Location expression standards for ITS: Testing the LRMS Cross Street Profile

Location can be expressed in a number of ways: coordinates, street addresses, landmark references, linear references, grid references, etc. The Cross Streets Profile is part of a location messaging specification developed for use in Intelligent Transportation Systems (ITS). It describes a location essentially in terms of street names. This paper presents an evaluation of the Cross Streets Profile based upon lab and field tests using commercial street network databases in the County of Santa Barbara. Results vary widely, depending upon database quality which in turn is dependent on geography (major streets vs minor streets, rural vs urban). Success rates can be improved with intelligent algorithms. Future directions to improve the quality of location messaging are discussed.     

Sulfate Attack on Cement-Stabilized Sand

A 3.5-km (2.2 mi) section of a road in Georgia developed unexpected transverse bumps within 6 months after construction. The source of the bumps appeared to be expansion within the cement-stabilized base course. Laboratory examination of samples from areas showing distress revealed the presence of ettringite, a calcium sulfoaluminate the formation of which can be accompanied by severe expansion. This expansive material was the probable cause of the volume changes causing the transverse bumps. The calcium and alumina needed to form ettringite were available from the portland cement and the stabilized soil's clay minerals. The source of the sulfur was identified as the well water that was mixed with the cement-stabilized base. Sulfate attack of cement-stabilized soils is a relatively infrequent problem, but it is highly destructive when it occurs. Currently, there are no firm criteria for identifying when sulfate attack of a cement-stabilized soil is a potential problem nor are there established methods of preventing the attack.     

A ground-based radar backscatter investigation in the percolation zone of the Greenland ice sheet

Satellite radar altimeters and scatterometers deployed over ice sheets experience backscatter from the surface and from within the snowpack, termed surface and volume backscatter respectively. In order to assess the errors in satellite altimeter measurements it is vital to know where the return is originating from in the snowpack. This return can vary spatially and temporally. Seasonal variations in the volume backscatter can be a major complicating factor in the radar return from the percolation zone. Ground-based step-frequency radar was deployed in the percolation zone of the Greenland Ice Sheet at ∼ 1945 m elevation (69 51N, 47 15W). Previous measurements in this area made by scientists from the Byrd Polar Research Centre and the University of Kansas, undertaken prior to summer melt events, have shown the strongest backscatter from ice features at around 1 m depth buried beneath the previous end-of-summer surface. In autumn 2004, radar measurements in the Ku band with bandwidths of 1 and 8 GHz were made alongside detailed stratigraphic observations within a 1 km² site. The radar results revealed no continuous reflecting horizons in the upper 3.5 m of the firn. Shallow cores and snowpits also indicated that there were no spatially continuous stratigraphic horizons across the study site. An average electromagnetic wave velocity of 2.11 ± 0.05 × 10⁸ m s^− 1 was determined for the upper metre of the firn. Surface and volume backscatter at vertical incidence were calculated using a standard model. The contribution of the surface backscatter to the total backscatter was on average 6 dB higher than that of the volume backscatter. However, at the higher 8 GHz bandwidth the strongest return frequently originated not from the surface but from within the upper 30 cm of the snowpack, most probably from thin ice layers. At 1 GHz bandwidth these ice layers were not always resolved; their return merged with the surface return, causing it to broaden, with the peak and leading edge moving down. Modelling using density and thickness measurements from shallow cores and snowpits showed that the backscatter from these shallow, thin ice layers could be stronger than the surface return owing to constructive interference from the top and base of the layers.     

Regulatory Infrared Spectroscopic Method for the Rapid Determination of Total Isolated Trans Fat: A Collaborative Study

Using attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy, collaborating scientists in ten different laboratories measured (in duplicate) the total trans fat content of ten fat or oil test samples, two of which were blind duplicates. The procedure used entailed measuring the height of the negative second derivative of the IR absorption band at 966 cm^?1. This absorption is attributed to the C?CH deformation vibration that is characteristic of isolated (non-conjugated) double bonds with the trans configuration. The precision of ATR-FTIR results in this international collaborative study was satisfactory and led to the approval of this validated procedure as official method AOCS Cd 14e-09 in late 2009. This official method is also suitable for analysis of total isolated trans fat and oil products containing, or supplemented with, trans conjugated linoleic acid (CLA) isomers. Although this method does not require derivatization of the oil or fat test materials, as required for GC, fats and oils in foods must be extracted with organic solvents before analysis. This method is also rapid (5 min) and does not require any weighing or quantitative dilution of unknown neat fat or oil test samples in any solvent. The AOCS Cd 14e-09 method is suitable for determination of test samples with zero trans fat, which is defined according to the US labeling regulations as 0.5 g trans fat per serving or 1.8% trans fat, as a percentage of total fat.     

Random set framework for multiple instance learning

Multiple instance learning (MIL) is a technique used for learning a target concept in the presence of noise or in a condition of uncertainty. While standard learning techniques present the learner with individual samples, MIL alternatively presents the learner with sets of samples. Although sets are the primary elements used for analysis in MIL, research in this area has focused on using standard analysis techniques. In the following, a random set framework for multiple instance learning (RSF-MIL) is proposed that can directly perform analysis on sets. The proposed method uses random sets and fuzzy measures to model the MIL problem, thus providing a more natural mathematical framework, a more general MIL solution, and a more versatile learning tool. Comparative experimental results using RSF-MIL are presented for benchmark data sets. RSF-MIL is further compared to the state-of-the-art in landmine detection using ground penetrating radar data.     

Audience targeting by B-to-B advertisement classification: A neural network approach

As marketing communications proliferate, the ability to target the right audience for a message is of ever-increasing importance. Audience targeting practices for mass media, both in research and in industry, have tended to emphasize demographics, behavior, and other characteristics of customer groups as the bases for matching communications to audiences. These approaches overlook the opportunity to leverage the nature of advertising content, by automatically matching advertisement content to appropriate media channels and target audience. We model the semantic and sentiment content of advertisements with 103 variables. Based on these variables, a neural network classifier is used to assign advertisements to groups that represent different media channels. In its ability to classify unseen advertisements, the model outperforms the classification result generated by a random model, by 100–300%. This method also enables us to identify and describe divergent advertisement characteristics, by industry.     

Demontage von Komposit-Bauteilen – Potenzial energetischer Materialien zur Demontage von Rotorblättern

Rotor blades of wind turbines are a challenge for recycling due to the composite materials used and their large-volume construction. The article presents a new approach for the disassembly of composite components with energetic materials. The results illustrate the different disassembly effects of detonating cords and cutting charges as well as the dependence on the material fractions, the material thickness, the layer structure or even the fibre architecture.     

Enzymatic Conversion of Starch in Twin-Screw HTST-Extruder

Wheat starch was liquefied to DE 25–30 employing heat stable α-amylase and twin-screw Werner & Pfleiderer Continua 58 HTST-extruder. Most significant reduction in batch saccharification time was obtained when starch was liquefied as a slurry containing 60% water at 120°C mass temperature, feed rate 1 500 g min⁻¹, screw rotation rate 250 min⁻¹, and 0.9% (w/w, d.s.) Novo Termamyl 120 L α-amylase was added immediately after initiation of gelatinization in the extruder. Saccharification was carried out at 60°C employing 0.36% (w/w, d.s.) Novo glucoamylase 150 L to reach a DE 96 in 22 h. Best total conversion was, however, obtained when also saccharification was initiated in the extruder by adding glucoamylase just before the die element, after lowering mass temperature to 60°C, and by allowing the saccharification to continue at 60°C after extrusion processing to reach a DE 94 in 5 h and DE 97 in 21 h.