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1
artículo
El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.
2
artículo
Publicado 2019
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Modern studies have shown that mirrow neurons are involved in the development of social empathy and language. Consequently, deficiency in mirror neural networks response could be one of the dysfunctions present in autistic spectrum disorder (ASD), as a phenotypic functional expression of channelopathies in some brain regions.Early detection of deficiencies in mirror neural network systems could allow more efficient applications of behavioral therapies in patients with ASD. The detection of MU waves in the electroencephalogram (EEG) could be an interesting technique that refers to the functioning of these neural networks.In this article we present a simple technique, developed with the purpose of identifying the presence of MU waves in the EEG record. It consists of a processing that analyzes each one of the derivations of the EEG, with the implementation of a mathematical method. The sig...
3
objeto de conferencia
Publicado 2017
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Sleepiness could cause different accidents at work and in our daily lives. Activities such as driving a car, handling heavy machinery, being in charge of controlling a satellite or monitoring a nuclear plant, are activities that require short visual and motor reaction times. These reactions could be affected by sleepiness. The highest number of these accidents is related to vehicular accidents. WHO statistics show that 1.2 million people worldwide die every year due to road crashes, 50 million people are injured, and more than 3,000 people die daily from road traffic injuries. The primary objective of the present work is to develop a tool based on techniques of artificial intelligence and image processing that can detect states of sleepiness in people whose work needs the greatest attention-to avoid accidents. The idea is to develop an algorithm that can be executed on a computer and thr...
4
artículo
Attention deficit hyperactivity disorder (ADHD) represents a medical condition characterized by the presence of inattention, hyperactivity, and impulsivity, which affects the academic development of students globally. In Peru, it affects a proportion of the pediatric population ranging from 2% to 12%, with a prevalence of 12.1% in South Lima, particularly in public schools. This research presents an online application with machine learning to improve the detection of ADHD in elementary school children. Several machine learning algorithms were reviewed and Random Forest was selected as the best-performing model with an accuracy of 96.08%. The model uses 27 selected variables, optimizing data collection and training. The child answers the questionnaire within the app and psychologists can access the app to visualize the results, aiding in the early detection of ADHD. The experiment involve...
5
objeto de conferencia
Publicado 2018
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Classification green coffee beans is one of the main tasks during the quality grading process. This evaluation is normally carried out by specialist doing a visual inspection or using traditional instruments which have some limitations. This work is focused on the implementation of a computer vision system combining a hardware prototype and a software module. The hardware was made to guarantee the controlled conditions to capture the images of green coffee beans, the software is based on computer vision algorithms in order to detect defects of the coffee beans. The novelty of our proposal is the combination of algorithms to enhance the accuracy and the high number of defects detected. We applied a White Patch algorithm as an image enhancement procedure, color histograms as feature extractor and Support Vector Machine (SVM) for the classification task. It was constituted an image beans da...
6
tesis de maestría
Publicado 2018
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Object recognition in videos is one of the main challenges in computer vision. Several methods have been proposed to achieve this task, such as background subtraction, temporal differencing, optical flow, particle filtering among others. Since the introduction of Convolutonal Neural Networks (CNN) for object detection in the Imagenet Large Scale Visual Recognition Competition (ILSVRC), its use for image detection and classification has increased, becoming the state-of-the-art for such task, being Faster R-CNN the preferred model in the latest ILSVRC challenges. Moreover, the Faster R-CNN model, with minimum modifications, has been succesfully used to detect and classify objects (either static or dynamic) in video sequences; in such setup, the frames of the video are input “as is” i.e. without any pre-processing. In this thesis work we propose to use Robust PCA (RPCA, a.k.a. Principal...
7
tesis de maestría
Publicado 2018
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Object recognition in videos is one of the main challenges in computer vision. Several methods have been proposed to achieve this task, such as background subtraction, temporal differencing, optical flow, particle filtering among others. Since the introduction of Convolutonal Neural Networks (CNN) for object detection in the Imagenet Large Scale Visual Recognition Competition (ILSVRC), its use for image detection and classification has increased, becoming the state-of-the-art for such task, being Faster R-CNN the preferred model in the latest ILSVRC challenges. Moreover, the Faster R-CNN model, with minimum modifications, has been succesfully used to detect and classify objects (either static or dynamic) in video sequences; in such setup, the frames of the video are input “as is” i.e. without any pre-processing. In this thesis work we propose to use Robust PCA (RPCA, a.k.a. Principal...
8
tesis de maestría
Publicado 2018
Enlace
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Object recognition in videos is one of the main challenges in computer vision. Several methods have been proposed to achieve this task, such as background subtraction, temporal differencing, optical flow, particle filtering among others. Since the introduction of Convolutonal Neural Networks (CNN) for object detection in the Imagenet Large Scale Visual Recognition Competition (ILSVRC), its use for image detection and classification has increased, becoming the state-of-the-art for such task, being Faster R-CNN the preferred model in the latest ILSVRC challenges. Moreover, the Faster R-CNN model, with minimum modifications, has been succesfully used to detect and classify objects (either static or dynamic) in video sequences; in such setup, the frames of the video are input “as is” i.e. without any pre-processing. In this thesis work we propose to use Robust PCA (RPCA, a.k.a. Principal...
9
artículo
Publicado 2024
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Manual identification of diseases in crops is costly and subjective, driving the need for automated systems for accurate detection in the field. This requires the use of technologies based on the integration of IoT and deep learning models to improve the assessment capacity of crop health and leaf disease, with continuous monitoring. The literature review highlights technological solutions that include weed and disease detection using artificial intelligence and autonomous systems, as well as semantic segmentation algorithms to locate diseases in field images whose processes can be improved with systems based on microcontrollers and sensors. This research implements a leaf health monitoring system using IoT and AI technologies, with the development of an IoT device with a camera, the configuration of an MQTT broker in NODE-Red, and the implementation of a script in Python for leaf instan...
10
objeto de conferencia
This research was supported by the FONDO NA-CIONAL DE DESARROLLO CIENT´FICO, TEC-NOLÓGICO Y DE INNOVACIÓN TECNOLÓGICA -FONDECYT as executing entity of CONCYTEC under grant agreement no. 01-2019-FONDECYT-BM-INC.INV in the project RUTAS: Robots for Urban Tourism, Autonomous and Semantic web based.
11
objeto de conferencia
Publicado 2023
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21st LACCEI International Multi-Conference for Engineering, Education, and Technology: “Leadership in Education and Innovation in Engineering in the Framework of Global Transformations: Integration and Alliances for Integral Development”, Hybrid Event.
12
artículo
Publicado 2023
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This research study seeks to improve the efficiency of the production processes at a MSME metalworking company operating under the Make to Order (MTO) strategy. For these purposes, the authors first assessed the previous problems reported by the company, detecting a low efficiency rate of 69.56% in its production process, which generated an economic impact at 14.6%. Then, the design of a custom model based on several Lean Manufacturing tools, such as Sort and Set in Order Focused on the 5S, Visual Management Board and Work Standardization, production process efficiency improved by 6.4%, reprocessing experienced a 12.63% reduction, and search times decreased by 24 minutes. which translated into a 5.83% savings for the company. In fact, the proposed model generated positive improvements for the research study.
13
artículo
Publicado 2019
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It is known that 33% of traffic accidents worldwide are caused by drunk driving or drowsiness [1] [2], so a drowsiness level detection system that integrates image processing was developed with the use of Raspberry Pi3 with the OpenCV library; and sensors such as MQ-3 that measures the percentage of alcohol and the S9 sensor that measures the heart rate. In addition, it has an alert system and as an interface for the visualization of the data measured by the sensors a touch screen. With the image processing technique, facial expressions are analyzed, while physiological behaviors such as heart rate and alcohol percentage are measured with the sensors. In image test training you get an accuracy of x in a response time of x seconds. On the other hand, the evaluation of the operation of the sensors in 90% effective. So the method developed is effective and feasible.
14
artículo
Publicado 2019
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El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.
15
tesis de grado
Publicado 2020
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It is known that 33% of traffic accidents worldwide are caused by drunk driving or drowsiness [1] [2], so a drowsiness level detection system that integrates image processing was developed with the use of Raspberry Pi3 with the OpenCV library; and sensors such as MQ-3 that measures the percentage of alcohol and the S9 sensor that measures the heart rate. In addition, it has an alert system and as an interface for the visualization of the data measured by the sensors a touch screen. With the image processing technique, facial expressions are analyzed, while physiological behaviors such as heart rate and alcohol percentage are measured with the sensors. In image test training you get an accuracy of x in a response time of x seconds. On the other hand, the evaluation of the operation of the sensors in 90% effective. So the method developed is effective and feasible
16
tesis de grado
Publicado 2016
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Se explora la influencia del Trastorno de Espectro Autista en el desarrollo de la percepción visual y auditiva en un estudio de casos con seis escolares (3 con desarrollo normal, 3 diagnosticados con Autismo), entre 6 y 9 años de edad, utilizando una metodología experimental. Para la percepción visual, se midió el tiempo promedio de fijación visual al observar imágenes de diferentes características (color/blanco y negro, reales/caricatura, brillantes/opacas, en movimiento/estáticas). Para la percepción auditiva, se midió el tiempo promedio de detección de la localización de la fuente de sonido frente a estímulos auditivos desde locaciones diferentes (esquinas inferiores derecha e izquierda). Se encontró que los escolares con Autismo presentaron las siguientes características: (a) tiempos de fijación visual más altos al observar imágenes a color, brillantes y en movimie...
17
tesis de grado
Publicado 2016
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Se explora la influencia del Trastorno de Espectro Autista en el desarrollo de la percepción visual y auditiva en un estudio de casos con seis escolares (3 con desarrollo normal, 3 diagnosticados con Autismo), entre 6 y 9 años de edad, utilizando una metodología experimental. Para la percepción visual, se midió el tiempo promedio de fijación visual al observar imágenes de diferentes características (color/blanco y negro, reales/caricatura, brillantes/opacas, en movimiento/estáticas). Para la percepción auditiva, se midió el tiempo promedio de detección de la localización de la fuente de sonido frente a estímulos auditivos desde locaciones diferentes (esquinas inferiores derecha e izquierda). Se encontró que los escolares con Autismo presentaron las siguientes características: (a) tiempos de fijación visual más altos al observar imágenes a color, brillantes y en movimie...
18
tesis de grado
Publicado 2015
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Este proyecto tiene como objetivo la implementación de algoritmos para la detección de defectos en las telas poliéster. Como sabemos, desde sus inicios la industria ha utilizado avances tecnológicos no sólo para optimizar los procesos de fabricación sino también para mejorar la calidad de los productos. Ahora, si bien, no es posible evitar las fallas que alteran la calidad de las telas poliéster, sí es posible su detección mediante una inspección visual dentro del proceso de fabricación. En el presente estudio se realizó algoritmos de procesamiento de imágenes mediante el uso de librerías del software LabView para la detección de defectos en las telas poliéster, basándonos en muestras de telas con manchas comunes (MC), manchas de aceite (MA) y puntadas erróneas (PE), las cuales nos permitieron realizar varias pruebas experimentales, utilizando un módulo de pruebas a p...
19
tesis de grado
Publicado 2015
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La neumonía es la principal causa de muerte en niños menores de 5 años en el mundo. Se calculan más muertes por neumonía que por VIH, malaria y sarampión. Considerando la alta tasa de mortandad infantil por neumonía; el objetivo principal de este proyecto de tesis, fue diseñar e implementar un prototipo electrónico para detección temprana contra la neumonía en infantes. Para este propósito, se usó un sensor de temperatura, el LM35, el cual se adaptó a un electrodo médico, de esta manera fue adherido al cuerpo del paciente, además se usó un sensor magnético adaptado a una banda elástica, la cual se colocó alrededor del tórax del paciente. Estos sensores midieron la temperatura corporal en °C y el número de respiraciones por minuto (RPM), respectivamente. Ambas mediciones se acondicionaron, usando el amplificador operacional LM358N y se procesaron usando un Microcont...
20
artículo
Publicado 2020
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Objetives: To describe the occupational medical characteristics of professional drivers and the toxicological results present in traffic accidents in an occupational health center in Metropolitan Lima. 2014-2018. Material and methods: Retrospective descriptive study of secondary source data analysis. The sample size analyzed was 11520 professional drivers from the city of metropolitan Lima during 2014 to 2018, selected from an unnamed database using a probabilistic simple randomization sample. Univariate descriptive statistics were used using absolute and relative frequency values, calculation of 95% confidence intervals and error diagrams for each of the variables, identifying the differences in each of the categories or levels of the variable. The information processing was performed in the statistical program R version 3.6. Results: 64% of drivers suffer from overweight or obesity, 58...
