Development of planning level transportation safety tools using Geographically Weighted Poisson Regression

A common technique used for the calibration of collision prediction models is the Generalized Linear Modeling (GLM) procedure with the assumption of Negative Binomial or Poisson error distribution. In this technique, fixed coefficients that represent the average relationship between the dependent variable and each explanatory variable are estimated. However, the stationary relationship assumed may hide some important spatial factors of the number of collisions at a particular traffic analysis zone. Consequently, the accuracy of such models for explaining the relationship between the dependent variable and the explanatory variables may be suspected since collision frequency is likely influenced by many spatially defined factors such as land use, demographic characteristics, and traffic volume patterns. The primary objective of this study is to investigate the spatial variations in the relationship between the number of zonal collisions and potential transportation planning predictors, using the Geographically Weighted Poisson Regression modeling technique. The secondary objective is to build on knowledge comparing the accuracy of Geographically Weighted Poisson Regression models to that of Generalized Linear Models. The results show that the Geographically Weighted Poisson Regression models are useful for capturing spatially dependent relationships and generally perform better than the conventional Generalized Linear Models.     

A semantic approach to a framework for business domain software systems

In enterprise firms, enormous amounts of electronic documents are generated by business analysts and other business domain application users. Applications that use these documents are often driven by business logic that is hard-coded together with application logic. One approach to the separation of business logic from applications is to create and maintain business and information extraction rules in an external, user-friendly format. The drawback of such an externalization is that the business rules, usually, do not have machine interpretable semantics. This situation often leads to misinterpretation of domain analysis documents, which can inhibit the productivity of computer-assisted analytical work and the effectiveness of business solutions. This paper proposes an ontology and rule-based framework for the development of business domain applications, which includes semantic processing of externalized business rules and to some extent externalization of application logic. The creation of external information extraction rules by the business analyst is a cumbersome and time consuming task. In order to overcome this problem, the framework also includes a rule learning system to semi-automate the generation of information extraction rules from source documents with the help of manual annotations. The main idea behind the work presented in this paper is to re-engineer very large enterprise information systems to adapt to Semantic Web computing techniques. The work presented in this paper is inspired by an industrial project.     

Dynamic Matrix Control of a Bubble‐Column Reactor for Microbial Synthesis Gas Fermentation

A spatiotemporal metabolic model of a representative syngas bubble‐column reactor was applied to design and evaluate dynamic matrix control (DMC) schemes for regulation of the desired by‐product ethanol and the undesired by‐product acetate. This model was used to develop linear step response models for controller design and also served as the process in closed‐loop simulations. A 2 × 2 DMC scheme with manipulation of the liquid and gas feed flows to the column provided a superior performance to proportional integral (PI) control due to slow process dynamics combining the multivariable and constrained nature of the control problem. Ethanol concentration control for large disturbances was further improved by adding the flow of a pure hydrogen stream as a third manipulated variable. The advantages of DMC for syngas bubble‐column reactor control are demonstrated and a design strategy for future industrial applications is provided.     

A heuristic to manage perishable inventory with batch ordering,positive lead-times,and time-varying demand

So far the literature on inventory control for perishable products has mainly focused on (near-) optimal replenishment policies for a stylized environment, assuming no lead-time, no lot-sizing, stationary demand, a first in first out withdrawal policy and/or product life time equal to two periods. This literature has given fundamental insight in the behavior and the complexity of inventory systems for perishable products. In practice, many grocery retailers have recently automated the inventory replenishment for non-perishable products. They recognize they may need a different replenishment logic for perishable products, which takes into account e.g. the age of the inventory in the system. Due to new information technologies like RFID, it now also becomes more economically feasible to register this type of information. This paper suggests a replenishment policy for perishable products which takes into account the age of inventories and which requires only very simple calculations. It will be shown that in an environment, which contains important features of the real-life retail environment, this new policy leads to substantial cost reductions compared with a base policy that does not take into account the age of inventories.     

Considerations on nonlinear model predictive control techniques

The nonlinear model predictive control (NMPC) is an on-line application based on nonlinear convolution models. It is an appealing control methodology, but it is difficult to implement and its solution is not so performing since it unavoidably means to solve a usually large-scale, constrained, and multidimensional optimization. To increase the difficulty, this optimization problem is subject to computationally heavy differential and algebraic constraints constituting the same convolution model and the least squares nature of the objective function easily leads to narrow valleys and multimodality issues.Beyond a short review of the state-of-the-art, the paper is aimed at highlighting the possibility to exploit at best the intrinsic features of the specific system one is going to control using the NMPC. The idea is to give the NMPC the possibility to automatically select the best combination of algorithms (differential solvers and optimizers) in accordance with the specific problem to be solved. From this perspective, the NMPC could be easily extended to many scientific fields traditionally far from process systems and computer-aided process engineering and the user has not to worry about which specific differential solvers and optimizers are needed to solve his/her problem.     

On model design for simulation of collective intelligence

The study of collective intelligence (CI) systems is increasingly gaining interest in a variety of research and application domains. Those domains range from existing research areas such as computer networks and collective robotics to upcoming areas of agent-based and insect-based computing; also including applications on the internet and in games and movies. CI systems are complex by nature and (1) are effectively adaptive in uncertain and unknown environments, (2) can organise themselves autonomously, and (3) exhibit ‘emergent’ behaviour. Among others, multi-agent systems, complex adaptive systems, swarm intelligence and self-organising systems are considered to be such systems. The explosive wild growth of research studies of CI systems has not yet led to a systematic approach for model design of these kinds of systems. Although there have been recent efforts on the issue of system design (the complete design trajectory from identifying system requirements up to implementation), the problem of choosing and specifying a good model of a CI system is often done implicitly and sometimes even completely ignored. The aim of this article is to bring to the attention that model design is an essential as well as an integral part of system design. We present a constructive approach to systematically design, build and test models of CI systems. Because simulation is often used as a way to research CI systems, we particularly focus on models that can be used for simulation. Additionally, we show that it is not necessary to re-invent the wheel: here, we show how existing models and algorithms can be used for CI model design. The approach is illustrated by means of two example studies on a (semi-automated) multi-player game and collaborative robotics.     

Kinetic modeling of the peroxide cross-linking of polymers: From a theoretical model framework to its application for a complex polymer system

Peroxides react with polymers in a variety of ways. The fundamental comprehension and prediction of pertinent kinetics of reactions is consequently indispensable. Based on the mechanisms of reactions of cross-linking process, a new theoretical kinetic model framework was developed. The kinetic model was then applied to the reactions of cross-linking process of various peroxides and a chosen complex polymer compound, namely partially hydrogenated poly(acrylonitrile-co-1,3-butadiene). Whereas the initial macromolecular backbone structure was determined utilizing attached proton test carbon nuclear magnetic resonance, the evolution of overall concentration of cross-links was monitored through viscoelastic characteristics of the system. The model demonstrated good agreement with experimentally measured data and, moreover; the evolution of concentrations of various crucial species inherent to the cross-linking process were predicted. The most significant advantage of the developed kinetic model is that it may be readily applied to an assortment of polymer/peroxide systems.     

Prevention of fuel cell starvation by model predictive control of pressure,excess ratio,and current

Starvation of polymer electrolyte fuel cells (PEFC) takes place, especially during transients, if reactants are consumed in the fuel cell faster than they can be supplied. It is one of the main causes of aging and degeneration of fuel cells.     

交通系统仿真在城市规划交通影响评价中的应用前瞻

基于交通影响评价，对目前国内城市规划中存在的道路交通系统问题进行分析，剖析了目前城市规划中实施交通影响评价的意义。对交通系统仿真技术的概念和发展现状作了简单介绍，并就交通系统仿真技术在交通影响评价中的实际应用，以及交通影响评价和交通系统仿真的发展前景进行了预测。