Mobile Fair Diary: hybrid interface for taking,browsing and sharing context-aware notes

This paper describes the Mobile Fair Diary (MFD), which is designed to allow a housing fair customer to make a personalized digital recording of his/her visit to a hectic fairground for later use. The MFD is a hybrid interface service comprising of an application for a camera equipped smart phone and a website accessed by a PC. The smart phone application is used for taking context-aware notes such as visual codes, photos, dictations and text. The notes are uploaded onto a website, where they can be viewed with a PC in a contextually ordered view for browsing, organizing and sharing. The MFD was empirically evaluated in a real-life environment of use with genuine end users by a large-scale field trial at a national housing fair. The results testify to the very successful design of the MFD with high usefulness.     

Design and evaluation of a lyophilized liposomal gel of an antiviral drug for intravaginal delivery

Liposomes of antiviral drug(acyclovir) prepared by rotary evaporation method were incorporated into two bioadhesive polymers, carbopol and HPMC and freeze dried to obtain a unit dosage form. The liposomes, liposomal gels and freeze dried rods were evaluated for various parameters. TEM analysis showed the formation of unilamellar liposomes with a mean diameter ranging from 0.9 μm to 1.2 μm. As the cholesterol content increases from 0.5% to 2%w/w, the entrapment efficiency and vesicle size increased. Carbopol gels exhibited higher viscosity, spreadability, mucoadhesiveness than HPMC gels. The redipsersion of freeze dried forms in SVF was found to be slow and its ex‐vivo retention time was found to be 12 hrs while acyclovir gel retained only for 8.25 hrs. The tablet and gel released 96.93±0.15% acyclovir within 6 hrs and 92.31±0.31% by 8 hrs respectively while freeze dried forms could sustain the release upto 12 hrs. From the stability studies the optimum storage condition was found to be 4‐8°C. © 2013 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014 , 131, 39804.     

FIR, Allpass, and IIR Variable Fractional Delay Digital Filter Design

This paper presents two-step design methodologies and performance analyses of finite-impulse response (FIR), allpass, and infinite-impulse response (IIR) variable fractional delay (VFD) digital filters. In the first step, a set of fractional delay (FD) filters are designed. In the second step, these FD filter coefficients are approximated by polynomial functions of FD. The FIR FD filter design problem is formulated in the peak-constrained weighted least-squares (PCWLS) sense and solved by the projected least-squares (PLS) algorithm. For the allpass and IIR FD filters, the design problem is nonconvex and a global solution is difficult to obtain. The allpass FD filters are directly designed as a linearly constrained quadratic programming problem and solved using the PLS algorithm. For IIR FD filters, the fixed denominator is obtained by model reduction of a time-domain average FIR filter. The remaining numerators of the IIR FD filters are designed by solving linear equations derived from the orthogonality principle. Analyses on the relative performances indicate that the IIR VFD filter with a low-order fixed denominator offers a combination of the following desirable properties including small number of denominator coefficients, lowest group delay, easily achievable stable design, avoidance of transients due to nonvariable denominator coefficients, and good overall magnitude and group delay performances especially for high passband cutoff frequency ( ges 0.9pi) . Filter examples covering three adjacent ranges of wideband cutoff frequencies [0.95, 0.925, 0.9], [0.875, 0.85, 0.825], and [0.8, 0.775, 0.75] are given to illustrate the design methodologies and the relative performances of the proposed methods.     

Measuring cancer patients' psychological distress and well-being: A factor analytic assessment of the Mental Health Inventory.

This study examined the psychometric structure of the Mental Health Inventory (MHI) in 433 cancer patients. Using structural equation modeling, confirmatory factor analyses (CFAs) were conducted. Next, exploratory factor analysis (EFA) was used to explore an alternative MHI factor structure with a randomly chosen subsample. Finally, CFAs were conducted on 6 MHI models with the second subsample. Convergent validity was examined by administering the Positive and Negative Affect Schedule (PANAS) and the Dyadic Adjustment Scale (DAS). The CFAs with the original MHI factor structure indicated inadequate fit, supporting the need to conduct an EFA. Results of the EFA indicated support for a 5-factor solution but numerous differences in item factor loadings. The CFA indicated that the 5-factor correlated model was the best fitting model. Correlations between the PANAS and the DAS with the MHI provided preliminary support for the convergent validity of the MHI. Together, these results indicate that the original MHI factor structure may require modification for use in patients with cancer. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Macromodel of Spatial Smoothing in Wind Farms

Departing from aerodynamics (micromodel), the macromodel begins with the power output of a single wind turbine generator (WTG). The N units of WTGs in a wind farm are characterized by the time delays it takes wind, at average velocity, to traverse the distances separating them. Predictions from simulations are in agreement with recorded wind farm data. Smoothing of high-frequency power components is by a factor close to N^-1/2. Smoothing of low-frequency harmonic power components is small because the wind farm is limited in size. A theory, based on Fourier analysis, is presented to explain how the macromodel simultaneously copes with: 1) the high-frequency components of wind velocity (which have poor correlation) even for short distances and 2) the low-frequency components (which have some correlation)     

Detection of vehicles from traffic scenes using fuzzy integrals

This paper presents an improved vehicle detection algorithm for traffic scene interpretation. In our previous high-level dynamic traffic scene interpretation systems (Dance et al., Picture Interpretation: A Symbolic Approach, World Scientific, New Jersey, 1995; Liu et al., IEEE Trans. Syst. Man Cybernet. Part B (2001) to appear), we used a simple background-subtraction procedure (referred to as Method 0) for vehicle detection, which, although adequate for well-defined image sequences, was not applicable to slightly displaced and noisy images. Our new method (referred to as Method 1) uses the Hough transform to extract the contour lines of the vehicles and morphological operations to reduce noise and improve the shape of the object regions. Finally, in the detection process we compute fuzzy integrals based on the evidence gathered. We have carried out extensive experiments. For all vehicles in the images, including the ones partially occluded and cut off at the image boundary, we were able to achieve a detection rate of 80% (Method 1) compared to 13% (Method 0). For the vehicles that are almost completely visible, the detection rate was 90%. In addition, for a set of 492 images, our new method reduces the number of false alarms from 427 (by Method 0) to only 9.     

Guided Intra-Patch Smoothing Graph Filtering for Single-Image Denoising

Graph filtering is an important part of graph signal processing and a useful tool for image denoising. Existing graph filtering methods, such as adaptive weighted graph filtering (AWGF), focus on coefficient shrinkage strategies in a graph-frequency domain. However, they seldom consider the image attributes in their graph-filtering procedure. Consequently, the denoising performance of graph filtering is barely comparable with that of other state-of-the-art denoising methods. To fully exploit the image attributes, we propose a guided intra-patch smoothing AWGF (AWGF-GPS) method for single-image denoising. Unlike AWGF, which employs graph topology on patches, AWGF-GPS learns the topology of superpixels by introducing the pixel smoothing attribute of a patch. This operation forces the restored pixels to smoothly evolve in local areas, where both intra- and inter-patch relationships of the image are utilized during patch restoration. Meanwhile, a guided-patch regularizer is incorporated into AWGF-GPS. The guided patch is obtained in advance using a maximum-a-posteriori probability estimator. Because the guided patch is considered as a sketch of a denoised patch, AWGF-GPS can effectively supervise patch restoration during graph filtering to increase the reliability of the denoised patch. Experiments demonstrate that the AWGF-GPS method suitably rebuilds denoising images. It outperforms most state-of-the-art single-image denoising methods and is competitive with certain deep-learning methods. In particular, it has the advantage of managing images with significant noise.     

Reliability inference for VGA adapter from dual suppliers based on contaminated type‐I interval‐censored data

Type‐I interval‐censoring scheme only documents the number of failed units within two prespecified consecutive exam times at the larger time point after putting all units on test at the initial time schedule. It is challenging to use the collected information from type‐I interval‐censoring scheme to evaluate the reliability of unit when not all admitted units are operated or tested at the same initial time and a majority of units are randomly selected to replace the failed test units at unrecorded time points. Moreover, the lifetime distribution of all pooled units from dual resources usually follows a mixture distribution. To overcome these two problems, a two‐stage inference process that consists of a data‐cleaning step and a parameter estimation step via either Markov chain Monte Carlo (MCMC) algorithm or profile likelihood method is proposed based on the contaminated type‐I interval‐censored sample from a mixture distribution with unknown proportion. An extensive simulation study is conducted under the mixture smallest extreme value distributions to evaluate the performance of the proposed method for a case study. Finally, the proposed methods are applied to the mixture lifetime distribution modeling of video graphics array adapters for the support of reliability decision.