According to worldwide statistics, traffic accidents are the cause of a high percentage violent deaths. The time taken send medical response accident site is largely affected by human factor and correlates with survival probability. Due this wide use video surveillance intelligent systems, an automated detection approach becomes desirable for computer vision researchers. Nowadays, Deep Learning (DL)-based approaches have shown performance in tasks that involve complex features relationship....

In recent years, the use of deep learning-based models for developing advanced healthcare systems has been growing due to results they can achieve. However, majority proposed learning-models largely convolutional and pooling operations, causing a loss in valuable data focusing on local information. this paper, we propose approach that uses global features which are importance medical image segmentation process. order train architecture, used extracted three-dimensional (3D) blocks from full...

El conocimiento teórico y práctico que adquieren los estudiantes de las carreras forman a futuros profesionales negocios (Administración, Contabilidad, Marketing, etc.) es un asunto escasamente investigado. En particular, no se ha investigado si universidades radicadas en el mismo país mismos conocimientos sobre este tema. Este relevante porque existen consensos teóricos concepto Responsabilidad Social Empresarial, esa falta consenso podría trasladarse su enseñanza. objetivo del trabajo...

Each year, more than 1 million people die due to traffic accidents, and one-third of these lives could be saved by reducing medical response time. Multi-Modal Deep Learning (MMDL) has emerged in recent years as a powerful tool that integrates different types data enhance decision-making capabilities models. Additionally, Vision Transformers (ViT) are approach for processing images videos shown promising results various fields knowledge. In this project, we propose ViT-based architecture...

High-resolution 3D scanning devices produce high-density point clouds, which require a large capacity of storage and time-consuming processing algorithms. In order to reduce both needs, it is common apply surface simplification algorithms as preprocessing stage. The goal cloud the volume data while preserving most relevant features original cloud. this paper, we present new feature-preserving algorithm. We use global approach detect saliencies on given Our method estimates feature vector for...

Denoising the point cloud is fundamental for reconstructing high quality surfaces with details in order to eliminate noise and outliers 3D scanning process. The challenges a denoising algorithm are reduction sharp features preservation. In this paper, we present new model reconstruct smooth clouds that combine L1-median filtering sparse L1 regularization both normal vectors updating position of points preserve cloud. filter robust compared mean. norm way measure sparsity solution, applying...

In this work, we present a shape-based approach to automatic skin lesion segmentation and classification in dermoscopic images. We aim differentiate three types of 1) common nevi, 2) atypical 3) melanomas by exploring the morphology features segmented lesions. Our method is an attempt design computer-aided ABCDEs melanoma, where Asymmetry Border components are estimated using morphological features. The lesions first super-pixel merging strategy with RGB criterion. Later, was evaluated on...

Small urban areas in developing countries have very little resources, especially for keep up to date maps that serves the management of territory by public authorities. Roads are probably one most rapidly, but important and expensive maintain elements infrastructure. Use available affordable aerial imagery sounded deep learning technology could help this matter. This work presents a pipeline using an Image Translation approach instead traditional image segmentation architecture extraction...

<p class="Texto">El modelado y simulación de pequeños sistemas industriales ha adquirido gran importancia en los procesos toma decisiones, toda vez que les permite a microempresas fundamentar sus decisiones producción. Este artículo hace un análisis una empresa dedicada la confección ropa exterior masculina con producción semanal promedio 490 prendas. La motivación del estudio radica el interés incrementar su productividad; por esto, se desarrolló modelo sistema real herramienta...

We theoretically and quantitatively analyze the impact of fiscal monetary stimulus during after 2020 Covid recession on output, inflation, house prices. Our theoretical analysis clarifies that increases consumption demand in a by providing liquidity, redistributing from savers to borrowers, lowering return saving if it causes future inflation. Future inflation only occurs taxes do not increase pay for stimulus. In our quantitative analysis, we study temporary shift passive policy with low...

The COVID-19 pandemic has had a significant impact on various aspects of society, including economic, health, political, and work-related domains. also caused an emotional effect individuals, reflected in their opinions comments social media platforms, such as Twitter. This study explores the evolution sentiment Spanish tweets through data analysis based fine-tuned BERT architecture. A total six million were collected using web scraping techniques, pre-processing was applied to filter clean...

Detection and Semantic Segmentation of vehicles in drone aerial orthomosaics has applications a variety fields such as security, traffic parking management, urban planning, logistics, transportation, among many others. This paper presents the HAGDAVS dataset fusing RGB spectral channel Digital Surface Model DSM for detection segmentation from images, including three vehicle classes: cars, motorcycles, ghosts (motorcycle or car). We supply an additional variable to be included deep learning...

Vegetation encroachment in power line corridors remains a major challenge for modern energy-dependent societies, as it can cause outages and lead to significant financial losses. Unmanned Aerial Vehicles (UAVs) have emerged promising solution monitoring infrastructure, owing their ability acquire high-resolution overhead images of these areas quickly affordably. However, accurate segmentation the vegetation this imagery is challenging task, due complexity scene high pixel imbalance between...

In education, chatbots provide personalized learning, instant feedback, and accessible support, enhancing student engagement understanding across various academic subjects. This study investigates the deployment of a chatbot on SnatchBot platform, integrated with Telegram, to assist university students in Object-Oriented Programming (OOP). The development included defining objectives, designing its personality, selecting tools, creating conversation flow using natural language processing...

Abstract The hyperloop system constitutes one of the most promising alternative means transportation for next years. Nevertheless, there are still some challenges to face, such as blockage air surrounding pod inside tube. To solve that, proposal consists including a compressor that helps relieve pressure conditions between and Thus, this work makes, first time in context application, numerical analysis with CFD tools performance under low Reynolds by decreasing until operation values. By...

Many scientific articles have been written about management students’ perceptions of corporate social responsibility. Most these investigations were carried out on small samples, made up students from a single university. Very few compared different universities and countries. The main objective this paper is to investigate whether countries operate as an explanatory variable for their concept. Fifty-four previous reviewed, identifying some important conceptual problems high amount...