Straight-line Model Research Articles

Research into the integrated navigation of a deep-sea towed vehicle with USBL/DVL and pressure gauge

Underwater Towed Vehicle navigation and localization in deep sea environments are particularly challenging without high-precision inertial sensors. In this paper, the multi-sensors navigation fusion method of a towed underwater vehicle based on the ultrashort baseline (USBL) system, Dopplervelocitylog (DVL) and a pressure gauge in the deep sea is investigated. Combined with GPS real-time tide detection technology, the positioning principle of the USBL based on the depth constraint is given, and a straight-line model be proposed to estimate the position of the vehicle used the average heading when underwater towed vehicle is working normally in deep sea without DVL. The interacting multiple model (IMM) algorithm based on smoothing algorithm is proposed to improve the positioning accuracy in the deep sea, and the nonlinearity of the model, precision and stability of filtering are considered simultaneously using the adaptive robust square root cubature Kalman filter. The results of the simulated and practical experiments at 4800 m verify that the new algorithm can take full use of high-precision observation information and greatly improve the positioning accuracy and robustness of a deep sea underwater towed system.

Against Common Assumptions, the World’s Shark Bite Rates Are Decreasing

The trends of the world’s top ten countries relating to shark bite rates, defined as the ratio of the annual number of shark bites of a country and its resident human population, were analyzed for the period 2000-2016. A nonparametric permutation-based methodology was used to determine whether the slope of the regression line of a country remained constant over time or whether so-called joinpoints, a core feature of the statistical software Joinpoint, occurred, at which the slope changes and a better fit could be obtained by applying a straight-line model. More than 90% of all shark bite incidents occurred along the US, Australia, South Africa, and New Zealand coasts. Since three of these coasts showed a negative trend when transformed into bite rates, the overall global trend is decreasing. Potential reasons for this decrease in shark bite rates—besides an increase in the world’s human population, resulting in more beach going people, and a decrease of sharks due to overfishing—are discussed.

Determining acceptable limits of fast-electron preheat in direct-drive-ignition–scale target designs

In direct-drive–ignition designs, preheat by fast electrons created by the two-plasmon–decay or stimulated Raman instabilities can increase the adiabat in the fuel layer and reduce compression and neutron yields. Since eliminating the preheat entirely is a major challenge, it is necessary to understand the levels of preheat that preclude ignition in a direct-drive target. Two 1-D ignition-scale target designs serve as the basis for examining the effects of synthetically increasing the levels of fast electrons using the 1-D radiation–hydrodynamic code LILAC, which include two models of fast-electron transport. The first is an ignition design adapted from a 2-D polar-direct-drive design for the National Ignition Facility. The second is a variant of the first with identical dimensions and compositions but using a laser pulse that generates stronger shocks and a higher fuel adiabat. This more stable design approaches ignition and achieves yield multiplication as a result of alpha heating. The designs are then re-optimized to recover performance. The igniting design, when fast-electron transport was modeled with diffusion, was found to tolerate 50% more fast-electron preheat of the cold (sub-50 eV) deuterium-tritium (DT) ice layer when the laser pulse was optimized using the optimizer Telios. When a straight-line fast-electron transport model was used, the effects of optimization were negligible. For the subignition design, an increase of over a factor of at least 3 in the tolerable level of fast-electron preheat was obtained for both transport models.

Direct Calculation Method of Fringing Field Reluctance in MEC Analysis for An Axisymmetric Solenoid Actuator

In this paper, a method is introduced to directly calculate the reluctances of fringing fields in analyzing a magnetic equivalent circuit model for an axisymmetric solenoid actuator including radial air gaps as well as axial air gaps. The introduced method was motivated by the possibility to calculate the cross section area depending on the radial position of an infinitesimal element when the infinitesimal element is defined to be integrated in the flux flow direction in a circular-arc straight-line model of an axisymmetric model. In this method, the reluctance of fringing field near an air gap can be calculated directly. For an objective model, the MEC analysis was performed using the introduced method and an iterative method. In the iterative method, the nonlinearity of the ferromagnetic material parts is resolved. In order to validate the introduced method, MEC analysis and FEA results are compared. And for validating the method in a view of computation also, an optimized design satisfying pre-defined constraints was searched using MEC analysis, and then the results of the MEC analysis using the introduced method and FEA results are compared for the searched design and the initial design.

Mesoscale model for elastic modulus of warp-knitted fabric-reinforced composites based on spring model

In this paper, a ‘mesoscale spring model’ was generated to predict the tensile modulus of warp-knitted fabric-reinforced composites. A previously developed geometrical model was used for generating a mechanical model as a set of series and parallel springs. For this purpose, the unit cell of straight line model was discretized into different segments. Each segment was modelled as a spring with definite constant based on the alignment of yarns in the segment. Warp-knitted fabrics (Queen's Cord) were used as reinforcement of composites. In order to validate the presented model, samples of composites were produced using hand layup method. Tensile tests were carried out on the prepared samples. The comparison between theoretical and experimental elastic modulus showed a reasonable agreement between experimental and theoretical data. Also, the comparison between the results of different models and experimental data showed that the results of spring model are closer to the experimental results than that of Krenchel's model. It can be concluded that the spring model can predict adequately the elastic modulus of composites.

Detection of Multiple Maneuvering Extended Targets by Three-Dimensional Hough Transform and Multiple Hypothesis Tracking

Existing extended target probability hypothesis density (ET-PHD) filters are insufficient in tracking weak extended targets. Hough transform-based track-before-detect methods are designed to detect the weak targets in a straight-line constant-velocity model. Therefore, this paper presents a novel method for detecting and tracking multiple maneuvering weak extended targets by a 3-dimensional Hough transform (3DHT) and multiple hypothesis tracking (MHT). The proposed method consists of two stages. In stage 1, the measurements in multiple scans are partitioned into overlapped time windows. The tracklets in each window can be detected by the 3DHT. In stage 2, the tracklets are associated to get the entire trajectories by the MHT. The tracklets of weak targets can be detected by the 3DHT in stage 1. Association in stage 2 is designed to detect maneuvering targets. Some false alarm tracklets could be built in stage 1. However, the false alarm tracklets are independent and unlikely to form a sequential trajectory in stage 2. Merely, the trajectories whose target likelihood ratio larger than a detection threshold can be confirmed as a target. Both the real data and the synthetic data are performed with the proposed approach and several existing algorithms. The result infers that the proposed approach is superior to the others with much less prior information that is necessary.

Least-Squares Analysis of Data with Uncertainty in y and x: Algorithms in Excel and KaleidaGraph

For the least-squares analysis of data having multiple uncertain variables, the generally accepted best solution comes from minimizing the sum of weighted squared residuals over all uncertain variables, with, for example, weights in xi taken as inversely proportional to the variance σxi2. A complication in this method, here called “total variance” (TV), is the need to calculate residuals δi in every uncertain variable. In x–y problems, that means adjustments must be obtained for x as well as for the customary y. However, for the straight-line fit model, there is a simpler procedure, a version of effective variance (EV) methods, that requires only the residuals in y and agrees exactly with the TV method. Furthermore, Monte Carlo calculations have shown that this EV2 method is statistically comparable to the TV method for many common nonlinear fit models. This method is easy to code for computation in Excel and programs like KaleidaGraph, as is illustrated here for several examples, including implicit nonli...

Robust Bayesian linear regression with application to an analysis of the CODATA values for the Planck constant

Weighted least-squares estimation is commonly applied in metrology to fit models to measurements that are accompanied with quoted uncertainties. The weights are chosen in dependence on the quoted uncertainties. However, when data and model are inconsistent in view of the quoted uncertainties, this procedure does not yield adequate results.When it can be assumed that all uncertainties ought to be rescaled by a common factor, weighted least-squares estimation may still be used, provided that a simple correction of the uncertainty obtained for the estimated model is applied. We show that these uncertainties and credible intervals are robust, as they do not rely on the assumption of a Gaussian distribution of the data. Hence, common software for weighted least-squares estimation may still safely be employed in such a case, followed by a simple modification of the uncertainties obtained by that software. We also provide means of checking the assumptions of such an approach.The Bayesian regression procedure is applied to analyze the CODATA values for the Planck constant published over the past decades in terms of three different models: a constant model, a straight line model and a spline model. Our results indicate that the CODATA values may not have yet stabilized.

A Comparison of Performance Between Straight-Line Muscle and Curved Muscle Models

The straight-line muscle biomechanical models of the lumbar spine have been utilized to predict spinal loads to assess the potential risk of work-related injuries. The curved muscle paths have been suggested to realistically simulate muscles’ behavior in complex lumbar motions. However, the effect of curved muscle paths on the modeling performances and spinal loads in the lumbar spine model during complex lifting exertions has not been fully investigated. The objective of this study was to characterize the differences in modeling performances and spinal loads between the conventional straight-line muscle model and the curved muscle model of the lumbar spine. Twelve subjects (6 males and 6 females) participated in this study. Mean values and standard deviations of age, body mass, and height of all subjects were 26.6 (5.3) years, 73.6 (13.3) kg, and 172.7 (5.4) cm, respectively. Electromyographic (EMG) activities with surface electrodes (Motion Lab Systems MA300-XVI, Baton Rouge, Louisiana, USA) were collected over 10 trunk muscles (pair of the latissimus dorsi, erector spinae, rectus abdominis, external oblique, and internal oblique) with 1000 Hz sampling rate. The OptiTrack optical motion capture system (NaturalPoint, Corvallis, OR, USA) with 24 Flex 3 infrared cameras was used to monitor whole body kinematics with 100 Hz sampling rate. A Bertec 4060A force plate (Bertec, Worthington, OH, USA) was used to measure ground reaction forces with 1000 Hz sampling rate. Customized Laboratory software via a National Instruments USB-6225 data acquisition board (National Instruments, Austin, TX, USA) was utilized to collect all signals simultaneously and efficiently run the model. Subjects performed complex lifting tasks by various load weight (9.1kg and 15.9kg), load origins (counterclockwise 90⁰, counterclockwise 45⁰, 0⁰, clockwise 45⁰, and clockwise 90⁰), and load height (mid-calf, mid-thigh, and shoulder). Both curved muscle model and straight-line muscle model were tested under same experiment conditions, respectively. The curved muscle model showed better model fidelity (average coefficient of determination (R2) = 0.83; average absolute error (AAE) = 14.4%) than the straight-line muscle model (R2 = 0.79; AAE = 20.7%), especially in upper levels of the lumbar spine. The curved muscle model showed higher R2 than the straight-line muscle model, and the T12/L1 level showed the biggest difference as 0.1. The curved muscle model had lower AAE than the straight-line muscle model, and the T12/L1 showed the biggest difference as 18%. The curved muscle model generally showed higher compression (up to 640N at T12/L1), lower anterior-posterior shear loads (up to 575N at T12/L1), and lower lateral shear loads (up to 521N at T12/L1) than the straight-line muscle model. The biggest difference in spinal loads between two models (especially in anterior-posterior shear and lateral shear loads) occurred at upper levels of the lumbar spine, which could be related to the amount of muscle curvatures at each spine level. The curved muscle model generally showed higher compression and lower anterior-posterior and lateral shear loads than the straight-line muscle model. It might be partially related to the muscle paths of the erector spinae (major power producing muscle). In curved muscle model, erector spinae was placed more parallel with the lumbar spine curvature than the straight-line muscle model. It could affect the spinal load distributions such as higher compression and lower shears loads in the curved muscle model compared to the straight-line muscle model. In conclusion, the improved performance of the curved muscle model indicated that the curved muscle approach would be advantageous to estimate precise spinal loads in complex lifting jobs compared to the straight-line muscle approach.

Modeling of LOB scheduling with learning development effect

ABSTRACTSeveral techniques have been used to schedule repetitive projects; the most widely one is Line-Of-Balance (LOB). The primary advantage of LOB is maintaining work continuity, which leads to maximizing learning development effect and minimizing idle time of crews. While LOB is basically applicable to repetitive projects, learning development effect that naturally inherent with repetition is usually ignored. Several mathematical models, or learning curves, have been developed to investigate variation in productivity as a function of the number of units produced. The most practical and used one is the straight-line model. In this paper, learning development effect is incorporated into traditional LOB scheduling. The basic equation of LOB technique has been modified to consider learning development effect, in which straight-line learning curve model is adopted. An example project is used to demonstrate model calculations and obtained results are then analyzed. The developed model has been applied on a real-life project in order to demonstrate its applicability and practicality. Incorporating learning development effect into LOB scheduling provides for more realistic forecast of repetitive projects duration and/or cost. The proposed model provides both academics and practitioners with an effective tool for scheduling repetitive projects based on realistic assumptions.

Beam scan mode analysis and design for geosynchronous SAR

The beam velocity of geosynchronous synthetic aperture radar (GEO SAR) varies seriously with the orbital position and the scene position, which leads to a significant variation of the scene length and the azimuth resolution in the stripmap (SM) mode. To obtain uniform scene length and azimuth resolution, beam scan modes can be utilized in GEO SAR, such as the sliding spotlight (SLL) mode and the terrain observation by progressive scans (TOPS) mode. However, the conventional design method of the beam scan mode is based on the straight line model (SLM), which does not consider the effects of the curved satellite track and the spherical earth surface. To solve this problem, a curvature circle model (CCM) is proposed considering the actual satellite-earth relationship. By using the CCM, the beam velocity after the beam scan is derived. The scene length and the azimuth resolution are analyzed. The SLL mode and the TOPS mode are recommended for GEO SAR. After that, a design method of the beam scan mode is proposed based on the CMM. The performance of the proposed method is verified by computer simulations.

Pareto-Lognormal Modeling of Known and Unknown Metal Resources. II. Method Refinement and Further Applications

Pareto-lognormal modeling of worldwide metal deposit size–frequency distributions was proposed in an earlier paper (Agterberg in Nat Resour 26:3–20, 2017). In the current paper, the approach is applied to four metals (Cu, Zn, Au and Ag) and a number of model improvements are described and illustrated in detail for copper and gold. The new approach has become possible because of the very large inventory of worldwide metal deposit data recently published by Patino Douce (Nat Resour 25:97–124, 2016c). Worldwide metal deposits for Cu, Zn and Ag follow basic lognormal size–frequency distributions that form straight lines on lognormal Q–Q plots. Au deposits show a departure from the straight-line model in the vicinity of their median size. Both largest and smallest deposits for the four metals taken as examples exhibit hyperbolic size–frequency relations and their Pareto coefficients are determined by fitting straight lines on log rank–log size plots. As originally pointed out by Patino Douce (Nat Resour Res 25:365–387, 2016d), the upper Pareto tail cannot be distinguished clearly from the tail of what would be a secondary lognormal distribution. The method previously used in Agterberg (2017) for fitting the bridge function separating the largest deposit size–frequency Pareto tail from the basic lognormal is significantly improved in this paper. A new method is presented for estimating the approximate deposit size value at which the upper tail Pareto comes into effect. Although a theoretical explanation of the proposed Pareto-lognormal distribution model is not a required condition for its applicability, it is shown that existing double Pareto-lognormal models based on Brownian motion generalizations of the multiplicative central limit theorem are not applicable to worldwide metal deposits. Neither are various upper tail frequency amplification models in their present form. Although a physicochemical explanation remains possible, it is argued that preferential mining of the largest and smallest orebodies can have economic historical reasons. The size–frequency distribution of uranium can be regarded as lognormal without Pareto tails. At the end of the paper, it is shown that original copper deposit size data can be used for forward projection of discovery trends toward the end of this century.

Collaborative guarded-hot-plate tests between the Laboratoire national de métrologie et d’essais and the National Institute of Standards and Technology

A collaborative study to compare the long-term measurement performance between guarded-hot-plate facilities at the Laboratoire national de métrologie et d’essais (LNE) in France and the National Institute of Standards and Technology (NIST) in the United States is presented. Thermal conductivity data were compiled from three international comparisons organized from 1997 to 2014. Measurements were conducted in accordance with standardized test methods (ISO 8302 or ASTM C 177) over a temperature range from 280 K to 320 K. Nine thermal insulating materials (either mineral fiber or expanded polystyrene) were examined covering broad ranges of bulk densities (13 kg · m−3–200 kg · m−3) and thicknesses (13 mm–70 mm). A different set of specimens was utilized for each comparison. Results of this study indicate that, over a 17 year interval, the majority of test data from LNE and NIST agreed to within ±1.0%, or less, for mineral fiber materials and to within ±0.5%, or less, for expanded polystyrene. The long-term variability limit of 1% between the two laboratories is in good agreement with their current measurement uncertainties. Regression coefficients and their standard uncertainties for a straight-line model relating thermal conductivity to temperature from 280 K to 320 K were computed by material and laboratory. Graphical analysis of the data and corresponding fits exhibit consistent behavior by material type between the two laboratories. Sources of measurement variability are addressed.

Validation of a personalized curved muscle model of the lumbar spine during complex dynamic exertions

Previous curved muscle models have typically examined their robustness only under simple, single-plane static exertions. In addition, the empirical validation of curved muscle models through an entire lumbar spine has not been fully realized. The objective of this study was to empirically validate a personalized biologically-assisted curved muscle model during complex dynamic exertions. Twelve subjects performed a variety of complex lifting tasks as a function of load weight, load origin, and load height. Both a personalized curved muscle model as well as a straight-line muscle model were used to evaluate the model’s fidelity and prediction of three-dimensional spine tissue loads under different lifting conditions. The curved muscle model showed better model performance and different spinal loading patterns through an entire lumbar spine compared to the straight-line muscle model. The curved muscle model generally showed good fidelity regardless of lifting condition. The majority of the 600 lifting tasks resulted in a coefficient of determination (R2) greater than 0.8 with an average of 0.83, and the average absolute error less than 15% between measured and predicted dynamic spinal moments. As expected, increased load and asymmetry were generally found to significantly increase spinal loads, demonstrating the ability of the model to differentiate between experimental conditions. A curved muscle model would be useful to estimate precise spine tissue loads under realistic circumstances. This precise assessment tool could aid in understanding biomechanical causal pathways for low back pain.

Testing straightness of line objects using total least squares

The paper presents the adaptation (fitting) of a set of points, with an estimated two-dimensional positions, to the straight line model of the by the application of the Weighted Total Least Squares, WTLS. The traditional method to solve this problem by using an iterative algorithm of the conditional adjustment with the parameters (Gauss-Helmert's model) is also shown. In the example of testing the straightness of the rail of the crane, a comparison of the efficiency of the two algorithms is performed by means of result of parameter estimation and to the number of required iterations to final solution.

Learning effect on labour productivity of repetitive concrete masonry blockwork

Purpose The applicability of learning curve theory to the construction industry has been investigated by several studies; however, the outcomes are characterised by inconsistent, rather sporadic patterns. Therefore, the purpose of this paper is to explore the effect of learning on concrete masonry blockwork labour productivity in recurring building floor cycles. Design/methodology/approach Repetitive blockwork labour inputs from 52 multi-storey residential buildings were collected and analysed using the straight-line learning curve model. The cumulative average labour input for each recurring floor and its corresponding cycle number were modelled using the least squares method. Findings According to the learning curve theory principles, labour inputs are expected to decrease by a certain percentage as the floor cycle number within each building observed increases. Nonetheless, the patterns emerged from this study provide little evidence for that. Practical implications Contrary to several previous findings which have asserted the significance of the learning concept to construction productivity, the results obtained for the activity investigated suggest that there is no potential context for the theory to be used as a useful tool to quantify productivity improvement, or to provide for a practical project management observation and control system. Originality/value Notwithstanding the numerous research into the effect of learning on construction activities, this study is unprecedented in examining the applicability of the theory to concrete masonry blockwork labour productivity in building construction. It can thus assist in achieving reliable planning, determining the plausibility of correlating past performances or predicting future expenditures, and appraising the potentiality of the learning phenomenon as a useful tool to quantify productivity improvement over the repetitive cycle process of such a distinct construction activity.

Efficient Lane Boundary Detection with Spatial-Temporal Knowledge Filtering.

Lane boundary detection technology has progressed rapidly over the past few decades. However, many challenges that often lead to lane detection unavailability remain to be solved. In this paper, we propose a spatial-temporal knowledge filtering model to detect lane boundaries in videos. To address the challenges of structure variation, large noise and complex illumination, this model incorporates prior spatial-temporal knowledge with lane appearance features to jointly identify lane boundaries. The model first extracts line segments in video frames. Two novel filters—the Crossing Point Filter (CPF) and the Structure Triangle Filter (STF)—are proposed to filter out the noisy line segments. The two filters introduce spatial structure constraints and temporal location constraints into lane detection, which represent the spatial-temporal knowledge about lanes. A straight line or curve model determined by a state machine is used to fit the line segments to finally output the lane boundaries. We collected a challenging realistic traffic scene dataset. The experimental results on this dataset and other standard dataset demonstrate the strength of our method. The proposed method has been successfully applied to our autonomous experimental vehicle.

A biologically-assisted curved muscle model of the lumbar spine: Model validation

BackgroundBiomechanical models have been developed to predict spinal loads in vivo to assess potential risk of injury in workplaces. Most models represent trunk muscles with straight-lines. Even though straight-line muscles behave reasonably well in simple exertions, they could be less reliable during complex dynamic exertions. A curved muscle representation was developed to overcome this issue. However, most curved muscle models have not been validated during dynamic exertions. Thus, the objective of this study was to investigate the fidelity of a curved muscle model during complex dynamic lifting tasks, and to investigate the changes in spine tissue loads. MethodsTwelve subjects (7 males and 5 females) participated in this study. Subjects performed lifting tasks as a function of load weight, load origin, and load height to simulate complex exertions. Moment matching measures were recorded to evaluate how well the model predicted spinal moments compared to measured spinal moments from T12/L1 to L5/S1 levels. FindingsThe biologically-assisted curved muscle model demonstrated better model performance than the straight-line muscle model between various experimental conditions. In general, the curved muscle model predicted at least 80% of the variability in spinal moments, and less than 15% of average absolute error across levels. The model predicted that the compression and anterior–posterior shear load significantly increased as trunk flexion increased, whereas the lateral shear load significantly increased as trunk twisted more asymmetric during lifting tasks. InterpretationA curved muscle representation in a biologically-assisted model is an empirically reasonable approach to accurately predict spinal moments and spinal tissue loads of the lumbar spine.

Road Roughness Evaluation by Curve-Fitting and Subspace-Identification Methods

AbstractIn this paper, for a quarter-car model, root-mean square response variables are calculated for roads classified by the international standard organization, based on the straight-line spectrum models. Covariance expressions are derived for vehicle response variables assuming that the road spectrum is that of a Motor Industry Research Association (MIRA) spectrum and compared with the existing results in the literature. The international standard and the MIRA spectra are then compared with the models delivered by high resolution frequency-domain subspace identification algorithms. The IRI statistic of the quarter-car response is calculated for the road models built by the curve fitting and the identification methods from the measured road spectrum assuming that the road excitation is a zero-mean Gaussian process

Modeling air concentration of fly ash in Belgrade, emitted from thermal power plants TNTA and TNTB

Abstract The aim of the study was to estimate if dust/fly ash emitted into the atmosphere from chimneys and the ash disposal sites of the thermal power plants Nikola Tesla A and B in Obrenovac could increase the concentration of PM 10 in New Belgrade. TNTA and TNTB are close to Belgrade (population of 2.5 million) and it is important to estimate the amount of the pollution emitted into the atmosphere from these sources. The pollution from chimneys is estimated from yearly amounts of discharge, while the lifting of ash/coal dust was parameterized by the model. The used model is the straight-line Gaussian plume model written in the Fortran programming language. The first estimation was done using mathematical modeling for the idealized situation with prescribed winds and stability. The second estimation was done using the observed meteorological data for the whole year of 2009. With strong winds (over 40 km/h), dust will reach Belgrade in dozens of minutes, while during moderate winds (∼10–30 km/h), it would take about one hour to reach it. In these cases atmosphere is close to the neutral stability class. In case of weaker winds and stable atmosphere, the increase of air dust concentration in Belgrade would start after a few hours (6–10). Regarding the other two sources of pollution, coal handling piles and ash deposit sites, during strong winds (>40 km/h) and neutral stability, fly ash would reach Belgrade in several dozen of minutes.