out using noisy synthetic data and real images containing corners and vertexes. Most of the promising results obtained are used to illustrate the experimental section of this paper.     

Joint estimation of motion and radiometry of rotating camera for HDR global mosaic

In this paper, we present a global approach for constructing high dynamic range mosaics from multiple images with large exposure differences. To minimize registration errors caused by intensity mismatches in the image intensity space with low dynamic range, we propose the use of a scene radiance space with high dynamic range. By relating image intensities to scene radiances with a convenient distortion model, we robustly estimate registration parameters for the high dynamic range global mosaic, simultaneously estimating scene radiances and distortion parameters in a single framework using a computationally optimized Levenberg–Marquardt approach.

Control surface failure detection and accommodation using neuro-controllers

The ability of neural networks to learn from repeated exposure to system characteristics has made them a popular choice for many applications in linear and non-linear control. In this paper, the capabilities of neural networks in detecting and accommodating control surface failures for a modified F/A-18 super-manoeuverable fighter aircraft are examined. To detect and accommodate a failure in the thrust vectoring vane during a pitch manoeuvre, a hierarchical neuro-controller is designed using thrust vectoring, symmetric leading edge flap and the throttle. This neuro- controller is then used as the fault accommodating neuro- controller. A separate neural network is trained to detect failures in the thrust vectoring vane. The performance of the controller and fault-detection networks are verified using a numerical simulation of a longitudinal model of the aircraft.     

Motion analysis for event detection and tracking with a mobile omnidirectional camera

A mobile platform mounted with omnidirectional vision sensor (ODVS) can be used to monitor large areas and detect interesting events such as independently moving persons and vehicles. To avoid false alarms due to extraneous features, the image motion induced by the moving platform should be compensated. This paper describes a formulation and application of parametric egomotion compensation for an ODVS. Omni images give 360 view of surroundings but undergo considerable image distortion. To account for these distortions, the parametric planar motion model is integrated with the transformations into omni image space. Prior knowledge of approximate camera calibration and camera speed is integrated with the estimation process using a Bayesian approach. Iterative, coarse-to-fine, gradient-based estimation is used to correct the motion parameters for vibrations and other inaccuracies in prior knowledge. Experiments with a camera mounted on various types of mobile platforms demonstrate successful detection of moving persons and vehicles.Published online: 11 October 2004     

An efficient approach of handling and deposition of micro and nano entities using sensorized microfluidic end-effector system

This paper presents a novel approach of handling and deposition of micro and nano entities using a microfluidic end effector system with in situ polyvinylidene fluoride (PVDF) sensing. The microfluidic end effector system consists of a DC micro-diaphragm pump, one region of flexible latex tube, a polyvinylidene fluoride (PVDF) sensor for in situ measurement of micro drag force, and a micropipette. The micropipette of the novel microfluidic end effector system has an internal diameter (ID) smaller than 20 m which is used for microfluidic handling and deposition of submicron entities such as carbon nanotubes and DNA. The DC micro-diaphragm pump is automatically controlled via a voltage driver interfaced with a computer in order to effectively and efficiently control suction force and pressure during microfluidic handling and droplet control in micro and nano manufacturing. The design, calibration, and experimental implementation of the novel microfluidic end effector are carried out in the paper. The experimental results show the success rate for depositing carbon nanotubes between micro electrodes can reach close to 80%. Ultimately, the technology will provide a critical and major step towards the development of automated process for manufacturing of micro and nanoelectronics as well as for microfluidic droplet control, and drug delivery.     

基于集成神经网络的智能决策入侵检测系统

针对传统入侵检测系统存在误报率、漏检率较高的问题,提出了一种将误用入侵检测和异常入侵检测相结合的智能决策入侵检测系统,该系统基于集成神经网络技术,通过D—S证据理论可以将两种技术很好地结合起来,提高入侵检测系统的效率。阐述了该入侵检测系统的总体结构部署以及各组成模块的相应结构设计。     

Integrating Optical Force Sensing with Visual Servoing for Microassembly

For microassembly tasks uncertainty exists at many levels. Single static sensing configurations are therefore unable to provide feedback with the necessary range and resolution for accomplishing many desired tasks. In this paper we present experimental results that investigate the integration of two disparate sensing modalities, force and vision, for sensor-based microassembly. By integrating these sensing modes, we are able to provide feedback in a task-oriented frame of reference over a broad range of motion with an extremely high precision. An optical microscope is used to provide visual feedback down to micron resolutions, while an optical beam deflection technique (based on a modified atomic force microscope) is used to provide nanonewton level force feedback or nanometric level position feedback. Visually servoed motion at speeds of up to 2 mm/s with a repeatability of 0.17 m are achieved with vision alone. The optical beam deflection sensor complements the visual feedback by providing positional feedback with a repeatability of a few nanometers. Based on the principles of optical beam deflection, this is equivalent to force measurements on the order of a nanonewton. The value of integrating these two disparate sensing modalities is demonstrated during controlled micropart impact experiments. These results demonstrate micropart approach velocities of 80 m/s with impact forces of 9 nN and final contact forces of 2 nN. Within our microassembly system this level of performance cannot be achieved using either sensing modality alone. This research will aid in the development of complex hybrid MEMS devices in two ways; by enabling the microassembly of more complex MEMS prototypes; and in the development of automatic assembly machines for assembling and packaging future MEMS devices that require increasingly complex assembly strategies.     

Application of the artificial memory approach to multicriteria scheduling problems

This paper is devoted to the development of a knowledge-based system (KBS) called Artificial Memory, The goal of this KBS is to solve multicriteria job-shop scheduling problems. Since job-shop scheduling problems are NP-hard, it is extremely difficult to obtain optimal solutions for industrial problems. Thus, a host of heuristic algorithms, most of which are based on priority rules, have been proposed in the literature. The efficiency of these algorithms strongly depends on the criteria to be optimized as well as the values of the parameters associated with the particular instance of the scheduling problem. The basic hypothesis of the artificial memory approach is a continuity assumption: we assume that identical decisions applied to similar instances lead to similar values of the criteria. This assumption is fundamental to validate this knowledge-based system. For each criterion, the artificial memory contains a synthesis of the performances of different algorithms upon sets of similar instances. These performances are acquired using simulation. When the artificial memory is employed, the characteristic values of a new instance are computed and examined by the artificial memory system. The performances of the different algorithms for the considered criterion are estimated for the new instance and an appropriate algorithm is chosen accordingly. In order to build this KBS and to estimate the performances of algorithms upon a new instance, we use a mathematical approach. Some difficulties arose in the development of this KBS and had to be overcome: the corresponding proposed solutions are developed. The paper also presents a number of numerical experimental applications.     

Laser remote measurements of atmospheric gas components by dial: Modeling and experiments

This paper reports the development of LIDAS (LIdar Differential Absorption Sensing) program-algorithmic system for laser remote sensing of minor gas constituents (MGCs) of the atmosphere by the differential absorption method. The system includes modules for the search of wave-lengths informative for laser gas analysis by the differential absorption method, for numerical simulation of lidar sensing of atmospheric MGCs, and for calculation of errors of methodical, atmospheric, spectral, and instrumental origin. Lidar sensing of gas constituents by the differential absorption method as applied to problems of sensing of atmospheric MGCs is simulated numerically. Results of experiments on remote sensing of gas constituents of the atmosphere with the use of CO laser are presented.