Universidad Tecnológica de Bolívar
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Las otras memorias - Exposición fotográfica
No full textLas Otras Memorias es una exposición fotográfica que se ha concebido para generar entre su público una reflexión crítica sobre cómo se ha construido la Cartagena de Indias contemporánea desde la imagen fotográfica y la narrativa comunitaria. Deseamos que sirva para comprender mejor las lógicas de esta ciudad. Una ciudad, como muchas otras en Colombia y en América Latina, con muchas heridas y atravesada por múltiples violencias que parecen no cesar nunca. También con muchos olvidos. Pero Las Otras Memorias también es un discurso de dignidad, porque habla de nuestra identidad cultural, de nuestro patrimonio, de la riqueza de nuestra diversidad y de la solidaridad permanente entre las clases populares
Revised cross-correlation and time-lag between cosmic ray intensity and solar activity using chatterjee’s correlation coefficient
No full textThis study revisits the cross-correlation between cosmic ray intensity (CRI) and solar activity (SA) by comparing traditional Pearson correlation
with Chatterjee’s correlation coefficient. Traditional analyses using Pearson correlation are useful for identifying linear relationships and time lags.
However, they may not fully capture more complex interactions in the data. Chatterjee’s correlation coefficient, while sensitive to different types of
relationships, including nonlinear ones, provides a complementary perspective on the temporal relationships between CRI and SA. This approach
broadens our understanding of potential dependencies, offering additional insights that may not be captured through Pearson correlation alone.
The findings reveal that Chatterjee’s correlation complements Pearson’s insights by providing an alternative view of the relationship between
cosmic ray intensity (CRI) and solar activity (SA). The results show that Chatterjee’s correlation coefficients are, on average, approximately
45-50% smaller than Pearson’s, which could reflect different sensitivities to the underlying data structure rather than solely indicating a nonlinear
component. Additionally, the time lags identified using Chatterjee’s correlation are generally shorter and more consistent across different solar
cycles compared to those obtained with Pearson’s correlation, suggesting that CCC may capture temporal patterns in a distinct manner.
Further analysis using Dynamic Time Warping (DTW) and Mean Absolute Percentage Error (MAPE) metrics demonstrated that, in more than
half of the scenarios considered, alignment based on Chatterjee’s time lags resulted in lower errors and better alignment of the series compared to
Pearson’s lags. This indicates that Chatterjee’s method is particularly effective for capturing the immediate and nuanced responses of CRI to SA
changes, especially in recent solar cycles.
This comprehensive approach provides broader insights into the dynamic interactions between cosmic ray intensity (CRI) and solar activity
(SA), highlighting the importance of considering multiple correlation measures, including both linear and nonlinear approaches, in space weather
research. The results suggest that Chatterjee’s correlation offers a complementary perspective on these interactions, providing additional details
about how SA influences CRI over time, which may not be fully captured by Pearson’s correlation alone
Nivel de procrastinación en estudiantes de la Universidad Tecnológica de Bolívar
No full textEn esta investigación se muestra la adaptación realizada al contexto colombiano, Análisis Factorial Exploratorio, Análisis Factorial Confirmatorio, Alfa de Cronbach, Prueba de adecuación de Kaiser- Meyer-Olkin y esfericidad de Bartlett de la escala de procrastinación irracional (IPS) y la escala de procrastinación pura (EPP) que evalúan la conducta de procrastinación de manera voluntaria. La IPS cuenta con 9 ítems y la EPP cuenta con 12 ítems. Se analizaron los datos obtenidos de una muestra de 110 estudiantes de la Universidad Tecnológica de Bolívar, universidad de carácter privado de la ciudad de Cartagena. Todos los análisis descriptivos y factoriales se llevaron a cabo en el software R. Se obtuvieron correlaciones significativas, índices de bondad de ajuste aceptables y con respecto a la fiabilidad una adecuada consistencia interna para ambas escalas.Maestría en Estadística AplicadaMaestrí
Multiannual Change Detection in Long and Dense Satellite Image Time Series Based on Dynamic Time Warping
No full textHigh-resolution (HR) satellite image time series (SITS) are a valuable data source for analyzing land cover change (LCC) due to their large amount of spatial, spectral, and temporal information. However, most existing LCC detection methods focus on binary change detection (CD) within a single year and fail to provide detailed information about the specific type of change. In this study, we propose a multiannual CD approach that identifies changes occurring between consecutive years and provides information about the type of LC transition. The proposed approach exploits multiannual and multispectral SITS to generate a hypertemporal feature space (FS). This FS is analyzed to create a set of CD maps that indicate the time, probability, and type of change. To measure the similarity between pixel time series, we use dynamic time warping (DTW) in the space of hypertemporal features. A hierarchical clustering technique is exploited to develop a set of class prototypes (CPs) that represent the characteristics of different LC classes. The CPs are then used to identify the most probable LC transition for each changed pixel. Two test areas were selected to evaluate the effectiveness of the proposed approach. The first one is located in Amazon and spans the years 2015 to 2019; and the second one is located in Sahel-Africa and covers the years 2015 and 2016, using multiannual Landsat 7 and 8 SITS. The results demonstrate that the proposed approach is effective in detecting multiannual changes and in identifying the LC transitions
A computer vision system for detecting motorcycle violations in pedestrian zones
No full textThis paper presents a system that relies on computer vision to identify instances of motorcycle
violations in crosswalks utilizing CNNs. The system was trained and evaluated on a novel
public dataset published by the authors, which contains traffic images classified into four
categories: motorcycles in crosswalks, motorcycles outside crosswalks, pedestrians in cross walks, and only motorbike outside. We demonstrate the viability of leveraging deep learning
models such as YOLOv8 for this purpose and provide details on the training and performance
of the model. This system has the potential to enable intelligent traffic enforcement to mit igate accidents in pedestrian zones; to develop the system, a dataset comprising over 6,000
images was amassed from publicly available traffic cameras and subsequently annotated.
Several models, including YOLOv8, SSD, and MobileNet, were trained on this dataset. The
YOLOv8 model attained the highest performance with a mean average precision of 84.6%
across classes. The study presents the system architecture and training process. Results illus trate the potential of utilizing deep learning to detect traffic violations in pedestrian zones,
which can promote intelligent traffic enforcement and improved safety
Modelo de evaluación para la innovación educativa en la formación profesional Centro de Comercio y Servicios, Sena Regional Bolívar
No full textEl proyecto de investigación representa un enfoque conceptual y metodológico destinado a definir un modelo de evaluación para la innovación educativa en la formación profesional, que parte de una revisión exhaustiva de las propuestas actuales en campo y la integración de estrategias y fundamentos respaldados por evidencia científica desde el ámbito de la innovación en educación. Es importante destacar que el objetivo principal de esta investigación es definir un modelo y hoja de ruta para la evaluación de la innovación educativa en el contexto de la formación profesional. La validación de este modelo puede ser considerada como un ejercicio en futuras investigaciones en el contexto de la investigación educativa.UNIVERSIDAD TECNOLOGICA DE BOLIVARMagister en Gestión de la InnovaciónMaestrí
Gentrificación, cultura y desarrollo en la comunidad de la Boquilla, Cartagena de Indias
No full textAl ser la gentrificación un proceso complejo que involucra cambios en la demografía, la estructura socioeconómica y la identidad cultural de un área, el presente estudio de caso puntualiza y emplea un análisis de los diferentes mecanismos que la gentrificación utiliza en el desarrollo de las transformaciones urbanísticas y cómo estos alcanzan a transformar, no solo el componente arquitectónico de un determinado territorio, sino, también aspectos culturales y económicos. Como caso de estudio, se utiliza a la comunidad de la Boquilla, territorio ubicado en la zona norte de la Ciudad de Cartagena, Colombia, la cual ha sentido algunos de los impactos de este fenómeno.Universidad Tecnológica de BolívarPolitólogoPregrad
A Computer vision based system for human detection and automatic people counting
No full textOccupancy control is a fundamental aspect of managing spaces and services effectively. It aims to ensure safety, compliance with regulations, emergency preparedness, and overall satisfaction for individuals and businesses. To align with the described need, this paper presents a computer vision based system for automatic people counting in gates. The system is divided in five stages: video capture, motion analysis, human detection, human tracking and people counting. An RGB camera captures the top-view image of the gate and analyze the change or movement in the objects in scene. When motion is detected, the frame is sent to the object detector, which is a convolutional neural network. Then, a tracking algorithm analyzes the movement patterns of people. According to the route, it is determined whether the person arrives or leaves and the count is updated. Two test scenarios are analyzed: the entry of a public bus and a building gate. The people detection module is tested, showing a mAP of 95.2% and a mean IoU (50%) of 55.9%. Also, the counting is tested showing an average precision of 96.8%, a recall of 92% and an F1-Score of 94.3%. Finally, the system performance is evaluated, showing an average processing time of 34.2 ms and 29.2 FPS
Evaluating generative AI tools: A comparative guide for new users
No full textOne of the most prominent forms of artificial intelligence that has been made public is generative AI, which offers a fresh perspective and direction for numerous global sectors. The impact of this artificial intelligence model on nearly every business and how certain vocations can be pursued has garnered a large audience. This paper evaluates generative AI from an objective standpoint and proposes a comparison of some of its key tools to help new users solve problems in their daily lives, at work or at home. This highlights the significance of understanding and utilizing this kind of AI
Optimización de la gestión del mantenimiento a través de la inteligencia artificial
No full textEste artículo analiza cómo la Inteligencia Artificial (IA) está revolucionando el mantenimiento en diversas industrias. Se enfoca en la transición de métodos convencionales a estrategias impulsadas por IA, destacando mejoras en eficiencia y predicción de fallas. Se exploran casos prácticos, resaltando las ventajas y retos en la integración de la IA en los sistemas de mantenimiento existentes. Se concluye con perspectivas sobre futuras investigaciones y desarrollos tecnológicos en este ámbito, subrayando la importancia de la adaptabilidad y la innovación continua