Tesis
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Colección de Tesis y Trabajos de grado (informe final del proyecto de investigación, tesina, u otro trabajo académico diferente a Tesis, sujeto a la revisión y aceptación de una comisión dictaminadora) presentados por alumnos para obtener un grado académico del Tecnológico de Monterrey.
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- Framework for the development of Alzheimer´s patients care intelligent systems based in Humanitude(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2023-06) Camacho Bustamante, Lili Marlene; Navarro Tuch, Sergio Alberto; emipsanchez; Izquierdo Reyes, Javier; Montesinos Silva, Luis Arturo; School of Engineering and Sciences; Campus Ciudad de MéxicoContemporary trends in fertility rates and life expectancy are propelling significant demographic changes. It is projected that by the year 2030, one in every six individuals will be over the age of 60. A consequential byproduct of this demographic shift is the anticipated global increase in conditions commonly associated with aging, such as Alzheimer’s disease. Under this anticipated scenario, there is a projected shortage of high-quality care services that not only enhance the quality of life but are also accessible to those who require them. Assistive services, bolstered by technology, frequently prioritize patient monitoring and concentrate on providing support to caregivers. These approaches, however, are not holistic in nature and lack the provision to enhance the mental and social well-being of the patients. In the present study, we propose a comprehensive framework designed for the development of assistance systems specifically tailored for individuals in the early stages of Alzheimer’s disease. This framework is underpinned by the Humanitude care methodology, a well-regarded approach to dementia patient care. A sequence of interviews was undertaken with medical professionals, aiming to pinpoint elements of relevance associated with the age spectrum and disease symptoms. Concurrently, specific components from the conversation aspect of the Humanitude methodology were incorporated. Furthermore, we identified, tested, and selected the most suitable technological tools for developing assistance systems focused on social verbal interactions. In conclusion, we acknowledged the emerging areas of opportunity within the field of dementia-related research, thus proposing the foundation for the adaptation of the Pitt corpus and the establishment of a Latin American Spanish corpus.
- Monitoring and diagnosis of the well-being with biosensors and intelligent systems(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2022-01-08) Machado Jaimes, Lizeth Guadalupe; Alfaro Ponce, Mariel; puemcuervo, emipsanchez; Argüelles Cruz, Amadeo José; School of Engineering and Sciences; Campus Ciudad de México; Bustamante Bello, RogelioNowadays, society is more aware about their wellbeing and health, making wearable devices an unexploited and affordable way to continuously monitor them. Smartwatches have gained popularity among wearable devices, enabling access to daily vital physiological measurements, which help people be aware of their health condition. Offering non-invasive, real-time daily monitoring,providing health-related data that may be used to identify a lack of stability in the body, whether it is physical or mental. This project introduces LM Research, a smart monitoring system consisted mainly of a webpage, REST APIs, machine learning algorithms and smartwatches. This system monitors users’ physical and mental indicators to prevent a potential well-being crisis. This will be accomplished by collecting psychological parameters in smartwatches and mental health data using a psychological questionnaire to further develop a supervised machine learning well-being model that will forecast smartwatch users’ well-being. The use of sensors in smartwatches provides an accurate measure of physiological functions of the body; for this reason, a well-established Brand (Garmin) was selected due to its high-quality sensors, which provide more accurate data in contrast with more economical alternatives. This research focuses on determining the most important physical and personal parameters that impact a person’s well-being by feature selection, which will be fed to the machine learning forecasting model. To engage with users and acquire all the data needed to predict their well-being, a website was built and housed in the cloud, allowing the creation of a larger and reachable dataset. In contrast to building the project in a local computing environment, which has more constraints such as data storage and processing, cloud computing makes it scalable, flexible and mobile due to using external servers’ capability.
- Reducción de defectos en una aplicación web corporativa. Un caso de estudio.(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2023-09-10) Diaz Castañeda, Juan Carlos; Padilla Zárate, Gerardo; emimmayorquin; Falcón Morales, Luis Eduardo; Mora Medina, GuillermoEl presente trabajo se enfoca en buscar una solución a una problemática muy común en los equipos de desarrollo de software: los defectos en las aplicaciones. Se centra específicamente en un equipo de desarrollo de software encargado de desarrollar una aplicación web corporativa, pero se desea, que tanto el método aplicado para identificar las causas raíz cómo las soluciones aplicadas para remediarlas puedan ser aprovechadas y replicadas por distintos equipos de desarrollo de software con problemáticas similares. Como parte de la investigación, se realizó primero una recolección y análisis de datos para dimensionar la magnitud del problema y poder exponerla al equipo. Este ejercicio sirvió para que en el equipo se tomara la decisión de priorizar la resolución de defectos sobre nuevas implementaciones, lo cual se vio reflejado muy pronto en una importante disminución en el número de defectos de la aplicación. Posteriormente, se llevó a cabo un análisis para identificar las causas raíz por las que la aplicación tiene muchos defectos. Para este análisis se realizaron diagramas Ishikawa con la colaboración de varios integrantes del equipo con distintos roles. Con las causas principales del problema identificadas, se procedió a diseñar una serie de soluciones para remediarlas: Se optó por mejorar sustancialmente el proceso de desarrollo de software que se seguía en el equipo, agregando varias técnicas de gestión de calidad de software; así como definir estándares de programación para el lenguaje usado en la aplicación. Para probar la eficacia de las soluciones diseñadas, se seleccionó una muestra de 7 desarrolladores miembros del equipo de desarrollo en cuestión, de los cuales se obtuvieron métricas y estadísticas en cuanto a números de defectos asignados. Una vez hecho esto, las soluciones se implementaron únicamente en esa muestra. 8 meses después, se volvieron a obtener métricas y estadísticas tanto de la muestra como de todo el equipo de desarrollo. Finalmente, se analizaron y compararon los resultados obtenidos para llegar a una conclusión. El presente documento describe a detalle los análisis, ejercicios y experimentos realizados con el fin de reducir el número de defectos en la aplicación concerniente, mejorar la calidad del código de la aplicación paulatinamente, mediante la introducción de prácticas que fomentan la mejora continua, y también de dejar establecido un proceso claro que evite que la calidad del software de la aplicación empeore en un futuro y se repita la problemática de la acumulación de defectos.
- Applying competitive technology intelligence to reveal advances in final end user applications, user acceptability, quality assurance, and digital technologies of 3D printing for oral drug delivery systems(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2023-06-12) Ríos Mata, Verónica Lissette; Rodríguez Salvador, Marisela; puemcuervo, emimayorquin; Smith Cornejo, Neale Ricardo; Bourguet Díaz, Rafael Ernesto; School of Engineering and Sciences; Campus MonterreyThe demands for high-value innovative treatments, investment in Research and Development (R&D), and personalized medicines are shaping the pharmaceutical industry, for this, current manufacturing methods may not be able to satisfy these needs. Three-dimensional printing offers different solutions for specific needs that cannot be attended due to the high cost of production, limitations on the process, or individualized demands. 3D printing oral drug delivery systems enhance the delivery of a pharmaceutical substances in the body and the dynamics between pharmaceutical ingredients, while providing personalized formulation, geometry, size, controlled release rate and time on the gastrointestinal tract. On the other hand, for a company to stay relevant in the market, it should be able to develop and integrate a sustainable differentiation, also known as a long-term competitive advantage (Porter, M., 1996). This competitive advantage can be based on the introduction and acquisition of new technologies. The process of identifying market opportunities, trends and new technologies is not always direct, for this, Competitive Technology Intelligence methodology and Scientometric analysis are utilized to reveal technological knowledge and technologies, in order to identify trends that can be turned into actionable information. The aim of this thesis is to use Competitive Technology Intelligence (CTI) methodology to reveal advances in Final End User Applications, User Acceptability, Quality Assurance, and Digital Technologies of 3D Printing for Oral Drug Delivery Systems and facilitate decision-making to stakeholders, upper management, firms or people belonging to the pharmaceutical, medical, healthcare and 3D printing area. Using a query developed from the CTI methodology a total of 621 papers from 01-01-1900 to 05-01-2023, after the database cleaning process the number of results decreased to 512. The 512 publications were categorized into 9 classifications, where the 149 corresponding to the categories Final End User Applications, User Acceptability, Quality Assurance, and Digital Technologies were analyzed. The results demonstrated a tendency towards digitalization of the industry, that looks forward to migrating clinical trials to digital solutions. Machine Learning is being used to optimize and predict parameters of the process and the behavior of the formulations. Applications like DEFEND3D are being examined to avoid the cyber risks of remote digital transfer of electronic prescriptions to the 3D printer. Quality assurance is one of the main concerns while developing 3D printed oral drug delivery systems. Quality by Design (QbD) approach is being used to efficient the design of a product. At the same time, protocols to standardize compounding procedures (mixing, preparation, and printing) as well as decision maps to facilitate decision-making of the pharmacist are being developed. The integration of all these methods can lead to quality assurance in the different types of dosage forms. In the Final End User application trend, abuse-deterrent 3D printed oral dosage forms are being designed to limit the accessibility to non-prescribed opioids, as a solution to the opioid abuse world crisis. For disease treatment, 3D printed capsules that permit the intake of multiple drugs and avoid the negative interactions between active pharmaceutical ingredients are being developed. User preferences and palatability are also being taken into consideration while designing 3D printed dosage forms, as it can facilitate their entry to the market.
- Automatic detection and segmentation of prostate cancer using deep learning techniques(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2023-05-20) Quihui Rubio, Pablo César; González Mendoza, Miguel; puemcuervo, emimayorquin; Alfaro Ponce, Mariel; Mata Miquel, Christian; Hinojosa Cervantes, Salvador Miguel; School of Engineering and Sciences; Campus Monterrey; Ochoa Ruiz, GilbertoProstate cancer is a major cause of death among men worldwide, and detecting it usually involves invasive procedures. Magnetic resonance imaging (MRI) has become a common research area for detecting this cancer because it represents a less invasive option. However, segmenting the prostate gland from MRI images can be a complicated task that requires expert opinions, which is both time-consuming and inconsistent. This thesis proposes a novel deep-learning architecture to automate and obtain accurate and reliable segmentation of the prostate gland in MRI scans. Precise segmentation is crucial for radiotherapy planning, as it determines the tumor’s location and size, which affects treat- ment effectiveness and reduces radiation exposure to surrounding healthy tissues. Therefore, a thorough comparison between architectures from the state-of-the-art is also performed. Convolutional neural networks have shown great potential in medical image segmenta- tion, but the uncertainty associated with their predictions is often overlooked. Therefore, this work proposes a novel approach incorporating uncertainty quantification to ensure reliable and trustworthy results. The models were evaluated on a dataset of prostate T2-MRI scans obtained in collab- oration with the Centre Hospitalarie Dijon and Universitat Politecnica de Catalunya. The results showed that the proposed architecture FAU-Net outperforms most existing models in the literature, with an improvement of 5% in the Dice Similarity Coefficient (DSC) and In- tersection over Union (IoU). However, the best model overall was R2U-Net, which achieved segmentation accuracy and uncertainty estimation values of 85% and 76% for DSC and IoU, respectively, with an uncertainty score lower than 0.05. In addition to the proposed model and comparison between models for prostate seg- mentation and uncertainty quantification, a web application was presented for easier access to the trained models in a clinical setting. This web app would allow medical professionals to upload MRI scans of prostate cancer patients and obtain accurate and reliable segmentation quickly and easily. This would reduce the time and effort required for manual segmentation and improve patient outcomes by facilitating better treatment planning. Overall, this work presents a novel strategy for prostate segmentation using deep learn- ing models and uncertainty quantification. The proposed method provides a reliable and trust- worthy segmentation while quantifying the uncertainty associated with the predictions. This research can benefit prostate cancer patients by improving treatment planning and outcomes.
- Removal of methylene blue from water by adsorption using alginate as activated carbon immobilization agent(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2022-05-24) Torres Bautista, Crhys Lorena Amelia; Álvarez Guerra, Alejandro Juan; tolmquevedo, emimayorquin; Mancilla Méndez, Yasmany; Santibañez Aguilar, José Ezequiel; School of Engineering and Sciences; Campus MonterreyActivated carbon (AC) is an adsorbent widely used in water treatment, however, it has some technical disadvantages, such as its high cost and difficulty to recover. To overcome these drawbacks, AC particles have been encapsulated within a polymeric support, mainly alginate-based. The use of these biological macromolecules results in composites with lower-cost, superior mechanical properties, and higher number of functional groups, advantages that have been attracted the attention of the scientific community. Four adsorbents, activated carbon (AC), alginate (AL), activated carbon/ alginate (AC/AL) and activated carbon, alginate, and bentonite (AC/AL/Bt) were proposed in this work to remove Methylene Blue (MB). The process parameters such as adsorbent diameter, column height, column diameter, mass composition and initial concentration of MB are investigated based on the dynamic simulation results using Aspen Adsorption V11 simulation software. The relationship between the five process parameters and saturation time were studied. Based on the optimized simulation results, AC/AL/Bt obtained the highest saturation time (63020 s) in a Fixed-bed column to treat water contaminated with 25 mg/L methylene blue concentration. Additionally, the suitable process parameters magnitudes are adsorbent particle, column height, column diameter, and mass composition of 1 mm, 2 m, 0.05 m, and 30% AC/ 15% AL/ 55% Bt, respectively. The outcomes of this study suggest the potential of AC/AL/Bt composite for cationic dye removal.
- Synthesis and Characterization of Dye - Sensitized Solar Cells based on (Gd, Yb)-doped ZnO Nanoparticles and Sensitized by Natural Dyes(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2023-06) Vela Plata, Astrid Alicia; López Mena, Edgar René; emimmayorquin; Sánchez Ante, Gildardo; Ceballo Sánchez, Oscar; Navarro López, Diego Eloyr; School of Engineering and Sciences; Campus Ciudad de México; Sánchez Martínez, AraceliUnderstanding that sunlight is Earth's predominant source of energy, the development of sustainable solar power solutions is needed to address the challenges of energy consumption and production, as well as to mitigate the environmental impact of fossil fuel use. Dye-sensitized solar cells (DSSCs) are a promising alternative to conventional siliconbased solar cells due to their low cost, simple production, and environmentally friendly nature. By using natural dyes and non-toxic materials, DSSCs have the potential to reduce the environmental impact of solar cell production and increase the accessibility of renewable energy. In this work, DSSCs were developed using Zinc-oxide (ZnO) doped with lanthanide ions of Gadolinium (Gd) and Ytterbium (Yb) nanoparticles at four different concentrations, Zn1−xGdxO (0, 10 at. %), Zn1−xGd x2Yb x2O (10 at. %), Zn1−xYb xO (10 at. %) as semiconducting layers, sensitized with two different natural dyes extracted from blueberries (Vaccinium corymbosum) that have an anthocyanin based chemical structure and chlorophyl. The solar cells were subjected to I-V analyses under 1 sun illumination to determine the best combination. The results showed that the highest efficiency was obtained with the ZnO: Yb 10 at. % cell, with η= 0.00009%, ISC = 2.31 µA, VOC = 126.50 mV and FF = 29.19% from the chlorophyl dye, representing an increment of 150% from the chlorophyl ZnO: Yb 0 at. % cell with an efficiency of η = 0.00006%. The highest efficiency for the anthocyanin dye was η = 0.00007 % with ISC = 2.46 µA, VOC = 111 mV and FF = 26.97% from the ZnO: Yb 10 at. % cell, representing and increment of 985.91 % from the ZnO: Yb 0 at. % cell with an efficiency of η = 0.0000071% These findings suggest that the doping of ZnO nanoparticles with Yb in 10 at. % can enhance the overall performance of the cell in both dyes, providing a potential solution for more sustainable and efficient solar energy production.
- Generation of optical bottle field arrays using structured light techniques for possible applications in quantum information(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2023) Iga Buitrón, Héctor Miguel; López Mago, Dorilián; emimmayorquin; Pérez García, Benjamín de Jesús; Jaimes Nájera, Alfonso Isaac; School of Engineering and Sciences; Campus MonterreyQuantum computing and quantum simulation are up-and-coming solutions to process information. Quantum information, unlike classical bits 0 or 1, is encoded in a two-level quantum system, what is called qubit. Using trapped neutral atoms as qubits is a rising technique for large-scale quantum computing due to the fact that each atom has discrete quantum states that can be used to encode a qubit. Light is a tool used to control the position and the quantum state of atoms. Although it is possible to trap a neutral atom in its ground state using optical tweezers, its lack of interaction with other atoms limits its use for the construction of many-qubit quantum systems, that require entanglement. Atoms excited to a Rydberg state have been proven successful for many bodies physics due to its strong dipole-dipole interaction. Rydberg atoms are atoms with their electrons excited to high-energy states, and they can strongly interact with each other due to its strong dipole-dipole interaction; however, Rydberg atoms can not be trapped using optical tweezers because they prefer to stay in the darker region of light. Three-dimensional zero-intensity zones, i.e., dark regions surrounded by light, are known as optical bottle fields. These bottle fields can be used to trap and manipulate atoms or small particles by means of repulsive optical forces. This trap can be used to optically contain a Rydberg atom, because it minimizes photon scattering and heating effects. Using structured light techniques it is possible create bottle field arrays taking advantage of the spatial structure of a beam. The aim of this work is create different arrays bottle fields using structured light techniques in order to help improve the performance of the quantum computing and quantum simulation.
- In silico Design and Analysis of Stability Parameters of Asymmetrical Liposomes(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2023-06-15) Núñez García, Eduardo; Montes Fonseca, Silvia Lorena; emimmayorquin; Oseguera Guerra, Berenice Erendira; School of Bioengineering and Sciences; Campus Monterrey; Flores Holguin, NormaAsymmetric liposomes are vesicles that can be assembled from different lipids compositions to improve specific characteristics for each leaflet of the liposome, depending on the intended use. However, the characterization of these nanosystems at an experimental level is complex. The use of MD simulations, and specifically CG models as the Martini force field, allows the design and analysis of these lipidic nanostructures to be faster and cheaper experimentally. Despite the innovation and constant development of MD simulations, this tool has not yet been used as a method to evaluate multiple lipid compositions for asymmetric liposomes, which led to this study, where the design and analysis of multiple asymmetric bilayers and vesicles containing DOTAP, DOPE, DSPC, and cholesterol were created through the INSANE and BUMPy scripts for further evaluation of their structure and stability by measuring their bilayer thicknesses, APL, SASA, gyration radius, and cholesterol positioning. All simulated structures remained stable for 3 microseconds and showed different behaviors depending on their composition, especially cholesterol content that strongly affected the structures' characteristics, meaning that the Martini CG model can be used to determine characteristics of interest in the analysis of multiple liposomal compositions. Based on the analysis made of the bilayers and vesicles during this work, bilayers’ compositions DOTMA:DOPE 1:1, DOTMA:DOPE:Cholesterol 1:1:1, and 5:3:0.4 had the best properties to remain stable over time, and vesicle’s composition DOTMA:DOPE:Cholesterol 1:1:1 presented more satisfactory results overall. Further analysis of the vesicle might be beneficial for a better understanding of the composition. The proposed work serves as a first approach to use MD simulations as a tool to be applied in the decision-making process for developing drug delivery carriers in experimental laboratories, reducing economic and time restrictions.
- Formación automática de ontologías de conceptos encontrados en documentos no estructurados(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2022-07-02) Rivera González, Martha Idalid; González Mendoza, Miguel; emimmayorquin; Cuevas Arenas, Alma; Gibrán Cansino, Héctor; Luévano García, Luis; Escuela de Ingeniería y Ciencias; Campus Estado de México; Guzmán, AdolfoEn las últimas décadas han sido desarrollados numerosos enfoques, métodos y técnicas para el desarrollo en la búsqueda del nuevo conocimiento, las ontologías es una prueba de ello, que permiten estructurar los datos, donde la información es almacenada en nodos y relaciones, agregando con ello, la aplicación de métodos, que permite realizar búsqueda de conocimientos de información no estructurada, tales como páginas web, documentos, artículos, palabras entre otros. El presente trabajo lleva a cabo una búsqueda en una gran cantidad de documentos, iniciando con un tema o concepto “semilla”, usando técnicas de minería de datos (minería de texto) se detectan palabras y frases temáticas que son candidatos a ser conceptos (se usará desambiguación para pasarlos a conceptos aunque generalmente en campos especializados, cada palabra o frase temática tiene un significado único). Las relaciones entre algunos de los conceptos se hallarán mediante la creación de un modelo que permitirá la formación del nuevo conocimiento para obtener las ontologías. La tarea de generar nuevo conocimiento no es nada trivial ya que se requiere de la elaboración de dos algoritmos el primero llamado AS-WT que da como resultado un conjunto de 6 palabras conjuntas, lematizadas y categorizadas y el segundo el AS-WT-ON da como resultado triadas compuestas por sustantivo-verbo-sustantivo para dar como resultado la generación de ontologías
