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We demonstrate that black hole evaporation can be modeled as a process where one symmetry of the system is spontaneously broken continuously. We then identify three free parameters of the system. The sign of one of the free parameters governs whether the particles emitted by the black hole are fermions or bosons. The present model explains why the black hole evaporation process is so universal. Interestingly, this universality emerges naturally inside certain modifications of gravity.
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The cosmological constant is normally introduced as an additional term entering the Einstein–Hilbert (EH) action. In this letter, we demonstrate that, instead, it appears naturally from the standard EH action as an invariant term emerging from spacetime symmetries. We then demonstrate that the same constraint emerging from this invariant suppresses the short wavelength modes and it favors the long wavelength ones. In this way, inside the proposed formulation, the observed value for the vacuum energy density is obtained naturally from the zero-point quantum fluctuations.
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The mutual information method has demonstrated to be very useful for deriving the potential order parameter of a system. Although the method suggests some constraints which help to define this quantity, there is still some freedom in the definition. The method then results inefficient for cases where we have order parameters with a large number of constants in the expansion, which happens when we have many degenerate vacuums. Here, we introduce some additional constraints based on the existence of broken symmetries, which help us to reduce the arbitrariness in the definitions of the order parameter in the proposed mutual information method.
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Industrial organization, theory of the firm and boundaries of the firm are well established fields of study involved in the size, structure and scope of a corporate entity (i.e. firm) to the market. However, a key characteristic of corporate entities is that economic concerns (costs and profit) is the overriding or dominant factor. This paper attempts to apply the above mentioned concepts to organizations such as public institutions where economic concerns are secondary considerations, to seek a more objective analysis on what the structure and scope of such organizations should be
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The Revenue Management (RM) problem in airlines for a fixed capacity, single resource and two classes has been solved before by using a standard formalism. In this paper we propose a model for RM by using the semi-classical approach of the Quantum Harmonic Oscillator. We then extend the model to include external factors affecting the people’s decisions, particularly those where collective decisions emerge.
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The global food industry generates substantial waste, posing significant environmental, economic, and social challenges. This dissertation explores circular business strategies for food waste management, aiming to develop an efficient model that integrates circular economy principles and innovative technologies. Key research questions include: What are current food waste management practices? How can circular economy principles reduce food waste effectively? What role can technology play in improving these systems? The study also examines barriers to implementation and identifies gaps in existing literature. The methodology involves a comprehensive literature review, case studies, and the development of a detailed mathematical model. The literature review covers circular economy concepts, current food waste treatment technologies, machine learning and Al applications in waste management. Case studies from various countries provide insights into regulatory frameworks and innovative solutions. Central to this research is the mathematical modelling of food waste management systems. The model employs Hamiltonian and/or Lagrangian formulations to optimise waste transportation and processing. This approach allows for the simulation of various scenarios, helping to identify the most efficient pathways for food waste reduction and resource recovery. The model also incorporates phase transitions better to understand the dynamics of waste generation and treatment processes. Phase transitions mark changes on tendencies and in this case they help us to evaluate the viability of the construction of a fast track for the transportation of food waste in any city. Results indicate that adopting circular economy principles in food waste management is feasible and beneficial. Effective strategies include bioplastics, insectutilisation, and machine learning models for waste prediction and management. The developed mathematical model suggests efficient waste transportation through a coupled network approach, ensuring rapid and effective waste evacuation. The research highlights the importance of technological integration and cross-sector collaboration for sustainable food waste management. It also stresses the need for robust regulatory frameworks and consumer education to drive behavioural changes and support circular practices
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