Accounting for Heterogeneity in Stop Frequency Models of Work Tours Using Latent Class Poisson Models

Stop frequency models, as one of the elements of activity based models, represent an important part of travel behavior. Unobserved heterogeneity across the travelers should be taken into consideration to prevent biasedness and inconsistency in the estimated parameters in the stop frequency models. Additionally, previous studies on the stop frequency have mostly been done in larger metropolitan areas and less attention has been paid to the areas with less population. This study addresses these gaps by using 2012 travel data from a medium sized U.S. urban area using the work tour for the case study. Stop in the work tour were classified into three groups of outbound leg, work based subtour, and inbound leg of the commutes. Latent Class Poisson Regression Models were used to analyze the data. The results indicate the presence of heterogeneity across the commuters. Using latent class models significantly improves the predictive power of the models compared to regular one class Poisson regression models. In contrast to one class Poisson models, gender becomes insignificant in predicting the number of tours when unobserved heterogeneity is accounted for. The commuters are associated with increased stops on their work based subtour when the employment density of service-related occupations increases in their work zone, but employment density of retail employment does not significantly contribute to the stop making likelihood of the commuters. Additionally, an increase in the number of work tours was associated with fewer stops on the inbound leg of the commute. The results of this study suggest the consideration of unobserved heterogeneity in the stop frequency models and help transportation agencies and policy makers make better inferences from such models.

Kinetic analysis and modeling of maize straw hydrochar combustion using a multi-Gaussian-distributed activation energy model

Combustion kinetics of the hydrochar was investigated using a multi-Gaussian-distributed activation energy model(DAEM)to ex-pand the knowledge on the combustion mechanisms.The results demonstrated that the kinetic parameters calculated by the multi-Gaussian-DAEM accurately represented the experimental conversion rate curves.Overall,the feedstock combustion could be divided into four stages:the decomposition of hemicellulose,cellulose,lignin,and char combustion.The hydrochar combustion could in turn be divided into three stages:the combustion of cellulose,lignin,and char.The mean activation energy ranges obtained for the cellulose,lignin,and char were 273.7-292.8,315.1-334.5,and 354.4-370 kJ/mol,respectively,with the standard deviations of 2.1-23.1,9.5-27.4,and 12.1-22.9 kJ/mol,re-spectively.The cellulose and lignin contents first increased and then decreased with increasing hydrothermal carbonization(HTC)temperature,while the mass fraction of char gradually increased.

An Adaptive Time-Step Backward Differentiation Algorithm to Solve Stiff Ordinary Differential Equations: Application to Solve Activated Sludge Models

A backward differentiation formula (BDF) has been shown to be an effective way to solve a system of ordinary differential equations (ODEs) that have some degree of stiffness. However, sometimes, due to high-frequency variations in the external time series of boundary conditions, a small time-step is required to solve the ODE system throughout the entire simulation period, which can lead to a high computational cost, slower response, and need for more memory resources. One possible strategy to overcome this problem is to dynamically adjust the time-step with respect to the system’s stiffness. Therefore, small time-steps can be applied when needed, and larger time-steps can be used when allowable. This paper presents a new algorithm for adjusting the dynamic time-step based on a BDF discretization method. The parameters used to dynamically adjust the size of the time-step can be optimally specified to result in a minimum computation time and reasonable accuracy for a particular case of ODEs. The proposed algorithm was applied to solve the system of ODEs obtained from an activated sludge model (ASM) for biological wastewater treatment processes. The algorithm was tested for various solver parameters, and the optimum set of three adjustable parameters that represented minimum computation time was identified. In addition, the accuracy of the algorithm was evaluated for various sets of solver parameters.

无数据库模型在rails的form_for表单中的应用

rails的Active Model作为模型可以应用于不需要数据库存储数据的场合。经过定制,它可以很好地在form_for表单中工作。

Studies on Heavy Metal Pollution in Soil-Plant System:A Review

Heavy metal pollution in soil-plant system is of major environmental concern on a world scale and in China in particular with the rapid development of industry. The heavy metal pollution status in soil-plant system in China, the research progress on the bioavailability of heavy metals (affecting factors, extraction methods, free-ion activity model, adsorption model, multivariate regression model, Q-I relationship, and compound pollution), and soil remediation are reviewed in the paper. Future research and monitoring is also discussed.

Activity model and its application in CaO-FeO-SiO_2-MoO_3 quarternary system

The activity model of CaO-FeO-SiO_2-MoO_3 quarternary system was establishedaccording to the coexistence theory of slag structure and the reduction thermodynamics of molybdenumoxide was discussed by applying this model. The activities of SiO_2 and MoO_3 decrease, while thatof CaO increases with increasing the basicity of slag. Among SiC, [C] and [Si] reactants, thereducing capability of SiC is the strongest, while that of [C] is the poorest at a high temperature(about 1873 K). It is advantageous to increase the yield of molybdenum by increasing the content of[Si] or [C]. Controlling of basicity of slag can prevent the oxidation loss of molybdenum.

ONLINE MODEL AND ACTUATOR FAULT TOLERANT CONTROL FOR AUTONOMOUS MOBILE ROBOT

A novel fault-tolerant adaptive control methodology against the actuator faults is proposed. The actuator effectiveness factors （AEFs） are introduced to denote the healthy of actuator, and the unscented Kalman filter （UKF） is employed for online estimation of both the motion states and the AEFs of mobile robot. A square root version of the UKF is introduced to improve efficiency and numerical stability. Using the information from the UKF, the reconfigurable controller is designed automatically based on an enhancement inverse dynamic control （IDC） methodology. The experiment on a 3-DOF omni-directional mobile robot is performed, and the effectiveness of the proposed method is demonstrated.

Anaerobic tapered fluidized bed reactor for starch wastewater treatment and modeling using multilayer perceptron neural network

treatability of synthetic sago wastewater was investigated in a laboratory anaerobic tapered fluidized bed reactor （ATFBR） with a mesoporous granular activated carbon （GAC） as a support material. The experimental protocol was defined to examine the effect of the maximum organic loading rate （OLR）, hydraulic retention time （HRT）, the efficiency of the reactor and to report on its steady- state performance. The reactor was subjected to a steady-state operation over a range of OLR up to 85.44 kg COD/（m^3·d）. The COD removal efficiency was found to be 92% in the reactor while the biogas produced in the digester reached 25.38 m^3/（m^3·d） of the reactor. With the increase of OLR from 83.7 kg COD/（m^3·d）, the COD removal efficiency decreased. Also an artificial neural network （ANN） model using multilayer perceptron （MLP） has been developed for a system of two input variable and five output dependent variables. For the training of the input-output data, the experimental values obtained have been used. The output parameters predicted have been found to be much closer to the corresponding experimental ones and the model was validated for 30% of the untrained data. The mean square error （MSE） was found to be only 0.0146.

Vacuum pressure swing adsorption process for coalbed methane enrichment

The enrichment of low concentration coalbed methane using adsorption process with activated carbon adsorbent was studied in this work.Adsorption isotherms of methane,nitrogen and carbon dioxide on activated carbon were measured by volumetric method,meanwhile a series of breakthrough tests with single component,binary components and three components feed mixture has been performed for exploring dynamic adsorption behaviors.Moreover,a rigorous mathematical model of adsorption bed containing mass,energy,and momentum conservation equation as well as dualsite Langmuir model with the Linear driving force model for gassolid phase mass transfer has been proposed for numerical modeling and simulation of fixed bed breakthrough process and vacuum pressure swing adsorption process.Furthermore,the lumped mass transfer coefficient of methane,nitrogen and carbon dioxide on activated carbon adsorbent has been determined to be 0.3 s^(-1),1.0 s^(-1) and 0.06 s^(-1) by fitting the breakthrough curves using numerical calculation.Additionally,a six bed VPSA process with twelve step cycle sequence has been proposed and investigated for low concentration coalbed methane enrichment.Results demonstrated that the methane molar fraction in feed mixture ranged from 10%to 50%could be enriched to 32.15%to 88.75%methane in heavy product gas with a methane recovery higher than 83%under the adsorption pressure of 3 bar(1 bar=105 Pa)and desorption pressure of 0.1 bar.Energy consumption of this VPSA process was varied from 0.165 k·W·h·m^(-3) CH_(4)to 0.649 k·W·h·m^(-3) CH_(4).Finally,a dualstage VPSA process has been successfully developed to upgrade a low concentration coalbed methane containing 20%methane to a target product gas with methane purity higher than 90%,meanwhile the total methane recovery was up to 98.71%with a total energy consumption of 0.504 k·W·h·m^(-3)CH_(4).

New edge detection method for high-resolution SAR images

A new edge detection method combining the scanning window central edge （SWCE） detector and an improved active contour model is proposed. The method first emploies the SWCE detector based on the difference of area pixel value means to perform an optimal edge detection, and then proposes an improved active contour model with modified energy functions to refine the location of the edges. The initial nodes of the improved active contour model are automatically found from the vectorised results of the SWCE detector. Tests on simulated speckled images and real airborne SAR images show that the combined method can benefit from the advantages of the both techniques and get satisfactory edge detection and localization abilities at the same time.

Mixed convection in gravity-driven nano-liquid film containing both nanoparticles and gyrotactic microorganisms

Analysis of a gravity-induced film flow of a fluid containing both nanoparticles and gyrotactic microorganisms along a convectively heated vertical surface is presented.The Buongiorno model is applied. Two kinds of boundary conditions, the passive and the active boundary conditions, are considered to investigate this film flow phenomenon.Through a set of similarity variables, the ordinary differential equations that describe the conservation of the momentum, the thermal energy, the nanoparticles, and the microorganisms are derived and then solved numerically by an efficient finite difference technique.The effects of various physical parameters on the profiles of momentum, thermal energy,nanoparticles, microorganisms, local skin friction, local Nusselt number, local wall mass flux, and local wall motile microorganisms flux are investigated. It is expected that the passively controlled nanofluid model can be much more easily achieved and applied in real circumstances than the actively controlled model.

Vehicle Active Steering Control Research Based on Two-DOF Robust Internal Model Control

Because of vehicle＇s external disturbances and model uncertainties,robust control algorithms have obtained popularity in vehicle stability control.The robust control usually gives up performance in order to guarantee the robustness of the control algorithm,therefore an improved robust internal model control（IMC） algorithm blending model tracking and internal model control is put forward for active steering system in order to reach high performance of yaw rate tracking with certain robustness.The proposed algorithm inherits the good model tracking ability of the IMC control and guarantees robustness to model uncertainties.In order to separate the design process of model tracking from the robustness design process,the improved 2 degree of freedom（DOF） robust internal model controller structure is given from the standard Youla parameterization.Simulations of double lane change maneuver and those of crosswind disturbances are conducted for evaluating the robust control algorithm,on the basis of a nonlinear vehicle simulation model with a magic tyre model.Results show that the established 2-DOF robust IMC method has better model tracking ability and a guaranteed level of robustness and robust performance,which can enhance the vehicle stability and handling,regardless of variations of the vehicle model parameters and the external crosswind interferences.Contradiction between performance and robustness of active steering control algorithm is solved and higher control performance with certain robustness to model uncertainties is obtained.

Design of active disturbance rejection internal model control strategy for SISO system with time delay process

A novel control scheme of active disturbance rejection internal model control(ADRIMC) is proposed to improve the anti-interference ability and robustness for the dead-time process. The active anti-interference concept is introduced into the internal model control(IMC) by analyzing the relationship between IMC and disturbance observer control(DOB). Further, a design process of disturbance filter is presented to realize the active anti-interference ability for ADRIMC scheme. The disturbance filter is used to estimate an equivalent disturbance consisting of both external disturbances and internal disturbances caused by model mismatches.Simulation results demonstrate that the proposed method possesses a good disturbance rejection performance, though losing some partial dynamic performance. In other words, the proposed method shows a tradeoff between the dynamic performance and the system robust.

Experimental study and simulations of infiltration in evapotranspiration landfill covers

Various cover systems have been designed for landfill sites in order to minimize infiltration （percolation） into the underlying waste. This study evaluated the soil water balance performance of evapotranspiration covers （ET covers） and simulated percolation in the systems using the active region model （ARM）. Experiments were conducted to measure water flow processes and water balance components in a bare soil cover and different ET covers. Results showed that vegetation played a critical role in controlling the water balance of the ET covers. In soil profiles of 60-cm depth with and without vegetation cover, the maximum soil water storage capacities were 97.2 mm and 62.8 mm, respectively. The percolation amount in the bare soil was 2.1 times that in the vegetation-covered soil. The ARM simulated percolation more accurately than the continuum model because it considered preferential flow. Numerical simulation results also indicated that using the ET cover system was an effective way of removing water through evanotransoiration, thus reducing nercolation.

Antitumor Activity of Diallyl Sulfide in Two-StageMouse Skin Model of Carcinogenesis

It has been reported that diallyl sulfide (DAS), a sulfur-containing volatile compound in garlic (Allium sativum ), exerts anticarcinogenic activity in various rodent tumor models. In the present study, the antitumor property of DAS was tested in Swiss albino mice in the two steqe initiation-promotion mouse skin carcinogenesis. Skin cancers were initiated topically with a single subcarcinOgenic dose (52μg) of 7, 12-dimethyl benz (a) anthracene (DMBA). Promotion was performed by twice weekly applications of 12-O-tetradecanoyl phorbol-13-acetate (TPA) at a dose of 5μg/animal for 32 weeks. DAS was applied topically (250μg/animal) thrice weekly for 3 weeks for anti-initiating and 1 h prior to each promotion treatment for anti-promoting studies. The results showed that the treatment schedule of DAS can effectively delay the onset of tumorigenesis and reduce the cumulative number of tumors and the average number of tumors per mouse. In groups in which DAS applied prior to initiation or promotion, a significant population of the aniinals remained tumor-free till the termination of experiment. These findings suggest that DAS can effectively inhibit chemically induced mouse skincarcinogenesis.

The Research of Automatic Classification of Ultrasound Thyroid Nodules

This paper proposes a computer-aided diagnosis system which can automatically detect thyroid nodules (TNs)and discriminate them as benign or malignant. The system firstly uses variational level set active contour withgradients and phase information to complete automatic extraction of the boundaries of thyroid nodules images.Then according to thyroid ultrasound images and clinical diagnostic criteria, a new feature extraction methodbased on the fusion of shape, gray and texture is explored. Due to the imbalance of thyroid sample classes, thispaper introduces a weight factor to improve support vector machine, offering different classes of samples withdifferent weights. Finally, thyroid nodules are classified and discriminated by the improved support vector machine.Experiments show that the efficiency of discrimination on benign and malignant thyroid nodules is improved.

A distribution prior model for airplane segmentation without exact template

In many practical applications of image segmentation problems,employing prior information can greatly improve segmentation results.This paper continues to study one kind of prior information,called prior distribution.Within this research,there is no exact template of the object;instead only several samples are given.The proposed method,called the parametric distribution prior model,extends our previous model by adding the training procedure to learn the prior distribution of the objects.Then this paper establishes the energy function of the active contour model(ACM)with consideration of this parametric form of prior distribution.Therefore,during the process of segmenting,the template can update itself while the contour evolves.Experiments are performed on the airplane data set.Experimental results demonstrate the potential of the proposed method that with the information of prior distribution,the segmentation effect and speed can be both improved efficaciously.

Generalized Internal Model Robust Control for Active Front Steering Intervention

Because of the tire nonlinearity and vehicle＇s parameters＇uncertainties,robust control methods based on the worst cases,such as H_∞,μsynthesis,have been widely used in active front steering control,however,in order to guarantee the stability of active front steering system（AFS）controller,the robust control is at the cost of performance so that the robust controller is a little conservative and has low performance for AFS control.In this paper,a generalized internal model robust control（GIMC）that can overcome the contradiction between performance and stability is used in the AFS control.In GIMC,the Youla parameterization is used in an improved way.And GIMC controller includes two sections：a high performance controller designed for the nominal vehicle model and a robust controller compensating the vehicle parameters＇uncertainties and some external disturbances.Simulations of double lane change（DLC）maneuver and that of braking on split-μroad are conducted to compare the performance and stability of the GIMC control,the nominal performance PID controller and the H_∞controller.Simulation results show that the high nominal performance PID controller will be unstable under some extreme situations because of large vehicle＇s parameters variations,H_∞controller is conservative so that the performance is a little low,and only the GIMC controller overcomes the contradiction between performance and robustness,which can both ensure the stability of the AFS controller and guarantee the high performance of the AFS controller.Therefore,the GIMC method proposed for AFS can overcome some disadvantages of control methods used by current AFS system,that is,can solve the instability of PID or LQP control methods and the low performance of the standard H_∞controller.

Extended activated sludge model no. 1 (ASM1) for simulating biodegradation process using bacterial technology

Phosphorus is one of the most important nutrients required to support various kinds of biodegradation processes. As this particular nutrient is not included in the activated sludge model no. 1 （ASM1）, this study extended this model in order to determine the fate of phosphorus during the biodegradation processes. When some of the kinetics parameters are modified using observed data from the restoration project of the Xuxi River in Wuxi City, China, from August 25 to 31 in 2009, the extended model shows excellent results. In order to obtain optimum values of coefficients of nitrogen and phosphorus, the mass fraction method was used to ensure that the final results were reasonable and practically relevant. The temporal distribution of the data calculated with the extended ASM1 approximates that of the observed data.

Application of Active Contour Model in Tracking Sequential Nearshore Waves

In the present study, a generalized active contour model of gradient vector flow is combined with the video techniques of Argus system to delineate and track sequential nearshore wave crest profiles in the shoaling process, up to their breaking on the shoreline. Previous applications of active contour models to water wave problems are limited to controllable wave tank experiments. By contrast, our application in this study is in a nearshore field environment where oblique images obtained under natural and varying condition of ambient light are employed. Existing Argus techniques produce plane image data or time series data from a selected small subset of discrete pixels. By contrast, the active contour model produces line image data along continuous visible curves such as wave crest profiles. The combination of these two existing techniques, the active contour model and Argus methodologies, facilitates the estimates of the direction wave field and phase speeds within the whole area covered by camera. These estimates are useful for the purpose of inverse calculation of the water depth. Applications of the present techniques to Hsi-tzu bay where a beach restoration program is currently undertaken are illustrated. This extension of Argus video techniques provides new application of optical remote sensing to study the hydrodynamics and morphology of a nearshore environment.