Using disability data to estimate design exclusion

Exclusion auditing is a process that can quantitatively evaluate the inclusive merit of different products, or alternative design decisions. The results from such an audit can provide prioritised directions for product improvement and support the business case for reducing the capability levels required to use mainstream products. The 1996/1997 disability follow-up survey, conducted by the Office of National Statistics, is currently the most comprehensive data source for estimating design exclusion in the UK. In this paper, the data source is explained in detail, and a method is presented that uses this data to estimate the exclusion associated with several tasks that occur in series or in parallel, illustrated through worked examples. Having evaluated how many people are excluded, one can investigate why they were excluded, thus generating design insights into how they could be included. Data from the survey is also converted to a series of stylised graphs, which are intended to inspire designers to think about the relationship between the demands required to use a product and the resulting levels of population exclusion.     

Using the maximum likelihood method to estimate test complexity levels

Consideration was given to the problem of estimating the levels of complexity of the test tasks for the remote education system. It was assumed that the random responses of the subjects obey the logistic distribution and the levels of student readiness are not known in advance. An algorithm based on the methods of maximum likelihood and Broyden-Fletcher-Goldfarb-Shanno was proposed to calculate the task complexity. Strict concavity of the logarithmic likelihood function was established, and an example was considered.     

Using cocitation information to estimate political orientation in web documents

This paper introduces a simple method for estimating cultural orientation, the affiliation of online entities in a polarized field of discourse. In particular, cocitation information is used to estimate the political orientation of hypertext documents. A type of cultural orientation, the political orientation of a document is the degree to which it participates in traditionally left- or right-wing beliefs. Estimating documents' political orientation is of interest for personalized information retrieval and recommender systems. In its application to politics, the method uses a simple probabilistic model to estimate the strength of association between a document and left- and right-wing communities. The model estimates the likelihood of cocitation between a document of interest and a small number of documents of known orientation. The model is tested on three sets of data, 695 partisan web documents, 162 political weblogs, and 198 nonpartisan documents. Accuracy above 90% is obtained from the cocitation model, outperforming lexically based classifiers at statistically significant levels.     

Using nonlinear approximation to estimate the parameters of plant time to failure

A method was proposed for construction of the generalized distributions employed in the graphs-analytical method which makes use of the experimental data to estimate the distribution parameters of the plant time to failure. The existence conditions for generalized distributions were formulated. The resources of the proposed approach were illustrated by way of analysis of the modeled sample data.     

Using multiple radiometric correction images to estimate leaf area index

Ecological applications of remote-sensing techniques are generally limited to images after atmospheric correction, though other radiometric correction data are potentially valuable. In this article, six spectral vegetation indices (VIs) were derived from a SPOT 5 image at four radiometric correction levels: digital number (DN), at-sensor radiance (SR), top of atmosphere reflectance (TOA) and post-atmospheric correction reflectance (PAC). These VIs include the normalized difference vegetation index (NDVI), ratio vegetation index (RVI), slope ratio of radiation curve (K), general radiance level (L), visible-infrared radiation balance (B) and band radiance variation (V). They were then related to the leaf area index (LAI), acquired from in situ measurement in Hetian town, Fujian Province, China. The VI–LAI correlation coefficients varied greatly across vegetation types, VIs as well as image radiometric correction levels, and were not surely increased by image radiometric corrections. Among all 330 VI–LAI models established, the R ² of multi-variable models were generally higher than those of the single-variable ones. The independent variables of the best VI–LAI models contained all VIs from all radiometric correction levels, showing the potentials of multi-radiometric correction images in LAI estimating. The results indicated that the use of VIs from multiple radiometric correction images can better exploit the capabilities of remote-sensing information, thus improving the accuracy of LAI estimating.     

Using constancy of distance to estimate position and displacementin space

The problem of computing structure and motion from the observation of points in two distinct images of a scene is considered. The proposed method explicitly utilizes the principle of conservation of distance during rigid-body motion. The formulation is such that it separates the problem of estimating object position from that of determining motion parameters. The equations of invariance of distance for a rigid body are solved for the points' position in space. When these coordinates in space are known, motion parameters are computed in a simple and straightforward manner. Examples are given to illustrate the efficiency of the algorithm     

Using the red-near infrared spectral to estimate ground cover based on vegetative indices

Rapid and accurate estimation of Ground Cover (GC) at regional and global scales for agricultural management application is only possible by using remote sensing (RS). In this study, two Vegetation Indices (VIs) including the Perpendicular Vegetation Index (PVI) and Normalized Difference Vegetation Index (NDVI) were used for estimating GC. Since the parameters of the bare soil line have an important role in calculating GC based on PVI, this line was extracted based on the red-NIRmin (minimum near infrared) method with different intervals (0.0001, 0.0005, and 0.0010). In addition to traditional statistics such as Root Mean Square Error (RMSE), the sensitivity analysis (S) was also used to sharpen the accuracy of the models' estimations. The results indicated that the PVI-based method, in contrast to the NDVI-based approach, had a better performance in estimating GC of wheat. The highest correlation between the observed GC and the estimated GC based on PVI method was achieved in interval length of 0.0005 (R2 = 0.91) with RMSE equal to 8.82. This regression line (GCEST = -3.47 + 0.96 GCOBS) was not significantly different from the 1:1 line. As expected, the best estimation was achieved when the sensitivity of estimated GC based on PVI (length of the interval: 0.0005) was almost constant and low compared to the other models.     

Using the hyperbolic distribution to estimate the precision of size distribution percentiles of fluvial gravels

The hyperbolic distribution is fitted to published grain-size data collected from the surface of two gravel-bed rivers (the Fraser and Mamquam River data sets of Rice and Church). Our parametric approach enables calculation of standard errors for estimates of percentiles, as an alternative to the use of the bootstrap for this purpose. For estimation, we have used the statistical package R and the advantages of this software for this type of analysis are highlighted in this paper.     

Using test case patterns to estimate software development and quality management cost

A novel process to discover test case patterns is proposed. This has led to the construction of a test case patterns catalogue. The catalogue has been analysed to estimate the potential reusability in different software applications. This has shown that 43% of system functions are generally application domain independent, whereas 57% are application domain dependent. Statistical tests showed that the level of specialisation in software systems could be as low as 20%, which supports the direction taken in this research to reuse test case patterns in software engineering activities, in particular, software cost estimation at the early sages of software development.

Using enterprise architecture analysis and interview data to estimate service response time

Insights into service response time is important for service-oriented architectures and service management. However, directly measuring the service response time is not always feasible or can be very costly. This paper extends an analytical modeling method which uses enterprise architecture modeling to support the analysis. The extensions consist of (i) a formalization using the Hybrid Probabilistic Relational Model formalism, (ii) an implementation in an analysis tool for enterprise architecture and (iii) a data collection approach using expert assessments collected via interviews and questionnaires. The accuracy and cost effectiveness of the method was tested empirically by comparing it with direct performance measurements of five services of a geographical information system at a Swedish utility company. The tests indicate that the proposed method can be a viable option for rapid service response time estimates when a moderate accuracy within 15% is sufficient.     

Application of current switching method to estimate the model parameters of proton exchange membrane fuel cell

This paper presents a model parameter estimation method for the proton exchange membrane fuel cell (PEMFC). The parameter estimation method is based on the current switching technique, intentionally switching the output current of PEMFC to obtain the waveform of the transient terminal voltage. The parameter values are found by analyzing transient waveform measurement results from the current switching test. To demonstrate the effectiveness of the current switching method, the method is tested on a practical PEMFC stack. Good agreement between the experimental and simulated results is obtained. The test results show the parameter estimation method is efficient and reliable.     

Using the normalized peak area of remote sensing reflectance in the near-infrared region to estimate total suspended matter

The normalized peak area (NPA) of remote-sensing reflectance (R _rs) in the near-infrared region was used to estimate the concentration of total suspended matter (C _TSM) in coastal waters. A linear regression model between C _TSM and S _NPA (R ²?=?0.83) was established, where S _NPA is the area encompassed by the reflectance curve and the straight line between wavelengths 768 and 840 nm where there is a maximum of R _rs near 715 nm. In the Pearl River estuary of South China, this NPA model performed better than other single-band and multi-band regression models, with a root mean square error (RMSE) of 4.07 mg l^–1. This model may be widely applied to in situ measurements of TSM.     

Myofilament proteins: From cardiac disorders to proteomic changes

Myofilament proteins of the cardiac sarcomere house the molecular machinery responsible for generating tension and pressure. Release of intracellular Ca(2+) triggers myofilament tension generation and shortening, but the response to Ca(2+) is modulated by changes in key regulatory proteins. We review how these proteomic changes are essential to adaptive physiological regulation of cardiac output and become maladaptive in cardiac disorders. We also review the essentials of proteomic techniques used to study myofilament protein changes, including degradation, isoform expression, phosphorylation and oxidation. Selected proteomic studies illustrate the applications of these approaches.     

Using hyperspectral vegetation indices to estimate the fraction of photosynthetically active radiation absorbed by corn canopies

The fraction of photosynthetically active radiation (FPAR) absorbed by vegetation – a key parameter in crop biomass and yields as well as net primary productivity models – is critical to guiding crop management activities. However, accurate and reliable estimation of FPAR is often hindered by a paucity of good field-based spectral data, especially for corn crops. Here, we investigate the relationships between the FPAR of corn (Zea mays L.) canopies and vegetation indices (VIs) derived from concurrent in situ hyperspectral measurements in order to develop accurate FPAR estimates. FPAR is most strongly (positively) correlated to the green normalized difference vegetation index (GNDVI) and the scaled normalized difference vegetation index (NDVI*). Both GNDVI and NDVI* increase with FPAR, but GNDVI values stagnate as FPAR values increase beyond 0.75, as previously reported according to the saturation of VIs – such as NDVI – in high biomass areas, which is a major limitation of FPAR-VI models. However, NDVI* shows a declining trend when FPAR values are greater than 0.75. This peculiar VI–FPAR relationship is used to create a piecewise FPAR regression model – the regressor variable is GNDVI for FPAR values less than 0.75, and NDVI* for FPAR values greater than 0.75. Our analysis of model performance shows that the estimation accuracy is higher, by as much as 14%, compared with FPAR prediction models using a single VI. In conclusion, this study highlights the feasibility of utilizing VIs (GNDVI and NDVI*) derived from ground-based spectral data to estimate corn canopy FPAR, using an FPAR estimation model that overcomes limitations imposed by VI saturation at high FPAR values (i.e. in dense vegetation).     

Using remote sensing to estimate sea ice thickness in the Bohai Sea,China based on ice type

It is challenging to use traditional remote sensing techniques to accurately determine the extent and thickness of ice in the Bohai Sea, on account of the presence of sea impurities (i.e. mud, salt bubbles and sand) and shape irregularities. Accordingly, we performed a series of reflectance spectra experiments to empirically link remote measurements of surface reflectance with in situ sea ice thickness measurements in the Bohai Sea. Two years of Thematic Mapper (TM) band 2 and Moderate Resolution Imaging Spectroradiometer (MODIS) band 4 data were used to distinguish between the following sea ice types, using spectral reflectance thresholds of 6.4, 9.6, 10.3 and 12.1%: (a) clean nilas ice (a thin elastic crust of ice up to 10 cm thick that, under pressure, may deform by finger rafting; (b) nilas ice and pancake ice (roughly circular accumulations of frazil ice, usually less than about 3 m in diameter, with raised rims caused by collisions); (c) grey and grey–white ice; and (d) cumulative ice (<30 cm). By establishing a relationship between sea ice type and ice thickness, a novel, practical and low-cost remote sensing technique is introduced to estimate the extent and distribution of sea ice thickness over a large spatial scale. The results obtained by remote sensing are validated with in situ ice shape measurements. The MODIS and TM data are used to distinguish between three ice thickness grades (6–9, 10–20 and 20–30 cm).     

Using a three-dimensional particle-tracking model to estimate the residence time and age of water in a tidal estuary

A three-dimensional hydrodynamic model that includes a Lagrangian particle-tracking simulation was applied to the Danshuei River estuarine system in northern Taiwan. The model's accuracy was validated with data from 1999; the results from the model agreed well with empirical observations of water surface elevation, tidal currents, and salinity. The validated model was then used to investigate the residence time and water age in response to different levels of freshwater discharge. A regression analysis of the model results revealed that an exponential equation best explained the correlation between residence time and freshwater input. We found that the residence times during the low and high freshwater discharge episodes were 4.4 and 2.5 days, respectively. The water age during the low-flow periods was greater than that during the high-flow periods. The modelled residence time and water age values without density-induced circulation were higher than those with density-induced circulation, which indicates that density-induced estuarine circulation may play a significant role in the estuary.     

Synaptic shot noise and conductance fluctuations affect the membrane voltage with equal significance

The subthreshold membrane voltage of a neuron in active cortical tissue is a fluctuating quantity with a distribution that reflects the firing statistics of the presynaptic population. It was recently found that conductance-based synaptic drive can lead to distributions with a significant skew. Here it is demonstrated that the underlying shot noise caused by Poissonian spike arrival also skews the membrane distribution, but in the opposite sense. Using a perturbative method, we analyze the effects of shot noise on the distribution of synaptic conductances and calculate the consequent voltage distribution. To first order in the perturbation theory, the voltage distribution is a gaussian modulated by a prefactor that captures the skew. The gaussian component is identical to distributions derived using current-based models with an effective membrane time constant. The well-known effective-time-constant approximation can therefore be identified as the leading-order solution to the full conductance-based model. The higher-order modulatory prefactor containing the skew comprises terms due to both shot noise and conductance fluctuations. The diffusion approximation misses these shot-noise effects implying that analytical approaches such as the Fokker-Planck equation or simulation with filtered white noise cannot be used to improve on the gaussian approximation. It is further demonstrated that quantities used for fitting theory to experiment, such as the voltage mean and variance, are robust against these non-Gaussian effects. The effective-time-constant approximation is therefore relevant to experiment and provides a simple analytic base on which other pertinent biological details may be added.     

How to estimate the sizes of domains

We present a statistical method which allows the estimation of the unknown sizes of domains of attributes in a relation of a data base. A confidence interval is given for each result. This method extends the scope of formulae for the sizes of results of relational algebra operators.     

Using remote sensing to estimate the change of carbon storage: A case study in the estuary of Yellow River delta

Land cover change can exert a crucial effect on the terrestrial carbon cycle. To estimate changes in the carbon pools and carbon fluxes to the atmosphere, Landsat Thematic Mapper (TM) data of 1992 and 1996 were used to calculate the extent of different land cover types and their changes in the estuary area of the Yellow River delta. Image processing and the unsupervised classification allowed accurate land cover maps for 1992 and 1996 to be generated, by which the changes in the carbon pools were detected. Estimation of the carbon pools and the carbon fluxes to the atmosphere was carried out employing the results of Landsat image analysis and the published data on carbon stocks in vegetation and soil. By calculating the area changed between different types of vegetation and their different carbon stocks, the quantity of the terrestrial carbon cycle in the estuary area of the Yellow River delta was acquired. The results shows that the vegetation carbon storage was 11.43 2 10 11 g and soil carbon pool 7.24 2 10 12 g in 1992, and the vegetation carbon pool increased by 3.77 2 10 11 g during the 4 years from 1992 to 1996.