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1
objeto de conferencia
Publicado 2018
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This research was supported by CIENCIACTIVA, CONCYTEC and the National University of San Agustin (UNSA). We thank all professors who collaborate in the research.
2
artículo
The soaring number of natural hazards in recent years due largely to climate change has resulted in an even higher level of investment in flood protection structures. However, such investments tend to be made in the aftermath of disasters. Very little is known about the proactive planning of flood protection investments that account for uncertainties associated with flooding events. Understanding the uncertainties such as “when” to invest on these structures to achieve the most optimal cost-saving amount is outmost important. This study fills this large knowledge gap by developing an investment decision-making assessment framework that determines an optimal timing of flood protection investment options. It combines real options with a net present value analysis to examine managerial flexibility in various investment timing options. Historical data that contain information about river...
3
artículo
Publicado 2011
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In this article, a method is presented based on artificial intelligence to control a plant DC motor for a personal microcomputer (PC), that interacted hardware and software achieves the control of the speed of the DC motor in real time using the control algorithm Fuzzy-PD+I. The acquisition of data and identification of the parameters of the DC motor have been necessary for the control of the speed of the motor DC, by means of the card of acquisition of data PCI NIDAQ 6024E whose interface runs in the real time that the Workshop Real-Time uses (RTW), the file of data is processed with the tool of identification of the program called IDENT of Matlab. The prototype of the system computer-controller is designed using the graphic programming of LabVIEW, in this case use of the tools Fuzzy Logic Control and Simulation Module. The control in real time of the system is carried out in the labora...
4
artículo
Publicado 2011
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Conventional data envelopment analysis (DEA) for measuring the relative efficiency of a set of decision-making units (DMUs) requires the observations to have precise values. When observations are imprecise and represented by interval values, the efficiencies are also expected to reflect interval values. Several methods exist to calculate the interval overall and technical efficiencies, but such methods are unable to calculate the interval scale efficiency. The focus of this paper is the application of a two-level programming technique to formulate the problem of determining the bounds of the interval scale efficiency. The associated models are essentially nonlinear programs with only bound constraints for variables in a sophisticated form. Hence, one can modify the conventional quasi-Newton method for unconstrained nonlinear programming problems to solve the two-level programs. Two examp...
5
artículo
Publicado 2025
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Nowcasting models based on machine learning (ML) algorithms deliver a noteworthy advantage for decision-making in the public and private sectors due to their flexibility and ability to handle large amounts of data. This article introduces real-time forecasting models for the monthly Peruvian GDP growth rate. These models merge structured macroeconomic indicators with high-frequency unstructured sentiment variables. The analysis spans January 2007 to May 2023, encompassing a set of 91 leading economic indicators. Six ML algorithms were evaluated to identify the most effective predictors for each model. The findings underscore the remarkable capability of ML models to yield more precise and foresighted predictions compared to conventional time series models. Notably, the gradient boosting machine, LASSO, and elastic net models emerged as standout performers, achieving a reduction in predic...
6
artículo
Publicado 2025
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Los modelos de nowcasting basados en algoritmos de Machine Learning (ML) ofrecen una ventaja notable para la toma de decisiones en los sectores público y privado debido a su flexibilidad y capacidad para manejar grandes cantidades de datos. Este documento presenta modelos de pronóstico en tiempo real para la tasa de crecimiento mensual del PIB peruano. Estos modelos combinan indicadores macroeconómicos estructurados con variables de sentimiento no estructurados de alta frecuencia. El análisis comprende desde enero de 2007 hasta mayo de 2023, abarcando un conjunto de 91 indicadores económicos principales. Se evaluaron seis algoritmos de ML para identificar los predictores más eficaces de cada modelo. Los resultados subrayan la notable capacidad de los modelos de ML para producir predicciones más precisas y previsoras que los modelos convencionales de series temporales. En particula...
7
tesis de grado
Publicado 2025
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Este estudio analiza el impacto del procesamiento de lenguaje natural (PLN) en el ámbito sanitario, evaluando las técnicas más eficaces para mejorar procesos y servicios médicos. La investigación utiliza una revisión sistemática basada en el protocolo PRISMA 2020, seleccionando 20 artículos clave de bases de datos académicas como IEEE Xplore y ScienceDirect. Se identifican cuatro técnicas principales: análisis de sentimientos, reconocimiento de NER, clasificación automática de textos y generación de resúmenes. Estas técnicas han demostrado ser herramientas efectivas para mejorar la precisión diagnóstica, optimizar la gestión de datos clínicos y reducir la carga administrativa. El análisis revela que los modelos avanzados de aprendizaje profundo, como BERT y CNN, logran tasas de precisión superiores al 90% en tareas como la clasificación de enfermedades y el resumen...
8
artículo
Publicado 2019
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The growing activity generated in digital communication platforms is raising new forms of relationship between organizations and their publics of interest. This has triggered, in turn, the production of a large amount of information, an explosion of data known as Big Data. In this new context, there is a need to study how the management of this huge amount of information faced in public relations, which is constantly generated at high speed and which requires even real-time management. In this work, we present a bibliographic review of the current state of research on the management of Big Data in Public Relations. The results showed a total 41 works. A content analysis of these works found that the activities of internal communications, media relations, crisis communications and issues management are the most related to massive data management.
9
artículo
Publicado 2020
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There has been an increasing relevance of the cultural sector in the economic and social development of different countries. However, this sector continues without much input from multi-criteria decision-making (MDCM) techniques and sustainability analysis, which are widely used in other sectors. This paper proposes an MCDM model to assess the sustainability of a musical institution’s program. To define the parameters of the proposed model, qualitative interviews with relevant representatives of Catalan cultural institutions and highly recognized professionals in the sector were performed. The content of the 2015–2016 season of the ‘Palau de la Música Catalana’, a relevant Catalan musical institution located in Barcelona, was used as a case study to empirically test the method. The method allows the calculation of a season value index (SVI), which serves to make more sustainable...
10
artículo
Publicado 2016
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The main objective on this research is the development of finding the optimal parameters for a routing algorithm for network routers based on the ant algorithm described as AntNet. The optimum parameters for this type of algorithm improve a more efficient alternative to those given by the RIP, EIGRP and OSPF routing protocols, to be applied in a data network. This shall be tested in two networks and routers defined, taking the same characteristics for the three groups: RIP, OSPF and by the result provided by the genetic algorithm implemented using a static network. The system recognizes the best path between networks of routers, based on the principle of AntNet networks or networks of ants, which are the best way from exploring almost all roads, using estimergia to go there and make optimal. MatLab was used to detect the best way. Later this road was implemented in a real network data, s...
11
artículo
Publicado 2016
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The main objective on this research is the development of finding the optimal parameters for a routing algorithm for network routers based on the ant algorithm described as AntNet. The optimum parameters for this type of algorithm improve a more efficient alternative to those given by the RIP, EIGRP and OSPF routing protocols, to be applied in a data network. This shall be tested in two networks and routers defined, taking the same characteristics for the three groups: RIP, OSPF and by the result provided by the genetic algorithm implemented using a static network. The system recognizes the best path between networks of routers, based on the principle of AntNet networks or networks of ants, which are the best way from exploring almost all roads, using estimergia to go there and make optimal. MatLab was used to detect the best way. Later this road was implemented in a real network data, s...
12
artículo
Publicado 2016
Enlace
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The main objective on this research is the development of finding the optimal parameters for a routing algorithm for network routers based on the ant algorithm described as AntNet. The optimum parameters for this type of algorithm improve a more efficient alternative to those given by the RIP, EIGRP and OSPF routing protocols, to be applied in a data network. This shall be tested in two networks and routers defined, taking the same characteristics for the three groups: RIP, OSPF and by the result provided by the genetic algorithm implemented using a static network. The system recognizes the best path between networks of routers, based on the principle of AntNet networks or networks of ants, which are the best way from exploring almost all roads, using estimergia to go there and make optimal. MatLab was used to detect the best way. Later this road was implemented in a real network data, s...
13
artículo
Publicado 2016
Enlace
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The main objective on this research is the development of finding the optimal parameters for a routing algorithm for network routers based on the ant algorithm described as AntNet. The optimum parameters for this type of algorithm improve a more efficient alternative to those given by the RIP, EIGRP and OSPF routing protocols, to be applied in a data network. This shall be tested in two networks and routers defined, taking the same characteristics for the three groups: RIP, OSPF and by the result provided by the genetic algorithm implemented using a static network. The system recognizes the best path between networks of routers, based on the principle of AntNet networks or networks of ants, which are the best way from exploring almost all roads, using estimergia to go there and make optimal. MatLab was used to detect the best way. Later this road was implemented in a real network data, s...
14
artículo
Publicado 2023
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Purpose: The theoretical debate of corruption's impact on economic growth remains unsettled, making it an empirical question. This study aims to investigate corruption's effect on BRICS countries' economic growth. Design/methodology/approach: A panel dataset on BRICS countries spanning 1996 to 2020 was used. Bias-corrected estimators in small dynamic panels were employed to estimate a growth model as a linear-quadratic function of corruption that accounts for cross-sectional dependence, endogeneity and unobserved heterogeneity due to country and time-specific characteristics. Findings: The results indicate that corruption is detrimental to economic growth in BRICS countries; the quadratic relationship implies corruption is less prevalent in some countries than others. Thus, governments of BRICS countries are encouraged to embark on anti-corruption policies to boost their economic perform...
15
artículo
Publicado 2020
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The pandemic of COVID-19 has shown that the information disseminated through peer-reviewed journals and accompanying online data sets is vital for decision-makers. However, we are currently seeing several deficiencies in open-data sharing mechanisms globally, and in particular Latin American countries, and therefore, this highlights the need for open access to data. Latin American and Caribbean countries have remarkable initiatives to publish ‘open-access’ science through the Scientific Electronic Library On-line (SciELO),1 comprising a network of 16 national open-access journal collections and included more than 1350 active titles. The SciELO collections publish the best journals from the most research-productive countries from Latin America and the Caribbean region. Moreover, the ‘LA Referencia’2 is a Latin American network of 10 countries whose open-access repositories share i...
16
artículo
Publicado 2024
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The financial sector faces difficulties in managing risks due to the increasing volume of structured and unstructured data, which complicates the identification of financial risks such as payment defaults. Traditional models are insufficient to address this problem, prompting the exploration of Big Data solutions. This study aims to review how Big Data architecture models can enhance the prediction and management of financial risks in banks. A systematic literature review was conducted, analyzing 32 relevant studies published between 2019 and 2023. The results indicate that various Big Data frameworks and architectures, such as those utilizing technologies like Apache Spark and Apache Storm, effectively process large data volumes in real-time. Additionally, data analysis techniques like machine learning were highlighted to improve accuracy in risk identification. This study concludes tha...
17
tesis de grado
Publicado 2022
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El presente trabajo detalla la implementación de Business Intelligence para mejorar la productividad del proceso de toma de decisiones frente al problema de datos almacenados en diversas fuentes haciendo dificultosa las consultas manuales y la generación de reportes gerenciales en la Empresa Newocean Technology S.A.C. La propuesta comprende la centralización de datos, determinación de necesidades de información del usuario y consulta intuitiva de los reportes automáticos generados en tiempo real, reflejando la reducción del tiempo y costo de generación de reportes asimismo la reducción en el porcentaje de inexactitud de estos. Se desarrolló la solución según la metodología de Inteligencia de negocios Hefesto dando como resultado un impacto positivo en la productividad del proceso de toma de decisiones. Se usó el diagrama Ishikawa, Diagrama de Pareto, la matriz de priorizaci...
18
artículo
Publicado 2023
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Purpose: As the influence of institutional investors over managerial decision-making grows, so does the importance of understanding the effect of institutional investor ownership (IO) on firm outcomes. The authors take a comprehensive approach to studying the effect of IO on earnings management (EM). Design/methodology/approach: The authors study the relation between IO and EM using a sample of 59,503 listed U.S. firm-year observations from 1981–2019. The authors proxy EM with earnings surprises and with accrual-based and real activity measures. The authors test for nonlinear relations and analyze changes resulting from the passage of the Sarbanes–Oxley Act. Findings: The findings support a positive IO-EM relation overall, but show that the relation is dynamic and heavily context-dependent with evidence of nonlinearity. The authors also find evidence that IO positively affects accrua...
19
artículo
The 21st century requires people to make good decisions based on thoughtful and reasoned thinking. It is the task of the university teacher to provide the necessary conditions to develop critical thinking by using strategies that place the student as the basis of teaching work. The objective of the research was to determine the relationship between the level of critical thinking and the level of learning of mathematics of students entering university. The research is based on the quantitative correlational scope approach with transectional, correlational design. The sample was 115 students belonging to two universities, one private and the other public, located in Lima, Peru. For data collection, two tests were administered: one to assess the level of critical thinking, and the other to assess the level of learning in mathematics. The results show that critical thinking and learning of m...
20
artículo
Publicado 2022
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The intelligent wireless system focuses on integrating with the advanced technologies like machine learning and related approaches in order to enhance the performance, productivity, and output. The implementation of machine learning approaches is mainly applied in order to enhance the efficient communication system, enable creation of variable node locations, support collection of data and information, analyze the pattern, and forecast so as to provide better services to the end users. The efficiency of using these technologies tend to lower the cost and support in deploying the resources effectively. The wireless network system tends to enhance the bandwidth, and the application of novel machine learning approaches supports detection of unrelated data and information and enables analysis of latency at each part of the communication channel. The study involves critically analyzing the ke...
