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

Denoising Deep Neural Networks Based Voice Activity Detection

Recently, the deep-belief-networks (DBN) based voice activity detection (VAD) has been proposed. It is powerful in fusing the advantages of multiple features, and achieves the state-of-the-art performance. However, the deep layers of the DBN-based VAD do not show an apparent superiority to the shallower layers. In this paper, we propose a denoising-deep-neural-network (DDNN) based VAD to address the aforementioned problem. Specifically, we pre-train a deep neural network in a special unsupervised denoising greedy layer-wise mode, and then fine-tune the whole network in a supervised way by the common back-propagation algorithm. In the pre-training phase, we take the noisy speech signals as the visible layer and try to extract a new feature that minimizes the reconstruction cross-entropy loss between the noisy speech signals and its corresponding clean speech signals. Experimental results show that the proposed DDNN-based VAD not only outperforms the DBN-based VAD but also shows an apparent performance improvement of the deep layers over shallower layers.Comment: This paper has been accepted by IEEE ICASSP-2013, and will be published online after May, 201

A mechanism of e22h\frac{e^2}{2h} conductance plateau without 1D chiral Majorana fermions

We address the question about the origin of the $\frac12 \frac{e^2}{h}$ conductance plateau observed in a recent experiment on an integer quantum Hall (IQH) film covered by a superconducting (SC) film. Since 1-dimensional (1D) chiral Majorana fermions on the edge of the above device can give rise to the half quantized plateau, such a plateau was regarded as a smoking-gun evidence for the chiral Majorana fermions. However, in this paper we give another mechanism for the $\frac12 \frac{e^2}{h}$ conductance plateau. We find the $\frac12 \frac{e^2}{h}$ conductance plateau to be a general feature of a good electric contact between the IQH film and SC film, and cannot distinguish the existence or the non-existence of 1D chiral Majorana fermions. We also find that the contact conductance between SC and an IQH edge channel has a non-Ohmic form $\sigma_\text{SC-Hall} \propto V^2$ in $k_BT \ll eV$ limit, if the SC and IQH bulks are fully gapped.Comment: 6 pages, 4 figures. The T=0 calculation is updated for a more general situation (k_F=/=0). The results are not affecte

GreenVis: Energy-Saving Color Schemes for Sequential Data Visualization on OLED Displays

The organic light emitting diode (OLED) display has recently become popular in the consumer electronics market. Compared with current LCD display technology, OLED is an emerging display technology that emits light by the pixels themselves and doesn’t need an external back light as the illumination source. In this paper, we offer an approach to reduce power consumption on OLED displays for sequential data visualization. First, we create a multi-objective optimization approach to find the most energy-saving color scheme for given visual perception difference levels. Second, we apply the model in two situations: pre-designed color schemes and auto generated color schemes. Third, our experiment results show that the energy-saving sequential color scheme can reduce power consumption by 17.2% for pre-designed color schemes. For auto-generated color schemes, it can save 21.9% of energy in comparison to the reference color scheme for sequential data

Designer Topological Insulators in Superlattices

Gapless Dirac surface states are protected at the interface of topological and normal band insulators. In a binary superlattice bearing such interfaces, we establish that valley-dependent dimerization of symmetry-unrelated Dirac surface states can be exploited to induce topological quantum phase transitions. This mechanism leads to a rich phase diagram that allows us to design strong, weak, and crystalline topological insulators. Our ab initio simulations further demonstrate this mechanism in [111] and [110] superlattices of calcium and tin tellurides.Comment: 5 pages, 4 figure