Standard cell automated layout for a CMOS 50 MHz 8 × 8 bit pipelined parallel dadda multiplier

An 8 × 8 pipelined parallel multiplier which uses the Dadda scheme is presented. The multiplier has been implemented in a 3-μm n-well CMOS process with two layers of metal using a standard cell automatic placement and routing program. The design uses a form of pipelined carry look-ahead adder in the final stage of summation, thus providing a significant contribution to the high performance of the multiplier. The design is expected to operate at a clock frequency of at least 50 MHz and has a flush time of seven clock cycles. The design illustrates a possible method of implementing an irregular architecture in VLSI using multiple levels of low-resistance, low-capacitance interconnect and automated layout techniques.

Biomimetic bone-like composites fabricated through an automated alternate soaking process.

Hydroxyapatite-gelatin composites have been proposed as suitable scaffolds for bone and dentin tissue regeneration. There is considerable interest in producing these scaffolds using biomimetic methods due to their low energy costs and potential to create composites similar to the tissues they are intended to replace. Here an existing process used to coat a surface with hydroxyapatite under near physiological conditions, the alternate soaking process, is modified and automated using an inexpensive "off the shelf" robotics kit. The process is initially used to precipitate calcium phosphate coatings. Then, in contrast to previous utilizations of the alternate soaking process, gelatin was added directly to the solutions in order to co-precipitate hydroxyapatite-gelatin composites. Samples were investigated by Fourier transform infrared spectroscopy, scanning electron microscopy, energy dispersive X-ray spectroscopy and nanoindentation. Calcium phosphate coatings formed by the alternate soaking process exhibited different calcium to phosphate ratios, with correspondingly distinct structural morphologies. The coatings demonstrated an interconnected structure with measurable mechanical properties, even though they were 95% porous. In contrast, hydroxyapatite-gelatin composite coatings over 2mm thick could be formed with little visible porosity. The hydroxyapatite-gelatin composites demonstrate a composition and mechanical properties similar to those of cortical bone.

Automated meshing for aero-thermal analysis of complex automotive geometries

Successful product development, especially in motorsport, increasingly depends not just on the ability to simulate aero-thermal behavior of complex geometrical configurations, but also the ability to automate these simulations within a workflow and perform as many simulations as possible within constrained time frames. The core of these aero-thermal simulations - and usually the main bottleneck - is generating the computational mesh. This paper describes recent work aimed at developing a mesh generator which can reliably produce meshes for geometries of essentially arbitrary complexity in an automated manner and fast enough to keep up with the pace of an engineering development program. Our goal is to be able to script the mesh generation within an automated workflow - and forget it. © 2011 SAE International.

Towards robust part tracking in an automated manufacturing process using RFID

Automated Identification and in particular, Radio Frequency Identification (RFID) promises to assist with the automation of mass customised production processes. RFID has long been used to gather a history or trace of part movements, but the use of it as an integral part of the control process is yet to be fully exploited. Such use places stringent demands on the quality of the sensor data and the method used to interpret that data. in particular, this paper focuses on the issue of correctly identifying, tracking and dealing with aggregated objects with the use of RFID. The presented approach is evaluated in the context of a laboratory manufacturing system that produces customised gift boxes. Copyright © 2005 IFAC.

Visual retrieval of concrete crack properties for automated post-earthquake structural safety evaluation

The safety of post-earthquake structures is evaluated manually through inspecting the visible damage inflicted on structural elements. This process is time-consuming and costly. In order to automate this type of assessment, several crack detection methods have been created. However, they focus on locating crack points. The next step, retrieving useful properties (e.g. crack width, length, and orientation) from the crack points, has not yet been adequately investigated. This paper presents a novel method of retrieving crack properties. In the method, crack points are first located through state-of-the-art crack detection techniques. Then, the skeleton configurations of the points are identified using image thinning. The configurations are integrated into the distance field of crack points calculated through a distance transform. This way, crack width, length, and orientation can be automatically retrieved. The method was implemented using Microsoft Visual Studio and its effectiveness was tested on real crack images collected from Haiti.

Automated Computation of the Fundamental Matrix for Vision-Based Construction Site Applications

Estimating the fundamental matrix (F), to determine the epipolar geometry between a pair of images or video frames, is a basic step for a wide variety of vision-based functions used in construction operations, such as camera-pair calibration, automatic progress monitoring, and 3D reconstruction. Currently, robust methods (e.g., SIFT + normalized eight-point algorithm + RANSAC) are widely used in the construction community for this purpose. Although they can provide acceptable accuracy, the significant amount of required computational time impedes their adoption in real-time applications, especially video data analysis with many frames per second. Aiming to overcome this limitation, this paper presents and evaluates the accuracy of a solution to find F by combining the use of two speedy and consistent methods: SURF for the selection of a robust set of point correspondences and the normalized eight-point algorithm. This solution is tested extensively on construction site image pairs including changes in viewpoint, scale, illumination, rotation, and moving objects. The results demonstrate that this method can be used for real-time applications (5 image pairs per second with the resolution of 640 × 480) involving scenes of the built environment.

Automated sparse 3D point cloud generation of infrastructure using its distinctive visual features

The commercial far-range (>10 m) spatial data collection methods for acquiring infrastructure’s geometric data are not completely automated because of the necessary manual pre- and/or post-processing work. The required amount of human intervention and, in some cases, the high equipment costs associated with these methods impede their adoption by the majority of infrastructure mapping activities. This paper presents an automated stereo vision-based method, as an alternative and inexpensive solution, to producing a sparse Euclidean 3D point cloud of an infrastructure scene utilizing two video streams captured by a set of two calibrated cameras. In this process SURF features are automatically detected and matched between each pair of stereo video frames. 3D coordinates of the matched feature points are then calculated via triangulation. The detected SURF features in two successive video frames are automatically matched and the RANSAC algorithm is used to discard mismatches. The quaternion motion estimation method is then used along with bundle adjustment optimization to register successive point clouds. The method was tested on a database of infrastructure stereo video streams. The validity and statistical significance of the results were evaluated by comparing the spatial distance of randomly selected feature points with their corresponding tape measurements.

Automated vision tracking of project related entities

Tracking of project related entities such as construction equipment, materials, and personnel is used to calculate productivity, detect travel path conflicts, enhance the safety on the site, and monitor the project. Radio frequency tracking technologies (Wi-Fi, RFID, UWB) and GPS are commonly used for this purpose. However, on large-scale sites, deploying, maintaining and removing such systems can be costly and time-consuming. In addition, privacy issues with personnel tracking often limits the usability of these technologies on construction sites. This paper presents a vision based tracking framework that holds promise to address these limitations. The framework uses videos from a set of two or more static cameras placed on construction sites. In each camera view, the framework identifies and tracks construction entities providing 2D image coordinates across frames. Combining the 2D coordinates based on the installed camera system (the distance between the cameras and the view angles of them), 3D coordinates are calculated at each frame. The results of each step are presented to illustrate the feasibility of the framework.