994 resultados para enterprise activities


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Passive monitoring of large sites typically requires coordination between multiple cameras, which in turn requires methods for automatically relating events between distributed cameras. This paper tackles the problem of self-calibration of multiple cameras which are very far apart, using feature correspondences to determine the camera geometry. The key problem is finding such correspondences. Since the camera geometry and photometric characteristics vary considerably between images, one cannot use brightness and/or proximity constraints. Instead we apply planar geometric constraints to moving objects in the scene in order to align the scene"s ground plane across multiple views. We do not assume synchronized cameras, and we show that enforcing geometric constraints enables us to align the tracking data in time. Once we have recovered the homography which aligns the planar structure in the scene, we can compute from the homography matrix the 3D position of the plane and the relative camera positions. This in turn enables us to recover a homography matrix which maps the images to an overhead view. We demonstrate this technique in two settings: a controlled lab setting where we test the effects of errors in internal camera calibration, and an uncontrolled, outdoor setting in which the full procedure is applied to external camera calibration and ground plane recovery. In spite of noise in the internal camera parameters and image data, the system successfully recovers both planar structure and relative camera positions in both settings.

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A series of nano-sized Ni/Al2O3 and Ni/La-Al2O3 catalysts that possess high activities for NH3 decomposition have been successfully synthesized by a coprecipitation method. The catalytic performance was investigated under the atmospheric conditions and a significant enhancement in the activity after the introduction of La was observed. Aiming to study the influence of La promoter on the physicochemical properties, we characterized the catalysts by N-2 adsorption/desorption, XRD, H-2-TPR, chemisorption and TEM techniques. Physisorption results suggested a high specific surface area and XRD spectra showed that nickel particles are in a highly dispersed state. A combination of XRD, TEM and chemisorption showed that Ni-0 particles with the average size lower, than 5.0 nm are always obtained even though the Ni loading ranged widely from 4 to 63 %. Compared with the Ni/Al2O3 catalysts, the Ni/La-Al2O3 ones with an appropriate amount of promoter enjoy a more open mesoporous structure and higher dispersion of Ni. Reduction kinetic studies of prepared catalysts were investigated by temperature-programmed reduction (TPR) method and the fact that La additive partially destroyed the metastable Ni-Al mixed oxide phase was detailed. (c) 2005 Elsevier B.V. All rights reserved.

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Gilmore, A.; Gallagher, D.; and Henry, S. (2007). E-marketing and SMEs: Operational lessons for the future. European Business Review. 19(3), pp.234-247 RAE2008

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Igor E. Moshkov, Galina V. Novikova, Luis A.J. Mur, Aileen R. Smith, and Michael A. Hall. (2003). Ethylene rapidly up-regulates the activities of both monomeric GTP-binding proteins and protein kinase(s) in epicotyls of pea. Plant Physiology, 131(4), 1718-1726 RAE2008

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Dissertação de Mestrado apresentada à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Mestre em Ciências Empresariais.

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This report demonstrates that religion among U.S. adolescents is positively related to participation in constructive youth activities. In addition, those who participate in religious activities seem to be less likely to participate in many delinquent and risk behaviors.

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http://www.archive.org/details/divineenterprise00pieruoft

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http://www.archive.org/details/upontheearththem013276mbp

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Seaweeds contain a range of antioxidant compounds such as polyphenols, carotenoids, sulphated polysaccharides and vitamins and have the potential to be used as ingredients in neutraceuticals. The antioxidant activity of crude 60% methanol extracts prepared from five Irish seaweeds, Ascophyllum nodosum, Laminaria hyperborea, Pelvetia canaliculata, Fucus vesiculosus and Fucus serratus were examined using in-vitro assays and a cell model system to determine the antioxidant activity of the extracts and their ability to protect against H2O2 and tert-BOOH-induced DNA damage and alterations in cellular antioxidant status in the human adenocarcinoma, Caco-2 cell line. To optimise the extraction of antioxidant compounds from seaweeds, an accelerated solvent extraction (ASE®) was used in combination with food grade solvents. The antioxidant activity of these extracts against H2O2 and tert-BOOH-induced DNA damage and alterations in cellular antioxidant status was also assessed. Extracts that exhibited the highest antioxidant activity, A. nodosum (100% water and 80% ethanol extracts) and F. vesiculosus (60% ethanol extract) were selected as ingredients for incorporation into fluid milk and yogurt at concentrations of 0.25% and 0.5%. The addition of the seaweed extracts to milk and yogurt did not affect the pH or shelf-life properties of the products. Seaweed addition did however significantly influence the colour properties of the milk and yogurt. Yellowness values were significantly higher in yogurts containing F. vesiculosus at both concentrations and A. nodosum (80% ethanol) at the 0.5% concentration. In milk, the F. vesiculosus (60% ethanol) and A. nodosum (80% ethanol) at both the 0.25% and the 0.5% concentrations had higher greenness and yellowness values than the milk containing A. nodosum (100% water). Sensory analysis revealed that appearance and flavour governed the overall acceptability of yogurts with the control yogurt, and yogurts containing A. nodosum (100% water) were the most preferred samples by panellists. However, in the milk trial the perception of a fishy taste was the determining factor in the negative perception of milk. The unsupplemented control and the milk containing A. nodosum (100% water) at a concentration of 0.5% were the most overall accepted milk samples by the sensory panellists. The antioxidant activity of the extracts in milk and yogurt remained stable during storage as determined by the in-vitro assays. Seaweed supplemented milk and yogurt were also subjected to an in-vitro digestion procedure which mimics the human digestive system. The milk and yogurt samples and their digestates were added to Caco-2 cells to investigate their antioxidant potential however neither the undigested or digested samples protected against H2O2-induced DNA damage in Caco-2 cells.

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In this study, marine sponges collected in Irish waters were analysed for their associated microbiota. Of the approximately 240 bacterial isolates obtained from two sponges several showed antimicrobial activity; among them members of genera which have rarely been shown to produce antimicrobial compounds. Differences observed from the sponge-derived groups of isolates in terms of bioactivity suggests that S. carnosus isolates may be a better source of antibacterial compounds, while Leucosolenia sp. isolates appear to be a better source of antifungal compounds. More than 60% of fungal isolates obtained from 12 sponge samples proved to be bioactive. One of the isolates, which was closely related to Fusarium oxysporum and showed activity against bacteria and fungi, was investigated for its secondary metabolite genes. At least 5 different NRPS genes, with a sequence similarity as low as 50 % to known genes, were identified highlighting the likelihood that this isolate may be capable of producing novel secondary metabolites. A Micromonospora sp. was isolated from a Haliclona simulans sample collected in Irish waters. The isolate inhibited the growth of Gram positive bacterial test strains in three different antimicrobial assays. Employing preparative layer chromatography the compound responsible for the bioactivity could be isolated. According to LC-MS andNMR data the bioactive compound could indeed be novel. Finally, two deep water sponges were shown to host a remarkably different bacterial and archaeal diversity by application of 454 Pyrosequencing. The L. diversichela –proteobacterial community was dominated by a single ƴ-proteobacterial bacterium whereas the S. normani sample hosted a largely sponge specific microbial community, even more diverse than has been previously reported for shallow water sponges. Organisms potentially involved in nitrification, sulphate reduction and secondary metabolite production were found to be spatially distributed in the sponge. Furthermore, a deep sea specific population was implied.

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Aim: This thesis examines a question posed by founding occupational scientist Dr. Elizabeth Yerxa (1993) – “what is the relationship between human engagement in a daily round of activity (such as work, play, rest and sleep) and the quality of life people experience including their healthfulness” (p. 3). Specifically, I consider Yerxa’s question in relation to the quotidian activities and health-related quality of life (HRQoL) of late adolescents (aged 15 - 19 years) in Ireland. This research enquiry was informed by an occupational perspective of health and by population health, ecological, and positive youth development perspectives. Methods: This thesis is comprised of five studies. Two scoping literature reviews informed the direction of three empirical studies. In the latter, cross-sectional time use and HRQoL data were collected from a representative sample of 731 school-going late adolescents (response rate 52%) across 28 schools across Cork city and county (response rate 76%). In addition to socio-demographic data, time use data were collected using a standard time diary instrument while a nationally and internationally validated instrument, the KIDSCREEN-52, was used to measure HRQoL. Variable-centred and person-centred analyses were used. Results: The scoping reviews identified the lack of research on well populations or an adolescent age range within occupational therapy and occupational science; limited research testing the popular assumption that time use is related to overall well-being and quality of life; and the absence of studies that examined adolescent 24-hour time use and quality of life. Established international trends were mirrored in the findings of the examination of weekday and weekend time use. Aggregate-level, variable-centred analyses yielded some significant associations between HRQoL and individual activities, independent of school year, school location, family context, social class, nationality or diary day. The person-centred analysis of overall time use identified three male profiles (productive, high leisure and all-rounder) and two female profiles (higher study/lower leisure and moderate study/higher leisure). There was tentative support for the association between higher HRQoL and more balanced time use profiles. Conclusion: The findings of this thesis highlight the gendered nature of adolescent time use and HRQoL. Participation in daily activities, singly and in combination, appears to be associated with HRQoL. However, the nature of this relationship is complex. Individually and collectively, adolescents need to be educated and supported to create health through their everyday patterns of doing.

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An enterprise information system (EIS) is an integrated data-applications platform characterized by diverse, heterogeneous, and distributed data sources. For many enterprises, a number of business processes still depend heavily on static rule-based methods and extensive human expertise. Enterprises are faced with the need for optimizing operation scheduling, improving resource utilization, discovering useful knowledge, and making data-driven decisions.

This thesis research is focused on real-time optimization and knowledge discovery that addresses workflow optimization, resource allocation, as well as data-driven predictions of process-execution times, order fulfillment, and enterprise service-level performance. In contrast to prior work on data analytics techniques for enterprise performance optimization, the emphasis here is on realizing scalable and real-time enterprise intelligence based on a combination of heterogeneous system simulation, combinatorial optimization, machine-learning algorithms, and statistical methods.

On-demand digital-print service is a representative enterprise requiring a powerful EIS.We use real-life data from Reischling Press, Inc. (RPI), a digit-print-service provider (PSP), to evaluate our optimization algorithms.

In order to handle the increase in volume and diversity of demands, we first present a high-performance, scalable, and real-time production scheduling algorithm for production automation based on an incremental genetic algorithm (IGA). The objective of this algorithm is to optimize the order dispatching sequence and balance resource utilization. Compared to prior work, this solution is scalable for a high volume of orders and it provides fast scheduling solutions for orders that require complex fulfillment procedures. Experimental results highlight its potential benefit in reducing production inefficiencies and enhancing the productivity of an enterprise.

We next discuss analysis and prediction of different attributes involved in hierarchical components of an enterprise. We start from a study of the fundamental processes related to real-time prediction. Our process-execution time and process status prediction models integrate statistical methods with machine-learning algorithms. In addition to improved prediction accuracy compared to stand-alone machine-learning algorithms, it also performs a probabilistic estimation of the predicted status. An order generally consists of multiple series and parallel processes. We next introduce an order-fulfillment prediction model that combines advantages of multiple classification models by incorporating flexible decision-integration mechanisms. Experimental results show that adopting due dates recommended by the model can significantly reduce enterprise late-delivery ratio. Finally, we investigate service-level attributes that reflect the overall performance of an enterprise. We analyze and decompose time-series data into different components according to their hierarchical periodic nature, perform correlation analysis,

and develop univariate prediction models for each component as well as multivariate models for correlated components. Predictions for the original time series are aggregated from the predictions of its components. In addition to a significant increase in mid-term prediction accuracy, this distributed modeling strategy also improves short-term time-series prediction accuracy.

In summary, this thesis research has led to a set of characterization, optimization, and prediction tools for an EIS to derive insightful knowledge from data and use them as guidance for production management. It is expected to provide solutions for enterprises to increase reconfigurability, accomplish more automated procedures, and obtain data-driven recommendations or effective decisions.