Robotization Effect Using Phase Vocoder Processing

The basic principle of the robotic effect relies on the phase vocoder, which splits an input signal into bands before the processing, in order to achieve this, a representation in the frequency domain is achieved by using a window function in conjunction with the Short Time Fourier Transform. Although many robot-robot effect devices have been available during the years, none of the allowed for a wide variation of effects thanks to selection of window function, window sizes or hop sizes, which in conjunction create a vast variation in the resulting signal which then can be used for diverse purposes with great success

Satisfacción laboral en las franquicias Starbucks de la ciudad de Cusco - 2019

La presente investigación en las Franquicias Starbucks de la Ciudad del Cusco - 2019, tiene por objeto conocer la Satisfacción Laboral de los colaboradores en las Franquicias Starbucks de la Ciudad del Cusco - 2019. Metodológicamente se ha efectuado una investigación es de tipo básica, el nivel de investigación es descriptiva con diseño no experimental, y la población en estudio son los colaboradores de las Franquicias Starbucks de la Ciudad del Cusco - 2019, que fueron 34 colaboradores, la técnica de recolección de datos ha sido la encuesta con su instrumento el cuestionario, datos que han sido procesados con ayuda del programa SPSS y se presentan mediante tablas y figuras. En el marco teórico se encontraron antecedentes a nivel internacional, nacional y regional, sin embargo no se han encontrado antecedentes en el ámbito franquicias, por otro parte se determinó las bases teóricas o teorías sobre la satisfacción laboral, su importancia, medición, efectos y factores como son la frecuencia de la supervisión, el ambiente físico, la remuneración, satisfacción intrínseca y la participación, con el fin de determinar la operacionalización, identificación de variables, dimensiones e indicadores. Para el procesamiento de los datos obtenidos de fuentes primarias, se ha usado el SPSS, y para su mayor entendimiento se muestran tablas resumen, gráficos y su interpretación. La satisfacción laboral en las Franquicias Starbucks de la Ciudad del Cusco, se considera como regularmente satisfechos por parte de los colaboradores, determinado por un 2.92 de promedio. La palabra clave es Satisfacción.The present investigation in the Starbucks Franchises of the City of Cusco - 2019, aims to know the Work Satisfaction of the collaborators in the Starbucks Franchises of the City of Cusco - 2019. Methodologically an investigation has been carried out is of basic type, the level of research is descriptive with non-experimental design, and the population under study are the collaborators of the Starbucks Franchises of the City of Cusco - 2019, which were 34 collaborators, the data collection technique has been the survey with its instrument the questionnaire, data that has been processed with the help of the SPSS program and is presented using tables and figures. In the theoretical framework, antecedents at international, national and regional levels were found, however no antecedents were found in the franchise field, on the other hand the theoretical bases or theories on job satisfaction, its importance, measurement, effects and factors were determined such as the frequency of supervision, physical environment, remuneration, intrinsic satisfaction and participation, in order to determine operationalization, identification of variables, dimensions and indicators. For the processing of data obtained from primary sources, the SPSS has been used, and for its greater understanding, summary tables, graphs and their interpretation are shown. Job satisfaction at Starbucks Franchises in the City of Cusco is considered as regularly satisfied by employees, determined by an average of 2.92. The keyword is Satisfaction.Tesi

Evaluación de la huella hídrica de centros educativos localizados en los distritos de Incahuasi, Cañaris, Jayanca y Túcume, en el departamento de Lambayeque, 2020

Como bien sabemos, la humanidad no se ha independizado de la naturaleza; esto quiere decir que hemos hecho y seguiremos haciendo uso de los recursos que ella nos brinda, en el presente proyecto, nos enfocamos en el agua, un insumo tan necesario para la vida humana y las diversas actividades que realiza. Es por ello, muy importante tener cifras exactas, de qué tanto estamos usando de este recurso, para así tener una transparencia en todos los sectores y tomar propuestas íntegras en post de una sociedad mejor. En este informe académico se buscó evaluar cuánta agua es necesaria para que un grupo de personas realicen sus actividades, y el nivel de contaminación que generaron durante el año 2019, exactamente dentro de cuatro instituciones educativas ubicadas en la región Lambayeque, esto es lo que se conoce como huella hídrica (HH). Se busca que por cada centro de enseñanza se evalúe el consumo directo e indirecto del recurso hídrico, expresando los resultados en volúmenes de agua. En este proyecto se explica la metodología a usar, propuesta por la WFN. Se tuvo que ir hasta los lugares en cuestión, recopilar datos de primera mano, fórmulas propuestas en la literatura inglesa, así como datos de instituciones y organismos serios. Además, este trabajo es un proyecto innovador por lo que se exhorta a investigar más acerca de este tema que intenta explicar el gran problema hídrico, ya que en este mundo globalizado resulta ser, la HH, un instrumento importante de medición para lograr tener sociedades sostenibles.As we well know, humanity has not become independent from nature; This means that we have made and will continue to make use of the resources that it provides us. In this project, we focus on water, an input that is so necessary for human life and the various activities that it carries out. That is why it is very important to have exact figures, of how much we are using this resource, in order to have transparency in all sectors and take full proposals in post for a better society. This academic report seeks to assess how much water is necessary for a group of people to carry out their activities, and the level of pollution they generate during the year 2019, exactly within four educational institutions located in the Lambayeque region, this is what is known as the water footprint (WF). The aim is for each school to evaluate the direct and indirect consumption of water resources, expressing the results in volumes of water. This project explains the methodology to be used, proposed by the WFN. It was necessary to go to the places in question, collect first-hand data, formulas proposed in the English literature, as well as data from serious institutions and organizations. In addition, this work is an innovative project, so it is encouraged to investigate more about this topic that tries to explain the great water problem, since in this globalized world it turns out to be, the HH, an important instrument of measurement to achieve sustainable societies

A Deep Learning based Fast Signed Distance Map Generation

Signed distance map (SDM) is a common representation of surfaces in medical image analysis and machine learning. The computational complexity of SDM for 3D parametric shapes is often a bottleneck in many applications, thus limiting their interest. In this paper, we propose a learning based SDM generation neural network which is demonstrated on a tridimensional cochlea shape model parameterized by 4 shape parameters. The proposed SDM Neural Network generates a cochlea signed distance map depending on four input parameters and we show that the deep learning approach leads to a 60 fold improvement in the time of computation compared to more classical SDM generation methods. Therefore, the proposed approach achieves a good trade-off between accuracy and efficiency

Impact of the development of bioinformatics in Cuba

Bioinformatics is the application of computer science to solve biological problems. Its application is becoming more necessary and common every day in the field of life science research. In this discipline, computational and human resources assist in the analysis of enormous amounts of biological data, to extract valuable information and obtain results with improved impacts on human, animal and plant health. This report addresses the emergence of the bioinformatics career as part of the natural cycle of the biotechnological advancement process in Cuba and the impact of its development in areas such as oncology, genetics, epidemiology and pharmacology. The exposed elements allows to understand the importance of its use, being every day more necessary and common in the field of life sciences research, despite the large investments in technology to be made. It is concluded that with the application of bioinformatics it is possible to solve a large number of current biomedical problems, which makes it a vital discipline for Cuba in its development plans and that it must play a leading role in horizon up to 2030

Gestión de inventario para mejorar la productividad en almacén de la empresa SEALERS.S. A en Ate 2022

El objetivo de la investigación es determinar que la gestión de inventario mejora la productividad en almacén de la empresa SEALERS S.A en Ate, 2022. El problema es la demoran en la atención de almacén en la entrega de los materiales, donde se implementó el modelo de la cantidad económica de pedido y la planificación de requerimiento de materiales, ayudando mejorar el nivel de cumplimiento y la optimizando del tiempo de atención. el tipo de investigación es aplicada y el tipo de diseño es pre experimental, la población de estudio es la atención de pedidos diarios que se realiza al transcurso del año 2022 en el almacén en la corporación SEALERS. S.A, nuestra técnica es el análisis de contenidos y observación, nuestro instrumento es el sotfware de la empresa que es un ERP. En el análisis inferencial se utilizó el software estadístico SPSS V24. En el análisis descriptivo se utilizó tablas de Excel antes y después. El resultado de productividad es un incremento de 27 %. Se concluyó que la gestión de inventario mejora positivamente la productividad en almacén de la empresa SEALERS S.A, porque aplicando las herramientas desarrolladas se llega aumento de la productividad

Robot Detector de Enfermedades en Cultivos de Gulupa

Se detallará el proceso de diseño y simulación de un Robot capaz de transitar a lo largo de un cultivo de gulupa detectando por medio de un algoritmo las gulupas presentes en el cultivo filtrando cada una de forma individual, además de una aplicación móvil que se comunica con el robot por medio de un servidor donde comparten las imágenes de los frutos, estas imágenes son mostradas en la aplicación dentro de una tabla que contiene información de una imagen. el diseño del robot se hizo en el software SolidWorks 2017, dicho modelo CAD fue exportado a Blender, para posteriormente ser cargado en el software de simulación GAZEBO para utilizar el framework ROS, esto con el fin de simular el movimiento del robot y desarrollar diversas pruebas de desempeño al dispositivo como el paso por obstáculos, visualización de objetos y correcto funcionamiento de los sensores. El algoritmo para la detección de frutos se basará en el uso de diversas técnicas de filtrado como convolución y watershet, utilizando las librerías para el lenguaje de programación Python: OpenCV y Numpy, para evaluar el rendimiento del algoritmo se hará con una base de datos que contiene 2090 imágenes de frutos tomadas en diversos estados de iluminación y posición del fruto. Al procesar cada imagen con el algoritmo se extraerán los falsos positivos y verdaderos positivos, con estos datos se calculará la efectividad que tuvo el algoritmo. La aplicación de dispositivo móvil se programará en el entorno de programación Android Studio y el lenguaje kotlin, dicha aplicación descargará la información almacenada en un servidor que será creado usando las funciones de apache en este será cargada una base de datos en la cual se utilizaran las herramientas MySQL y PhpMyAdmin, el desempeño de esta aplicación y servidor será medido cargando imágenes de salida del algoritmo en la base de datos y que sean visualizados en la aplicación.The design and simulation process of a robot capable of moving along a gulupa crop will be detailed, detecting by means of an algorithm the gulupas present in the crop, filtering each one individually, as well as a mobile application that communicates with the robot through a server where they share the images of the fruits, these images are shown in the application within a table that contains information about an image. The robot design was made in the SolidWorks 2017 software, said CAD model was exported to Blender, to later be loaded into the GAZEBO simulation software to use the ROS framework, this to simulate the movement of the robot and develop various tests. of performance to the device such as the passage through obstacles, visualization of objects and correct operation of the sensors. The algorithm for the detection of fruits will be based on the use of various filtering techniques such as convolution and watershet, using the libraries for the Python programming language: OpenCV and Numpy, to evaluate the performance of the algorithm it will be done with a database that contains 2090 images of fruits taken in various lighting states and position of the fruit. When processing each image with the algorithm, the false positives and true positives will be extracted, with these data the effectiveness of the algorithm will be calculated. The mobile device application will be programmed in the Android Studio programming environment and the kotlin language, said application will download the information stored on a server that will be created using the Apache functions, in which a database will be loaded in which the functions will be used. MySQL and PhpMyAdmin tools, the performance of this application and server will be measured by uploading output images of the algorithm to the database and displaying them in the application

Realistic Simulation of Electric Potential Distributions of Different Stimulation Modes in an Implanted Cochlea

International audienceSimulation of the intracochlear potentials is an important approach to study the activation of auditory nerve fibers under electrical stimulations.However, it is still unclear to which extent the simulation results are affected by precision in reproducing the exact cochlear geometry.In this study, we address to this question by comparing the actual electric potential measured from implanted human specimen with the simulationoutputs from two different parametric 3D cochlear models. One of the model is created from the default values[1] while the other is adapted to the micro-CT scan data of the implanted cochlea

In situ validation of a parametric model of electrical field distribution in an implanted cochlea

International audienceCochlear implants have been proved to be an effective treatment for patients with sensorineural hearing loss. Among all the approaches that have been developed to design better cochlear implants, 3D model-based simulation stands out due to its detailed description of the electric field which helps reveal the electrophysiological phenomena inside the cochlea. With the advances in the cochlear implant manufacturing technology, the requirement on simulation accuracy increases. Improving the simulation accuracy relies on two aspects: 1) a better geometrical description of the cochlea that is able to distinguish the subtle differences across patients; 2) a comprehensive and reliable validation of the created 3D model. In this paper, targeting at high precision simulation, we propose a parametric cochlea model which uses micro-CT images to adapt to different cochlea geometries, then demonstrate its validation process with multi-channel stimulation data measured from a implanted cochlea. Comparisons between the simulation and validation data show a good match under a variety of stimulation configurations. The results suggest that the electric field distribution is affected by the geometric characteristics of each individual cochlea. These differences can be correctly reflected by simulations based on a 3D model tuned with personalized data