4,384 research outputs found
Beam scanning by liquid-crystal biasing in a modified SIW structure
A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium
A stratified decision-making model for long-term planning: application in flood risk management in Scotland
In a standard decision-making model for a game of chance, the best strategy is chosen based on the current state of the system under various conditions. There is however a shortcoming of this standard model, in that it can be applicable only for short-term decision-making periods. This is primarily due to not evaluating the dynamic characteristics and changes in status of the system and the outcomes of nature towards an a priori target or ideal state, which can occur in longer periods. Thus, in this study, a decision-making model based on the concept of stratification (CST), game theory and shared socio-economic pathway (SSP) is developed and its applicability to disaster management is shown. The game of chance and CST have been integrated to incorporate the dynamic nature of the decision environment for long-term disaster risk planning, while accounting for various states of the system and an ideal state. Furthermore, an interactive web application with dynamic user interface is built based on the proposed model to enable decision makers to identify the best choices in their model by a predictive approach. The Monte Carlo simulation is applied to experimentally validate the proposed model. Then, it is demonstrated how this methodology can suitably be applied to obtain ad hoc models, solutions, and analysis in the strategic decision-making process of flooding risk strategy evaluation. The model's applicability is shown in an uncertain real-world decision-making context, considering dynamic nature of socio-economic situations and flooding hazards in the Highland and Argyll Local Plan District in Scotland. The empirical results show that flood forecasting and awareness raising are the two most beneficial mitigation strategies in the region followed by emergency plans/response, planning policies, maintenance, and self help
Aerial Network Assistance Systems for Post-Disaster Scenarios : Topology Monitoring and Communication Support in Infrastructure-Independent Networks
Communication anytime and anywhere is necessary for our modern society to function. However, the critical network infrastructure quickly fails in the face of a disaster and leaves the affected population without means of communication. This lack can be overcome by smartphone-based emergency communication systems, based on infrastructure-independent networks like Delay-Tolerant Networks (DTNs). DTNs, however, suffer from short device-to-device link distances and, thus, require multi-hop routing or data ferries between disjunct parts of the network. In disaster scenarios, this fragmentation is particularly severe because of the highly clustered human mobility behavior. Nevertheless, aerial communication support systems can connect local network clusters by utilizing Unmanned Aerial Vehicles (UAVs) as data ferries. To facilitate situation-aware and adaptive communication support, knowledge of the network topology, the identification of missing communication links, and the constant reassessment of dynamic disasters are required. These requirements are usually neglected, despite existing approaches to aerial monitoring systems capable of detecting devices and networks.
In this dissertation, we, therefore, facilitate the coexistence of aerial topology monitoring and communications support mechanisms in an autonomous Aerial Network Assistance System for infrastructure-independent networks as our first contribution. To enable system adaptations to unknown and dynamic disaster situations, our second contribution addresses the collection, processing, and utilization of topology information. For one thing, we introduce cooperative monitoring approaches to include the DTN in the monitoring process. Furthermore, we apply novel approaches for data aggregation and network cluster estimation to facilitate the continuous assessment of topology information and an appropriate system adaptation. Based on this, we introduce an adaptive topology-aware routing approach to reroute UAVs and increase the coverage of disconnected nodes outside clusters.
We generalize our contributions by integrating them into a simulation framework, creating an evaluation platform for autonomous aerial systems as our third contribution. We further increase the expressiveness of our aerial system evaluation, by adding movement models for multicopter aircraft combined with power consumption models based on real-world measurements. Additionally, we improve the disaster simulation by generalizing civilian disaster mobility based on a real-world field test. With a prototypical system implementation, we extensively evaluate our contributions and show the significant benefits of cooperative monitoring and topology-aware routing, respectively. We highlight the importance of continuous and integrated topology monitoring for aerial communications support and demonstrate its necessity for an adaptive and long-term disaster deployment. In conclusion, the contributions of this dissertation enable the usage of autonomous Aerial Network Assistance Systems and their adaptability in dynamic disaster scenarios
Throughput of Hybrid UAV Networks with Scale-Free Topology
Unmanned Aerial Vehicles (UAVs) hold great potential to support a wide range
of applications due to the high maneuverability and flexibility. Compared with
single UAV, UAV swarm carries out tasks efficiently in harsh environment, where
the network resilience is of vital importance to UAV swarm. The network
topology has a fundamental impact on the resilience of UAV network. It is
discovered that scale-free network topology, as a topology that exists widely
in nature, has the ability to enhance the network resilience. Besides,
increasing network throughput can enhance the efficiency of information
interaction, improving the network resilience. Facing these facts, this paper
studies the throughput of UAV Network with scale-free topology. Introducing the
hybrid network structure combining both ad hoc transmission mode and cellular
transmission mode into UAV Network, the throughput of UAV Network is improved
compared with that of pure ad hoc UAV network. Furthermore, this work also
investigates the optimal setting of the hop threshold for the selection of ad
hoc or cellular transmission mode. It is discovered that the optimal hop
threshold is related with the number of UAVs and the parameters of scale-free
topology. This paper may motivate the application of hybrid network structure
into UAV Network.Comment: 15 pages, 7 figure
2023-2024 Lynn University Academic Catalog
The 2023-2024 Academic Catalog initially published as a web-only document.
The Department of Marketing and Communication created a PDF version, which is available for download here.https://spiral.lynn.edu/accatalogs/1052/thumbnail.jp
Power, Gender, and Trust in Experiences of Pediatric Emergency Physician Teleconsultation and Maternal Antenatal Anxiety in Pakistan
Background: In Pakistan, innovative strategies for improving access to health care, such as telemedicine (TM) and task shifting, are growing rapidly to address critical gaps in maternal and child health (MCH). Qualitative studies of social and contextual factors can help improve the development or implementation of such interventions.
Objectives: This dissertation closely examines constructs of power, gender, and trust in the contexts of two populations: (1) pediatric emergency medicine (PEM) providers in a novel TM program applying synchronous expert teleconsultation to improve quality of care, and (2) pregnant women with experiences of anxiety informing the content of a psychological intervention by non-specialists.
Methods: Manuscript one uses the TM Theory of Use framework to thematically analyze 20 in-depth interviews covering experiences or perspectives of doctors, nurses, and TM program administrators, while Manuscript two draws on conversation analysis methods to examine transcripts of 88 PEM teleconsultations. Manuscript three is a secondary analysis applying a women’s empowerment framework to formative research interviews on sources and mitigators of antenatal anxiety in 19 symptomatic women. Data for the qualitative TM program evaluation were collected from October 2019 to January 2020 at Sindh government hospitals, while formative research interviews on antenatal anxiety were conducted between September 2017 and August 2018 at Holy Family Hospital in Rawalpindi.
Results: Perceived levels of asymmetric power and mutual trust in TM produced widely divergent and conflicting theories of use among PEM providers, while some gender-based opportunities in TM contributed to emergent social functions beyond its intended aims. Although teleconsultants accounted for a disproportionate share of asking questions and controlling topic, closer examination revealed strategic ambiguity and reciprocity as means of negotiating power and building trust in TM-mediated clinical discourse, particularly by women teleconsultants. For antenatal anxiety, gender norms and women’s disempowerment were key contextual factors contributing to women’s symptoms and limiting pregnancy-related agency and available coping strategies.
Conclusion: Efforts to expand access to high quality care for mothers and children must include studies of context, whether the sociotechnical context of TM innovations or the cultural context of psychosocial interventions, to understand associated opportunities, constraints, successes, and failures in improving MCH
Strategically Managing the Value Creation and Productivity Paradox of Artificial Intelligence : The General Purpose Technology View
ABSTRACT
This doctoral dissertation explores the strategic management of artificial intelligence as a general purpose technology and its value creation in the context of multiple industries. I study what makes AI-based value creation challenging from the management and organization perspective despite the high technological performance of AI. I analyze this through five sub-research questions, and by applying grounded theory.
Empirically, I turn to 34 AI solution developers from 18 different industries who have both technical and business understanding of using AI. The AI solution developers suit this study because of their skills, capabilities, and power position to shape the present and future through the combined use of machine learning (ML) and other AI related technologies that are already impacting our daily lives in and out of work context.
The extant literature on AI in premium outlets on general management and organizational studies can be typified into five AI use phases: 1) antecedents of AI use, 2) AI use, 3) (empirical) impacts of AI use, 4) expected (cumulative) impacts of AI, and 5) AI-related paradigm shift. The five sub-research questions of this doctoral dissertation explore the definition of AI and the use phases 1-4 by approaching AI as the subject of study. The fifth AI use phase is excluded from this study as it would require using AI also as the research method.
The main contributions of this doctoral thesis include giving an overview of AI in management and organization, and pre-theoretically identifying the technical and socially constructed decision-making criteria for AI investments, six AI use types, how empirical AI impacts have been measured, what temporal dimensions are expected to be impacted by AI, and what AI strategies organizations have already adopted to create AI-based value and overcome its productivity paradox.
KEYWORDS: Artificial intelligence, machine learning, strategic management, value creation, automation, augmentation, hybrid intelligence, conjoined agencyTIIVISTELMÄ
Tämä väitöskirja keskittyy tekoälypohjaisen arvonluonnin strategiseen johtamiseen yli teollisuudenalarajojen. Lähestyn tekoälyä korkean suorituskyvyn omaavana yleiskäyttöisenä teknologiana ja analysoin ilmiö- ja aineistopohjaisesti sitä, mikä tekee tekoälypohjaisesta arvonluonnista silti haastavaa johtamisen ja organisoinnin näkökulmasta viiden alatutkimuskysymyksen avulla.
Haastattelin tätä työtä varten 34 tekoälyratkaisuja 18 eri teollisuudenalalla kehittävää asiantuntijaa. He sopivat haastateltaviksi, koska heillä on alan osaamista sekä teknisestä että käytännön sovellusten näkökulmasta, ja koska heillä on valta-asema kehittää koneoppimiseen ja muihin tekoälyteknologoihin pohjautuvia ratkaisuja, jotka jo vaikuttavat päivittäiseen elämäämme työelämässä ja sen ulkopuolella.
Yleisen johtamisen ja organisaatiotutkimuksen huippujulkaisuista kerätty kirjallisuus voidaan jakaa viiteen tekoälyn käyttövaiheeseen: 1) tekoälyn käyttöä edeltävät tekijät, 2) tekoälyn käyttö, 3) tekoälyn (empiiriset) vaikutukset, 4) odotettavissa olevat tekoälyn (kumulatiiviset) vaikutukset, sekä 5) tekoälyyn liittyvät paradigman muutokset. Tämän väitöskirjan viisi alatutkimuskysymystä keskittyvät tekoälyn määritelmään sekä tekoälyn käyttövaiheisiin 1-4. Viides tekoälyn käyttövaihe on jätetty tämän tutkimuksen ulkopuolelle, koska se vaatisi tekoälyn käyttöä myös tutkimusmetodina.
Tämän tutkimuksen päätuotokset luovat yleiskuvan tekoälystä johtamisen ja organisoinnin kirjallisuudessa. Empiiriset tulokset tyypittelevät investointi-päätöksiin vaikuttavia tekijöitä, sekä kuusi erilaista tekoälyn käyttötapausta. Analysoin, miten tekoälyn vaikutuksia on mitattu, mihin aikaan liittyviin tekijöihin tekoälyn odotetaan vaikuttavan, ja mitä tekoälystrategioita organisaatiot ovat jo omaksuneet luodakseen arvoa ja ylittääkseen tekoälyn tuottavuusparadoksin.
ASIASANAT: Artificial intelligence, machine learning, strategic management, value creation, automation, augmentation, hybrid intelligence, conjoined agenc
Optimisation of Triboelectric Nanogenerator performance in vertical contact-separation mode
Triboelectric nanogenerator (TENG) is one of the most promising energy harvesters – a technology that uses repeated or reciprocating contact of suitably chosen materials to generate charge via the triboelectric effect (TE) and utilizes this as usable voltage and current. TENGs are attractive as they can continuously generate charge over a wide range of operating conditions and have several valuable advantages such as light weight, simple structure, low cost and high efficiency. Therefore, TENGs have been explored in a wide range of applications, including self-powered wearable electronics, powering electronics and even for harvesting ocean wave/wind energy. One of the major limitations of TENGs is their low power output (usually <500 W/m2). This thesis focuses of a few specific approaches to optimising TENG output performance. This thesis begins by presenting a solution to this challenge by optimizing a low permittivity substrate beneath the tribo-contact layer. The open circuit voltage is found to increase by a factor of 1.3 in moving from PET to the lower permittivity PTFE. TENG performance is also believed to depend on contact force, but the origin of the dependence had not previously been explored. Herein, we show that this behaviour results from a contact force dependent real contact area Ar as governed by surface roughness. The open circuit voltage Voc, short circuit current Isc and Ar for a TENG were found to increase with contact force/pressure. Critically, Voc and Isc saturate at the same contact pressure as Ar suggesting that electrical output follows the same evolution as Ar. Assuming that tribo charges can only transfer across the interface at areas of real contact, it follows that an increasing Ar with contact pressure should produce a corresponding increase in the electrical output. These results underline the importance of accounting for real contact area in TENG design, as well as the distinction between real and nominal contact area in tribo-charge density definition. High-performance ferroelectricassisted TENGs (Fe-TENGs) are developed using electrospun fibrous surfaces based on P(VDFTrFE) with dispersed BaTiO3 (BTO) nanofillers in either cubic (CBTO) or tetragonal (TBTO) form in this thesis. TENGs with three types of tribo-negative surface were investigated and output increased progressively. Critically, P(VDF-TrFE)/TBTO produced higher output than P(VDFTrFE)/ CBTO even though permittivity is nearly identical. Thus, it is shown that BTO fillers boost output, not just by increasing permittivity, but also by enhancing the crystallinity and amount of the β-phase (as TBTO produced a more crystalline β-phase present in greater amounts)
CITIES: Energetic Efficiency, Sustainability; Infrastructures, Energy and the Environment; Mobility and IoT; Governance and Citizenship
This book collects important contributions on smart cities. This book was created in collaboration with the ICSC-CITIES2020, held in San José (Costa Rica) in 2020. This book collects articles on: energetic efficiency and sustainability; infrastructures, energy and the environment; mobility and IoT; governance and citizenship
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