A Region Ensemble for 3-D Face Recognition

In this paper, we introduce a new system for 3D face recognition based on the fusion of results from a committee of regions that have been independently matched. Experimental results demonstrate that using 28 small regions on the face allow for the highest level of 3D face recognition. Score-based fusion is performed on the individual region match scores and experimental results show that the Borda count and consensus voting methods yield higher performance than the standard sum, product, and min fusion rules. In addition, results are reported that demonstrate the robustness of our algorithm by simulating large holes and artifacts in images. To our knowledge, no other work has been published that uses a large number of 3D face regions for high-performance face matching. Rank one recognition rates of 97.2% and verification rates of 93.2% at a 0.1% false accept rate are reported and compared to other methods published on the face recognition grand challenge v2 data set.     

Small blaze angle gratings with various surface treatments for use in the extreme ultraviolet

Three replica gratings were made from a single master; two were epoxy overcoated with different thicknesses of gold, and one was replicated directly in gold. Their performance in EUV light at grazing incidence angles was measured and compared.     

Biometric recognition using 3D ear shape

Previous works have shown that the ear is a promising candidate for biometric identification. However, in prior work, the preprocessing of ear images has had manual steps and algorithms have not necessarily handled problems caused by hair and earrings. We present a complete system for ear biometrics, including automated segmentation of the ear in a profile view image and 3D shape matching for recognition. We evaluated this system with the largest experimental study to date in ear biometrics, achieving a rank-one recognition rate of 97.8 percent for an identification scenario and an equal error rate of 1.2 percent for a verification scenario on a database of 415 subjects and 1,386 total probes.     

Using digital cameras for river plume and water quality measurements

The results from a pilot study in coastal waters off the east coast of Ireland using both an in situ and airborne mounted digital camera are described. In situ digital pictures are significantly affected by sea surface reflection. This can be eliminated with the use of a hollow pipe, attached to the camera lens, which intersects the sea surface such that a picture of light upwelled from beneath the surface is obtained. Used in this way, linear relations between both the ratio of red/green digital output (O/P) values (at a particular camera exposure) and the difference in green–red digital camera O/P were found with mineral suspended solid (MSS) concentration. A good comparison was also found between the ratios of red/green upwelling light measured with the camera and a conventional irradiance sensor. Semi‐empirical or analytical relationships between camera O/P and the inherent optical properties of the water could not be established, however. This was probably due, in part, to a lack of range in values for the water constituent parameters. An airborne mounted digital camera was used to successfully monitor the dynamics of a river plume discharging into the coastal water. The high dissolved organic material (CDOM) levels within the plume caused the plume to be easily visible in the digital imagery, with a significantly increased signal in the camera's red/green O/P values marking the spatial extent of the plume. The plume dynamics were principally controlled by the tidal flows in the coastal waters. During the ebb tide strong fronts, and inferred convergence zones, marked the edge of the river plume and were associated with increased values of the camera‐derived red/green ratio. As slack water commenced, the plume expanded away from the source and became thinner, with a decreased red/green signal. Associated with this time internal fronts were present within the plume's extent, marked by step changes, or spikes, in the camera's red/green values.     

Effect of vacuum‐drying,hot air‐drying and freeze‐drying on polyphenols and antioxidant capacity of lemon (Citrus limon) pomace aqueous extracts

The aim of this study was to investigate the effect of freeze‐drying, hot air‐drying and vacuum‐drying at 70, 90 and 110 °C, on dried lemon pomace polyphenols and antioxidant capacity. The total phenolic content and antioxidant capacity were higher in lemon pomace dried by hot air or under vacuum than those dried by freeze‐drying and increased as the temperature increased. The highest total flavonoid content was recorded in the pomace dried under vacuum at 70 and 90 °C. Lemon pomace dried by freeze‐drying had the highest neohesperidin content, whereas pomace dried under vacuum at 70 °C had the highest rutin and p‐coumaric acid content. The highest gallic acid content was recorded in the pomace dried by hot air at 110 °C. The results of this study indicate that drying technique should be carefully selected according to the bioactive compounds aimed to be extracted.     

Detecting and ordering salient regions

We describe an ensemble approach to learning salient regions from arbitrarily partitioned data. The partitioning comes from the distributed processing requirements of large-scale simulations. The volume of the data is such that classifiers can train only on data local to a given partition. Since the data partition reflects the needs of the simulation, the class statistics can vary from partition to partition. Some classes will likely be missing from some or even most partitions. We combine a fast ensemble learning algorithm with scaled probabilistic majority voting in order to learn an accurate classifier from such data. Since some simulations are difficult to model without a considerable number of false positive errors, and since we are essentially building a search engine for simulation data, we order predicted regions to increase the likelihood that most of the top-ranked predictions are correct (salient). Results from simulation runs of a canister being torn and from a casing being dropped show that regions of interest are successfully identified in spite of the class imbalance in the individual training sets. Lift curve analysis shows that the use of data driven ordering methods provides a statistically significant improvement over the use of the default, natural time step ordering. Significant time is saved for the end user by allowing an improved focus on areas of interest without the need to conventionally search all of the data.     

Baseline levels of Hsp 70, a stress protein and biomarker, in halibut from the Cook Inlet region of Alaska

The levels of Hsp 70, a heat shock protein, was quantitatively determined in Pacific halibut, Hippoglossus stenolepis, from the Cook Inlet region in south central Alaska. A dot blot analysis using a monoclonal antibody for Hsp 70 was combined with a standard protein analysis to determine Hsp 70 levels in 26 samples from gills. The average Hsp 70 concentration was 4.6 micrograms/mg, with levels ranging from 2.2 to 14.5 micrograms/mg total protein. Mercury in gill tissue also was measured and, in the 26 samples, only three samples had concentrations of mercury (X = 0.10 mg/kg, range = 0.09-0.11) above the minimum detection level.