ABSTRACT

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This research work explores the use of mobile and positioning technologies stimulating a context adaptive and location-based learning model. The proposed model utilizes a set of context factors for learning service dissemination; described as learning service area, learning service type, and service interaction level. In addition, the new model considers the availability of positioning technology for authoring location-based learning content, and for accurately disseminating learning services. Hence, tolerance to position errors is used to classify learning services into two types; generic and specific. An evaluation experiment was conducted measuring the relationship between the positioning performance and successful implementation of the m-learning model. Results have shown a significant affect of position accuracy towards learners' context understanding and interaction with learning activity.

Abstract:A new method of forward digital signatures is proposed in this paper. All of the previous forward digital signatures depend on changing the private key periodically but they keep the public key. The proposed system will change both private keys and public keys that can be generated only by authorized users to enhance the authenticity of users. Another important proposal is that the expiration of that public key depends on the length of the document so the sender must compute the expired time of his/her document depending on its length. This method also can be used to change the private key depending on the expired date of the document but the public key is still fixed. In order to make this digital signature more efficient, the system must change the private keys in terms of their critical times that indicate the period of exposure of the keys by different attacks types. So the ability to change these keys do not depend on fixed periods as in most forward digital signatures but also depend on these critical times and the entropy of the information of the keys.