Improving the performance of GIS/spatial analysts though novel applications of the Emotiv EPOC EEG headset

Geospatial information systems are used to analyze spatial data to provide decision makers with relevant, up-to-date, information. The processing time required for this information is a critical component to response time. Despite advances in algorithms and processing power, we still have many “human-in-the-loop” factors. Given the limited number of geospatial professionals, analysts using their time effectively is very important. The automation and faster humancomputer interactions of common tasks that will not disrupt their workflow or attention is something that is very desirable. The following research describes a novel approach to increase productivity with a wireless, wearable, electroencephalograph (EEG) headset within the geospatial workflow.

High temperature, low cycle fatigue of a hybrid particulate/fiber aluminum metal-matrix composite

The effect of shot particles on the high temperature, low cycle fatigue of a hybrid fiber/particulate metal-matrix composite (MMC) was studied. Two hybrid composites with the general composition A356/35%SiC particle/5%Fiber (one without shot) were tested. It was found that shot particles acting as stress concentrators had little effect on the fatigue performance. It appears that fibers with a high silica content were more likely to debond from the matrix. Final failure of the composite was found to occur preferentially in the matrix. SiC particles fracture progressively during fatigue testing, leading to higher stress in the matrix, and final failure by matrix overload. A continuum mechanics based model was developed to predict failure in fatigue based on the tensile properties of the matrix and particles. By accounting for matrix yielding and recovery, composite creep and particle strength distribution, failure of the composite was predicted.

Potential for hardware-based techniques for reuse distance analysis

Reuse distance analysis, the prediction of how many distinct memory addresses will be accessed between two accesses to a given address, has been established as a useful technique in profile-based compiler optimization, but the cost of collecting the memory reuse profile has been prohibitive for some applications. In this report, we propose using the hardware monitoring facilities available in existing CPUs to gather an approximate reuse distance profile. The difficulties associated with this monitoring technique are discussed, most importantly that there is no obvious link between the reuse profile produced by hardware monitoring and the actual reuse behavior. Potential applications which would be made viable by a reliable hardware-based reuse distance analysis are identified.

BENEFICIATION OF HIGH-MgO SEDIMENTARY PHOSPHATE ORES

Dolomite [CaMg(CO3)2] is an intolerable impurity in phosphate ores due to its MgO content. Traditionally, the Florida phosphate industry has avoided mining high-MgO phosphate reserves due to the lack of an economically viable process for removal of dolomite. However, as the high grade phosphate reserves become depleted, more emphasis is being put on the development of a cost effective method for separating dolomite from high-MgO phosphate ores. In general, the phosphate industry demands a phosphate concentrate containing less than 1%MgO. Dolomite impurities have mineralogical properties that are very similar to the desired phosphate minerals (francolite), making the separation of the two minerals very difficult. Magnesium is primarily found as distinct dolomite-rich pebbles, very fine dolomite inclusions in predominately francolite pebbles, and magnesium substituted into the francolite structure. Jigging is a gravity separation process that attempts to take advantage of the density difference between the dolomite and francolite pebbles. A unique laboratory scale jig was designed and built at Michigan Tech for this study. Through a series of tests it was found that a pulsation rate of 200 pulse/minute, a stroke length of 1 inch, a water addition rate of 0.5gpm, and alumina ragging balls were optimum for this study. To investigate the feasibility of jigging for the removal of dolomite from phosphate ore, two high-MgO phosphate ores were tested using optimized jigging parameters: (1) Plant #1 was sized to 4.00x0.85mm and contained 1.55%MgO; (2) Plant #2 was sized to 3.40mmx0.85mm and contained 3.07% MgO. A sample from each plant was visually separated by hand into dolomite and francolite rich fractions, which were then analyzed to determine the minimum achievable MgO levels. For Plant #1 phosphate ore, a concentrate containing 0.89%MgO was achieved at a recovery of 32.0%BPL. For Plant #2, a phosphate concentrate containing 1.38%MgO was achieved at a recovery of 74.7%BPL. Minimum achievable MgO levels were determined to be 0.53%MgO for Plant #1 and 1.15%MgO for Plant #2.