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Numerous non-profit driven establishments depend on volunteers to help achieve their administrative targets. Despite the fact that volunteers work side-by-side or now and again substitute representatives in delivering services, inputting volunteer work into non-profit ventures of delivering services presents remarkable difficulties. Understanding these difficulties provides a significant fundamental building step in comprehending the influence these challenges have on service developmental plans and operations when utilizing volunteers. In this study, the paper brings forward a Charity Fundraising Information System (CFIS) framework and presents the modelling and evaluation of a plan and operational variables applicable to volunteer fulfilment in non-profit driven organizations. Discoveries indicate that fulfilled volunteers are bound to stay longer with the same establishment, give monetarily to the non-profit driven organization, and prescribe the volunteer involvement to other people. Every one of these results guarantees the continuous sustenance of the non-profit driven establishment.

The spam is one of the illegal and negative practices that involves the use of email services to send unsolicited emails such as phishing for the purpose of scamming which influences the reliability of email. Investigations have been conducted from various perspectives in order to examine this spam problem and how it affects society. In this regard, many studies have been carried out with the aim of studying the effect of spam activity on finance, economy, marketing, business and management, while other studies have focused on studying the influence of spam on security and privacy. Consequently, the literature affords various anti-spam methods that blocks or filters spam emails. This paper investigates the existing anti-spam methods, highlights some current problems and carries out an improved anti-spam model. In this regard, a new agent-based of Multi-Natural Language Anti-Spam (MNLAS) model is proposed. The MNLAS model process in the spam filtering process of an email both visual information such as images and texts in English and Arabic languages. The Jade agent platform and Java environments are employed in the implementation of MNLAS model. The MNLAS model is tested on a 200 emails' dataset and the results show that it is able to detect and filter various kinds of spam emails with high accuracy.

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