In This Issue

Software Quality Journal -     

Spectroelectrochemical sensing based on multimode selectivity simultaneously achievable in a single device. 9. Incorporation of planar waveguide technology

Incorporation of planar waveguide technology into a spectroelectrochemical sensor is described. In this sensor design, a potassium ion-exchanged BK7 glass waveguide was over-coated with a thin film of indium tin oxide (ITO) that served as an optically transparent electrode. A chemically selective film was spin-coated on top of the ITO film. The sensor supported five optical modes at 442 nm and three at 633 nm. Investigations on the impact of the ITO film on the optical properties of the waveguide and on the spectroelectrochemical performance of the sensor are reported. Sensing was based on the change in attenuation of light propagated through the waveguide resulting from an optically absorbing analyte. By applying either a triangular or square wave excitation potential waveform, electromodulation of the optical signal has been demonstrated with Fe(CN)6(3-/4-) as a model electroactive couple that partitions into a PDMDAAC-SiO2 film [where PDMDAAC = poly(dimethyldiallylammonium chloride)] and absorbs at 442 nm.     

From template to image: reconstructing fingerprints from minutiae points

Most fingerprint-based biometric systems store the minutiae template of a user in the database. It has been traditionally assumed that the minutiae template of a user does not reveal any information about the original fingerprint. In this paper, we challenge this notion and show that three levels of information about the parent fingerprint can be elicited from the minutiae template alone, viz., 1) the orientation field information, 2) the class or type information, and 3) the friction ridge structure. The orientation estimation algorithm determines the direction of local ridges using the evidence of minutiae triplets. The estimated orientation field, along with the given minutiae distribution, is then used to predict the class of the fingerprint. Finally, the ridge structure of the parent fingerprint is generated using streamlines that are based on the estimated orientation field. Line integral convolution is used to impart texture to the ensuing ridges, resulting in a ridge map resembling the parent fingerprint. The salient feature of this noniterative method to generate ridges is its ability to preserve the minutiae at specified locations in the reconstructed ridge map. Experiments using a commercial fingerprint matcher suggest that the reconstructed ridge structure bears close resemblance to the parent fingerprint     

The State‐of‐the‐Art in Predictive Visual Analytics

Predictive analytics embraces an extensive range of techniques including statistical modeling, machine learning, and data mining and is applied in business intelligence, public health, disaster management and response, and many other fields. To date, visualization has been broadly used to support tasks in the predictive analytics pipeline. Primary uses have been in data cleaning, exploratory analysis, and diagnostics. For example, scatterplots and bar charts are used to illustrate class distributions and responses. More recently, extensive visual analytics systems for feature selection, incremental learning, and various prediction tasks have been proposed to support the growing use of complex models, agent‐specific optimization, and comprehensive model comparison and result exploration. Such work is being driven by advances in interactive machine learning and the desire of end‐users to understand and engage with the modeling process. In this state‐of‐the‐art report, we catalogue recent advances in the visualization community for supporting predictive analytics. First, we define the scope of predictive analytics discussed in this article and describe how visual analytics can support predictive analytics tasks in a predictive visual analytics (PVA) pipeline. We then survey the literature and categorize the research with respect to the proposed PVA pipeline. Systems and techniques are evaluated in terms of their supported interactions, and interactions specific to predictive analytics are discussed. We end this report with a discussion of challenges and opportunities for future research in predictive visual analytics.     

Smart carboxymethylchitosan hydrogels that have thermo‐ and pH‐responsive properties

Thermo‐responsive poly(N‐isopropylacrylamide) (poly(NIPAAm)) and pH‐responsive poly(N,N′‐diethylaminoethyl methacrylate) (poly(DEAEMA)) polymers were grafted to carboxymethylchitosan (CMC) via radical polymerization to form highly water swellable hydrogels with dual responsive properties. Ratios of CMC, NIPAAm to DEAEMA used in the reactions were finely adjusted such that the thermo and pH responsiveness of the hydrogels was retained. Scanning electron microscopy (SEM) indicated the formation of an internal porous structure for the swollen CMC hydrogels upon incorporation of poly(NIPAAm) and poly(DEAEMA). Effect of temperature and pH changes on water swelling properties of the hydrogels was investigated. It was found that the water swelling of the hydrogels was enhanced when the solution pH was under basic conditions (pH 11) or the temperature was below its lower critical solution temperature (LCST). These responsive properties can be used to regulate releasing rate of an entrapped drug from the hydrogels, a model drug, indomethacin was used to demonstrate the release. These smart and nontoxic CMC‐based hydrogels show great potential for use in controlled drug release applications with controllable on‐off switch properties. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 41505.     

Monitoring Highly Correlated Multivariate Processes Using Hotelling's T2 Statistic: Problems and Possible Solutions

Hotelling's T² statistic is the default control statistic for continuous multivariate data, but there are dangers in applying this statistic without the appropriate level of checks and balances. This paper discusses the potential issues with using the Hotelling's T² statistic when the quality variable measures are highly correlated and provides some solutions that will help mitigate the risks with applying the Hotelling's T² control charts in such practical examples. Copyright © 2014 John Wiley & Sons, Ltd.     

What matters the most for economic development? Evidence from the Community Development Financial Institutions Fund

Governments use incentive programmes to attract new businesses. Due to limited resources, there are questions about which incentives are most effective. Using establishment data from California, and data on the location of disbursements through two federal programmes, we consider the effectiveness of different programmes in attracting new businesses. We find that the amount of funding through the New Markets Tax Credit programme has a significant impact on business activity but find no evidence of an effect from the Community Development Financial Institutions programme. Our results suggest that the effectiveness of these programmes depends on how they provide assistance.