Duckweed-based Wastewater Treatment Systems: Design Aspects and Integrated Reuse Options for Queensland Conditions

Point sources of wastewater pollution, including effluent from municipal sewage treatment plants and intensive livestock and processing industries, can contribute significantly to the degradation of receiving waters (Chambers et al. 1997; Productivity Commission 2004). This has led to increasingly stringent local wastewater discharge quotas (particularly regarding Nitrogen, Phosphorous and suspended solids), and many municipal authorities and industry managers are now faced with upgrading their existing treatment facilities in order to comply. However, with high construction, energy and maintenance expenses and increasing labour costs, traditional wastewater treatment systems are becoming an escalating financial burden for the communities and industries that operate them. This report was generated, in the first instance, for the Burdekin Shire Council to provide information on design aspects and parameters critical for developing duckweed-based wastewater treatment (DWT) in the Burdekin region. However, the information will be relevant to a range of wastewater sources throughout Queensland. This information has been collated from published literature and both overseas and local studies of pilot and full-scale DWT systems. This report also considers options to generate revenue from duckweed production (a significant feature of DWT), and provides specifications and component cost information (current at the time of publication) for a large-scale demonstration of an integrated DWT and fish production system.

Specifying Reuse Interfaces for Task-Oriented Framework Specialization

Reuse of existing carefully designed and tested software improves the quality of new software systems and reduces their development costs. Object-oriented frameworks provide an established means for software reuse on the levels of both architectural design and concrete implementation. Unfortunately, due to frame-works complexity that typically results from their flexibility and overall abstract nature, there are severe problems in using frameworks. Patterns are generally accepted as a convenient way of documenting frameworks and their reuse interfaces. In this thesis it is argued, however, that mere static documentation is not enough to solve the problems related to framework usage. Instead, proper interactive assistance tools are needed in order to enable system-atic framework-based software production. This thesis shows how patterns that document a framework s reuse interface can be represented as dependency graphs, and how dynamic lists of programming tasks can be generated from those graphs to assist the process of using a framework to build an application. This approach to framework specialization combines the ideas of framework cookbooks and task-oriented user interfaces. Tasks provide assistance in (1) cre-ating new code that complies with the framework reuse interface specification, (2) assuring the consistency between existing code and the specification, and (3) adjusting existing code to meet the terms of the specification. Besides illustrating how task-orientation can be applied in the context of using frameworks, this thesis describes a systematic methodology for modeling any framework reuse interface in terms of software patterns based on dependency graphs. The methodology shows how framework-specific reuse interface specifi-cations can be derived from a library of existing reusable pattern hierarchies. Since the methodology focuses on reusing patterns, it also alleviates the recog-nized problem of framework reuse interface specification becoming complicated and unmanageable for frameworks of realistic size. The ideas and methods proposed in this thesis have been tested through imple-menting a framework specialization tool called JavaFrames. JavaFrames uses role-based patterns that specify a reuse interface of a framework to guide frame-work specialization in a task-oriented manner. This thesis reports the results of cases studies in which JavaFrames and the hierarchical framework reuse inter-face modeling methodology were applied to the Struts web application frame-work and the JHotDraw drawing editor framework.

Query on the burial of persons married to Gentiles from the trustees answered

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Briefs for GSDR - Urban stormwater reuse: An agenda for sustainable development

We treat urban stormwater as a problem as it causes flooding, transports pollutants and degrades the ecosystem health of waterways (Goonetilleke et al., 2014). Municipal authorities devote a significant component of their budget to capture and remove stormwater from urban areas as rapidly as possible. Unfortunately, it is a largely unappreciated fact that urban stormwater is the last available uncommitted water resource for our cities as the demand for potable water escalates due to growing urbanisation, industrialisation and higher living standards.

Reuse of treated sewage in Delhi city: Microbial evaluation of STPs and reuse options

Microbiological quality of the treated wastewater is an important parameter for its reuse. The data oil the Fecal Coliform (FC) and Fecal Streptococcus (FS) at different stages of treatment in the Sewage Treatment Plants (STPs) in Delhi watershed is not available, therefore in the present study microbial profiling of STPs was carried out to assess the effluent quality for present and future reuse options. This Study further evaluates the water quality profiles at different stages of treatment for 16 STPs in Delhi city. These STPs are based on conventional Activated Sludge Process (ASP), extended aeration, physical, chemical and biological treatment (BIOFORE), Trickling Filter and Oxidation Pond. The primary effluent quality produced from most of the STPs was suitable for Soil Aquifer Treatment (SAT). Extended Hydraulic Retention Time (HRT) as a result Of low inflow to the STPS Was responsible for high turbidity, COD and BODs removal. Conventional ASP based STPs achieved 1.66 log FC and 1.06 log FS removal. STPs with extended aeration treatment process produced better quality effluent with maximum 4 log order reduction in FC and FS levels. ``Kondli'' and ``Nilothi'' STPs employing ASP, produced better quality secondary effluent as compared to other STPs based oil similar treatment process. Oxidation Pond based STPs showed better FC and FS removals, whereas good physiochemical quality was achieved during the first half of the treatment. Based upon physical, chemical and microbiological removal efficiencies, actual integrated efficiency (IEa) of each STP was determined to evaluate its Suitability for reuse for irrigation purposes. Except Mehrauli'' and ``Oxidation Pond'', effluents from all other STPs require tertiary treatment for further reuse. Possible reuse options, depending Upon the geographical location, proximity of facilities of potential users based oil the beneficial uses, and sub-soil types, etc. for the Delhi city have been investigated, which include artificial groundwater recharge, aquaculture, horticulture and industrial uses Such as floor washing, boiler feed, and cooling towers, etc. (C) 2009 Elsevier B.V. All rights reserved.

Nash equilibrium based semantic cache in mobile sensor grid database systems

Mobile applications are being increasingly deployed on a massive scale in various mobile sensor grid database systems. With limited resources from the mobile devices, how to process the huge number of queries from mobile users with distributed sensor grid databases becomes a critical problem for such mobile systems. While the fundamental semantic cache technique has been investigated for query optimization in sensor grid database systems, the problem is still difficult due to the fact that more realistic multi-dimensional constraints have not been considered in existing methods. To solve the problem, a new semantic cache scheme is presented in this paper for location-dependent data queries in distributed sensor grid database systems. It considers multi-dimensional constraints or factors in a unified cost model architecture, determines the parameters of the cost model in the scheme by using the concept of Nash equilibrium from game theory, and makes semantic cache decisions from the established cost model. The scenarios of three factors of semantic, time and locations are investigated as special cases, which improve existing methods. Experiments are conducted to demonstrate the semantic cache scheme presented in this paper for distributed sensor grid database systems.

Intent Based Clustering of Search Engine Query Log

The keyword based search technique suffers from the problem of synonymic and polysemic queries. Current approaches address only theproblem of synonymic queries in which different queries might have the same information requirement. But the problem of polysemic queries,i.e., same query having different intentions, still remains unaddressed. In this paper, we propose the notion of intent clusters, the members of which will have the same intention. We develop a clustering algorithm that uses the user session information in query logs in addition to query URL entries to identify cluster of queries having the same intention. The proposed approach has been studied through case examples from the actual log data from AOL, and the clustering algorithm is shown to be successful in discerning the user intentions.

Truthful and Quality Conscious Query Incentive Networks

Query incentive networks capture the role of incentives in extracting information from decentralized information networks such as a social network. Several game theoretic tilt:Kids of query incentive networks have been proposed in the literature to study and characterize the dependence, of the monetary reward required to extract the answer for a query, on various factors such as the structure of the network, the level of difficulty of the query, and the required success probability.None of the existing models, however, captures the practical andimportant factor of quality of answers. In this paper, we develop a complete mechanism design based framework to incorporate the quality of answers, in the monetization of query incentive networks. First, we extend the model of Kleinberg and Raghavan [2] to allow the nodes to modulate the incentive on the basis of the quality of the answer they receive. For this qualify conscious model. we show are existence of a unique Nash equilibrium and study the impact of quality of answers on the growth rate of the initial reward, with respect to the branching factor of the network. Next, we present two mechanisms; the direct comparison mechanism and the peer prediction mechanism, for truthful elicitation of quality from the agents. These mechanisms are based on scoring rules and cover different; scenarios which may arise in query incentive networks. We show that the proposed quality elicitation mechanisms are incentive compatible and ex-ante budget balanced. We also derive conditions under which ex-post budget balance can beachieved by these mechanisms.

SPSA algorithms with measurement reuse

Four algorithms, all variants of Simultaneous Perturbation Stochastic Approximation (SPSA), are proposed. The original one-measurement SPSA uses an estimate of the gradient of objective function L containing an additional bias term not seen in two-measurement SPSA. As a result, the asymptotic covariance matrix of the iterate convergence process has a bias term. We propose a one-measurement algorithm that eliminates this bias, and has asymptotic convergence properties making for easier comparison with the two-measurement SPSA. The algorithm, under certain conditions, outperforms both forms of SPSA with the only overhead being the storage of a single measurement. We also propose a similar algorithm that uses perturbations obtained from normalized Hadamard matrices. The convergence w.p. 1 of both algorithms is established. We extend measurement reuse to design two second-order SPSA algorithms and sketch the convergence analysis. Finally, we present simulation results on an illustrative minimization problem.

Lazy structure sharing for query optimization

We study lazy structure sharing as a tool for optimizing equivalence testing on complex data types, We investigate a number of strategies for implementing lazy structure sharing and provide upper and lower bounds on their performance (how quickly they effect ideal configurations of our data structure). In most cases when the strategies are applied to a restricted case of the problem, the bounds provide nontrivial improvements over the naive linear-time equivalence-testing strategy that employs no optimization. Only one strategy, however, which employs path compression, seems promising for the most general case of the problem.

Efficiently Approximating Query Optimizer Plan Diagrams

Given a parametrized n-dimensional SQL query template and a choice of query optimizer, a plan diagram is a color-coded pictorial enumeration of the execution plan choices of the optimizer over the query parameter space. These diagrams have proved to be a powerful metaphor for the analysis and redesign of modern optimizers, and are gaining currency in diverse industrial and academic institutions. However, their utility is adversely impacted by the impractically large computational overheads incurred when standard brute-force exhaustive approaches are used for producing fine-grained diagrams on high-dimensional query templates. In this paper, we investigate strategies for efficiently producing close approximations to complex plan diagrams. Our techniques are customized to the features available in the optimizer's API, ranging from the generic optimizers that provide only the optimal plan for a query, to those that also support costing of sub-optimal plans and enumerating rank-ordered lists of plans. The techniques collectively feature both random and grid sampling, as well as inference techniques based on nearest-neighbor classifiers, parametric query optimization and plan cost monotonicity. Extensive experimentation with a representative set of TPC-H and TPC-DS-based query templates on industrial-strength optimizers indicates that our techniques are capable of delivering 90% accurate diagrams while incurring less than 15% of the computational overheads of the exhaustive approach. In fact, for full-featured optimizers, we can guarantee zero error with less than 10% overheads. These approximation techniques have been implemented in the publicly available Picasso optimizer visualization tool.

On the Limits of Spatial Reuse and Cooperative Communication for Dense Wireless Networks

We consider a dense ad hoc wireless network comprising n nodes confined to a given two dimensional region of fixed area. For the Gupta-Kumar random traffic model and a realistic interference and path loss model (i.e., the channel power gains are bounded above, and are bounded below by a strictly positive number), we study the scaling of the aggregate end-to-end throughput with respect to the network average power constraint, P macr, and the number of nodes, n. The network power constraint P macr is related to the per node power constraint, P macr, as P macr = np. For large P, we show that the throughput saturates as Theta(log(P macr)), irrespective of the number of nodes in the network. For moderate P, which can accommodate spatial reuse to improve end-to-end throughput, we observe that the amount of spatial reuse feasible in the network is limited by the diameter of the network. In fact, we observe that the end-to-end path loss in the network and the amount of spatial reuse feasible in the network are inversely proportional. This puts a restriction on the gains achievable using the cooperative communication techniques studied in and, as these rely on direct long distance communication over the network.

Exploiting Programmable Network Interfaces for Parallel Query Execution in Workstation Clusters

Workstation clusters equipped with high performance interconnect having programmable network processors facilitate interesting opportunities to enhance the performance of parallel application run on them. In this paper, we propose schemes where certain application level processing in parallel database query execution is performed on the network processor. We evaluate the performance of TPC-H queries executing on a high end cluster where all tuple processing is done on the host processor, using a timed Petri net model, and find that tuple processing costs on the host processor dominate the execution time. These results are validated using a small cluster. We therefore propose 4 schemes where certain tuple processing activity is offloaded to the network processor. The first 2 schemes offload the tuple splitting activity - computation to identify the node on which to process the tuples, resulting in an execution time speedup of 1.09 relative to the base scheme, but with I/O bus becoming the bottleneck resource. In the 3rd scheme in addition to offloading tuple processing activity, the disk and network interface are combined to avoid the I/O bus bottleneck, which results in speedups up to 1.16, but with high host processor utilization. Our 4th scheme where the network processor also performs apart of join operation along with the host processor, gives a speedup of 1.47 along with balanced system resource utilizations. Further we observe that the proposed schemes perform equally well even in a scaled architecture i.e., when the number of processors is increased from 2 to 64

On Pushing Multilingual Query Operators into Relational Engines

To effectively support today’s global economy, database systems need to manage data in multiple languages simultaneously. While current database systems do support the storage and management of multilingual data, they are not capable of querying across different natural languages. To address this lacuna, we have recently proposed two cross-lingual functionalities, LexEQUAL[13] and SemEQUAL[14], for matching multilingual names and concepts, respectively. In this paper, we investigate the native implementation of these multilingual functionalities as first-class operators on relational engines. Specifically, we propose a new multilingual storage datatype, and an associated algebra of the multilingual operators on this datatype. These components have been successfully implemented in the PostgreSQL database system, including integration of the algebra with the query optimizer and inclusion of a metric index in the access layer. Our experiments demonstrate that the performance of the native implementation is up to two orders-of-magnitude faster than the corresponding outsidethe- server implementation. Further, these multilingual additions do not adversely impact the existing functionality and performance. To the best of our knowledge, our prototype represents the first practical implementation of a crosslingual database query engine.