Abstract: The more an educational system knows about a learner, the more personalised interaction it can provide, which leads to better learning. However, asking a learner directly is potentially disruptive, and often ignored by learners. Especially in the booming realm of MOOC Massive Online Learning platforms, only a very low percentage of users disclose demographic information about themselves. Thus, in this paper, we aim to predict learners’ demographic characteristics, by proposing an approach using linguistically motivated Deep Learning Architectures for Learner Profiling, particularly targeting gender prediction on a FutureLearn MOOC platform. Additionally, we tackle here the difficult problem of predicting the gender of learners based on their comments only – which are often available across MOOCs. The most common current approaches to text classification use the Long Short-Term Memory (LSTM) model, considering sentences as sequences. However, human language also has structures. In this research, rather than considering sentences as plain sequences, we hypothesise that higher semantic - and syntactic level sentence processing based on linguistics will render a richer representation. We thus evaluate, the traditional LSTM versus other bleeding edge models, which take into account syntactic structure, such as tree-structured LSTM, Stack-augmented Parser-Interpreter Neural Network (SPINN) and the Structure-Aware Tag Augmented model (SATA). Additionally, we explore using different word-level encoding functions. We have implemented these methods on Our MOOC dataset, which is the most performant one comparing with a public dataset on sentiment analysis that is further used as a cross-examining for the models' results.
Abstract: This first-attempt study revealed that decolorized
intermediates of azo dyes could act as redox mediators to assist
wastewater (WW) decolorization due to enhancement of
electron-transport phenomena. Electrochemical impedance spectra
indicated that hydroxyl and amino-substituent(s) were functional
group(s) as redox-mediator(s). As azo dyes are usually multiple
benzene-rings structured, their derived decolorized intermediates are
likely to play roles of electron shuttles due to lower barrier of energy
gap for electron shuttling. According to cyclic voltammetric profiles,
redox mediating characteristics of decolorized intermediates of azo
dyes (e.g., RBu171, RR198, RR141, RBk5) were clearly disclosed.
With supplementation of biodecolorized metabolites of RR141 and
198, decolorization performance of could be evidently augmented.
This study also suggested the optimal modes of microbial fuel cell
(MFC)-assisted WW decolorization would be plug-flow or batch
mode of operation with no mix. Single chamber-MFCs would be more
favourable than double chamber MFCs due to non-mixing contacting
reactor scheme for operation.
Abstract: A sign pattern is a matrix whose entries belong to the set
{+,−, 0}. An n-by-n sign pattern A is said to allow an eventually
positive matrix if there exist some real matrices A with the same
sign pattern as A and a positive integer k0 such that Ak > 0 for all
k ≥ k0. It is well known that identifying and classifying the n-by-n
sign patterns that allow an eventually positive matrix are posed as two
open problems. In this article, the tree sign patterns of small order
that allow an eventually positive matrix are classified completely.
Abstract: Cloud computing is the innovative and leading
information technology model for enabling convenient, on-demand
network access to a shared pool of configurable computing resources
that can be rapidly provisioned and released with minimal
management effort. In this paper, we aim at the development of
workflow management system for cloud computing platforms based
on our previous research on the dynamic allocation of the cloud
computing resources and its workflow process. We took advantage of
the HTML5 technology and developed web-based workflow interface.
In order to enable the combination of many tasks running on the cloud
platform in sequence, we designed a mechanism and developed an
execution engine for workflow management on clouds. We also
established a prediction model which was integrated with job queuing
system to estimate the waiting time and cost of the individual tasks on
different computing nodes, therefore helping users achieve maximum
performance at lowest payment. This proposed effort has the potential
to positively provide an efficient, resilience and elastic environment
for cloud computing platform. This development also helps boost user
productivity by promoting a flexible workflow interface that lets users
design and control their tasks' flow from anywhere.
Abstract: In high bitrate information hiding techniques, 1 bit is
embedded within each 4 x 4 Discrete Cosine Transform (DCT)
coefficient block by means of vector quantization, then the hidden bit
can be effectively extracted in terminal end. In this paper high bitrate
information hiding algorithms are summarized, and the scheme of
video in video is implemented. Experimental result shows that the host
video which is embedded numerous auxiliary information have little
visually quality decline. Peak Signal to Noise Ratio (PSNR)Y of host
video only degrades 0.22dB in average, while the hidden information
has a high percentage of survives and keeps a high robustness in
H.264/AVC compression, the average Bit Error Rate(BER) of hiding
information is 0.015%.
Abstract: If there exists a nonempty, proper subset S of the set of all (n + 1)(n + 2)/2 inertias such that S Ôèå i(A) is sufficient for any n × n zero-nonzero pattern A to be inertially arbitrary, then S is called a critical set of inertias for zero-nonzero patterns of order n. If no proper subset of S is a critical set, then S is called a minimal critical set of inertias. In [3], Kim, Olesky and Driessche identified all minimal critical sets of inertias for 2 × 2 zero-nonzero patterns. Identifying all minimal critical sets of inertias for n × n zero-nonzero patterns with n ≥ 3 is posed as an open question in [3]. In this paper, all minimal critical sets of inertias for 3 × 3 zero-nonzero patterns are identified. It is shown that the sets {(0, 0, 3), (3, 0, 0)}, {(0, 0, 3), (0, 3, 0)}, {(0, 0, 3), (0, 1, 2)}, {(0, 0, 3), (1, 0, 2)}, {(0, 0, 3), (2, 0, 1)} and {(0, 0, 3), (0, 2, 1)} are the only minimal critical sets of inertias for 3 × 3 irreducible zerononzero patterns.
Abstract: If there exists a nonempty, proper subset S of the set of all (n+1)(n+2)/2 inertias such that S Ôèå i(A) is sufficient for any n×n zero-nonzero pattern A to be inertially arbitrary, then S is called a critical set of inertias for zero-nonzero patterns of order n. If no proper subset of S is a critical set, then S is called a minimal critical set of inertias. In [Kim, Olesky and Driessche, Critical sets of inertias for matrix patterns, Linear and Multilinear Algebra, 57 (3) (2009) 293-306], identifying all minimal critical sets of inertias for n×n zero-nonzero patterns with n ≥ 3 and the minimum cardinality of such a set are posed as two open questions by Kim, Olesky and Driessche. In this note, the minimum cardinality of all critical sets of inertias for 4 × 4 irreducible zero-nonzero patterns is identified.
Abstract: In this note, some properties of potentially powerpositive sign patterns are established, and all the potentially powerpositive sign patterns of order ≤ 3 are classified completely.
Abstract: Motivated by Berman et al. [Sign patterns that allow eventual positivity, ELA, 19(2010): 108-120], we concentrate on the potential eventual positivity of irreducible tridiagonal sign patterns. The minimal potential eventual positivity of irreducible tridiagonal sign patterns of order less than six is established, and all the minimal potentially eventually positive tridiagonal sign patterns of order · 5 are identified. Our results indicate that if an irreducible tridiagonal sign pattern of order less than six A is minimal potentially eventually positive, then A requires the eventual positivity.