62,470 research outputs found
Authentication of Students and Students’ Work in E-Learning : Report for the Development Bid of Academic Year 2010/11
Global e-learning market is projected to reach $107.3 billion by 2015 according to a new report by The Global Industry Analyst (Analyst 2010). The popularity and growth of the online programmes within the School of Computer Science obviously is in line with this projection. However, also on the rise are students’ dishonesty and cheating in the open and virtual environment of e-learning courses (Shepherd 2008). Institutions offering e-learning programmes are facing the challenges of deterring and detecting these misbehaviours by introducing security mechanisms to the current e-learning platforms. In particular, authenticating that a registered student indeed takes an online assessment, e.g., an exam or a coursework, is essential for the institutions to give the credit to the correct candidate. Authenticating a student is to ensure that a student is indeed who he says he is. Authenticating a student’s work goes one step further to ensure that an authenticated student indeed does the submitted work himself. This report is to investigate and compare current possible techniques and solutions for authenticating distance learning student and/or their work remotely for the elearning programmes. The report also aims to recommend some solutions that fit with UH StudyNet platform.Submitted Versio
Evaluation of methods for determining hardware projected life
An investigation of existing methods of predicting hardware life is summarized by reviewing programs having long life requirements, current research efforts on long life problems, and technical papers reporting work on life predicting techniques. The results indicate that there are no accurate quantitative means to predict hardware life for system level hardware. The effectiveness of test programs and the cause of hardware failures is considered
Classification and Verification of Online Handwritten Signatures with Time Causal Information Theory Quantifiers
We present a new approach for online handwritten signature classification and
verification based on descriptors stemming from Information Theory. The
proposal uses the Shannon Entropy, the Statistical Complexity, and the Fisher
Information evaluated over the Bandt and Pompe symbolization of the horizontal
and vertical coordinates of signatures. These six features are easy and fast to
compute, and they are the input to an One-Class Support Vector Machine
classifier. The results produced surpass state-of-the-art techniques that
employ higher-dimensional feature spaces which often require specialized
software and hardware. We assess the consistency of our proposal with respect
to the size of the training sample, and we also use it to classify the
signatures into meaningful groups.Comment: Submitted to PLOS On
A flexible model for dynamic linking in Java and C#
Dynamic linking supports flexible code deployment, allowing partially linked code to link further code on the fly, as needed.
Thus, end-users enjoy the advantage of automatically receiving any updates, without any need for any explicit actions on their side,
such as re-compilation, or re-linking. On the down side, two executions of a program may link in different versions of code, which
in some cases causes subtle errors, and may mystify end-users.
Dynamic linking in Java and C# are similar: the same linking phases are involved, soundness is based on similar ideas, and
executions which do not throw linking errors give the same result. They are, however, not identical: the linking phases are combined
differently, and take place in different order. Consequently, linking errors may be detected at different times by Java and C# runtime
systems.
We develop a non-deterministic model, which describes the behaviour of both Java and C# program executions. The nondeterminism
allows us to describe the design space, to distill the similarities between the two languages, and to use one proof of
soundness for both. We also prove that all execution strategies are equivalent with respect to terminating executions that do not
throw link errors: they give the same results
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