9,379 research outputs found
Key technologies for safe and autonomous drones
Drones/UAVs are able to perform air operations that are very difficult to be performed by manned aircrafts. In addition, drones' usage brings significant economic savings and environmental benefits, while reducing risks to human life. In this paper, we present key technologies that enable development of drone systems. The technologies are identified based on the usages of drones (driven by COMP4DRONES project use cases). These technologies are grouped into four categories: U-space capabilities, system functions, payloads, and tools. Also, we present the contributions of the COMP4DRONES project to improve existing technologies. These contributions aim to ease drones’ customization, and enable their safe operation.This project has received funding from the ECSEL Joint Undertaking (JU) under grant agreement No 826610. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and Spain, Austria, Belgium, Czech Republic, France, Italy, Latvia, Netherlands. The total project budget is 28,590,748.75 EUR (excluding ESIF partners), while the requested grant is 7,983,731.61 EUR to ECSEL JU, and 8,874,523.84 EUR of National and ESIF Funding. The project has been started on 1st October 2019
A fuzzy set theory-based fast fault diagnosis approach for rotators of induction motors
Induction motors have been widely used in industry, agriculture, transportation, national defense engineering, etc. Defects of the motors will not only cause the abnormal operation of production equipment but also cause the motor to run in a state of low energy efficiency before evolving into a fault shutdown. The former may lead to the suspension of the production process, while the latter may lead to additional energy loss. This paper studies a fuzzy rule-based expert system for this purpose and focuses on the analysis of many knowledge representation methods and reasoning techniques. The rotator fault of induction motors is analyzed and diagnosed by using this knowledge, and the diagnosis result is displayed. The simulation model can effectively simulate the broken rotator fault by changing the resistance value of the equivalent rotor winding. And the influence of the broken rotor bar fault on the motors is described, which provides a basis for the fault characteristics analysis. The simulation results show that the proposed method can realize fast fault diagnosis for rotators of induction motors
AI & Blockchain as sustainable teaching and learning tools to cope with the 4IR
The Fourth Industrial Revolution (4IR) is transforming the way we live and
work, and education is no exception. To cope with the challenges of 4IR, there
is a need for innovative and sustainable teaching and learning tools. AI and
block chain technologies hold great promise in this regard, with potential
benefits such as personalized learning, secure credentialing, and decentralized
learning networks. This paper presents a review of existing research on AI and
block chain in education, analyzing case studies and exploring the potential
benefits and challenges of these technologies. The paper also suggests a unique
model for integrating AI and block chain into sustainable teaching and learning
practices. Future research directions are discussed, including the need for
more empirical studies and the exploration of ethical and social implications.
The key summary of this discussion is that, by enhancing accessibility,
efficacy, and security in education, AI and blockchain have the potential to
revolutionise the field. In order to ensure that students can benefit from
these potentially game-changing technologies as technology develops, it will be
crucial to find ways to harness its power while minimising hazards. Overall,
this paper highlights the potential of AI and block chain as sustainable tools
for teaching and learning in the 4IR era and their respective advantages,
issues and future prospects have been discussed in this writing
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
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Ensuring Access to Safe and Nutritious Food for All Through the Transformation of Food Systems
Hardware Acceleration of Neural Graphics
Rendering and inverse-rendering algorithms that drive conventional computer
graphics have recently been superseded by neural representations (NR). NRs have
recently been used to learn the geometric and the material properties of the
scenes and use the information to synthesize photorealistic imagery, thereby
promising a replacement for traditional rendering algorithms with scalable
quality and predictable performance. In this work we ask the question: Does
neural graphics (NG) need hardware support? We studied representative NG
applications showing that, if we want to render 4k res. at 60FPS there is a gap
of 1.5X-55X in the desired performance on current GPUs. For AR/VR applications,
there is an even larger gap of 2-4 OOM between the desired performance and the
required system power. We identify that the input encoding and the MLP kernels
are the performance bottlenecks, consuming 72%,60% and 59% of application time
for multi res. hashgrid, multi res. densegrid and low res. densegrid encodings,
respectively. We propose a NG processing cluster, a scalable and flexible
hardware architecture that directly accelerates the input encoding and MLP
kernels through dedicated engines and supports a wide range of NG applications.
We also accelerate the rest of the kernels by fusing them together in Vulkan,
which leads to 9.94X kernel-level performance improvement compared to un-fused
implementation of the pre-processing and the post-processing kernels. Our
results show that, NGPC gives up to 58X end-to-end application-level
performance improvement, for multi res. hashgrid encoding on average across the
four NG applications, the performance benefits are 12X,20X,33X and 39X for the
scaling factor of 8,16,32 and 64, respectively. Our results show that with
multi res. hashgrid encoding, NGPC enables the rendering of 4k res. at 30FPS
for NeRF and 8k res. at 120FPS for all our other NG applications
INVESTIGATING THE PERCEPTION OF EXPATRIATES TOWARDS IMMIGRATION SERVICE QUALITY IN SHARJAH, UNITED ARAB EMIRATES THROUGH MIXED METHOD APPROACH
The public sectors in UAE are under immense pressure to demonstrate that their services are customer-focused and that continuous performance improvement is being delivered. The United Arab Emirates is a favoured destination for expatriates due to its own citizens form a minority of the population and are barely represented in the private sector workforce. These highly unusual demographics confer high importance on the national immigration services. Recently, increased interest in international migration, specifically within the United Arab Emirates, has been shown both by government agencies and by the governments of industrialised countries. Given the importance of the expatriate labour force to economic stability and growth in the Emirates, this research investigates how immigration services are perceived, with the aim of contributing to their improvement, thus ultimately supporting economic growth. It proposes a service quality perception framework to improve understanding within SID of how to raise levels of service delivered to migrants and other persons directly or indirectly affected by SID services.
Qualitative data were collected by means of semi-structured interviews and quantitative data by means of a questionnaire survey based on the abovementioned framework. The survey data, on the variables influencing participants’ experiences and perceptions of SID services, were subjected to statistical analysis. The framework was then used to evaluate quality of service in terms of general impressions, delivery, location, response, SID culture and behaviour. Numerical data were analysed using inferential and descriptive statistics. It was found that service quality positively influenced service behaviour and that this relationship was mediated by SID culture.
This research makes an original contribution to knowledge as one of the few studies of immigration to the United Arab Emirates. By examining the workings of one immigration department, it adds to the literature on immigration departments and organisational development in developing countries. It illuminates the mechanics of immigration services and demonstrates their increasing importance to the world economy
Review of Methodologies to Assess Bridge Safety During and After Floods
This report summarizes a review of technologies used to monitor bridge scour with an emphasis on techniques appropriate for testing during and immediately after design flood conditions. The goal of this study is to identify potential technologies and strategies for Illinois Department of Transportation that may be used to enhance the reliability of bridge safety monitoring during floods from local to state levels. The research team conducted a literature review of technologies that have been explored by state departments of transportation (DOTs) and national agencies as well as state-of-the-art technologies that have not been extensively employed by DOTs. This review included informational interviews with representatives from DOTs and relevant industry organizations. Recommendations include considering (1) acquisition of tethered kneeboard or surf ski-mounted single-beam sonars for rapid deployment by local agencies, (2) acquisition of remote-controlled vessels mounted with single-beam and side-scan sonars for statewide deployment, (3) development of large-scale particle image velocimetry systems using remote-controlled drones for stream velocity and direction measurement during floods, (4) physical modeling to develop Illinois-specific hydrodynamic loading coefficients for Illinois bridges during flood conditions, and (5) development of holistic risk-based bridge assessment tools that incorporate structural, geotechnical, hydraulic, and scour measurements to provide rapid feedback for bridge closure decisions.IDOT-R27-SP50Ope
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The influence of blockchains and internet of things on global value chain
Copyright © 2022 The Authors. Despite the increasing proliferation of deploying the internet of things (IoT) in the global value chain (GVC), several challenges might lead to a lack of trust among value chain partners, for example, technical challenges (i.e., confidentiality, authenticity, and privacy); and security challenges (i.e., counterfeiting, physical tampering, and data theft). In this study, we argue that blockchain technology (BT), when combined with the IoT ecosystem, will strengthen GVC and enhance value creation and capture among value chain partners. Therefore, we examine the impact of BT combined with the IoT ecosystem and how it can be utilized to enhance value creation and capture among value chain partners. We collected data through an online survey, and 265 U.K. Agri-food retailers completed the survey. Our data were analyzed using structural equation modeling. Our finding reveals that BT enhances GVC by improving IoT scalability, security, and traceability combined with the IoT ecosystem. Moreover, the combination of BT and IoT strengthens GVC and creates more value for value chain partners, which serves as a competitive advantage. Finally, our research outlines the theoretical and practical contribution of combining BT and the IoT ecosystem
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