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Journal articleSerban A-I, Soreq E, Barnaghi P, et al., 2022,
The effect of COVID-19 on the home behaviours of people affected by dementia
, npj Digital Medicine, Vol: 5, ISSN: 2398-6352The COVID-19 pandemic has dramatically altered the behaviour of most of the world’s population, particularly affecting the elderly, including people living with dementia (PLwD). Here we use remote home monitoring technology deployed into 31 homes of PLwD living in the UK to investigate the effects of COVID-19 on behaviour within the home, including social isolation. The home activity was monitored continuously using unobtrusive sensors for 498 days from 1 December 2019 to 12 April 2021. This period included six distinct pandemic phases with differing public health measures, including three periods of home ‘lockdown’. Linear mixed-effects modelling is used to examine changes in the home activity of PLwD who lived alone or with others. An algorithm is developed to quantify time spent outside the home. Increased home activity is observed from very early in the pandemic, with a significant decrease in the time spent outside produced by the first lockdown. The study demonstrates the effects of COVID-19 lockdown on home behaviours in PLwD and shows how unobtrusive home monitoring can be used to track behaviours relevant to social isolation.
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Journal articleZhang Qiu P, Yongxuan T, Thompson O, et al., 2022,
Soft tissue characterisation using a novel robotic medical percussion device with acoustic analysis and neural networks
, IEEE Robotics and Automation Letters, Vol: 7, Pages: 11314-11321, ISSN: 2377-3766Medical percussion is a common manual examination procedure used by physicians to determine the state of underlying tissues from their acoustic responses. Although it has been used for centuries, there is a limited quantitative understanding of its dynamics, leading to subjectivity and a lack of detailed standardisation. This letter presents a novel compliant two-degree-of-freedom robotic device inspired by the human percussion action, and validates its performance in two tissue characterisation experiments. In Experiment 1, spectro-temporal analysis using 1-D Continuous Wavelet Transform (CWT) proved the potential of the device to identify hard nodules, mimicking lipomas, embedded in silicone phantoms representing a patient's abdominal region. In Experiment 2, Gaussian Mixture Modelling (GMM) and Neural Network (NN) predictive models were implemented to classify composite phantom tissues of varying density and thickness. The proposed device and methods showed up to 97.5% accuracy in the classification of phantoms, proving the potential of robotic solutions to standardise and improve the accuracy of percussion diagnostic procedures.
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Journal articlePlanella FB, Ai W, Boyce AM, et al., 2022,
A continuum of physics-based lithium-ion battery models reviewed
, PROGRESS IN ENERGY, Vol: 4- Author Web Link
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- Citations: 20
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Journal articleAi W, Wu B, Martínez-Pañeda E, 2022,
A coupled phase field formulation for modelling fatigue cracking in lithium-ion battery electrode particles
, Journal of Power Sources, Vol: 544, ISSN: 0378-7753Electrode particle cracking is one of the main phenomena driving battery capacity degradation. Recent phase field fracture studies have investigated particle cracking behaviour. However, only the beginning of life has been considered and effects such as damage accumulation have been neglected. Here, a multi-physics phase field fatigue model has been developed to study crack propagation in battery electrode particles undergoing hundreds of cycles. In addition, we couple our electrochemo-mechanical formulation with X-ray CT imaging to simulate fatigue cracking of realistic particle microstructures. Using this modelling framework, non-linear crack propagation behaviour is predicted, leading to the observation of an exponential increase in cracked area with cycle number. Three stages of crack growth (slow, accelerating and unstable) are observed, with phenomena such as crack initialisation at concave regions and crack coalescence having a significant contribution to the resulting fatigue crack growth rates. The critical values of C-rate, particle size and initial crack length are determined, and found to be lower than those reported in the literature using static fracture models. Therefore, this work demonstrates the importance of considering fatigue damage in battery degradation models and provides insights on the control of fatigue crack propagation to alleviate battery capacity degradation.
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Journal articleYang S, Zhou C, Wang Q, et al., 2022,
Highly‐aligned ultra‐thick gel‐based cathodes unlocking ultra‐high energy density batteries
, Energy & Environmental Materials, Vol: 5, Pages: 1332-1339, ISSN: 2575-0356Increasing electrode thickness can substantially enhance the specific energy of lithium-ion batteries, however ionic transport, electronic conductivity and ink rheology are current barriers to adoption. Here a novel approach using a mixed xanthan gum and locust bean gum binder to construct ultra-thick electrodes is proposed to address above issues. After combining aqueous binder with single walled carbon nanotubes (SWCNT), active material (LiNi0.8Co0.1Mn0.1O2) and subsequent vacuum freeze drying, highly-aligned and low tortuosity structures with a porosity of ca. 50% can be achieved with an average pore size of 10 μm, whereby the gum binder-SWCNT-NMC811 forms vertical structures supported by tissue-like binder/SWCNT networks allowing for excellent electronic conducting phase percolation. As a result, ultra-thick electrodes with a mass loading of about 511 mg·cm-2 and 99.5 wt% active materials have been demonstrated with a remarkable areal capacity of 79.3 mAh·cm−2, which is the highest value reported so far. This represents a >25x improvement compared to conventional electrodes with an areal capacity of about 3 mAh·cm-2. This route also can be expanded to other electrode materials, such as LiFePO4 and Li4Ti5O12, and thus opens the possibility for low-cost and sustainable ultra-thick electrodes with increased specific energy for future lithium-ion batteries.
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Journal articleCursi F, Bai W, Yeatman EM, et al., 2022,
Optimization of surgical robotic instrument mounting in a macro-micro manipulator setup for improving task execution
, IEEE Transactions on Robotics, Vol: 38, Pages: 2858-2874, ISSN: 1552-3098In Minimally Invasive Robotic Surgery (MIRS),the surgical instrument is usually inserted inside the patient’sbody through a small incision, which acts as a Remote Centerof Motion (RCM). Serial-link manipulators can be used asmacro robots on which micro surgical robotic instruments aremounted to increase the number of degrees of freedom (DOFs)of the system and ensure safe task and RCM motion execution.However, the surgical instrument needs to be placed in anappropriate configuration when completing the motion tasks.The contribution of this work is to present a novel frameworkthat preoperatively identifies the best base configuration, interms or Roll, Pitch, and Yaw angles, of the micro surgicalinstrument with respect to the macro serial-link manipulator’send-effector in order to achieve the maximum accuracy anddexterity in performing specified tasks. The framework relieson Hierarchical Quadratic Programming (HQP) for the control,Genetic Algorithm (GA) for the optimization, and on a resilienceto error strategy to make sure deviations from the optimum donot affect the system’s performance.Simulation results show that the mounting configuration ofthe surgical instrument significantly impacts the performanceof the whole macro-micro manipulator in executing the desiredmotion tasks, and both the simulation and experimental resultsdemonstrate that the proposed optimization method improves theoverall performance.
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Journal articlePinson P, Han L, Kazempour J, 2022,
Regression markets and application to energy forecasting
, TOP, Vol: 30, Pages: 533-573, ISSN: 1134-5764 -
Journal articleXiang Y, Cao Y, Yang W, et al., 2022,
Laser-Induced Recoverable Fluorescence Quenching of Perovskite Films at a Microscopic Grain Scale
, ENERGY & ENVIRONMENTAL MATERIALS, Vol: 5, Pages: 1189-1199- Author Web Link
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- Citations: 1
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Journal articleWen H, Pinson P, Ma J, et al., 2022,
Continuous and Distribution-Free Probabilistic Wind Power Forecasting: A Conditional Normalizing Flow Approach
, IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, Vol: 13, Pages: 2250-2263, ISSN: 1949-3029 -
Journal articleBi J, Zhang J, Giannakou P, et al., 2022,
A Highly integrated flexible photo-rechargeable system based on stable ultrahigh-rate quasi-solid-state zinc-ion micro-batteries and perovskite solar cells
, ENERGY STORAGE MATERIALS, Vol: 51, Pages: 239-248, ISSN: 2405-8297- Author Web Link
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- Citations: 22
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Journal articleCacciarelli D, Kulahci M, Tyssedal JS, 2022,
Stream-based active learning with linear models
, Knowledge-Based Systems, Vol: 254, Pages: 109664-109664, ISSN: 0950-7051 -
Conference paperNguyen QT, Mougenot C, 2022,
We’re still people and not only emails that we’re sending - shared cognition in distributed design collaboration: A qualitative study on distributed creative teams and the relation of communication ecology on virtual collaboration shared understanding
, 2022 4th International Electronics Communication Conference (IECC), Publisher: ACM, Pages: 40-46To identify challenges for future design collaborative systems, we conducted a qualitative study, interviewing expert design practitioners working in creative, multidisciplinary distributed teams The development of shared mental models, previously not examined through the construct of the CSCW ecology, presented four dimensions: task-specific knowledge, task-related knowledge, knowledge of teammates and attitudes/beliefs, where the latter one being the most vulnerable. The study informs the design of future CSCW tools for virtual collaboration tools to fully support remote creative teams.
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Journal articleBurge T, Jones G, Jordan C, et al., 2022,
A computational tool for automatic selection of total knee replacementimplant size using x-ray images
, Frontiers in Bioengineering and Biotechnology, Vol: 10, Pages: 1-11, ISSN: 2296-4185Purpose: The aim of this study was to outline a fully automatic tool capable of reliably predicting the most suitable total kneereplacement implant sizes for patients, using bi-planar X-ray images. By eliminating the need for manual templating or guidingsoftware tools via the adoption of convolutional neural networks, time and resource requirements for pre-operative assessmentand surgery could be reduced, the risk of human error minimized, and patients could see improved outcomes.Methods: The tool utilizes a machine learning-based 2D – 3D pipeline to generate accurate predictions of subjects’ distal femur andproximal tibia bones from X-ray images. It then virtually fits different implant models and sizes to the 3D predictions, calculatesthe implant to bone root-mean-squared error and maximum over/under hang for each, and advises the best option for thepatient. The tool was tested on 78, predominantly White subjects (45 female/33 male), using generic femur component and tibiaplate designs scaled to sizes obtained for five commercially available products. The predictions were then compared to the groundtruth best options, determined using subjects’ MRI data.Results: The tool achieved average femur component size prediction accuracies across the five implant models of 77.95% in termsof global fit (root-mean-squared error), and 71.79% for minimizing over/underhang. These increased to 99.74% and 99.49% with ±1size permitted. For tibia plates, the average prediction accuracies were 80.51% and 72.82% respectively. These increased to99.74% and 98.98% for ±1 size. Better prediction accuracies were obtained for implant models with fewer size options, howeversuch models more frequently resulted in a poor fit.Conclusion: A fully automatic tool was developed and found to enable higher prediction accuracies than generally reported formanual templating techniques, as well as similar computational methods.
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Conference paperChappell D, Yang Z, Son HW, et al., 2022,
Towards instant calibration in myoelectric prosthetic hands: a highly data-efficient controller based on the Wasserstein distance
, International Conference on Rehabilitation Robotics (ICORR), Publisher: IEEEProsthetic hand control research typically focuses on developing increasingly complex controllers to achieve diminishing returns in pattern recognition of muscle activity signals, making models less suitable for user calibration. Some works have investigated transfer learning to alleviate this, but such approaches increase model size dramatically—thus reducing their suitability for implementation on real prostheses. In this work, we propose a novel, non-parametric controller that uses the Wasserstein distance to compare the distribution of incoming signals to those of a set of reference distributions,with the intended action classified as the closest distribution. This controller requires only a single capture of data per reference distribution, making calibration almost instantaneous. Preliminary experiments building a reference library show that, in theory, users are able to produce up to 9 distinguishable muscle activity patterns. However, in practice, variation whenrepeating actions reduces this. Controller accuracy results show that 10 non-disabled and 1 disabled participant were able to use the controller with a maximum of two recalibrations to perform 6 actions at an average accuracy of 89.9% and 86.7% respectively. Practical experiments show that the controller allows users to complete all tasks of the Jebsen-Taylor HandFunction Test, although the task of picking and placing small common objects required on average more time than the protocol’s maximum time.
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Journal articleStratton E, Lampit A, Choi I, et al., 2022,
Trends in Effectiveness of Organizational eHealth Interventions in Addressing Employee Mental Health: Systematic Review and Meta-analysis
, JOURNAL OF MEDICAL INTERNET RESEARCH, Vol: 24, ISSN: 1438-8871- Author Web Link
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- Citations: 3
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Journal articleCalvo R, Peters D, Cook D, et al., 2022,
Assessing the design of Conversational Agents for Asthma support: Protocol for an Observational Pilot Study (Preprint)
<sec> <title>BACKGROUND</title> <p>A significant number of people have poorly controlled asthma – 60% according to some estimates. One likely reason is poor self-assessment of risk by those with asthma, an issue that could be addressed with a conversational agent that assesses and communicates risk accurately. Such a system could further improve outcomes by providing follow-up recommendations to address other common obstacles to asthma control such as poor inhaler technique and insufficient understanding of asthma triggers and management strategies.</p> </sec> <sec> <title>OBJECTIVE</title> <p>The aims of this study are to: 1) Determine the feasibility and usability of a text-based conversational agent (i.e. chatbot) that processes a patient’s text responses and short sample voice recordings to calculate an estimate of their risk for an asthma exacerbation and then offers follow-up information for improving asthma control; 2) Assess the level of engagement of different types of users, particularly those who do not control their asthma well; 3) Assess self-reported level of asthma control and symptoms and 4) explores associations between asthma control and engagement with the conversational agent.</p> </sec> <sec> <title>METHODS</title> <p>For this pilot study we will recruit 90 adults with asthma through NHS outpatient clinics across primary and secondary care. Participants will have access to the conversational agent through WhatsApp on their mobile phone. Participants will be sent scheduled and randomly timed messages to invite them to engage in a dialogue about their asthma management during the period of the study. After a data collection pe
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Journal articleChilds P, Han J, Chen L, et al., 2022,
The creativity diamond - a framework to aid creativity
, Journal of Intelligence, Vol: 10, Pages: 1-20, ISSN: 2079-3200There are many facets to creativity and the topic has a profound impact on society. Substantial and sustained study on creativity has been undertaken and much is now known about the fun-damentals and how creativity can be augmented. To draw these elements together a framework has been developed called the creativity diamond, formulated based on reviews of prior work as well as consideration of 20 PhD studies on the topics of creativity, design, innovation and product development. The framework embodies the principles that quantity of ideas breeds quality through selection, and that a range of creativity tools can provoke additional ideas to augment our innate creativity. The creativity diamond proposed is a tool consisting of a divergent phase as-sociated with the development of many distinctive ideas and a convergent phase associated with the refinement of ideas. The creativity diamond framework can be used to prompt and help select which tool or approach to use in a creative environment for innovative tasks. The framework has now been used by many students and professionals in diverse contexts.
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Conference paperMalone L, Cardin M-A, Cilliers J, et al., 2022,
Development of a Comprehensive Lunar Mining Simulator to Study Design and Decision-Making under Uncertainty
, Paris, France, International Astronautical Congress -
Journal articleSaiger MJ, Deterding S, Gega L, 2022,
Children and Young People’s Involvement in Designing Applied Games: Scoping Review (Preprint)
<sec> <title>BACKGROUND</title> <p>User involvement is widely accepted as key for designing effective applied games for health. This especially holds true for children and young people as target audiences, whose abilities, needs, and preferences can diverge substantially from those of adult designers and players. Nevertheless, there is little shared knowledge about how concretely children and young people have been involved in the design of applied games, let alone consensus guidance on how to do so effectively.</p> </sec> <sec> <title>OBJECTIVE</title> <p>The aim of this scoping review was to describe which user involvement methods have been used in the design of applied games with children and young people, how these methods were implemented, and in what roles children and young people were involved as well as what factors affected their involvement.</p> </sec> <sec> <title>METHODS</title> <p>We conducted a systematic literature search and selection across the ACM Digital Library, IEEE Xplore, Scopus, and Web of Science databases using State of the Art through Systematic Review software for screening, selection, and data extraction. We then conducted a qualitative content analysis on the extracted data using NVivo.</p> </sec> <sec> <title>RESULTS</title> <p>We retrieved 1085 records, of which 47 (4.33%) met the eligibility criteria. The chief involvement methods were participatory design (20/47, 43%) and co-design (16/47, 37%), spanning a wide range of 45 concrete activities with paper prototyping, group discussions, and playtesting b
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Conference paperBaker CE, Montemiglio A, Li R, et al., 2022,
Assessing the influence of parameter variation on kinematic head injury metric uncertainty in multibody reconstructions of real-world pedestrian vehicle and ground impacts
, 2022 IRCOBI Conference, Pages: 393-394, ISSN: 2235-3151 -
Conference paperSeah CEL, Sun S, Zhang Z, et al., 2022,
Using a User Centered Design Approach to Design Mindfulness Conversational Agent for Persons with Dementia and their Caregivers
, Pages: 207-210Caring for people with dementia is itself a difficult task affecting the wellbeing and relationship of the patient and carer. Conversational agents (CA), like Alexa, can support mindfulness training for these dyads of persons with early-stage dementia and their caregivers. But so far, no study has utilised a user centered design (UCD) approach for such interventions. We address this, using an iterative UCD approach where experts in dementia and mindfulness (N=4) and end-users (carers and patients, N=20) were interviewed. Four design iterations resulted in the creation of a working prototype. From this expert and user feedback, general user needs were identified and integrated into future designs. By addressing the needs of dyads, the prototype CA could be well received and may be used to support mindfulness practices using CA, that could be helpful for dyads.
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BookGeronazzo M, Serafin S, 2022,
Sonic interactions in virtual environments
, Publisher: Springer, ISBN: 9783031040207This book tackles the design of 3D spatial interactions in an audio-centered and audio-first perspective, providing the fundamental notions related to the creation and evaluation of immersive sonic experiences. The key elements that enhance the sensation of place in a virtual environment (VE) are:Immersive audio: the computational aspects of the acoustical-space properties of Virutal Reality (VR) technologiesSonic interaction: the human-computer interplay through auditory feedback in VEVR systems: naturally support multimodal integration, impacting different application domainsSonic Interactions in Virtual Environments will feature state-of-the-art research on real-time auralization, sonic interaction design in VR, quality of the experience in multimodal scenarios, and applications. Contributors and editors include interdisciplinary experts from the fields of computer science, engineering, acoustics, psychology, design, humanities, and beyond.Their mission is to shape an emerging new field of study at the intersection of sonic interaction design and immersive media, embracing an archipelago of existing research spread in different audio communities and to increase among the VR communities, researchers, and practitioners, the awareness of the importance of sonic elements when designing immersive environments.
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Journal articleYu X, Halldin P, Ghajari M, 2022,
Oblique impact responses of Hybrid III and a new headform with more biofidelic coefficient of friction and moments of inertia
, Frontiers in Bioengineering and Biotechnology, Vol: 10, Pages: 1-14, ISSN: 2296-4185New oblique impact methods for evaluating head injury mitigation effects of helmets are emerging, which mandate measuring both translational and rotational kinematics of the headform. These methods need headforms with biofidelic mass, moments of inertia (MoIs) and coefficient of friction (CoF). To fulfil this need, the working group 11 of the European standardization head protection committee (CEN/TC158) has been working on the development of a new headform with realistic MoIs and CoF, based on recent biomechanics research on the human head. In this study, we used a version of this headform (Cellbond) to test a motorcycle helmet under oblique impacts at 8m/s at five different locations. We also used the Hybrid III headform, which is commonly used in helmet oblique impacts. We tested whether there is a difference between the predictions of the headforms in terms of injury metrics based on head kinematics, including peak translational and rotational acceleration, peak rotational velocity and BrIC (Brain Injury Criterion). We also used Imperial College finite element model of human head to predict strain and strain rate across the brain and tested whether there is a difference between the headforms in terms of predicted strain and strain rate. We found that the Cellbond headform produced similar or higher peak translational accelerations depending on the impact location (-3.2% in front-side impact to 24.3% in rear impact). The Cellbond headform however produced significantly lower peak rotational acceleration (-41.8% in rear impact to -62.7% in side impact), peak rotational velocity (-29.5% in side impact to -47.6% in rear impact) and BrIC (-29% in rear-side impact to -45.3% in rear impact). The 90th percentile value of the maximum brain strain and strain rate were also significantly lower using this headform. Our results suggest that MoIs and CoF have significant effects on headform rotational kinematics, and consequently brain deformation, during helmeted oblique imp
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Journal articleYan M, Wang P, Pan X, et al., 2022,
Quadrupling the stored charge by extending the accessible density of states
, CHEM, Vol: 8, Pages: 2410-2418, ISSN: 2451-9294- Author Web Link
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- Citations: 1
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Journal articleLiu X, Zhang L, Yu H, et al., 2022,
Bridging multiscale characterization technologies and digital modeling to evaluate lithium battery full lifecycle
, Advanced Energy Materials, Vol: 12, ISSN: 1614-6832The safety, durability and power density of lithium-ion batteries (LIBs) are currently inadequate to satisfy the continuously growing demand of the emerging battery markets. Rapid progress has been made from material engineering to system design, combining experimental results and simulations to enhance LIB performance. Limited by spatial and temporal resolution, state-of-the-art advanced characterization techniques fail to fully reveal the complex multi-scale degradation mechanism in LIBs. Strengthening interaction and iteration between characterization and modeling improves the understanding of reaction mechanisms as well as design and management of LIBs. Herein, a seed cyber hierarchy and interactional network framework is demonstrated to evaluate the overall lifecycle of LIBs. The typical examples of bridging the characterization techniques and modeling are discussed. The critical parameters extracted from multi-scale characterization can serve as digital inputs for modeling. Furthermore, advanced computational techniques including cloud computing, big data, machine learning, and artificial intelligence can also promote the comprehensive understanding and precise control of the whole battery lifecycle. Digital twins techniques will be introduced enabling the real-time monitoring and control of LIBs, autonomous computer-assisted characterizations and intelligent manufacturing. It is anticipated that this work will provide a roadmap for further intensive research on developing high-performance LIBs and intelligent battery management.
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Journal articleBrooks R, Wang H, Ding Z, et al., 2022,
A review on stamp forming of continuous fibre-reinforced thermoplastics
, International Journal of Lightweight Materials and Manufacture, Vol: 5, Pages: 411-430, ISSN: 2588-8404Continuous fibre-reinforced thermoplastics (FRTPs) are replacing metals in certain applications in the aerospace industry due to their superior properties e.g., high strength-to-weight ratio and good fatigue resistance. Adopting these lightweight materials in vehicles is a solution for improving vehicle efficiency across the transport industry. Among various manufacturing techniques for FRTP parts, stamp forming is one of the most advantageous when small structures and mass production are targeted. However, a significant barrier for this technique is the quality control of manufacturing. The current paper reviews the development of stamp forming technology, benefits of using such technology and the typical quality issues in stamp forming of FRTP parts. First, advantages of stamp forming, compared to other thermoforming techniques, are discussed, followed by a review of the historical development of the process. Second, deformation mechanisms of FRTPs during stamp forming are examined, with particular focuses on the frictional behaviour and testing thereof. Third, the main defects associated with stamp forming are considered, alongside suggestions towards reducing their presence. Finally, an extensive survey of the effect of process parameters on the mechanical properties of formed parts is included, with generally expected trends highlighted and methodologies for finding optimum conditions presented. Based on the thorough review of state-of-the-art stamp forming, future trends and research gaps to be tackled for widening the applicability of FRTP stamp forming are suggested.
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Journal articleMazzolai B, Mondini A, Del Dottore E, et al., 2022,
Roadmap on soft robotics: multifunctionality, adaptability and growth without borders
, Multifunctional Materials, Vol: 5Soft robotics aims at creating systems with improved performance of movement and adaptability in unknown, challenging, environments and with higher level of safety during interactions with humans. This Roadmap on Soft Robotics covers selected aspects for the design of soft robots significantly linked to the area of multifunctional materials, as these are considered a fundamental component in the design of soft robots for an improvement of their peculiar abilities, such as morphing, adaptivity and growth. The roadmap includes different approaches for components and systems design, bioinspired materials, methodologies for building soft robots, strategies for the implementation and control of their functionalities and behavior, and examples of soft-bodied systems showing abilities across different environments. For each covered topic, the author(s) describe the current status and research directions, current and future challenges, and perspective advances in science and technology to meet the challenges.
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Journal articleCaunhye AM, Cardin M-A, Rahmat M, 2022,
Flexibility and real options analysis in power system generation expansion planning under uncertainty
, IISE Transactions, Vol: 54, Pages: 832-844, ISSN: 2472-5854Over many years, there has been a drive in the electricity industry towards better integration of environmentally friendly and renewable generation resources for power systems. Such resources show highly variable availability, impacting the design and performance of power systems. In this paper, we propose using a stochastic programming approach to optimize generation expansion planning (GEP), with explicit consideration of generator output capacity uncertainty. Flexibility implementation - via real options exercised in response to uncertainty realizations - is considered as an important design approach to the GEP problem. It more effectively captures upside opportunities, while reducing exposure to downside risks. A decision-rule based approach to real options modeling is used, combining conditional-go and finite adaptability principles. The solutions provide decision makers with easy-to-use guidelines with threshold values from which to exercise the options in operations. To demonstrate application of the proposed methodologies and decision rules, a case study situated in the Midwest United States is used. The case study demonstrates how to quantify the value of flexibility, and showcases the usefulness of the proposed approach.
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Journal articlePolonelli T, Magno M, Niculescu V, et al., 2022,
An open platform for efficient drone-to-sensor wireless ranging and data harvesting
, SUSTAINABLE COMPUTING-INFORMATICS & SYSTEMS, Vol: 35, ISSN: 2210-5379 -
Journal articleBasak S, Dzieciol K, Durmus YE, et al., 2022,
Characterizing battery materials and electrodes via <i>in situ</i>/<i>operando</i> transmission electron microscopy
, CHEMICAL PHYSICS REVIEWS, Vol: 3
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