Doctorado
Permanent URI for this communityhttps://hdl.handle.net/11285/551013
Colección de Tesis presentadas por alumnos para obtener un Doctorado del Tecnológico de Monterrey.
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- Development of a competitive technology intelligence methodology to identify technology dynamics: the case of M-health for diabetes(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-11-13) Castillo Valdez, Pedro Fernando; Rodríguez Salvador, Marisela; emipsanchez; Martínez Ledesma, Emmanuel; Díaz de la Garza, Rocío Isabel; Hernánez Brenes, Carmen; Tejeda Alejandre, Raquel; School of Engineering and Sciences; Rectoría Tec de MonterreyThe unprecedented development of technological advances brings new challenges and opportunities to create competitive advantages. It is necessary the effective use of technology as a facilitator to bring better products and services in all sectors such as industry, business, education, healthcare, and government. An adequate assessment of science and technology is fundamental to impact present and future Research and Development (R&D) and innovation decisions. Diverse disciplines based on metrics analysis have emerged to facilitate science and technology understanding, such as scientometrics, patentometrics, and altmetrics. They offer fundamental theoretical and methodological contributions to quantify scientific research literature, patents, scholarly activities on social networks and websites, aiming to reveal the process of scientific and technology development. However, the current accelerated technological advances require researchers to implement a superior approach to detect continuous changes in the external environment identifying opportunities and vulnerabilities to strengthen the decision-making process regarding R&D and innovation. Organizations can increase their advantages by systematically analyzing the external environment, identify movements of competitors and detect opportunities for growth. In this context, Competitive Technology Intelligence (CTI) offers a strategic approach where information is transformed into opportunities for an actionable result. This research proposes a CTI methodology of eight steps that incorporates experts feedback, a scientometrics and a word distribution analysis into a process to provide a broader scope to science and technology. This thesis provides a more robust analytical approach than traditional scientometric analysis where indicators as relevant authors, institutions, countries, citations, and impactful articles are identified. In this context, this thesis goes further since current hotspots and landscape of main research topics are also determined as well as technological trends, gaps, and opportunity areas to research, evolving the traditional scientometric approach. To demonstrate the methodology proposed, a case study was carried out around diabetes m-Health which is particularly relevant given the worldwide increase in diabetes prevalence. Identifying its technological dynamics can facilitate the adoption of effective technologies that enhance patients' quality of life. As a result of all this process, three scientific publications were developed and published in Q1, and Q2 journals. In the first publication (2021) the proposed CTI methodology is VII presented, while in the second publication (2024) the methodology is applied through a scientometric analysis where current hotspots on diabetes m-Health are determined. Finally, the third publication (2024) provides a landscape of main research topics in diabetes m-Health, and technological trends and opportunity areas to research are identified. These studies aim to contribute researchers, decision makers, and policy makers to prioritize R&D efforts, consolidate areas of interest and explore new research topics.
- Design and operational considerations for optimizing DC-iEK devices for particle manipulation in low voltage implementations(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-11-15) Santos Ramírez, Jesús Martín de los; Pérez González, Víctor Hugo; emimmayorquin; Benavides Lozano, Jorge Alejandro; Lapizco Encinas, Blanca H.; Xuan, Xiangchun; Vázquez Lepe, Elisa Virginia; Escuela de Ingeniería y Ciencias; Campus MonterreyDirect current insulator-based electrokinetic (DC-iEK) devices have been around for two decades and in that time, they have positioned among the most popular microfluidic particle manipulation techniques used in conceptual applications. They have been demonstrated to manipulate (e.g., trap, concentrate, and separate), from synthetic particles like polystyrene-based microspheres to biological samples such as mammal cells, bacteria, exosomes, and proteins. In addition, DC-iEK are considerably cheap and easy to fabricate, adding a plus to their implementation. However, the major challenge that DC-iEK system have presented has been their (almost unpractical) operating voltage conditions, that are not uncommon to be in the orders or thousands or volts, needed to produce the necessary electric field inside the channel required for proper particle manipulation. This work focused on identifying the main design parameters that influence DC-iEK systems capabilities to produce the necessary electric field while reducing their voltage requirements. The results from this project have elucidated how each of the geometric design parameters contribute to DC-iEK systems performance. This allowed for the design and testing of low voltage particle trapping, separation, and characterization in voltages between 80 and 18 V which seems to be close to the limits that DC-iEK are capable of achieving.
- Analysis of optimization models under different approaches to deal with uncertainty regarding pre-disaster planning in food bank supply chains(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-12-11) Rivera Morales, Adrian Fernando; Smith Cornejo, Neale Ricardo; emimmayorquin; Cárdenas Barrón, Leopoldo Eduardo; Bourguet Díaz, Rafael Ernesto; Güemes Castorena, David; Vázquez Lepe,Elisa Virginia; Ciencias de la ingeniería Escuela de Ingeniería y Ciencias; Campus Monterrey; Ruiz, AngelA critical decision in humanitarian logistics pre-disaster planning is the sufficient pre-establishment of relief supplies to provide efficient and quick operations in the aftermath of the event. This thesis identifies some of the challenges faced by food banks from an operations management perspective. To support managers making such decisions, we propose four mathematical formulations that seek to optimize food prepositioning (before the event) and further distribution (after the event) in order to minimize unmet demand (MUD). These formulations will first be analyzed under the assumption of uncertainty in demand, finally comparing results considering uncertainty in supply. The two first formulations adopt the cardinality-constrained (CC) approach to handle uncertainty. These formulations differ in their objective functions, the first formulation’s objective seeks to MUD, whilst the second incorporates equity in the way that demand is satisfied. The two remaining formulations are scenario-based (SB), and as in the previous two formulations, seek to MUD with and without equity considerations, respectively. The formulations are applied to a case study where a food bank faces the arrival of a hurricane in Mexico. For the formulations with uncertainty in demand, we compare the differences between the solutions produced by the proposed formulations and the solutions that would have been produced without uncertainty (perfect information) to have a better understanding of their performance and their behavior. A discussion of the strengths and weaknesses of each model is provided to help managers choose the model that best suits their needs. For the formulations with uncertainty in supply, a series of experiments was done to compare results and further conclusions. Our results demonstrate that the CC approach has an acceptable behavior for every situation, while the SB approach can have exceptional outcomes when the predicted scenarios are good, but worst solutions otherwise, making this approach dependent of the capability of predicting good scenarios.
- Síndromes geriátricos en pacientes con artropatía inflamatoria(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-09-17) Lozano Lozano, Rodrigo; Vega Morales, David; González Guerra, José Luis; Sánchez Ávila, María Teresa; Esquivel Valerio, Jorge Antonio; Garza Elizondo, Mario Alberto; Escuela de Medicina y Ciencias de la Salud; Campus MonterreyLas enfermedades reumatológicas son alteraciones observadas con mucha frecuencia en nuestra población en general, sin embargo, son cada vez más comunes en los adultos mayores. Son a menudo infradiagnosticadas e infratratadas y como nos podemos imaginar, la prevalencia de dichas enfermedades aumenta de forma importante con la edad.El proceso del envejecimiento se asocia a múltiples cambios tanto físicos como mentales y sociales que afectan directamente sobre la capacidad funcional del adulto mayor, ocasionando una pérdida de la autonomía y la aparición de la dependencia. Es posible que las características fisiológicas del envejecimiento estén siendo amplificadas por las propias enfermedades reumatológicas o por los medicamentos utilizados en ellas; ocasionando con ello la aparición de grandes síndromes geriátricos e impactando principalmente tanto en la salud como en la vida diaria del adulto mayor. Debido a esto, es importante tomar medidas para aumentar la conciencia, la prevención, la detección y el tratamiento de todos los síndromes geriátricos.En esta línea de investigación, se desarrollaron diversos proyectos con la finalidad de estudiar los grandes síndromes geriátricos presentados en los pacientes con enfermedades reumatológicas. Primero se realizó una encuesta en formato digital a los geriatras certificados por el Consejo Mexicano de Geriatría para buscar las escalas más adecuadas dentro de la valoración geriátrica integral para realizar a nuestros pacientes. Al obtener un consenso sobre las escalas más utilizadas en nuestro país, se realizó una Clínica de Reumageriatría donde se evaluaron a pacientes tanto por Reumatología como por Geriatría. Derivado de esto, seobtuvieron múltiples protocolos de investigación y 4 proyectos que mencionaremos más adelante.En el primero se estudió la prevalencia de la polifarmacia y la interacción medicamentosa en los adultos mayores de 65 años con enfermedad reumática, en el segundo se buscó la prevalencia de fragilidad en la misma población, en el tercero se evaluó la prevalencia del deterioro cognitivo en los ancianos con artritis reumatoide y en el cuarto se analizó la relación de los puntajes DAS-28 y HAD-DI con el riesgo de caídas en pacientes con artritis reumatoide.Los resultados de estos proyectos son el primer escalón para poder abordar este problema tan complejo que tienen los reumatólogos y que cada vez se hace más frecuente. Y con esto recordar la importancia de la geriatrización no solo en la reumatología si no en todas las especialidades, ya que eso nos podrá permitir llevar a nuestros pacientes a un envejecimiento saludable.
- Hacia visiones pluriversales de las tecnologías digitales: las experiencias de la Red de comunicadoras y comunicadores, Boca de Polen, A.C.(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024) Manjarrez Bastidas, Laura Elizabeth; Ricaurte, Paola; dnbsrp; Baca, Carlos; Escuela de Humanidades y Educación; Campus Ciudad de México; Lugo, NohemíLa presente investigación se propone ofrecer una perspectiva emergente para el análisis de las tecnologías digitales, focalizándose en los conceptos de pluriversalidad y comunalidad y a partir en las vivencias de la Red de Comunicadores Boca de Polen, una entidad civil que ha respaldado a emisoras comunitarias e indígenas en Chiapas, México, durante más de dos décadas. A partir de los preceptos de la investigación colaborativa y mediante un proceso de sistematización, este estudio ahonda en las vivencias tanto de la red como de las radios acompañadas, desvelando una profunda interacción de prácticas sociotécnicas enraizadas en experiencias comunales. Al enfocarse en una experiencia específica de apropiación y resistencia, y al buscar cambiar el lugar de enunciación, se exploran nuevas facetas de preocupaciones y oportunidades habilitadas por las tecnologías digitales. Así, el conocimiento experiencial obtenido de Boca de Polen emerge como una representación palpable de una visión pluriversal de la tecnología, crucial para fomentar reflexiones críticas inclusivas sobre las múltiples implicaciones de las tecnologías digitales.
- Emotional intelligence, local brands, and brand coolness: Unveiling the dynamics of consumer responsibility in sustainable consumption(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-09-09) Agredano González, Carlos; Toldos Romero, María de la Paz; emimmayorquin; Alvarado Herrera, Alejandro; Escuela de Graduados en Administración y Dirección de Empresas; Sede EGADE Estado de México; Rialp-Criado, JosepThe study of consumer behavior is a fascinating yet complex subject in both marketing literature and human psychology. Recently, there has been a heightened interest in sustainable consumption and consumption patterns have affected serious environmental issues, causing us to question whether making these conscious and responsible decisions will impact how we perceive brands and influence future consumer purchases. To respond to this question and based on the signaling theory (Erdem and Swait, 1989) and the theory of planned behavior (Ajzen, 1991), three scientific studies were elaborated to empirically prove the relationships between variables with a methodical basis that can conduct responsible behavior while making stronger brands. The manuscript presents three studies that aim to identify the antecedent variables that explain consumer decision-making in the relationship between consumer responsibility for sustainable consumption and local or global brands, specifically, the objective is to understand the factors that influence this behavior. Firstly, the role of emotional intelligence and flourishing in predicting consumer responsibility for sustainable consumption was examined, and the relationship between these variables and the mediating effect of personal norms, and frugality. Secondly, the study examines how consumer responsibility for sustainable consumption can affect the likelihood of purchasing local brands, the mediation role of local brand attitude and local brand as a social signaling value, and how these relationships are moderated through materialism and ethnocentrism. Lastly, it was presented the impact of the perceived local or global brand on how cool those brands are. In the findings for studies one and two, PLS structural equation modeling was applied to a representative sample of 430 respondents from an online survey in Mexico. This study demonstrated that emotional intelligence has a positive impact on individuals' flourishing, and personal norms and frugal behaviors play a mediating role that positively influences consumer responsibility for sustainable consumption. The second study explored the consumer responsibility for sustainable consumption and its positive direct and indirect effect on local brand purchase likelihood through the mediation of local brand attitude, and local brand as a social signaling value and the moderation role of materialism and ethnocentrism in those direct and indirect effects. In the last study it was applied PLS structural equation modeling and a multigroup analysis, to evaluate the impact of perceived local and global brands on brand coolness and how this perception is affected by their attitude toward a global or local consumer culture in retailers’ brands. A multinational survey was used to collect information from the United States, Australia, and Mexico. Businesses, brand managers, and policymakers should prioritize these factors in marketing strategies to enhance local brand visibility and influence consumer behavior positively and responsibly. The initial investigation offered insights into the antecedent factors driving responsible and sustainable consumption. The findings in second study, enhance the understanding of how to develop effective local brand marketing strategies from the perspective of construal level theory, and this is particularly relevant when targeting consumers who have a strong sense of personal responsibility and prioritize sustainability, providing managerial implications on how to promote consuming locally, thereby promoting responsible consumption. These results suggest that adopting a glocal strategy can benefit retailers seeking international growth and enhance their overall coolness factor.
- Methodology to improve compact extended range ev-powertrain module(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2023-06-07) Puma Benavides, David Sebastian; Calderón Nájera, Juan de Dios; puemcuervo, emipsanchez; Galluzzi Aguilera, Renato; Bustamante Bello, Martin Rogelio; Loyola Morales, Félix; School of Engineering and Sciences; Campus Monterrey; Izquierdo Reyes, JavierThe constant growth of the vehicle fleet means that more and more emissions are being emitted into the environment, with the transportation sector contributing around 21% of CO2 in data updated to 2023. Reducing emissions and carbon footprint, leaving aside the dependence on fossil fuels, has been the premise for developing vehicles with new technologies and developing clean energy for their use. As a result, the sale of internal combustion vehicles reached its highest peak in 2017, and from there, the sale of electric and hybrid vehicles has grown yearly. However, combustion, electric and hybrid vehicles have yet to achieve optimal efficiency; therefore, generating optimizations in their powertrain is viable as research topics, as well as for the extension of the range in electric vehicles, which at the moment is a factor that makes their purchase unattractive. Therefore, this thesis aims to review and evaluate technologies that can function as range extenders for electric vehicles, considering their efficiency, low pollution levels, and compatibility for integration into electric vehicle platforms. To facilitate this evaluation, an algorithm incorporating equations representing characteristic curves of mechanical or electrical components will be developed for Extended Range Electric Vehicle EREV. This algorithm will provide valuable insights into the behavior and energy analysis of potential range extender (ICE-Alternator/Generator). Furthermore, the optimization of the entire powertrain system will be considered to ensure all components operate at peak efficiency. These objectives constitute the core of this dissertation. Through powertrain improvement, specifically by adjusting the differential gear ratio from 4.3 to 3.54, significant improvements in vehicle performance can be achieved. Energy savings during standardized driving cycles such as NEDC, WLTC-2, and WLTC-3 can reach up to 10%. Additionally, integrating an auxiliary power unit (APU) into the vehicle architecture can substantially enhance the vehicle's range. By employing an ICE-Alternator configuration with a maximum power of 12.8 kW, the vehicle's travel distance can be extended by up to 170%. Alternatively, an ICE-Generator configuration with a maximum power of 3.2 kW can increase travel distance by up to 39%. Implementing an effective control strategy that optimizes fuel consumption based on the battery's state of charge further enhances APU utilization, resulting in efficiency gains of up to 3.5%. The proposed methodology for developing extended-range electric vehicles, along with the validated algorithm through practical implementations and testing, enables comprehensive energy analyses. This approach provides a more accurate understanding of the performance of vehicle platforms incorporating range extenders.
- DC-DC high-order converters for renewable applications(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-05-07) Garza Arias, Enrique; Valdez Resendiz, Jesús Elias; Rosas Caro, Julio César; Escobar Valderrama, Gerardo; Castañeda Cuevas, Herman; Escuela de Ingeniería y Ciencias; Campus Monterrey; Guillén Aparicio, DanielThis dissertation develops new theory and techniques for DC-DC power converters interfacing renewable energies, specifically for converters classified as high-order based on their mathematical model, and thus generally more complex and difficult to analyze. The thesis encompasses the development of a new circuit topology, a control design focused on high-order dynamic systems, and the study of conversion systems between renewables and the utility grid. The dynamics of high-order converters present challenges for the stability and synthesis of controllers. By studying the nonlinear model of fourth-order non-minimum phase converters through zero dynamics, it has been established that some of these can attain stability under direct voltage at high regulation, in contrast to second-order converters. Controllers have been designed to take advantage of these results in order to remove the current sensing stage while still achieving high bandwidth voltage regulation. Research has also been conducted into creating novel DC converters with a lower component size than similar circuits. From this, an improved super-boost converter has been developed that requires lower energy storage on its capacitors and inductors than the traditional boost and fourth-order boost converters, for a given specification of input current and output voltage ripples. Additionally, an inverter system for a fuel cell stack has been developed using double-dual converters in cascade to increase the voltage gain and power handling of the system. Results from tests at different power and voltage levels show that the proposed system also achieves reduced switch voltage stresses and reduced output current ripples. Simulation and experimental results were obtained in order to validate the theoretical analysis. Mathematical models, steady state values and stability conditions were calculated, and prototype designs were developed to corroborate the performance of the converters, control and efficiency.
- Commercial delivery policies: inventory management models with power demand pattern(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-06-29) Khan, Md. Al-Amin; Cárdenas Barrón, Leopoldo Eduardo; emiggomez, emipsanchez; Loera Hernández, Imelda de Jesús; Smith, Neale R.; Treviño Garza, Gerardo; Bourguet Díaz, Rafael Ernesto; School of Engineering and Sciences; Campus MonterreyIn the fast-paced, ever-changing environment of contemporary business, inventory management stands as a vital, ongoing endeavor. The discipline of decision-making in inventory management assumes a central role in this dynamic environment that is marked by continuous change and intense competition. Navigating the complexities of decision-making poses challenges, particularly in accurately assessing the multifaceted aspects of decision-making processes amid varying circumstances, including demand fluctuations, different types of discounts, and contractual agreements. At the same time, the increasing concern among consumers regarding the environmental footprint of their purchases, coupled with government-mandated regulations, complicates the decision-making process for businesses. In this milieu, sustainable inventory management practices have emerged as a pertinent research area, prompting heightened scrutiny of the impacts of emission guidelines on inventory practices, not only aimed at addressing broader societal concerns but also at ensuring the financial sustainability of businesses. This thesis adopts a specialized demand structure known as the power demand pattern (PDP) to depict fluctuations in demand over the storage period of a company, providing a robust framework for understanding customer demand dynamics across various products. The company maintains its inventory by acquiring items through quantity discounts in exchange for a quantity-sensitive prepayment as part of a contractual arrangement. This thesis introduces a novel concept by considering the installment frequency for fulfilling prepayment obligations as a decision variable for the company, incorporating a transaction fee for each installment. Furthermore, theoretical formulas are developed under different sorts of demand structures, incorporating the influences of selling price and storage time, to assess the profitability of inventory management processes under a combined link-to-order prepayment and quantity discount scheme. A significant advancement by integrating sustainability considerations into both inventory management and pricing strategies within the framework of the PDP is accomplished in this thesis. Through systematic identification and comparison of sustainable inventory management practices under varying emission guidelines, this study provides valuable insights aimed at optimizing profits within the PDP. Therefore, the insights derived from this study offer organizations practical techniques to navigate the complex regulatory environment effectively and achieve sustainable financial performance. Moreover, intensive and comprehensive in-depth sustainable inventory practices under the PDP are established specifically for growing items (GIs). This thesis investigates the impact of weight loss resulting from bleeding and non-consumable components on optimal pricing and inventory strategies for a farm, delving into previously unexplored areas within the literature on GIs. A comparative analysis is conducted on the operations of a livestock farm, operating within several environmental regulations. Consequently, the comprehensive methodology improves sustainable inventory management techniques and offers practical strategies to mitigate environmental impacts and enhance economic feasibility in livestock production.
- Extracting the embedded knowledge in class visualizations from artificial neural networks for applications in dataset and model compression and combinatorial optimization(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-04-25) Abreu Pederzini, Jose Ricardo; Terashima Marín, Hugo; emiggomez, emipsanchez; González Mendoza, Miguel; Juárez Jiménez, Julio Antonio; Rosales Pérez, Alejandro; Bendre, Nihar; School of Engineering and Sciences; Campus Monterrey; Ortiz Bayliss, José CarlosArtificial neural networks are efficient learning algorithms, considered universal approxima-tors for solving numerous real-world problems in areas like computer vision, language processing, or reinforcement learning. To approximate any given function, neural networks train a large number of parameters that can go up to the millions or even billions in some cases. The large number of parameters and hidden layers in neural networks makes them hard to interpret, which is why they are often referred to as black boxes. In the quest to make artificial neural networks interpretable in the field of computer vision, feature visualization stands outas one of the most developed and promising research directions. While feature visualizations are a useful tool to gain insights about the underlying function learned by a neural network, they are still considered simply as visual aids that require human interpretation. In this doctoral work, we propose that feature visualizations—class visualizations in particular—are analogous to mental imagery in humans and contain the knowledge that the model extracted from the training data. Therefore, when correctly generated, class visualiza-tions can be considered as a conceptual compression of the data used to train the underlying model, resembling the experience of perceiving the actual training samples just as mental imagery resembles the real experience of perceiving the actual physical event. We present results showing that class visualizations can be considered a conceptual compression of the training data used to train the underlying model and present a methodology that enables the use of class visualizations as training data. To achieve this goal, we show that class visualizations can be used as training data to develop new models from scratch, achieving, in some cases, the same accuracy as the underlying model. Additionally, we explore the nature of class visualizations through different experiments to gain insights on what exactly class visualizations represent and what knowledge is embedded in them. To do so, we com- pare class visualizations to the class average image from the training data and demonstrate how the other classes that a model is trained on affect the shape and the knowledge embedded in a class visualization. We show that class visualizations are equivalent to visualizing the weight matrices of the output neurons in shallow network architectures and demonstrate that class visualizations can be used as pretrained convolutional filters. We experimentally show the potential of class visualizations for extreme model compression purposes. Finally, we present a novel methodology to enable the use of Artificial Neural Networks along with class visualizations for the solution of combinatorial optimization problems, such as the 2D Bin Packing Problem, by training an Artificial Neural Network to score potential solutions to a 2D BPP and then using that network to generate an ’optimal’ (local optima) solution to the problem by extracting a class visualization from the network via backpropagation to the network’s input. Even though we show the use of class visualizations as a tool to solve the bin packing problem, it is important to note that class visualizations have the potential to be used in the same way to solve other types of combinatorial optimization problems. For other types of combinatorial optimization problems, we just need to design a neural network that is capable of scoring solutions to the particular combinatorial optimization problem and extract class visualizations from such a network to generate a candidate solution to the problem.
