426 resultados para software creation methodology


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Design based research (DBR) is an appropriate method for small scale educational research projects involving collaboration between teachers, students and researchers. It is particularly useful in collaborative projects where an intervention is implemented and evaluated in a grounded context. The intervention can be technological, or a new program required by policy changes. It can be applied to educational contexts, such as when English teachers undertake higher degree research projects in their own or others’ sites; or for academics working collaboratively as researchers with teams of teachers. In the case described here the paper shows that DBR is designed to make a difference in the real world contexts in which occurs.

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This demonstration highlights the applications of our research work i.e. second generation (Scalable Fault Tolerant Agent Grooming Environment - SAGE) Multi Agent System, Integration of Software Agents and Grid Computing and Autonomous Agent Architecture in the Agent Platform. It is a conference planner application that uses collaborative effort of services deployed geographically wide in different technologies i.e. Software Agents, Grid computing and Web services to perform useful tasks as required. Copyright 2005 ACM.

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This study seeks to fill the gap in the existing literature by examining at how and whether disclosure of social value creation becomes a part of legitimation strategies of social enterprises. By using Suchman’s (1995) moral dimension of legitimacy theory this study sets out that three global social organizations, Grameen Bank, Charity Water, and the Bill and Melinda Gates Foundation, disclose social value creation as if they conform to expectations of the broader community. The study finds that there is an apparent disconnection between disclosure and actions by social enterprises. With references to few incidents highlighted in this study, social enterprises, use disclosures as their managerial efforts, rather than creating moral legitimacy. The notion of apparent disconnection between disclosure and real action by the case social enterprises is common with the notion of the motivation behind disclosure practices by corporations as captured in extant disclosure literature. The finding suggest that when an organisation (whether it is a corporation or a social enterprise) face legitimacy crisis, it appears to disclose good news than bad news questioning organizational moral legitimacy.

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Free software is viewed as a revolutionary and subversive practice, and in particular has dealt a strong blow to the traditional conception of intellectual property law (although in its current form could be considered a 'hack' of IP rights). However, other (capitalist) areas of law have been swift to embrace free software, or at least incorporate it into its own tenets. One area in particular is that of competition (antitrust) law, which itself has long been in theoretical conflict with intellectual property, due to the restriction on competition inherent in the grant of ‘monopoly’ rights by copyrights, patents and trademarks. This contribution will examine how competition law has approached free software by examining instances in which courts have had to deal with such initiatives, for instance in the Oracle Sun Systems merger, and the implications that these decisions have on free software initiatives. The presence or absence of corporate involvement in initiatives will be an important factor in this investigation, with it being posited that true instances of ‘commons-based peer production’ can still subvert the capitalist system, including perplexing its laws beyond intellectual property.

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Water quality data are often collected at different sites over time to improve water quality management. Water quality data usually exhibit the following characteristics: non-normal distribution, presence of outliers, missing values, values below detection limits (censored), and serial dependence. It is essential to apply appropriate statistical methodology when analyzing water quality data to draw valid conclusions and hence provide useful advice in water management. In this chapter, we will provide and demonstrate various statistical tools for analyzing such water quality data, and will also introduce how to use a statistical software R to analyze water quality data by various statistical methods. A dataset collected from the Susquehanna River Basin will be used to demonstrate various statistical methods provided in this chapter. The dataset can be downloaded from website http://www.srbc.net/programs/CBP/nutrientprogram.htm.

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Twitter’s hashtag functionality is now used for a very wide variety of purposes, from covering crises and other breaking news events through gathering an instant community around shared media texts (such as sporting events and TV broadcasts) to signalling emotive states from amusement to despair. These divergent uses of the hashtag are increasingly recognised in the literature, with attention paid especially to the ability for hashtags to facilitate the creation of ad hoc or hashtag publics. A more comprehensive understanding of these different uses of hashtags has yet to be developed, however. Previous research has explored the potential for a systematic analysis of the quantitative metrics that could be generated from processing a series of hashtag datasets. Such research found, for example, that crisis-related hashtags exhibited a significantly larger incidence of retweets and tweets containing URLs than hashtags relating to televised events, and on this basis hypothesised that the information-seeking and -sharing behaviours of Twitter users in such different contexts were substantially divergent. This article updates such study and their methodology by examining the communicative metrics of a considerably larger and more diverse number of hashtag datasets, compiled over the past five years. This provides an opportunity both to confirm earlier findings, as well as to explore whether hashtag use practices may have shifted subsequently as Twitter’s userbase has developed further; it also enables the identification of further hashtag types beyond the “crisis” and “mainstream media event” types outlined to date. The article also explores the presence of such patterns beyond recognised hashtags, by incorporating an analysis of a number of keyword-based datasets. This large-scale, comparative approach contributes towards the establishment of a more comprehensive typology of hashtags and their publics, and the metrics it describes will also be able to be used to classify new hashtags emerging in the future. In turn, this may enable researchers to develop systems for automatically distinguishing newly trending topics into a number of event types, which may be useful for example for the automatic detection of acute crises and other breaking news events.