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https://purl.org/pe-repo/ocde/ford#5.02.04
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ODS 3: Salud y bienestar. Garantizar una vida sana y promover el bienestar de todos a todas las edades
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1
artículo
Publicado 2023
Enlace
Enlace
Process automation is being implemented in different disciplines of earth sciences, as seen in the implementation of libraries such as Pyrolite, PyGeochemCalc, dh2loop 1.0, NeuralHydrology, GeoPyToo among others. The present work addresses a methodology to automate the geochemical univariate analysis by using Python and open-source packages such as pandas, seaborn, matplotlib, statsmodels which will be integrated into a script in a local work environment such as Jupyter notebook or in an online environment such as Google Collaboratory. The script is designed to process any type of geochemical data, allowing to remove outliers, perform calculations and graphs of the elements and their respective geological domain. The results include graphics such as boxplot, quantile-quantile and calculations of normality tests and geochemical parameters, allowing to determine the background and threshol...
2
artículo
Publicado 2023
Enlace
Enlace
With the increase of the university population, the individual psychological care service by psychologists in universities has been affected. Which has caused discomfort among students to access the psychological consulting service. Therefore, this project aims to implement a data analysis system to control the psychological variables that affect university students, improving attention to them through the use of artificial intelligence (AI). We present a system that allows the visualization of data related to the mental health of the students who developed a psychological test, with which the psychologist will be able to diagnose the student's mental state and determine if he or she requires personalized attention. Finally, with this research, we achieved an improvement in the speed of attention and quality of service for the student.
3
objeto de conferencia
Publicado 2018
Enlace
Enlace
The present work was achieved thanks to the joint work with my advisor, for her persistence and tenacity at the moment of sharing her teachings with me, to my distinguished teachers who have forged knowledge from the first day of classes, whom with nobility and enthusiasm influenced as an example in me and my colleagues in the master’s degree in computer science; also thanks to CONCYTEC, FONDECYT and Cienciactiva for the support and opportunities provided that made this work possible.
4
artículo
Publicado 2025
Enlace
Enlace
Esta investigación se centra en la implementación de la reingeniería del proceso de medición de los Stock Keeping Unit (SKU) importados por un centro de distribución de una empresa especializada en la venta de productos para la mejora del hogar y materiales de construcción. Para identificar los factores que influyen en el proceso y optimizarlo, se realizó un estudio de tiempos y movimientos del proceso utilizando la herramienta conocida como diagrama de espagueti. Como resultado, se incrementó la productividad y disminuyeron los tiempos muertos, lo que permitió medir en menos tiempo el universo de SKU. El estudio también condujo a la configuración del sistema utilizando datos correctos, lo que facilitó la operación dentro del almacén.
5
objeto de conferencia
The growth of cloud application services delivered through data centers with varying traffic demands unveils limitations of traditional load balancing methods. Aiming to attend evolving scenarios and improve the overall network performance, this paper proposes a load balancing method based on an Artificial Neural Network (ANN) in the context of Knowledge-Defined Networking (KDN). KDN seeks to leverage Artificial Intelligence (AI) techniques for the control and operation of computer networks. KDN extends Software-Defined Networking (SDN) with advanced telemetry and network analytics introducing a so-called Knowledge Plane. The ANN is capable of predicting the network performance according to traffic parameters paths. The method includes training the ANN model to choose the path with least load. The experimental results show that the performance of the KDN-based data center has been greatl...
6
artículo
In this paper, we propose an optimization model for medical services processes to reduce waiting time using process mining. In medical services, there is a high percentage of dissatisfaction with medical care due to the processes related to appointment booking and waiting time for medical consultation. As a result, patients change medical services due to the urgency of the symptoms they suffer, generating distrust in health services in Peru. Through a medical information system, events of medical care processes are collected for analysis using the Celonis tool. The process mining discipline uses the discovery of the study process to identify existing bottlenecks in the process and violations that are included when monitoring process events. The proposed model is based on identifying the existing bottlenecks in the processes, which are appointment booking and office care, as these process...
7
capítulo de libro
Publicado 2019
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This work proposes a semi-automated analysis and modeling package for Machine Learning related problems. The library goal is to reduce the steps involved in a traditional data science roadmap. To do so, Sparkmach takes advantage of Machine Learning techniques to build base models for both classification and regression problems. These models include exploratory data analysis, data preprocessing, feature engineering and modeling. The project has its basis in Pymach, a similar library that faces those steps for small and medium-sized datasets (about ten millions of rows and a few columns). Sparkmach central labor is to scale Pymach to overcome big datasets by using Apache Spark distributed computing, a distributed engine for large-scale data processing, that tackle several data science related problems in a cluster environment. Despite the software nature, Sparkmach can be of use for local ...
8
artículo
Publicado 2018
Enlace
Enlace
Disruptive technologies and their impact on journalism and communication force us to assume challenges in learning new techniques for data and information processing. Interdisciplinary knowledge is evident in the teaching of new professional profiles. Data journalism is an example of this, so the immersion into a data culture must be preceded by awareness in the learning of news applications, algorithms or the treatment of Big Data, elements that configure new paradigms among journalists of the media on the Internet. With the revision of texts, direct observation of selected applications and case study, some conclusions are established that contain a growing demand in the knowledge of new techniques. The results show the use of technological resources and the proposal of changes in the curricula of the communication faculties.
9
artículo
Publicado 2018
Enlace
Enlace
Disruptive technologies and their impact on journalism and communication force us to assume challenges in learning new techniques for data and information processing. Interdisciplinary knowledge is evident in the teaching of new professional profiles. Data journalism is an example of this, so the immersion into a data culture must be preceded by awareness in the learning of news applications, algorithms or the treatment of Big Data, elements that configure new paradigms among journalists of the media on the Internet. With the revision of texts, direct observation of selected applications and case study, some conclusions are established that contain a growing demand in the knowledge of new techniques. The results show the use of technological resources and the proposal of changes in the curricula of the communication faculties.
10
artículo
Publicado 2024
Enlace
Enlace
This study presents Datalyzer, a system designed for data extraction, visualization, and prediction in the mining sector using advanced NLP and machine learning, specifically GPT-3.S Turbo. The system enhances operational efficiency through rigorous data preprocessing and specialized fine-tuning, validated on a simulated mining dataset. Results show significant improvements: data extraction time reduced by 94 % and visualization time by 97.6%. These improvements indicate a transformation in efficiency, usability, and user satisfaction. Despite limitations in data variability and complexity, this pioneering approach highlights the potential of NLP and machine learning in modernizing the mining industry and supporting data-driven decision-making.
11
artículo
Publicado 2022
Enlace
Enlace
so, machine learning techniques are being developed to improve performance and maintenance prediction. Increasing our knowledge of the relationship between humans and algorithms, Because data is so valuable, improving strategies for intelligently having to manage the now-ubiquitous content infrastructures is a necessary part of the process toward completely autonomous agents. Numerous researchers recently developed numerous computer-aided diagnostic algorithms employing various supervised learning approaches. Early identification of sickness may help to reduce the number of people who die as a result of these illnesses. Using machine learning techniques, this research creates an efficient automated illness diagnostic algorithm. We chose three key disorders in this paper: coronavirus, cardiovascular diseases, and diabetes. The data are inputted into a mobile application in the suggested m...
12
artículo
Publicado 2014
Enlace
Enlace
Globalization has intensified competition in many markets. To remain competitive, the companies look for satisfying the needs of customers by meeting market requirements. In this context, Process Capability Indices (PCI) play a crucial role in assessing the quality of processes. In the case of non-normal data there are two general approaches based on transformations (Box-Cox and Johnson Transformation) and Percentiles (Pearson’s and Burr’s Distribution Systems). However, previous studies on the comparison of these methods show different conclusions, and thus arises the need to clarify the differences between these methods to implement a proper estimation of these indices. In this paper, a simulation study is made in order to compare the above methods and to propose an appropriate methodology for estimating the PCI in non-normal data. Furthermore, it is concluded that the best method ...
13
artículo
Globalization has intensified competition in many markets. To remain competitive, the companies look for satisfying the needs of customers by meeting market requirements. In this context, Process Capability Indices (PCI) play a crucial role in assessing the quality of processes. In the case of non-normal data there are two general approaches based on transformations (Box-Cox and Johnson Transformation) and Percentiles (Pearson’s and Burr’s Distribution Systems). However, previous studies on the comparison of these methods show different conclusions, and thus arises the need to clarify the differences between these methods to implement a proper estimation of these indices. In this paper, a simulation study is made in order to compare the above methods and to propose an appropriate methodology for estimating the PCI in non-normal data. Furthermore, it is concluded that the best method ...
14
artículo
Despite the growing literature on bank efficiency worldwide over the last decade, researchers have neglected the Peruvian banking sector. In this paper, the technique of data envelopment analysis (DEA) is used to investigate the efficiency of Peruvian banks for the period 2000 to 2009 to benchmark currently existing banks based on their super-efficiency scores over time. Further, an in-depth analysis of currently existing banks for the period 2008 to 2009 is conducted to check the robustness of DEA efficiency scores and the potential improvement of inputs and outputs for inefficient banks, indicating by how much and in what areas inefficient banks need to improve in order to be efficient. Our finding shows an increasing trend in technical efficiency during the period 2000 to 2009 which gives an indication of an affirmative effect of the reform process in the Peruvian banking sector. On a...
15
tesis de grado
Publicado 2023
Enlace
Enlace
En los últimos años, la llegada de las cámaras de profundidad de bajo costo y sensores LiDAR ha incentivado a las industrias a invertir en estas tecnologías, lo cual incluye también mayor interés en investigaciones sobre procesamiento digital de señales. En esta ocasión, la reconstrucción tridimensional de túneles mineros utilizando LiDARs y un robot de auto-navegación ha sido propuesta como proyecto de investigación, y el presente trabajo forma parte en cargándose del alineamiento de nubes de puntos tridimensionales en tiempo real, un proceso que es más conocido como Registro de Nubes de Puntos. Existen muchos algoritmos que pueden resolver este problema, pero para el proyecto, el algoritmo solo necesita calcular la alineación fina y rígida. Al comparar los algoritmos de registro más avanzados, se encontró que el popular algoritmo ICP es el más adecuado para este caso...
16
tesis de grado
Publicado 2023
Enlace
Enlace
En los últimos años, la llegada de las cámaras de profundidad de bajo costo y sensores LiDAR ha incentivado a las industrias a invertir en estas tecnologías, lo cual incluye también mayor interés en investigaciones sobre procesamiento digital de señales. En esta ocasión, la reconstrucción tridimensional de túneles mineros utilizando LiDARs y un robot de auto-navegación ha sido propuesta como proyecto de investigación, y el presente trabajo forma parte en cargándose del alineamiento de nubes de puntos tridimensionales en tiempo real, un proceso que es más conocido como Registro de Nubes de Puntos. Existen muchos algoritmos que pueden resolver este problema, pero para el proyecto, el algoritmo solo necesita calcular la alineación fina y rígida. Al comparar los algoritmos de registro más avanzados, se encontró que el popular algoritmo ICP es el más adecuado para este caso...
17
artículo
Based on the concepts of decision support system (DSS), a framework is presented for IT portfolio selection, which could be adaptable in different degrees to the needs of the different stakeholders of the company. This framework provides a flexible, expandable and interactive DSS to select IT projects for portfolio management A case is showed to demonstrate the practical application of the proposed approach.
18
artículo
Based on the concepts of decision support system (DSS), a framework is presented for IT portfolio selection, which could be adaptable in different degrees to the needs of the different stakeholders of the company. This framework provides a flexible, expandable and interactive DSS to select IT projects for portfolio management A case is showed to demonstrate the practical application of the proposed approach.
19
artículo
Publicado 2025
Enlace
Enlace
The main goal of this research is to demonstrate that the use of innovative technology like business intelligence (BI) in a specific type of business significantly impacts their sales processes, enhancing decision-making, promotional strategies, and consequently customer loyalty and sales growth. The case study is a manufacturing business located in Lima, Peru. The information requirements of this business were analyzed, and a data mart model was created using the Kimball methodology. This multidimensional model enabled the comparison of client sales trends to propose new promotions and marketing strategies. The data analysis used to evaluate the results included hypothesis testing, analysis of employee responses to questionnaires to measure the impact of technology use on sales processes, and data reviews to assess sales increases both before and after the implementation of this technol...
20
artículo
Objective: To describe the characteristics of the use of a preventive app by the Peruvian population during its first year of operations between 2019 and 2020. Materials and methods: A descriptive, cross-sectional and retrospective study, in which the database of the Salud Total preventive app, concerning the demographic characteristics of and usage by the Peruvian population, was reviewed during its first year of operations. Sociodemographic variables (sex and age) and usage (health data, pathological findings, frequency of use, and type and number of services requested) were analyzed. The analysis and processing of descriptive data were performed using Microsoft Excel. Results: The number of users who downloaded and registered in the app was 9,737 people. A similar sex ratio was found, and the 21- to 50-year-old group prevailed. A total of 2,254 health data voluntarily entered by the u...
