989 resultados para Complex Signals


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Complex flow datasets are often difficult to represent in detail using traditional vector visualisation techniques such as arrow plots and streamlines. This is particularly true when the flow regime changes in time. Texture-based techniques, which are based on the advection of dense textures, are novel techniques for visualising such flows (i.e., complex dynamics and time-dependent). In this paper, we review two popular texture-based techniques and their application to flow datasets sourced from real research projects. The texture-based techniques investigated were Line Integral Convolution (LIC), and Image-Based Flow Visualisation (IBFV). We evaluated these techniques and in this paper report on their visualisation effectiveness (when compared with traditional techniques), their ease of implementation, and their computational overhead.

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Cognitive radio is an emerging technology proposing the concept of dynamic spec- trum access as a solution to the looming problem of spectrum scarcity caused by the growth in wireless communication systems. Under the proposed concept, non- licensed, secondary users (SU) can access spectrum owned by licensed, primary users (PU) so long as interference to PU are kept minimal. Spectrum sensing is a crucial task in cognitive radio whereby the SU senses the spectrum to detect the presence or absence of any PU signal. Conventional spectrum sensing assumes the PU signal as ‘stationary’ and remains in the same activity state during the sensing cycle, while an emerging trend models PU as ‘non-stationary’ and undergoes state changes. Existing studies have focused on non-stationary PU during the transmission period, however very little research considered the impact on spectrum sensing when the PU is non-stationary during the sensing period. The concept of PU duty cycle is developed as a tool to analyse the performance of spectrum sensing detectors when detecting non-stationary PU signals. New detectors are also proposed to optimise detection with respect to duty cycle ex- hibited by the PU. This research consists of two major investigations. The first stage investigates the impact of duty cycle on the performance of existing detec- tors and the extent of the problem in existing studies. The second stage develops new detection models and frameworks to ensure the integrity of spectrum sensing when detecting non-stationary PU signals. The first investigation demonstrates that conventional signal model formulated for stationary PU does not accurately reflect the behaviour of a non-stationary PU. Therefore the performance calculated and assumed to be achievable by the conventional detector does not reflect actual performance achieved. Through analysing the statistical properties of duty cycle, performance degradation is proved to be a problem that cannot be easily neglected in existing sensing studies when PU is modelled as non-stationary. The second investigation presents detectors that are aware of the duty cycle ex- hibited by a non-stationary PU. A two stage detection model is proposed to improve the detection performance and robustness to changes in duty cycle. This detector is most suitable for applications that require long sensing periods. A second detector, the duty cycle based energy detector is formulated by integrat- ing the distribution of duty cycle into the test statistic of the energy detector and suitable for short sensing periods. The decision threshold is optimised with respect to the traffic model of the PU, hence the proposed detector can calculate average detection performance that reflect realistic results. A detection framework for the application of spectrum sensing optimisation is proposed to provide clear guidance on the constraints on sensing and detection model. Following this framework will ensure the signal model accurately reflects practical behaviour while the detection model implemented is also suitable for the desired detection assumption. Based on this framework, a spectrum sensing optimisation algorithm is further developed to maximise the sensing efficiency for non-stationary PU. New optimisation constraints are derived to account for any PU state changes within the sensing cycle while implementing the proposed duty cycle based detector.

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Detailed representations of complex flow datasets are often difficult to generate using traditional vector visualisation techniques such as arrow plots and streamlines. This is particularly true when the flow regime changes in time. Texture-based techniques, which are based on the advection of dense textures, are novel techniques for visualising such flows. We review two popular texture based techniques and their application to flow datasets sourced from active research projects. The techniques investigated were Line integral convolution (LIC) [1], and Image based flow visualisation (IBFV) [18]. We evaluated these and report on their effectiveness from a visualisation perspective. We also report on their ease of implementation and computational overheads.

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Maize streak virus (MSV; Genus Mastrevirus, Family Geminiviridae) occurs throughout Africa, where it causes what is probably the most serious viral crop disease on the continent. It is obligately transmitted by as many as six leafhopper species in the Genus Cicadulina, but mainly by C. mbila Naudé and C. storeyi. In addition to maize, it can infect over 80 other species in the Family Poaceae. Whereas 11 strains of MSV are currently known, only the MSV-A strain is known to cause economically significant streak disease in maize. Severe maize streak disease (MSD) manifests as pronounced, continuous parallel chlorotic streaks on leaves, with severe stunting of the affected plant and, usuallly, a failure to produce complete cobs or seed. Natural resistance to MSV in maize, and/or maize infections caused by non-maize-adapted MSV strains, can result in narrow, interrupted streaks and no obvious yield losses. MSV epidemiology is primarily governed by environmental influences on its vector species, resulting in erratic epidemics every 3-10 years. Even in epidemic years, disease incidences can vary from a few infected plants per field, with little associated yield loss, to 100% infection rates and complete yield loss. Taxonomy: The only virus species known to cause MSD is MSV, the type member of the Genus Mastrevirus in the Family Geminiviridae. In addition to the MSV-A strain, which causes the most severe form of streak disease in maize, 10 other MSV strains (MSV-B to MSV-K) are known to infect barley, wheat, oats, rye, sugarcane, millet and many wild, mostly annual, grass species. Seven other mastrevirus species, many with host and geographical ranges partially overlapping those of MSV, appear to infect primarily perennial grasses. Physical properties: MSV and all related grass mastreviruses have single-component, circular, single-stranded DNA genomes of approximately 2700 bases, encapsidated in 22 × 38-nm geminate particles comprising two incomplete T = 1 icosahedra, with 22 pentameric capsomers composed of a single 32-kDa capsid protein. Particles are generally stable in buffers of pH 4-8. Disease symptoms: In infected maize plants, streak disease initially manifests as minute, pale, circular spots on the lowest exposed portion of the youngest leaves. The only leaves that develop symptoms are those formed after infection, with older leaves remaining healthy. As the disease progresses, newer leaves emerge containing streaks up to several millimetres in length along the leaf veins, with primary veins being less affected than secondary or tertiary veins. The streaks are often fused laterally, appearing as narrow, broken, chlorotic stripes, which may extend over the entire length of severely affected leaves. Lesion colour generally varies from white to yellow, with some virus strains causing red pigmentation on maize leaves and abnormal shoot and flower bunching in grasses. Reduced photosynthesis and increased respiration usually lead to a reduction in leaf length and plant height; thus, maize plants infected at an early stage become severely stunted, producing undersized, misshapen cobs or giving no yield at all. Yield loss in susceptible maize is directly related to the time of infection: Infected seedlings produce no yield or are killed, whereas plants infected at later times are proportionately less affected. Disease control: Disease avoidance can be practised by only planting maize during the early season when viral inoculum loads are lowest. Leafhopper vectors can also be controlled with insecticides such as carbofuran. However, the development and use of streak-resistant cultivars is probably the most effective and economically viable means of preventing streak epidemics. Naturally occurring tolerance to MSV (meaning that, although plants become systemically infected, they do not suffer serious yield losses) has been found, which has primarily been attributed to a single gene, msv-1. However, other MSV resistance genes also exist and improved resistance has been achieved by concentrating these within individual maiz genotypes. Whereas true MSV immunity (meaning that plants cannot be symptomatically infected by the virus) has been achieved in lines that include multiple small-effect resistance genes together with msv-1, it has proven difficult to transfer this immunity into commercial maize genotypes. An alternative resistance strategy using genetic engineering is currently being investigated in South Africa. Useful websites: 〈http://www.mcb.uct.ac.za/MSV/mastrevirus.htm〉; 〈http://www. danforthcenter.org/iltab/geminiviridae/geminiaccess/mastrevirus/Mastrevirus. htm〉. © 2009 Blackwell Publishing Ltd.

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Objectives: To investigate the efficacy of progestin treatment to achieve pathological complete response (pCR) in patients with complex atypical endometrial hyperplasia (CAH) or early endometrial adenocarcinoma (EC). Methods: A systematic search identified 3245 potentially relevant citations. Studies containing less than ten eligible CAH or EC patients in either oral or intrauterine treatment arm were excluded. Only information from patients receiving six or more months of treatment and not receiving other treatments was included. Weighted proportions of patients achieving pCR were calculated using R software. Results: Twelve studies met the selection criteria. Eleven studies reported treatment of patients with oral (219 patients, 117 with CAH, 102 with grade 1 Stage I EC) and one reported treatment of patients with intrauterine progestin (11 patients with grade 1 Stage IEC). Overall, 74% (95% confidence interval [CI] 65-81%) of patients with CAH and 72% (95% CI 62-80%) of patients with grade 1 Stage I EC achieved a pCR to oral progestin. Disease progression while on oral treatment was reported for 6/219 (2.7%), and relapse after initial complete response for 32/159 (20.1%) patients. The weighted mean pCR rate of patients with grade 1 Stage I EC treated with intrauterine progestin from one prospective pilot study and an unpublished retrospective case series from the Queensland Centre of Gynaecologic Oncology (QCGC) was 68% (95% CI 45- 86%). Conclusions: There is a lack of high quality evidence for the efficacy of progestin in CAH or EC. The available evidence however suggests that treatment with oral or intrauterine progestin is similarly effective. The risk of progression during treatment is small but longer follow-up is required. Evidence from prospective controlled clinical trials is warranted to establish how the efficacy of progestin for the treatment of CAH and EC can be improved further.

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This paper reports the findings of a qualitative study which investigated 25 international students’ use of online information resources for study purposes at two Australian universities. Using an expanded critical incident approach, the study viewed international students through an information literacy lens, as information-using learners. The findings are presented in two complementary parts: as a word picture that describes their whole experience of using online information resources to learn; and as a tabulated set of critical findings that summarises their associated information literacy learning needs. The word picture shows international students’ resource use as a complex interplay of eight inter-related elements: students; information-learning environment; interactions (with online resources); strengths-challenges; learning-help; affective responses; reflective responses; cultural-linguistic dimensions. In using online resources, the international students experience an array of strengths and challenges, and an apparent information literacy imbalance between their more developed information skills and less developed critical information use. The critical findings about information literacy needs provide a framework for developing an inclusive informed learning approach that responds to international students’ complex information using experiences and needs. While the study is situated in Australia, the findings are of potential interest to educators, information professionals and researchers worldwide who seek to support learning in culturally diverse higher education contexts.

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While highly cohesive groups are potentially advantageous they are also often correlated with the emergence of knowledge and information silos based around those same functional or occupational clusters. Consequently, an essential challenge for engineering organisations wishing to overcome informational silos is to implement mechanisms that facilitate, encourage and sustain interactions between otherwise disconnected groups. This paper acts as a primer for those seeking to gain an understanding of the design, functionality and utility of a suite of software tools generically termed social media technologies in the context of optimising the management of tacit engineering knowledge. Underpinned by knowledge management theory and using detailed case examples, this paper explores how social media technologies achieve such goals, allowing for the transfer of knowledge by tapping into the tacit and explicit knowledge of disparate groups in complex engineering environments.

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This study used both content and frame analyses to test news-media representations of homelessness in The Courier-Mail newspaper for evidence of restricted journalism practice. Specifically, it sought signs of either direct manipulation of issue representation based on ideological grounds, and also evidence of news organisations prioritising low-cost news production over Public Sphere journalistic news values. The study found that news stories from the earlier parts of the longitudinal study showed stereotypical misrepresentations of homelessness for public deliberation which might be attributed to either, or both of the nominated restricting factors. However news stories from the latter part of the study saw a distinct change in the way the issue was represented, indicating a journalistic capacity to thoughtfully and sensitively represent a complex social issue to the public. Further study is recommended to ascertain how and why this change occurred, so that journalistic practice might be further improved.

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A complex attack is a sequence of temporally and spatially separated legal and illegal actions each of which can be detected by various IDS but as a whole they constitute a powerful attack. IDS fall short of detecting and modeling complex attacks therefore new methods are required. This paper presents a formal methodology for modeling and detection of complex attacks in three phases: (1) we extend basic attack tree (AT) approach to capture temporal dependencies between components and expiration of an attack, (2) using enhanced AT we build a tree automaton which accepts a sequence of actions from input message streams from various sources if there is a traversal of an AT from leaves to root, and (3) we show how to construct an enhanced parallel automaton that has each tree automaton as a subroutine. We use simulation to test our methods, and provide a case study of representing attacks in WLANs.

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The fungal genera Ustilago, Sporisorium and Macalpinomyces represent an unresolved complex. Taxa within the complex often possess characters that occur in more than one genus, creating uncertainty for species placement. Previous studies have indicated that the genera cannot be separated by morphology alone. Here we chronologically review the history of the Ustilago-Sporisorium-Macalpinomyces complex, argue for its resolution and suggest methods to accomplish a stable taxonomy. A combined molecular and morphological approach is required to identify synapomorphic characters that underpin a new classification. Ustilago, Sporisorium and Macalpinomyces require explicit re-description and new genera, based on monophyletic groups, are needed to accommodate taxa that no longer fit the emended descriptions. A resolved classification will end the taxonomic confusion that surrounds generic placement of these smut fungi.

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The dawn of the twenty-first century encouraged a number of scientific and technological organisations to identify what they saw as ‘Grand Challenges and Opportunities’. Issues of environment and health featured very prominently in these quite short lists, as can be seen from a sample of these challenges in Table 1. Indeed, the first two lists of challenges in Table 1 were identified as for the environment and for health, respectively.

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The genera Ustilago, Sporisorium and Macalpinomyces are a polyphyletic complex of plant pathogenic fungi. The four main morphological characters used to define these genera have been considered homoplasious and not useful for resolving the complex. This study re-evaluates character homology and discusses the use of these characters for defining monophyletic groups recovered from a reconstructed phylogeny using four nuclear loci. Generic delimitation of smut fungi based on their hosts is also discussed as a means for identifying genera within this group. Morphological characters and host specificity can be used to circumscribe genera within the Ustilago-Sporisorium-Macalpinomyces complex.

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Purpose of review: The study provides a review of current evidence about the role of complex nonpharmacological strategies in managing the multidimensional components of the breathlessness experience for individuals with life-limiting conditions. Recent findings: Evidence continues to demonstrate the significant impact of breathlessness on patients’ quality of life, day-to-day activity, and physical and psychosocial functioning. Recent evidence also confirms that patients draw on a number of self-initiated actions to cope with breathlessness, although many do not use strategies that are supported by a growing body of evidence from randomized controlled trials. Current literature supports the use of multicomponent, nonpharmacological interventions comprising strategies to improve breathing efficiency and reducing psychological distress to manage breathlessness. However trials of these approaches have mostly been conducted among patients with chronic obstructive pulmonary disease (COPD) or lung cancer, and few studies have investigated the benefits of nonpharmacological for patients in later stages of disease. Further investigation of interventions is required across a broader range of chronic life-limiting conditions. Addressing breathlessness and its co-occurring symptoms (symptom clusters) is also an area for future enquiry. Summary: The experience of breathlessness and strategies adopted by patients to manage the experience highlight the importance of multidimensional approaches to improve outcomes for patients with life-limiting conditions. There is good evidence to support the role of multicomponent, nonpharmacological interventions in reducing breathlessness for patients with COPD and lung cancer, although further studies are required to understand the particular clinical contexts in which such interventions are appropriate.

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Many older people have difficulties using modern consumer products due to increased product complexity both in terms of functionality and interface design. Previous research has shown that older people have more difficulty in using complex devices intuitively when compared to the younger. Furthermore, increased life expectancy and a falling birth rate have been catalysts for changes in world demographics over the past two decades. This trend also suggests a proportional increase of older people in the work-force. This realisation has led to research on the effective use of technology by older populations in an effort to engage them more productively and to assist them in leading independent lives. Ironically, not enough attention has been paid to the development of interaction design strategies that would actually enable older users to better exploit new technologies. Previous research suggests that if products are designed to reflect people's prior knowledge, they will appear intuitive to use. Since intuitive interfaces utilise domain-specific prior knowledge of users, they require minimal learning for effective interaction. However, older people are very diverse in their capabilities and domain-specific prior knowledge. In addition, ageing also slows down the process of acquiring new knowledge. Keeping these suggestions and limitations in view, the aim of this study was set to investigate possible approaches to developing interfaces that facilitate their intuitive use by older people. In this quest to develop intuitive interfaces for older people, two experiments were conducted that systematically investigated redundancy (the use of both text and icons) in interface design, complexity of interface structure (nested versus flat), and personal user factors such as cognitive abilities, perceived self-efficacy and technology anxiety. All of these factors could interfere with intuitive use. The results from the first experiment suggest that, contrary to what was hypothesised, older people (65+ years) completed the tasks on the text only based interface design faster than on the redundant interface design. The outcome of the second experiment showed that, as expected, older people took more time on a nested interface. However, they did not make significantly more errors compared with younger age groups. Contrary to what was expected, older age groups also did better under anxious conditions. The findings of this study also suggest that older age groups are more heterogeneous in their capabilities and their intuitive use of contemporary technological devices is mediated more by domain-specific technology prior knowledge and by their cognitive abilities, than chronological age. This makes it extremely difficult to develop product interfaces that are entirely intuitive to use. However, by keeping in view the cognitive limitations of older people when interfaces are developed, and using simple text-based interfaces with flat interface structure, would help them intuitively learn and use complex technological products successfully during early encounter with a product. These findings indicate that it might be more pragmatic if interfaces are designed for intuitive learning rather than for intuitive use. Based on this research and the existing literature, a model for adaptable interface design as a strategy for developing intuitively learnable product interfaces was proposed. An adaptable interface can initially use a simple text only interface to help older users to learn and successfully use the new system. Over time, this can be progressively changed to a symbols-based nested interface for more efficient and intuitive use.