Microprocessor-based, tractor-mounted soil cone penetrometer

A microprocessor-based, tractor-mounted soil cone penetrometer was developed for automating soil strength measurements. This unit was designed to operate over a 4-row (3-m) width and to a maximum penetrating depth of 61 cm. The penetrating force was applied to the penetrometer shaft via a hydraulic cylinder. The hydraulic cylinder and associated depth and force measuring sensors were mounted on a carriage assembly which traveled along a 4-m track. The carriage was moved laterally along the track by a cable assembly driven by a DC winch. The penetrometer frame and track were attached to a 4-row toolbar which had a category II, 3-point hitch. Optical position encoders were used to measure depth of penetration and carriage position along the track. Force of penetration was calculated by measuring hydraulic pressure acting on the hydraulic cylinder. A microprocessor-based control unit activated all moving mechanisms and automatically recorded data on magnetic tape for computing depth versus force of penetration profiles. Liquid crystal displays provided visual output of these measurements. The control unit was field programmable for operating in various modes. Seven parameters which affected operation of the penetrometer could be changed depending upon the application of the test. The control unit consisted of two modules: (1) the MRU module which included a 8-bit Microprocessor Unit (MC6802), 4K RAM, 4K EPROM, two peripheral interface adapters, an asynchronous interface adapter, 12-bit analog-to-digital converter, three 8-bit data latches, and a BAUD rate generator; (2) the input/output module included two liquid crystal displays, key pad, and light emitting diodes

Rain gauge calibration and testing

Prior to the Tropical Oceans Global Atmosphere-Coupled Ocean Atmosphere Response Experiment (TOGA-COARE), 42 Model 100 series optical gauges were tested in the rain simulator facility at Wallops Island before shipment to the field. Baseline measurements at several rain rates were made simultaneously with collector cans, tipping bucket, and a precision weighing gauge and held for post-COARE evaluation with a repeat set of measurements that were to be recorded after the instruments were returned. This was done as a means of detecting any calibration changes that might have occurred while deployed. Although it was known that the artificial rain in the simulator did not contain the required exponential distribution for accurate optical rain gauge rate measurements, use of the facility was necessary because it was the only means available for taking controlled observations with instruments that were received, tested, and shipped out in groups over a period of months. At that point, it was believed that these measurements would be adequately precise for detecting performance changes over time. However, analysis of the data by STI now indicates that this may not be true. Further study of the data will be undertaken to resolve this

Using Cases about Teaching for Faculty Development

Creating and Collecting Cases Setting Up Case-Based Workshops Facilitating Case Discussions Setting Clear Expectations Managing Time Asking and Encouraging Questions Listening Organizing and Structuring Avoiding Common Problems Conclusion References Other Resource

A Parallel Implementation of Stickel\u27s AC Unification Algorithm in a Message-Passing Environment

Unification algorithms are an essential component of automated reasoning and term rewriting systems. Unification finds a set of substitutions or unifiers that, when applied to variables in two or more terms, make those terms identical or equivalent. Most systems use Robinson\u27s unification algorithm or some variant of it. However, terms containing functions exhibiting properties such as associativity and commutativity may be made equivalent without appearing identical. Systems employing Robinson\u27s unification algorithm must use some mechanism separate from the unification algorithm to reason with such functions. Often this is done by incorporating the properties into a rule base and generating equivalent terms which can be unified by Robinson\u27s algorithm. However, rewriting the terms in this manner can generate large numbers of useless terms in the problem space of the system. If the properties of the functions are incorporated into the unification algorithm itself, there is no need to rewrite the terms such that they appear identical. Stickel developed an algorithm to unify two terms containing associative and commutative functions. The unifiers (there may be more than one) are found by creating a homogeneous linear Diophantine equation with integer coefficients from the terms being unified. The unifiers can be constructed from solutions to this equation. The unifiers generated from one solution of the Diophantine equation are independent of any other solution to the equation. Therefore, once the Diophantine equation has been solved, the unifiers can be calculated from the solutions in parallel. We have implemented Stickel\u27s AC unification algorithm to run in parallel on a local area network of Sun 4/110 workstations in an effort to improve the speed of AC unification

Airborne Temperature Surveys Of Lake Michigan, October 1966 And 1967

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/109998/1/lno19701520289.pd