Matching of graphical symbols in line-drawing images using angular signature information

In this paper, a method for matching complex objects in line-drawings is presented. Our approach is based on the notion of -signatures, which are a special kind of histogram of forces [17,19,28]. Such histograms have low time complexity and describe signatures that are invariant to fundamental geometrical transformations such as scaling, translation, symmetry, and rotation. This article presents a new application of this notion in the field of symbol identification and recognition. To improve the efficiency of matching, we propose using an approximation of the -signature from Fourier series and the associated matching.Received: 7 October 2002, Accepted: 1 December 2002, Published online: 4 July 2003     

Extraction of the spectral information of terahertz signals using superconducting Josephson junction

Using YBa2Cu3O7-δ/MgO bicrystal Josephson junction,we have developed a setup for spectrum analyses of terahertz signals,up to 2.5 THz,with a frequency resolution of 3 GHz.The junction works at liquid nitrogen temperature when the signal frequencies are low while for signals at 1.6 THz and 2.5 THz the junction is cooled to 6 K.Digital signal processing(DSP) chips are made use of to build a data acquisition and processing system so that it can be compact,fast,and intelligent.With the completion of the relevan...     

Utility of spectral vegetation index for estimation of gross CO2 flux under varied sky conditions

To estimate the gross CO₂ flux (F_CO2) of deciduous coniferous forest from canopy spectral reflectance, we introduced spectral vegetation indices (VIs) into a light use efficiency (LUE) model of mature Japanese larch (Larix kaempferi) forest. We measured the eddy covariance CO₂ flux and spectral reflectance of larch canopy at half-hourly intervals during one growing season, and investigated the relationships between the parameters of the LUE model (FAPAR, ?) and 3 types of VIs (NDVI, PRI, EVI) in both clear sky and cloudy conditions.FAPAR (fraction of absorbed photosynthetically active radiation) had a positive linear relationship with both NDVI (normalized difference vegetation index) and EVI (enhanced vegetation index), and the sky condition had little effect on the relationships. The relative RMSE (root mean square error) of the APAR (absorbed photosynthetically active radiation) based on the incoming PAR and estimated FAPAR from a linear function of NDVI was less than 10.5%, irrespective of sky condition.Half-hourly values of ? (conversion efficiency of absorbed energy) showed both seasonal variation related to leaf phenology and short-term variation related to light intensity due to varied sun position and sky condition. Both EVI and PRI (photochemical reflectance index) were significantly correlated with ?. EVI showed a positive linear relationship with ? as a result of their similar seasonal variation. However, since EVI did not detect short-term variation of ?, their relationship differed among sky conditions. On the other hand, although PRI could trace the short-term variation of ? in green needles, the relationship became non-linear due to drastic reduction of PRI in the senescent needles.EVI/(PRI/PRI_min), a combined index based on a 6-day moving minimum value of PRI (PRI_min), showed a linear relationship with half-hourly values of ? throughout the seasons irrespective of sky condition. This index allow us to estimate ? in all sky conditions with a smaller error (rRMSE = 35.2%) than using EVI or PRI alone (38.7%-48.7%). Consequently, this combined index-derived ? and NDVI-based FAPAR gave a low estimation error of F_CO2 (rRMSE = 36.4%, RMSE = 8.3 μmol m^− 2 s^− 1). Although there are still various issues to resolve, including adaptive limit and combination of vegetation index type, we conclude that the combination of PRI and EVI increased the accuracy of estimation of CO₂ uptake in deciduous forest even though sky conditions varied.     

Satellite-based estimation of regional particulate matter (PM) in Beijing using vertical-and-RH correcting method

Theoretical analysis based on the atmospheric radiative transfer indicated a positive correlation between the aerosol optical thickness (AOT) and the surface-level particulate matter (PM) concentrations, and this correlation is improved significantly using vertical-and-RH correcting method. The correlative analysis of the ground-based measurement indicates that, (a) the correlation between AOT and the aerosol extinction coefficient at surface level (k_a,0) is improved as a result of the vertical correction, with the coefficient of determination R² increasing from 0.35 to 0.56; (b) the correlation between k_a,0 and PM concentrations can be significantly improved by the RH correction with the R² increasing from 0.43 to 0.77 for PM10, and from 0.35 to 0.66 for PM2.5. Based on the in-situ measurements in Beijing, two linear correlative models between the ground-based AOT and PMs (e.g. PM10 and PM2.5) concentrations were developed. These models are used to estimate the regional distribution of PM10 and PM2.5 using the satellite-retrieved AOT in Beijing area. Validation against the in-situ measurements in Beijing shows that both of the correlations of the satellite-estimated PM10 and PM2.5 with the measurements are R² = 0.47, and the biases are 26.33% and 6.49% respectively. When averaged in the urban area of Beijing, the R² between the estimated PM10 and the measurements increased to 0.66. These results suggest that by using the vertical-and-RH correcting method we can use the MODIS data to monitor the regional air pollution.     

Speed and rotor flux estimation of induction machines using a two-stage extended Kalman filter

This paper presents an effective implementation of an extended Kalman filter used for the estimation of both rotor flux and rotor velocity of an induction motor. An algorithm proposed by Hsieh and Chen in [Hsieh, C.S., & Chen, F.C. (1999). Optimal solution of the two-stage Kalman estimator. IEEE Transactions on automatic control, 44(1), 194-199] for linear parameter estimation is extended to non-linear estimation, where parameters such as the velocity of an induction machine are present in the transition matrix and in the augmented state space. Compared to a straightforward implementation of an extended Kalman filter, our modified optimal two-stage Kalman estimator reduces the number of arithmetic operations by 25%, allowing higher sampling rate or the use of a cheaper microcontroller.     

Effects of chlorophyll fluorescence on the estimation of microphytobenthos biomass using spectral reflectance indices

The communities of benthic microalgae that form dense biofilms at the surface of aquatic sediments, or microphytobenthos, are important primary producers in estuarine intertidal flats and shallow coastal waters. The microalgal biomass present in the photic zone of the sediment is a key parameter for ecological and photophysiological studies on microphytobenthos, and has been routinely estimated using hyperspectral reflectance indices based on the chlorophyll (Chl) a red absorption peak at 675 nm, usually the Normalised Difference Vegetation Index (NDVI). This study reports that red region-based biomass indices measured on microphytobenthos biofilms can be significantly affected by the enrichment of reflected light with solar-induced Chl fluorescence emitted by the microalgae. Chl fluorescence emission peaks at 683 nm, counterbalancing the decrease in reflectance centered at 675 nm, thus causing the underestimation of NDVI. The interference of Chl fluorescence was found to be easily identified by a conspicuous double-peak feature in the 670-700 nm region of the second-derivative reflectance spectra. The fluorescence-induced NDVI underestimation was shown to be most pronounced for high surface biomass levels and low incident solar irradiance. Particular aspects of microphytobenthos biofilms, such as the increase in surface Chl fluorescence due the contribution of emission by subsurface layers, and vertical migratory responses by motile microalgae to changes in ambient light, further complicate the effects on biomass estimation using NDVI-like indices. By comparing NDVI with a fluorescence-independent biomass index for a wide range of natural light conditions, it was found that Chl fluorescence interference may cause the underestimation of microalgal biomass to reach over 25%, with errors above 10% being expected for more than half of the measuring occasions. These results indicate that the use of NDVI may compromise the correct assessment of important aspects of microphytobenthos ecology, such as the characterisation of migratory behaviour or the determination of biomass-specific productivity rates, and call for the use of alternative biomass indices, not based on the Chl a red absorption peak.     

Scale influences on the remote estimation of evapotranspiration using multiple satellite sensors

There is considerable interest in using remote sensing to characterize the hydrologic behavior of the land surface on a routine basis. Information on moisture fluxes between the surface and lower atmosphere reveals linkages and land-atmosphere feedback mechanisms, aiding our understanding of energy and water balance cycles. Techniques that combine information on land and atmospheric properties with remotely sensed variables would allow improved prediction for a number of hydrological variables. Over the last few decades, there has been a focus on better determining evapotranspiration and its spatial variability, but for many regions routine prediction is not generally available at a spatial resolution appropriate to the underlying surface heterogeneity. Over agricultural regions, this is particularly critical, since the spatial extent of typical field scales is not regularly resolved within the pixel resolution of satellite sensors. Understanding the role of landscape heterogeneity and its influence on the scaling behavior of surface fluxes as observed by satellite sensors with different spatial resolutions is a critical research need. To attend this task, data from Landsat-ETM (60 m), ASTER (90 m), and MODIS (1020 m) satellite platforms are employed to independently estimate evapotranspiration. The range of the satellite sensor resolutions allows analyses that span scales from (point-scale) in-situ tower measurements to the MODIS kilometer-scale. Evapotranspiration estimates derived at these multiple resolutions were assessed against eddy covariance flux measurements collected during the 2002 Soil Moisture Atmospheric Coupling Experiment (SMACEX) over the Walnut Creek watershed in Iowa. Together, these data allow a comprehensive scale intercomparison of remotely sensed predictions, which include intercomparisons of the evapotranspiration products from the various sensors as well as a statistical analysis for the retrievals at the watershed scale. A high degree of consistency was observed between the retrievals from the higher-resolution satellite platforms (Landsat-ETM and ASTER). The MODIS-based estimates, while unable to discriminate the influence of land surface heterogeneity at the field scale, effectively reproduced the watershed average response, illustrating the utility of this sensor for regional-scale evapotranspiration estimation.     

On the estimation of independent binomial random variables using occurrence and sequential information

We re-visit² the age-old problem of estimating the parameters of a distribution from its observations. Traditionally, scientists and statisticians have attempted to obtain strong estimates by ‘extracting’ the information contained in the observations taken as a set. However, generally speaking, the information contained in the sequence in which the observations have appeared, has been ignored—i.e., except to consider dependence information as in the case of Markov models and n-gram statistics. In this paper, we present results which, to the best of our knowledge, are the first reported results, which consider how estimation can be enhanced by utilizing both the information in the observations and in their sequence of appearance. The strategy, known as sequence based estimation (SBE) works as follows. We first quickly allude to the results pertaining to computing the maximum likelihood estimates (MLE) of the data when the samples are taken individually. We then derive the corresponding MLE results when the samples are taken two-at-a-time, and then extend these for the cases when they are processed three-at-a-time, four-at-a-time etc. In each case, we also experimentally demonstrate the convergence of the corresponding estimates. We then suggest various avenues for future research, including those by which these estimates can be fused to yield a superior overall cumulative estimate of the parameter of the distribution, in pattern recognition (PR), and in other internet and compression applications. We believe that our new estimates have great potential for practitioners, especially when the cardinality of the observation set is small.     

Retrieval of the canopy leaf area index in the BOREAS flux tower sites using linear spectral mixture analysis

This paper reports on the use of linear spectral mixture analysis for the retrieval of canopy leaf area index (LAI) in three flux tower sites in the Boreal Ecosystem-Atmosphere Study (BOREAS) southern study area: Old Black Spruce, Old Jack Pine, and Young Jack Pine (SOBS, SOJP, and SYJP). The data used were obtained by the Compact Airborne Spectrographic Imager (CASI) with a spatial resolution of 2 m in the winter of 1994. The convex geometry method was used to select the endmembers: sunlit crown, sunlit snow, and shadow. Along transects for these flux tower sites, the fraction of sunlit snow was found to have a higher correlation with the field-measured canopy LAI than the fraction of sunlit crown or the fraction of shadow. An empirical equation was obtained to describe the relation between canopy LAI and the fraction of sunlit snow. There is a strong correlation between the estimated LAI and the field-measured LAI along transects (with R² values of 0.54, 0.71, and 0.60 obtained for the SOBS, SYJP, and SOJP sites, respectively). The estimated LAI for the whole tower site is consistent with that obtained by the inversion of a canopy model in our previous study where values of 0.94, 0.92, and 0.63 were obtained for R² for the SOBS, SYJP and SOJP sites, respectively.The CASI 2-m summer data over the SOBS site was also employed to investigate the possibility of deriving canopy LAI from the summer data using linear mixture analysis. At a spatial resolution of 10 m, the correlation between the field-measured LAI and the estimated LAI along transects is small at R² less than 0.3, while R² increases to 0.6 at a spatial resolution of 30 m. The difficulty in canopy LAI retrieval from the summer data at a spatial resolution of 10 m is likely due to the variation of the understory reflectance across the scene, although spatial misregistration of the CASI data used may also be a possible contributing factor.     

超声波测风系统中自适应时延估计算法的研究

在时差法超声波测风系统中,风速的测量精度受到时间延迟估计精度、两超声波传感器的距离精度等的影响。在后者一定的情况下,测风精度对时延估计精度提出了更高的要求。对此,采用了一种基于权值检测的最小均方误差(LMS)自适应时延估计算法,从而实现了高精度时延估计。计算机仿真与实际测试表明:该算法的估计精度满足了所研制的超声波测风系统的设计要求,能够用于机场区域低空风场情况的监测。     

Selection of optimal AR spectral estimation method for internal carotid arterial Doppler signals using Cramer-Rao bound

In this study, Doppler signals recorded from internal carotid artery of 80 subjects were processed by PC-computer using autoregressive method and Doppler power spectra were obtained. The parameters of autoregressive method were estimated by different estimation methods such as Yule-Walker, covariance, modified covariance, Burg, least squares, and maximum likelihood estimation. Doppler spectra were then used to compare the applied estimation methods in terms of their frequency resolution and the effects in determination of stenosis in internal carotid arteries. The Cramer-Rao bounds were derived for the estimated autoregressive parameters of the internal carotid arterial Doppler signals and the performance evaluation of the estimation methods was performed using the Cramer-Rao bound values. Finally, the optimal autoregressive spectral estimation method for the internal carotid arterial Doppler signals was selected according to the computed Cramer-Rao bound values.     

Statistical modelling of information sharing: Community, membership, and content

File-sharing systems, like many online and traditional information sharing communities (e.g. newsgroups, BBS, forums, interest clubs), are dynamical systems in nature. As peers get in and out of the system, the information content made available by the prevailing membership varies continually in amount as well as composition, which in turn affects all peers’ join/leave decisions. As a result, the dynamics of membership and information content are strongly coupled, suggesting interesting issues about growth, sustenance, and stability.

In this paper, we propose to study such communities with a simple statistical model of an information sharing club. Carrying their private payloads of information goods as potential supply to the club, peers join or leave on the basis of whether the information they demand is currently available. Information goods are chunked and typed, as in a file-sharing system where peers contribute different files, or a forum where messages are grouped by topics or threads. Peers’ demand and supply are then characterized by statistical distributions over the type domain.

This model reveals interesting critical behaviour with multiple equilibria. A sharp growth threshold is derived: the club may grow towards a sustainable equilibrium only if the value of an control parameter is above the threshold, or shrink to emptiness otherwise. The control parameter is composite and comprises the peer population size, the level of their contributed supply, the club’s efficiency in information search, the spread of supply and demand over the type domain, as well as the goodness of match between them.     

LTI modelling of NFIR systems: near-linearity and control, LS estimation and linearization

Linear time-invariant (LTI) modelling of nonlinear finite impulse response (NFIR) systems is studied from a control point of view. Nearly linear NFIR systems and their control-relevant properties are analysed in detail. The main modelling interest is in the analysis of least squares (LS) LTI identification when the true system is an NFIR system, which is possibly nearly linear. Linearization is used for comparison purposes as the second LTI modelling technique. Nearly linear systems provide a natural generalization of LTI systems to include nonlinearities that allow globally good LTI approximations, while at the same time, such nonlinearities can have a very dramatic effect on the local characteristics of the system. Several control-oriented examples illustrate the possible weaknesses and strengths of the studied LTI modelling techniques. Linearization is found to be especially vulnerable to the presence of even very small, only locally significant, nonlinearities. LS estimation can largely avoid such difficulties, but input design becomes a more critical issue than in standard linear estimation theory. Certain counter-intuitive properties of commonly used input-output stability notions, such as ?₂ stability, are discussed via the concept of near-linearity.     

A new information system in support of landscape assessment: PLAINS

Several business sectors have identified the potential benefits of a landscape/urban assessment based upon the objective appraisal of the interaction of the cultural and natural landscapes. This paper describes a recently approved project (PLAINS) funded by DGXII of the European Union under the Framework IV Environment and Climate Programme. The aim of this project is to identify the benefits of introducing satellite Earth Observation data into the landscape assessment process and to develop a decision support system that will provide for landscape/urban classification tuned to satisfy specific customer requirements. The system will also allow the exploration of impact assessment (‘what if’) scenarios. The project involves three different business sectors who have inherently similar requirements in landscape assessment. The ‘customer’ organisations involved in the project cover the sectors: regional planning authorities, Estate Agents and tourism. In all, there are 13 partners involved in the project from five countries (UK, Denmark, Germany, Italy, Poland). The initial development of the system will use test sites in the counties of Hereford and Worcester in the UK, with subsequent validation being carried out at sites in Italy (Province of Savona), Germany and Poland.     

A new approach for land surface emissivity estimation using LDCM data in semi-arid areas: exploitation of the ASTER spectral library data set

In this research, a new approach called non-vegetated based emissivity estimation method (NV-method) for estimating land surface emissivity (LSE) on Landsat-8 (known as Landsat Data Continuity Mission, LDCM) data has been proposed for semi-arid areas. At first, a simulation of channel emissivities and reflective bands of basic classes in vegetation and non-vegetated areas is accomplished based on convolving Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) spectral Library with LDCM spectral response functions. Then, four main classes in non-vegetated areas are defined to determine separate emissivity estimate model as a function of reflective bands from basic spectra associated with the main class. The LSEs in mixed and vegetation areas are adopted from the simplified normalized difference vegetation index (NDVI)-based emissivity threshold method (N-method^THM), namely SN-method^THM and improved N-method^THM (IN-method^THM) methods, respectively. The NV-method is empirically tested using LDCM data and the obtained LSEs were compared with two scenes of LSE product of the ASTER. The root mean square error (RMSE) values of computed LSEs by NV-method are 0.46% and 0.81%, for band 10 and 11, respectively, in the first examined scene. While, for the second scene, the RMSE are 0.36% and 0.56% for band 10 and 11, respectively. Moreover, the NV-method were compared with N-method^THM, SN-method^THM, and IN-method^THM in non-vegetated areas. Generally, the obtained results of LSEs by NV-method are better than that of results from the compared methods in non-vegetated areas in terms of statistical measures. Except in rocky class, for which N-method^THM provides better results, the NV-method achieved superior results in soil texture and man-made classes, which are dominating classes in the study area.     

Observability analysis of rotation estimation by fusing inertial and line-based visual information: A revisit

This note presents a simple approach to the observability analysis of the rotation estimation using line-based dynamic vision and inertial sensors. The problem was originally raised and formulated in Rehbinder, and Ghosh [2003. Pose estimation using line-based dynamic vision and inertial sensors. IEEE Transactions on Automatic Control, 48(2), 186-199.] where the unobservable subgroup was derived using complex matrix manipulations. By solving linear quaternion equations and using set operations, we not only successfully obtain the same result but also naturally extend it for the case with linearly dependent lines. The development in this note is more straightforward and gives rise to a clearer picture of the problem.     

Development of a micrometeorological model for the estimation of methane flux from paddy fields: Validation with standard direct measurements

This work has focussed on the development of an indirect method for estimating methane fluxes from paddy fields and wetlands. A micrometeorological model, based on an analytical solution of the Eulerian advection–diffusion equation for vertical diffusion, has been used; model parameters include the location of the methane analyser and standard surface layer scaling factors. Flux chambers, which are commonly used for measuring methane fluxes from agricultural sources, are usually mechanically operated with a rated induced-draft fan and as such cannot replicate the real world atmospheric conditions. The results are not very reliable due to leakages along the piping and at fittings, especially when these chambers are used over a relatively rough surface like an agricultural field or a wetland. The results of the model have been compared with those from the direct method. The seasonal average methane flux calculated by the indirect method, for the cultivar type “Sundari”, is 7.13E+05 g/ha, while cultivar type “Shatabdi” gives a little lower value of 5.22E+05 g/ha. In case of the direct chamber method also, the seasonal average methane flux for the cultivar type “Sundari” (6.20E+05 g/ha) is more than cultivar type “Shatabdi” (4.84E+05 g/ha). When the two methods of assessment were compared, season September–December 2004 gave r² = 0.91, RMSE = 0.16 and MNB = 0.13 while we got r² = 0.94, RMSE = 1.22 and MNB = 0.06 for the season September–December 2005.In very few experiments we could cover a huge aerial plot instead of a huge number of experiments necessary for the direct chamber method.     

Management of information systems: Insights from accounting research

This paper advances our knowledge of information systems (IS) management by applying ideas and insights from accounting. An integrative cost–benefit framework is developed and applied to four areas of research: chargeback, outsourcing, decision support, and business process re-engineering and improvement. We show that the accounting literature contributes significantly to scholarship on the management of IS.     

Novel hybrid optimization algorithm using PSO and MADS for the trajectory estimation of a four track wheel skid-steered mobile robot

Several optimization algorithms, such as the particle swarm optimization (PSO), genetic algorithm (GA), and ant colony optimization, have previously been applied in order to reliably obtain more accurate trajectory estimation for mobile robot. However, these optimization algorithms can get easily trapped in local optima when solving a complex system, which has many local optima and many input variables. This paper proposes a novel hybrid optimization algorithm-based tuning of the extended Kalman filter, which involves the PSO and mesh adaptive direct search algorithms, prior to operation. As demonstrated by our experimental results, the advantages of the novel hybrid optimization algorithm resolve the limitations of other algorithms in the trajectory estimation of a four track wheel skid-steered mobile robot (4-TW SSMR).     

Effects of spectral response function on surface reflectance and NDVI measured with moderate resolution satellite sensors: Extension to AVHRR NOAA-17, 18 and METOP-A

This work extends the previous study of Trishchenko et al. [Trishchenko, A. P., Cihlar, J., & Li, Z. (2002). Effects of spectral response function on surface reflectance and NDVI measured with moderate resolution satellite sensors. Remote Sensing of Environment 81 (1), 1-18] that analyzed the spectral response function (SRF) effect for the Advanced Very High Resolution Radiometer (AVHRR) onboard the NOAA satellites NOAA-6 to NOAA-16 as well as the Moderate Resolution Imaging Spectroradiometer (MODIS), the VEGETATION sensor (VGT) and the Global Imager (GLI). The developed approach is now applied to cover three new AVHRR sensors launched in recent years on NOAA-17, 18, and METOP-A platforms. As in the previous study, the results are provided relative to the reference sensor AVHRR NOAA-9. The differences in reflectance among these three radiometers relative to the AVHRR NOAA-9 are similar to each other and range from − 0.015 to 0.015 (− 20% to + 2% relative) for visible (red) channel, and from − 0.03 to 0.02 (− 5% to 5%) for the near infrared (NIR) channel. The absolute change in the Normalized Difference Vegetation Index (NDVI) ranged from − 0.03 to + 0.06. Due to systematic biases of the visible channels toward smaller values and the NIR channels toward slightly larger values, the overall systematic biases for NDVI are positive. The polynomial approximations are provided for the bulk spectral correction with respect to the AVHRR NOAA-9 for consistency with previous study. Analysis was also conducted for the SRF effect only among the AVHRR-3 type of radiometer on NOAA-15, 16, 17, 18 and METOP-A using AVHRR NOAA-18 as a reference. The results show more consistency between sensors with typical correction being under 5% (or 0.01 in absolute values). The AVHRR METOP-A reveals the most different behavior among the AVHRR-3 group with generally positive bias for visible channel (up to + 5%, relative), slightly negative bias for the NIR channel (1%-2% relative), and negative NDVI bias (− 0.02 to + 0.005). Polynomial corrections are also suggested for normalization of AVHRR on NOAA-15, 16, 17 and METOP-A to AVHRR NOAA-18.