KSUTraffic: A Microscopic Traffic Simulator for Traffic Planning in Smart Cities

Simulation is a powerful tool for improving, evaluating and analyzing the performance of new and existing systems. Traffic simulators provide tools for studying transportation systems in smart cities as they describe the evolution of traffic to the highest level of detail. There are many types of traffic simulators that allow simulating traffic in modern cities. The most popular traffic simulation approach is the microscopic traffic simulation because of its ability to model traffic in a realistic manner. In many cities of Saudi Arabia, traffic management represents a major challenge as a result of expansion in traffic demands and increasing number of incidents. Unfortunately, employing simulation to provide effective traffic management for local scenarios in Saudi Arabia is limited to a number of commercial products in both public and private sectors. Commercial simulators are usually expensive, closed source and inflexible as they allow limited functionalities. In this project, we developed a local traffic simulator “KSUtraffic” for traffic modeling, planning and analysis with respect to different traffic control strategies and considerations. We modeled information specified by GIS and real traffic data. Furthermore, we designed experiments that manipulate simulation parameters and the underlying area. KSUTraffic visualizes traffic and provides statistical results on the simulated traffic which would help to improve traffic management and efficiency.     

Monte Carlo simulation-based traffic speed forecasting using historical big data

Because the traffic patterns on roads vary according to the roads’ specific spatio-temporal behavior, if we would like to forecast the traffic speed by day of the week, it is necessary to determine an optimal set of the highly related historical patterns to achieve high prediction accuracy. The goal of our paper is to suggest a new statistical modeling method that finds the best historical dataset according to various analyses for each link and provides a more accurate prediction of traffic flow by day of the week. First, we suggest a three-step filtering algorithm based on changepoint analysis, correlation analysis, and Monte Carlo simulation to simultaneously find and remove historical data outliers. Second, we determine the optimal historical data range by using decision factors such as the Mean Squared Error (MSE) and Akaike Information Criterion. Moreover, to verify our statistical model, we use various prediction accuracy measures such as Mean Absolute Percentage Error (MAPE), R-squared value, and Root MSE (RMSE). Finally, we construct a big data processing framework to handle the overall prediction process and calculate large amounts of traffic data. The forecasting results show that the proposed model can achieve a high prediction accuracy for each road by using three measures: less than 20% for MAPE, more than 80% for R-squared value, and less than 1 on average for RMSE.     

Effect of genetic merit for energy balance on luteal activity and subsequent reproductive performance in primiparous Holstein-Friesian cows

Postpartum energy status is critically important to fertility. However, studies dealing with the relationship between both traits are rare and most refer only to the phenotypic level. In this study, random regression models were used to generate cow-specific lactation curves for daily breeding values (BV) of energy balance (EB) to assess the effect of genetic merit for energy status on different traits derived from progesterone profiles and on subsequent reproductive performance of high-producing dairy cows. Individual feed intake, milk yield, and live weight were recorded for lactation d 11 to 180, and EB was estimated on a daily basis. The results provided the basis for the estimation of BV for 824 primiparous Holstein-Friesian cows. For a subset of these cows (n = 334), progesterone profiles for the resumption of ovarian activity were available. Four different traits describing the genetic merit for EB were defined to evaluate their relationship with fertility. Two EB traits referred to the period in which the average daily EB across all cows was negative (d 11 to 55 postpartum), and 2 parameters were designed considering only daily BV for d 11 to 180 in lactation that were negative. We found that cows with a high genetic merit for EB had a significantly earlier resumption of ovarian activity postpartum. Thus, an EB (indicator) trait should be included in future breeding programs to reduce the currently prolonged anovulatory intervals after parturition.     

Simulation of a Bubble Column by Computational Fluid Dynamics and Population Balance Equation Using the Cell Average Method

An axisymmetric computational fluid dynamics (CFD) simulation coupled with a population balance equation (PBE) has been applied in simulating the gas‐liquid flow in a bubble column with an in‐house code. The novel feature of this simulation is the application of the cell average method in a CFD‐PBE coupled model for the first time. The predicted results by this method are compared with those by the traditional fixed pivot method and experimental data. For both methods, the simulated results are in reasonable agreement with the reported experimentally measured values. However, the bubble size distributions determined by the cell average method are slightly better than those found by means of the fixed pivot method, i.e., the latter provides a smaller peak value and a wider bubble size distribution, and the probability density function of large bubbles is higher.     

Economic feasibility of algal biodiesel under alternative public policies

The motivation for this research was to determine the influence of public policies on economic feasibility of producing algal biodiesel in a system that produced all its energy needs internally. To achieve this, a steady-state mass balance/unit operation system was modeled first. Open raceway technology was assumed for the production of algal feedstock, and the residual biomass after oil extraction was assumed fermented to produce ethanol for the transesterification process. The project assumed the production of 50 million gallons of biodiesel per year and using about 14% of the diesel output to supplement internal energy requirements. It sold the remainder biodiesel and ethanol as pure biofuels to maximize the rents from the renewable fuel standards quota system. Assuming a peak daily yield of 500 kg algal biomass (dry basis)/ha, the results show that production of algal biodiesel under the foregoing constraints is only economically feasible with direct and indirect public policy intervention. For example, the renewable fuel standards' tracking RIN (Renewable fuel Identification Number) system provides a treasury-neutral value for biofuel producers as does the reinstatement of the renewable fuel tax credit. Additionally, the capital costs of an integrated system are such that some form of capital cost grant from the government would support the economic feasibility of the algal biodiesel production.     

An automatic tool for reconstructing monthly time-series of hydro-climatic variables at ungauged basins

Integrative information models for filling/reconstructing hydro-climatic time-series are required for a variety of practical applications. A GIS-based model for a rapid and reliable assessment of monthly time-series of several key hydro-climatic variables at the basin scale, is here developed as plug-in and applied to the entire region of Sicily (Italy). The plug-in, once the desired basin outlet section and time-window are selected, uses appropriate spatial techniques and algorithms to identify its drainage area and estimate the corresponding mean areal rainfall and temperatures time-series. A recent regional regressive rainfall-runoff model is successively applied for the assessment of the runoff time-series. Finally, a consolidated temperature-based method is applied to estimate monthly potential evapotranspiration time-series, while, actual evapotranspiration and soil moisture storage time-series are derived through a classical water balance model. The tool, supported by a preliminarily developed database, includes automatic procedures for data retrieving and processing and a user friendly interface.     

TG 328B型机械天平的示值误差测量不确定度评定

本文主要介绍了TG328B型机械天平示值误差测量不确定度的评定和分析。     

交通工程施工管理和质量控制综述

在城市建筑过程中，交通工程的施工是城市建筑的重要组成部分。它不仅仅对城市市民的日常生活有着直接的关系，同时也对城市的市容有着影响，是一个城市管理水平的反应。     

Development and validation of a self-report measure of bus driver behaviour

There are likely to be individual differences in bus driver behaviour when adhering to strict schedules under time pressure. A reliable and valid assessment of these individual differences would be useful for bus companies keen to mitigate risk of crash involvement. This paper reports on three studies to develop and validate a self-report measure of bus driver behaviour. For study 1, two principal components analyses of a pilot questionnaire revealed six components describing bus driver behaviour and four bus driver coping components. In study 2, test–retest reliability of the components were tested in a sub-sample and found to be adequate. Further, the 10 components were used to predict bus crash involvement at three levels of culpability with consistently significant associations found for two components. For study 3, avoidance coping was consistently associated with celeration variables in a bus simulator, especially for a time-pressured drive.

Statement of Relevance:The instrument can be used by bus companies for driver stress and fatigue management training to identify at-risk bus driver behaviour. Training to reduce the tendency to engage in avoidance coping strategies, improve evaluative coping strategies and hazard monitoring when under stress may improve bus driver safety.