6.1 Proyectos de investigación científica
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Publicación3D Pose Estimation Oriented to the Initialization of an Augmented Reality System Applied to Cultural Heritage(Digital Cultural Heritage, 2018)
;Rodriguez, RM ;Aguilar, R ;Uceda, SCastaneda, BLa realidad aumentada (AR) aplicada al patrimonio cultural pretende mejorar la experiencia de aprendizaje en sitios arqueológicos, no solo para los visitantes sino también para los investigadores. La estimación de Pose 3D es un problema común en aplicaciones para AR, reconocimiento de objetos, modelado 3D, entre otros. Los sistemas AR utilizan diferentes métodos para estimar la pose de la cámara: detección de bordes y detección de puntos clave, entre otros. La elección del método a utilizar depende de las características del escenario a detectar. En este trabajo se realiza un estudio comparativo de los principales métodos de estimación de pose basados en modelos 3D. Además, presentamos la implementación y validación de un algoritmo de estimación de pose, orientado a la inicialización de un sistema AR aplicado a la “Huaca de la Luna”, una pirámide de ladrillos de adobe construida por la civilización Moche en el norte del Perú. El algoritmo propuesto presenta dos fases, una fase de entrenamiento, donde se extraen puntos clave 3D de una imagen de referencia, y una fase de detección, donde el proceso de inicialización se realiza comparando la correspondencia de puntos 2D/3D utilizando un algoritmo PnP. Hemos comparado cuatro variaciones del algoritmo de estimación de poses 3D utilizando diferentes métodos: descriptores SIFT y SURF para la descripción de puntos clave y algoritmos EPnP y REPPnP para la estimación de poses PnP. Los resultados muestran un error de traducción de 1,54 cm, con un tiempo medio de procesamiento de 2,78 s, un error máximo de reproyección de 1,5 píxeles y una tasa de estimación exitosa del 100 % en escenarios con condiciones de luz normales y altas. -
PublicaciónA Low-Cost IoT Platform for Heat Stress Monitoring in Dairy Cattle(Institute of Electrical and Electronics Engineers Inc., 2021)
;Choquehuanca-Zevallos J.J.Mayhua-Lopez E.This paper presents a compact and modular system based on Internet-of- Things for monitoring cattle behavior and stress in real-time. It will help to model certain parameters such as temperature and certain weather variables such as relative humidity, solar radiation, among others thanks to Internet-of- Things (IoT) sensors localized in different points of barns and the fields for cattle farming. A main benefit of the system is that it is built with low-cost hardware and low battery consumption. The wireless system also allows the collection of data in real-time and obtains the temperature-humidity index. This index will give an approach to the heat stress in cattle not only on the farm but in the vicinity of the farm. Finally, the high amount of collected data will allow employing Big Data solutions for estimating the impact on milk productivity. In the future, more sensors will be deployed for a more detailed reading of weather variables and their impact on dairy cattle. © 2021 IEEE. -
PublicaciónA Low-Resourced Peruvian Language Identification Model(CEUR-WS, 2017)
;Linares A.E.Oncevay-Marcos A.Due to the linguistic revitalization in Peru´ through the last years, there is a growing interest to reinforce the bilingual education in the country and to increase the research focused in its native languages. From the computer science perspective, one of the first steps to support the languages study is the implementation of an automatic language identification tool using machine learning methods. Therefore, this work focuses in two steps: (1) the building of a digital and annotated corpus for 16 Peruvian native languages extracted from documents in web repositories, and (2) the fit of a supervised learning model for the language identification task using features identified from related studies in the state of the art, such as ngrams. The obtained results were promising (97% in average precision), and it is expected to take advantage of the corpus and the model for more complex tasks in the future. -
PublicaciónA multi-modal visual emotion recognition method to instantiate an ontology(SciTePress, 2021)
;Heredia J.P.A. ;Cardinale Y. ;Dongo I.Díaz-Amado J.Human emotion recognition from visual expressions is an important research area in computer vision and machine learning owing to its significant scientific and commercial potential. Since visual expressions can be captured from different modalities (e.g., face expressions, body posture, hands pose), multi-modal methods are becoming popular for analyzing human reactions. In contexts in which human emotion detection is performed to associate emotions to certain events or objects to support decision making or for further analysis, it is useful to keep this information in semantic repositories, which offers a wide range of possibilities for implementing smart applications. We propose a multi-modal method for human emotion recognition and an ontology-based approach to store the classification results in EMONTO, an extensible ontology to model emotions. The multi-modal method analyzes facial expressions, body gestures, and features from the body and the environment to determine an emotional state; this processes each modality with a specialized deep learning model and applying a fusion method. Our fusion method, called EmbraceNet+, consists of a branched architecture that integrates the EmbraceNet fusion method with other ones. We experimentally evaluate our multi-modal method on an adaptation of the EMOTIC dataset. Results show that our method outperforms the single-modal methods. Copyright © 2021 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved -
PublicaciónA virtual reality and brain computer interface system for upper limb rehabilitation of post stroke patients(Institute of Electrical and Electronics Engineers Inc., 2017)
;Achanccaray D. ;Acuña K. ;Carranza E.Andreu-Perez J.This work presents a brain computer interface (BCI) framework for upper limb rehabilitation of post stroke patients, combining BCI and virtual reality (VR) technology; a VR feedback is shown to the participants to achieve a greater activation of certain brain regions involved with the performing of upper limb motor task. This system uses an adaptive neuro-fuzzy inference system (ANFIS) classifier to discriminate between a motor task and rest condition, the first one classifies between extension and rest conditions; and the second one classifies between flexion and rest conditions. In the training stage, eight healthy subjects participated in the sessions, the best accuracies are 99.3% and 88.9%, as a result of cross-validation. Meanwhile, the best accuracy in online test is 89%. The methodology here presented can be straightforwardly employed as a rehabilitation system for brain repair in individuals with neurological diseases or brain injury. -
PublicaciónAdaptive PID controller with auto-tuning applied to the agricultural food industry(IEEE Sensors Journal, 2017)
;Figueroa, AAP ;Silupu, JJMZabaleta, RSGAfter being aware of the high demand of vapor compression refrigeration systems for the conservation of agri-food and hydrobiological products and the high economic costs that the use of these systems produces, both academia and industry have carried out studies that have allowed them to develop advanced technologies in order to produce savings in energy consumption. These advances lie in the production of new control algorithms to be implemented in the domestic as well as the industrial, and for the case of the academy, for tests in pilot plants. This document explains the design of a control system based on the algorithm of an adaptive PID autotunning that has a learning process, which, to demonstrate a better performance of the systems of cooling by compression of steam and, in addition, the controller must avoid compressor starts, during which there is a lot of energy consumption. In addition, the construction of the mathematical model used to express the dynamics of a conventional refrigeration system used in product preservation processes in the agro-food industry is presented. -
PublicaciónAdaptive Predictive Control of Dissolved Oxygen Concentration in a Dynamic Model of Whiteleg Shrimp Culture(Institute of Electrical and Electronics Engineers (IEEE), 2017)
;Sacasqui, M ;Sanchez, IVasquez, EIt introduces a dynamic model for dissolved oxygen content in an aquaculture system of whiteleg shrimp. Additionally, a non-linear controller has been designed for hourly control. This time frequency is necessary because of the time required to reach the predicted levels of oxygen. The dynamic model has incorporated a shrimp growth model calibrated with real data. The results show how the controller maintains the dissolved oxygen levels in the desired target, helping to improve production and minimize costs. -
PublicaciónAn enhanced algorithmic approach for automatic defects detection in green coffee beans(Institution of Engineering and Technology, 2018)
;Zambrano C.E.P. ;Caceres J.C.G. ;Ticona J.R. ;Beltran-Castanon N.J. ;Cutipa J.M.R.Beltran-Castanon C.A.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 database of 1930 instances, and it was extracted 768 features, finally, the model was applied over 13 categories of defects described by the Specialty Coffee Association of America (SCAA). Results of classification achieved a 98.8% of overall accuracy detection, therefore the proposed system proved to be effective in classifying physical defects of green coffee beans. With this work we showed that the grading green coffee process can be automatized, adding a new paradigm in quality evaluation task to enhance the coffee industry. -
PublicaciónAn Evaluation of Physiological Public Datasets for Emotion Recognition Systems(Springer Science and Business Media Deutschland GmbH, 2021)
;Mendoza A. ;Cuno A. ;Condori-Fernandez N.Lovón W.R.[Background] The performance of emotion recognition systems depends heavily on datasets used in their training, validation, or testing stages. [Aims] This research aims to evaluate the extent to which public available physiological datasets created for emotion recognition systems meet a set of reference requirements. [Method] Firstly, we analyze the applicability of some reference requirements proposed for stress datasets and adjust the corresponding evaluation criteria. Secondly, nine public physiological datasets were identified from a previous survey. [Results] None of the evaluated datasets satisfy all the reference requirements in order to be considered as a reference dataset for being used in the construction of reliable emotion recognition systems. [Conclusion] Although the evaluated datasets do not support the whole reference requirements, they provide a baseline for further development. Also, a greater effort is needed to establish specific reference requirements that can appropriately guide the creation of physiological datasets for emotion recognition systems. © 2021, Springer Nature Switzerland AG. -
PublicaciónAn improved 1D diode model for the accurate modeling of parasitics in silicon modulators(SPIE, 2021)
;Prosopio-Galarza R.R. ;Adanaque-Infante L.A. ;Hernandez-Figueroa H.E.Rubio-Noriega R.E.Silicon modulators paved the way for silicon photonics to take control of optical interconnects. Since its popularization, most works use the 1-D diode model approximation to design the horizontal PN junction, which estimates the modulator bandwidth and efficiency. Some works do not even consider the effects of fringe capacitance, alleging that the junction's dimensions are large. The 1-D model is suitable for vertically uniform PN junctions. However, there are essential deviations for the typical rib waveguide used in most horizontal-junction silicon modulators. Our work aims to quantify such deviations incorporating details from 2D model simulations and offer a corrected 1-D model for estimating modulation bandwidth. This study was carried out as follows: Firstly, we incorporated an improved scheme for phase shifting and loss for different junction locations and widely used doping concentrations. Next, we analyzed the generation-recombination effects and their impact on the depletion width at the top and bottom of the waveguide. We calculated the depletion width via the 1-D model and the two-dimensional Poisson's equation finite-element calculation for the rib and identified an important mismatch. Lastly, we propose and demonstrate an accurate equivalent circuit with our 1-D model corrections. Our model considers the total depletion capacitance, the fringe capacitance, the capacitance due to the wider depletion widths at the top and bottom surfaces of the diode, and other capacitive effects at the border of the rib as a result of high reverse bias. We found that although the 1-D model is well-suited for small reverse biases, higher voltages and extreme junction locations affect the bandwidth's estimation dramatically. © 2021 SPIE. -
PublicaciónApplication of innovative remediation processes to mining effluents contaminated by heavy metals(EDP Sciences, 2013)
;Ubaldini S. ;Luptakova A. ;Fornari P.Yoplac E.The scope of the paper was to demonstrate the technical feasibility of the remediation processes by electrowinning and selective sequential precipitation, for toxic metals removal from acid mine drainage. By electrochemical experiments, high metals removal has been achieved: in particular, by Zn and Mn electrodeposition, it was possible to achieve about 93-99% Zn and Mn removal (as MnO2), with a relatively low energetic consumption. The principle of the heavy metals selective sequential precipitation is the combined application of sodium hydroxide solution and hydrogen sulfide produced by sulfate-reducing bacteria. For the hydrogen sulfide production the sulphate-reducing bacteria of genus Desulfovibrio was used. The selective sequential precipitation process reaches the selective precipitation of chosen metals with 99% efficiency – Fe, As, Al and Mn in the form of metal hydroxides, Cu and Zn as metal sulfides. -
PublicaciónApplication of the field system-FS9 and a PC to the antenna control unit interface in radio astronomy in Peru(Proceedings of the International Astronomical Union, 2006)
;Vidal E. ;Ishitsuka J.Koyama Y.We are in the process to transform a 32m antenna in Peru, used for telecommunications, into a Radio Telescope to perform Radio Astronomy in Peru. The 32m antenna of Peru constructed by NEC was used for telecommunications with communications satellites at 6 GHz for transmission, and 4 GHz for reception. -
PublicaciónAssessment of Sugarcane Byproducts for Energy Use in Peru(Elsevier, 2017)
;Marcelo D. ;Bizzo W. ;Alamo M.Vásquez E.The scope of this paper is to make a feasibility analysis for energy production from sugarcane byproducts in Perú. Therefore, it is shown the history, methods, current scenario and future prospects of sugarcane plantations related to the ethanol industry and the sugar industry. There will be shown analysis of harvest residues (top and leaves). Bagasse is a mill residue, produced after sugarcane juice is extracted from the sugarcane. Nowadays this residue is burnt in boilers and this energy is used to generate steam. In the other hand, harvest residues represent a significant part of the energy contained in the sugarcane, but it is left in the field, or worse; burnt before the harvest. There will also be shown an estimated value of the electricity generation potential from sugarcane residues. -
PublicaciónAssessment of Vulnerability Curves of Pircas over Slopes by the Discrete Element Method (DEM) - A Case Study in Carabayllo, Peru(American Society of Civil Engineers (ASCE), 2018)
;Zanelli C. ;Cruz S.S. ;Valderrama N.Daudon D.The increase of urban population in seismic areas and the lack of urban planning have caused the occupancy of hazardous zones around most cities in Latin America. Some dwellings in these settlements are located on terraces on steep hills supported by pircas (dry stone retaining walls). Seismic vulnerability analysis of these structures becomes a crucial step to assess the level of damage generated in possible events, and to propose alternatives for risk reduction and prevention. This analysis was conducted through a numerical model based on the discrete element method (DEM), three typologies of pircas where modelled according to a statistical analysis carried out in the case study. Damage state was defined taking into account the maximum displacement response. According to the lateral seismic acceleration in the out of plane direction, four states of damage were defined: slight, moderate, extensive, and complete. Seismic vulnerability curve represents the relationship between the structural damage of pircas and the seismic acceleration. The obtained curve showed that during frequent earthquakes pircas would be in extensive damage, while for occasional earthquakes almost all typologies of pircas would be in complete damage. -
PublicaciónAssessment of Vulnerability Curves of Pircas over Slopes by the Discrete Element Method (DEM)-A Case Study in Carabayllo, Peru(5th Geotechnical Earthquake Engineering and Soil Dynamics Conference (GEESD), 2018)
;Zanelli, C ;Santa Cruz, S ;Valderrama, NDaudon, DThe increase of urban population in seismic areas and the lack of urban planning have caused the occupancy of hazardous zones around most cities in Latin America. Some dwellings in these settlements are located on terraces on steep hills supported by pircas (dry stone retaining walls). Seismic vulnerability analysis of these structures becomes a crucial step to assess the level of damage generated in possible events, and to propose alternatives for risk reduction and prevention. This analysis was conducted through a numerical model based on the discrete element method (DEM), three typologies of pircas where modelled according to a statistical analysis carried out in the case study. Damage state was defined taking into account the maximum displacement response. According to the lateral seismic acceleration in the out of plane direction, four states of damage were defined: slight, moderate, extensive, and complete. Seismic vulnerability curve represents the relationship between the structural damage of pircas and the seismic acceleration. The obtained curve showed that during frequent earthquakes pircas would be in extensive damage, while for occasional earthquakes almost all typologies of pircas would be in complete damage. -
PublicaciónAttenuation coefficient estimation of the healthy human thyroid in vivo(Elsevier, 2015)
;Rouyer J. ;Cueva T. ;Portal A. ;Yamamoto T.Lavarello R.Previous studies have demonstrated that attenuation coefficients can be useful towards characterizing thyroid tissues. In this work, ultrasonic attenuation coefficients were estimated from healthy human thyroids in vivo using a clinical scanner. The selected subjects were five young, healthy volunteers (age: 26 ± 6 years old, gender: three females, two males) with no reported history of thyroid diseases, no palpable thyroid nodules, no smoking habits, and body mass index less than 30 kg/m2. Echographic examinations were conducted by a trained sonographer using a SonixTouch system (Ultrasonix Medical Corporation, Richmond, BC) equipped with an L14-5 linear transducer array (nominal center frequency of 10 MHz, transducer footprint of 3.8 cm). Radiofrequency data corresponding to the collected echographic images in both transverse and longitudinal views were digitized at a sampling rate of 40 MHz and processed with Matlab codes (MathWorks, Natick, MA) to estimate attenuation coefficients using the spectral log difference method. The estimation was performed using an analysis bandwidth spanning from 4.0 to 9.0 MHz. The average value of the estimated ultrasonic attenuation coefficients was equal to 1.34 ± 0.15 dB/(cm.MHz). The standard deviation of the estimated average attenuation coefficient across different volunteers suggests a non-negligible inter-subject variability in the ultrasonic attenuation coefficient of the human thyroid. -
PublicaciónCalculation of fluidization velocities and pressure drop in bubbling fluidized bed gasifier [Cálculo de las velocidades de fluidización y caída de presión en gasificador de lecho fluidizado burbujeante](Latin American and Caribbean Consortium of Engineering Institutions, 2017)
;Marcelo D. ;Bizzo W.García R.This study aims to show the methodology and results related to the calculation of fluidization velocities in a bubbling fluidized bed gasifier. The pressure drops encountered by a fluidizing agent in the particle bed are also exposed. Velocity calculation is important because it enables a good fluidization, which induces a uniform distribution of particles. The good distribution of particles causes a uniform distribution of temperatures in the gasifier where the thermochemical reactions of the process are performed. Biomass functions as a reactor fuel, and accurate fluidization provides a summarized way for correct gasification. Good calculation of pressure drop in the bed is vital for the correctly selecting a blower, a device responsible for providing the power and airflow necessary for fluidization. The bed particles are bauxite with 86% alumina with a density of 2960 kg/m3 and an average diameter of 1.5 mm, the fluidization agent is air, and shredded leaves constitute the spent fuel. -
PublicaciónCareer planning development in system engineering students(Institute of Electrical and Electronics Engineers Inc., 2018)
;Sandoval R.R.Ramos-Diaz J.it is well known that an economy based on knowledge has a strong potential for human capital. In this sense, universities have a key role in student's professional development and performance, as well as to increase the number of professional population in science, technology, engineer, and mathematics. The aim of the present study is to obtain student's individual, structural and external characteristics by considering their context, which represents a condition that shape student's interest, persistence and goals in computing engineering discipline through career development. To accomplish this, we used self-reports based on Social Cognitive Career Theory in a sample of system engineering students (n=270) from three universities in the north of Lima. In addition to this, we evaluate the model through Structural Equation Modeling (SEM) under the partial least squared (PLS-SEM) approach. Results showed different associations and effects in individual and contextual variables among system engineering students. -
PublicaciónCataclysmic variable stars: Photometry of V893 Sco star and spectroscopy of HS 0220 + 0603 star(Institute of Physics Publishing, 2018)
;Cori W.Tello J.Differential photometry was applied on V893 Sco star, observed from the Astronomical Observatory of the Universidad Nacional de Ingeniería in Peru. From its light curve it was measured an orbital period of 0.076 days approximately. Moreover, spectroscopic analysis was performed on the HS 0220 + 0603 star, which data was acquired from a database. A fitting program was written in Python to find, out of several synthetic spectra of white dwarf and templates of red dwarf, the combination of a white dwarf and a red dwarf spectrum that fits best the HS 0220 + 0603 spectrum, thus we found that this spectrum is a composition of a white dwarf spectrum of 30000 K and surface gravity (log g) = 8.0, and a M5.5 type red dwarf star. -
PublicaciónChanot: An intelligent annotation tool for indigenous and highly agglutinative languages in Peru(European Language Resources Association (ELRA), 2019)
;Mercado-Gonzales R. ;Pereira-Noriega J. ;Sobrevilla M.Oncevay A.Linguistic corpus annotation is one of the most important phases for solving Natural Language Processing (NLP) tasks, as these methods are deeply involved with corpus-based techniques. However, meta-data annotation is a highly laborious manual task. A supportive alternative requires the use of computational tools. They are likely to simplify some of these operations, while can be adjusted appropriately to the needs of particular language features at the same time. Therefore, this paper presents ChAnot, a web-based annotation tool developed for Peruvian indigenous and highly agglutinative languages, where Shipibo-Konibo was the case study. This new tool is able to support a diverse set of linguistic annotation tasks, such as word segmentation, POS-tag markup, among others. Also, it includes a suggestion engine based on historic and machine learning models, and a set of statistics about previous annotations.