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1
artículo
Publicado 2025
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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.
2
artículo
Technological advances have allowed to collect and store large volumes of data over the years. Besides, it is significant that today's applications have high performance and can analyze these large datasets effectively. Today, it remains a challenge for data mining to make its algorithms and applications equally efficient in the need of increasing data size and dimensionality [1]. To achieve this goal, many applications rely on parallelism, because it is an area that allows the reduction of cost depending on the execution time of the algorithms because it takes advantage of the characteristics of current computer architectures to run several processes concurrently [2]. This paper proposes a parallel version of the FuzzyPred algorithm based on the amount of data that can be processed within each of the processing threads, synchronously and independently.
3
artículo
Publicado 2018
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Geo-referenced textual data has been the subject of multiple investigations, by providing opportunities to better understand certain phenomena according to the content that is shared, either on-line such as social networks, blogs, and news; or through repositories such as scientific research articles, geo-referenced virtual books, among others. However, the characteristics of this information are studied, analyzed and processed separately, either through its textual components or its geo-spatial components, which offers a separate understanding of the results. In this paper, we propose an integration of textual and geo-spatial components from the pre-processing phase to the visualization stage, As a part of the Document Mapping process based on the phases of the Knowledge Discovery in Databases (KDD). Achieving two main results (1) minimize the problems that arise in the visual phase, su...
4
objeto de conferencia
Publicado 2018
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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.
5
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 ...
6
artículo
Publicado 2014
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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 ...
7
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 ...
8
informe técnico
En el presente trabajo, se sistematizan los conceptos inherentes al Modelo Data Warehouse, haciendo referencia a cada uno de ellos en forma ordenada, en un marco conceptual claro, en el que se desplegarán sus características y cualidades, y teniendo siempre en cuenta su relación o interrelación con los demás componentes del ambiente. Inicialmente, se definirá los conceptos generales relacionados al Data WareHouse, Seguidamente, se introducirá a la definición de requerimientos y los procesos de negocio para modelar un Data Warehouse, y se expondrán sus aspectos más relevantes y significativos. Luego, se precisarán y detallarán todos los componentes que intervienen en la Integración de Datos, de manera organizada e intuitiva, atendiendo su interrelación. Posterior se describe el Diseño Dimensional para los procesos de Negocio. Finalmente, se describirán algunos conceptos qu...
9
tesis de maestría
Publicado 2021
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Basado en los datos de observación de alta precisión GNSS y el cambio de coordenadas de la estación de monitoreo CORS antes y después del terremoto 8.0 de Perú de 2019, el autor desarrolló el software de análisis de deformación de la superficie basado en el software de procesamiento científico, que tiene valor científico y práctico en la investigación del epicentro del terremoto, magnitud y geodinámica. Se muestran los resultados obtenidos utilizando el software científico de procesamiento GNSS PANDA, un paquete de precisión para el análisis de datos GNSS, desarrollado por la Universidad de Wuhan, China. Los resultados son de alta precisión en el orden de los milímetros. Los resultados obtenidos tienen un desplazamiento de alrededor de 2 cm en las estaciones GNSS cercanas al terremoto, al noroeste.
10
artículo
Publicado 2024
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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 2019
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Is there a correspondence or affinity between the juridicalprincipiological and factual-economical conceptions for the effective protection of the consent of the holder of personal data when hiring in a network?Under the mantle of the present question, it aims to analyze the contemporary contractual scenario under the perspective of the privacy policy and the Brazilian General Data Protection Law (LGPD). In this context, it is proposed a skeptical reflection on the principles and economic guidelines defended by law and doctrine to verify if the consent is an instrument of real effectiveness to the tutelage of the subjects in network. The first topic concerns the conceptual and conceptual analysis of consent in the LGPD and in the specialized doctrine. The second topic deals with the limited rationality of the users of the network services in understanding the dispositions in the pol...
12
artículo
Publicado 2015
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In order to set realistic goals and carry out its functions effectively, the auditors of automatic data processing (EDP), should know what they expect their companies. Possess a clear understanding of the objectives of the administration. This booklet expresses these issues and describes some responsibilities that must exist between the EDP auditor and management in enterprises.
13
artículo
Publicado 2023
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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...
14
artículo
Publicado 2025
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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...
15
artículo
Publicado 2024
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The underrepresentation of women in STEM fields needs to be highlighted through data to assist decisionmakers and public policy creators in addressing the issue effectively. However, the lack of structured, organized data published openly in this domain is still a reality. To address this problem, a Latin American research network called ELLAS was created. The project’s goal is to develop a platform with Semantic Web-based technologies to structure and concentrate data from Brazil, Peru, and Bolivia, initially. This paper presents the processes defined for the collection and curation of both unstructured and structured data, sourced from scientific articles, social networks, and existing open data. We explore the architecture design in a way that facilitates understanding of the details of the processes and the actors involved for each data source. We present the preliminary results fr...
16
artículo
Publicado 2018
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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.
17
artículo
Publicado 2018
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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.
18
tesis doctoral
Publicado 2024
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This dissertation investigates the potential improvement of volcanic eruption understanding and forecasting methods by using advanced data processing techniques to analyze large datasets at three target volcanoes (Piton de la Fournaise (PdlF) (France), Sabancaya, and Ubinas (Peru)). The central objective of this study is to search for possible empirical relationships between the pre-eruptive behavior of the accelerated increase in seismic activity using the Failure Forecast Method (FFM) and velocity variations measured by Coda Wave Interferometry (CWI), since both observations are reported to be independently associated with medium damage. The FFM is a deterministic method used to forecast volcanic eruptions using an empirical relationship of increased and accelerated evolution of an observable (e.g., volcano-seismic event rates). The event rates used with FFM in this study were generate...
19
tesis doctoral
Publicado 2024
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This dissertation investigates the potential improvement of volcanic eruption understanding and forecasting methods by using advanced data processing techniques to analyze large datasets at three target volcanoes (Piton de la Fournaise (PdlF) (France), Sabancaya, and Ubinas (Peru)). The central objective of this study is to search for possible empirical relationships between the pre-eruptive behavior of the accelerated increase in seismic activity using the Failure Forecast Method (FFM) and velocity variations measured by Coda Wave Interferometry (CWI), since both observations are reported to be independently associated with medium damage. The FFM is a deterministic method used to forecast volcanic eruptions using an empirical relationship of increased and accelerated evolution of an observable (e.g., volcano-seismic event rates). The event rates used with FFM in this study were generate...
20
artículo
Publicado 2019
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This article presents a methodology that applies natural language processing and classification algorithms by using data mining techniques, and incorporating procedures for validation and verification of significance. This is conducted according to the analysis and selection of data and results based on quality statistical analysis, which guarantees the effectiveness percentage in knowledge construction. The analysis of computer incidents within an educational institution and a standardized database of historical computer incidents collected by the Service Desk area is used as case study. Such area is linked to all information technology processes and focuses on the support requirements for the performance of employee activities. As long as users’ requirements are not fulfilled in a timely manner, the impact of incidents may give rise to work problems at different levels, making it d...