Design for disassembly : an architectural strategy

A study of historic examples of buildings that were designed for disassembly reveals a number of important lessons in the technology employed. These lessons can inform designers such that they may better design for disassembly to attempt to increase the rates of reuse and recycling in the building industry.

Tax expenditures in Australia : the elevation from ‘disguised’ expenditures to architectural pillars of the 21st century

The current Australian Treasury approach to tax expenditures management and reporting is a culmination of 36 years of Government and Parliamentary reviews and reports. The most notable outcome of these reviews and reports is the publication of the annual tax expenditures statement, which commenced in 1986. Since its inception, the Australian annual tax expenditures statements have themselves been the subject of review. Most recently, the Australian National Audit Office has undertaken a performance audit in the Department of the Treasury and released its report entitled Preparation of the Tax Expenditures Statement. In addition to this 2008 report, a second recent opportunity to consider tax expenditures within the Australian tax regime has arisen. The Australian tax system is currently undergoing a comprehensive and broad review with the terms of reference requiring a consideration of all relevant tax expenditures. While the recommendations of the Australian National Audit Office are not novel, and it is not unusual for a broader review to consider the role of tax expenditures within the Australian tax system, both the recommendations of the Australian National Audit Office and the views of the current Review Panel take on a renewed sense of importance given the proliferation of tax expenditures in Australia. Tax expenditures, in terms of number and pecuniary value, have increased significantly in Australia in recent years. The latest Tax Expenditures Statement lists around 320 tax expenditures with the pecuniary value of those expenditures estimated at $73.69 billion or 7.1% of GDP. The largest category of tax expenditures listed in the 2008 Tax Expenditures Statement, totalling $29.23 billion, relate to concessions aimed at retirement savings.

Using approximate Bayesian computation to estimate transmission rates of nosocomial pathogens

In this paper, we apply a simulation based approach for estimating transmission rates of nosocomial pathogens. In particular, the objective is to infer the transmission rate between colonised health-care practitioners and uncolonised patients (and vice versa) solely from routinely collected incidence data. The method, using approximate Bayesian computation, is substantially less computer intensive and easier to implement than likelihood-based approaches we refer to here. We find through replacing the likelihood with a comparison of an efficient summary statistic between observed and simulated data that little is lost in the precision of estimated transmission rates. Furthermore, we investigate the impact of incorporating uncertainty in previously fixed parameters on the precision of the estimated transmission rates.

Capping computation time and storage requirements for appearance-based localization with CAT-SLAM

Appearance-based localization is increasingly used for loop closure detection in metric SLAM systems. Since it relies only upon the appearance-based similarity between images from two locations, it can perform loop closure regardless of accumulated metric error. However, the computation time and memory requirements of current appearance-based methods scale linearly not only with the size of the environment but also with the operation time of the platform. These properties impose severe restrictions on longterm autonomy for mobile robots, as loop closure performance will inevitably degrade with increased operation time. We present a set of improvements to the appearance-based SLAM algorithm CAT-SLAM to constrain computation scaling and memory usage with minimal degradation in performance over time. The appearance-based comparison stage is accelerated by exploiting properties of the particle observation update, and nodes in the continuous trajectory map are removed according to minimal information loss criteria. We demonstrate constant time and space loop closure detection in a large urban environment with recall performance exceeding FAB-MAP by a factor of 3 at 100% precision, and investigate the minimum computational and memory requirements for maintaining mapping performance.

A human-simulated immune evolutionary computation approach

Premature convergence to local optimal solutions is one of the main difficulties when using evolutionary algorithms in real-world optimization problems. To prevent premature convergence and degeneration phenomenon, this paper proposes a new optimization computation approach, human-simulated immune evolutionary algorithm (HSIEA). Considering that the premature convergence problem is due to the lack of diversity in the population, the HSIEA employs the clonal selection principle of artificial immune system theory to preserve the diversity of solutions for the search process. Mathematical descriptions and procedures of the HSIEA are given, and four new evolutionary operators are formulated which are clone, variation, recombination, and selection. Two benchmark optimization functions are investigated to demonstrate the effectiveness of the proposed HSIEA.

Toward a theory of the architectural subject

The extraordinary event, for Deleuze, is the object becoming subject – not in the manner of an abstract formulation, such as the substitution of one ideational representation for another but, rather, in the introduction of a vast, new, impersonal plane of subjectivity, populated by object processes and physical phenomena that in Deleuze’s discovery will be shown to constitute their own subjectivities. Deleuze’s polemic of subjectivity (the refusal of the Cartesian subject and the transcendental ego of Husserl) – long attempted by other thinkers – is unique precisely because it heralds the dawning of a new species of objecthood that will qualify as its own peculiar subjectivity. A survey of Deleuze’s early work on subjectivity, Empirisme et subjectivité (Deleuze 1953), Le Bergsonisme (Deleuze 1968), and Logique du sens (Deleuze 1969), brings the architectural reader into a peculiar confrontation with what Deleuze calls the ‘new transcendental field’, the field of subjectproducing effects, which for the philosopher takes the place of both the classical and modern subject. Deleuze’s theory of consciousness and perception is premised on the critique of Husserlian phenomenology; and ipso facto his question is an architectural problematic, even if the name ‘architecture’ is not invoked...

An evolutionary computation approach to three-dimensional path planning for unmanned aerial vehicles with tactical and kinematic constraints

This paper presents a novel evolutionary computation approach to three-dimensional path planning for unmanned aerial vehicles (UAVs) with tactical and kinematic constraints. A genetic algorithm (GA) is modified and extended for path planning. Two GAs are seeded at the initial and final positions with a common objective to minimise their distance apart under given UAV constraints. This is accomplished by the synchronous optimisation of subsequent control vectors. The proposed evolutionary computation approach is called synchronous genetic algorithm (SGA). The sequence of control vectors generated by the SGA constitutes to a near-optimal path plan. The resulting path plan exhibits no discontinuity when transitioning from curve to straight trajectories. Experiments and results show that the paths generated by the SGA are within 2% of the optimal solution. Such a path planner when implemented on a hardware accelerator, such as field programmable gate array chips, can be used in the UAV as on-board replanner, as well as in ground station systems for assisting in high precision planning and modelling of mission scenarios.

Improving the efficiency of RFID authentication with pre-computation

Security of RFID authentication protocols has received considerable interest recently. However, an important aspect of such protocols that has not received as much attention is the efficiency of their communication. In this paper we investigate the efficiency benefits of pre-computation for time-constrained applications in small to medium RFID networks. We also outline a protocol utilizing this mechanism in order to demonstrate the benefits and drawbacks of using thisapproach. The proposed protocol shows promising results as it is able to offer the security of untraceableprotocols whilst only requiring the time comparable to that of more efficient but traceable protocols.

Monitoring android for collaborative anomaly detection : a first architectural draft

Our daily lives become more and more dependent upon smartphones due to their increased capabilities. Smartphones are used in various ways, e.g. for payment systems or assisting the lives of elderly or disabled people. Security threats for these devices become more and more dangerous since there is still a lack of proper security tools for protection. Android emerges as an open smartphone platform which allows modification even on operating system level and where third-party developers first time have the opportunity to develop kernel-based low-level security tools. Android quickly gained its popularity among smartphone developers and even beyond since it bases on Java on top of "open" Linux in comparison to former proprietary platforms which have very restrictive SDKs and corresponding APIs. Symbian OS, holding the greatest market share among all smartphone OSs, was even closing critical APIs to common developers and introduced application certification. This was done since this OS was the main target for smartphone malwares in the past. In fact, more than 290 malwares designed for Symbian OS appeared from July 2004 to July 2008. Android, in turn, promises to be completely open source. Together with the Linux-based smartphone OS OpenMoko, open smartphone platforms may attract malware writers for creating malicious applications endangering the critical smartphone applications and owners privacy. Since signature-based approaches mainly detect known malwares, anomaly-based approaches can be a valuable addition to these systems. They base on mathematical algorithms processing data that describe the state of a certain device. For gaining this data, a monitoring client is needed that has to extract usable information (features) from the monitored system. Our approach follows a dual system for analyzing these features. On the one hand, functionality for on-device light-weight detection is provided. But since most algorithms are resource exhaustive, remote feature analysis is provided on the other hand. Having this dual system enables event-based detection that can react to the current detection need. In our ongoing research we aim to investigates the feasibility of light-weight on-device detection for certain occasions. On other occasions, whenever significant changes are detected on the device, the system can trigger remote detection with heavy-weight algorithms for better detection results. In the absence of the server respectively as a supplementary approach, we also consider a collaborative scenario. Here, mobile devices sharing a common objective are enabled by a collaboration module to share information, such as intrusion detection data and results. This is based on an ad-hoc network mode that can be provided by a WiFi or Bluetooth adapter nearly every smartphone possesses.

Facebook : a 24 hour studio environment for contemporary architectural education

The popularity of Web 2.0 technology amongst tertiary students has become an increased talking point due to its pedagogical capabilities. The purpose of this research was to incorporate the social network Facebook within an architectural design studio to reintroduce the social interaction that was once generated within the traditional, 24 hour setting. This interaction has proven vital to an architect’s future as here they develop the initial peer network within the industry. The study draws upon existing literature to gage the effectiveness of introducing Facebook within the contemporary university environment, further, a case study was established within a second year architectural class. The correspondence was monitored at five intervals across the semester, with the information that was shared, quantified. The aim of this research was to provide the necessary foundation for the feasibility on the possible inclusion of Facebook within architectural tertiary education.

Bayesian computation via empirical likelihood

Approximate Bayesian computation has become an essential tool for the analysis of complex stochastic models when the likelihood function is numerically unavailable. However, the well-established statistical method of empirical likelihood provides another route to such settings that bypasses simulations from the model and the choices of the approximate Bayesian computation parameters (summary statistics, distance, tolerance), while being convergent in the number of observations. Furthermore, bypassing model simulations may lead to significant time savings in complex models, for instance those found in population genetics. The Bayesian computation with empirical likelihood algorithm we develop in this paper also provides an evaluation of its own performance through an associated effective sample size. The method is illustrated using several examples, including estimation of standard distributions, time series, and population genetics models.

Re-strengthening 20th century architectural heritage : A case study of Brisbane City Hall restoration

Restoring old buildings to conform the current building policies and standards is a great challenge to engineers and architects. The restoration of the Brisbane City Hall, a heritage building listed by the State of Queensland in Australia, developed an innovative approach to upgrade the building using the method called ‘concrete overlay’ following the guidelines of both the International Council on Monuments and Sites and the Burra Charter of Australia. Concrete overlay is a new method of structural strengthening by drilling new reinforcement and placing new concrete on top of the existing structure, akin to a bone transplant or bone grafting in the case of a human being. This method is popularly used for newer bridges which have suffered load stresses. However, this method had never been used on any heritage buildings which were built on different conditions and standards. The compatibility of this method is currently being monitored. Most of the modern historic buildings are rapidly deteriorating and require immediate interventions in order to be saved. As most of these heritage buildings are on the stage of advanced deterioration, significant attempts are being made and several innovations are being applied to upgrade these structures to conform with the current building requirements. To date, the knowledge and literature in regarding ‘concrete cancer’ in relation to rehabilitating these reinforced concrete heritage structures is significantly lacking. It is hoped that the method of concrete overlay and the case study of Brisbane City Hall restoration will contribute to the development of restoration techniques and policies for Modern Heritage Buildings.

Open up the building : architectural relevance of building-users and their participations

As buildings have become more advanced and complex, our ability to understand how they are operated and managed has diminished. Modern technologies have given us systems to look after us but it appears to have taken away our say in how we like our environment to be managed. The aim of this paper is to discuss our research concerning spaces that are sensitive to changing needs and allow building-users to have a certain level of freedom to understand and control their environment. We discuss why, what we call the Active Layer, is needed in modern buildings; how building inhabitants are to interact with it; and the development of interface prototypes to test consequences of having the Active Layer in our environment.

Composite SaaS resource management in cloud computing using evolutionary computation

Cloud computing is an emerging computing paradigm in which IT resources are provided over the Internet as a service to users. One such service offered through the Cloud is Software as a Service or SaaS. SaaS can be delivered in a composite form, consisting of a set of application and data components that work together to deliver higher-level functional software. SaaS is receiving substantial attention today from both software providers and users. It is also predicted to has positive future markets by analyst firms. This raises new challenges for SaaS providers managing SaaS, especially in large-scale data centres like Cloud. One of the challenges is providing management of Cloud resources for SaaS which guarantees maintaining SaaS performance while optimising resources use. Extensive research on the resource optimisation of Cloud service has not yet addressed the challenges of managing resources for composite SaaS. This research addresses this gap by focusing on three new problems of composite SaaS: placement, clustering and scalability. The overall aim is to develop efficient and scalable mechanisms that facilitate the delivery of high performance composite SaaS for users while optimising the resources used. All three problems are characterised as highly constrained, large-scaled and complex combinatorial optimisation problems. Therefore, evolutionary algorithms are adopted as the main technique in solving these problems. The first research problem refers to how a composite SaaS is placed onto Cloud servers to optimise its performance while satisfying the SaaS resource and response time constraints. Existing research on this problem often ignores the dependencies between components and considers placement of a homogenous type of component only. A precise problem formulation of composite SaaS placement problem is presented. A classical genetic algorithm and two versions of cooperative co-evolutionary algorithms are designed to now manage the placement of heterogeneous types of SaaS components together with their dependencies, requirements and constraints. Experimental results demonstrate the efficiency and scalability of these new algorithms. In the second problem, SaaS components are assumed to be already running on Cloud virtual machines (VMs). However, due to the environment of a Cloud, the current placement may need to be modified. Existing techniques focused mostly at the infrastructure level instead of the application level. This research addressed the problem at the application level by clustering suitable components to VMs to optimise the resource used and to maintain the SaaS performance. Two versions of grouping genetic algorithms (GGAs) are designed to cater for the structural group of a composite SaaS. The first GGA used a repair-based method while the second used a penalty-based method to handle the problem constraints. The experimental results confirmed that the GGAs always produced a better reconfiguration placement plan compared with a common heuristic for clustering problems. The third research problem deals with the replication or deletion of SaaS instances in coping with the SaaS workload. To determine a scaling plan that can minimise the resource used and maintain the SaaS performance is a critical task. Additionally, the problem consists of constraints and interdependency between components, making solutions even more difficult to find. A hybrid genetic algorithm (HGA) was developed to solve this problem by exploring the problem search space through its genetic operators and fitness function to determine the SaaS scaling plan. The HGA also uses the problem's domain knowledge to ensure that the solutions meet the problem's constraints and achieve its objectives. The experimental results demonstrated that the HGA constantly outperform a heuristic algorithm by achieving a low-cost scaling and placement plan. This research has identified three significant new problems for composite SaaS in Cloud. Various types of evolutionary algorithms have also been developed in addressing the problems where these contribute to the evolutionary computation field. The algorithms provide solutions for efficient resource management of composite SaaS in Cloud that resulted to a low total cost of ownership for users while guaranteeing the SaaS performance.