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DROPS: Dynamic Radio Protocol Selection for Energy-Constrained Wearable IoT Healthcare
No full textWe propose 'DROPS', a scheme which dynamically selects radio protocols in an energy-constrained wearable IoT healthcare system. We consider the use of multiple radio protocols, which are capable of transmitting a patient's sensed physiological parameters to the server through Local Processing Units (LPUs). As the health parameters are non-stationary and temporally fluctuating, especially for critical patients, the selection of an appropriate radio protocol is essential to maintain the accuracy and timely delivery of data from the patient to the server. Additionally, the mobility of patients through various locations within the hospital mandates the selection of the best radio protocol among the multiple available ones for each location, to enable data to offload to the remote server. We use single-leader-multiple-follower Stackelberg non-cooperative game to map the strategic interactions between a patient's LPU and the hospital's server. 'DROPS' dynamically selects the appropriate radio protocol, based on the criticality index of a patient, the reputation of the radio, the Euclidean distance between the radios and the LPU, and the load on the protocol. Results on real-life data and their large-scale emulation show that the data rate increases by almost 78% and throughput by approximately 7%, as compared to existing schemes
A Socio-Technical Perspective on Urban Analytics: The Case of City-Scale Digital Twins
No full textThis paper demonstrates that a shift from a purely technical to a more socio-technical perspective has significant implications for the conceptualization, design, and implementation of smart city technologies. Such implications are discussed and illustrated through the case of an emerging urban analytics tool, the City-scale Digital Twin. Based on interdisciplinary insights and a participatory knowledge co-production and tool co-development process, including both researchers and prospective users, we conclude that in order to move beyond a mere “hype technology,” City-Scale Digital Twins must reflect the specifics of the urban and socio-political context
Machine-learned interatomic potentials for alloys and alloy phase diagrams
No full textWe introduce machine-learned potentials for Ag-Pd to describe the energy of alloy configurations over a wide range of compositions. We compare two different approaches. Moment tensor potentials (MTPs) are polynomial-like functions of interatomic distances and angles. The Gaussian approximation potential (GAP) framework uses kernel regression, and we use the smooth overlap of atomic position (SOAP) representation of atomic neighborhoods that consist of a complete set of rotational and permutational invariants provided by the power spectrum of the spherical Fourier transform of the neighbor density. Both types of potentials give excellent accuracy for a wide range of compositions, competitive with the accuracy of cluster expansion, a benchmark for this system. While both models are able to describe small deformations away from the lattice positions, SOAP-GAP excels at transferability as shown by sensible transformation paths between configurations, and MTP allows, due to its lower computational cost, the calculation of compositional phase diagrams. Given the fact that both methods perform nearly as well as cluster expansion but yield off-lattice models, we expect them to open new avenues in computational materials modeling for alloys
Improving the track friendliness of a four-axle railway vehicle using an inertance-integrated lateral primary suspension
No full textImproving the track friendliness of a railway vehicle can benefit the railway industry significantly. Rail surface damage in curves can be reduced by using vehicles with a lower Primary Yaw Stiffness (PYS); however, this can reduce high-speed stability and worsen ride comfort. Previous studies have shown that this trade-off between track friendliness and passenger comfort can be successfully combated by using an inerter in the primary suspension; however, these utilise simplified vehicle models, contact models, and track inputs. Considering a realistic four-axle passenger vehicle model, this paper investigates the extent to which the PYS can be reduced with inertance-integrated primary lateral suspensions without increasing root-mean-square (RMS) carbody lateral accelerations. The vehicle model, with these enhanced suspensions, has been created in VAMPIRE (Formula presented.), with the dynamics being captured over a range of vehicle velocities and equivalent conicities. Based on systematic optimisations using network-synthesis theory, several beneficial inertance-integrated configurations are identified, and the PYS can be reduced by up to 47% compared to the default vehicle (a potential Network Rail Variable Usage Charge saving of 26%), without increasing RMS carbody lateral accelerations. Further simulations are performed to investigate the vehicle's performance in curve transitions and when subject to one-off peak lateral track irregularities
More than a feeling? Toward a theory of customer delight
No full textPurpose: Responding to an increasing call for a more comprehensive conceptualization of customer delight, the purpose of this paper is to expand the theory of customer delight and to examine the implications of such an expanded view for service theory and practice. Design/methodology/approach: This paper presents the results of three qualitative studies. The first study explores customer delight through self-reported consumption experiences in customer-selected contexts, followed by one-on-one in-depth interviews. The second involves focus groups and the third examines self-reported incidents of delightful customer experiences. Findings: This research finds that customer delight goes beyond extreme satisfaction and joy and surprise to include six properties that—individually or in combination—characterize customer delight. An expanded conceptualization of how customer delight can be defined is proposed in which customer delight is associated with various combinations of six properties – the customer experiencing positive emotions, interacting with others, successful problem-solving, engaging customer’s senses, timing of the events and sense of control that characterizes the customer's encounter. Research limitations/implications: It is clear from the findings of this research that there is no single property that is associated with delight. Through the facilitation of multiple properties, managers have the potential to create a multitude of routes to delight. It is recommended that future research (1) identify and explicate these alternative routes for engendering delight using the six properties identified, and (2) develop a general typology based on service context and characteristics, customer segment, etc. that further stimulates scholarship on delight, and offers more industry-specific insights for managers. Practical implications: Insights from this investigation will encourage managers and service designers to think more broadly and creatively about delight. Doing so will open up new opportunities for achieving customer delight, beyond merely focusing on extreme satisfaction or surprise and joy strategies currently dominating discussions of customer delight. Originality/value: This paper makes several contributions to the service literature. First, it extends current conceptualizations of customer delight and offers an expanded definition. Next, it demonstrates how this new understanding extends the existing literature on delight. Finally, it proposes an agenda for future delight research and discusses managerial implications, opening up new opportunities for firms to design delightful customer experiences
Shape optimization of thermoacoustic systems using a two-dimensional adjoint helmholtz solver
No full textThermoacoustic instabilities, which arise due to the interaction between flames and acoustics, are sensitive to small changes to the system parameters. In this paper, we apply adjoint-based shape optimization to a 2D finite element Helmholtz solver to find accurately and inexpensively the shape changes that most stabilize a 2D thermoacoustic system in the linear regime. We examine two cases: a Rijke tube and a turbulent swirl combustor. Both systems exhibit an unstable longitudinal mode and we suppress the instability by slightly modifying the geometry. In the case of the turbulent swirl combustor, the sensitivities are higher in the plenum and in the burner than in the combustion chamber, mainly due to the effect of the mean temperature. In the cooler regions, the local wavelength is shorter, which means that geometry changes of a given distance have more influence than they do where the local wavelength is longer. This is the first time adjoint-based shape optimization is applied to 2D Helmholtz solvers in thermoacoustics, after being previously applied to low-order thermoacoustic networks. But Helmholtz solvers have an intrinsic advantage: they can handle complex geometries. The easy scalability of this method to complex 3D geometries makes this tool a strong candidate for the iterative design of thermoacoustically stable combustors
Wavelength-sensitive photocatalytic H<inf>2</inf> evolution from H<inf>2</inf>S splitting over g-C<inf>3</inf>N<inf>4</inf> with S,N-codoped carbon dots as the photosensitizer
No full textPhotocatalytic splitting of hydrogen sulfide (H2S) for hydrogen evolution is a promising method to solve the energy and environmental issues. In this work, S,N-codoped carbon dots (S,N-CDs)/graphitic carbon nitride (g-C3N4) nanosheet is synthesized by hydrothermal method as an efficient photocatalyst for the decomposition of H2S. In addition to the characterization of the morphology and structure, chemical state, optical and electrochemical performances of S,N-CDs/g-C3N4, hydrogen evolution tests show that the activity of g-C3N4 is improved by introducing S,N-CDs, and the enhancement depends strongly on the wavelength of incident light. The photocatalytic hydrogen production rate of S,N-CDs/g-C3N4 composite reaches 832 μmol g−1h−1, which is 38 times to that of g-C3N4 under irradiation at 460 nm. Density functional theory calculations and electron paramagnetic resonance as well as photoluminescence technologies have altogether authenticated that the unique wavelength-dependent photosensitization of S,N-CDs on g-C3N4; meanwhile, a good match between the energy level of S,N-CDs and g-C3N4 is pivotal for the effective photocatalytic activity. Our work has unveiled the detailed mechanism of the photocatalytic activity enhancement in S,N-CDs/g-C3N4 composite and showed its potential in photocatalytic splitting of H2S for hydrogen evolution
24 [1×12] Wavelength Selective Switches Integrated on a Single 4k LCoS Device
No full textThis article demonstrates the design, assembly, optimisation, and characterisation of 24 [1 × 12] wavelength selective switches (WSSs) based on a single set of optics and a 4k liquid crystal on silicon (LCoS) device. The average insertion loss was measured to be 8.4 dB with an average crosstalk level of 26.9 dB. To our knowledge, this module with 312 fibre ports is the highest-capacity WSS demonstrated so far. The module can be flexibly reconfigured into different switches and port counts for advanced reconfigurable optical add/drop multiplexer (ROADM) applications
Supply network design to address United Nations Sustainable Development Goals: A case study of blockchain implementation in Thai fish industry
No full textSustainable Development Goals present an opportunity for industries to (re)design their supply chains. It is understood that digital technologies like blockchain can be helpful in achieving certain Sustainable Development Goals linked to livelihoods, food security, and the environment, by identifying issues and implementing interventions in real-time. However, there is limited understanding over data structure requirements for blockchain technology implementation in digitally-enabled food supply chains. Therefore, this research studies the design of blockchain-centric food supply chains that promote Sustainable Development Goals, within the context of the Thai fish industry. Key findings suggest that data asymmetry exists in supply chains to achieve Sustainable Development Goals. This research presents four design principles and an integrated technology implementation framework, derived from empirical data, for blockchain-centric food supply chains. The research outcome contributes to the supply chain management field and could ultimately impact the resilience of fishery ecosystems and the achievement of Sustainable Development Goals
Frequency and Voltage Regulation in Hybrid AC/DC Networks
No full textHybrid ac/dc networks are a key technology for sustainable electrical power systems, due to the increasing number of converter-based distributed energy resources such as solar or wind. In this article, we consider the design of control schemes for hybrid ac/dc networks, focusing especially on the control of the interlinking converters (ILCs). We present two control schemes: first for decentralized primary control and second a distributed controller to achieve secondary control objectives as well. In the primary case, the stability of the controlled system is proven in a general hybrid ac/dc network, which may include asynchronous ac subsystems. Furt hermore, it is demonstrated that power sharing across the ac/dc network is significantly improved compared to previously proposed dual-droop control. The proposed scheme for secondary control guarantees the convergence of the ac system frequencies and the average dc voltage of each dc subsystem to their nominal values. An optimal power allocation is also achieved at steady state. The applicability and effectiveness of the proposed algorithms are verified by advanced simulations on a test hybrid ac/dc network in Simscape Power Systems