Next generation Bridge weigh-in-motion using fibre optic sensors

There have been over 3000 bridge weigh-in-motion (B-WIM) installations in 25 countries worldwide, this has led vast improvements in post processing of B-WIM systems since its introduction in the 1970’s. Existing systems are based on electrical resistance strain gauges which can be prohibitive in achieving data for long term monitoring of rural bridges due to power consumption. This paper introduces a new low-power B-WIM system using fibre optic sensors (FOS). The system consisted of a series of FOS which were attached to the soffit of an existing integral bridge with a single span of 19m. The site selection criteria and full installation process has been detailed in the paper. A method of calibration was adopted using live traffic at the bridge site and based on this calibration the accuracy of the system was determined. New methods of axle detection for B-WIM were investigated and verified in the field.

PatchCity: Procedural City Generation using Texture Synthesis

PatchCity is a new approach to the procedural generation of city models. The algorithm uses texture synthesis to create a city layout in the visual style of one or more input examples. Data is provided in vector graphic form from either real or synthetic city definitions. The paper describes the PatchCity algorithm, illustrates its use, and identifies its strengths and limitations. The technique provides a greater range of features and styles of city layout than existing generative methods, thereby achieving results that are more realistic. An open source implementation of the algorithm is available.

Cross-layer Framework for Fine-grained Channel Access in Next Generation High-density WiFi Networks

Densely deployed WiFi networks will play a crucial role in providing the capacity for next generation mobile internet. However, due to increasing interference, overlapped channels in WiFi networks and throughput efficiency degradation, densely deployed WiFi networks is not a guarantee to obtain higher throughput. An emergent challenge is how to efficiently utilize scarce spectrum resources, by matching physical layer resources to traffic demand. In this aspect, access control allocation strategies play a pivotal role but remain too coarse-grained. As a solution, this research proposes a flexible framework for fine-grained channel width adaptation and multi-channel access in WiFi networks. This approach, named SFCA (Sub-carrier Fine-grained Channel Access), adopts DOFDM (Discontinuous Orthogonal Frequency Division Multiplexing) at the PHY layer. It allocates the frequency resource with a sub-carrier granularity, which facilitates the channel width adaptation for multi-channel access and thus brings more flexibility and higher frequency efficiency. The MAC layer uses a frequency-time domain backoff scheme, which combines the popular time-domain BEB scheme with a frequency-domain backoff to decrease access collision, resulting in higher access probability for the contending nodes. SFCA is compared with FICA (an established access scheme) showing significant outperformance. Finally we present results for next generation 802.11ac WiFi networks.

Realistic Traffic Scenarios Using a Census Methodology: Vila Real Case Study

This paper presents the first phase of the redevelopment of the Electric Vehicle Scenario Simulator (EVeSSi) tool. A new methodology to generate traffic demand scenarios for the Simulation of Urban MObility (SUMO) tool for urban traffic simulation is described. This methodology is based on a Portugal census database to generate a synthetic population for a given area under study. A realistic case study of a Portuguese city, Vila Real, is assessed. For this area the road network was created along with a synthetic population and public transport. The traffic results were obtained and an electric buses fleet was evaluated assuming that the actual fleet would be replaced in a near future. The energy requirements to charge the electric fleet overnight were estimated in order to evaluate the impacts that it would cause in the local electricity network.

Phase resetting as a mechanism of ERP generation: evidence from the power spectrum

A Neural Mass model is coupled with a novel method to generate realistic Phase reset ERPs. The power spectra of these synthetic ERPs are compared with the spectra of real ERPs and synthetic ERPs generated via the Additive model. Real ERP spectra show similarities with synthetic Phase reset ERPs and synthetic Additive ERPs.

Conceptualisation of an application of adaptive synthetic socioeconomic agents for intelligent network control

The deployment of Quality of Service (QoS) techniques involves careful analysis of area including: those business requirements; corporate strategy; and technical implementation process, which can lead to conflict or contradiction between those goals of various user groups involved in that policy definition. In addition long-term change management provides a challenge as these implementations typically require a high-skill set and experience level, which expose organisations to effects such as “hyperthymestria” [1] and “The Seven Sins of Memory”, defined by Schacter and discussed further within this paper. It is proposed that, given the information embedded within the packets of IP traffic, an opportunity exists to augment the traffic management with a machine-learning agent-based mechanism. This paper describes the process by which current policies are defined and that research required to support the development of an application which enables adaptive intelligent Quality of Service controls to augment or replace those policy-based mechanisms currently in use.

3D digital elevation model generation

This chapter presents techniques used for the generation of 3D digital elevation models (DEMs) from remotely sensed data. Three methods are explored and discussed—optical stereoscopic imagery, Interferometric Synthetic Aperture Radar (InSAR), and LIght Detection and Ranging (LIDAR). For each approach, the state-of-the-art presented in the literature is reviewed. Techniques involved in DEM generation are presented with accuracy evaluation. Results of DEMs reconstructed from remotely sensed data are illustrated. While the processes of DEM generation from satellite stereoscopic imagery represents a good example of passive, multi-view imaging technology, discussed in Chap. 2 of this book, InSAR and LIDAR use different principles to acquire 3D information. With regard to InSAR and LIDAR, detailed discussions are conducted in order to convey the fundamentals of both technologies.

Multi-level planning for semi-autonomous vehicles in traffic scenarios based on separation maximization

The planning of semi-autonomous vehicles in traffic scenarios is a relatively new problem that contributes towards the goal of making road travel by vehicles free of human drivers. An algorithm needs to ensure optimal real time planning of multiple vehicles (moving in either direction along a road), in the presence of a complex obstacle network. Unlike other approaches, here we assume that speed lanes are not present and that different lanes do not need to be maintained for inbound and outbound traffic. Our basic hypothesis is to carry forward the planning task to ensure that a sufficient distance is maintained by each vehicle from all other vehicles, obstacles and road boundaries. We present here a 4-layer planning algorithm that consists of road selection (for selecting the individual roads of traversal to reach the goal), pathway selection (a strategy to avoid and/or overtake obstacles, road diversions and other blockages), pathway distribution (to select the position of a vehicle at every instance of time in a pathway), and trajectory generation (for generating a curve, smooth enough, to allow for the maximum possible speed). Cooperation between vehicles is handled separately at the different levels, the aim being to maximize the separation between vehicles. Simulated results exhibit behaviours of smooth, efficient and safe driving of vehicles in multiple scenarios; along with typical vehicle behaviours including following and overtaking.

Characterization of proteinases from the midgut of Rhipicephalus (Boophilus) microplus involved in the generation of antimicrobial peptides

Background: Hemoglobin is a rich source of biologically active peptides, some of which are potent antimicrobials (hemocidins). A few hemocidins have been purified from the midgut contents of ticks. Nonetheless, how antimicrobials are generated in the tick midgut and their role in immunity is still poorly understood. Here we report, for the first time, the contribution of two midgut proteinases to the generation of hemocidins. Results: An aspartic proteinase, designated BmAP, was isolated from the midgut of Rhipicephalus (Boophilus) microplus using three chromatographic steps. Reverse transcription-quantitative polymerase chain reaction revealed that BmAP is restricted to the midgut. The other enzyme is a previously characterized midgut cathepsin L-like cysteine proteinase designated BmCL1. Substrate specificities of native BmAP and recombinant BmCL1 were mapped using a synthetic combinatorial peptide library and bovine hemoglobin. BmCL1 preferred substrates containing non-polar residues at P2 subsite and polar residues at P1, whereas BmAP hydrolysed substrates containing non-polar amino acids at P1 and P1`. Conclusions: BmAP and BmCL1 generate hemocidins from hemoglobin alpha and beta chains in vitro. We postulate that hemocidins may be important for the control of tick pathogens and midgut flora.

In situ generation of n-butanethiol and its reaction with electron-deficient olefines

n-Butanethiol is generated in situ by sequential addition of n-butyllithium and water to elemental sulfur. The n-butanethiol formed was reacted with electron-deficient olefines to give Michael-type addition products in good yields. The method avoids the manipulation of the bad-smelling n-butanethiol.

Analysis of EnterpriseVoIP Traffic from aWire line IMS System

With the rapid development of telecommunication industry, the IP multimedia Subsystem (IMS) could very well be the panacea for most telecom operators. It is originally defined as the core network for 3G mobile systems by the 3rd Generation Partnership Project (3GPP), the more recent development is merging between fixed line network and wireless networkd This report researchs the characteristic of the IMS data and proposes an IMS characterization analysis. We captured the IMS traffic data with 10 tousands users for about 41 hours. By analyzing the characteristics of the IMS, we know that the most important application in the IMS is VoIP call. Then we use the tool designed by Tsinghua University & Ericsson Company to recognize the data, and the results we got can be used to build the traffic models. From the results of the traffic models, I will get some reasons and conclusion. The traffic model gives out the types of session and types of VoIP call. I bring into a concept—busy hour. This concept is very important because it can help us to know which period is the peak of the VoIP call. The busy hour is from 10:00 to 11:00 in the morning. I also bring into another concept—connection ratio. This concept is significant because it can evaluate whether the VoIP call is good when it use IMS network. By comparing the traffic model with other one’s models, we found the different results from them, both the accuracy and the busy hour. From the contract, we got the advantages of our traffic models.

A simulation model for video traffic performance via ATM over TCP/IP

Although TCP has emerged as the standard in data communication, the introduction of ATM technology has raised numerous problems regarding the effectiveness of using TCP over A TM networks, especially when video traffic performance is considered. This paper presents a simulation model for transmission performance of video traffic via ATM over TCP/IP. The interactivity between TCP/IP and ATM, generation of MPEG traffic and evaluation of traffic performance are implemented in the model. The design and implementation details of the model are carefully described. The experiments conducted using the model and experimental results are briefly introduced, revealing the capability of our model in simulating network events and in evaluating potential solutions to performance issues.

Synthetic evaluation method for bridge priority ranking

In order to maintain the transportation operation, proper monitoring systems should be established on road structures, especially bridges. Since these systems need enormous investments, only a part of bridges should be equipped. Thus, the priorities of the bridges should be ranked. In this paper, a method based on two-level synthetic evaluation is proposed. First, the importance of each bridge is analyzed through the economic analysis. Six factors are considered for the bridges in a network, including construction cost, service duration, length, location importance coefficient, traffic volume, and reconstruction time. Second, the safety condition of the bridge is evaluated by using improved entropy method (IEM) which combines subjective weight with objective entropy weight. Five indices are incorporated in this step, i.e., design and construction condition, technical condition, level of overloading, hazard of wind and earthquake and environmental factors. Finally, the priorities of all the bridge in one network can be ranked and classified through a judge matrix. To demonstrate the effectiveness of the proposed method, a main highway including 16 bridges is taken as an illustrative example. The results show that the bridges can be ranked and classified quickly by using the proposed method.