Repositorio Institucional de la Universidad ESAN
Not a member yet
581 research outputs found
Sort by
Proposal for a Model for Diabetes Detection Using Machine Learning Techniques
No full textCurrently a very relevant problem is diabetes, this disease is the cause of thousands of deaths and tends to grow in the coming years. The objective of the present research is to detect diabetes using Machine Learning techniques. For this purpose, the Indian PIMA database (PID) was used, which was extracted from Kaggle. Preprocessing techniques such as null value treatment and feature normalization were applied. Finally, various learning models such as Multilayer Perceptron, Neural Networks, Decision Tree, Support Vector Machines, K-Nearest Neighbors, Logistic Regression, Random Forest and Gradient Boosting algorithm were developed. From the best results obtained from the evaluation of the models, it was obtained that the best of them is the one generated by the Multilayer Perceptron Neural Networks and Support Vector Machine whose metrics were superior in Accuracy with 84.62% and Recall with 76.92%; however, in Precision it was surpassed by the Random Forest algorithm with 81.81%. It follows that both the Multilayer Perceptron and Support Vector Machine models accurately predicted the onset of diabetes, thus establishing their effectiveness in this predictive task, offering invaluable assistance to the healthcare sector. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024
Innovation in KIBS firms: the effects of innovation activities, employees’ level of education, and the sources in the supply chain
No full textThere has been a growing interest in the study of knowledge-intensive business services (KIBS) due to the important role that they play in the business processes of their clients. Even though extant literature assumes that KIBS firms are innovators, there is evidence that not all KIBS are equally innovative. Our exploratory research uses data gathered from the National Survey of Innovation in the manufacturing and KIBS industries and uses the LOGIT model on a sample of 311 Peruvian KIBS firms. The effects of innovation activities, employee level of education and the sources in the supply chain on developing innovations are determined. Findings indicate that not all innovation activities positively affect innovation. We found that most of these activities are related to technological innovation, rather than nontechnological innovation, and the hiring of graduated personnel favours the development of organisational innovation. However, the interplay with customers, suppliers and competitors gives no benefit concerning the development of innovation. Copyright © 2024 Inderscience Enterprises Ltd
Sentiment Analysis Based on Twitter Comments Using Artificial Intelligence Techniques to Predict Peruvian Presidential Election Results
No full textCurrently, the use of social networks as the main means of communication and expression has increased. In Peru, the social network Twitter is preferred by political leaders and is key for political campaigns. The present research aims to implement a sentiment analysis model based on Twitter comments using artificial intelligence techniques to predict the results in the Peruvian presidential elections. The applied methodology was based on 5 phases: dataset construction, preprocessing, feature extractions, model implementations and Evaluation. Word2Vec and Tf-idf techniques were used for feature extraction. Finally, different machine learning models were developed, such as logistic regression (LR), Support Vector Machine (SVM), random forest (RF) and logistic regression (RL) and MLP classifier. The best model results from the combination of the SVM algorithm with Word2vec vectorization has superior performance in the metrics 0.89 Accuracy and 0.88 Precision. However, Recall is lower compared to the Tf-idf vectorization (0.87 Recall) and both vectorizations have the same result in the 0.87 F1-Score metric. Finally, the results of the second-round show PPK winning by a minimal margin over Keiko, 16.1% and 15.3% respectively. However, the percentage of undecided voters is about 34% on average. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024
Factors influencing the profitability of small and medium-sized companies in the food sector; [Factores que influyen en la rentabilidad de las pequeñas y medianas empresas del sector gastronómico]
No full textThe food sector has been one of the most affected economic areas due to the restrictions that were put in place to mitigate the spread of Covid-19 during the pandemic. The purpose of this body of research was to determine the factors that affected the profitability of Chilean small and medium-sized companies in the food sector, from a contingency perspective and from the standpoint of resources and capability. To do this, quantitative research was conducted with a sample of 59 companies. The results of the logistic regression analysis indicated that when firms made three or fewer workers redundant, the probability that their performance would improve or remain the same rose by 422%. On the other hand, for each additional decision the firm made, this likelihood fell by 51%. Technology and size were not relevant for these types of companies. © Universidad de Santiago de Compostela
The ark of shared value: Using shared value creation to increase corporate social responsibility investments
No full textThe Ark of Shared Value is a fundamental guide for those involved in designing and implementing sustainable business projects. The Ark is a one-page tool that is easy to use and presents the key elements of sustainable projects. This tool incorporates visual thinking for sustainable projects, allowing designers to discuss and collaborate on the project effectively. Cesar Saenz offers the Ark of Shared Value as a tangible way to present sustainable projects, including the stakeholders involved, resources used, activities conducted, and benefits received for each stakeholder, all on a single page. Companies and organizations, as well as professionals who believe that doing business can enhance the environment and social well-being, can utilize The Ark of Shared Value. © 2024 Cesar Saenz. All rights reserved
Including the change in natural capital stock and environmental degradation in Peruvian mining GDP and NNP
No full textThis study adjusts the net national product (NNP) and gross domestic product (GDP) of the Peruvian mining sector by incorporating natural capital depreciation, new discoveries, and environmental degradation during the period 1994–2018. The results suggest that NNP has been overestimated, on average, by 172 % to 210 %, which is attributed to the omission of natural depreciation. When GDP was corrected, the overestimation fluctuated between 64 % and 72 %. This underscores the importance of including natural capital depreciation, especially in countries whose economy is highly dependent on extractive industries, as is the case of Peru.</jats:p
Evaluación del desperdicio de alimentos: normas y acciones para fomentar la circularidad
No full textEl crecimiento poblacional genera una mayor demanda alimenticia y, con ello, aumenta el desperdicio de alimentos. La lucha contra este problema inició en varios países con estrictas regulaciones que gestionan los residuos alimentarios. En el caso del Perú, se muestra un análisis de lo avanzado en el rubro. El objetivo del artículo es analizar el manejo de residuos alimentarios en el Perú y el mundo, tanto en normatividad y situación; para ello se realizó una revisión bibliográfica tomando en cuenta los lineamientos de circularidad en los alimentos.Los resultados obtenidos demuestran deficiencias en el marco regulatorio tanto peruano como mundial, con excepción de Europa. Se analizó el incremento de la generación de residuos alimentarios a nivel mundial en hogares, establecimientos minoristas y la industria del servicio. Los países coinciden en la preocupación por el aumento de los residuos y buscan enmarcarse en el modelo de circularidad.En el caso del Perú, ello implica modificar y mejorar la regulación con la participación de actores involucrados. Ante ello, se propone acciones para fomentar la circularidad en la gestión de alimentos con una visión de sostenibilidad, tales como propuestas de acciones nacionales y principios básicos, con la colaboración entre industrias, gobierno y sociedad civil
Implementation of a Web Application to Improve Tuber Farming Project Management in Family Agriculture
No full textAccording to the FAO (Food and Agriculture Organization of the United Nations), family farming units occupy about 80% of the global agricultural area and contribute more than 80% of the total value of food production worldwide. According to INEI (National Institute of Statistics and Informatics), in Peru there are 2.2 million people engaged in agriculture, 95% of whom are family farmers and cover almost 80% of the national food demand. However, they lack access to technological tools that facilitate the management of their crops and make it possible to evaluate profitability and make informed decisions. This lack of technological resources leads to frequent losses, and the farmer, lacking key information, is limited in improving his quality of life. The objective of this research is to implement a web application to improve tuber crop project management in family farming. For the development, the scrum development framework has been taken following the following phases: initiation phase; planning and estimation; implementation; review and retrospective; and launch. After implementation, a satisfaction survey was conducted with 50 farmers in the Huancavelica region, where a high score was obtained, ranging between 4 and 5 on the Likert scale for the 15 satisfaction questions. In addition, the reliability of the survey was verified by applying Cronbach’s alpha coefficient, obtaining a result of 0.76, which is within the range of excellent reliability. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024
Model Proposal for the Detection of Infected Potato Leaves Using Deep Learning
No full textIn Peru, the cultivation of potatoes holds significant economic importance, serving as a cornerstone of the agricultural sector. However, the potato crop faces persistent threats from various diseases and pests, impacting both yield and quality. Addressing this issue is crucial for both the economy and food security in agricultural communities. Therefore, the study aimed to find the best classifier of infected potato leaves in the Peruvian context. For this purpose, the dataset titled’Data for: Identification of Plant Leaf Diseases Using a 9-layer Deep Convolutional Neural Network’ was chosen due to its relevance in the agricultural domain. This dataset comprises 39 different classes of plant leaf and background images, collected from various locations worldwide, totaling 61,486 images. Naturally, we applied preprocessing, which consisted of three phases: Preparation of Processing Tools, Pixel Values Normalization, Organization of Dataset. These phases were necessary to prepare the data and tools required for subsequent analysis, ensuring that the data are in an appropriate format and that the algorithms can work more efficiently and accurately. Finally, different Deep Learning models were implemented: InceptionV3, Resnet, and Vision Transformer. The results were evaluated according to the Accuracy, Precision, Recall and F1-score metrics. The best model resulted in Vision Transformer, whose metrics were superior to the others with 96.00% Accuracy, 96.18% Sensitivity, 96.00%, Precision and 95.94% F1-score. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024
Implement a System Based on Hybrid Databases that Expedites Documentary Management for the Development of the Urban Area of the Municipality of Breña
No full textThe article addresses the problem of document management in the Municipality of Breña, where systems with SQL Server databases are used. The goal of the research is to improve query performance and user satisfaction by implementing a hybrid database and microservices architecture components. It seeks to optimize document management times and offer more efficient and fluid systems. To achieve this, a hybrid database was implemented that combined SQL Server and MongoDB (a NoSQL database). In addition, a microservices architecture was chosen to increase the flexibility and scalability of the system. The Scrum agile methodology was adopted to manage the project, dividing it into sprints with specific objectives. Database migration was prioritized using Python libraries and the development of microservices components. In addition, a dummy, a desktop application, was created to perform concept tests and validate the correct functioning of the microservices API. This hybrid approach and the use of the Scrum methodology proved to be effective in optimizing document management in the Municipality of Breña, providing tangible improvements in system performance and efficiency. Of which based on the results it was achieved greater efficiency in municipal management, data integration and increased ability to adapt and grow. On this, the results of the survey are based on questions related to the four dimensions around the independent variable showing an existence of Spearman correlation supporting to take a question from each dimension which showed results of “Strongly agree” and “Agree” in the dimensions of 40%, 32.5%, 37.5% and 35%. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024