96 resultados para Onofri, Vincenzo, fl. 1500.


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Web data can often be represented in free tree form; however, free tree mining methods seldom exist. In this paper, a computationally fast algorithm FreeS is presented to discover all frequently occurring free subtrees in a database of labelled free trees. FreeS is designed using an optimal canonical form, BOCF that can uniquely represent free trees even during the presence of isomorphism. To avoid enumeration of false positive candidates, it utilises the enumeration approach based on a tree-structure guided scheme. This paper presents lemmas that introduce conditions to conform the generation of free tree candidates during enumeration. Empirical study using both real and synthetic datasets shows that FreeS is scalable and significantly outperforms (i.e. few orders of magnitude faster than) the state-of-the-art frequent free tree mining algorithms, HybridTreeMiner and FreeTreeMiner.

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There is an increase in the uptake of cloud computing services (CCS). CCS is adopted in the form of a utility, and it incorporates business risks of the service providers and intermediaries. Thus, the adoption of CCS will change the risk profile of an organization. In this situation, organisations need to develop competencies by reconsidering their IT governance structures to achieve a desired level of IT-business alignment and maintain their risk appetite to source business value from CCS. We use the resource-based theories to suggest that collaborative board oversight of CCS, competencies relating to CCS information and financial management, and a CCS-related continuous audit program can contribute to business process performance improvements and overall firm performance. Using survey data, we find evidence of a positive association between these IT governance considerations and business process performance. We also find evidence of positive association between business process performance improvements and overall firm performance. The results suggest that the suggested considerations on IT governance structures can contribute to CCS-related IT-business alignment and lead to anticipated business value from CCS. This study provides guidance to organizations on competencies required to secure business value from CCS.

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The concept of cloud computing services (CCS) is appealing to small and medium enterprises (SMEs). However, while there is a significant push by various authorities on SMEs to adopt the CCS, knowledge of the key considerations to adopt the CCS is very limited. We use the technology-organization-environment (TOE) framework to suggest that a strategic and incremental intent, understanding the organizational structure and culture, understanding the external factors, and consideration of the human resource capacity can contribute to sustainable business value from CCS. Using survey data, we find evidence of a positive association between these considerations and the CCS-related business objectives. We also find evidence of positive association between the CCS-related business objectives and CCS-related financial objectives. The results suggest that the proposed considerations can ensure sustainable business value from the CCS. This study provides guidance to SMEs on a path to adopting the CCS with the intention of a long-term commitment and achieving sustainable business value from these services.

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Identifying unusual or anomalous patterns in an underlying dataset is an important but challenging task in many applications. The focus of the unsupervised anomaly detection literature has mostly been on vectorised data. However, many applications are more naturally described using higher-order tensor representations. Approaches that vectorise tensorial data can destroy the structural information encoded in the high-dimensional space, and lead to the problem of the curse of dimensionality. In this paper we present the first unsupervised tensorial anomaly detection method, along with a randomised version of our method. Our anomaly detection method, the One-class Support Tensor Machine (1STM), is a generalisation of conventional one-class Support Vector Machines to higher-order spaces. 1STM preserves the multiway structure of tensor data, while achieving significant improvement in accuracy and efficiency over conventional vectorised methods. We then leverage the theory of nonlinear random projections to propose the Randomised 1STM (R1STM). Our empirical analysis on several real and synthetic datasets shows that our R1STM algorithm delivers comparable or better accuracy to a state-of-the-art deep learning method and traditional kernelised approaches for anomaly detection, while being approximately 100 times faster in training and testing.

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Volatility-hygroscopicity tandem differential mobility analyzer measurements were used to infer the composition of sub-100 nm diameter Southern Ocean marine aerosols at Cape Grim in November and December 2007. This study focuses on a short-lived high sea spray aerosol (SSA) event on 7–8 December with two externally mixed modes in the Hygroscopic Growth Factor (HGF) distributions (90% relative humidity (RH)), one at HGF > 2 and another at HGF~1.5. The particles with HGF > 2 displayed a deliquescent transition at 73–75% RH and were nonvolatile up to 280°C, which identified them as SSA particles with a large inorganic sea-salt fraction. SSA HGFs were 3–13% below those for pure sea-salt particles, indicating an organic volume fraction (OVF) of up to 11–46%. Observed high inorganic fractions in sub-100 nm SSA is contrary to similar, earlier studies. HGFs increased with decreasing particle diameter over the range 16–97 nm, suggesting a decreased OVF, again contrary to earlier studies. SSA comprised up to 69% of the sub-100 nm particle number, corresponding to concentrations of 110–290 cm−3. Air mass back trajectories indicate that SSA particles were produced 1500 km, 20–40 h upwind of Cape Grim. Transmission electron microscopy (TEM) and X-ray spectrometry measurements of sub-100 nm aerosols collected from the same location, and at the same time, displayed a distinct lack of sea salt. Results herein highlight the potential for biases in TEM analysis of the chemical composition of marine aerosols.

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Bactrocera tryoni (Froggatt) is Australia's major horticultural insect pest, yet monitoring females remains logistically difficult. We trialled the ‘Ladd trap’ as a potential female surveillance or monitoring tool. This trap design is used to trap and monitor fruit flies in countries other (e.g. USA) than Australia. The Ladd trap consists of a flat yellow panel (a traditional ‘sticky trap’), with a three dimensional red sphere (= a fruit mimic) attached in the middle. We confirmed, in field-cage trials, that the combination of yellow panel and red sphere was more attractive to B. tryoni than the two components in isolation. In a second set of field-cage trials, we showed that it was the red-yellow contrast, rather than the three dimensional effect, which was responsible for the trap's effectiveness, with B. tryoni equally attracted to a Ladd trap as to a two-dimensional yellow panel with a circular red centre. The sex ratio of catches was approximately even in the field-cage trials. In field trials, we tested the traditional red-sphere Ladd trap against traps for which the sphere was painted blue, black or yellow. The colour of sphere did not significantly influence trap efficiency in these trials, despite the fact the yellow-panel/yellow-sphere presented no colour contrast to the flies. In 6 weeks of field trials, over 1500 flies were caught, almost exactly two-thirds of them being females. Overall, flies were more likely to be caught on the yellow panel than the sphere; but, for the commercial Ladd trap, proportionally more females were caught on the red sphere versus the yellow panel than would be predicted based on relative surface area of each component, a result also seen the field-cage trial. We determined that no modification of the trap was more effective than the commercially available Ladd trap and so consider that product suitable for more extensive field testing as a B. tryoni research and monitoring tool.