Dual-frequency decoupling networks for compact antenna arrays

Decoupling networks can alleviate the effects of mutual coupling in antenna arrays. Conventional decoupling networks can provide decoupled and matched ports at a single frequency. This paper describes dual-frequency decoupling which is achieved by using a network of series or parallel resonant circuits instead of single reactive elements.

The determinants of corporate sustainability performance

This paper investigates the factors that drive high levels of corporate sustainability performance (CSP), as proxied by membership of the Dow Jones Sustainability World Index. Using a stakeholder framework, we examine the incentives for US firms to invest in sustainability principles and develop a number of hypotheses that relate CSP to firm-specific characteristics. Our results indicate that leading CSP firms are significantly larger, have higher levels of growth and a higher return on equity than conventional firms. Contrary to our predictions, leading CSP firms do not have greater free cash flows or lower leverage than other firms.

Reframing the development of corporate learning

Due to increasing recognition by industry that partnerships with universities can lead to more effective knowledge and skills acquisition and deployment, corporate learning programmes are currently experiencing a resurgence of interest. Rethinking of corporations’ approaches to what has traditionally been classed as ‘training’ has resulted in a new focus on learning and the adoption of philosophies that underlie the academic paradigm. This paper reports on two studies of collaboration between major international engineering corporations and an Australian university, the aim of which was to up-skill the workforce in response to changing markets. The paper highlights the differences between the models of learning adopted in such collaboration and those in more conventional, university-based environments. The learning programmes combine the ADDIE (analysis, design, develop, implement and evaluate) development and workplace learning models. Adaptations that have added value for industry partners and recommendations as to how these can be evolved to cope with change are discussed. The learning is contextualised by industry- based subject matter experts working in close collaboration with university experts and learning designers to develop programmes that are reflective of current and future needs in the organisation. Results derived from user feedback indicate that the learning programmes are effectively aligned with the needs of the industry partners whilst simultaneously upholding academic ideals. In other words, it is possible to combine academic and more traditional approaches to develop corporate learning programmes that satisfy requirements in the workplace. Emerging from the study, a new conceptual framework for the development of corporate learning is presented.

Deceit and Bruno Taut's Glashaus

The historical context surrounding Bruno Taut's Glashaus has been established through work of authors like Reyner Banham, Dennis Sharp and Ian Boyd-Whyte. However, these English language translations, are mostly derived from secondary sources such as Adolf Behne and Paul Scheerbart. Surprisingly, Taut's own writings largely do not feature in this prevailing account of his work. Since 1990, strong doubts have arisen about this conventional picture of Taut's Glashaus. Manfred spiedel, for instance, minimizes Paul Scheerbart's contribution to the design by arguing that Scheerbart met Taut only a few months before the construction of the Glashaus, that is, after Taut had finished his preliminary sketches. Kurt Junghanns goes further and asserts that the Glashaus design was complete beefore Taut and Scheerbart ever met. In 2005, Kai Gutschow published The Culture of Criticism: Adolf Behne and the Development of Modern Architecture in Germany, 1910 - 1914. Most startling, Gutschow asserts that Behne acts as the propagandist for the Glashaus by fabricating its link with Expressionism. This is particularly troubling because nobody contributed more to establishing the link between the Glashaus, Bruno Taut and Expressionism than Behne. As a result of this new evidence, this paper concurs that the established historical understanding of the Glashaus is flawed. By returning to Taut's own writings, a reinterpretation can be offered that strongly links the Glashaus to the Victoria regia lily and Strasbourg Cathedral. The significance of this approach is that it re-establishes Taut's own rational behind the design of the Glashaus, and thus contributes to the re-evaluation of the generally accepted histories of the Modern movement.

Gap analysis of intrusion detection in smart grids

Given the recent emergence of the smart grid and smart grid related technologies, their security is a prime concern. Intrusion detection provides a second line of defense. However, conventional intrusion detection systems (IDSs) are unable to adequately address the unique requirements of the smart grid. This paper presents a gap analysis of contemporary IDSs from a smart grid perspective. This paper highlights the lack of adequate intrusion detection within the smart grid and discusses the limitations of current IDSs approaches. The gap analysis identifies current IDSs as being unsuited to smart grid application without significant changes to address smart grid specific requirements.

Categorisation of activities of daily living of lower limb amputees during short-term use of a portable kinetic recording system : a preliminary study

The purpose of this preliminary study was to determine the relevance of the categorization of the load regime data to assess the functional output and usage of the prosthesis of lower limb amputees. The objectives were a) to introduce a categorization of load regime, b) to present some descriptors of each activity, and c) to report the results for a case. The load applied on the osseointegrated fixation of one transfemoral amputee was recorded using a portable kinetic system for 5 hours. The periods of directional locomotion, localized locomotion, and stationary loading occurred 44%, 34%, and 22% of recording time and each accounted for 51%, 38%, and 12% of the duration of the periods of activity, respectively. The absolute maximum force during directional locomotion, localized locomotion, and stationary loading was 19%, 15%, and 8% of the body weight on the anteroposterior axis, 20%, 19%, and 12% on the mediolateral axis, and 121%, 106%, and 99% on the long axis. A total of 2,783 gait cycles were recorded. Approximately 10% more gait cycles and 50% more of the total impulse than conventional analyses were identified. The proposed categorization and apparatus have the potential to complement conventional instruments, particularly for difficult cases.

A learning-based approach to reactive security

Despite the conventional wisdom that proactive security is superior to reactive security, we show that reactive security can be competitive with proactive security as long as the reactive defender learns from past attacks instead of myopically overreacting to the last attack. Our game-theoretic model follows common practice in the security literature by making worst-case assumptions about the attacker: we grant the attacker complete knowledge of the defender’s strategy and do not require the attacker to act rationally. In this model, we bound the competitive ratio between a reactive defense algorithm (which is inspired by online learning theory) and the best fixed proactive defense. Additionally, we show that, unlike proactive defenses, this reactive strategy is robust to a lack of information about the attacker’s incentives and knowledge.

Classification with a reject option using a hinge loss

We consider the problem of binary classification where the classifier can, for a particular cost, choose not to classify an observation. Just as in the conventional classification problem, minimization of the sample average of the cost is a difficult optimization problem. As an alternative, we propose the optimization of a certain convex loss function φ, analogous to the hinge loss used in support vector machines (SVMs). Its convexity ensures that the sample average of this surrogate loss can be efficiently minimized. We study its statistical properties. We show that minimizing the expected surrogate loss—the φ-risk—also minimizes the risk. We also study the rate at which the φ-risk approaches its minimum value. We show that fast rates are possible when the conditional probability P(Y=1|X) is unlikely to be close to certain critical values.

Reversed bias Pt/nanostructured ZnO Schottky diode with enhanced electric field for hydrogen sensing

In this paper, the effect of electric field enhancement on Pt/nanostructured ZnO Schottky diode based hydrogen sensors under reverse bias condition has been investigated. Current-voltage characteristics of these diodes have been studied at temperatures from 25 to 620 °C and their free carrier density concentration was estimated by exposing the sensors to hydrogen gas. The experimental results show a significantly lower breakdown voltage in reversed bias current-voltage characteristics than the conventional Schottky diodes and also greater lateral voltage shift in reverse bias operation than the forward bias. This can be ascribed to the increased localized electric fields emanating from the sharp edges and corners of the nanostructured morphologies. At 620 °C, voltage shifts of 114 and 325 mV for 0.06% and 1% hydrogen have been recorded from dynamic response under the reverse bias condition. © 2010 Elsevier B.V. All rights reserved.

Proteasome inhibitors trigger NOXA-mediated apoptosis in melanoma and myeloma cells

Patients with metastatic melanoma or multiple myeloma have a dismal prognosis because these aggressive malignancies resist conventional treatment. A promising new oncologic approach uses molecularly targeted therapeutics that overcomes apoptotic resistance and, at the same time, achieves tumor selectivity. The unexpected selectivity of proteasome inhibition for inducing apoptosis in cancer cells, but not in normal cells, prompted us to define the mechanism of action for this class of drugs, including Food and Drug Administration-approved bortezomib. In this report, five melanoma cell lines and a myeloma cell line are treated with three different proteasome inhibitors (MG-132, lactacystin, and bortezomib), and the mechanism underlying the apoptotic pathway is defined. Following exposure to proteasome inhibitors, effective killing of human melanoma and myeloma cells, but not of normal proliferating melanocytes, was shown to involve p53-independent induction of the BH3-only protein NOXA. Induction of NOXA at the protein level was preceded by enhanced transcription of NOXA mRNA. Engagement of mitochondrial-based apoptotic pathway involved release of cytochrome c, second mitochondria-derived activator of caspases, and apoptosis-inducing factor, accompanied by a proteolytic cascade with processing of caspases 9, 3, and 8 and poly(ADP)-ribose polymerase. Blocking NOXA induction using an antisense (but not control) oligonucleotide reduced the apoptotic response by 30% to 50%, indicating a NOXA-dependent component in the overall killing of melanoma cells. These results provide a novel mechanism for overcoming the apoptotic resistance of tumor cells, and validate agents triggering NOXA induction as potential selective cancer therapeutics for life-threatening malignancies such as melanoma and multiple myeloma.

Application of machine learning in fault diagnostics of mechanical systems

A diagnostic method based on Bayesian Networks (probabilistic graphical models) is presented. Unlike conventional diagnostic approaches, in this method instead of focusing on system residuals at one or a few operating points, diagnosis is done by analyzing system behavior patterns over a window of operation. It is shown how this approach can loosen the dependency of diagnostic methods on precise system modeling while maintaining the desired characteristics of fault detection and diagnosis (FDD) tools (fault isolation, robustness, adaptability, and scalability) at a satisfactory level. As an example, the method is applied to fault diagnosis in HVAC systems, an area with considerable modeling and sensor network constraints.

Measuring driver responses at railway level crossings

Railway level crossings are amongst the most complex of road safety control systems, due to the conflicts between road vehicles and rail infrastructure, trains and train operations. Driver behaviour at railway crossings is the major collision factor. The main objective of the present paper was to evaluate the existing conventional warning devices in relation to driver behaviour. The common conventional warning devices in Australia are a stop sign (passive), flashing lights and a half boom-barrier with flashing lights (active). The data were collected using two approaches, namely: field video recordings at selected sites and a driving simulator in a laboratory. This paper describes and compares the driver response results from both the field survey and the driving simulator. The conclusion drawn is that different types of warning systems resulted in varying driver responses at crossings. The results showed that on average driver responses to passive crossings were poor when compared to active ones. The field results were consistent with the simulator results for the existing conventional warning devices and hence they may be used to calibrate the simulator for further evaluation of alternative warning systems.

The rules of autogeddon : sex death and law in J G Ballard’s Crash

It was reported that the manuscript of Crash was returned to the publisher with a note reading ‘The author is beyond psychiatric help’. Ballard took the lay diagnosis as proof of complete artistic success. Crash conflates the Freudian tropes of libido and thanatos, overlaying these onto the twentieth century erotic icon, the car. Beyond mere incompetent adolescent copulatory fumblings in the back seat of the parental sedan or the clichéd phallic locomotor of the mid-life Ferrari, Ballard engages the full potentialities of the automobile as the locus and sine qua non of a perverse, though functional erotic. ‘Autoeroticism’ is transformed into automotive, traumatic or surgical paraphilia, driving Helmut Newton’s insipid photo-essays of BDSM and orthopædics into an entirely new dimension, dancing precisely where (but more crucially, because) the ‘body is bruised to pleasure soul’. The serendipity of quotidian accidental collisions is supplanted, in pursuit of the fetishised object, by contrived (though not simulated) recreations of iconographic celebrity deaths. Penetration remains as a guiding trope of sexuality, but it is confounded by a perversity of focus. Such an obsessive pursuit of this autoerotic-as-reality necessitates the rejection of the law of human sexual regulation, requiring the re-interpretation of what constitutes sex itself by looking beyond or through conventional sexuality into Ballard’s paraphiliac and nightmarish consensual Other. This Other allows for (if not demands) the tangled wreckage of a sportscar to function as a transformative sexual agent, creating, of woman, a being of ‘free and perverse sexuality, releasing within its dying chromium and leaking engine-parts, all the deviant possibilities of her sex’.

Non-redundant sequential association rule mining based on closed sequential patterns

In many applications, e.g., bioinformatics, web access traces, system utilisation logs, etc., the data is naturally in the form of sequences. People have taken great interest in analysing the sequential data and finding the inherent characteristics or relationships within the data. Sequential association rule mining is one of the possible methods used to analyse this data. As conventional sequential association rule mining very often generates a huge number of association rules, of which many are redundant, it is desirable to find a solution to get rid of those unnecessary association rules. Because of the complexity and temporal ordered characteristics of sequential data, current research on sequential association rule mining is limited. Although several sequential association rule prediction models using either sequence constraints or temporal constraints have been proposed, none of them considered the redundancy problem in rule mining. The main contribution of this research is to propose a non-redundant association rule mining method based on closed frequent sequences and minimal sequential generators. We also give a definition for the non-redundant sequential rules, which are sequential rules with minimal antecedents but maximal consequents. A new algorithm called CSGM (closed sequential and generator mining) for generating closed sequences and minimal sequential generators is also introduced. A further experiment has been done to compare the performance of generating non-redundant sequential rules and full sequential rules, meanwhile, performance evaluation of our CSGM and other closed sequential pattern mining or generator mining algorithms has also been conducted. We also use generated non-redundant sequential rules for query expansion in order to improve recommendations for infrequently purchased products.

Least-squares congealing for large numbers of images

In this paper we pursue the task of aligning an ensemble of images in an unsupervised manner. This task has been commonly referred to as “congealing” in literature. A form of congealing, using a least-squares criteria, has been recently demonstrated to have desirable properties over conventional congealing. Least-squares congealing can be viewed as an extension of the Lucas & Kanade (LK)image alignment algorithm. It is well understood that the alignment performance for the LK algorithm, when aligning a single image with another, is theoretically and empirically equivalent for additive and compositional warps. In this paper we: (i) demonstrate that this equivalence does not hold for the extended case of congealing, (ii) characterize the inherent drawbacks associated with least-squares congealing when dealing with large numbers of images, and (iii) propose a novel method for circumventing these limitations through the application of an inverse-compositional strategy that maintains the attractive properties of the original method while being able to handle very large numbers of images.