5,757 research outputs found
Automated Mapping of Adaptive App GUIs from Phones to TVs
With the increasing interconnection of smart devices, users often desire to
adopt the same app on quite different devices for identical tasks, such as
watching the same movies on both their smartphones and TV.
However, the significant differences in screen size, aspect ratio, and
interaction styles make it challenging to adapt Graphical User Interfaces
(GUIs) across these devices.
Although there are millions of apps available on Google Play, only a few
thousand are designed to support smart TV displays.
Existing techniques to map a mobile app GUI to a TV either adopt a responsive
design, which struggles to bridge the substantial gap between phone and TV or
use mirror apps for improved video display, which requires hardware support and
extra engineering efforts.
Instead of developing another app for supporting TVs, we propose a
semi-automated approach to generate corresponding adaptive TV GUIs, given the
phone GUIs as the input.
Based on our empirical study of GUI pairs for TV and phone in existing apps,
we synthesize a list of rules for grouping and classifying phone GUIs,
converting them to TV GUIs, and generating dynamic TV layouts and source code
for the TV display.
Our tool is not only beneficial to developers but also to GUI designers, who
can further customize the generated GUIs for their TV app development.
An evaluation and user study demonstrate the accuracy of our generated GUIs
and the usefulness of our tool.Comment: 30 pages, 15 figure
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The Role of Interactive Web Broadcasts in Fostering Distance Learning Students’ Engagement with Practical Lab and Fieldwork
Practical work in science and technology disciplines is crucial for students’ understanding and mastery. For educators who teach those disciplines at a distance and for students who learn remotely, this endeavour may be challenging.
The study presented in this thesis investigates the use of Interactive Web Broadcasts (IWBs) in five undergraduate practical science and technology modules at The Open University. The study examines the reasons for using IWBs, as well as the strategies and types of interactions that staff and students use to engage and interact with one another. The study gathered perspectives from academics (n=18); associate lecturers (n=10); technical production team (n=3); students (n=88), and an external guest expert about the purposes, strategies and motivations of participating in IWBs. The study used a qualitatively mixed-methods design. An adapted protocol of Flanders’s Interaction Analysis Categories was used to analyse the interaction patterns in the web broadcast transcripts and text-chat logs, and a discourse analysis coding scheme was applied to analyse the text-chat. Student online questionnaires were administered towards the end of the modules to capture the student perceptions of IWBs. Student interviews and staff focus groups were also conducted to gain a fuller picture of experiences of using and engaging with IWBs.
Findings show that the purposes and aims of using IWBs are to facilitate student engagement, foster a sense of community, and demonstrate an authentic practice of the sciences in real-world contexts. The communicative strategies were primarily affective and met students’ interests and expectations. The IWBs mitigated feelings of isolation that are common in distance education environments. IWBs had positive impacts on professional teaching practices and fostered collegiality and collaboration among staff. The findings are relevant to other distance and traditional campus-based universities that teach practical science and technology, those who teach online using synchronous technology-mediated systems, and those who are interested in student engagement and practical work
Exploring Natural Language Processing Methods for Interactive Behaviour Modelling
Analysing and modelling interactive behaviour is an important topic in
human-computer interaction (HCI) and a key requirement for the development of
intelligent interactive systems. Interactive behaviour has a sequential
(actions happen one after another) and hierarchical (a sequence of actions
forms an activity driven by interaction goals) structure, which may be similar
to the structure of natural language. Designed based on such a structure,
natural language processing (NLP) methods have achieved groundbreaking success
in various downstream tasks. However, few works linked interactive behaviour
with natural language. In this paper, we explore the similarity between
interactive behaviour and natural language by applying an NLP method, byte pair
encoding (BPE), to encode mouse and keyboard behaviour. We then analyse the
vocabulary, i.e., the set of action sequences, learnt by BPE, as well as use
the vocabulary to encode the input behaviour for interactive task recognition.
An existing dataset collected in constrained lab settings and our novel
out-of-the-lab dataset were used for evaluation. Results show that this natural
language-inspired approach not only learns action sequences that reflect
specific interaction goals, but also achieves higher F1 scores on task
recognition than other methods. Our work reveals the similarity between
interactive behaviour and natural language, and presents the potential of
applying the new pack of methods that leverage insights from NLP to model
interactive behaviour in HCI
Inclusive Intelligent Learning Management System Framework - Application of Data Science in Inclusive Education
Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data ScienceBeing a disabled student the author faced higher education with a handicap which as experience
studying during COVID 19 confinement periods matched the findings in recent research about the
importance of digital accessibility through more e-learning intensive academic experiences. Narrative
and systematic literature reviews enabled providing context in World Health Organization’s
International Classification of Functioning, Disability and Health, legal and standards framework and
information technology and communication state-of-the art. Assessing Portuguese higher education
institutions’ web sites alerted to the fact that only outlying institutions implemented near perfect,
accessibility-wise, websites.
Therefore a gap was identified in how accessible the Portuguese higher education websites are, the
needs of all students, including those with disabilities, and even the accessibility minimum legal
requirements for digital products and the services provided by public or publicly funded organizations.
Having identified a problem in society and exploring the scientific base of knowledge for context and
state of the art was a first stage in the Design Science Research methodology, to which followed
development and validation cycles of an Inclusive Intelligent Learning Management System
Framework. The framework blends various Data Science study fields contributions with accessibility
guidelines compliant interface design and content upload accessibility compliance assessment.
Validation was provided by a focus group whose inputs were considered for the version presented in
this dissertation. Not being the purpose of the research to deliver a complete implementation of the
framework and lacking consistent data to put all the modules interacting with each other, the most
relevant modules were tested with open data as proof of concept.
The rigor cycle of DSR started with the inclusion of the previous thesis on Atlântica University Institute
Scientific Repository and is to be completed with the publication of this thesis and the already started
PhD’s findings in relevant journals and conferences
The Metaverse: Survey, Trends, Novel Pipeline Ecosystem & Future Directions
The Metaverse offers a second world beyond reality, where boundaries are
non-existent, and possibilities are endless through engagement and immersive
experiences using the virtual reality (VR) technology. Many disciplines can
benefit from the advancement of the Metaverse when accurately developed,
including the fields of technology, gaming, education, art, and culture.
Nevertheless, developing the Metaverse environment to its full potential is an
ambiguous task that needs proper guidance and directions. Existing surveys on
the Metaverse focus only on a specific aspect and discipline of the Metaverse
and lack a holistic view of the entire process. To this end, a more holistic,
multi-disciplinary, in-depth, and academic and industry-oriented review is
required to provide a thorough study of the Metaverse development pipeline. To
address these issues, we present in this survey a novel multi-layered pipeline
ecosystem composed of (1) the Metaverse computing, networking, communications
and hardware infrastructure, (2) environment digitization, and (3) user
interactions. For every layer, we discuss the components that detail the steps
of its development. Also, for each of these components, we examine the impact
of a set of enabling technologies and empowering domains (e.g., Artificial
Intelligence, Security & Privacy, Blockchain, Business, Ethics, and Social) on
its advancement. In addition, we explain the importance of these technologies
to support decentralization, interoperability, user experiences, interactions,
and monetization. Our presented study highlights the existing challenges for
each component, followed by research directions and potential solutions. To the
best of our knowledge, this survey is the most comprehensive and allows users,
scholars, and entrepreneurs to get an in-depth understanding of the Metaverse
ecosystem to find their opportunities and potentials for contribution
The Viability and Potential Consequences of IoT-Based Ransomware
With the increased threat of ransomware and the substantial growth of the Internet of Things (IoT) market, there is significant motivation for attackers to carry out IoT-based ransomware campaigns. In this thesis, the viability of such malware is tested.
As part of this work, various techniques that could be used by ransomware developers to attack commercial IoT devices were explored. First, methods that attackers could use to communicate with the victim were examined, such that a ransom note was able to be reliably sent to a victim. Next, the viability of using "bricking" as a method of ransom was evaluated, such that devices could be remotely disabled unless the victim makes a payment to the attacker. Research was then performed to ascertain whether it was possible to remotely gain persistence on IoT devices, which would improve the efficacy of existing ransomware methods, and provide opportunities for more advanced ransomware to be created. Finally, after successfully identifying a number of persistence techniques, the viability of privacy-invasion based ransomware was analysed.
For each assessed technique, proofs of concept were developed. A range of devices -- with various intended purposes, such as routers, cameras and phones -- were used to test the viability of these proofs of concept. To test communication hijacking, devices' "channels of communication" -- such as web services and embedded screens -- were identified, then hijacked to display custom ransom notes. During the analysis of bricking-based ransomware, a working proof of concept was created, which was then able to remotely brick five IoT devices. After analysing the storage design of an assortment of IoT devices, six different persistence techniques were identified, which were then successfully tested on four devices, such that malicious filesystem modifications would be retained after the device was rebooted. When researching privacy-invasion based ransomware, several methods were created to extract information from data sources that can be commonly found on IoT devices, such as nearby WiFi signals, images from cameras, or audio from microphones. These were successfully implemented in a test environment such that ransomable data could be extracted, processed, and stored for later use to blackmail the victim.
Overall, IoT-based ransomware has not only been shown to be viable but also highly damaging to both IoT devices and their users. While the use of IoT-ransomware is still very uncommon "in the wild", the techniques demonstrated within this work highlight an urgent need to improve the security of IoT devices to avoid the risk of IoT-based ransomware causing havoc in our society. Finally, during the development of these proofs of concept, a number of potential countermeasures were identified, which can be used to limit the effectiveness of the attacking techniques discovered in this PhD research
A Decision Support System for Economic Viability and Environmental Impact Assessment of Vertical Farms
Vertical farming (VF) is the practice of growing crops or animals using the vertical dimension via multi-tier racks or vertically inclined surfaces. In this thesis, I focus on the emerging industry of plant-specific VF. Vertical plant farming (VPF) is a promising and relatively novel practice that can be conducted in buildings with environmental control and artificial lighting. However, the nascent sector has experienced challenges in economic viability, standardisation, and environmental sustainability. Practitioners and academics call for a comprehensive financial analysis of VPF, but efforts are stifled by a lack of valid and available data.
A review of economic estimation and horticultural software identifies a need for a decision support system (DSS) that facilitates risk-empowered business planning for vertical farmers. This thesis proposes an open-source DSS framework to evaluate business sustainability through financial risk and environmental impact assessments. Data from the literature, alongside lessons learned from industry practitioners, would be centralised in the proposed DSS using imprecise data techniques. These techniques have been applied in engineering but are seldom used in financial forecasting. This could benefit complex sectors which only have scarce data to predict business viability.
To begin the execution of the DSS framework, VPF practitioners were interviewed using a mixed-methods approach. Learnings from over 19 shuttered and operational VPF projects provide insights into the barriers inhibiting scalability and identifying risks to form a risk taxonomy. Labour was the most commonly reported top challenge. Therefore, research was conducted to explore lean principles to improve productivity.
A probabilistic model representing a spectrum of variables and their associated uncertainty was built according to the DSS framework to evaluate the financial risk for VF projects. This enabled flexible computation without precise production or financial data to improve economic estimation accuracy. The model assessed two VPF cases (one in the UK and another in Japan), demonstrating the first risk and uncertainty quantification of VPF business models in the literature. The results highlighted measures to improve economic viability and the viability of the UK and Japan case.
The environmental impact assessment model was developed, allowing VPF operators to evaluate their carbon footprint compared to traditional agriculture using life-cycle assessment. I explore strategies for net-zero carbon production through sensitivity analysis. Renewable energies, especially solar, geothermal, and tidal power, show promise for reducing the carbon emissions of indoor VPF. Results show that renewably-powered VPF can reduce carbon emissions compared to field-based agriculture when considering the land-use change.
The drivers for DSS adoption have been researched, showing a pathway of compliance and design thinking to overcome the ‘problem of implementation’ and enable commercialisation. Further work is suggested to standardise VF equipment, collect benchmarking data, and characterise risks. This work will reduce risk and uncertainty and accelerate the sector’s emergence
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