Acceptable Error Limits Research Articles

Performance of operational systems with respect to water level forecasts in the Gulf of Finland

This paper is devoted to the validation of water level forecasts in the Gulf of Finland. Daily forecasts produced by four setups of operational, three-dimensional Baltic Sea oceanographic models are analyzed using statistical means and are compared with water level observations at three Finnish stations located on the northern coast of the Gulf of Finland. The overall conclusion is that the operational systems were skillful in forecasting water level variations during the study period from November 1, 2003, to January 31, 2005. The factors causing differences between the water level forecasts of different models are discussed as well. An important task of operational sea level forecasting services is to provide accurate and early information about extreme water levels, both positive and negative surges. During the study period, two major winter storms occurred which caused coastal flooding in the region. According to our analysis, the operational models forecast the rise of water levels during these events rather successfully. Nowadays, operational forecasts can provide early warnings of extreme water levels at least 1 day in advance, which may be regarded as a minimum requirement for an operational forecasting system. The paper concludes that the models generally performed very well, with over 93% of the hourly water level forecasts found to be within the range of ±15 cm of the observed water levels, and with the timing of the water level peaks accurately predicted. Further discussion and studies dealing with the assessment of the skills of both operational meteorological and oceanographic forecasts, especially in connection with rare surge events, will be necessary. Skill assessment of operational oceanographic models would be relatively easy if acceptable error limits or a quality system was developed for the Baltic Sea operational models.

Procrustean solution of the 9-parameter transformation problem

Abstract The Procrustean “matching bed” is employed here to provide direct solution to the 9-parameter transformation problem inherent in geodesy, navigation, computer vision and medicine. By computing the centre of mass coordinates of two given systems; scale, translation and rotation parameters are optimised using the Frobenius norm. To demonstrate the Procrustean approach, three simulated and one real geodetic network are tested. In the first case, a minimum three point network is simulated. The second and third cases consider the over-determined eight- and 1 million-point networks, respectively. The 1 million point simulated network mimics the case of an air-borne laser scanner, which does not require an isotropic scale since scale varies in the X, Y, Z directions. A real network is then finally considered by computing both the 7 and 9 transformation parameters, which transform the Australian Geodetic Datum (AGD 84) to Geocentric Datum Australia (GDA 94). The results indicate the effectiveness of the Procrustean method in solving the 9-parameter transformation problem; with case 1 giving the square root of the trace of the error matrix and the mean square root of the trace of the error matrix as 0.039 m and 0.013 m, respectively. Case 2 gives 1.13×10−12 m and 2.31×10−13 m, while case 3 gives 2.00×10−4 m and 1.20 × 10−5 m, which is acceptable from a laser scanning point of view since the acceptable error limit is below 1 m. For the real network, the values 6.789 m and 0.432 m were obtained for the 9-parameter transformation problem and 6.867 m and 0.438 m for the 7-parameter transformation problem, a marginal improvement by 1.14%.

Estimating coal reserves using a support vector machine

The basic principles of the Support Vector Machine (SVM) are introduced in this paper. A specific process to establish an SVM prediction model is given. To improve the precision of coal reserve estimation, a support vector machine method, based on statistical learning theory, is put forward. The SVM model was trained and tested by using the existing exploration and exploitation data of Chencun mine of Yima bureau's as the input data. Then coal reserves within a particular region were calculated. These calculated results and the actual results of the exploration block were compared. The maximum relative error was 10.85%, within the scope of acceptable error limits. The results show that the SVM coal reserve calculation method is reliable. This method is simple, practical and valuable.

Sintering of titanium dioxide nanoparticles: a comparison between molecular dynamics and phenomenological modeling

Molecular dynamics simulations were used to determine the melting points of anatase and rutile nanoparticles. The melting points decrease with decrease in particle diameter and are in reasonable agreement with the empirical formula derived by Buffat and Borel. The phenomenological model of Koch and Friedlander is unable to predict the temperature rise during initial stages of sintering with acceptable accuracy. It is argued that the Koch and Friedlander assumption of linear surface reduction rate upon sintering may be inadequate for the time scales under consideration. A theoretical model using direct area measurement from molecular dynamics simulations and a single adjustable parameter is able to predict temperature rise during initial stages of sintering within acceptable error limits.

Quantification of Plume Opacity by Digital Photography

The United States Environmental Protection Agency (USEPA) developed Method 9 to describe how plume opacity can be quantified by humans. However, use of observations by humans introduces subjectivity, and is expensive due to semiannual certification requirements of the observers. The Digital Opacity Method (DOM) was developed to quantify plume opacity at lower cost, with improved objectivity, and to provide a digital record. Photographs of plumes were taken with a calibrated digital camera under specified conditions. Pixel values from those photographs were then interpreted to quantify the plume's opacity using a contrast model and a transmission model. The contrast model determines plume opacity based on pixel values that are related to the change in contrast between two backgrounds that are located behind and next to the plume. The transmission model determines the plume's opacity based on pixel values that are related to radiances from the plume and its background. DOM was field tested with a smoke generator. The individual and average opacity errors of DOM were within the USEPA Method 9 acceptable error limits for both field campaigns. Such results are encouraging and support the use of DOM as an alternative to Method 9.

Evaluation of professional choice of sampling locations for indoor air quality assessment

The uncertainties of professional choice of ‘representative’ sampling locations for general indoor air quality (IAQ) assessment are reported from the perspective of probable errors deviated from the sample-spatial average pollutant concentration of an indoor environment. In this study, associations between the professional choices of the sampling locations and attributes of the assessors were examined to quantify the uncertainties of the IAQ assessment results for a typical air-conditioned office in Hong Kong. In particular, a long-term (one-year) measurement result of the spatial indoor carbon dioxide (CO 2) concentrations in this office was used as a basis to investigate the probable errors due to the choices of sampling locations. Comparing with the random choices, the assessment accuracy with the expert choices would be significantly improved for coarse sampling point densities at certain engineering acceptable error limits. It was reported that the location choices and assessment accuracy would be significantly influenced by the academic background of the assessors. An assessor group with higher academic level would make a choice leaning towards more accurate assessment results. To avoid an inappropriate level of reliance on the assessment results, uncertainties must be quantified for IAQ assessment. This study provided a template for further investigations into the uncertainties of IAQ assessment results involving professional choice of ‘representative’ sampling locations and the results might be a useful reference for assessing indoor environment elsewhere.

Spatial Significant Wave Height Variation Assessment and Its Estimation

Significant wave height is a very important variable used in ocean engineering studies. Spatial variation of the significant wave height is very important for wave energy abstraction studies which is highly dependent on the wave climate. Significant wave height and period are two of the most important wave features that directly affect the energy production. In nature these two variables exhibit temporal randomness and spatial changes. These variations cause heterogeneous regional dispersion of wave energy. In order to assess regional energy distribution, it is necessary to use the concept of regionalized variables through geostatistical methods. The main purpose of this paper is to evaluate the spatial characteristics of significant wave height by the point cumulative semivariogram approach leading to a standard regional dependence function (SRDF) based on concepts of the semivariogram. It is also possible to estimate the unmeasured station value from the closest stations by using SRDF and determine the optimum station intervals. The SRDFs are obtained from available spatial data decreasing with distance for a given set of sites. The wave energy resource in a region of the Pacific Ocean off the west coast of the United States has been evaluated as the application of proposed methodology. It is found that spatial modeling of the region considered can be achieved by using the SRDF function in acceptable error limits.

Sensorless vector control of a Permanent magnet synchronuous motor with fuzzy logic observer

In this paper, a new method for sensorless vector control of a permanent magnet synchronous motor (PMSM) using a fuzzy logic observer is developed. This method is based on determination of rotor position and thereby speeds by estimating back-emf components which result from fuzzy logic observers. The rotor position angle and rotating speed are estimated by evaluating the instantaneous values of stator voltages and currents. The estimators are two fuzzy logic observers. They have two inputs: the estimated stator currents and the difference between the measured and estimated stator currents. In addition, the outputs of the fuzzy logic observers are the back-emf components in an α–β reference frame. The proposed method was implemented using a MATLAB/Simulink software package program. The obtained results are within acceptable error limits for a wide speed range, from 40 rad/s up to 500 rad/s.

Fuzzy logic modeling of the dissolved oxygen fluctuations in Golden Horn

The modern modeling techniques show a significant progress in recent years. Fuzzy logic approach is one of these methods that can be used for forecasting purposes and identification of complex systems. In this study, it is aimed to model monthly dissolved oxygen (DO) amount variations. Firstly, regression technique is used to remove the trend from the actual dissolved oxygen time series. Detrended time series is then modeled with Takagi–Sugeno Fuzzy logic approach. The monthly historical records of DO as considered in this paper provide a fundamental data exhibiting persistence. It is this dependence that gives opportunity for the serial modeling of the data sequence concerned. These models are the prime and sole means to derive the future likely excedences over the historical values and hence provide a chance for the future planner with decision variables such as the minimum DO amounts and their persistence for some duration. In the scope of this study, DO concentration changes in the two stations located in Golden Horn at the 0.5 m (upper layer) depth were modeled. As a result of the study, it is seen that one can forecast the next month's DO amount from antecedent measurements within an acceptable relative error limits.

Analysis of Temporal Backscattering of Cotton Crops Using a Semiempirical Model

To develop an operational methodology for estimating soil moisture and crop biophysical parameters and to generate a crop cover map, backscattering signatures of vegetation canopies are investigated using multitemporal Radarsat synthetic aperture radar (SAR) data over a predominantly cotton-growing area in India during low to peak crop growth stage. A simple parameterization of the water-cloud model with volumetric soil moisture content (m/sub v/) and leaf area idex (LAI) is used to simulate the microwave backscattering coefficient (/spl sigma//sup 0/), as it is found to be a good candidate for operational purposes as demonstrated by several workers in past. The influence of crop height (H), LAI, and m/sub v/ on /spl sigma//sup 0/ is investigated during peak crop growth stage. A linear relationship between LAI and crop height is derived semiempirically, and a linear zone is chosen for analysis during the peak crop-growing stage. Estimation of average volume fraction of leaves (V~/sub l/) and attenuation factor (L) by two different approaches is discussed: 1) using linear relationship between LAI versus crop height and 2) from the water-cloud model parameter (/spl kappa/) estimation by iterative minimum least square error approach. It is observed that model-estimated parameters agree well with the measured values within an acceptable error limit. At lower soil moisture, m/sub v//spl cong/0.02(cm/sup 3//spl middot/cm/sup -3/), the dynamic range of /spl sigma//sup 0/ is found to be about +5 dB for 0-70 cm of crop height but monotonously decreases to null at a transition point, having m/sub v//spl ap/0.38(cm/sup 3//spl middot/cm/sup -3/). A positive correlation is found between backscattering coefficient and crop height till this transition point but shows a negative correlation beyond that, signifying the predominant attenuation by vegetation over soil. Differential moisture sensitivity (d/spl sigma//sup 0//dm/sub v/) of the backscattering coefficient decreases by half from 20.55 dB/(cm/sup 3//spl middot/cm/sup -3/) for dry and bare-field conditions to 10.68 dB/(cm/sup 3//spl middot/cm/sup -3/) for wet and crop-covered fields (m/sub v/=0.38cm/sup 3//spl middot/cm/sup -3/, H=70cm), whereas differential crop height sensitivity (d/spl sigma//sup 0//dH) varies from 0.22-0.03 dB/cm for bare-field conditions to crop-covered fields with crop height 70 cm. It is found that the percentage of relative error is smallest (2.27%) for LAI and attenuation factor estimation using the value of V~/sub l/, from LAI models, whereas it is 4.25% when estimating from the attenuation coefficient (/spl kappa/) from the model.

Decoherence in a Josephson-junction qubit

The zero-voltage state of a Josephson junction biased with constant current consists of a set of metastable quantum energy levels. We probe the spacings of these levels by using microwave spectroscopy to enhance the escape rate to the voltage state. The widths of the resonances give a measurement of the coherence time of the two states involved in the transitions. We observe a decoherence time shorter than that expected from dissipation alone in resonantly isolated 20 um x 5 um Al/AlOx/Al junctions at 60 mK. The data is well fit by a model including dephasing effects of both low-frequency current noise and the escape rate to the continuum voltage states. We discuss implications for quantum computation using current-biased Josephson junction qubits, including the minimum number of levels needed in the well to obtain an acceptable error limit per gate.

Closing the Mackenzie basin water budget, water years 1994/95 to 1996/97

A particularly elusive science objective for the Mackenzie Global Energy and Water Cycle Experiment (GEWEX) Study (MAGS) has been to close the atmospheric moisture budget and rationalize it against the surface water budget at annual or even monthly timescales. The task, while not difficult in principle, is complicated by two factors. First is the importance of basin snow‐cover, soil and water‐body storage in the surface water budget. Month‐to‐month changes in these components are frequently greater than the atmospheric flux terms, for example, during spring snowmelt. Furthermore, there is approximately a six‐week lag before local changes are evident in the discharge at the mouth of the basin. Second, the coarse resolution of all of the supporting data may add significant systematic errors. For example, the two radiosonde soundings per day available to the project are unlikely to account adequately for all the moisture generated locally through evapotranspiration during the summer convective season. This analysis will directly address these two main issues by applying hydrologic and atmospheric computations to assess the storage question, and by using additional soundings at a single site to sample the diurnal signature in atmospheric moisture caused by evapotranspiration. Resulting modifications to the atmospheric moisture and surface water budgets then allow near closure of the MAGS monthly water budget within acceptable error limits.

Modelling the seismic attributes of overpressured siliciclastic rocks, with a genetic annealing (GAN) algorithm

A genetic annealing (GAN) algorithm is used to derive an empirical model which predicts compressional-wave velocity values for overpressured siliciclastic rocks. The algorithm involves non-linear random searching and mutation techniques and its annealing component imposes a very strict control over the rate of convergence of the search. This technique provides an alternative to the standard calculations involving the effective stress coefficient (n). The pore pressure is introduced into the model as an explicit variable and as part of an overpressure coefficient, (P p /P c ) - the ratio of pore to confining pressure. Empirical model-derived data and known laboratory data are compared and their differences are shown to be within statistically acceptable error limits. The empirical equation fits all under- and overpressured data simultaneously, irrespective of pore fluid pressure level, with the same parameters. It is used to predict seismic velocities very accurately for extreme levels of overpressure, starting from normally pressured experimental data. The model highlights the effect of pore pressure on the compressional-wave velocity of fully saturated samples with different clay contents. It can be used when the experimental data available are sparse and particularly when a prediction of material behaviour is necessary at specific pore fluid pressure and depth conditions.

Detection of linear substructures in calibration model by robust approach: Maximum sum of binary-coded residuals (MASBR) regression

The MASBR (maximum sum of binary-coded residuals) procedure proposed previously as a robust regression method has been modified and applied to find the linear substructures in a data set. A graphic approach is used to identify the acceptable error limit (AEL) in the MASBR algorithm. Some data sets with mixed linear substructures are interpreted by the proposed method showing satisfactory results. A MATLAB program for the MASBR algorithm is given.

Maximum sum of binary‐coded residuals (MASBR) regression as a robust procedure for treatment of spectral data

AbstractIn this paper, a novel robust regression method, the maximum sum of binary coded residuals (MASBR), is proposed. Instead of the sum of squared residuals used in least squares regression as the minimization criterion, MASBR regression maximizes the sum of binary coded residuals. MASBR regression is designed for cases where the conventional robust regression methods with breakdown points less than 50% fail. To circumvent the problem of being trapped in local optima, a stepwise‐varying acceptable error limit (SVAEL) algorithm is proposed. Both numerical simulation and treatment of real analytical data demonstrate the feasibility of MASBR regression in conjunction with the SVAEL algorithm.

Transmission electron microscopy of C70 single crystals at room temperature

Transmission electron microscopy (TEM) techniques have been employed to study the room temperature solid state form of chromatographically purified C70. Tilting and electron diffraction experiments in three-dimensional reciprocal space, on samples prepared by crystallization from several different solvents, show that C70 crystallites adopt hexagonal close packed (hcp) structure with a = 1.01 ± 0.05 nm and c = 1.70 ± 0.08 nm. The extinctions and observed reflections conform to the P63/mmc space group. High resolution TEM images reveal the molecular order and periodicity associated with C70 crystallites in real space. The experimental results are in agreement with the preliminary computations of crystal structure within acceptable error limits.

Estimating Water Volume Discharge through Salt-Marsh Tidal Channels: An Aspect of Material Exchange

Water volume discharge estimates were made at a sample cross-section of the Canary Creek salt marsh (Lewes, Delaware). To account for cross-sectional velocity variations, a dense spatial array of current meters was used. Simultaneous measurements were taken at hourly intervals over three complete tidal cycles. A practical method is presented whereby instantaneous average cross-sectional velocity, instantaneous cross-sectional discharge and tidal cycle discharge can be estimated from a dense current meter array, orideal data set. Based on theseideal estimates, it is shown that a simplified spatial array can be used to estimate water discharges within acceptable error limits. Instantaneous cross-sectional discharges and total tidal cycle discharges were estimated with uncertainties of ±11% and ±7%, respectively. To minimize errors when estimating material exchange between salt marshes and adjacent waters, it is suggested that a comprehensive assessment of cross-sectional lateral current velocity variations be conducted.

Relation of the Gibbs free energy of transfer of ions from water to polar solvents to the properties of the solvents and the ions

A statistical treatment of data for the standard molar Gibbs free energies of transfer of monovalent ions from water to polar solvents has been made in terms of properties of the solvents and the ions. A common multiple regression equation with seven fitting constants, for almost 200 data points, has been found to describe the data in terms of four solvent properties: their electron donor and acceptor abilities, dielectric constant, and cohesive energy density, and three ionic properties: charge, size, and softness. For the ions Na+, K+, Rb+, Cs+, Tl+, (Ph)4As+, Cl−, Br− and N3− the predictions of the equation are within acceptable error limits of the data, and encourage its application to solvents beyond the thirteen used for the data base. For other ions, e.g. H+, Ag+, and the larger anions, further interactions must be taken into account.

Error-analysis for the determination of molecular weight distributions by dynamic light scattering

Various effects which can distort the molecular weight distribution (MWD) determined by dynamic light scattering (DLS) are discussed. For example, it is shown that the required molecular weight dependence of the diffusion coefficient must be fairly accurately known if the MWD is to be determined with acceptable error limits. It is moreover investigated to what extent a result for the MWD may be distorted when this result is obtained by a fit under the assumption of an incorrect MWD-type. In addition, the scattering-angle accuracy required for a reliable determination of the MWD, and consequences (for the MWD) which may arise from statistical errors in the experimental DLS-curves, are treated.

Optimal insulation of solar heating system pipes and tanks

A compact and time-effective insulation design procedure for solar heating system piping and water-filled thermal storage tanks was developed. Recognizing the particular sensitivity of solar systems to cost, the economic aspect of the problem was treated by a comprehensive present-value life-cycle cost analysis. In the development of the method, a numerical sensitivity analysis was performed to determine the relative effects of all relevant independent variables (within their pertinent ranges) on piping and tank heat transfer coefficient values. For the acceptable error limits of ± 14% for pipes and ± 19% for tanks, it was found that one may assume that only the nominal pipe diameter (or tank diameter), the thermal conductivity of the insulation, and the insulation's thickness have an effect on the overall heat transfer coefficient. Based on this result, design graphs and tables are presented which can be used to determine the optimal insulation thickness and type, total annual heat losses, present-value annual costs of insulation and lost heat, and overall insulation R-values. The use of the method is illustrated by calculating all the above quantities for all piping and storage tanks for the University of Pennsylvania SolaRow House. The present method provided insulation thicknesses slightly greater than those obtained by the ETI technique. A major conclusion of the study is that the cost of insulation in solar systems is not insignificant (e.g., ~15% in SolaRow), and that heat losses through insulation could amount to an important percentage of the useful solar energy collected (e.g., 24% in SolaRow). This re-emphasizes the need for a careful design of insulation in solar systems.