Odour emission ability (OEA) and its application in assessing odour removal efficiency

Odourous emissions from sewer networks and wastewater treatment plants (WWTPs) can significantly impact a local population. Sampling techniques such as wind tunnels and flux hood chambers are traditionally used to collect area source samples for subsequent quantification of odour emission rates using dilution olfactometry, however these methods are unsuitable for assessing liquid samples from point sources due to the large liquid volumes required. To overcome this limitation, a gas phase sample preparation method was developed for assessing the total Odour Emission Ability (OEA) from a liquid sample. The method was validated using two volatile organic sulphur compounds (VOSCs), dimethyl-trisulphide (DMTS) and bismethylthiomethane (BMTM) that are frequently detected from sewers and WWTPs and are relatively stable compared with common VOSCs like mercaptan or methyl mercaptan. The recovery rates of DMTS and BMTM were quantified by injecting a known volume of a standard liquid sample into Tedlar bags using a static injection and a dynamic injection methodology. It was confirmed that both dynamic and static injection methods at ambient condition achieved high recovery rates with no need to consider increasing evaporation by elevating the temperature. This method can also be used to assess odour removal effectiveness of liquids by comparing the OEA before and after the treatment tests. Two application examples were presented.     

3D model based tracking for omnidirectional vision: A new spherical approach

The current work addresses the problem of 3D model tracking in the context of monocular and stereo omnidirectional vision in order to estimate the camera pose. To this end, we track 3D objects modeled by line segments because the straight line feature is often used to model the environment. Indeed, we are interested in mobile robot navigation using omnidirectional vision in structured environments. In the case of omnidirectional vision, 3D straight lines are projected as conics in omnidirectional images. Under certain conditions, these conics may have singularities.In this paper, we present two contributions. We, first, propose a new spherical formulation of the pose estimation withdrawing singularities, using an object model composed of lines. The theoretical formulation and the validation on synthetic images thus show that the new formulation clearly outperforms the former image plane one. The second contribution is the extension of the spherical representation to the stereovision case. We consider in the paper a sensor which combines a camera and four mirrors. Results in various situations show the robustness to illumination changes and local mistracking. As a final result, the proposed new stereo spherical formulation allows us to localize online a robot indoor and outdoor whereas the classical formulation fails.     

Adaptive ROC-based ensembles of HMMs applied to anomaly detection

Hidden Markov models (HMMs) have been successfully applied in many intrusion detection applications, including anomaly detection from sequences of operating system calls. In practice, anomaly detection systems (ADSs) based on HMMs typically generate false alarms because they are designed using limited amount of representative training data. Since new data may become available over time, an important feature of an ADS is the ability to accommodate newly acquired data incrementally, after it has originally been trained and deployed for operations. In this paper, a system based on the receiver operating characteristic (ROC) is proposed to efficiently adapt ensembles of HMMs (EoHMMs) in response to new data, according to a learn-and-combine approach. When a new block of training data becomes available, a pool of base HMMs is generated from the data using a different number of HMM states and random initializations. The responses from the newly trained HMMs are then combined to those of the previously trained HMMs in ROC space using a novel incremental Boolean combination (incrBC) technique. Finally, specialized algorithms for model management allow to select a diversified EoHMM from the pool, and adapt Boolean fusion functions and thresholds for improved performance, while it prunes redundant base HMMs. The proposed system is capable of changing the desired operating point during operations, and this point can be adjusted to changes in prior probabilities and costs of errors. Computer simulations conducted on synthetic and real-world host-based intrusion detection data indicate that the proposed system can achieve a significantly higher level of performance than when parameters of a single best HMM are estimated, at each learning stage, using reference batch and incremental learning techniques. It also outperforms the learn-and-combine approaches using static fusion functions (e.g., majority voting). Over time, the proposed ensemble selection algorithms form compact EoHMMs, while maintaining or improving system accuracy. Pruning allows to limit the pool size from increasing indefinitely, thereby reducing the storage space for accommodating HMMs parameters without negatively affecting the overall EoHMM performance. Although applied for HMM-based ADSs, the proposed approach is general and can be employed for a wide range of classifiers and detection applications.     

Cell formation in group technology using constraint programming and Boolean satisfiability

Cell formation consists in organizing a plant as a set of cells, each of them containing machines that process similar types or families of parts. The idea is to minimize the part flow among cells in order to reduce costs and increase productivity. The literature presents different approaches devoted to solve this problem, which are mainly based on mathematical programming and on evolutionary computing. Mathematical programming can guarantee a global optimal solution, however at a higher computational cost than an evolutionary algorithm, which can assure a good enough optimum in a fixed amount of time. In this paper, we model and solve this problem by using state-of-the-art constraint programming (CP) techniques and Boolean satisfiability (SAT) technology. We present different experimental results that demonstrate the efficiency of the proposed optimization models. Indeed, CP and SAT implementations are able to reach the global optima in all tested instances and in competitive runtime.     

Quantification of condition indicator performance on a split torque gearbox

The requirement for higher energy density transmissions (lower weight) in helicopters has led to the development of the split torque gearbox (STG) to replace the traditional planetary gearbox by the drive train designer. This may pose a challenge for the current gear analysis methods used in health and usage monitoring systems (HUMS). Gear analysis uses time synchronous averages to separates in frequency gears that are physically close to a sensor. The effect of a large number of synchronous components (gears or bearing) in close proximity may significantly reduce the fault signal (reduce signal to noise ratio) and therefore reduce the effectiveness of current gear analysis algorithms. In this paper, quantification of condition indicator performance on a split torque gearbox is reported. The vibration signatures are processed through a number of gear analysis algorithms to quantify the gear fault performance. The performance metric is separability.     

Fracture Assessment of Carbon Fibre/Epoxy Reinforcing Rings through a Combination of Full-Scale Testing, Small-Scale Testing and Stress Modeling

Carbon fibre/epoxy rings are used as radial reinforcement for polymer bearing elements with nominal diameter 250 mm functioning under 150 MPa. Full-scale static and dynamic testing revealed no catastrophic failure for loading to 400 MPa, although there was circumferential splitting of carbon fibres at the machined top edge causing counterface wear under sliding. A combined numerical–experimental analysis was applied for design improvement with a representative small-scale qualification test on the real ring geometry, inducing additional stress concentrations compared to ASTM standards. Full-scale modelling revealed high radial–axial shear stresses (33 MPa) in non-hydrostatically loaded zones, while it increased towards 104 MPa under hydrostatic load conditions. The former is the most critical and should be simulated either on a small-scale unidirectional compression test or on a representative short beam shear test, respectively, measuring the radial–axial or radial–tangential shear strength. A relation between both small-scale states of stress was experimentally and numerically studied, experiencing that the composite ring has lower radial–tangential shear stress compared to radial–axial shear stress as a different hydrostatic stress state is observed in the bulk of the composite ring. As a compressive test is however more difficult to perform than a short-beam-shear test, a representative design criterion for shear fracture is determined from failure at 27 kN normal load in a short-beam-shear test. Finally, fracture is avoided by optimising the cross-sectional geometry of the composite reinforcing ring and close control of the processing parameters.     

NdAlO3掺杂对Ba4.2Nd9.2Ti18O54陶瓷微波介电性能的影响

研究了NdAlO3掺杂对Ba4.2Nd9.2Ti18O54(简称BNT)陶瓷材料微观结构及其微波介电性能的影响.采用XRD和场发射扫描电子显微镜分析了掺NdAlO3后的BNT陶瓷材料的微观结构.结果表明,掺入的NdAlO3与Ba4.2Nd9.2Ti18O54形成了固溶体.随着NdAlO3掺入量的增加,材料的介电常数和谐振频率温度系数逐渐减小,Q×f值先增大后减小.当NdAlO3的掺入量为10wt%时,材料的Q×f值达到最大(11400GHz),谐振频率温度系数接近为零(-0.7ppm/℃),此时材料的相对介电常数为66.29(3.5GHz).     

Risk Management and Design of Critical Bridges for Terrorist Attacks

In the aftermath of the September 11th tragedies, the vulnerability of the United States' transportation infrastructure to terrorist attack has gained national attention. In light of this vulnerability, various governmental agencies are looking into ways to improve the design of structures to better withstand extreme loadings. Until recently, little attention has been given to bridges which are critical to our economy and transportation network. This paper summarizes the results of ongoing research to investigate economical, unobtrusive, and effective methods to mitigate the risk of terrorist attacks against critical bridges. It outlines a recommended plan to reduce these threats through proven risk management techniques, lists possible cost-effective security measures, discusses blast effects on bridges, and provides structural design and retrofit guidelines. It also discusses ongoing research oriented towards the development of a performance-based design methodology. In using proper risk management techniques, transportation managers and bridge engineers can mitigate the risk of terrorist attacks against critical bridges to an acceptable level, while ensuring efficient use of limited resources.