985 resultados para Open Addressing Hash Table


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The effect of an edible film obtained from a commercial Aloe vera extract, on the quality maintenance of minimally processed grapes belonging to three different cultivars (Sugar One, Victoria and Black Magic) was evaluated by enzymatic (PPO, PME, β-GAL), physicochemical (pH, acidity, °Brix), and sensorial methods. All the analyzed parameters were measured in extracts obtained from minimally processed grapes packaged in ordinary atmosphere and stored at 4 °C for 15 days. Samples dipped into Aloe vera showed significant differences (p≤0.05) compared to untreated ones. The determination of such parameters and the evaluation of consumer acceptability were helpful to determine the effectiveness of the post-harvest treatment with Aloe vera for a storage period of 15 days.

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This thesis presented the overview of Open Data research area, quantity of evidence and establishes the research evidence based on the Systematic Mapping Study (SMS). There are 621 such publications were identified published between years 2005 and 2014, but only 243 were selected in the review process. This thesis highlights the implications of Open Data principals’ proliferation in the emerging era of the accessibility, reusability and sustainability of data transparency. The findings of mapping study are described in quantitative and qualitative measurement based on the organization affiliation, countries, year of publications, research method, star rating and units of analysis identified. Furthermore, units of analysis were categorized by development lifecycle, linked open data, type of data, technical platforms, organizations, ontology and semantic, adoption and awareness, intermediaries, security and privacy and supply of data which are important component to provide a quality open data applications and services. The results of the mapping study help the organizations (such as academia, government and industries), re-searchers and software developers to understand the existing trend of open data, latest research development and the demand of future research. In addition, the proposed conceptual framework of Open Data research can be adopted and expanded to strengthen and improved current open data applications.

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Syksy Räsänen's presentation at Kirjastoverkkopäivät, Helsinki 21.10.2015.

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Kai Karin Geschun's presentation at Kirjastoverkkopäivät, Helsinki 21.10.2015.

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Globalization and interconnectedness in the worldwide sphere have changed the existing and prevailing modus operandi of organizations around the globe and have challenged existing practices along with the business as usual mindset. There are no rules in terms of creating a competitive advantage and positioning within an unstable, constantly changing and volatile globalized business environment. The financial industry, the locomotive or the flagship industry of global economy, especially, within the aftermath of the financial crisis, has reached a certain point trying to recover and redefine its strategic orientation and positioning within the global business arena. Innovation has always been a trend and a buzzword and by many has been considered as the ultimate answer to any kind of problem. The mantra Innovate or Die has been prevailing in any organizational entity in a, sometimes, ruthless endeavour to develop cutting-edge products and services and capture a landmark position in the market. The emerging shift from a closed to an open innovation paradigm has been considered as new operational mechanism within the management and leadership of the company of the future. To that respect, open innovation has been experiencing a tremendous growth research trajectory by putting forward a new way of exchanging and using surplus knowledge in order to sustain innovation within organizations and in the level of industry. In the abovementioned reality, there seems to be something missing: the human element. This research, by going beyond the traditional narratives for open innovation, aims at making an innovative theoretical and managerial contribution developed and grounded on the on-going discussion regarding the individual and organizational barriers to open innovation within the financial industry. By functioning across disciplines and researching out to primary data, it debunks the myth that open innovation is solely a knowledge inflow and outflow mechanism and sheds light to the understanding on the why and the how organizational open innovation works by enlightening the broader dynamics and underlying principles of this fascinating paradigm. Little attention has been given to the role of the human element, the foundational pre-requisite of trust encapsulated within the precise and fundamental nature of organizing for open innovation, the organizational capabilities, the individual profiles of open innovation leaders, the definition of open innovation in the realms of the financial industry, the strategic intent of the financial industry and the need for nurturing a societal impact for human development. To that respect, this research introduces the trust-embedded approach to open innovation as a new insightful way of organizing for open innovation. It unveils the peculiarities of the corporate and individual spheres that act as a catalyst towards the creation of productive open innovation activities. The incentive of this research captures the fundamental question revolving around the need for financial institutions to recognise the importance for organizing for open innovation. The overarching question is why and how to create a corporate culture of openness in the financial industry, an organizational environment that can help open innovation excel. This research shares novel and cutting edge outcomes and propositions both under the prism of theory and practice. The trust-embedded open innovation paradigm captures the norms and narratives around the way of leading open innovation within the 21st century by cultivating a human-centricity mindset that leads to the creation of human organizations, leaving behind the dehumanization mindset currently prevailing within the financial industry.

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New emerging technologies in the recent decade have brought new options to cross platform computer graphics development. This master thesis took a look for cross platform 3D graphics development possibilities. All platform dependent and non real time solutions were excluded. WebGL and two different OpenGL based solutions were assessed via demo application by using most recent development tools. In the results pros and cons of the each solutions were noted.

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Castor bean fruits are already used for biodiesel production but obtaining quality seeds is still a challenge. Seed cleaning improves lot quality but little is known about the effects of upgrading castor bean seed lots on a densimetric table. The objective of this study was to evaluate the influence of cleaning castor bean seed lots on a densimetric table on their physical, physiological and sanitary characteristics. Two commercial lots of the AL Guarani 2002 cultivar, separated into five categories according to their classification on a densimetric table (uncleaned and low, low intermediate, high intermediate and high outlets), were evaluated. Tests for the yield, one-thousand seed weight, germination, seedling emergence, electrical conductivity and seed health were performed. The classification of castor bean seeds on a densimetric table significantly improved the physical, physiological and sanitary quality of commercial seed lots. The physiological response of the different classified lots varied according to their initial weight. Castor bean seeds separated on a densimetric table for the upper outlet showed a better physical, physiological and sanitary quality compared to those for the lower outlet.

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In the new age of information technology, big data has grown to be the prominent phenomena. As information technology evolves, organizations have begun to adopt big data and apply it as a tool throughout their decision-making processes. Research on big data has grown in the past years however mainly from a technical stance and there is a void in business related cases. This thesis fills the gap in the research by addressing big data challenges and failure cases. The Technology-Organization-Environment framework was applied to carry out a literature review on trends in Business Intelligence and Knowledge management information system failures. A review of extant literature was carried out using a collection of leading information system journals. Academic papers and articles on big data, Business Intelligence, Decision Support Systems, and Knowledge Management systems were studied from both failure and success aspects in order to build a model for big data failure. I continue and delineate the contribution of the Information System failure literature as it is the principal dynamics behind technology-organization-environment framework. The gathered literature was then categorised and a failure model was developed from the identified critical failure points. The failure constructs were further categorized, defined, and tabulated into a contextual diagram. The developed model and table were designed to act as comprehensive starting point and as general guidance for academics, CIOs or other system stakeholders to facilitate decision-making in big data adoption process by measuring the effect of technological, organizational, and environmental variables with perceived benefits, dissatisfaction and discontinued use.

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In the new age of information technology, big data has grown to be the prominent phenomena. As information technology evolves, organizations have begun to adopt big data and apply it as a tool throughout their decision-making processes. Research on big data has grown in the past years however mainly from a technical stance and there is a void in business related cases. This thesis fills the gap in the research by addressing big data challenges and failure cases. The Technology-Organization-Environment framework was applied to carry out a literature review on trends in Business Intelligence and Knowledge management information system failures. A review of extant literature was carried out using a collection of leading information system journals. Academic papers and articles on big data, Business Intelligence, Decision Support Systems, and Knowledge Management systems were studied from both failure and success aspects in order to build a model for big data failure. I continue and delineate the contribution of the Information System failure literature as it is the principal dynamics behind technology-organization-environment framework. The gathered literature was then categorised and a failure model was developed from the identified critical failure points. The failure constructs were further categorized, defined, and tabulated into a contextual diagram. The developed model and table were designed to act as comprehensive starting point and as general guidance for academics, CIOs or other system stakeholders to facilitate decision-making in big data adoption process by measuring the effect of technological, organizational, and environmental variables with perceived benefits, dissatisfaction and discontinued use.