功能菌强化应急处理苯胺突发污染事故研究

近年来各种环境污染事故频发，据统计仅2001~2003年间，发生的各类环境污染事故就高达5606次，其中水污染事故3235次，占全部的57.7%。这些事故不仅给人民生命财产造成巨大损失，也给生态环境造成严重的破坏。因此开发安全高效的应急处理技术迫在眉睫。本研究以筛选高效苯胺降解菌为基础，通过对高效菌降解性能的研究指导将高效菌作为功能郡主投加到已有生物处理系统强化应急处理苯胺突发污染事故废液，取得了良好的效果。 苯胺高效降解菌AN-P1为红球菌（Rhodococcus sp.），其通过间位途径降解苯胺，AN-P1利用苯胺生长和降解的最佳pH为6，最适浓度为2000 mg/L，最适温度为30 ℃，最佳接种量为0.3‰。AN-P1降解含500 mg/L、1000 mg/L、2000 mg/L苯胺的培养物分别经过28 h、24 h、32 h降解，出水苯胺含量能达到《污水综合排放标准》（GB8978-1996）一级标准。但由于苯胺降解过程中释放了大量氨氮，出水氨氮仍较高未能达标排放。而常规SBR系统应急处理效果较差，苯胺和COD去除率均低于10%，出水未能达标排放。活性碳吸附后的回收和后续处理也会带来操作不变和二次污染问题，且处理后出水往往难于达标排放，尚需进行进一步处理。 生物处理系统应急处理后恢复运行处理效果监测和PCR-DGGE图谱分析显示，用AN-P1菌强化应急处理系统后不仅能快速高效的去除苯胺，而且可以有效保障处理系统对污染物的净化性能，有效的保护系统中的功能微生物免受苯胺毒害。 研究结果表明，从实际处理效果、对原有生物系统性能保护及实际应用操作等多方面考虑，用AN-P1菌强化应急处理苯胺突发污染事故在技术上都是可行的。本研究为应急处理苯胺突然污染事故废液提供了新的方法。 Recent years, environment pollution accidents happened frequently, the data showed that there are 5606 accidents between 2001 and 2003, including 3235 water environment accidents, which is 57.7% of all. These accedents not only caused money lost and life lost but also caused serious damage to the ecologicl environment. So exploring highly-effective and secure methods to solve these accidents is an urgent mission. We screened a highly-effective aniline-degrading bacterium and did some researches on its ability to degrade aniline, in order to guide the emergency treatment of aniline containing wastewater that caused by sudden accident pollution with bioaugmentation. A highly-effective aniline-degrading bacterium AN-P1 was isolate and characterized as Rhodococcus sp. It degrades aniline through meta-cleavage pathway. The optimal pH and temperature for cell growth and aniline degradation were 6 and 30 ℃, respectively, and the opitimal concentration of aniline was 2000 mg/L, the optimal inoculation amount was 0.3‰.It took bacterium AN-P1 only 18 h, 24 h and 32 h, respectively, for the treatment of MSB containing 500 mg/L, 1000 mg/L, 2000 mg/L aniline to meet the first grade of national some of the NH4+-N which caused by aniline degradation. It took bacterium AN-P1 only 10 h, 20 h and 32 h, respectively, for the treatment of wastewater containing 500 mg/L, 1000 mg/L, 2000 mg/L aniline to meet the first grade of national integrated wastewater discharge standard. The bacterium AN-P1 can also remove some of the NH4+-N which caused by aniline degradation. It took bacterium AN-P1 only 10 h, 20 h and 32 h, respectively, for the treatment of wastewater containing 500 mg/L, 1000 mg/L, 2000 mg/L aniline to meet the first grade of national integrated wastewater discharge standard. By combing AN-P1 with regular SBR system, it took only 36 h for the emergency treatment of wastewater containing 2000 mg/L aniline under simulating engineering conditions to meet the discharge standard. While the NH4+-N of effluent can not meet the standard because of the high amount NH4+-N caused by aniline degradation. The regular SBR system was not good at aniline and COD removal. The removal efficiency of which are less than 10%. It cost 67.8 g activated carbon to absorbed 1000 mg aniline. It is inconvenient to transport and use it for the emergency treatment of aniline when the sudden pollution accident happened. Meanwhile, it was complex ad hard to recycle the activated carbon and treat the aniline wastewater get from activated carbon recycling too. Hard to meet the effluent standard was also a problem of activated carbon absorption method. According to the PCR-DGGE profile and removal efficiency of pollutants and COD when the systerm recover from emergency treatment, AN-P1 can efficiently protect the microbial community of regular activated sludge system against the aniline. It proved that combing AN-P1 with regular biological system is a feasible strategy for emergency treatment of aniline sudden pollution accident. The research offered a new way for emergency treatment of aniline sudden pollution accident.

Robust Learning Control for Manipulators with Uncertainty Disturbances Based on Internal Model

In this paper, a disturbance controller is designed for making robotic system behave as a decoupled linear system according to the concept of internal model. Based on the linear system, the paper presents an iterative learning control algorithm to robotic manipulators. A sufficient condition for convergence is provided. The selection of parameter values of the algorithm is simple and easy to meet the convergence condition. The simulation results demonstrate the effectiveness of the algorithm..

Mermera: Non-Coherent Distributed Shared Memory for Parallel Computing

The proliferation of inexpensive workstations and networks has prompted several researchers to use such distributed systems for parallel computing. Attempts have been made to offer a shared-memory programming model on such distributed memory computers. Most systems provide a shared-memory that is coherent in that all processes that use it agree on the order of all memory events. This dissertation explores the possibility of a significant improvement in the performance of some applications when they use non-coherent memory. First, a new formal model to describe existing non-coherent memories is developed. I use this model to prove that certain problems can be solved using asynchronous iterative algorithms on shared-memory in which the coherence constraints are substantially relaxed. In the course of the development of the model I discovered a new type of non-coherent behavior called Local Consistency. Second, a programming model, Mermera, is proposed. It provides programmers with a choice of hierarchically related non-coherent behaviors along with one coherent behavior. Thus, one can trade-off the ease of programming with coherent memory for improved performance with non-coherent memory. As an example, I present a program to solve a linear system of equations using an asynchronous iterative algorithm. This program uses all the behaviors offered by Mermera. Third, I describe the implementation of Mermera on a BBN Butterfly TC2000 and on a network of workstations. The performance of a version of the equation solving program that uses all the behaviors of Mermera is compared with that of a version that uses coherent behavior only. For a system of 1000 equations the former exhibits at least a 5-fold improvement in convergence time over the latter. The version using coherent behavior only does not benefit from employing more than one workstation to solve the problem while the program using non-coherent behavior continues to achieve improved performance as the number of workstations is increased from 1 to 6. This measurement corroborates our belief that non-coherent shared memory can be a performance boon for some applications.

Bridge-vehicle interaction for structural health monitoring: potentials, applications, and limitations

Structural Health Monitoring (SHM) is an integral part of infrastructure maintenance and management systems due to socio-economic, safety and security reasons. The behaviour of a structure under vibration depends on structure characteristics. The change of structure characteristics may suggest the change in system behaviour due to the presence of damage(s) within. Therefore the consistent, output signal guided, and system dependable markers would be convenient tool for the online monitoring, the maintenance, rehabilitation strategies, and optimized decision making policies as required by the engineers, owners, managers, and the users from both safety and serviceability aspects. SHM has a very significant advantage over traditional investigations where tangible and intangible costs of a very high degree are often incurred due to the disruption of service. Additionally, SHM through bridge-vehicle interaction opens up opportunities for continuous tracking of the condition of the structure. Research in this area is still in initial stage and is extremely promising. This PhD focuses on using bridge-vehicle interaction response for SHM of damaged or deteriorating bridges to monitor or assess them under operating conditions. In the present study, a number of damage detection markers have been investigated and proposed in order to identify the existence, location, and the extent of an open crack in the structure. The theoretical and experimental investigation has been conducted on Single Degree of Freedom linear system, simply supported beams. The novel Delay Vector Variance (DVV) methodology has been employed for characterization of structural behaviour by time-domain response analysis. Also, the analysis of responses of actual bridges using DVV method has been for the first time employed for this kind of investigation.

Discharge competence and pattern formation in peatlands: a meta-ecosystem model of the Everglades ridge-slough landscape.

Regular landscape patterning arises from spatially-dependent feedbacks, and can undergo catastrophic loss in response to changing landscape drivers. The central Everglades (Florida, USA) historically exhibited regular, linear, flow-parallel orientation of high-elevation sawgrass ridges and low-elevation sloughs that has degraded due to hydrologic modification. In this study, we use a meta-ecosystem approach to model a mechanism for the establishment, persistence, and loss of this landscape. The discharge competence (or self-organizing canal) hypothesis assumes non-linear relationships between peat accretion and water depth, and describes flow-dependent feedbacks of microtopography on water depth. Closed-form model solutions demonstrate that 1) this mechanism can produce spontaneous divergence of local elevation; 2) divergent and homogenous states can exhibit global bi-stability; and 3) feedbacks that produce divergence act anisotropically. Thus, discharge competence and non-linear peat accretion dynamics may explain the establishment, persistence, and loss of landscape pattern, even in the absence of other spatial feedbacks. Our model provides specific, testable predictions that may allow discrimination between the self-organizing canal hypotheses and competing explanations. The potential for global bi-stability suggested by our model suggests that hydrologic restoration may not re-initiate spontaneous pattern establishment, particularly where distinct soil elevation modes have been lost. As a result, we recommend that management efforts should prioritize maintenance of historic hydroperiods in areas of conserved pattern over restoration of hydrologic regimes in degraded regions. This study illustrates the value of simple meta-ecosystem models for investigation of spatial processes.

Signal restoration from band-pass filtered data

The restoration problem for a band-pass linear system is examined in the case the input signal is weighted by a profile function. The singular system is evaluated analytically for three different forms of the profile function. An example of restoration process is presented.

Wireless networked control systems with QoS-based sampling

Closing feedback loops using an IEEE 802.11b ad hoc wireless communication network incurs many challenges sensitivity to varying channel conditions and lower physical transmission rates tend to limit the bandwidth of the communication channel. Given that the bandwidth usage and control performance are linked, a method of adapting the sampling interval based on an 'a priori', static sampling policy has been proposed and, more significantly, assuring stability in the mean square sense using discrete-time Markov jump linear system theory. Practical issues including current limitations of the 802.11 b protocol, the sampling policy and stability are highlighted. Simulation results on a cart-mounted inverted pendulum show that closed-loop stability can be improved using sample rate adaptation and that the control design criteria can be met in the presence of channel errors and severe channel contention.

Improved conjugate gradient implementation for least squares support vector machines

As a promising method for pattern recognition and function estimation, least squares support vector machines (LS-SVM) express the training in terms of solving a linear system instead of a quadratic programming problem as for conventional support vector machines (SVM). In this paper, by using the information provided by the equality constraint, we transform the minimization problem with a single equality constraint in LS-SVM into an unconstrained minimization problem, then propose reduced formulations for LS-SVM. By introducing this transformation, the times of using conjugate gradient (CG) method, which is a greatly time-consuming step in obtaining the numerical solution, are reduced to one instead of two as proposed by Suykens et al. (1999). The comparison on computational speed of our method with the CG method proposed by Suykens et al. and the first order and second order SMO methods on several benchmark data sets shows a reduction of training time by up to 44%. (C) 2011 Elsevier B.V. All rights reserved.

Robust visual tracking based on online learning sparse representation

Handling appearance variations is a very challenging problem for visual tracking. Existing methods usually solve this problem by relying on an effective appearance model with two features: (1) being capable of discriminating the tracked target from its background, (2) being robust to the target's appearance variations during tracking. Instead of integrating the two requirements into the appearance model, in this paper, we propose a tracking method that deals with these problems separately based on sparse representation in a particle filter framework. Each target candidate defined by a particle is linearly represented by the target and background templates with an additive representation error. Discriminating the target from its background is achieved by activating the target templates or the background templates in the linear system in a competitive manner. The target's appearance variations are directly modeled as the representation error. An online algorithm is used to learn the basis functions that sparsely span the representation error. The linear system is solved via ℓ1 minimization. The candidate with the smallest reconstruction error using the target templates is selected as the tracking result. We test the proposed approach using four sequences with heavy occlusions, large pose variations, drastic illumination changes and low foreground-background contrast. The proposed approach shows excellent performance in comparison with two latest state-of-the-art trackers.

Structural damage diagnosis of steel truss bridges by outlier detection

This study discusses structural damage diagnosis of real steel truss bridges by measuring trafficinduced vibration of bridges and utilizing a damage indicator derived from linear system parameters of a time series model. On-site damage experiments were carried out on real steel truss bridges. Artificial damage was applied to the bridge by severing a truss member with a cutting machine.Vehicle-induced vibrations of the bridges before and after applying damagewere measured and used in structural damage diagnosis of the bridges. Changes in the damage indicator are detected by Mahalanobis-Taguchi system (MTS) which is one of multivariate outlier analyses. The damage indicator and outlier detection was successfully applied to detect anomalies in the steel truss bridges utilizing vehicle-induced vibrations. Observations through this study demonstrate feasibility of the proposed approach for real world applications.

A-level Mathematics Options – Views of Secondary-level Teachers

The A-level Mathematics qualification is based on a compulsory set of pure maths modules and a selection of applied maths modules with the pure maths representing two thirds of the assessment. The applied maths section includes mechanics, statistics and (sometimes) decision maths. A combination of mechanics and statistics tends to be the most popular choice by far. The current study aims to understand how maths teachers in secondary education make decisions regarding the curriculum options and offers useful insight to those currently designing the new A-level specifications.

Semi-structured interviews were conducted with A-level maths teachers representing 27 grammar schools across Northern Ireland. Teachers were generally in agreement regarding the importance of pure maths and the balance between pure and applied within the A-level maths curriculum. A wide variety of opinions existed concerning the applied options. While many believe that the basic mechanics-statistics (M1-S1) combination is most accessible, it was also noted that the M1-M2 combination fits neatly alongside A-level physics. Lack of resources, timetabling constraints and competition with other subjects in the curriculum hinder uptake of A-level Further Maths.

Teachers are very conscious of the need to obtain high grades to benefit both their pupils and the school’s reputation. The move to a linear assessment system in England while Northern Ireland retains the modular system is likely to cause some schools to review their choice of exam board although there is disagreement as to whether a modular or linear system is more advantageous for pupils. The upcoming change in the specification offers an opportunity to refresh the assessment also and reduce the number of leading questions. However, teachers note that there are serious issues with GCSE maths and these have implications for A-level.

The Robustness of Periodic Orchestrations in Uncertain Evolving Environments

A framework for assessing the robustness of long-duration repetitive orchestrations in uncertain evolving environments is proposed. The model assumes that service-based evaluation environments are stable over short time-frames only; over longer periods service-based environments evolve as demand fluctuates and contention for shared resources varies. The behaviour of a short-duration orchestration E in a stable environment is assessed by an uncertainty profile U and a corresponding zero-sum angel-daemon game Γ(U) [2]. Here the angel-daemon approach is extended to assess evolving environments by means of a subfamily of stochastic games. These games are called strategy oblivious because their transition probabilities are strategy independent. It is shown that the value of a strategy oblivious stochastic game is well defined and that it can be computed by solving a linear system. Finally, the proposed stochastic framework is used to assess the evolution of the Gabrmn IT system.

Avaliação para as aprendizagens de alunos com necessidades educativas especiais no 1º ciclo de ensino básico : da diversidade da avaliação à avaliação da diversidade

Tese de doutoramento, Educação (Avaliação em Educação), Universidade de Lisboa, Instituto de Educação, 2014

Controladores linguísticos Fuzzy

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

Development and Evaluation of Blind Identification Techniques for Nonlinear Systems

Identification and Control of Non‐linear dynamical systems are challenging problems to the control engineers.The topic is equally relevant in communication,weather prediction ,bio medical systems and even in social systems,where nonlinearity is an integral part of the system behavior.Most of the real world systems are nonlinear in nature and wide applications are there for nonlinear system identification/modeling.The basic approach in analyzing the nonlinear systems is to build a model from known behavior manifest in the form of system output.The problem of modeling boils down to computing a suitably parameterized model,representing the process.The parameters of the model are adjusted to optimize a performanace function,based on error between the given process output and identified process/model output.While the linear system identification is well established with many classical approaches,most of those methods cannot be directly applied for nonlinear system identification.The problem becomes more complex if the system is completely unknown but only the output time series is available.Blind recognition problem is the direct consequence of such a situation.The thesis concentrates on such problems.Capability of Artificial Neural Networks to approximate many nonlinear input-output maps makes it predominantly suitable for building a function for the identification of nonlinear systems,where only the time series is available.The literature is rich with a variety of algorithms to train the Neural Network model.A comprehensive study of the computation of the model parameters,using the different algorithms and the comparison among them to choose the best technique is still a demanding requirement from practical system designers,which is not available in a concise form in the literature.The thesis is thus an attempt to develop and evaluate some of the well known algorithms and propose some new techniques,in the context of Blind recognition of nonlinear systems.It also attempts to establish the relative merits and demerits of the different approaches.comprehensiveness is achieved in utilizing the benefits of well known evaluation techniques from statistics. The study concludes by providing the results of implementation of the currently available and modified versions and newly introduced techniques for nonlinear blind system modeling followed by a comparison of their performance.It is expected that,such comprehensive study and the comparison process can be of great relevance in many fields including chemical,electrical,biological,financial and weather data analysis.Further the results reported would be of immense help for practical system designers and analysts in selecting the most appropriate method based on the goodness of the model for the particular context.