Large-scale,adhesive-free and omnidirectional 3D nanocone anti-reflection films for high performance photovoltaics

An effective and low-cost front-side anti-reflection(AR) technique has long been sought to enhance the performance of highly efficient photovoltaic devices due to its capability of maximizing the light absorption in photovoltaic devices. In order to achieve high throughput fabrication of nanostructured flexible and anti-reflection films, large-scale, nano-engineered wafer molds were fabricated in this work. Additionally, to gain in-depth understanding of the optical and electrical performance enhancement with AR films on polycrystalline Si solar cells, both theoretical and experimental studies were performed. Intriguingly,the nanocone structures demonstrated an efficient light trapping effect which reduced the surface reflection of a solar cell by17.7% and therefore enhanced the overall electric output power of photovoltaic devices by 6% at normal light incidence. Notably, the output power improvement is even more significant at a larger light incident angle which is practically meaningful for daily operation of solar panels. The application of the developed AR films is not only limited to crystalline Si solar cells explored here, but also compatible with any types of photovoltaic technology for performance enhancement.     

Selection criteria for the analysis of data-driven clusters in cerebral FMRI

Functional MRI (fMRI) may be possible without a priori models of the cerebral hemodynamic response. First, such data-driven fMRI requires that all cerebral territories with distinct patterns be identified. Second, a systematic selection method is necessary to prevent the subjective interpretation of the identified territories. This paper addresses the second point by proposing a novel method for the automated interpretation of identified territories in data-driven fMRI. Selection criteria are formulated using: 1) the temporal cross-correlation between each identified territory and the paradigm and 2) the spatial contiguity of the corresponding voxel map. Ten event-design fMRI data sets are analyzed with one prominent algorithm, fuzzy c-means clustering, before applying the selection criteria. For comparison, these data are also analyzed with an established, model-based method: statistical parametric mapping. Both methods produced similar results and identified potential activation in the expected territory of the sensorimotor cortex in all ten data sets. Moreover, the proposed method classified distinct territories in separate clusters. Selected clusters have a mean temporal correlation coefficient of 0.39+/-0.07 (n=19) with a mean 2.7+/-1.4 second response delay. At most, four separate contiguous territories were observed in 87% of these clusters. These results suggest that the proposed method may be effective for exploratory fMRI studies where the hemodynamic response is perturbed during cerebrovascular disease.     

从PC至移动应用,DisplayPort技术方兴未艾

未来几年内,HDMI与DisplayPort将作为两种消费者可用的数字视频接口同时主宰市场.HDMI将继续在消费视频产品中存在,而DisplayPort则将取代VGA和DVI,成为PC显示器接口.     

Effects of Augmented Reality Display Settings on Human Wayfinding Performance

Augmented reality (AR) entails overlaying the real world with information from computer-generated displays. Current AR technologies support limited mobility, although this is expected to change in the future. This paper presents experimental results of effects of various AR display strategies on human performance in a simulation-based analog of a ldquosearch and rescuerdquo navigation task. The augmentation scheme was a spatially and temporally registered map that was overlaid onto a corresponding real-world maze. The experiment required the participants to traverse the maze, periodically answer orientation questions, obtain a target object, and exit the maze as quickly as possible. One hundred twenty participants were evaluated in six different conditions. There were two control conditions (paper map or compass prior to entering the maze), and four experimental conditions (combinations of egocentric and exocentric maps, and continuously on or on-demand map display). Performance measures consisted of duration of time to traverse the maze and percentage of maze covered. AR resulted in better performance than the control conditions in terms of accuracy by facilitating the participants' coverage of the maze. Results show that the better performance with respect to time was in the map control condition. This result may be due to the small size of the maze, which could be memorized. However, AR is expected to exhibit better performance compared to a paper map, when more complex environments are employed. These results demonstrate promising benefits in mobile AR usage in specific navigation tasks. Design guidelines were extracted to guide future AR systems continued progress in enhancing performance.     

A model for residual life prediction based on Brownian motion with an adaptive drift

A degradation model is presented in this paper for the prediction of the residual life using an adapted Brownian motion-based approach with a drifting parameter. This model differs from other Brownian motion-based approaches in that the drifting parameter of the degradation process is adapted to the history of monitored information. This adaptation is performed by Kalman filtering. We also use a threshold distribution instead of the usual single threshold line which is sometime difficult to obtain in practice. We demonstrate the model using some examples and show that the model performs reasonably well and has a better prediction ability than the standard Brownian motion-based model. The model is then fitted to the data generated from a simulator using the expectation-maximization algorithm. We also fit a standard Brownian motion-based model to the same data to compare the difference and performance. The result shows that the adapted model performs better in terms of certain test statistics and the total mean square errors.     

Bayesian regularization applied to ultrasound strain imaging

Noise artifacts due to signal decorrelation and reverberation are a considerable problem in ultrasound strain imaging. For block-matching methods, information from neighboring matching blocks has been utilized to regularize the estimated displacements. We apply a recursive Bayesian regularization algorithm developed by Hayton et al. [Artif. Intell., vol. 114, pp. 125-156, 1999] to phase-sensitive ultrasound RF signals to improve displacement estimation. The parameter of regularization is reformulated, and its meaning examined in the context of strain imaging. Tissue-mimicking experimental phantoms and RF data incorporating finite-element models for the tissue deformation and frequency-domain ultrasound simulations are used to compute the optimal parameter with respect to nominal strain and algorithmic iterations. The optimal strain regularization parameter was found to be twice the nominal strain and did not vary significantly with algorithmic iterations. The technique demonstrates superior performance over median filtering in noise reduction at strains 5% and higher for all quantitative experiments performed. For example, the strain SNR was 11 dB higher than that obtained using a median filter at 7% strain. It has to be noted that for applied deformations lower than 1%, since signal decorrelation errors are minimal, using this approach may degrade the displacement image.     

Distributed detection of replica node attacks with group deployment knowledge in wireless sensor networks

Several protocols have been proposed to mitigate the threat against wireless sensor networks due to an attacker finding vulnerable nodes, compromising them, and using these nodes to eavesdrop or undermine the operation of the network. A more dangerous threat that has received less attention, however, is that of replica node attacks, in which the attacker compromises a node, extracts its keying materials, and produces a large number of replicas to be spread throughout the network. Such attack enables the attacker to leverage the compromise of a single node to create widespread effects on the network. To defend against these attacks, we propose distributed detection schemes to identify and revoke replicas. Our schemes are based on the assumption that nodes are deployed in groups, which is realistic for many deployment scenarios. By taking advantage of group deployment knowledge, the proposed schemes perform replica detection in a distributed, efficient, and secure manner. Through analysis and simulation experiments, we show that our schemes achieve effective and robust replica detection capability with substantially lower communication, computational, and storage overheads than prior work in the literature.     

Transport and Mechanical Properties of High-ZT Mg2.08Si0.4−x Sn0.6Sb x Thermoelectric Materials

Mg₂(Si,Sn) compounds are promising candidate low-cost, lightweight, nontoxic thermoelectric materials made from abundant elements and are suited for power generation applications in the intermediate temperature range of 600 K to 800 K. Knowledge on the transport and mechanical properties of Mg₂(Si,Sn) compounds is essential to the design of Mg₂(Si,Sn)-based thermoelectric devices. In this work, such materials were synthesized using the molten-salt sealing method and were powder processed, followed by pulsed electric sintering densification. A set of Mg_2.08Si_0.4?x Sn_0.6Sb _x (0 ≤ x ≤ 0.072) compounds were investigated, and a peak ZT of 1.50 was obtained at 716 K in Mg_2.08Si_0.364Sn_0.6Sb_0.036. The high ZT is attributed to a high electrical conductivity in these samples, possibly caused by a magnesium deficiency in the final product. The mechanical response of the material to stresses is a function of the elastic moduli. The temperature-dependent Young’s modulus, shear modulus, bulk modulus, Poisson’s ratio, acoustic wave speeds, and acoustic Debye temperature of the undoped Mg₂(Si,Sn) compounds were measured using resonant ultrasound spectroscopy from 295 K to 603 K. In addition, the hardness and fracture toughness were measured at room temperature.     

Radar cross section of trihedral corner reflectors using PO and MEC

Physical optics (po) and the method of equivalent currents (mec) are used for the formulation and calculation of the backscatter cross section of both the triangular and square trihedral corner reflectors. Scattering from a trihedral corner reflector is dominated by single, double, and triple reflections by the interior walls. A physical optics integration is performed on the entire surface of each plate for the evaluation of the singly reflected fields. Doubly and triply reflected fields are evaluated by first using geometrical optics (go) at initial reflections to calculate the incident plane wave on the plate where the last reflection occurs. Physical optics is then applied on the illuminated area of that plate. First-order diffractions, which are based on the fringe current expressions for the exterior edges of the trihedral, are also included in the analysis. Predictions compare very well with both experimental and fdtd data.     

Single frequency inverse obstacle scattering: a sparsity constrained linear sampling method approach

The linear sampling method (LSM) offers a qualitative image reconstruction approach, which is known as a viable alternative for obstacle support identification to the well-studied filtered backprojection (FBP), which depends on a linearized forward scattering model. Of practical interest is the imaging of obstacles from sparse aperture far-field data under a fixed single frequency mode of operation. Under this scenario, the Tikhonov regularization typically applied to LSM produces poor images that fail to capture the obstacle boundary. In this paper, we employ an alternative regularization strategy based on constraining the sparsity of the solution's spatial gradient. Two regularization approaches based on the spatial gradient are developed. A numerical comparison to the FBP demonstrates that the new method's ability to account for aspect-dependent scattering permits more accurate reconstruction of concave obstacles, whereas a comparison to Tikhonov-regularized LSM demonstrates that the proposed approach significantly improves obstacle recovery with sparse-aperture data.