Ciencias Exactas y Ciencias de la Salud

Permanent URI for this collectionhttps://hdl.handle.net/11285/551039

Pertenecen a esta colección Tesis y Trabajos de grado de las Maestrías correspondientes a las Escuelas de Ingeniería y Ciencias así como a Medicina y Ciencias de la Salud.

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20 Años Así-Edición Única
(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2009-06-01) Rodríguez Maldonado, Laura Elena; Flores Garza, Jorge Lorenzo; Hernández Sotillo, Omar Danilo; Cervantes Sandoval, Cristina María; Cervantes Sandoval, Cristina María; Tecnológico de Monterrey, Campus Monterrey; Pedroza Villarreal, Gabriela de Lourdes
En la actualidad la sociedad mexicana ha evolucionado a tal grado que en la mayoría de los casos el núcleo familiar ha cambiado, rompiendo así con los estereotipos culturales en los que nos desenvolvemos. Este cambio ha surgido gracias a la necesidad familiar de que la mujer colabore con el mantenimiento de la casa, es decir, deje de ser solamente ama de casa y lo combine con un trabajo. En algunos casos, los roles no solo se han unido sino que han sido invertidos. Este documental muestra el caso específico de una familia donde los roles han sido intercambiados por completo, es decir que la mujer es la que sale a trabajar mientras que el hombre cubre la función de ama de casa. Las reacciones de familiares y de la sociedad son de vital importancia para el desarrollo de esta relación por lo que son incluidas así como la opinión de un experto que nos da su punto de vista respecto a la situación en la que viven, los aspectos de la pareja y los hijos.
3-D Detection & tracking for semi-deformable objects
(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024) De Los Rios Alatorre, Gustavo; Muñoz Ubando, Luis Alberto; emimmayorquin; Hernández Gress, Neil; Ceballos Cancino, Héctor Gibrán; Raygosa Barahona, Rubén Renan; Maestro en Ciencias de la Computación; Campus Monterrey
This thesis introduces a computer vision system designed for real-time detection and pose estimation of semi-deformable objects in 3-D space, leveraging edge computing devices. The primary motivation for this research stems from the need to enhance the capabilities of vision-based systems, which in turn can aid in improving the efficiency and effectiveness of robotics systems in a variety of fields. For the context of the thesis the chosen field was agriculture, focusing on the recognition, tracking and pose estimation of bell peppers by harvesting robots, an application where traditional methods often fall short due to the nature of semi-deformable objects like fruits. A Jetson Nano was used as the main component, while an Intel DE10-Nano was considered as a complementary part of the system for performing image preprocessing tasks with the Azure Kinect being considered as the main camera sensor. The algorithm was successfully deployed in the Jetson Nano, successfully tracking and estimating the pose of a bell pepper in 3-D by performing the necessary rotations and deformations to a canonical model used by the system as a general means to estimate the pose of the pepper in the real world scene. The algorithm was also tested in a ROS 2 Gazebo simulation where an x-arm robot was used to simulate the vision part of a pick and place operation with a simulated bell pepper, using the proposed method to accurately identify and estimate the pose of the pepper in the simulation. Lastly, a set of different segmentation techniques using both deep learning and traditional methods are presented as a means to explore how these could better the current segmentation capacity of the system.
3D printed emitters for nanofibers production using VAT photopolymerization
(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2023-06-16) Almanza Vázquez, Luis Enrique; García López, Erika; dnbsrp; Rodríguez Gónzalez, Ciro Ángel; School of Engineering and Science; Campus Monterrey; Tejeda Alejandre, Raquel
Electrospinning is a method centered on electrostatic forces for fabricating continuous nanofibers with a substantial active surface area per mass unit in which the morphology of electro spun nanofiber is influenced by some parameters such as voltage, space electric field distribution, surface charge density, liquid supply rate, solution surface tension, viscosity, conductivity, and humidity. This technique is being applied by designing a Multiplexed Source using VAT photopolymerization which will allow to produce the nanofibers. Several test probes varying geometrically (Hexagonal, Pentagonal, Quadrangular, Triangular and Circular) were designed to analyze the resolution of the EnvisionTEC and to observe if the multiplexed source geometry nozzles should be changed or remain the same. After an Error Data Analysis, it was concluded that the circular geometry was the one to work with because it does not get clogged by the time the experiments were computed thus because it does not have any angle or angles that affects its manufacturing in comparison with the other geometries. In this study the polymer used to produce the nanofibers was polyethylene oxide (PEO) with a molecular wight of 900,000 gr/mol. The electrospinning experiments were conducted at flow rates ranging from 0.1 and 1 ml / hr and working distances between 12.5 and 16.5 cm. The voltage remains constant at the value of 20kV. The collected fibers were analyzed using Scanning Electron Microscopy (SEM). Based on the solution and processing conditions, different structures from droplets, and heavily beaded fibers to defect-free mats were obtained. PEO’s concentration was 4% w/v and the volume of Deionized water was 96 ml. The solution was diluted and prepared by using a water bath for 8 hours until the PEO is completely diluted. Based on the solution and processing conditions, different structures from droplets, and heavily beaded fibers to defect-free mats were obtained and measured their diameter (if applicable) by using the image j software and by computing a Data analysis of the average diameter per sample of nanofibers check out which one is the optimal combination of parameters by producing the nanofibers. The final application of this is the manufacture of a multilayer patch for a biomedical application that is the tissue regeneration for second degree burning wounds.
3D printed nutritious food: printability, rheology, and novel approaches towards modification of their structural properties
(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2021-12-02) Maldonado Rosas, Rubén; Tejada Ortigoza, Viridiana Alejandra; puemcuervo/tolmquevedo; Morales de la Peña, Mariana; Campanella, Osvaldo H.; School of Engineering and Sciences; Campus Monterrey; Cuan Urquizo, Enrique
A study in extrusion-based 3D printing of nutritious food is presented in this dissertation. This study covers the design of a novel food-ink formulation, printability and rheology. Also, the mechanical analysis of post-processed printed products. Chapter 1 includes the motivation, problem statement and context of this study. It also includes the theoretical framework regarding 3D customized food and 3D food printing techniques’ basic principles. Chapter 2 includes the engineering parameters for extrusion of 3D printed food materials. Then Chapter 3 contains the Hypothesis, Objectives and Reserch Plan followed during this project. Manuscript 1 (Chapter 4) is entitled "3D printed nutritious food: printability, rheology, and novel approaches towards modification of their structural properties." Herein correlations among the printability of formulations and their rheological properties were established. This manuscript is planned to be published in the journal Additive Manufacturing. Chapter 5 presents the mechanical properties of the post-processed materials. The abstract and acceptance letter for an oral presentation accepted in the conference Congreso Iberoamericano de Ingeniería en Alimentos (CIBIA XIII) is presented in Chapter 6. Finally, it is included a disclosure regarding scientific material and an appendix section containing complementary information collected during data organization and analysis. This dissertation showed rheological properties describing promising applications for novel ingredients. Pregelatinized starch results on printing quality can be used to provide guidance for future Three-Dimensional Food Printing (3DFP) studies, especially for those where a hydrocolloid is used as an additive to improve printing behavior of the food-ink formulations.
3G (migrando a LTE) vs WiMAX, complementos o rivales: aplicación de un estudio de caso en México
(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2010-05-01) Jiménez Pérez, Ricardo; Ibarra Yúnez, Alejandro; Torres Arcadia, Carmen Celina; Rodríguez Dagnino, Ramón Martín; Maranto Vargas, Daniel; Programa de Graduados en Mecatrónica y Tecnologías de la Información; División de Mecatrónica y Tecnologías de Información; Campus Monterrey
La industria de las telecomunicaciones, en los últimos años, ha evolucionado significativamente tanto para las operadoras relacionadas con la oferta de servicios como para los usuarios. En este sentido, la telefonía móvil está siendo considerada como referencia obligada para observar cuál es la madurez de ciertas operadoras con respecto a los factores económicos, regulatorios, organizacionales, de servicios y tecnológicos. Los usuarios actuales de telefonía móvil están observando las posibilidades que les proporcionan los diferentes competidores, así como los costos que representaría en adquirir una tecnología en específico. Las tecnologías móviles están evolucionando para aprovechar la disponibilidad del espectro en la mayoría de los países del mundo y así establecer alternativas en el ofrecimiento de mayor ancho de banda para un mercado que está en constante crecimiento o para un nicho en particular. Los usuarios actuales de telefonía móvil están observando las posibilidades que les proporcionan los diferentes competidores, así como los costos que representaría en adquirir una tecnología en específico. Las tecnologías móviles están evolucionando para aprovechar la disponibilidad del espectro en la mayoría de los países del mundo y así establecer alternativas en el ofrecimiento de mayor ancho de banda para un mercado que está en constante crecimiento o para un nicho en particular. La importancia se centra en analizar un estudio de caso en México, que ha contemplado el despliegue de WiMAX en ciertas ciudades y el cual, con base en opiniones de expertos, ofrecerá una mayor visión del estado de esa tecnología no sólo en el país sino en el mundo. El modelo propuesto para analizar los despliegues generalizados de 3G y WiMAX es una adaptación y propuesta propia basada en el modelo de Bouwman, Haaker & De Vos (2008).
4d printing research trends and applications in the medical field: a scientometric analysis
(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2022-07-28) Padilla Aguirre, Karen Marcela; RODRIGUEZ SALVADOR, MARISELA; 20562; Rodríguez Salvador, Marisela; emijzarate, emipsanchez; Urbina Coronado, Pedro Daniel; Elizondo Noriega, Armando; Escuela de Ingeniería y Ciencias; Campus Monterrey
Innovation plays a key role on a company’s either success or failure. But innovation is not just the creating or adopting new technologies; it is also directly connected with a solid strategic planning. Competitive technology intelligence is based on the systematic and ethical process of gathering, analyzing and transforming information into actionable knowledge. It aims to support decision making and strategic planning, because the knowledge produced by this methodology constitutes an early warning for research, development and innovation [19]. Three-dimensional (3D) printing is a technique of additive manufacturing that has revolutionized engineering, product design and manufacturing, as it allows the rapid conversion of digital 3D model information into physical static objects [45]. However, in the last few years a new possibility has been introduced to add ’time’ as a new dimension to create 4D printing. The medical field keeps changing and progressing at a high speed with new technologies emerging every day. 4D printing on the medical field is an area where it is necessary to provide decision makers with an overview of technological knowledge that helps them generate innovation opportunities. On this thesis, a Competitive technology intelligence approach was executed to identify trends in 4D printing technologies applied to the medical field, in order to provide relevant information through a technological landscape to support decision makers to uncover innovation opportunities. The results of the analysis revealed that most of the research developed is on the materials category, which relates completely to the fact that smart materials are the key difference between 3D and 4D printing. Most of the researches focus on shape memory polymers, hydrogels and liquid crystal elastomers. On the processes category researched is focused on the physical configuration of the printing model, printing parameters and adapting machines to modify the printing configurations. As for the applications, three main subcategories were identified, hollow tubes/stents, tissue engineering and drug delivery. According to the growth kinetics it is a field that although is fairly new, keeps growing and will keep gaining attention.
A C-MEMS based electroosmotic microreactor for anisotropic AuNPs synthesis: Proof of concept
(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2020-05-28) Ortiz Castillo, José Eric; ORTIZ CASTILLO, JOSE ERIC; 885252; Pérez González, Víctor Hugo; ilquio; Martinez Chapa, Sergio Omar; Gallo Villanueva, Roberto Carlos; School of Engineering and Sciences; Campus Monterrey
Anisotropic gold nanoparticle synthesis has aroused great attention in the scientific community in the last two decades. These nanomaterials have unique properties that make them suitable for a wide range of applications in the biomedical field such as optical sensing, biomedicine, chemical catalysis, etc. Therefore, there have been several efforts in the seek of novel and green synthetic methodologies for gold nanoparticles. The control of the concentration of reactants and the kinetics of the reaction are two crucial parameters for the developing of a good synthetic procedure. Microfluidics offers different approaches to deal with the materials synthesis at a microscale with a higher synthetic control at a molecular level. A proof of concept for the synthesis of anisotropic gold nanoparticles was carried on a C-MEMS based electroosmotic microreactor. This microfluidic design was used previously specifically as a bidirectional electroosmotic flow micropump. The velocity profile produced by this microfluidic device was employed to mix the reaction components for the chemical synthesis of anisotropic gold nanoparticles. The reactor was studied with an experimental design and computational modelling. Finally, the anisotropic gold nanoparticles were characterized by UV-Vis and TEM microscopy.
A CMOS cantilever platform using adsorption-induced surface stress and piezoresistive transduction for biosensing
(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2012-12-01) Rendón Hernández, Adrián Abdalá; Rendón Hernández, Adrían Abdalá; 315444; Martínez Chapa, Sergio Omar; Dieck Assad, Graciano; Camacho León, Sergio; School of Engineering and Information Technologies Graduate Program; Campus Monterrey
This work proposes a biosensing platform based on a microcantilever operating in static mode. The microcantilever transforms the adsorption-induced surface stress into a deflection which is then transformed in an electrical signal by means of a piezoresistive element that is embedded in the structure. A non-destructive and independent-of-fabrication-processes method to characterize residual stress within composite micromachined beams has been proposed. The method was validated by comparing available experimental data and simulation results from fourteen microbeams obtaining an average of 27% absolute error concerning the maximum deflection of the structures. A multipysics model incorporating a suspended beam, a piezoresistor and a Wheatstone bridge has been created in Comsol and used to explore performance of different piezoresistor geometries. A serpentine piezoresistor compared favorably among different geometries and showed a sensibility of 116Ω/µm. Finally, several Bandgap references were designed to be used in conjunction with the Wheatstone bridge in order to get low sensibilities to temperature and voltage supply variations. The best reference showed sensibilities of 18 ppm/ ◦C and 3.2mV/V. This platform was entirely designed to be fabricated in a CMOS process, and is expected to be used in the future to detect and quantify different analytes for environmental monitoring, food industry and biomedicine.
A Comparative analysis of a three-phase DAB and an improved LLC bidirectional DC/DC converter for wide input and output voltage range applications
(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2025-11-04) Escobar Pescina, Luis Arturo; Escobar Valderrama, Gerardo; mtyahinojosa, emipsanchez; Galluzzi Aguilera, Renato; Pool Mazun, Erick I.; Aqui Tapia, Juan; Escuela de Ingeniería y Ciencias; Campus Monterrey; Valdez Reséndiz, Jesús Elias
Bidirectional DC/DC power conversion is a key element in vehicle electrification to provide auxiliary power, typically for battery charging and discharging. There are currently various challenges in single stage isolated bidirectional DC/DC conversion that limit efficiency, especially for wide input and output voltage range conditions. The Dual Active Bridge (DAB) is a popular topology for this purpose; however, it presents a hard-switched operation under wide voltage and partial load conditions, due to its limited soft-switching region using typical Single-Phase Shift (SPS) modulation. Resonant converters, on the other hand, possess attractive features such as wide ZVS region, high frequency operation with low switching power losses, high efficiency at a wide voltage range and high power density that can potentially solve the current limitations. The LLC resonant tank is one of the most commonly used configurations, even though it does not have a symmetric voltage gain curve in forward and backward energy flow modes, it can reduce the component count and increase power density compared to a more complex tank network such as the CLLC. However, the conventional LLC topology has limited backward voltage gain that leads to a condition referred to in this thesis as the inequality problem, and for wide input voltage range it is necessary to add a mechanism that is capable of dynamically changing the converter gain to further step up the input voltage and meet the system requirements. Hence, this thesis presents the following: 1. An improved LLC resonant converter with a center-tapped transformer that can dynamically change the transformer turns-ratio in a tap-changer fashion and considerably increase the input and output voltage range. 2. A comparative analysis between the popular Three-Phase DAB converter and the proposed Center-Tapped LLC (CT-LLC) for a 15-kW application through their simulation models in OrCAD using non-ideal PSpice components. 3. Relevant conclusions derived from the comparative study that highlight the benefits and drawbacks of each topology according to efficiency, performance, reliability, and cost metrics.
A comparison between fuzzy logic, and PID controllers to guidance their application in a DC-DC boost converter system with PV source
(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2023-12-01) Aguirre Damián, Bernabé; Ponce Cruz, Pedro; emiggomez, emipsanchez; Molina Gutiérrez, Arturo; School of Engineering and Sciences; Campus Ciudad de México; Sánchez García, José Manuel
There is a need to integrate alternative sources of energy due to the expected lack of conventional sources, in addition to this energy consumption is expected to grow. Solar photovoltaic (PV) energy has emerged as a highly abundant source, and its use has increased in recent years, but it is important to consider that, as this source produces direct DC power, the voltage regulation is a crucial part in PV systems. To achieve this task PID control is a widely used control technique, however intelligent control strategies have been developed in recent years, among these strategies, Fuzzy Logic Control (FLC) use has been increasing, as it aims to be a simpler control technique. PID and FLC have both been used to control the voltage in PV systems, each of these techniques being capable of regulating the output voltage in DC-DC converters, but both controllers behave differently, and each have their own tuning mechanism, so, in order to prove the performance of both control methodologies, a comparison to differentiate the main features that these controllers can bring in PV systems is required. In this work it is developed a DC-DC boost converter model in MATLAB/SIMULINK, and with the application of optimization algorithms, such as particleswarm, patternsearch, simulannealbnd and genetic algorithms it is tuned the PID gains, and it is developed a PID controller tuned by each algorithm and are compared with fuzzy controllers whose membership functions are tuned with the information obtained by the PID controllers performance. In total 8 different controllers are compared, even though the PID controllers presented lower error values, the FLC’s presented advantages in rise time and settling time reduction, overshoot minimization and ripple limitation in the response. In addition, a robustness analysis of both controller methodologies is carried out, changing the temperature and irradiance from the PV source, and a sensitivity analysis of the controllers changing the voltage reference.
A comparison between Machine Learning models for OSA detection based on ECG signal
(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2023-12-04) Espinosa Varela, Miguel Angel; Ponce Cruz, Pedro; emimmayorquin; Ponce, Pedro; Rojas, Mario; Borja, Vicente; Mata, Omar; Molina, Arturo; School of Engineering and Sciences; Campus Ciudad de México; Rojas Hernández, Mario
OSA is a one of the most common sleep disorders nowadays, which is diagnosed by a Polysomnography (PSG) study. Even though this is the golden standard to diagnose OSA, it is time consuming, very expensive and there are not many specialized centers to conduct it, this implies that fewer patients are diagnosed. The development of new solutions at a lower cost and in less time would allow more patients to be diagnosed and treated promptly. There are solutions that enable the diagnosis of OSA through monitoring signals from the human body, including an auto-diagnosis. However, these solutions do not aim to perform screening on the most significant parameters along with the best model for making predictions. The main objective of this tesis is to make a comparison between 27 Machine Learning (ML) models in order to find the best model to diagnose OSA. It also aims to find which are the most representative parameters in OSA detection. By doing a frequency-domain, time-domain and non-linear domain analysis to extract them from the RR intervals, and with a wilcoxon test and correlation matrix, select the most useful ones. The results showed that the best model was Support Vector Machine (SVM) with an accuracy, balanced accuracy, ROC AUC and F1 Score of 0.97. The most significant parameters found were: RR tri index, LF/HF ratio, alpha 2, HF\%, SDNN and RMSSD. This solution can be integrated into current clinical cases for a quick OSA diagnosis. Proposal does not aim to replace PSG for a complete and accurate diagnosis, but to be a pre diagnosis accessible to a larger number of patients. Health providers can implement this solution and reduce the number of patients in the waiting list. Also, this proposal would make research in OSA diagnosis more accessible and provide a framework that can be the starting point to other researchs.
A comparison of cautious learning procedures in statistical process monitoring
(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2023) Ibarra Tovar, Alain; Víctor Gustavo, Tercero Gómez; emimmayorquin; Cordero Franco, Álvaro Eduardo; School of Engineering and Sciences; Campus Monterrey; Garza Venegas, Jorge Arturo
Statistical process control relies heavily on control charts to gather insights of operational processes and assess their performance. The construction of effective control charts rest on accurate estimations of its parameters, mean and variance when observations are normal. This is a challenge often encountered in real-world applications, and parameters have to be estimated. Various authors have proposed solutions to this challenge by augmenting control limits to ensure a minimum level of performance. Nonetheless, increasing control limits diminish the power of a chart to detect changes. Addressing this trade-off, cautious learning procedures have been introduced to mitigate the impact of imprecise parameter estimates. Cautious Learning is a method which seeks to use the data of the process itself with the objective of increasing the precision of the estimates, making use of certain criteria to select useful information, these criteria vary according to the author. Several authors have presented their proposal, each has its advantages and limitations. This research systematically assesses the effectiveness of such learning procedures when applied to control charts for location, specifically those following CUSUM approaches.
A comparison of control schemes for an articulated 2 degree-of-freedom robot manipulator optimized via genetic algorithms
(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2010-05-01) Arriaga González, Jonathan; Arriaga González, Jonathan; 268989; Soto, Rogelio; Meza, José Luis; Rodríguez, Ernesto; Tecnológico de Monterrey, Campus Monterrey
Robot manipulators play an important role in actual industrial processes. The trajectory following of robot manipulators is a non-linear problem that still requires much research [34]. This research work focuses on the control of the dynamics of an articulated robot manipulator. A 2 degree-of-freedom (DOF) articulated robot manipulator is simulated, each of the two links of the robot having its respective controller. Two different kind of control objectives for the robot's links are considered, position control and velocity control. Four control schemes for the robot's dynamics were selected. For position, a PID Controller [24] and a Fuzzy Self-tuning (FST) PID Controller [14] are considered. On the other hand, for velocity control the FST PD+ Controller [35] and the Fuzzy Sliding Mode (FSM) Controller [12, 16, 28] were chosen. Controller's performance and robustness in relevant tasks are evaluated and compared in order to determine which control scheme fits best for each task. Empirical adjustment of most controller's parameters always depend on the time and tests invested in tuning the controller, it is time consuming and subject to human error. As a fair comparison is intended, controller's parameters are optimized via Genetic Algorithms [22]. With this method, the tuning of parameters is not subtle to human error and the comparison can avoid possible erroneous conclusions. Optimization of parameters of all controllers was carried out successfully. Pa-rameters set by the GA are interpreted and show several details about the structure of the considered controllers. Performance comparison of controllers is discussed and conclusions about the complexity of controllers and its equivalence when performing some tasks is presented.
A computer-aided framework for manufacturability analysis of robot-made assemblies
(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2003-05-01) Barrón Cano, Olivia Maricela; BARRON CANO, OLIVIA MARICELA; 66618; Gordillo Moscoso, José Luis; Sucar Sucar, Luis Enrique; Molina Gutiérrez, Arturo; Sánchez García, José Manuel; ITESM
It has been proven that manufacturing enterprises could obtain signi cant savings, both in time and money, by making changes during the early phases of design of their products. This fact has lead to the development of a number of methodologies and software systems tailored to give designers tools to analyze manufacturability during the design stage. Two different approaches could be taken for analyzing the manufacturability of a given design. One is to use metrics based on different factors, like number of operations, complexity of the involved operations, etc. The other one is to simulate the manufacturing process to see if it is feasible to build the design without having to do a physical mock-up. In the case of robotic assembly of electro-mechanical devices, the second approach is more useful because detailed assembly plans are generated in order to do the analysis. In order to test if a given design could be manufactured by a speci c robotic cell, designers must answer a number of questions about sequencing, stability, xturing, grasping, motion planning and tool accessibility. Although several tools have been developed for computing some of the answers required by designers, they have been developed in an isolated fashion making hard the integration of their results. Each tool uses its own ob ject models, sets of constraints, scale factors, and base units leading to incompatibility problems when designers have to use the output from one tool as the input for another one. Unfortunately, these problems make designers would rather answer their questions empirically, one by one, and thus a system that integrates these tools is need. Such a system will relieve designers from the integration burden allowing them to focus on the creative aspects of their jobs. This thesis describes a computer-aided framework that enables the integration of software tools for manufacturability analysis. Based on a given description of the assembly, a feasible assembly sequence, a robotic cell model, a set of software tools and a description of the order in which the tools must be called, the framework is capable of giving detailed plans for the assembly (if they exist) or feedback about the manufacturability problems (when it is impossible to make the assembly in the given cell). The framework is designed in such a way the software tools do not have to be run locally, instead they could be run in any place in the world which can be accessed trough Internet. Two Web-accesible computer systems were implemented to accomplish this research; the rst one was developed as a mean to gure out the problems that must be tackled down to integrate several software tools, and the second one was developed to show the feasibility of building the proposed framework. The ma jor contributions of this research can be characterized as follows: De nition and formal speci cation of a central assembly-oriented data model which includes information about assemblies, robotic cells and constraints. The data model is based on a comprehensive domain ontology that enables the interoperation of manufacturability analysis software tools by managing information for chaining processes, storing solutions and giving feedback to the user. De nition of a modular framework for integration of software tools and feedback mechanisms. A black box integration approach is used allowing the software tools to be implemented in any computer language as long as they use the standard input/output system to read variables and output results. Constraint management is used as a communication mechanism between the tools. The integration of their solutions is made by testing each solution generated to keep coherence with the requirements of all the tools. Sockets are used to communicate with the software tools, so they could be run in any computer plugged to the World-Wide Web at any location around the world. A simple example was set and four tests were run in order to prove the main characteristics of the framework. Also, a survey was designed and applied to expert assembly designers to have an evaluation of the system's usefulness.
A computer-based method to estimate the level of sensitivity of typical somatosensorial responses
(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-11) Cepeda Zapata, Luis Kevin; Alonso Valerdi, Luz Maria; emipsanchez; Angulo Sherman, Irma Nayeli; Muñoz Ubando, Luis Alberto; School of Engineering and Sciences; Campus Monterrey; Ibarra Zaratre, David Isaac
Understanding somatosensory responses is fundamental to human interaction with the environment, yet quantitative tools for assessing typical tactile responses remain underdeveloped. This thesis introduces a novel computer-based method to evaluate somatosensory processing through electroencephalographic data, focusing on responses to different tactile stimuli. The project will be conducted in three stages: 1) registration of typical somatosensory evoked responses due to touch, air, and vibration in incremental intensities using electroencephalography, 2) validation of the prototypes to evoke tactile evoked potentials, 3) development and evaluation of a classification model to differentiate tactile stimuli and intensities. The study involved the creation of a database of Electroencephalographic recordings from 34 healthy adult volunteers exposed to air, vibration, and caress stimuli, under four diffrent intensity levels intensity levels. The neural responses were analyzed using Discrete Wavelet Transform and classified with machine learning models including K-Nearest Neighbors, Random Forest, and Multilayer Perceptron. For a generalized classification model, an accuracy of 72.6% was achieved for distinguishing stimulus type, 39.3% accuracy for intensity classification and 33.4% for both stimulus type and intensity. Individual classifiers for each subject had an increase in accuracy of 6-10%. Additionally, a deep learning model, EEGNet, was implemented, yielding similar results for stimulus type but lower performance for intensity. Analysis revealed significant inter-subject variability, with subject-specific models outperforming generalized ones, highlighting the need for individualized approaches in somatosensory assessments. This study offers a novel dataset and model framework, which enhances the understanding of neural tactile processing to advance sensory-based interfaces and diagnostic tools in neurophysiological research.
A controller for an LCI to extend the operating range of single-phase brushless exciter synchronous motors
(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2025-06-05) Huidobro Bandala, Franco; Escobar Valderrama, Gerardo; emipsanchez; Villarreal Villarreal, Rommel Daed; School of Engineering and Sciences; Campus Monterrey; Galluzzi Aguilera, Renato
This thesis proposes a control scheme for a load commutated inverter-based drive for a single- phase brushless exciter synchronous motor, which represents a modification to a conventional field-oriented control that (i) improves the pulse generation accuracy including a load synchro- nized pulse generation scheme based on the estimated stator fluxes; (ii) effectively regulates the rotor speed and the estimated stator flux magnitude considering a simplified model of the single- phase brushless exciter; and (iii) extends the rotor speed and load torque operating range through the online calculation of the inverter firing angle based on the commutation model, which obeys the reduction, on average, of the exciter field current and stator current during the overall process. Hardware-in-the-loop tests show the response of the rotor speed and stator flux under a typicalmilling load profile.
A data analytics approach for university competitiveness: the QS rankings
(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2020-06) Estrada Real, Ana Carmen; ESTRADA REAL, ANA CARMEN; 791773; Cantú Ortiz, Francisco Javier; emipsanchez/puemcuervo; Sucar Succar, Luis Enrique; Galeano Sánchez, Natalíe María; Hernández Gress, Neil; Monroy Borja, Raúl; School of Engineering and Sciences; Campus Estado de México; Ceballos Cancino, Héctor Gibrán
In recent years, higher education has been facing the entrance to the internationalmarket due to globalization, this has developed a highly competitive environment, in whichmany institutions have used university rankings as a tool to attract the best academic andstudent talent from all over the world. In this work we take as a base the ranking of QSWord University Rankings and QS Best Student Cities, to apply data science techniques.Extract information on the performance of the most attractive institutions and cities forstudents worldwide, and develop a methodology that allows the stakeholders of the insti-tutions and cities to improve their services for the benefit of students interested in receivingan education of global quality. We accumulated ten years of university rankings (2011-2020) and six years of city rankings (2014-2019), we carried out an exploratory analysisof the indicators and their influence with the final score, later we trained a multiple regres-sion model and panel data to make predictions in the score. Finally, in order to predictthe position, we carry out groupings and train various machine learning algorithms. Withthis work we show a methodology that allows administrators to plan long-term institutionalimprovements to offer a better education and improve their performance in world rankings.
A Deep Learning-Based Computational Framework for the analysis of neurofibrillary tangles in post-mortem brain micrographs from alzheimer’s patients using object detection and semi-automatic segmentation
(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2025-06) Hernández Morales, José Eduardo; Cantoral Ceballos, José Antonio; emipsanchez; González Mendoza, Miguel; Gutiérrez Rodríguez, Andrés Eduardo; School of Engineering and Sciences; Campus Monterrey; Ontiveros Torres, Miguel Ángel
Neurofibrillary tangles (NFTs) are a pathological hallmark of Alzheimer’s disease (AD) and related tauopathies, consisting of abnormal accumulations of the tau protein. Immunofluorescence microscopy remains the standard method for visualizing these aggregates, yet its manual interpretation is time-consuming and prone to variability. Their precise quantification is crucial for understanding disease progression, as it allows researchers to correlate NFT burden with cognitive decline, providing valuable insights into the underlying mechanisms of neurodegeneration. However, the labor-intensive nature of manual assessment and its susceptibility to observer variability limit scalability, highlighting the need for automated, reproducible methodologies in large-scale studies. To address these limitations, we present a deep learning-based computational framework for automated detection, segmentation, and quantitative analysis of NFTs in post-mortem brain micrographs from AD patients. Our approach integrates state-of-the-art object detectors—YOLO11/v12, Faster R-CNN, and transformerbased DETR/RT-DETR—with the Segment Anything Model (SAM) to refine bounding boxes into pixel-accurate masks. Evaluated on a curated dataset of over 900 hippocampal and entorhinal micrographs, our framework achieves an mAP50 of 0.81 for detection and a mean IoU of 0.86 for segmentation. Additionally, we conduct a comprehensive NFT burden analysis across brain regions, highlighting the hippocampal subiculum as the most affected area. These results demonstrate the potential of deep learning to enable high-throughput and reproducible NFT quantification, supporting large-scale neuropathological studies.
A deep-learning application for epithelial cells image detection
(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2021-09-16) Anaya Alvarez, Sergio Eduardo; CORTES CAPETILLO, AZAEL JESUS; 366841; Cortes Capetillo, Azael Jesus; tolmquevedo/mscuervo; Güemes Castorena, David; Lozoya Santos, Jorge de Jesús; School of Engineering and Sciences; Campus Monterrey
Urinary particles are used to evaluate the different urinary tract diseases in patients. Currently, doctors use the traditional methods for urinalysis such as urine dipstick, urine culture and microscopy. Microscopy is an effective method for the diagnosis and treatment of many kidney and urinary tract diseases. However, manual microscopic examination of urine is labor-intensive, subjective, imprecise, and time-consuming. In this project, we proposed the development of a different deep learning models classifier for an automated microscopic urinalysis system for epithelial cells. A dataset was constructed from scratch taking urine samples from the Hospital Ginequito obtaining a total of 857 images. Then, the images were labeled into urine samples with and without epithelial cells for binary classification. Last, we created three deep learning models using the InceptionV3 architectures with different series of fully connected layers randomly initialized and ReLU activation, a dropout rate of 0.2 and a final sigmoid layer for classification. The best model obtained a training accuracy of 81.89% with sensitivity of 77.84%, specificity of 85.94% and precision of 84.70% and a validation accuracy of 84.28% with a sensitivity of 87.50%, specificity of 81.25% and precision of 82.35%. It was concluded that microscopic urinalysis can be done automatically, this opens the door for the classification of more urine particles with improved metrics.
A Digital Lean Thinking Framework & Human-Centric Modelling Approach for Patients Processes Continuous Improvement
(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2022-02-04) Rodríguez Estrada, Regina; Romero Díaz, David Carlos; dnbsrp; Ruiz Soto, Gabriela María; Montesinos Silva, Luis Arturo; School of Engineering and Sciences; Campus Ciudad de México
Lean is a management and engineering methodology that promotes customer-centric value-added creation, continuous improvement, and operational excellence. It provides an organisational culture focused on leadership, communication, empowerment, and teamwork-oriented to customer satisfaction. Furthermore, it offers practical methods and tools to create highly efficient and effective processes for operational excellence. The Lean Healthcare Paradigm aims to create extraordinary patient care in the form of the highest quality, safety, and empathy with the patients, and the easiest and timely access to healthcare services at an affordable cost. It allows hospitals to improve the quality of their healthcare services by reducing errors, risks, and waiting times. Moreover, with the emergence of new digital tools, Lean Hospitals have started their Digital Transformation journey towards a novel Digital Lean Healthcare Paradigm in the pursuit of the next level of operational excellence and patient satisfaction. However, in the healthcare sector, it has been found that hospitals tend to struggle with their “digital transformation” for different reasons, either because they focus only on implementing digital technologies without having control over their processes, or because they do not take into account the needs of the patient, or simply they stay halfway. Thus, this thesis aims to create a Digital Lean Thinking Framework & Human-Centric Modelling Approach for healthcare organisations with a focus on patient-centredness to provide hospitals with a clearer and practical guide on how to carry out their “Digital Lean Healthcare Transformation”. Likewise, the proposed framework emphasises the need to follow a continuous improvement method such as the Plan-Do-Check-Act (PDCA) Cycle to have a more structured strategic planning with clear objectives, tasks, methods, timelines, and responsibilities. Finally, the case study of this thesis focuses on enriching and validating the proposed Digital Lean Thinking Framework & Human-Centric Modelling Approach for Patients Processes Continuous Improvement by “improving” the medical consultation process of a patient in the Gynaecology area of a private hospital in Monterrey, Mexico.