903 resultados para Mobile money


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Mobile malwares are increasing with the growing number of Mobile users. Mobile malwares can perform several operations which lead to cybersecurity threats such as, stealing financial or personal information, installing malicious applications, sending premium SMS, creating backdoors, keylogging and crypto-ransomware attacks. Knowing the fact that there are many illegitimate Applications available on the App stores, most of the mobile users remain careless about the security of their Mobile devices and become the potential victim of these threats. Previous studies have shown that not every antivirus is capable of detecting all the threats; due to the fact that Mobile malwares use advance techniques to avoid detection. A Network-based IDS at the operator side will bring an extra layer of security to the subscribers and can detect many advanced threats by analyzing their traffic patterns. Machine Learning(ML) will provide the ability to these systems to detect unknown threats for which signatures are not yet known. This research is focused on the evaluation of Machine Learning classifiers in Network-based Intrusion detection systems for Mobile Networks. In this study, different techniques of Network-based intrusion detection with their advantages, disadvantages and state of the art in Hybrid solutions are discussed. Finally, a ML based NIDS is proposed which will work as a subsystem, to Network-based IDS deployed by Mobile Operators, that can help in detecting unknown threats and reducing false positives. In this research, several ML classifiers were implemented and evaluated. This study is focused on Android-based malwares, as Android is the most popular OS among users, hence most targeted by cyber criminals. Supervised ML algorithms based classifiers were built using the dataset which contained the labeled instances of relevant features. These features were extracted from the traffic generated by samples of several malware families and benign applications. These classifiers were able to detect malicious traffic patterns with the TPR upto 99.6% during Cross-validation test. Also, several experiments were conducted to detect unknown malware traffic and to detect false positives. These classifiers were able to detect unknown threats with the Accuracy of 97.5%. These classifiers could be integrated with current NIDS', which use signatures, statistical or knowledge-based techniques to detect malicious traffic. Technique to integrate the output from ML classifier with traditional NIDS is discussed and proposed for future work.

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This mixed methods research explores the role of reading engagement in 30 grade 1 students’ motivation to read mobile electronic storybooks (eBooks) and cognitive strategies used during eBook reading. Data collection comprised motivation and parent questionnaires, behavioural observation checklists, cognitive strategies rubric, and teacher interviews. Students’ emotional engagement with and enjoyment of mobile eBooks corresponded to 4 motivational aspects of intrinsic motivation: curiosity, control, choice, and challenge. Post-intervention results indicated that most student participants enjoyed answering eBook comprehension questions and preferred eBooks to print books; by the end of the study, all had access to a mobile device at home. A majority of participants were actively engaged during mobile eBook reading sessions and persisted in answering embedded eBook comprehension questions, which together reflected students’ behavioural engagement and time-on-task during mobile reading. Students’ off-task behaviours related to iPads’ accessibility features and inherent reader-friendliness. All participants successfully answered evaluative questions requiring them to activate prior knowledge, and experienced higher levels of difficulty with making personal connections. The study highlights the importance of making school-based literacy practices relevant to students’ outside worlds, and discusses implications for teacher educators, administrators, curriculum developers, and eBook and other digital developers concerning the need for greater collaboration in order to more closely align technology resources with national curriculum expectations.

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Mobile augmented reality applications are increasingly utilized as a medium for enhancing learning and engagement in history education. Although these digital devices facilitate learning through immersive and appealing experiences, their design should be driven by theories of learning and instruction. We provide an overview of an evidence-based approach to optimize the development of mobile augmented reality applications that teaches students about history. Our research aims to evaluate and model the impacts of design parameters towards learning and engagement. The research program is interdisciplinary in that we apply techniques derived from design-based experiments and educational data mining. We outline the methodological and analytical techniques as well as discuss the implications of the anticipated findings.

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Mobile augmented reality applications are increasingly utilized as a medium for enhancing learning and engagement in history education. Although these digital devices facilitate learning through immersive and appealing experiences, their design should be driven by theories of learning and instruction. We provide an overview of an evidence-based approach to optimize the development of mobile augmented reality applications that teaches students about history. Our research aims to evaluate and model the impacts of design parameters towards learning and engagement. The research program is interdisciplinary in that we apply techniques derived from design-based experiments and educational data mining. We outline the methodological and analytical techniques as well as discuss the implications of the anticipated findings.

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Letter regarding an estimate on the amount of money needed for the construction of the road. The salutation is “Sir”. There is no signature, May 28, 1855.

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This paper proposes a theory of the good life for use in answering the question how much money the rich should spend on fighting poverty. The paper moves from the abstract to the concrete. To begin with, it investigates various ways to get an answer to the question what is good, and finds itself drawn to objective theories of the good. It then develops, taking Bernard Williams and Martha Nussbaum as its guides, a broad outline of a theory of the good. It holds that something evil happens to people if they do not have a real choice from a reasonable number of projects that realize most of their key capacities to a certain degree, and in connection to this it points to the great importance of money. The paper goes on specifically to consider what criticisms of Nussbaum's version of the capability approach are implied in this outline of a theory of the good. Next, it gets more specific and asks how much money the rich can give -and how they can be restricted in spending their money- without suffering any evil. It does three suggestions: the tithe suggestion, the ecological (or footprint) suggestion, and the fair trade suggestion. To conclude, the paper returns to the question how much money the rich should spend on fighting poverty.

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Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal.