Industrial wireless sensor networks can be designed to meet the strict requirements of specific distributed applications. Emerging standards have enabled the development of low-cost, lowpower sensor nodes that are qui...
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A group of undergraduate students from the School of Electrical and Computer Engineering at Purdue University worked on developing and fabricating a printed circuit board (PCB) design to demonstrate the full functiona...
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A group of undergraduate students from the School of Electrical and Computer Engineering at Purdue University worked on developing and fabricating a printed circuit board (PCB) design to demonstrate the full functionality and capabilities of the FIR filter design. The PCB design includes a simplified power supply for the entire PCB as well as high-speed programmable logic devices (PLDs) to handle storing and loading the preselected coefficients via the multiplexed input bus. The high-speed PLDs were chosen to quickly change the coefficients of the desired filter without having to worry about the timing and bus management issues associated with memory ICs. The PLDs will effectively serve as memory units, preprogrammed to load the coefficients into the FIR filter using the enable signal that is automatically generated by the FIR filter. The team designed a circuit using a variable-frequency clock generator to produce the operating frequency for the FIR filter that will allow the device to be clocked to a maximum frequency to accommodate testing for CD quality audio filtering. The design meets both area and speed design constraints and provides expected results in both synthesis and transistor-level simulations.
We propose a probabilistic, hierarchical, and discriminant (PHD) framework for fast and accurate detection of deformable anatomic structures from medical images. The PHD framework has three characteristics. First, it ...
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Network-centric data acquisition and telemetry systems continue to gain momentum and adoption. However, inherent non-deterministic network delays hinder these systems' suitability for use where high-accuracy timin...
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Intelligent Transportation systems (ITS) have unique deployment characteristics that affect the way and timing that new and emerging technology should be integrated. It is important for ITS managers to understand the ...
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Intelligent Transportation systems (ITS) have unique deployment characteristics that affect the way and timing that new and emerging technology should be integrated. It is important for ITS managers to understand the effects of dominant design, disruptive technology, innovation, standards, and industry trends on product, technology, and system lifecycles. Industry and related examples are provided to illustrate the importance of technology management as it pertains to ITS communications infrastructures. Under this context, considerations are discussed for deploying a new or upgrading an existing infrastructure.
This work presents a methodology for detecting anomalous conditions on transportation infrastructure assets and generating alarms to draw the attention of personnel monitoring them via various sensing technologies. Th...
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This work presents a methodology for detecting anomalous conditions on transportation infrastructure assets and generating alarms to draw the attention of personnel monitoring them via various sensing technologies. The methodology developed, which consists of a four part process, is capable of detecting conditions that vary substantially from those that are normally observed. This four part process consists of the following steps: (1) an intensity characteristic model of the transportation asset is learned during a training phase. (2) During the foreground object segmentation phase, objects are segmented based on pixel characteristics that vary substantially from those embodied in the intensity characteristic model. (3) Segmented objects that match certain morphological, topological, and/or geometric constraints are flagged as being candidates for further (temporal) processing. (4) Segmented objects with unanticipated temporal persistence or geometric characteristics are then identified and brought to the attention of a human operator.
Between 1994 and 1997, researchers at Southwest Research Institute (SwRI) investigated methods for distributing parallel computation and data visualization under the support of an internally funded Research Initiative...
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Between 1994 and 1997, researchers at Southwest Research Institute (SwRI) investigated methods for distributing parallel computation and data visualization under the support of an internally funded Research Initiative Program entitled the Advanced Visualization Technology Project (AVTP). A hierarchical data cache architecture was developed to provide a flexible interface between the modeling or simulation computational processes and data visualization programs. Compared to conventional post facto data visualization approaches, this data cache structure provides many advantages including simultaneous data access by multiple visualization clients, comparison of experimental and simulated data, and visual analysis of computer simulation as computation proceeds. However, since the data cache was resident on a single workstation, this approach did not address the issue of scalability of methods for avoiding the data storage bottleneck by distributing the data across multiple networked workstations. Scalability through distributed database approaches is being investigated as part of the Applied Visualization using Advanced Network Technology Infrastructure (AVANTI) project. This paper describes a methodology currently under development that is intended to avoid bottlenecks that typically arise as the result of data consumers (e.g. visualization applications) that must access and process large amounts of data that has been generated and resides on other hosts, and which must pass through a central data cache prior to being used by the data consumer.
Even though computer vision systems are not able to match the ability of biological vision in dealing with complex scenes, many problems are being solved. Often multiple sensors are used, including stereo cameras, str...
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Even though computer vision systems are not able to match the ability of biological vision in dealing with complex scenes, many problems are being solved. Often multiple sensors are used, including stereo cameras, structured light patterns, laser light striping, and multiple optical wave lengths. The use of sensor fusion to combine information from these multiple sensors provides robust and high speed systems. As computer, electronic and sensor technology develops, this application of multiple types of sensors with high speed data fusion can be expected to increase and provide more robust systems for the future.< >
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