Optimization of an RFID location identification scheme based on the neural network

An indoor localization technology is increasingly critical as location‐aware applications evolve. Researchers have proposed several indoor localization technologies. Because most of the proposed indoor localization technologies simply involve using the received signal strength indicator value of radio‐frequency identification (RFID) for indoor localization, radio‐frequency interference, and environmental factors often limit the accuracy of localization results. Therefore, this study proposes an accurate RFID localization based on the neural network (ARL‐N²), a passive RFID indoor localization scheme for identifying tag positions in a room, combining a location identification based on dynamic active RFID calibration algorithm with a backpropagation neural network (BPN). The proposed scheme composed of two phases: in the training phase, an appropriate BPN architecture is constructed using the training data derived from the coordinates of reference tags and the coordinates obtained using the localization algorithm. By contrast, the online phase involves calculating the tracking tag coordinates and using these values as BPN inputs, thereby enhancing the estimated location. A performance evaluation of the ARL‐N² schemes confirms its high localization accuracy. The proposed method can be used to locate critical objects in difficult‐to‐find areas by creating minimal errors and applying and economical technique. Copyright © 2013 John Wiley & Sons, Ltd.     

A Genetic Algorithm Approach for Optimizing Traffic Control Signals Considering Routing

Abstract:   It is well known that coordinated, area-wide traffic signal control provides great potential for improvements in delays, safety, and environmental measures. However, an aspect of this problem that is commonly neglected in practice is the potentially confounding effect of drivers re-routing in response to changes in travel times on competing routes, brought about by the changes to the signal timings. This article considers the problem of optimizing signal green and cycle timings over an urban network, in such a way that the optimization anticipates the impact on traffic routing patterns. This is achieved by including a network equilibrium model as a constraint to the optimization. A Genetic Algorithm (GA) is devised for solving the resulting problem, using total travel time across the network as an illustrative fitness function, and with a widely used traffic simulation-assignment model providing the equilibrium flows. The procedure is applied to a case study of the city of Chester in the UK, and the performance of the algorithms is analyzed with respect to the parameters of the GA method. The results show a better performance of the signal timing as optimized by the GA method as compared to a method that does not consider rerouting. This improvement is found to be more significant with a more congested network whereas under a relatively mild congestion situation the improvement is not very clear.     

Partial extraction method for the rapid analysis of total lipids and γ-oryzanol contents in rice bran

Total lipids and γ-oryzanol in rice bran were determined by a partial extraction method. The results agreed well with the conventional total extraction methods. The proposed method uses fewer hazardous organic solvents, takes a shorter extraction time and requires no special extraction apparatus. Total lipids and γ-oryzanol in nine rice bran varieties were analysed by the developed technique. Daw Dum 5647 had the highest total lipids and γ-oryzanol while the lowest content was found in KD XBT 313-19-1-1 and SP XBT 43-7, respectively. The adsorption coefficient (K_d) of the lipids and γ-oryzanol, between hexane and bran, at 30 °C are between 1.16 and 2.00 and 2.02 and 2.65, respectively (depending on the moisture content of the bran). From the K_d values, it was estimated that about 92–95% of the lipids and 95–96% of the γ-oryzanol were extracted into hexane at a 10:1 (v/w) ratio of hexane to bran. The effect of solvents on the extraction of γ-oryzanol from rice bran was also studied. It was found that isopropanol was the most suitable solvent for extraction and determination of γ-oryzanol in rice bran. It showed better agreement with the total extraction method.     

Immobilization of malarial (Plasmodium falciparum) dihydrofolate reductase for the selection of tight-binding inhibitors from combinatorial library

A simple procedure for selection of tight-binding inhibitors of mutant dihydrofolate reductases from Plasmodium falciparum (PfDHFRs) based on preferential binding to the enzyme immobilized on a Sepharose column has been described. PfDHFRs with a cysteine residue at the C-terminal have been prepared in order to immobilize to a thiopropyl-Sepharose gel via S-S linkage. The amount of immobilized DHFRs was estimated to be 4-5 mg/g of dried gel, and the activities of bound DHFRs were comparable to that of free enzymes. The prepared immobilized enzyme has been used for the selection of tight-binding inhibitors from combinatorial libraries, based on the affinities of each ligand with the enzyme. Free ligands were then identified and analyzed quantitatively by high-performance liquid chromatography-mass spectrometry, and the components with high binding affinity of the library could thus be realized. Results could be confirmed by quantitative analysis of the bound ligands released from the enzyme by guanidine hydrochloride treatment.     

Design of Sustainable Cordon Toll Pricing Schemes in a Monocentric City

This paper addresses the design issue of sustainable cordon toll pricing schemes in a monocentric city. An analytical model that maximizes the total social welfare of urban system is first proposed for simultaneous optimization of the cordon toll location and charge level. The solution properties of the model with/without considering traffic congestion and/or environmental effects are explored and compared analytically. The proposed model is then extended to explicitly incorporate the effects of subsidizing the retrofit of old vehicles on reduction in average vehicle emissions. The optimal subsidy scheme for maximizing the social welfare of the system is also determined. Finally, a numerical example is given to illustrate the model applications. Insightful findings are reported on the interrelationships among cordon toll scheme, traffic congestion and environmental effects, urban population distribution, and subsidy scheme as well as their implications in practice.     

A Cell‐Based Model for Multi‐class Doubly Stochastic Dynamic Traffic Assignment

Abstract: This article proposes a cell‐based multi‐class dynamic traffic assignment problem that considers the random evolution of traffic states. Travelers are assumed to select routes based on perceived effective travel time, where effective travel time is the sum of mean travel time and safety margin. The proposed problem is formulated as a fixed point problem, which includes a Monte–Carlo‐based stochastic cell transmission model to capture the effect of physical queues and the random evolution of traffic states during flow propagation. The fixed point problem is solved by the self‐regulated averaging method. The results illustrate the properties of the problem and the effectiveness of the solution method. The key findings include the following: (1) Reducing perception errors on traffic conditions may not be able to reduce the uncertainty of estimating system performance, (2) Using the self‐regulated averaging method can give a much faster rate of convergence in most test cases compared with using the method of successive averages, (3) The combination of the values of the step size parameters highly affects the speed of convergence, (4) A higher demand, a better information quality, or a higher degree of the risk aversion of drivers can lead to a higher computation time, (5) More driver classes do not necessarily result in a longer computation time, and (6) Computation time can be significantly reduced by using small sample sizes in the early stage of solution processes.     

Finding Reliable Shortest Paths in Road Networks Under Uncertainty

The aim of this study is to investigate the solution algorithm for solving the problem of determining reliable shortest paths in road networks with stochastic travel times. The availability of reliable shortest paths enables travelers, in the face of travel time uncertainty, to plan their trips with a pre-specified on-time arrival probability. In this study, the reliable shortest path between origin and destination nodes is determined using a multiple-criteria shortest path approach when link travel times follow normal distributions. The dominance conditions involved in such problems are established, thereby reducing the number of generated non-dominated paths during the search processes. Two solution algorithms, multi-criteria label-setting and A* algorithms, are proposed and their complexities analyzed. Computational results using large scale networks are presented. Numerical examples using data from a real-world advanced traveller information system is also given to illustrate the applicability of the solution algorithms in practice.     

The use of natural rubber latex as a renewable and sustainable modifier of asphalt binder

Natural rubber (NR) powder as a bio-modifier of asphalt binder has been shown to have some beneficial effects. However, there is limited research into the use of the liquid form of NR, i.e. concentrated NR latex, as an asphalt binder modifier. Compared to NR powder, NR latex is cheaper and more accessible in some countries, and potentially creates viscosity-reducing foams in the modified binder during mixture production. In this research, asphalt binders modified with different amount of NR latex were systematically studied, including the rotational viscosities, rutting resistance, fatigue resistance, low-temperature behaviour and temperature sensitivity. The dispersion of the NR latex in the modified binders was examined using fluorescence microscope and atomic force microscope. Test results indicate that the addition of NR latex increases the viscosity and elastic recovery of the modified binders and potentially enhances asphalt pavements’ resistance to rutting, thermal cracking and fatigue damage. The NR latex also reduces the temperature sensitivity of the modified binders. The optimum NR latex content was found to be 7% of the total mass of the modified binder. A network of extensive microstructures mixed with bubbles was identified in the modified binders under heat. As a renewable and sustainable material, NR latex has the potential to be used as an effective asphalt modifier.