En la presente investigación se realizará la evaluación y mejora de la defensa ribereña del rio Llullan del distrito de Caraz, la cual tiene como propósito identificar y evaluar las zonas con vulnerabilidad a los desbordes, en esta investigación se formulo como problema ¿La evaluación del muro de gaviones mejorará la defensa ribereña del río Llullan, distrito de Caraz, provincia de Huaylas, departamento Ancash – 2024? Y para esto se estableció como objetivo general Evaluar el muro de gaviones para mejorar las defensas ribereñas del rio Llullan, distrito de Caraz, provincia de Huaylas, departamento Ancash – 2024, el proyecto se desarrolló con una metodología de nivel cualitativo, tipo descriptiva y no experimental, utilizando como población la defensa ribereña del rio Llullan y como muestra el muro de gaviones del rio Llullan, en la investigación concluimos que el mu...

Uno de los grandes retos de la agricultura moderna es la falta de eficiencia de las técnicas de cultivo frente al aumento de la población mundial. Diversas estrategias se han puesto en marcha con el finde abordar esta situación problemática, incluido el Internet de las Cosas (IoT), en busca de mejorar la calidad de los cultivos y desarrollar métodos para el cultivo agrícola más rentable. El presente estudio realizo un análisis exhaustivo y metodológico de 50 artículos científicos publicados entre el 2020 y el 2025. Los objetivos planteados buscan determinar las principales aplicaciones de IoT en la agricultura, categorizar los de sensores más utilizados en el cultivo agrícola, examinar los protocolos de comunicación e identificar las políticas de seguridad implementadas en las aplicaciones de agricultura de precisión.

La investigación tiene como título “Estrategias Competitivas Genéricas y el Posicionamiento de las Orquestas Musicales de la Ciudad de Huaraz, 2015”. Este trabajo se planteó como objetivo determinar la incidencia que hay entre estas dos variables. A través del diagnóstico transversal, no experimental de tipo descriptivo correlacional se realizó una encuesta orientada al público con la premisa de haber participado en algún evento social donde haya participado una orquesta de la localidad, objeto de estudio. Para la prueba estadística se usaron las pruebas para medidas ordinales y nominales; el procesamiento de los datos se hizo a través del proceso estadístico del software SPSS. Como resultado, se ha identificado que el empleo de las estrategias competitivas genéricas se hace importante para incrementar el posicionamiento de las orquestas de la ciudad de Huaraz. Sin embar...

This paper is intended to determine the extent to which the M-learning model with methodological strategies improves the learning of student’s undergraduates of the Systems Engineering career. The method used was developed through a study of quasi-experimental type and conformed by an experimental group composed of 25 students of section B and a control group by 25 students of section A of the subject of Software Design Patterns. of the Autonomous University of Peru. To obtain the results of the inferential analysis, the Student T test and the Mann Whitney U test were used. Likewise, a prestest and a posttest were applied to evidence the learning improved, previously tests of validity and reliability were performed in each case, the corresponding calculations were subsequently made for the test of the hypotheses. After applying the M-learning model with methodological strategies, signi...

This paper proposes a technology adoption model called TAM 4, based on the TAM model considering the trust and perceived risk factors to the adoption of technology in response to governments’ concern to achieve competitiveness in the most important economic activities. The methodology used considers the predictive method. The sample was selected from 67 companies related to foreign trade that carry out agro export tasks, with a confidence level of 90% and an error percentage of ± 10% and the 0.787 of Cronbach’s Alpha obtained for the instrument’s validation. In conclusion, 97% of the companies informally adopt technology. This shows that 68% of the companies surveyed in the sector would be willing to adopt the model.

This study explores the potential of converting domestic graywater into electrochemical energy as a sustainable energy solution amidst growing environmental concerns. Employing a custom-designed galvanic cell prototype, the research aims to transform the chemical energy in graywater into electrical energy through redox reactions, quantifying the electrical potential generated. Results demonstrate the prototype's success in generating an average no-load voltage of 5.1907 volts, effectively powering low-power devices like LEDs and validating the viability of greywater as an alternative energy source. However, the study acknowledges limitations such as the prototype's small scale and the potential impact of varied graywater compositions on energy efficiency, suggesting cautious application at larger scales. Future research directions include enhancing prototype efficiency and scalability, u...

To identify the most relevant factors that a knowledge management model (KM model) should consider to contribute to the satisfaction of the response times to the information technology requirements (RTITR) of a financial institution in Lima (Peru) was the main objective of the research, for this a quantitative approach was considered in which the ordinal logistic regression analysis was applied to a sample consisted of 31 specialists from the systems area of the financial institution under study to whom the questionnaire was applied to identify the necessary factors according to their relevance in the KM model to contribute to the satisfaction of the RTITR which has been the concern of the specialists from the systems area to generate fast responses, therefore, with the ordinal logistic regression analysis using the significance and orientation of coefficients, the most relevant factors ...

The purpose of the research was to determine the influence of industrial wastewater treatment using the Lemna Minor aquatic plant. Certain varieties of macrophyte plants can absorb or retain various contaminants. Thanks to this, it has been determined that the variety known as Lemna Minor presents this type of property. Three treatment trials were carried out varying the amounts of Lemna Minor (100, 200, and 300g). They are keeping constant the retention time of 10 days that were analyzed at 3, 6, and 10 days after the treatment and with a constant volume of the residual effluent. The results indicate that in terms of the parameters that determine organic contamination, BOD was reduced by (61 %); COD was reduced by (68 %) and the concentration of total suspended solids by (61 %).

The purpose of this research is the design of a green infrastructure that allows a regional conservation area to revalue the Ventanilla wetlands to promote ecotourism through spaces for the conservation of natural resources, turning it into a tourist attraction. The proposal considers design and construction criteria with adequate technology, biodegradable, and sustainable materials where environmental impact is minimized in this context. The collection of information through field visits and the use of different software for the topographic survey. Results show that the infrastructure design proposed was validated by a survey of potential users of the place, with 75% of the interviewees agreeing with the design proposal that allows interaction and harmony with nature, giving it a landscape value, generating local, national, and international visitors. The value is in the ecosystem servi...

Machine learning is used in medicine to diagnose diseases quickly and accurately, the results of which support the physician in making correct decisions. Pleural effusion, a common disease in which 50% of patients are diagnosed with cancer. The objective was to describe machine learning techniques that are used for the diagnosis of cancer cells in cytological images of pleural fluid. For the systematic review, the PICO strategy and the PRISMA methodology were used. For the research questions, selection criteria were established, identifying 142 articles, selecting 18 articles after filtering. The techniques used were U_Net with 8 articles, Transfer Learning with 4 articles, Support vector machine with 3 articles, CNN with 3 articles, ANN with 3 articles, X-Boost with one article, K-Means with one article and other ML techniques with 4 articles. Regarding the data set, the most used were ...

neumonia has become the respiratory disease that continuously causes deaths in the world; as a response to this serious problem, a literature review is performed to identify Deep Learning classification models for pneumonia detection with an accuracy higher than 95%. For the identification of the models, different architectures such as InceptionV3, MobileNet, MobileNetV2 Xception, VGG16, VGG19, DenseNet201, NasnetMobile, CNN, and LSTM were evaluated. Although they all show very acceptable accuracy indicators, which justifies their evaluation for model identification, the datasets were evaluated with chest X-ray images in different categories. As a result, it was determined that ResNet152V2 achieved an accuracy of 99.22%, which is considered one of the best models for pneumonia detection.

The objective of this work is to implement the logistic regression technique in datasets of gyms to identify and make a respective analysis for a correct segmentation of clients and, in this way, maximize the possibility of retaining clients; this will also allow us to rule out wrong decisions and incorrect assumptions, in addition to optimizing management according to customer data, which will be vital for a correct loyalty of gym users. The precision calculated the loyalty by the logistic regression algorithm considering important factors such as the rate of abandonment.

The implementation of chatbots in multiple platforms with which man interacts has allowed automating processes and being able to respond to requests, one of its applications is the educational field, where they are still experimenting with good results in some areas and in others analyzing their feasibility, the deployment of this technology has been used both in basic education and in higher education, the former mainly addresses the resolution of simple queries facilitating the work of the teacher, and the latter seeks to go further by offering itself as a learning assistant. This work focuses on understanding the impact that chatbots have on education and their integration in some areas of the educational process, analyzing the results offered by other research and real applications. Chatbots have proved to be effective and increase user efficiency by providing information and being a...

The evolution of data science and the constant challenge of carrying out different processes using a few resources with simultaneous personalization has promoted interest in the development of voice cloning. Nowadays, different machine learning techniques are used, given their efficiency in generating relationships across multiple parameters. In this regard, we evaluated the best-performing models and the different process optimization strategies within this sector, where through neural network models separated modularly by their functionality, it is possible to generate independent processes taking into account the most significant number of linguistic factors in the generation of the voice, thus obtaining significant results of a clear improvement in the whole process of synthesizing the voice of a target speaker.

The present investigation is the study of the Peru case on the strategies implemented by the Peruvian government from the detection of patient zero with the objective of containing the spread of the pandemic decreed by the WHO for the coronavirus COVID-19. The behavior of the evolution of the number of infected from March 6 to April 24, 2020 is detailed. The first groups of measures were adopted from the detection of patient zero until the declaration by the WHO (World Health Organization) as a pandemic, accompanied by the implementation of protocols coupled to our health system and measures taken by the Peruvian government through Supreme Decree 008-2020-SA declaring a national health emergency for a period of 90 days. Subsequently, a series of measures evaluated were taken from March 12 to 26 and from March 27 to April 24, 2020, the date this study ends, detailing the strategies consid...

La presente investigación es el estudio del caso Perú sobre las estrategias implementadas por el gobierno peruano a partir de la detección del paciente cero con el objetivo de contener la propagación de la pandemia por el coronavirus COVID-19 decretada por la OMS. Se detalla el comportamiento de la evolución de la cantidad de infectados a partir del 6 marzo al 24 de abril 2020. El primer grupo de medidas se adoptaron a partir de la detección del paciente cero hasta la declaración por la OMS (Organización Mundial de la Salud) como pandemia, acompañado de la implementación de protocolos acoplados a nuestro sistema de salud y medidas tomadas por el gobierno peruano mediante Decreto Supremo 008-2020-SA declarando emergencia sanitaria a nivel nacional por un plazo de 90 días. Posteriormente se pasó a tomar una serie de medidas evaluadas desde el 12 al 26 de marzo y del 27 de marzo...

Today X has become one of the most important socialnetworks for expressing opinions and interests on the web.The large amount of data generated allows automatedsystems to profile users based on gender, nationality andthematic interests. There are difficulties in this process notonly because of the short content, but also because of theambiguity and the use of several languages.The goal of this proposal is to generate a deep learningmodel using BERT that is able to identify demographic andthematic attributes from tweets. Pre-trained models of theBERT and Multilingual BERT type will be used, applied on PAN Author Profiling Task (CLEF 2019) corpora in English and Spanish.The proposed work will deepen the analysis using supervised classification data for gender and nationality classification and topic extraction through unsupervised techniques, such as LDA and BERTopic. These options include...