Miracle-dz/UniFAR-FTUs huggingface dataset:
Determinants of the intention to use technology: Comparison between Malaysian and Singaporean female student teachers

As we progress into a technology-based society, it is imperative that teaching experiences with computers as effective pedagogical tools are made available to teachers [3]. Given the rapid development of computer technology in Malaysia and Singapore, cross-cultural comparisons are indeed needed to understand the determinants of technology acceptance by female student teachers from two diverse cultures. Based on the Technology Acceptance Model (TAM), a sample of 183 Malaysian students was compared with a similar sample of 175 Singaporean students. The variables that were tested included perceived usefulness (PU), perceived ease of use (PEU), computer attitudes (CA), and behavioural intentions to use the computer (BI). This study provides evidence that PEU and PU are two important predictors of BI. It also reveals the cultural differences in the application of TAM where CA is not significant towards BI for the Singaporean female student teachers but is significant for the Malaysian counterparts.
A queueing theoretic model of a gene regulatory network

We consider an infinite server queue into which customers arrive according to a Cox process and have independent service times with a general distribution. The model is motivated by a linear feed-forward gene regulatory network, in which the rate of protein synthesis is modulated by the number of RNA molecules present in a cell. The system can be modelled as a nonstandard tandem of infinite server queues, in which the number of customers present in a queue modulates the arrival rate into the next queue in the tandem. We first study second order statistics of the equilibrium queue length by making a simplifying assumption on the service time distribution. We then establish a Large Deviations Principle for this queueing system in the asymptotic regime in which the arrival process is sped up, while the service process is not scaled.
WIDEBAND RECONFIGURABLE LOG PERIODIC PATCH ARRAY

This paper presents a novel wideband to narrow band reconflgurable log periodic aperture coupled patch array. The wide to narrow band reconflguration is realized by closing a selected group of slot apertures, to deactivate the corresponding group of patches. The patches are fed with a modulated meander line through aperture slots. A wideband mode from 7{10GHz and three selected narrow band modes at 7.1, 8.2 and 9.4GHz are demonstrated. Potentially, the number of sub bands can be increased or decreased as can the bandwidth of the sub bands by selecting a speciflc number of active elements. To verify and demonstrate the proposed design method, a prototype has been developed with ideal switches. Very good agreements between the measured and simulated results are presented.
Texture Analysis Platform for Imaging Biomarker Research

The rate of progress in improving survival of patients with solid tumors is slow due to late stage diagnosis and poor tumor characterization processes that fail to effectively reflect the nature of tumor before treatment or the subsequent change in its dynamics because of treatment. Further advancement of targeted therapies relies on advancements in biomarker research. In the context of solid tumors, bio-specimen samples such as biopsies serve as the main source of biomarkers used in the treatment and monitoring of cancer, even though biopsy samples are susceptible to sampling error and more importantly, are local and offer a narrow temporal scope. Because of its established role in cancer care and its non-invasive nature imaging offers the potential to complement the findings of cancer biology. Over the past decade, a compelling body of literature has emerged suggesting a more pivotal role for imaging in the diagnosis, prognosis, and monitoring of diseases. These advances have facilitated the rise of an emerging practice known as Radiomics: the extraction and analysis of large numbers of quantitative features from medical images to improve disease characterization and prediction of outcome. It has been suggested that radiomics can contribute to biomarker discovery by detecting imaging traits that are complementary or interchangeable with other markers. This thesis seeks further advancement of imaging biomarker discovery. This research unfolds over two aims: I) developing a comprehensive methodological pipeline for converting diagnostic imaging data into mineable sources of information, and II) investigating the utility of imaging data in clinical diagnostic applications. Four validation studies were conducted using the radiomics pipeline developed in aim I. These studies had the following goals: (1 distinguishing between benign and malignant head and neck lesions (2) differentiating benign and malignant breast cancers, (3) predicting the status of Human Papillomavirus in head and neck cancers, and (4) predicting neuropsychological performances as they relate to Alzheimer’s disease progression. The long-term objective of this thesis is to improve patient
Towards managing visual impacts on public spaces: a quantitative approach to studying visual complexity and enclosure using visual bowl and fractal dimension

Diverging opinions on the visual impact of high-rise developments on public spaces and the lack of measurements to justify these impacts drive our inquiry for this paper. To address this, we propose a workflow by 1) conceptualising and modelling a visual bowl's volume, 2) quantifying sky and height-width ratio, sightline distance and, 3) estimating the fractal dimension of geometry using a voxelization process and box-counting method. Using this workflow, we report a negative correlation between enclosure and visual complexity indicators when assessing the visual impacts of future high- rise developments in Central Melbourne. The computation of a volumetric visual bowl and its fractal dimension potentially offer a new approach to study these impacts.
Teaching expertise reconsidered: The Technology, Pedagogy, Content and Space (TPeCS) knowledge framework

School practitioners are increasingly expected to lead construction projects in their schools to create future learning spaces (FLSs) that support learning in today's networked society. This study examined the process by which practitioners of one school developed their readiness to incorporate an FLS into the school via a long‐lasting research–practice partnership (RPP) that focused on co‐designing learning materials for contemporary teaching. To conceptualize this process, we introduce the Technology, Pedagogy, Content and Space (TPeCS) knowledge framework, which expands current conceptualizations of teaching expertise by tying them into the emerging field of FLSs. We interpret practitioners' learning within a series of action–reaction progressive developments along a two‐year timeline of the partnership. Visits to an FLS, where researchers modeled, coached and then faded their guidance along this timeline played a key role in practitioners' development of readiness to incorporate an FLS into their school. The pedagogical domain was the most challenging among all the dimensions of TPeCS. We conclude that school practitioners' involvement leading FLS endeavors within their schools can serve as an unprecedented opportunity for practitioners to develop contemporary teaching skills, with FLSs serving as ideal spaces that make pedagogy visible. Practitioner NotesWhat is already known about this topic School practitioners are increasingly expected to participate in construction/renovation projects of FLSs.Teaching expertise is often conceptualized in terms of technological, pedagogical and content knowledge (TPaCK). What this paper adds A novel framework for conceptualizing teaching expertise as the competence to flexibly use knowledge that combines technological, pedagogical, content and space (TPeCS) considerations.The pedagogical component within TPeCS has a bottleneck quality. Reducing pedagogical gaps accelerates the development of other TPeCS components.Visits to state‐of‐the‐art FLSs, involving modeling, coaching and fading of expert guidance can foster practitioners' development of TPeCS knowledge and competencies, increasing their readiness to incorporate FLSs into their schools. FLSs and specifically the use of large digital displays are ideal for making pedagogy visible.Implications for practice and/or policy School practitioners can, and should, be key players in leading FLS endeavors within their schools. When appropriately guided, this can serve as an unprecedented opportunity for practitioners to develop contemporary teaching skills [ABSTRACT FROM AUTHOR] uracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
GlobSim (v1.0): deriving meteorological time series for point locations from multiple global reanalyses

Abstract. Simulations of land-surface processes and phenomena often require driving time series of meteorological variables. Corresponding observations, however, are unavailable in most locations, even more so, when considering the duration, continuity and data quality required. Atmospheric reanalyses provide global coverage of relevant meteorological variables, but their use is largely restricted to grid-based studies. This is because technical challenges limit the ease with which reanalysis data can be applied to models at the site scale. We present the software toolkit GlobSim, which automates the downloading, interpolation and scaling of different reanalyses – currently ERA5, ERA-Interim, JRA-55 and MERRA-2 – to produce meteorological time series for user-defined point locations. The resulting data have consistent structure and units to efficiently support ensemble simulation. The utility of GlobSim is demonstrated using an application in permafrost research. We perform ensemble simulations of ground-surface temperature for 10 terrain types in a remote tundra area in northern Canada and compare the results with observations. Simulation results reproduced seasonal cycles and variation between terrain types well, demonstrating that GlobSim can support efficient land-surface simulations. Ensemble means often yielded better accuracy than individual simulations and ensemble ranges additionally provide indications of uncertainty arising from uncertain input. By improving the usability of reanalyses for research requiring time series of climate variables for point locations, GlobSim can enable a wide range of simulation studies and model evaluations that previously were impeded by technical hurdles in obtaining suitable data.
Rich-context: an unsupervised context-driven recommender system based on user reviews

Title Rich-context: an unsupervised context-driven recommender system based on user reviews Author(s) Peña, Francisco J. Publication date 2019 Original citation Peña, F. J. 2019. Rich-context: an unsupervised context-driven recommender system based on user reviews. PhD Thesis, University College Cork. Type of publication Doctoral thesis Rights © 2019, Francisco J. Peña. http://creativecommons.org/licenses/by-nc-nd/3.0/
Using Authentic Materials in Teaching Reading Comprehension to EFL Learners

The aim of this study was to investigate the effect of authentic-based and non-authentic-based materials on improving reading comprehension of the Iranian intermediate EFL learners. To perform this study, 50 Iranian EFL learners studying English in Pooya Language Institute in Abadan were selected. They took part in a proficiency test (OPT) and 24 of them were randomly assigned into two homogeneous groups. Then, both groups were given a pre-test before the treatments to determine how well the subjects in reading comprehension. During a 12-session course, both groups were taught 12 passages selected by the researcher. The authentic group under treatment received authentic-based reading passages while the non-authentic group received non-authentic-based reading passages. Having finished the treatments, the learners in the both groups were given the post-test. Independent Samples t-test were used to compare the means of the pre-test and the post-test in both groups. The findings revealed that reading comprehension performance of both groups improved. Moreover, Independent Samples t-test showed that there was a significant difference between the two groups concerning reading comprehension.
The Effectiveness of a Systems Engineering Course in Developing Systems Thinking

Contribution: An evaluation of the effectiveness of systems engineering (SE) courses in developing students’ systems thinking (ST) capacity in both the cognitive and affective domains. A combined cognitive ST performance and affective engagement with ST assessment is proposed as an approach to assess students’ ST in both domains. The results can support course change decisions and guide learning experience development. Background: SE education aims to produce graduates with strong knowledge and skills in SE and a strong appreciation of the practical value of ST, which addresses the cognitive and affective domains in education. Consequently, it is important to evaluate the effectiveness of SE courses in developing students’ ST in these domains, an area that studies do not consider. Intended Outcomes: An understanding of the ST ability of undergraduate students in an SE course in a domain specific engineering program in both the cognitive and affective domains. Application Design: A study evaluated the effectiveness of two SE classes in developing students’ ST capacity using a combined cognitive and affective assessment tool developed and validated in previous studies. ST assessment is determined by combining ST performance and affective engagement. To observe the transformation of students’ ST capacity, a longitudinal design collected data at two times in each of two offerings of an SE course offered by the same university in two locations—Australia and Singapore. Findings: The course developed students in most dimensions of cognitive ST, but did not appear to improve students’ affective engagement with ST.
Deep Q-Learning-Based Content Caching With Update Strategy for Fog Radio Access Networks

In order to improve the edge caching efficiency of the fog radio access network (F-RAN), this paper put forward a distributed deep Q-learning-based content caching scheme based on user preference prediction and content popularity prediction. Given that the constraint that the storage capacity of each device is limited, and the optimization problem is formulated so as to maximize the caching hit rate. Specifically, by taking users’ selfishness into consideration, user preference is predicted in an offline manner by applying popular topic models. Then, the online predicted content popularity is achieved by combining the network topology relationship together with the obtained user preference. Finally, with the predicted user preference and content popularity, the deep Q-learning network (DQN)-based content caching algorithm is proposed to achieve the optimal content caching strategy. Moreover, we further present a content update policy with user preference and content popularity prediction, so that the proposed algorithm can handle the variations of contents popularity in a timely manner. Simulation results demonstrate that the proposed scheme achieves better caching hit rate compared with existing algorithms.
Representability of derived stacks

Lurie's representability theorem gives necessary and sufficient conditions for a functor to be an almost finitely presented derived geometric stack. We establish several variants of Lurie's theorem, making the hypotheses easier to verify for many applications. Provided a derived analogue of Schlessinger's condition holds, the theorem reduces to verifying conditions on the underived part and on cohomology groups. Another simplification is that functors need only be defined on nilpotent extensions of discrete rings. Finally, there is a pre-representability theorem, which can be applied to associate explicit geometric stacks to dg-manifolds and related objects.
Reconceptualizing games for integrating computational thinking and science as practice: collaborative agent-based disciplinarily-integrated games

ABSTRACT This paper situates a critical review of studies that we have conducted within the broader research literature to analyze the affordances of integrating modeling within disciplinarily-integrated games from computational thinking and science as practice perspectives. Across the studies, the analyses pursue two themes: (a) the role of agent-based modeling as a synergistic local practice around which we can integrate computational thinking and scientific modeling within digital games and (b) the role of collaboration in leveraging those synergies. We then present a design of a disciplinarily-integrated game that integrates these themes to demonstrate one such possible instantiation of the themes. Finally, we discuss the implications for design and praxis with a particular focus on learning in classrooms across the curriculum. Specifically, we first explore the implications in terms of connecting to teachers’ views of practice by framing computational modeling and computational thinking as mathematization. We then explore the implications of shifting from a focus on single players to communities of practice in terms of computational participation as science as practice. We close by exploring the pragmatic and pedagogical affordances of shifting from stand-alone single-topic games to flexible agent-based environments in terms of student development across the curriculum.
Towards a Legibility Metric: How to Measure the Perceived Value of a Robot

Our goal is to assess the perceived value of autonomous robots in human working and living environments. As a specific indicator we define legibility as an important prerequisite for high perceived value. Inspired by recommender systems, which also target the perceived value of products, we identify different measurements for explicit and implicit user feedback in a framework to compare different algorithms. Finally we propose the design of a specific study to measure the legibility of robot navigation behavior in dynamic situations.
The Impact of Avatar Blushing on the Duration of Interaction between a Real and Virtual Person

This paper describes an experimental study on human participants’ reactions towards a blushing avatar. As one of the “most human of all expressions”, blushing serves an important role in interpersonal communication. In this paper we describe an experiment in which there is an interaction between a person and an avatar who “blushes” in an embarrassing situation. Our major question of interest was whether participants would be influenced by the blushing, and whether they would tolerate the avatar longer than in the situation where there was no blushing. Moreover, two different type of blushing were considered: whole-face blushing and cheek blushing. This work uses behavioural and questionnaire responses. The results show first, participants tended to withdraw early when the avatar was blushing only on the cheek; second, the whole-face blushing improved participants’ degree of “co-presence”.
Information Coding and Hardware Architecture of Spiking Neural Networks

Inspired from the brain, neuromorphic computing would be the right alternative to traditional Von-Neumann architecture computing that knows its end of growth as predicted by Moore's law. In this paper, we explore bio-inspired neural networks as an AI-accelerator for embedded systems. To do so, we first map neural networks from formal to spiking domain, then choose the information coding method resulting in better performances. Afterwards, we present the design of two different hardware architectures: time-multiplexed and fully-parallel. Finally, we compare their performances and their hardware cost to select at the end the adequate architecture and conclude about spike-based neural networks as a potential solution for embedded artificial intelligence applications.
Super Resolution of Wavelet-Encoded Images and Videos

In this dissertation, we address the multiframe super resolution reconstruction problem for waveletencoded images and videos. The goal of multiframe super resolution is to obtain one or more high resolution images by fusing a sequence of degraded or aliased low resolution images of the same scene. Since the low resolution images may be unaligned, a registration step is required before super resolution reconstruction. Therefore, we first explore in-band (i.e. in the wavelet-domain) image registration; then, investigate super resolution. Our motivation for analyzing the image registration and super resolution problems in the wavelet domain is the growing trend in wavelet-encoded imaging, and wavelet-encoding for image/video compression. Due to drawbacks of widely used discrete cosine transform in image and video compression, a considerable amount of literature is devoted to wavelet-based methods. However, since wavelets are shift-variant, existing methods cannot utilize wavelet subbands efficiently. In order to overcome this drawback, we establish and explore the direct relationship between the subbands under a translational shift, for image registration and super resolution. We then employ our devised in-band methodology, in a motion compensated video compression framework, to demonstrate the effective usage of wavelet subbands. Super resolution can also be used as a post-processing step in video compression in order to decrease the size of the video files to be compressed, with downsampling added as a pre-processing step. Therefore, we present a video compression scheme that utilizes super resolution to reconstruct the high frequency information lost during downsampling. In addition, super resolution is a crucial post-processing step for satellite imagery, due to the fact that it is hard to update imaging devices after a satellite is launched. Thus, we also demonstrate the usage of our devised methods in enhancing resolution of pansharpened multispectral images.
Intrusion Detection Using N-Grams of Object Access Graph Components

Cyber warfare demonstrates an arms race between mutually escalating malware and Intrusion Detection System (IDS) technologies. We put forward a novel process for defining system behavior with the end result being a highly effective IDS. System calls accumulated under normal network operation are converted into graph components, and used as part of the IDS normalcy profile. This paper are as follows: detection of attacks based on the anomalous use of program functionality; reduced window of attack; reduced false positive rate; increased performance in comparison to standard n-gram methods; a graph compression algorithm for efficient processing of system call graphs. The proposed IDS can be used within limited access environments such as industrial or military systems where only approved applications are running and any anomalies are indicative of a cyber attack or malfunction.