The Contribution of MCDM to SUMP: The Case of Spanish Cities during 2006–2021

Sustainable Urban Mobility Plans (SUMP) are increasingly popular planning tools in cities with environmental issues where numerous actions are usually proposed to reduce pollution from urban transport. However, the diagnosis and implementation of these processes requires broad consensus from all stakeholders and the ability to fit them into urban planning in such a way that it allows the proposals to become realistic actions. In this study, a review of the sustainable urban mobility plans of 47 cities in Spain during the last 15 years has been carried out, analyzing both the diagnosis and proposal of solutions and their subsequent implementation. From the results obtained, a new framework based on a structured hybrid methodology is proposed to aid decision-making for the evaluation of alternatives in the implementation of proposals in SUMP. This hybrid methodology considers experts’ and stakeholders’ opinion and applies two different multi-criteria decision making (MCDM) methods in different phases to present two rankings of best alternatives. From that experience, an analysis based on the MCDM methods called ‘Sequential Interactive Modelling for Urban Systems (SIMUS)’ and weighted sum method (WSM) was applied to a case study of the city of Cartagena, a southeastern middle-size city in Spain. This analytic proposal has been transferred to the practical field in the SUMP of Cartagena, the first instrument of this nature developed after COVID-19 in Spain for a relevant city. The results show how this framework, based on a hybrid methodology, allows the development of complex decision mapping processes using these instruments without obviating the need to generate planning tools that can be transferred from the theoretical framework of urban reality.

Digital Image Encryption Using Double Crossover Approach for SARS-CoV-2 Infected Lungs in a Blockchain Framework

As the (Covid-19) pandemic spreads, the creativity of the scientific community is thriving while trying to control the situation. They are trying to treat patients viably and work with the almost exhausted medical equipment and staff, while growing new, successful antibodies. Successful screening of SARS-CoV-2 empowers fast and proficient determination of COVID-19 and can relieve the weight on medical care frameworks. Numerous forecast models are being created to comprehend and prognosticate the spread of the pandemic and to stay away from the following wave. But in the coming time, we can be sure that the models would experience the ill effects of a few issues, security being one of them. All the models need to be built in such a way that the investigation task gets successfully conducted without compromising the privacy and security of the patients. To take care of this, we propose a blockchain framework for sharing patients’ personal data or medical reports. A blockchain will take care of the integrity part, but we still need to worry about confidentiality. Therefore, combining a genetic approach with a blockchain seemed like a good idea. A twofold hybrid methodology is proposed in this paper to tackle the issue of confidentiality. The outcomes displayed high entropy accomplishment for the utilized dataset. The sensitivity of the plaintext and ciphertext is also checked and compared with existing approaches which thus demonstrates the security of the proposed approach in the given setting.

A Hybrid Molecular Dynamics Kinetic Monte Carlo Simulation Methodology

<p>This thesis describes a novel hybrid computational methodology in which the Molecular Dynamics and Kinetic Monte Carlo methods are concurrently combined. This hybrid methodology has been developed to simulate phenomena which are unfeasible to treat with either Molecular Dynamics or Kinetic Monte Carlo alone, due to the wide range of time scales involved and the need for highly detailed atom dynamics. Is is shown that the hybrid methodology can reproduce the results of a larger (more atoms) all Molecular Dynamics simulation at a significant reduction in computational cost (run time) - due to the replacement of Molecular Dynamics atoms with Kinetic Monte Carlo atoms. The hybrid methodology has been successfully used to study the dynamics of epitaxial stacking fault grain boundaries. This work identified that grain boundary motion was hindered by atoms lodging in off-lattice sites, and also by overlayer islands built up by adatom deposition. It was verified that the ‘kink flip” move is a key element in the motion of grain boundaries. Methods for enhancing the hybrid methodology were researched. It was shown that by an optimal choice of damping parameter γ, wave reflections back into the Molecular Dynamics domain could be minimised. This is expected to enable the hybrid methodology to operate successfully with smaller Molecular Dynamics domains, making larger and/or longer simulation runs feasible. This research included the derivation of the dispersion relation for the discrete case with damping and net reflectivity formulas. These are believed to be new results. The hybrid model can be applied to a wide variety of MD and KMC methods. Other MD potentials such as Embedded Atom or Modified Embedded Atom could be employed. The KMC component can be developed to use a more refined lattice or an ”on the fly” KMC method could be employed. Both the MD and KMC components can be extended to handle more than one species of atom. Parallelised versions of the MD and KMC components could also be developed. Any situation where the problem can be decomposed into distinct domains of fine scale and coarse scale modelling respectively, is potentially suitable for treatment with a hybrid model of this design.</p>

A Hybrid Molecular Dynamics Kinetic Monte Carlo Simulation Methodology

<p>This thesis describes a novel hybrid computational methodology in which the Molecular Dynamics and Kinetic Monte Carlo methods are concurrently combined. This hybrid methodology has been developed to simulate phenomena which are unfeasible to treat with either Molecular Dynamics or Kinetic Monte Carlo alone, due to the wide range of time scales involved and the need for highly detailed atom dynamics. Is is shown that the hybrid methodology can reproduce the results of a larger (more atoms) all Molecular Dynamics simulation at a significant reduction in computational cost (run time) - due to the replacement of Molecular Dynamics atoms with Kinetic Monte Carlo atoms. The hybrid methodology has been successfully used to study the dynamics of epitaxial stacking fault grain boundaries. This work identified that grain boundary motion was hindered by atoms lodging in off-lattice sites, and also by overlayer islands built up by adatom deposition. It was verified that the ‘kink flip” move is a key element in the motion of grain boundaries. Methods for enhancing the hybrid methodology were researched. It was shown that by an optimal choice of damping parameter γ, wave reflections back into the Molecular Dynamics domain could be minimised. This is expected to enable the hybrid methodology to operate successfully with smaller Molecular Dynamics domains, making larger and/or longer simulation runs feasible. This research included the derivation of the dispersion relation for the discrete case with damping and net reflectivity formulas. These are believed to be new results. The hybrid model can be applied to a wide variety of MD and KMC methods. Other MD potentials such as Embedded Atom or Modified Embedded Atom could be employed. The KMC component can be developed to use a more refined lattice or an ”on the fly” KMC method could be employed. Both the MD and KMC components can be extended to handle more than one species of atom. Parallelised versions of the MD and KMC components could also be developed. Any situation where the problem can be decomposed into distinct domains of fine scale and coarse scale modelling respectively, is potentially suitable for treatment with a hybrid model of this design.</p>

A Hybrid Methodology for Dental Hospital Quality Performance Gap Using HOQ and Process Analysis

A hybrid methodology is described to identify a quality gap in a dental hospital. The research case study illustrates how to implement quality improvement in a real-life context. A combination of an ethnographic, narrative, and phenomenological approach in data collection and observations within the dental hospital validates the case findings. A unique method based on systems study and Taguchi loss function is shown to reduce the service quality gap in a dental hospital. A house of quality (HOQ) combines the correlation between “patient's expectations” and the hospital's “technical” characteristics. The correlation between service quality and technical characteristics measures a patient's expectations gap. Factor analysis helps to group service and technical factors for better patient management. A strategy map correlation analysis is generated to manage the quality gap. The correlation analysis between patient expectations and the hospital's technical characteristics identify areas of immediate attention.