Researcher in fields like Digital Systems Design based on FPGA, Embedded Systems, Open-Source Hardware, Artificial Intelligence and Biomedical Signal Processing with a major research interest in Brain-Computer Interface.
⭐ For more information visit our blog:
https://vasanza.blogspot.com/
Iot attendance system using fingerprint module AjinkyaMore29
An Internet of Things (IoT) based portable biometric
attendance system can prove to be of great value to educational institutions in
this regard as it proves to be highly efficient and secure. The cost involved in
making this system is quite less, when compared to conventional biometric
attendance system. The use of cloud computing to store the attendance records
makes all the data easy to access and retrieve as end when required by the
teachers. The use of fingerprint scanner ensures the reliability of the attendance
record.
IEEE Radio & Wireless Week IoT Powered by Wireless PresentationMark Goldstein
Mark Goldstein, President of International Research Center (http://www.researchedge.com/) presented on the next Internet wave, how the Internet of Things (IoT), will connect tens of billions of new sensors and devices in the coming years driving sustainability while transforming home, business, government, industrial, medical, transportation, and other complex ecosystems. The presentation examined how IoT will be implemented and monetized across a various application spaces, creating new business models from pervasive sensor deployments and data gathering, accompanied by new privacy and security risks. Explore IoT’s evolving wireless protocols, their pro and cons, and deployment prospects including the impact of 5G, as well as roadblocks and operational challenges, emerging standards and protocols, gateways and ecosystem integration, big data strategies, and analytic opportunities.
Iot attendance system using fingerprint module AjinkyaMore29
An Internet of Things (IoT) based portable biometric
attendance system can prove to be of great value to educational institutions in
this regard as it proves to be highly efficient and secure. The cost involved in
making this system is quite less, when compared to conventional biometric
attendance system. The use of cloud computing to store the attendance records
makes all the data easy to access and retrieve as end when required by the
teachers. The use of fingerprint scanner ensures the reliability of the attendance
record.
IEEE Radio & Wireless Week IoT Powered by Wireless PresentationMark Goldstein
Mark Goldstein, President of International Research Center (http://www.researchedge.com/) presented on the next Internet wave, how the Internet of Things (IoT), will connect tens of billions of new sensors and devices in the coming years driving sustainability while transforming home, business, government, industrial, medical, transportation, and other complex ecosystems. The presentation examined how IoT will be implemented and monetized across a various application spaces, creating new business models from pervasive sensor deployments and data gathering, accompanied by new privacy and security risks. Explore IoT’s evolving wireless protocols, their pro and cons, and deployment prospects including the impact of 5G, as well as roadblocks and operational challenges, emerging standards and protocols, gateways and ecosystem integration, big data strategies, and analytic opportunities.
Mark Goldstein, President of International Research Center gave the opening keynote address “Internet of Things – Transformative Megatrends for Sustainability” to the IEEE Conference on Technologies for Sustainability (IEEE SusTech, http://sites.ieee.org/sustech/) on October 10, 2016 in Phoenix, AZ. He explored the next Internet wave, the Internet of Things (IoT), expected to connect tens of billions of new sensors and devices in the coming years driving sustainability while transforming home, business, government, industrial, medical, transportation, and other complex ecosystems. This deck examines how IoT will be implemented and monetized creating new business models from pervasive sensor deployments and data gathering, accompanied by new privacy and security risks. Explore IoT’s roadblocks and operational challenges, emerging standards and protocols, gateway and wireless integration, and big data strategies and opportunities.
Call for Papers- Special Session: Applications of Computational Intelligence, Internet of Things and Cutting Edge Technologies
Christo Ananth, Dr.Akhatov Akmal Rustamovich, Dr.Muhtor Nasirov
Professor, Samarkand State University, Uzbekistan
12th International conference on Parallel, Distributed Computing and Applicat...ijccmsjournal
12th International conference on Parallel, Distributed Computing and Applications (IPDCA 2023) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Parallel, Distributed Computing. Original papers are invited on Algorithms and Applications, computer Networks, Cyber trust and security, Wireless networks and mobile Computing and Bioinformatics. The aim of the conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field.
This presentation was prepared to support IoT developments for post-graduation students @ IT and Telco Strategic Management. It aims to get an overview on what IoT is, its technology and market innovative applications
⭐⭐⭐⭐⭐ Device Free Indoor Localization in the 28 GHz band based on machine lea...Victor Asanza
By exploiting the received power change in a communication link produced by the presence of a human body in an otherwise empty room, this work evaluates indoor free device localization methods in the 28 GHz band using machine learning techniques. For this objective, a database is built using results from ray tracing simulations of a system comprised of 4 receivers and up to 2 transmitters, while a person is standing within the room. Transmitters are equipped with uniform linear arrays that switch their main beams sequentially at 21 angles, whereas the receivers operate with omnidirectional antennas. Statistical localization error reduction of at least 16% over a global-based classification technique can be obtained through the combination of two independent classifiers using one transmitter and a reduction of at least 19% for 2 transmitters. An additional improvement is achieved by combining each independent classifier with a regression algorithm. Results also suggest that the number of examples per class and size of the blocks (strips) in which the study area is partitioned play a role in the localization error.
La siguiente partición funcional que incluye una Maquina Secuencial Sincrónica (MSS) y tres registros de sostenimiento, debe realizar el ingreso de datos a cada uno de los registros y luego permitirá encontrar el valor máximo y mínimo ingresado. Además, cada uno de los registros indicados es de 8 bits para mostrar los valores encontrados de máximo (Qmax) y mínimo (Qmin) serán de 8 bits cada uno. El sistema digital funciona con una MSS modelo Moore de la siguiente forma:
1. La MSS luego de ser reiniciado empieza en el estado inicial.
2. El Sistema Digital en el estado inicial, esperará que el usuario presione y suelte la tecla Start dos veces, luego de lo cual esperará el ingreso de datos.
3. El ingreso de datos se lo hará presentando un byte en la entrada Datos, presionando y soltando la tecla Load (el usuario deberá realizar este paso tres veces, uno por cada registro).
4. Luego de ingresar los 3 datos, el usuario deberá presionar y soltar la tecla Find. Esta señal es la que le indica a la MSS del Sistema Digital, que es momento de realizar la búsqueda del valor máximo y mínimo.
5. Una vez finalizado el proceso de búsqueda de los valores máximo y mínimo, se activará la salida Done. El valor máximo se guardará en el RegistroMax y se presentará en su salida Qmax, por otro lado, el valor mínimo se guardará en el RegistroMin y se presentará en su salida Qmin.
6. La señal Done, las salidas Qmax y Qmin se presentarán hasta que el usuario presione y suelte la tecla Start una vez, luego de lo cual la MSS regresará al estado inicial.
Mark Goldstein, President of International Research Center gave the opening keynote address “Internet of Things – Transformative Megatrends for Sustainability” to the IEEE Conference on Technologies for Sustainability (IEEE SusTech, http://sites.ieee.org/sustech/) on October 10, 2016 in Phoenix, AZ. He explored the next Internet wave, the Internet of Things (IoT), expected to connect tens of billions of new sensors and devices in the coming years driving sustainability while transforming home, business, government, industrial, medical, transportation, and other complex ecosystems. This deck examines how IoT will be implemented and monetized creating new business models from pervasive sensor deployments and data gathering, accompanied by new privacy and security risks. Explore IoT’s roadblocks and operational challenges, emerging standards and protocols, gateway and wireless integration, and big data strategies and opportunities.
Call for Papers- Special Session: Applications of Computational Intelligence, Internet of Things and Cutting Edge Technologies
Christo Ananth, Dr.Akhatov Akmal Rustamovich, Dr.Muhtor Nasirov
Professor, Samarkand State University, Uzbekistan
12th International conference on Parallel, Distributed Computing and Applicat...ijccmsjournal
12th International conference on Parallel, Distributed Computing and Applications (IPDCA 2023) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Parallel, Distributed Computing. Original papers are invited on Algorithms and Applications, computer Networks, Cyber trust and security, Wireless networks and mobile Computing and Bioinformatics. The aim of the conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field.
This presentation was prepared to support IoT developments for post-graduation students @ IT and Telco Strategic Management. It aims to get an overview on what IoT is, its technology and market innovative applications
⭐⭐⭐⭐⭐ Device Free Indoor Localization in the 28 GHz band based on machine lea...Victor Asanza
By exploiting the received power change in a communication link produced by the presence of a human body in an otherwise empty room, this work evaluates indoor free device localization methods in the 28 GHz band using machine learning techniques. For this objective, a database is built using results from ray tracing simulations of a system comprised of 4 receivers and up to 2 transmitters, while a person is standing within the room. Transmitters are equipped with uniform linear arrays that switch their main beams sequentially at 21 angles, whereas the receivers operate with omnidirectional antennas. Statistical localization error reduction of at least 16% over a global-based classification technique can be obtained through the combination of two independent classifiers using one transmitter and a reduction of at least 19% for 2 transmitters. An additional improvement is achieved by combining each independent classifier with a regression algorithm. Results also suggest that the number of examples per class and size of the blocks (strips) in which the study area is partitioned play a role in the localization error.
La siguiente partición funcional que incluye una Maquina Secuencial Sincrónica (MSS) y tres registros de sostenimiento, debe realizar el ingreso de datos a cada uno de los registros y luego permitirá encontrar el valor máximo y mínimo ingresado. Además, cada uno de los registros indicados es de 8 bits para mostrar los valores encontrados de máximo (Qmax) y mínimo (Qmin) serán de 8 bits cada uno. El sistema digital funciona con una MSS modelo Moore de la siguiente forma:
1. La MSS luego de ser reiniciado empieza en el estado inicial.
2. El Sistema Digital en el estado inicial, esperará que el usuario presione y suelte la tecla Start dos veces, luego de lo cual esperará el ingreso de datos.
3. El ingreso de datos se lo hará presentando un byte en la entrada Datos, presionando y soltando la tecla Load (el usuario deberá realizar este paso tres veces, uno por cada registro).
4. Luego de ingresar los 3 datos, el usuario deberá presionar y soltar la tecla Find. Esta señal es la que le indica a la MSS del Sistema Digital, que es momento de realizar la búsqueda del valor máximo y mínimo.
5. Una vez finalizado el proceso de búsqueda de los valores máximo y mínimo, se activará la salida Done. El valor máximo se guardará en el RegistroMax y se presentará en su salida Qmax, por otro lado, el valor mínimo se guardará en el RegistroMin y se presentará en su salida Qmin.
6. La señal Done, las salidas Qmax y Qmin se presentarán hasta que el usuario presione y suelte la tecla Start una vez, luego de lo cual la MSS regresará al estado inicial.
⭐⭐⭐⭐⭐ Trilateration-based Indoor Location using Supervised Learning AlgorithmsVictor Asanza
The indoor positioning system (IPS) has a wide range of applications, due to the advantages it has over Global Positioning Systems (GPS) in indoor environments. Due to the biosecurity measures established by the World Health Organization (WHO), where the social distancing is provided, being stricter in indoor environments. This work proposes the design of a positioning system based on trilateration. The main objective is to predict the positioning in both the ‘x’ and ‘y’ axis in an area of 8 square meters. For this purpose, 3 Access Points (AP) and a Mobile Device (DM), which works as a raster, have been used. The Received Signal Strength Indication (RSSI) values measured at each AP are the variables used in regression algorithms that predict the x and y position. In this work, 24 regression algorithms have been evaluated, of which the lowest errors obtained are 70.322 [cm] and 30.1508 [cm], for the x and y axes, respectively.
Published in: 2022 International Conference on Applied Electronics (AE)
⭐ For more information visit our blog:
https://vasanza.blogspot.com/
⭐⭐⭐⭐⭐ Learning-based Energy Consumption PredictionVictor Asanza
✅ Published in: https://doi.org/10.1016/j.procs.2022.07.035
As more people send information to the cloud-fog infrastructure, this brings many problems to the management of computer energy consumption. Therefore, energy consumption management of servers, fog devices and cloud computing platform should be investigated to comply with the Green IT requirement. In this paper, we propose an energy consumption prediction model consisting of several components such as hardware design, data pre-processing, characteristics extraction and selection. Our main goal is to develop a non-invasive meter based on a network of sensors that includes a microcontroller, the MQTT communication protocol and the energy measurement module. This meter measures voltage, current, power, frequency, energy and power factor while a dashboard is used to present the energy measurements in real-time. In particular, we perform measurements using a workstation that has similar characteristics to the servers of a Datacenter locate at the Information Technology Center in ESPOL,
which currently provide this type of services in Ecuador. For convenience, we evaluated different linear regression models to select the best one and to predict future energy consumption based on the several measurements from the workstation during several hours which enables the consumer to optimize and to reduce the maintenance costs of the IT equipment. The supervised machine learning algorithms presented in this work allow us to predict the energy consumption by hours and by days.
⭐ The matlab code used for data processing are available in: https://github.com/vasanza/Matlab_Code/tree/EnergyConsumptionPredictionDatacenter
⭐ The dataset used for data processing are available in:https://ieee-dataport.org/open-access/data-server-energy-consumption-dataset
✅ Read more related topics:
https://vasanza.blogspot.com/
This project analyses the optimal parameters for the shrimp farming, trying to help the aquaculture of Ecuador, using a cyberphysical system, which includes temperature, salinity, dissolved oxygen, and pH sensors to monitor the water conditions and an embedded system to control it using an XBee andATMega328p microcontrollers to remotely activate and deactivate aerators to maintain the quality of each pool in neat conditions.
⭐⭐⭐⭐⭐Classification of Subjects with Parkinson's Disease using Finger Tapping...Victor Asanza
La enfermedad de Parkinson es el segundo trastorno neurodegenerativo más común y afecta a más de 7 millones de personas en todo el mundo. En este trabajo, clasificamos a los sujetos con la enfermedad de Parkinson utilizando datos de la pulsación de los dedos en un teclado. Utilizamos una base de datos gratuita de Physionet con más de 9 millones de registros, preprocesada para eliminar los datos atípicos. En la etapa de extracción de características, obtuvimos 48 características. Utilizamos Google Colaboratory para entrenar, validar y probar nueve algoritmos de aprendizaje supervisado que detectan la enfermedad. Como resultado, conseguimos un grado de precisión superior al 98 %.
Examen 1er parcial que incluye temas de los capítulos:
Capítulo 1, historia de los sistemas IoT y sistemas ciberfísicos.
Capítulo 2, tipos de arquitecturas incluyendo las multiprocessor y multicore.
Capítulo 3, donde se estudia las memorias FLASH, RAM, EEPROM.
Capítulo 4, registros de configuraciones del ADC, PWM, comunicacion serial, I2C y SPI.
⭐ For more information visit our blog:
https://vasanza.blogspot.com/
⭐⭐⭐⭐⭐ CHARLA #PUCESE Arduino Week: Hardware de Código Abierto TSC-LAB Victor Asanza
✅ #PUCESE, organizó el webinar: "ARDUINO WEEK 2022 PUCESE"
✅ Arduino Week PUCE Esmeraldas- Charla con Expertos
➡️ This is an initiative developed by FIEC-ESPOL professors. Temperature and Speed Control Lab (TSC-LAB) is an open-source hardware development.
➡️ Topics
1- Introducción
2- Hardware de Código Abierto
3- Temperature and Speed Control Lab (TSC-LAB)
4- Códigos de ejemplo
5- Datasets
6- Publicaciones científicas
7- Proyectos
8- Cursos
⭐ Para más contenido visita nuestro blog:
https://vasanza.blogspot.com/
⭐⭐⭐⭐⭐ #BCI System using a Novel Processing Technique Based on Electrodes Sele...Victor Asanza
This work proposes an end-to-end model architecture, from feature extraction to classification using an Artificial Neural Network. The feature extraction process starts from an initial set of signals acquired by electrodes of a Brain-Computer Interface (BCI). The proposed architecture includes the design and implementation of a functional six Degree-of-Freedom (DOF) prosthetic hand. A Field Programmable Gate Array (FPGA) translates electroencephalography (EEG) signals into movements in the prosthesis. We also propose a new technique for selecting and grouping electrodes, which is related to the motor intentions of the subject. We analyzed and predicted two imaginary motor-intention tasks: opening and closing both fists and flexing and extending both feet. The model implemented with the proposed architecture showed an accuracy of 93.7% and a classification time of 8.8y«s for the FPGA. These results present the feasibility to carry out BCI using machine learning techniques implemented in a FPGA card.
⭐ For more information visit our blog:
https://vasanza.blogspot.com/
⭐⭐⭐⭐⭐ SOLUCIÓN EVALUACIÓN FUNDAMENTOS DE ELECTRICIDAD Y SISTEMAS DIGITALES, 2...Victor Asanza
Problema 1A: (10%) Dado la siguiente expresión booleana que define el comportamiento de la señal de salida F sin minimizar, reducir dicha expresión usando mapas de Karnaugh (A, B, C, D) agrupando unos. Luego, seleccionar cuál de las siguientes opciones es la correcta.
Problema 2: (10%) Dado la siguiente expresión booleana que define el comportamiento de la señal de salida F sin minimizar, reducir dicha expresión usando mapas de Karnaugh (A, B, C, D) agrupando unos. Luego, seleccionar cuál de las siguientes opciones es la correcta.
Problema 3: (25%) Se desea diseñar un Sistemas Digital que capaz de controlar dos actuadores tipo bomba (A y B) en función del nivel de agua presente en un tanque. Este nivel de agua se monitorea con dos sensores (S0 y S1). El Sistemas Digital se muestra en la siguiente gráfica.
Problema 5: (15%): Dado el siguiente circuito digital, primero obtener la expresión resultante y luego seleccionar el mapa que corresponde al funcionamiento de dicha expresión.
Problema 6: (15%): Dado el siguiente circuito, encontrar la expresión booleana que define el comportamiento de la señal de salida F sin minimizar, luego reducir la expresión booleana usando mapas de Karnaugh (A, B, C, D) agrupando unos.
Problema 7: (20%). En la siguiente gráfica se puede observar el registro de un electrodo de Electromiografía (EMG) durante la ejecución de una tarea motora en extremidad superior. La señal EMG tiene una amplitud en el orden de los microvoltio - milivoltios y es susceptible a ruido debido a la adherencia del electrodo utilizado, frecuencia cardiaca, red eléctrica, tejido adiposo, etc. Como se muestra en la Fig. 1 el análisis post adquisición en el dominio de la frecuencia de la señal EMG indica que existe ruido de baja frecuencia menores a 5Hz debido a ruidos relacionados a movimientos relativos y en 50 Hz debido a la red eléctrica. Las señales EMG tienen información en el rango de 7 a 20Hz, por lo cual se sugiere diseñar un filtro RC paso banda que permita eliminar el ruido de la señal EMG.
⭐ For more information visit our blog:
https://vasanza.blogspot.com/
Problema #1 (50%) Dado el siguiente diagrama de un microprocesador genérico de 32 bits por instrucción de hasta 1023 instrucciones visto completamente en clase, que utiliza datos almacenados en memoria RAM (Register Files), como se muestra a continuación.
Problema #2: (10%) ¿Cuáles de las siguientes afirmaciones referentes a las memorias de Instrucciones de un microprocesador son ciertas?
Problema #3: (10%) ¿Cuáles de las siguientes afirmaciones referentes a las memorias EEPROM son ciertas?
Problema #4: (10%) ¿Cuáles de las siguientes afirmaciones referentes a las memorias de datos (Register File) son ciertas?
Problema #5: (20%) Shen et Al., escribió el paper titulado “An FPGA-based Distributed Computing System with Power and Thermal Management Capabilities” en donde desarrolla una plataforma computacional distribuida compuesta de múltiples FPGAs conectadas via Ethernet y cada FPGA está configurada como un sistema multi-core. Los núcleos en el mismo FPGA se comunican a través de la memoria compartida, mientras que diferentes FPGA se comunican a través de enlaces Ethernet, como se muestra en la siguiente gráfica.
⭐ For more information visit our blog:
https://vasanza.blogspot.com/
⭐⭐⭐⭐⭐ Performance Comparison of Database Server based on #SoC #FPGA and #ARM ...Victor Asanza
New emerging storage technologies have a great application for IoT systems. Running database servers on development boards, such as Raspberry or FPGA, has a great impact on effective performance when using large amounts of data while serving requests from many clients at the same time. In this paper, we designed and implemented an embedded system to monitor the access of a database using MySql database server installed on Linux in a standard FPGA DE10 with HPS resources. The database is designed to keep the information of an IoT system in charge of monitoring and controlling the temperature inside greenhouses. For comparison purposes, we carried out a performance analysis of the database service running on the FPGA and in a Raspberry Pi 4 B to determine the efficiency of the database server in both development cards. The performance metrics analyzed were response time, memory and CPU usage taking into account scenarios with one or more requests from clients simultaneously.
⭐ For more information visit our blog:
https://vasanza.blogspot.com/
La siguiente partición funcional que incluye una Maquina Secuencial Sincrónica (MSS) y tres registros de sostenimiento, debe realizar el ingreso de datos a cada uno de los registros y luego permitirá encontrar el valor máximo y mínimo ingresado. Además, cada uno de los registros indicados es de 8 bits para mostrar los valores encontrados de máximo (Qmax) y mínimo (Qmin) serán de 8 bits cada uno. El sistema digital funciona con una MSS modelo Moore de la siguiente forma:
1. La MSS luego de ser reiniciado empieza en el estado inicial.
2. El Sistema Digital en el estado inicial, esperará que el usuario presione y suelte la tecla Start dos veces, luego de lo cual esperará el ingreso de datos.
3. El ingreso de datos se lo hará presentando un byte en la entrada Datos, presionando y soltando la tecla Load (el usuario deberá realizar este paso tres veces, uno por cada registro).
4. Luego de ingresar los 3 datos, el usuario deberá presionar y soltar la tecla Find. Esta señal es la que le indica a la MSS del Sistema Digital, que es momento de realizar la búsqueda del valor máximo y mínimo.
5. Una vez finalizado el proceso de búsqueda de los valores máximo y mínimo, se activará la salida Done. El valor máximo se guardará en el RegistroMax y se presentará en su salida Qmax, por otro lado, el valor mínimo se guardará en el RegistroMin y se presentará en su salida Qmin.
6. La señal Done, las salidas Qmax y Qmin se presentarán hasta que el usuario presione y suelte la tecla Start una vez, luego de lo cual la MSS regresará al estado inicial.
⭐ For more information visit our blog:
https://vasanza.blogspot.com/
⭐⭐⭐⭐⭐ Charla FIEC: #SSVEP_EEG Signal Classification based on #Emotiv EPOC #BC...Victor Asanza
Este trabajo presenta el diseño experimental para el registro de señales de electroencefalografía (EEG) en 20 sujetos sometidos a potenciales evocados visualmente en estado estable (SSVEP). Además, la implementación de un sistema de clasificación basado en las señales SSVEP-EEG de la región occipital del cerebro obtenidas con el dispositivo Emotiv EPOC.
⭐ For more information visit our blog:
https://vasanza.blogspot.com/
⭐⭐⭐⭐⭐ #FPGA Based Meteorological Monitoring StationVictor Asanza
In this paper, we propose to implement a meteorological monitoring station using embedded systems. This model is possible thanks to different sensors that enable us to measure several environmental parameters, such as i) relative humidity, ii) average ambient temperature, iii) soil humidity, iv) rain occurrence, and v) light intensity. The proposed system is based on a field-programmable gate array device (FPGA). The proposed design aims at ensuring highresolution data acquisition and at predicting samples with precision and accuracy in real-time. To present the collected data, we develop also a web application with a simple and friendly user interface.
⭐ For more information visit our blog:
https://vasanza.blogspot.com/
⭐⭐⭐⭐⭐ SSVEP-EEG Signal Classification based on Emotiv EPOC BCI and Raspberry PiVictor Asanza
This work presents the experimental design for recording Electroencephalography (EEG) signals in 20 test subjects submitted to Steady-state visually evoked potential (SSVEP). The stimuli were performed with frequencies of 7, 9, 11 and 13 Hz. Furthermore, the implementation of a classification system based on SSVEP-EEG signals from the occipital region of the brain obtained with the Emotiv EPOC device is presented. These data were used to train algorithms based on artificial intelligence in a Raspberry Pi 4 Model B. Finally, this work demonstrates the possibility of classifying with times of up to 1.8 ms in embedded systems with low computational capacity.
⭐ For more information visit our blog:
https://vasanza.blogspot.com/
⭐⭐⭐⭐⭐ SOLUCIÓN LECCIÓN FUNDAMENTOS DE ELECTRICIDAD Y SISTEMAS DIGITALES, 2do ...Victor Asanza
Problema #1,2,3: (10%) El siguiente circuito es de un filtro paso banda. Los datos del circuito son los siguientes, R1 = 1K[Ω] y R2 = 1K[Ω]. ¿cuáles de las siguientes afirmaciones son correctas?
Problema #4,5,6: (10%) El siguiente bloque convertidor analógico digital (ADC) de 8 bits de resolución, se tiene un voltaje de referencia de 5Vcc. ¿cuáles de las siguientes afirmaciones son correctas?
⭐ For more information visit our blog:
https://vasanza.blogspot.com/
Problema #1 (x%). El siguiente es un Sistema Digital que tiene las señales ‘A’,’ B’, ‘C’ y ‘D’ como entradas de un bit; por otro lado, la señal ‘Y’ es una salida de un bit tal como se muestra en la siguiente imagen:
El comportamiento de la señal de salida ‘Y’ en función de las señales de entrada, es descrito con el siguiente código VHDL:
Código GitHub:
https://github.com/vasanza/MSI-VHDL/blob/2021PAO1/ExamenParcial/ExamSD1_1.vhd
Realizar los siguientes desarrollos:
a) Usando mapas de karnaught y agrupamiento de minterms (SOP), simplificar la expresión booleana hasta obtener su minima expresión (x/2 %).
b) Utilizando puertas lógicas, graficar el circuito que represente a la ecuación simplificada en el literal anterior (x/2 %).
Problema #2 (x%). El siguiente es un Sistema Digital que tiene las señales ‘A’ y ‘B’ como entradas de dos bits; por otro lado, la señal ‘Y’ es una salida de dos bits tal como se muestra en la siguiente imagen:
El comportamiento de la señal de salida ‘Y’ en función de las señales de entrada, es descrito con el siguiente código VHDL:
Código GitHub:
https://github.com/vasanza/MSI-VHDL/blob/2021PAO1/ExamenParcial/ExamSD1_2.vhd
Realizar los siguientes desarrollos:
a) Usando mapas de karnaught y agrupamiento de minterms (SOP), simplificar la expresión booleana hasta obtener su minima expresión de Y(1) = f(A(1),A(0),B(1),B(0)) y Y(0) = f(A(1),A(0),B(1),B(0)) (x/2 %).
b) Indicar con sus propias palabras el funcioamiento que realiza el sistemas digital propuesto (x/2 %).
⭐ For more information visit our blog:
https://vasanza.blogspot.com/
Propuesta 1: BÚSQUEDA DE DATOS
Propuesta 2-3: ORDENAMIENTO DE DATOS
Propuesta 4: Microprocessor Architecture.
⭐ For more information visit our blog:
https://vasanza.blogspot.com/
Proyectos propuestos basados en MSS:
VALOR MÍNIMO DE 3 NÚMEROS
VALOR MÁXIMO DE 3 NÚMEROS
VALOR PROMEDIO DE 4 NÚMEROS
CONTADOR UP EN GRAY
CONTADOR DOWN EN BCD
VALIDADOR DE CLAVE DE 3 DIGITOS
SUMADOR DE 3 NUMEROS BCD
VALIDADOR DE 3 NÚMEROS ASCENDENTES
VALIDADOR DE 3 NÚMEROS DESCENDENTE
VALIDADOR DE 3 NÚMEROS MULTIPLOS DE BASE 2
⭐ For more information visit our blog:
https://vasanza.blogspot.com/
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
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Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
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Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
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2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
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Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
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Macroeconomics- Movie Location
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Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
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⭐⭐⭐⭐⭐ CV Victor Asanza
1. Vı́ctor Manuel Asanza Armijos, Ph.D.
Last updated: January 28, 2023
Personal data
Name: Vı́ctor Manuel Asanza Armijos
Date of Birth: May 30, 1986. (Balsas - El Oro, Ecuador)
Nationality: Ecuadorian
Civil status: Married
Work address: ESPOL - Ecuador.
Km. 30.5 vı́a Perimetral,
Campus Gustavo Galindo
Guayaquil, Ecuador
E-mail: vasanza@gmail.com
Scopus ID: 57192640451
Personal Web Site: https://vasanza.blogspot.com
GitHub: https://github.com/vasanza
LinkedIn: https://www.linkedin.com/in/vasanza/
ORCID ID: https://orcid.org/0000-0002-2786-4162
Biography
Researcher in fields like Digital Systems Design based on FPGA, Open-Source Processor, Open-
Source Hardware, Edge Computing, Artificial Intelligence and Human-Machine Interaction with a
major research interest in Brain-Computer Interface. He was graduated as Electronic and Telecom-
munications Engineering on 2010 (ESPOL, Ecuador). He was graduated as master in Automation
and Industrial Control on 2013 and was graduated as Ph.D. in Applied Computer Science on 2022
(ESPOL, Ecuador). Currently, He is work as Professor of Electronic’s Department since 2012 at
Escuela Superior Politécnica del Litoral.
Education
2022: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ph.D. in Applied Computer Science.
Facultad de Ingenierı́a en Electricidad y Computación.
Escuela Superior Politécnica del Litoral (ESPOL) – Guayaquil.
Thesis topic:
EEG Signal Processing for Motor Intention of Lower Limbs Detection in Subjects with Cerebral
Palsy.
Thesis objectives:
Define the experiment method to be carried out in Guayaquil with the help of the Hospital Luis
Vernaza.
Thesis Goals:
1. Define the experiment method to be carried out in Guayaquil with the help of the Hospital
Luis Vernaza.
2. Use deep learning techniques in post-acquisition data.
3. Evaluate the classification algorithms.
Available from: https://www.dspace.espol.edu.ec/handle/123456789/56048
2. Vı́ctor Asanza Armijos Ph.D. in Applied Computer Science 2
2013: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Master in Automation and Industrial Control.
Facultad de Ingenierı́a en Electricidad y Computación.
Escuela Superior Politécnica del Litoral (ESPOL) – Guayaquil.
Thesis topic:
Design and implementation of a pilot plant as a didactic tool for acquisition and control.
Thesis Goals:
1. Instrumentation and signal acquisition for subsequent storage.
2. Signal processing ofline for identification of SISO and MIMO systems.
3. Design of PID and fuzzy logic controllers in embedded systems.
2010: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Electronic and Telecomunication Engineer.
Facultad de Ingenierı́a en Electricidad y Computación.
Escuela Superior Politécnica del Litoral (ESPOL) – Guayaquil.
Thesis topic:
Security System for a Laboratory.
Thesis Goals:
1. Development of hardware based on microcontrollers.
2. Image recognition using LabView.
3. Remote monitoring and control.
Certifications
2022:
[1]. Certified Interconnect Designer (CID) in the IPC (IPC-2220, IPC-2221, IPC-2222) Designer
certification program. Institute of Printed Circuits (IPC), https://www.ipc.org. Bannock-
burn, Illinois, United States. August 2022. Serial No.: CID-22082681126.
Available from: https://my.ipcedge.org/static/verify_certification.html.
[2]. Certified IPC Specialist (CIS) in the industry developed and approved IPC-A-610 (Acceptabil-
ity of Electronic Assemblies) Training and Certification Program. Institute of Printed Circuits
(IPC), https://www.ipc.org. Bannockburn, Illinois, United States. August 2022. Serial
No.: CIS-A610SH-22102751579.
Available from: https://my.ipcedge.org/static/verify_certification.html.
Microcontroller and Microprocessor Experience
1. Microcontroller: AVR, STM, Nordic, ARM Cortex-M, ESP32, RISC-V.
2. Soft-processor: RISC-V, NIOS II, MicroBlaze on Field Programmable Gate Array (FPGA).
3. Microprocessor: ARM Cortex-A, Intel 8085.
4. Protocols: MQTT, HTTP. Available from: https://tsc-lab.blogspot.com/2021/10/
practice-14-thingspeak-http.html.
5. Interface: I2C, SPI, RS232, RS485, OneWire. Available from: https://tsc-lab.blogspot.
com/p/summary.html.
6. RTOS: FreeRTOS, TinyOS, RT-Thread.
Available from: https://github.com/DanielMontoyaS/Prosthesis-Control.
7. OTA: for updating microcontroller firmware using IOTAppStory. Available from: https:
//tsc-lab.blogspot.com/2022/06/practice-26-ota.html.
8. Code debugging: SW and HW debugging.
3. Vı́ctor Asanza Armijos Ph.D. in Applied Computer Science 3
Software and IoT Platforms Experience
1. Github: for code version control. Available from: https://github.com/vasanza.
2. Visual Studio Code (VS Code): for the programming of microcontrollers and micropro-
cessors. Available from: https://github.com/Embedded-Systems-Architecture.
3. Anaconda and Jupiter Notebook: for Raspberry phyton programming. Available from:
https://github.com/Human-Machine-Interface.
4. Proteus: for microcontroller simulation.
5. MPLAB: for programming MicroChip microcontrollers.
6. SMT32 IDE: for programming STM microcontrollers. Available from: https://github.
com/Human-Machine-Interface/Prosthesis-Control
7. Eclipse IDE + ESP-IDF: to program the ESP32.
8. Docker: for microservices between software and hardware.
9. Quartus: for programming Intel FPGAs. Available from: https://github.com/vasanza/
MSI-VHDL.
10. Vivado: for programming AMD FPGAs. Available from: https://opencores.org/projects/
ecriscv.
11. Influxdb, NodeRed, ThigSpeak and Ubidots: as IoT platform using HTTP and MQTT
protocols. Available from: https://github.com/TSC-LAB.
12. FireBase: for cloud data storage using HTTP protocols. Available from: https://github.
com/TSC-LAB.
13. Matlab: for simulations, Artificial Intelligence, modeling, connections to Microcontrollers or
Microprocessors. Available from: https://github.com/vasanza/Matlab_Code.
14. Labview: for virtualizations, connections with Microcontrollers or Microprocessors. Available
from: https://github.com/vasanza/Labview_Code.
15. Altium Designer: for Printed Circuit Boards (PCB) design.
16. Circuit Maker: for Printed Circuit Boards (PCB) design. Available from: https://
circuitmaker.com/User/Details/vasanza.
Open-Source Hardware
[1]. Open Source Hardware Association (OSHWA): Vı́ctor Asanza, Kevin Chica-Orellana, Jonathan
Cagua, Douglas Plaza, César Martı́n, Diego Hernan Peluffo-Ordóñez. (July 15, 2021). Tempera-
ture and Speed Control Lab (TSC-Lab). OSHWA UID: EC000003.
Available from: https://certification.oshwa.org/ec000003.html
[2]. Open Source Hardware Association (OSHWA): Adrian Bazurto, Vı́ctor Asanza, Ronald Reyes,
Douglas Plaza, Diego Hernan Peluffo-Ordóñez. (December 01, 2021). 2 Phase Energy Meter 100A
(2PEM-100A). OSHWA UID: EC000004.
Available from: https://certification.oshwa.org/ec000004.html
Open-Source Processor
[1]. Open Source gateware IP cores (OpenCores): Guillermo Montesdeoca, Vı́ctor Asanza. (Aug
19, 2022). Reduced Instruction Set Computer V - Ecuador (RISCV-EC). OpenCore ID: ECRISCV.
Available from: https://opencores.org/projects/ecriscv
4. Vı́ctor Asanza Armijos Ph.D. in Applied Computer Science 4
Industry Experience
2015 - 2018 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ELECTROAVILES - Ecuador.
Supervisor of the design team, manufacturing and assembly of Printed Circuit Boards (PCB).
Supervisor of the firmware developer team for embedded systems in C/C++ and VHDL language.
Available from: http://www.electroaviles.com.ec/.
2013 - 2014 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ESPOL & INOCAR & IRD-France.
Research project with Institut de Recherche pour le Développement (IRD-France) with Instituto
Oceanográfico de la Armada (INOCAR) and FICT. Escuela Superior Politécnica del Litoral (ES-
POL).
2010 - 2015 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . SERDECOM CIA. LTDA. - Perú / Ecuador.
C/C++ firmware developer. Printed Circuit Board (PCB) design, manufacturing and assembly
consultant. Available from: https://www.serdecom.com/.
2005 - 2010 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IDETEC CIA. LTDA. - Ecuador.
Senior firmware programmer for embedded systems in C language, consultant in control and au-
tomation processes.
Teaching Experience
2012 - Today . . . . . . . . . . . . . . . . . . . . . . . . . Escuela Superior Politécnica del Litoral (ESPOL) - Ecuador.
Subjects: Electronic Prototypes Design, Embedded Systems, Embedded Systems Laboratory, Fun-
damentals of Electricity and Digital Systems, Digital Systems 1, Digital Systems 1 Laboratory,
Digital Systems 2, Digital Systems Design, Digital Systems Design Laboratory, Microcontrollers
Laboratory and Electrical Networks 1. Sub Decano: Cesar Martı́n. Phone: +593(4)2269-860.
2012: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Universidad Politécnica Salesiana (UPS) - Ecuador.
Subjects: Digital Systems 1, Electrical engineering 1, electronic circuits 1 and Electrical Networks.
Phone: +593 (4)259-0630.
Research Experience
2022:
[1]. Multidisciplinary research project, ”Preprocesamiento, extracción de caracterı́sticas y predicción
de consumo de energı́a en tiempo real basada en Inteligencia Artificial en el borde o en la
niebla”. Escuela Superior Politécnica del Litoral (ESPOL). Duration: 2022 - 2023. (Research
Code CTI-7-2022). Available from:
http://www.espol.edu.ec/es/investigacion/lg/proyectos-en-ejecucion
[2]. Multidisciplinary research project, ”Modelo de predicción de la degradación de la señal de la
red inalámbrica publica basado en parámetros de calidad de servicio y calidad de experiencia
del usuario”. Escuela Superior Politécnica del Litoral (ESPOL). Duration: 2022 - 2023.
(Research Code CTI-10-2022). Available from:
http://www.espol.edu.ec/es/investigacion/lg/proyectos-en-ejecucion
[3]. Multidisciplinary research project, ”Diseño de intervenciones comportamentales de actividad
fı́sica basadas en modelos dinámicos y técnicas de ingeniera de control aplicables a entornos
transculturales”. Escuela Superior Politécnica del Litoral (ESPOL). Duration: 2022 - 2023.
(Research Code FIEC-13-2022). Available from:
http://www.espol.edu.ec/es/investigacion/lg/proyectos-en-ejecucion
5. Vı́ctor Asanza Armijos Ph.D. in Applied Computer Science 5
2021:
[1]. Multidisciplinary research project, ”Mejoramiento del Desempeño de Sistemas Industriales y
Mecatrónicos por medio de técnicas de Control Avanzado”. Escuela Superior Politécnica del
Litoral (ESPOL). Duration: 2021 - 2022. (Research Code FIEC-730-2021). Available from:
http://www.espol.edu.ec/es/investigacion/lg/proyectos-en-ejecucion
[2]. Multidisciplinary research project, ”Identificación de patrones anatómicos cerebrales en pa-
cientes de Parkinson con desórdenes Impulsivos compulsivos”. Escuela Superior Politécnica
del Litoral (ESPOL). Duration: 2021 - 2022. (Research Code FIMCP-16-2021). Available
from: http://www.espol.edu.ec/es/investigacion/lg/proyectos-en-ejecucion
[3]. Multidisciplinary research project, ”Modelo de predicción de consumo energético de la in-
fraestructura de un Data Center”. Escuela Superior Politécnica del Litoral (ESPOL). Dura-
tion: 2021 - 2022. (Research Code CTI-05-2021). Available from:
http://www.espol.edu.ec/es/investigacion/lg/proyectos-en-ejecucion
2020:
[1]. Multidisciplinary research project, ”Interfaces cerebro computadora para el control de dispos-
itivos mediante algoritmos de inteligencia artificial”. Escuela Superior Politécnica del Litoral
(ESPOL). Duration: 2020 - 2021. (Research Code FIMCP-74-2020). Available from:
http://www.espol.edu.ec/es/investigacion/lg/proyectos-en-ejecucion
2019:
[1]. Multidisciplinary research project, ”Procesamiento de señales EEG para detección de inten-
ciones motoras de extremidades inferiores en sujetos con lesión leve en médula espinal”.
Escuela Superior Politécnica del Litoral (ESPOL). Duration: 2019 - 2021. (Research Code
FIEC-11-2019)
Available from: http://investigacion.espol.edu.ec/Reporte/Proyecto/1346
[2]. Multidisciplinary research project, ”Proyecto de investigación: Independencia y Dignidad a
discapacitados (InDi). FONDO CANADIENSE PARA INICIATIVAS LOCALES”, with the
Neurobiology Laboratory (LNB-FIMCP). Escuela Superior Politécnica del Litoral (ESPOL).
Duration: 2019 - 2021.
2018:
[1]. Multidisciplinary research project, ”Desarrollo de aplicaciones de sistemas embebidos basados
en FPGAs”. Escuela Superior Politécnica del Litoral (ESPOL). Duration: 2018 - 2020.
(Research Code FIEC-32-2018)
Available from: http://investigacion.espol.edu.ec/Reporte/Proyecto/507
2014:
[1]. Multidisciplinary research project, ”Exoskeleton for rehabilitation of children with motor dis-
abilities in the lower extremities”, with the Neurobiology Laboratory (LNB-FIMCP). Escuela
Superior Politécnica del Litoral (ESPOL). Duration: 2014 - 2016.(Research Code T6-DI-2014)
Available from: http://investigacion.espol.edu.ec/Reporte/Proyecto/73
[2]. Multidisciplinary research project, ”Diseño, Construcción y Evaluación de Dispositivos de
Estimulación Periférica en Extremidades Inferiores, Para Ayuda a Pacientes de Parkinson
con Problemas de Congelamiento de la Marcha”, with the Neurobiology Laboratory (LNB-
FIMCP). Escuela Superior Politécnica del Litoral (ESPOL). Duration: 2014 - 2016. (Research
Code FIMCP-04-2014)
Available from: http://investigacion.espol.edu.ec/Reporte/Proyecto/146
6. Vı́ctor Asanza Armijos Ph.D. in Applied Computer Science 6
Repositories
[1]. Mendeley Data: Asanza, Vı́ctor; Montoya, Daniel; Peláez, Enrique; Loayza, Francis; Lorente-
Leyva, Leandro Leonardo; Peluffo-Ordóñez, Diego Hernan; González, Kléber (2022), ”MILimbEEG:
An EEG Signals Dataset based on Upper and Lower Limb Task During the Execution of Motor
and Motorimagery Tasks”, Mendeley Data, V1, doi: 10.17632/x8psbz3f6x.1
Available from: https://data.mendeley.com/datasets/x8psbz3f6x/1
[2]. IEEE DataPort: Vı́ctor Asanza, Kevin Chica-Orellana, Jonathan Cagua, Douglas Plaza, César
Martı́n, Diego Hernan Peluffo-Ordóñez. (2021). Temperature and Speed Control Lab (TSC-Lab).
IEEE Dataport. Available from: https://dx.doi.org/10.21227/8cty-6069
[3]. IEEE DataPort: Adrian Bazurto, Danny Torres, Vı́ctor Asanza, Ronald Reyes. (2021). 2 PHASE
ENERGY METER 100A (2PEM-100A). IEEE Dataport. Available from: https://dx.doi.org/
10.21227/6f3r-t917
[4]. IEEE DataPort: Jerry Landivar G., Carolina Ormaza C., Vı́ctor Asanza, Verónica Ojeda C., Juan
Carlos Aviles. (2021). Trilateration based on RSSI values in transmitters and receivers. IEEE
Dataport. Available from: https://dx.doi.org/10.21227/kjta-6551
[5]. IEEE DataPort: Adrian Bazurto, Danny Torres, Vı́ctor Asanza, Rebeca Estrada. (2021). Data
Server Energy Consumption Dtaset. IEEE Dataport. Available from: https://dx.doi.org/10.
21227/x6jw-m015
[6]. IEEE DataPort: Juan Cadena, Steven Santillan, Vı́ctor Asanza, Rebeca Estrada. (2021). Weather
Monitoring Station For Farms And Agriculture. IEEE Dataport. Available from: https://dx.
doi.org/10.21227/mdfs-ya42
[7]. IEEE DataPort: Raquel Tinoco-Egas, Karla Aviles, Jamil Torres-Brunes, Hector Trivino-Gonzalez,
Vı́ctor Asanza, Félix Rosales-Uribe, Francis R. Loayza, Enrique Peláez. (2021). SSVEP-EEG
data collection using Emotiv EPOC. IEEE Dataport. Available from: https://dx.doi.org/10.
21227/0j42-qd38
[8]. IEEE DataPort: Vı́ctor Asanza, Jesús Miranda, Nathaly Sánchez, Enrique Peláez, Francis Loayza,
Diego Hernan Peluffo-Ordóñez. (2021). Electromyography (EMG) of the Extraocular Muscles
(EOM). IEEE Dataport. Available from: https://dx.doi.org/10.21227/bhpj-mz94
[9]. IEEE DataPort: Anthony Maisincho J, Ulbio Alejandro S, Vı́ctor Asanza, Tonny Toscano Q.
(2021). Temperature data acquisition for a turkey hatchery. IEEE Dataport.
Available from: https://dx.doi.org/10.21227/hsqh-5959
Memberships
[1]. Smart Data Analysis Systems Group (SDAS), External Researchers. research group (www.
sdas-group.com). Pasto, Colombia. 2019-To the present.
Available from: https://www.sdas-group.com/members/Victor-Asanza/
[2]. IEEE professional member, IEEE Computational Intelligence Society Membership, IEEE
Young Professionals. 2015-To the present.
Available from: https://ieee-collabratec.ieee.org/app/p/vasanza
[3]. Artificial Intelligence Research (IA) group. Researcher. Escuela Superior Politécnica del Litoral
(ESPOL-FIEC).Guayaquil, Ecuador. 2018-To the present.
Available from: http://www.espol.edu.ec/es/ingestigacion/grupos-de-investigacion/
inteligencia-artificial
7. Vı́ctor Asanza Armijos Ph.D. in Applied Computer Science 7
Scientific Publications
Journal papers
2022:
[1]. Estrada, R., Asanza, V., Torres, D., Bazurto, A., Valeriano, I. Learning-based Energy Con-
sumption Prediction. In: Procedia Computer Science, 203, 272-279.
doi: 10.1016/j.procs.2022.07.035. Available from: doi:https://doi.org/10.1016/j.
procs.2022.07.035
[2]. Asanza, V.; Peláez, E.; Loayza, F.; Lorente-Leyva, L.L.; Peluffo-Ordóñez, D.H. Identification
of Lower-Limb Motor Tasks via Brain-Computer Interfaces: A Topical Overview. In: Sensors
2022, 22, 2028. https://doi.org/10.3390/s22052028. Available from: https://www.mdpi.
com/1424-8220/22/5/2028
2018:
[1]. Cordova, R., Garcia, I. M., Muñoz-Arcentales, A., Asanza, V., & Vargas, W. A. V.Modelo
de red de comunicación que soporta un sistema de detección basado en criterios de robustez.
In:IEEE Latin America Transactions ( Volume: 16 , Issue: 10 , October 2018 ). ISSN: 1548-
0992. Available from: https://www.inaoep.mx/~IEEElat/index.php/transactions/
article/view/497
2015:
[1]. Gabriel Romero, Carlos Salazar, Vı́ctor Asanza. Desarrollo de un Prototipo de Sistema
Hidrometeorológico. In: Revista Tecnológica ESPOL ISSN 1390-3659. Available from:
http://www.rte.espol.edu.ec/index.php/tecnologica/article/view/455
Proceedings book chapter
2020:
[1]. Asanza V., Sanchez G., Cajo R., Peláez E. Behavioral Signal Processing with Machine Learn-
ing Based on FPGA. In: Botto-Tobar M., Zamora W., Larrea Plúa J., Bazurto Roldan J.,
Santamarı́a Philco A. (eds) Systems and Information Sciences. ICCIS 2020. Advances in
Intelligent Systems and Computing, vol 1273. Springer, Cham. Available from: https:
//doi.org/10.1007/978-3-030-59194-6_17
Conference papers
2022:
[1]. V. Asanza et al. Electrooculography Signals Classification for FPGA-based Human-Computer
Interaction. In: 2022 IEEE ANDESCON, Barranquilla, Colombia, 2022, pp. 1-7.
doi: 10.1109/ANDESCON56260.2022.9989664. Available from: https://ieeexplore.
ieee.org/document/9989664
[2]. J. Luna, E. Peláez, F. R. Loayza, A. Saravia, I. Obeso and V. Asanza. Anatomical Patterns
Recognition of Impulse Control Disorders of Parkinsonian Patients Using Deep Learning of
MRI structural images. In: 2022 IEEE ANDESCON, Barranquilla, Colombia, 2022, pp. 1-6.
doi: 10.1109/ANDESCON56260.2022.9989825. Available from: https://ieeexplore.
ieee.org/document/9989825
8. Vı́ctor Asanza Armijos Ph.D. in Applied Computer Science 8
[3]. G. Montesdeoca, V. Asanza, K. Chica and D. H. Peluffo-Ordóñez. Analysis of Sorting Algo-
rithms Using a WSN and Environmental Pollution Data based on FPGA. In: 2022 Interna-
tional Conference on Applied Electronics (AE), 2022, pp. 1-4.
doi: 10.1109/AE54730.2022.9920090. Available from: https://ieeexplore.ieee.org/
document/9920090
[4]. J. Landı́var, C. Ormaza, V. Asanza, V. Ojeda, J. C. Avilés and D. H. Peluffo-Ordóñez.
Trilateration-based Indoor Location using Supervised Learning Algorithms. In: 2022 Interna-
tional Conference on Applied Electronics (AE), 2022, pp. 1-6.
doi: 10.1109/AE54730.2022.9920073. Available from: https://ieeexplore.ieee.org/
document/9920073
2021:
[1]. V. Asanza, R. Estrada, J. Miranda, L. Rivas and D. Torres. Performance Comparison of
Database Server based on SoC FPGA and ARM Processor. In: 2021 IEEE Latin-American
Conference on Communications (LATINCOM), 2021, pp. 1-6,
doi: 10.1109/LATINCOM53176.2021.9647742. Available from: https://doi.org/10.
1109/LATINCOM53176.2021.9647742
[2]. V. Asanza, K. Avilés-Mendoza, H. Trivino-Gonzalez, F. Rosales-Uribe, J. Torres-Brunes,
F. Loayza, E. Peláez, R. Cajo, and R. Tinoco-Egas. SSVEP-EEG Signal Classification
based on Emotiv EPOC BCI and Raspberry Pi. In: IFAC-PapersOnLine, 54(15), 388-393,
doi: 10.1016/j.ifacol.2021.10.287. Available from: https://doi.org/10.1016/j.ifacol.
2021.10.287
[3]. V. Asanza, N. Sánchez-Pozo, L. Lorente-Leyva, D. Peluffo-Ordóñez, F. Loayza, and E. Peláez.
Classification of Subjects with Parkinson's Disease using Finger Tapping Dataset. In: IFAC-
PapersOnLine, 54(15), 376-381, doi: 10.1016/j.ifacol.2021.10.285. Available from: https:
//doi.org/10.1016/j.ifacol.2021.10.285
[4]. A. Constantine, V. Asanza, F. Loayza, E. Peláez and D. Peluffo-Ordóẽz. BCI System using
a Novel Processing Technique Based on Electrodes Selection for Hand Prosthesis Control.
In: IFAC-PapersOnLine, 54(15), 364-369, doi: 10.1016/j.ifacol.2021.10.283. Available from:
https://doi.org/10.1016/j.ifacol.2021.10.283
[5]. J. A. Maisincho-Jivaja; U. Alejandro-Sanjines, V. Asanza, T. Toscano-Quiroga, N. Sánchez-
Pozo, L. Lorente-Leyva and D. Peluffo-Ordóñez. Monitoring a turkey hatchery based on
a cyber-physical system. In: 2021 International Conference on Applied Electronics (AE),
Pilsen, Czech Republic, 2021, pp. 1-6, doi: 10.23919/AE51540.2021.9542899. Available
from: https://ieeexplore.ieee.org/document/9542899
[6]. J. Capelo, E. Ruiz, V. Asanza, T. Toscano-Quiroga, N. Sánchez-Pozo, L. Lorente-Leyva and
D. Peluffo-Ordóñez. Raspberry Pi-based IoT for shrimp farms Real-time remote monitoring
with automated system. In: 2021 International Conference on Applied Electronics (AE),
Pilsen, Czech Republic, 2021, pp. 1-4, doi: 10.23919/AE51540.2021.9542907. Available
from: https://ieeexplore.ieee.org/document/9542907
[7]. V. Asanza, R. E. Pico, D. Torres, S. Santillan and J. Cadena. FPGA Based Meteorologi-
cal Monitoring Station. In: 2021 IEEE Sensors Applications Symposium (SAS), Sundsvall,
Sweden, 2021, pp. 1-6, doi: 10.1109/SAS51076.2021.9530151. Available from: https:
//ieeexplore.ieee.org/document/9530151
[8]. J. Fuentes-Gonzalez, A. Infante-Alarcón, V. Asanza and F. R. Loayza. A 3D-Printed EEG
based Prosthetic Arm. In: 2020 IEEE International Conference on E-health Networking, Ap-
plication & Services (HEALTHCOM), Shenzhen, China, 2021, pp. 1-5, doi: 10.1109/HEALTH-
COM49281.2021.9399035. Available from: https://ieeexplore.ieee.org/abstract/
document/9399035
9. Vı́ctor Asanza Armijos Ph.D. in Applied Computer Science 9
2020:
[1]. V. A. Armijos, N. S. Chan, R. Saquicela and L. M. Lopez. Monitoring of system memory
usage embedded in FPGA. In: 2020 International Conference on Applied Electronics (AE),
Pilsen, Czech Republic, 2020, pp. 1-4, doi: 10.23919/AE49394.2020.9232863. Available
from: https://ieeexplore.ieee.org/abstract/document/9232863
[2]. C. Angel Silva, V. Asanza, N. Sánchez and J. Arias. Implementation Of Automated Sys-
tem For The Reservoir 66 of the Irrigation System Chambo Guano. In: 2020 Interna-
tional Conference on Applied Electronics (AE), Pilsen, Czech Republic, 2020, pp. 1-6,
doi: 10.23919/AE49394.2020.9232888. Available from: https://ieeexplore.ieee.org/
abstract/document/9232888
[3]. V. Asanza, A. Constantine, S. Valarezo and E. Peláez. Implementation of a Classification
System of EEG Signals Based on FPGA. In: 2020 Seventh International Conference on
eDemocracy & eGovernment (ICEDEG), Buenos Aires, Argentina, 2020, pp. 87-92, doi:
10.1109/ICEDEG48599.2020.9096752. Available from: https://ieeexplore.ieee.org/
document/9096752
2019:
[1]. C. Cedeño Z., J. Cordova-Garcia, V. Asanza A., R. Ponguillo and L. Muñoz M. k-NN-Based
EMG Recognition for Gestures Communication with Limited Hardware Resources. In: 2019
IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing,
Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People
and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI). Avail-
able from: https://ieeexplore.ieee.org/document/9060290
2018:
[1]. Vı́ctor Asanza, Enrique Peláez, Francis Loayza, Iker Mesa, Javier Dı́az, Edwin Valarezo.
EMG Signal Processing with Clustering Algorithms for motor gesture Tasks. In: 2018 IEEE
Third Ecuador Technical Chapters Meeting (ETCM). Available from: https://ieeexplore.
ieee.org/abstract/document/8580270
2017:
[1]. Vı́ctor Asanza, Enrique Peláez, Francis Loayza. Supervised pattern recognition techniques for
detecting motor intention of lower limbs in subjects with cerebral palsy. In: 2017 IEEE Sec-
ond Ecuador Technical Chapters Meeting (ETCM). Available from: https://ieeexplore.
ieee.org/abstract/document/8247452
[2]. Vı́ctor Asanza, Enrique Peláez, Francis Loayza. EEG signal clustering for motor and imaginary
motor tasks on hands and feet. In: 2017 IEEE Second Ecuador Technical Chapters Meeting
(ETCM). Available from: https://ieeexplore.ieee.org/abstract/document/8247451
[3]. Vı́ctor Asanza, César A. Martin, Parisa Eslambolchilar, Hugo van Woerden, Ricardo Cajo,
Carlos Salazar. Finding a dynamical model of a social norm physical activity intervention. In:
2017 IEEE Second Ecuador Technical Chapters Meeting (ETCM). Available from: https:
//ieeexplore.ieee.org/abstract/document/8247450
2016:
[1]. Vı́ctor Asanza, Kerly Ochoa, Christian Sacarelo, Carlos Salazar, Francis Loayza, Carmen Vaca,
Enrique Peláez. Clustering of EEG occipital signals using k-means. In: 2016 IEEE Ecuador
Technical Chapters Meeting (ETCM). Available from: https://ieeexplore.ieee.org/
abstract/document/7750874
10. Vı́ctor Asanza Armijos Ph.D. in Applied Computer Science 10
References
Colón Enrique Peláez Jarrı́n, Ph.D.
Professor
Faculty of Electrical and Computer Engineering
Escuela Superior Politécnica del Litoral - Ecuador
Head of Artificial Intelligence Research Group
Tel. +593 (4) 2269 - 818
E-mail: epelaez@espol.edu.ec
Francis Loayza Paredes, Ph.D.
Professor
Faculty of Mechanical and Production Science Engineering
Escuela Superior Politécnica del Litoral - Ecuador
Head of Laboratory of NeuroBiology
Tel. +593 (4) 2269 - 369
E-mail: jloaiza@espol.edu.ec
Diego Hernán Peluffo-Ordóñez, Ph.D.
MSDA Research Program
(https://msda.um6p.ma/home )
Université Mohammed VI Polytechnique
Lot 660, Hay Moulay Rachid, Ben Guerir 43150, Morocco
E-mail: peluffo.diego@um6p.ma
Head of the SDAS Research Group
(www.sdas-group.com )
Phone: +212665396851, +573108212316
E-mail: diego.peluffo@sdas-group.com
Website: www.diegopeluffo.com
Vı́ctor Manuel Asanza Armijos