Predicting real-time roadside CO and NO2 concentrations using neural networks

The main aim of this paper is to develop a model based on neural network (NN) theory to estimate real-time roadside CO and $hbox{NO}_{2}$ concentrations using traffic and meteorological condition data. The location of the study site is at a road intersection in Melton Mowbray, which is a town in Leicestershire, U.K. Several NNs, which can be classified into three types, namely, the multilayer perceptron, the radial basis function, and the modular network, were developed to model the nonlinear relationships that exist in the pollutant concentrations. Their performances are analyzed and compared. The transferability of the developed models is studied using data collected from a road intersection in another city. It was concluded that all NNs provide reliable estimates of pollutant concentrations using limited information and noisy data

Predicting real-time roadside CO and NO2 concentrations using neural networks

The main aim of this paper is to develop a model based on neural network (NN) theory to estimate real-time roadside CO and $hbox{NO}_{2}$ concentrations using traffic and meteorological condition data. The location of the study site is at a road intersection in Melton Mowbray, which is a town in Leicestershire, U.K. Several NNs, which can be classified into three types, namely, the multilayer perceptron, the radial basis function, and the modular network, were developed to model the nonlinear relationships that exist in the pollutant concentrations. Their performances are analyzed and compared. The transferability of the developed models is studied using data collected from a road intersection in another city. It was concluded that all NNs provide reliable estimates of pollutant concentrations using limited information and noisy data

Reducing Urban Pollution Exposure from Road Transport(RUPERT)

This paper presents the preliminary results of a two-year study on reducing urban pollution exposure from road transport (RUPERT). The main aim of this project is to develop a new modelling framework for nitrogen dioxide, carbon monoxide and particulate matter to simulate exposures of different population groups across a city, and to assess the impact of roadside concentrations on these exposures. This will be achieved by modelling the frequency distribution of personal exposures (PEFDs) as a function of urban background and roadside concentrations, under different traffic conditions. The modelling approach combines new and existing models relating traffic and air pollution data, with particular emphasis of the impact of congestion, and the probabilistic modelling framework of personal exposure. Modelling of roadside concentrations consists of two main elements, namely the analysis of concentrations patterns at different roadside sites and of the relationship between traffic conditions and added roadside pollution. Roadside concentrations are predicted using empirically derived relationships; statistical models, novel statistics and artificial neural networks namely feed forward neural network and radial basis neural network. The exposure modelling is carried out by linking two models: the INDAIR model, which is designed to simulate probabilistically diurnal profiles of air pollutant concentrations in a range of microenvironments, and the EXPAIR model, which is designed to simulate population exposure patterns based on population time-activity patterns and a library of micro-environmental concentrations derived from the INDAIR model

Use of hydraulic rating to set environmental flows in the Zhangxi River, China

Ningbo city, China, is a rapidly growing residential and industrial centre, with a current population of 4 million. Its development has required a major water supply expansion programme providing 400,000 m3 of water per day from the upper reaches of the Zhangxi River by means of a cascade of reservoirs. Water resources management is achieved through operation of two major reservoirs, Jiaokou (75 million m3) and Zhougongzhai (93 million m3). Water is released from the reservoirs, via turbines (generating hydropower), for local industry, irrigated agriculture and public supply along the lower reaches of the River and to maintain the river ecosystem. Surveys of local residents along the Zhangxi River showed its important role in aspects of life, social activity, culture and leisure. Analysis of ecological monitoring data demonstrated the diverse nature of fish, plants and invertebrates within the river. Some elements of the ecosystem have a high local economic value to local people. This paper reports an assessment of the environmental flow needed to support key species in the river ecosystem. It employs hydraulic ratings to define sections of the river where flow velocity reaches 0.5 ms-1, required to stimulate spawning of the moonlight fish, an economically important and indicator species in the river. In two out of 6 cross-sections studied, flow releases from the reservoirs meet the needs of fish. The reservoirs reduce flood flows, which may lead to a loss of deep pools that are essential for the fish to survive during winter month

Collective dynamics in phospholipid bilayers investigated by inelastic neutron scattering: Exploring the dynamics of biological membranes with neutrons

We present the first inelastic neutron scattering study of the short wavelength dynamics in a phospholipid bilayer. We show that inelastic neutron scattering using a triple-axis spectrometer at the high flux reactor of the ILL yields the necessary resolution and signal to determine the dynamics of model membranes. The results can quantitatively be compared to recent Molecular Dynamics simulations. Reflectivity, in-plane correlations and the corresponding dynamics can be measured simultaneously to gain a maximum amount of information. With this method, dispersion relations can be measured with a high energy resolution. Structure and dynamics in phospholipid bilayers, and the relation between them, can be studied on a molecular length scale

Electrical and ultraviolet characterization of 4H-SiC Schottky photodiodes

Fabrication and electrical and optical characterization of 4H-SiC Schottky UV photodetectors with nickel silicide interdigitated contacts is reported. Dark capacitance and current measurements as a function of applied voltage over the temperature range 20 °C – 120 °C are presented. The results show consistent performance among devices. Their leakage current density, at the highest investigated temperature (120 °C), is in the range of nA/cm2 at high internal electric field. Properties such as barrier height and ideality factor are also computed as a function of temperature. The responsivities of the diodes as functions of applied voltage were measured using a UV spectrophotometer in the wavelength range 200 nm - 380 nm and compared with theoretically calculated values. The devices had a mean peak responsivity of 0.093 A/W at 270 nm and −15 V reverse bias

Control of a Movable Robot Head Using Vision-Based Object Tracking

This paper presents a visual tracking system to support the movement of the robot head for detecting the existence of objects. Object identification and object position estimation were conducted using image-based processing. The movement of the robot head was in four directions namely  to the right, left, top, and bottom of the robot head. Based on the distance of the object, it shifted the object to many points to assess the accuracy of the process of tracking the object. The targeted objects are detected through several processes, namely normalization of RGB images, thresholding, and object marking. The process of tracking the object conducted by the robot head varied in 40 various object points with high accuracy. The further the object’s distance to the robot, the smaller the corner of the movement of the robot produced compared to the movement of the robot head to track an object that was closer even though with the same distance stimulant shift object. However, for the distance and the shift of the same object, the level of accuracy showed almost the same results. The results showed the movement of the robot head to track the object under the head of the robot produced the movement with a larger angular error compared to the movement of the robot head in another direction even though with the stimulant distance of the same object position and the distance shift of the same object

Minimal Z' models: present bounds and early LHC reach

We consider `minimal' Z' models, whose phenomenology is controlled by only three parameters beyond the Standard Model ones: the Z' mass and two effective coupling constants. They encompass many popular models motivated by grand unification, as well as many arising in other theoretical contexts. This parameterization takes also into account both mass and kinetic mixing effects, which we show to be sizable in some cases. After discussing the interplay between the bounds from electroweak precision tests and recent direct searches at the Tevatron, we extend our analysis to estimate the early LHC discovery potential. We consider a center-of-mass energy from 7 towards 10 TeV and an integrated luminosity from 50 to several hundred pb^-1, taking all existing bounds into account. We find that the LHC will start exploring virgin land in parameter space for M_Z' around 700 GeV, with lower masses still excluded by the Tevatron and higher masses still excluded by electroweak precision tests. Increasing the energy up to 10 TeV, the LHC will start probing a wider range of Z' masses and couplings, although several hundred pb^-1 will be needed to explore the regions of couplings favored by grand unification and to overcome the Tevatron bounds in the mass region around 250 GeV.Comment: 25 pages. v2: small improvements and minor corrections, version accepted for publication on JHE

A New and Elementary CP^n Dyonic Magnon

We show that the dressing transformation method produces a new type of dyonic CP^n magnon in terms of which all the other known solutions are either composites or arise as special limits. In particular, this includes the embedding of Dorey's dyonic magnon via an RP^3 subspace of CP^n. We also show how to generate Dorey's dyonic magnon directly in the S^n sigma model via the dressing method without resorting to the isomorphism with the SU(2) principle chiral model when n=3. The new dyon is shown to be either a charged dyon or topological kink of the related symmetric-space sine-Gordon theories associated to CP^n and in this sense is a direct generalization of the soliton of the complex sine-Gordon theory.Comment: 21 pages, JHEP3, typos correcte