Perpendicular-incidence photometric ellipsometry of biaxial anisotropic thin films

A new measurement technique for the characterization of uniaxial as well as biaxial anisotropic surfaces and thin films is introduced. This technique is based on perpendicular-incidence photometric ellipsometry, in which a spectral-photometric dynamic ellipsometer with a rotating polarizer is used. This method is sensitive, contactless, nondestructive, and efficient for the estimation of anisotropic behavior. Furthermore, the spectroscopic measurement directly provides the anisotropy dispersion down to the UV wavelength range. Results on structurally anisotropic HfO(2) coatings are presented.     

Granularity in ion-beam-sputtered TiO(2) films

TiO(2)-SiO(2) multilayer dielectric stacks that were deposited by ion-beam sputtering were found to have a granular structure. The grains were in the TiO(2) layers rather than in the SiO(2) layers. Their formation was due to the heating of the film during deposition. When the apparatus was modified to reduce the substrate temperature, the granularity was eliminated.     

Approximate dynamic programming solutions with a single network adaptive critic for a class of nonlinear systems

Approximate dynamic programming (ADP) formulation implemented with an adaptive critic (AC)-based neural network (NN) structure has evolved as a powerful technique for solving the Hamilton-Jacobi-Bellman (HJB) equations. As interest in ADP and the AC solutions are escalating with time, there is a dire need to consider possible enabling factors for their implementations. A typical AC structure consists of two interacting NNs, which is computationally expensive. In this paper, a new architecture, called the ‘cost-function-based single network adaptive critic (J-SNAC)’ is presented, which eliminates one of the networks in a typical AC structure. This approach is applicable to a wide class of nonlinear systems in engineering. In order to demonstrate the benefits and the control synthesis with the J-SNAC, two problems have been solved with the AC and the J-SNAC approaches. Results are presented, which show savings of about 50% of the computational costs by J-SNAC while having the same accuracy levels of the dual network structure in solving for optimal control. Furthermore, convergence of the J-SNAC iterations, which reduces to a least-squares problem, is discussed; for linear systems, the iterative process is shown to reduce to solving the familiar algebraic Ricatti equation.     

Automated extraction of DNA from blood and PCR setup using a Tecan Freedom EVO liquid handler for forensic genetic STR typing of reference samples

We have implemented and validated automated protocols for DNA extraction and PCR setup using a Tecan Freedom EVO liquid handler mounted with the Te-MagS magnetic separation device (Tecan, M?nnedorf, Switzerland). The protocols were validated for accredited forensic genetic work according to ISO 17025 using the Qiagen MagAttract DNA Mini M48 kit (Qiagen GmbH, Hilden, Germany) from fresh whole blood and blood from deceased individuals. The workflow was simplified by returning the DNA extracts to the original tubes minimizing the risk of misplacing samples. The tubes that originally contained the samples were washed with MilliQ water before the return of the DNA extracts. The PCR was setup in 96-well microtiter plates. The methods were validated for the kits: AmpF?STR Identifiler, SGM Plus and Yfiler (Applied Biosystems, Foster City, CA), GenePrint FFFL and PowerPlex Y (Promega, Madison, WI). The automated protocols allowed for extraction and addition of PCR master mix of 96 samples within 3.5h. In conclusion, we demonstrated that (1) DNA extraction with magnetic beads and (2) PCR setup for accredited, forensic genetic short tandem repeat typing can be implemented on a simple automated liquid handler leading to the reduction of manual work, and increased quality and throughput.     

Picbreeder: a case study in collaborative evolutionary exploration of design space

For domains in which fitness is subjective or difficult to express formally, interactive evolutionary computation (IEC) is a natural choice. It is possible that a collaborative process combining feedback from multiple users can improve the quality and quantity of generated artifacts. Picbreeder, a large-scale online experiment in collaborative interactive evolution (CIE), explores this potential. Picbreeder is an online community in which users can evolve and share images, and most importantly, continue evolving others' images. Through this process of branching from other images, and through continually increasing image complexity made possible by the underlying neuroevolution of augmenting topologies (NEAT) algorithm, evolved images proliferate unlike in any other current IEC system. This paper discusses not only the strengths of the Picbreeder approach, but its challenges and shortcomings as well, in the hope that lessons learned will inform the design of future CIE systems.     

Shape recognition and pose estimation for mobile Augmented Reality

Nestor is a real-time recognition and camera pose estimation system for planar shapes. The system allows shapes that carry contextual meanings for humans to be used as Augmented Reality (AR) tracking targets. The user can teach the system new shapes in real time. New shapes can be shown to the system frontally, or they can be automatically rectified according to previously learned shapes. Shapes can be automatically assigned virtual content by classification according to a shape class library. Nestor performs shape recognition by analyzing contour structures and generating projective-invariant signatures from their concavities. The concavities are further used to extract features for pose estimation and tracking. Pose refinement is carried out by minimizing the reprojection error between sample points on each image contour and its library counterpart. Sample points are matched by evolving an active contour in real time. Our experiments show that the system provides stable and accurate registration, and runs at interactive frame rates on a Nokia N95 mobile phone.     

iView: a feature clustering framework for suggesting informative views in volume visualization

The unguided visual exploration of volumetric data can be both a challenging and a time-consuming undertaking. Identifying a set of favorable vantage points at which to start exploratory expeditions can greatly reduce this effort and can also ensure that no important structures are being missed. Recent research efforts have focused on entropy-based viewpoint selection criteria that depend on scalar values describing the structures of interest. In contrast, we propose a viewpoint suggestion pipeline that is based on feature-clustering in high-dimensional space. We use gradient/normal variation as a metric to identify interesting local events and then cluster these via k-means to detect important salient composite features. Next, we compute the maximum possible exposure of these composite feature for different viewpoints and calculate a 2D entropy map parameterized in longitude and latitude to point out promising view orientations. Superimposed onto an interactive track-ball interface, users can then directly use this entropy map to quickly navigate to potentially interesting viewpoints where visibility-based transfer functions can be employed to generate volume renderings that minimize occlusions. To give full exploration freedom to the user, the entropy map is updated on the fly whenever a view has been selected, pointing to new and promising but so far unseen view directions. Alternatively, our system can also use a set-cover optimization algorithm to provide a minimal set of views needed to observe all features. The views so generated could then be saved into a list for further inspection or into a gallery for a summary presentation.