84 resultados para Nearest Neighbour


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Capacity probability models of generating units are commonly used in many power system reliability studies, at hierarchical level one (HLI). Analytical modelling of a generating system with many units or generating units with many derated states in a system, can result in an extensive number of states in the capacity model. Limitations on available memory and computational time of present computer facilities can pose difficulties for assessment of such systems in many studies. A cluster procedure using the nearest centroid sorting method was used for IEEE-RTS load model. The application proved to be very effective in producing a highly similar model with substantially fewer states. This paper presents an extended application of the clustering method to include capacity probability representation. A series of sensitivity studies are illustrated using IEEE-RTS generating system and load models. The loss of load and energy expectations (LOLE, LOEE), are used as indicators to evaluate the application

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Topic recommendation can help users deal with the information overload issue in micro-blogging communities. This paper proposes to use the implicit information network formed by the multiple relationships among users, topics and micro-blogs, and the temporal information of micro-blogs to find semantically and temporally relevant topics of each topic, and to profile users' time-drifting topic interests. The Content based, Nearest Neighborhood based and Matrix Factorization models are used to make personalized recommendations. The effectiveness of the proposed approaches is demonstrated in the experiments conducted on a real world dataset that collected from Twitter.com.

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Carrion-breeding Sarcophagidae (Diptera) can be used to estimate the post-mortem interval (PMI) in forensic cases. Difficulties with accurate morphological identifications at any life stage and a lack of documented thermobiological profiles have limited their current usefulness of these flies. The molecular-based approach of DNA barcoding, which utilises a 648-bp fragment of the mitochondrial cytochrome oxidase subunit I gene, was previously evaluated in a pilot study for the discrimination between 16 Australian sarcophagids. The current study comprehensively evaluated DNA barcoding on a larger taxon set of 588 adult Australian sarcophagids. A total of 39 of the 84 known Australian species were represented by 580 specimens, which includes 92% of potentially forensically important species. A further eight specimens could not be reliably identified, but included as six unidentifable taxa. A neighbour-joining phylogenetic tree was generated and nucleotide sequence divergences were calculated using the Kimura-two-parameter distance model. All species except Sarcophaga (Fergusonimyia) bancroftorum, known for high morphological variability, were resolved as reciprocally monophyletic (99.2% of cases), with most having bootstrap support of 100. Excluding S. bancroftorum, the mean intraspecific and interspecific variation ranged from 0.00-1.12% and 2.81-11.23%, respectively, allowing for species discrimination. DNA barcoding was therefore validated as a suitable method for the molecular identification of the Australian Sarcophagidae, which will aid in the implementation of this fauna in forensic entomology.

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Smartphones are getting increasingly popular and several malwares appeared targeting these devices. General countermeasures to smartphone malwares are currently limited to signature-based antivirus scanners which efficiently detect known malwares, but they have serious shortcomings with new and unknown malwares creating a window of opportunity for attackers. As smartphones become host for sensitive data and applications, extended malware detection mechanisms are necessary complying with the corresponding resource constraints. The contribution of this paper is twofold. First, we perform static analysis on the executables to extract their function calls in Android environment using the command readelf. Function call lists are compared with malware executables for classifying them with PART, Prism and Nearest Neighbor Algorithms. Second, we present a collaborative malware detection approach to extend these results. Corresponding simulation results are presented.

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Currently, recommender systems (RS) have been widely applied in many commercial e-commerce sites to help users deal with the information overload problem. Recommender systems provide personalized recommendations to users and thus help them in making good decisions about which product to buy from the vast number of product choices available to them. Many of the current recommender systems are developed for simple and frequently purchased products like books and videos, by using collaborative-filtering and content-based recommender system approaches. These approaches are not suitable for recommending luxurious and infrequently purchased products as they rely on a large amount of ratings data that is not usually available for such products. This research aims to explore novel approaches for recommending infrequently purchased products by exploiting user generated content such as user reviews and product click streams data. From reviews on products given by the previous users, association rules between product attributes are extracted using an association rule mining technique. Furthermore, from product click streams data, user profiles are generated using the proposed user profiling approach. Two recommendation approaches are proposed based on the knowledge extracted from these resources. The first approach is developed by formulating a new query from the initial query given by the target user, by expanding the query with the suitable association rules. In the second approach, a collaborative-filtering recommender system and search-based approaches are integrated within a hybrid system. In this hybrid system, user profiles are used to find the target user’s neighbour and the subsequent products viewed by them are then used to search for other relevant products. Experiments have been conducted on a real world dataset collected from one of the online car sale companies in Australia to evaluate the effectiveness of the proposed recommendation approaches. The experiment results show that user profiles generated from user click stream data and association rules generated from user reviews can improve recommendation accuracy. In addition, the experiment results also prove that the proposed query expansion and the hybrid collaborative filtering and search-based approaches perform better than the baseline approaches. Integrating the collaborative-filtering and search-based approaches has been challenging as this strategy has not been widely explored so far especially for recommending infrequently purchased products. Therefore, this research will provide a theoretical contribution to the recommender system field as a new technique of combining collaborative-filtering and search-based approaches will be developed. This research also contributes to a development of a new query expansion technique for infrequently purchased products recommendation. This research will also provide a practical contribution to the development of a prototype system for recommending cars.

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Introduction: There is a recognised relationship between dry weather conditions and increased risk of anterior cruciate ligament (ACL) injury. Previous studies have identified 28 day evaporation as an important weather-based predictor of non-contact ACL injuries in professional Australian Football League matches. The mechanism of non-contact injury to the ACL is believed to increased traction and impact forces between footwear and playing surface. Ground hardness and the amount and quality of grass are factors that would most likely influence this and are inturn, related to the soil moisture content and prevailing weather conditions. This paper explores the relationship between soil moisture content, preceding weather conditions and the Clegg Soil Impact Test (CSIT) which is an internationally recognised standard measure of ground hardness for sports fields. Methodology: The 2.25 kg Clegg Soil Impact Test and a pair of 12 cm soil moisture probes were used to measure ground hardness and percentage moisture content. Five football fields were surveyed at 13 prescribed sites just before seven football matches from October 2008 to January 2009 (an FC Women’s WLeague team). Weather conditions recorded at the nearest weather station were obtained from the Bureau of Meteorology website and total rainfall less evaporation was calculated for 7 and 28 days prior to each match. All non-contact injuries occurring during match play and their location on the field were recorded. Results/conclusions: Ground hardness varied between CSIT 5 and 17 (x10G) (8 is considered a good value for sports fields). Variations within fields were typically greatest in the centre and goal areas. Soil moisture ranged from 3 to 40% with some fields requiring twice the moisture content of others to maintain similar CSIT values. There was a non-linear, negative relationship for ground hardness versus moisture content and a linear relationship with weather (R2, of 0.30 and 0.34, respectively). Three non-contact ACL injuries occurred during the season. Two of these were associated with hard and variable ground conditions.

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Objective: To perform a 1-stage meta-analysis of genome-wide association studies (GWAS) of multiple sclerosis (MS) susceptibility and to explore functional consequences of new susceptibility loci. Methods: We synthesized 7 MS GWAS. Each data set was imputed using HapMap phase II, and a per single nucleotide polymorphism (SNP) meta-analysis was performed across the 7 data sets. We explored RNA expression data using a quantitative trait analysis in peripheral blood mononuclear cells (PBMCs) of 228 subjects with demyelinating disease. Results: We meta-analyzed 2,529,394 unique SNPs in 5,545 cases and 12,153 controls. We identified 3 novel susceptibility alleles: rs170934T at 3p24.1 (odds ratio [OR], 1.17; p ¼ 1.6 � 10�8) near EOMES, rs2150702G in the second intron of MLANA on chromosome 9p24.1 (OR, 1.16; p ¼ 3.3 � 10�8), and rs6718520A in an intergenic region on chromosome 2p21, with THADA as the nearest flanking gene (OR, 1.17; p ¼ 3.4 � 10�8). The 3 new loci do not have a strong cis effect on RNA expression in PBMCs. Ten other susceptibility loci had a suggestive p < 1 � 10�6, some of these loci have evidence of association in other inflammatory diseases (ie, IL12B, TAGAP, PLEK, and ZMIZ1). Interpretation: We have performed a meta-analysis of GWAS in MS that more than doubles the size of previous gene discovery efforts and highlights 3 novel MS susceptibility loci. These and additional loci with suggestive evidence of association are excellent candidates for further investigations to refine and validate their role in the genetic architecture of MS.

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Automated crowd counting has become an active field of computer vision research in recent years. Existing approaches are scene-specific, as they are designed to operate in the single camera viewpoint that was used to train the system. Real world camera networks often span multiple viewpoints within a facility, including many regions of overlap. This paper proposes a novel scene invariant crowd counting algorithm that is designed to operate across multiple cameras. The approach uses camera calibration to normalise features between viewpoints and to compensate for regions of overlap. This compensation is performed by constructing an 'overlap map' which provides a measure of how much an object at one location is visible within other viewpoints. An investigation into the suitability of various feature types and regression models for scene invariant crowd counting is also conducted. The features investigated include object size, shape, edges and keypoints. The regression models evaluated include neural networks, K-nearest neighbours, linear and Gaussian process regresion. Our experiments demonstrate that accurate crowd counting was achieved across seven benchmark datasets, with optimal performance observed when all features were used and when Gaussian process regression was used. The combination of scene invariance and multi camera crowd counting is evaluated by training the system on footage obtained from the QUT camera network and testing it on three cameras from the PETS 2009 database. Highly accurate crowd counting was observed with a mean relative error of less than 10%. Our approach enables a pre-trained system to be deployed on a new environment without any additional training, bringing the field one step closer toward a 'plug and play' system.

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A key challenge for the 21st Century is to make our cities more liveable and foster economically sustainable, environmentally responsible, and socially inclusive communities. Design thinking, particularly a human-centred approach, offers a way to tackle this challenge. Findings from two recent Australian research projects highlight how facilitating sustainable, liveable communities in a humid sub-tropical environment requires an in-depth understanding of people’s perspectives, experiences and practices. Project 1 (‘Research House’) documents the reflections of a family who lived in a ‘test’ sustainable house for two years, outlining their experience and evaluations of universal design and sustainable technologies. The study family was very impressed with the natural lighting, natural ventilation, spaciousness and ease of access, which contributed significantly to their comfort and the liveability of their home. Project 2 (‘Inner-Urban High Density Living’) explored Brisbane residents’ opinions about high-density living, through a survey (n=636), interviews (n=24), site observations (over 300 hours) and environmental monitoring, assessing opinions on the liveability of their individual dwelling, the multi-unit host building and the surrounding neighbourhood. Nine areas, categorised into three general domains, were identified as essential for enhancing high density liveability. In terms of the dwelling, thermal comfort/ventilation, natural light, noise mitigation were important; shared space, good neighbour protocols, and support for environmentally sustainable behaviour were desired in the building/complex; and accessible/sustainable transport, amenities and services, sense of community were considered important in the surrounding neighbourhood. Combined, these findings emphasise the importance and complexity associated with designing liveable building, cities and communities, illustrating how adopting a design thinking, human-centred approach will help create sustainable communities that will meet the needs of current and future generations.

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This paper shows how multiple interconnected microgrids can operate in autonomous mode in a self–healing medium voltage network. This is possible if based on network self– healing capability, the neighbour microgrids are interconnected and a surplus generation capacity is available in some of the Distributed Energy Resources (DERs) of the interconnected microgrids. This will reduce or prevent load shedding within the microgrids with less generation capacity. Therefore, DERs in a microgrid are controlled such that they share the local load within that microgrid as well as the loads in other interconnected microgrids. Different control algorithms are proposed to manage the DERs at different operating conditions. On the other hand, a Distribution Static Compensator (DSTATCOM) is employed to regulate the voltage. The efficacy of the proposed power control, sharing and management among DERs in multiple interconnected microgrids is validated through extensive simulation studies using PSCAD/EMTDC.

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To minimise the number of load sheddings in a microgrid (MG) during autonomous operation, islanded neighbour MGs can be interconnected if they are on a self-healing network and an extra generation capacity is available in the distributed energy resources (DER) of one of the MGs. In this way, the total load in the system of interconnected MGs can be shared by all the DERs within those MGs. However, for this purpose, carefully designed self-healing and supply restoration control algorithm, protection systems and communication infrastructure are required at the network and MG levels. In this study, first, a hierarchical control structure is discussed for interconnecting the neighbour autonomous MGs where the introduced primary control level is the main focus of this study. Through the developed primary control level, this study demonstrates how the parallel DERs in the system of multiple interconnected autonomous MGs can properly share the load of the system. This controller is designed such that the converter-interfaced DERs operate in a voltage-controlled mode following a decentralised power sharing algorithm based on droop control. DER converters are controlled based on a per-phase technique instead of a conventional direct-quadratic transformation technique. In addition, linear quadratic regulator-based state feedback controllers, which are more stable than conventional proportional integrator controllers, are utilised to prevent instability and weak dynamic performances of the DERs when autonomous MGs are interconnected. The efficacy of the primary control level of the DERs in the system of multiple interconnected autonomous MGs is validated through the PSCAD/EMTDC simulations considering detailed dynamic models of DERs and converters.

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In urban scholarship Master Planned Estates (MPEs) are viewed as illustrative of broader changes to the urban environment and characterised as homogenous, affluent enclaves where community life is largely orchestrated by the developer. Yet no study has fully considered if, and to what extent, MPEs can be distinguished from other suburb types in terms of their residential composition and their levels of sociability and community attachment. In this article, we empirically test if MPEs are different from ‘conventional’ suburbs by examining them structurally in terms of their demographic and socio-economic characteristics, as well as in terms of their key community social processes. Using data from a 2008 study of 148 suburbs across Brisbane, Australia (which includes data from two MPEs), we undertake a comparative analysis of suburbs and examine the density of neighbour networks, residents' reports of place attachment and cohesion and neighbourly contact in MPEs compared to other residential suburbs. Our findings suggest that MPEs are not distinct in terms of their degree of homogeneity and socio-economic characteristics, but that connections among residents are lower than other suburbs despite—or perhaps because of—the active interventions of the developer.

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Antechinus argentus sp. nov. is currently only known from the plateau at the eastern escarpment of Kroombit Tops National Park, about 400km NNW of Brisbane and 60km SSW of Gladstone, south-east Queensland, Australia. Antechinus flavipes (Waterhouse) is also known from Kroombit Tops NP, 4.5km W of the nearest known population of A. argentus; A. mysticus Baker, Mutton and Van Dyck has yet to be found within Kroombit Tops, but is known from museum specimens taken at Bulburin NP, just 40km ESE, as well as extant populations about 400km to both the south-east and north-west of Kroombit NP. A. argentus can be easily distinguished in the field, having an overall silvery/grey appearance with much paler silver feet and drabber deep greyish-olive rump than A. flavipes, which has distinctive yellow-orange toned feet, rump and tail-base; A. argentus fur is also less coarse than that of A. flavipes. A. argentus has a striking silver-grey head, neck and shoulders, with pale, slightly broken eye-rings, which distinguish it from A. mysticus which has a more subtle greyish-brown head, pale buff dabs of eyeliner and more colourful brownish-yellow rump. Features of the dentary can also be used for identification: A. argentus differs from A. flavipes in having smaller molar teeth, as well as a narrower and smaller skull and from A. mysticus in having on average a narrower snout, smaller skull and dentary lengths and smaller posterior palatal vacuities in the skull. A. argentus is strongly divergent genetically (at mtDNA) from both A. flavipes (9.0–11.2%) and A. mysticus (7.2–7.5%), and forms a very strongly supported clade to the exclusion of all other antechinus species, in both mtDNA and combined (mtDNA and nDNA) phylogenies inferred here. We are yet to make detailed surveys in search of A. argentus from forested areas to the immediate east and north of Kroombit Tops. However, A. mysticus has only been found at these sites in low densities in decades past and not at all in several recent trapping expeditions conducted by the authors. With similar habitat types in close geographic proximity, it is plausible that A. argentus may be found outside Kroombit. Nevertheless, it is striking that from a range of surveys conducted at Kroombit Tops in the last 15 years and intensive surveys by the authors in the last 3 years, totalling more than 5 080 trap nights, just 13 A. argentus have been captured from two sites less than 6 km apart. If this is even close to the true geographic extent of the species, it would possess one of the smallest distributions of an Australian mammal species. With several threats identified, we tentatively recommend that A. argentus be listed as Endangered, pending an exhaustive trapping survey of Kroombit and surrounds.

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In order to minimize the number of load shedding in a Microgrid during autonomous operation, islanded neighbour microgrids can be interconnected if they are on a self-healing network and an extra generation capacity is available in Distributed Energy Resources (DER) in one of the microgrids. In this way, the total load in the system of interconnected microgrids can be shared by all the DERs within these microgrids. However, for this purpose, carefully designed self-healing and supply restoration control algorithm, protection systems and communication infrastructure are required at the network and microgrid levels. In this chapter, first a hierarchical control structure is discussed for interconnecting the neighbour autonomous microgrids where the introduced primary control level is the main focus. Through the developed primary control level, it demonstrates how the parallel DERs in the system of multiple interconnected autonomous microgrids can properly share the load in the system. This controller is designed such that the converter-interfaced DERs operate in a voltage-controlled mode following a decentralized power sharing algorithm based on droop control. The switching in the converters is controlled using a linear quadratic regulator based state feedback which is more stable than conventional proportional integrator controllers and this prevents instability among parallel DERs when two microgrids are interconnected. The efficacy of the primary control level of DERs in the system of multiple interconnected autonomous microgrids is validated through simulations considering detailed dynamic models of DERs and converters.

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Dispute resolution in strata schemes in Peninsular Malaysia should focus on more than just "settlement." The quality of the outcome, its sustainability and its relevance in supporting the basic principles of a good neighbourhood and self-governance in a strata scheme are also fundamental. Based on the comprehensive law movement, this thesis develops a theoretical framework for strata scheme disputes within the parameters of therapeutic jurisprudence, preventive law, alternative dispute resolution (ADR) and problem-solving courts. The therapeutic orientation of this model offers approaches that promote positive communication between disputing parties, preserve neighbour relations and optimise people's psychological and emotional well-being.