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Vol. 3 (2024)

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Authors in this issue:

Mathews Emmanuel, J. Jabez Adrian Padilla-Cancho, Gibson Quispe-Minaya, Brian Meneses-Claudio, Gustavo Zarate-Ruiz Carolina Torres-Sipión, Franz Brito-Trujillo, Néstor Felix-Brisolesse, Moises Solis-Pozo, Julio Evangelista-Azañero, Camila Morales-Susanibar, Paul Mallqui-Rivera, Víctor Linares-Cabrera, Felix Caro-Soto, Damaris Medina-Palma Laura Alejandra Almanza Ríos, Rubén Oliver Espinoza, Hortensia Gómez Viquez R. Uma Maheswari, N. Sudha Patricia Elena Ramos La Rosa, Ana Juliani Rodriguez Cadillo, Maria del Rosario Grados Olivera, Santiago Ernesto Ramos y Yovera, José Luis Ausejo Sánchez Sumita Grewal, Manoj Manuel, Roy P Veettil Sivakumar Karuppan, Krishnaprasath V T, Pradeep V, Sruthi S Madhavan Polo-Gonzales S, Samar-Ventocilla J, Meneses-Claudio B, Zarate-Ruiz G Ernestina Choccata-Cruz, Rosa Villanueva-Figueroa, Veronica Galvez-Aurazo, Gustavo Zarate-Ruiz, Elder Miranda-Aburto José Antonio Hernández Salinas, Ramsés Daniel Martínez García, Mijael Altamirano Santiago Elias Mejia-Mejia, Francis Díaz-Flores Oscar Yabar-Velarde, Yeny Irigoin-Silva, Brian Meneses-Claudio, Gustavo Zarate-Ruiz María Cruz Cuevas Álvarez, Marcos Pérez Mendoza, Perla del Rocío Rojas León, Carlos David Zetina Pérez, Hilda Ofelia Eslava Gómez, Jeniffer Yajabibe Maldonado Guillén K. Prabavathy, M. Nalini Javier Perez-Nuñez, Ana Sofia Quispe-Ubilla, Jenny Gutiérrez-Flores, Brian Meneses-Claudio Paul Ríos-Jimenes, Brenda Solis-Briceño, Brian Meneses-Claudio, Gustavo Zarate-Ruiz Edwin Gustavo Estrada-Araoz, Guido Raúl Larico-Uchamaco , Franklin Jara-Rodríguez, Ronald Pachacutec-Quispicho M. Yuvaraja, S. Sureshkumar, S. Joseph James, S. Thillaikkarasi Rebeca Pablo-Huamani, Wilder García-Vázquez, Ruth Karina Alejandro-Bustamante, Cecilia Patricia Sánchez-Llontop, Jhonny Richard Rodriguez-Barboza Serafeim A. Triantafyllou , Theodosios Sapounidis, Yousef Farhaoui N. Murali, S. Palani Murugan, K. Sivakumar, Manojkumar Vivekanandan, Mishmala Sushith, S.Manikandan V. S. Lavanya , R. Anushiya Ahmed EL YOUSSEFI , Abdelaaziz HESSANE, Imad ZEROUAL, Yousef FARHAOUI K.Babu, M.S.Roobini, S.Prabhakaran, S.Sadagopan, N.Kanimozhi Manivannan R, G.Venkateshwaran, D. Menaga, S. Sivakumar, M. Hema Kumar, Minu Susan Jacob Elizabeth Camposano-Castillo, Roberto Mañuico-Yupanqui, Brian Meneses-Claudio, Gustavo Zarate-Ruiz Miguel Ángel Vite Pérez B. Karthiga, Sathya Selvaraj Sinnasamy, V.C. Bharathi, Azarudeen, Sherubha. P R. Manivannan, S. Manikandan, R. Vadivel, S. Sophana Jennifer Elvis Mauricio Carranza; Freddy Verde-Bocanegra, Brian Meneses-Claudio, Gustavo Zarate-Ruiz Luis Alberto Rojas Farfán, Martha García López Ronald Vladimir Revelo Mera , Bolívar Alfredo Potes Berzosa, Alejandro Julián Terreros Bueno, Geovanna Paola Jaramillo Calderón, Rómulo Daniel Vargas Sánchez ,

Published: March 6, 2024

Contents

2024-03-07 Original
Classifying alzheimer's disease from sMRI data using a hybrid deep learning approaches

The chance of developing "Alzheimer's Disease (AD)" increases every 5 years after 65 years of age, making it a particularly common form of neurodegenerative disorder among the older population. The use of "Magnetic Resonance Imaging (MRI)" to diagnose AD has grown in popularity in recent years. A further benefit of MRI is that it provides excellent contrast and exquisite structural detail. As a result, some studies have used biological markers backed by "structural MRI (sMRI)" to separate AD populations, which indicate differences in brain tissue size and degradation of the nervous system. The lack of properly segmented regions and essential features by the existing models might affect classification accuracy for AD. The categorization of AD in this study is based on sMRI. In this research, the hybrid Deep-Learning Models "SegNet and ResNet (SegResNet)" have been proposed for segmentation, feature extraction, and to classify the AD. SegNet network is used to identify and segment specific brain areas. Edges and circles are the SegNet's first levels, whereas the deeper layers acquire more nuanced and useful features. SegNet's last deconvolution layer produces a wide range of segmented images linked to the 3 categorization labels "Cognitive Normal (CN)", "Mild Cognitive Impairment (MCI)", and "AD" which the machine has earlier found out. To increase classification performance, the attributes of each segmented sMRI image serve as strong features of the labels. To enhance the feature information used for classification, a feature vector is built by combining the values of the pixel intensity of the segmented sMRI images. ResNet-101 classifiers are then used for characterizing vectors to identify the presence or absence of AD or MCI in each sMRI image. In terms of detection and classification accuracy, the proposed SegResNet Model is superior to the existing KNN, EFKNN, AANFIS, and ACS approaches

By Mathews Emmanuel, J. Jabez

2024-01-01 Original
Neuromarketing and consumer behavior of the company Alimentos Procesados Agrícolas S.A.C., in Los Olivos 2022

Neuromarketing strategies are very important for companies to attract and retain customers or end consumers. But nowadays these strategies are not being applied in our country in a professional way. Therefore, the study developed proposes to analyze neuromarketing in the behavior of consumers of the company Alimentos Procesados agrícola S.AC. The methodology proposed in this research was of qualitative approach with a descriptive scope. The results of the interviewees indicate that they do not apply neuromarketing correctly or do not have professional knowledge of neuromarketing. In conclusion, the importance of applying the study proposed in this research work is identified because it provides many benefits and improvements to their businesses or companies.

By Adrian Padilla-Cancho, Gibson Quispe-Minaya, Brian Meneses-Claudio, Gustavo Zarate-Ruiz

2024-03-28 Original
Management of information systems projects in virtual environments and distributed teams

In today's business environment, effective information systems project management has evolved with the increasing adoption of virtual environments and distributed teams. This article addresses the challenges and best practices in managing information systems projects in virtual contexts, where teams work remotely and collaborate through digital tools. It highlights the advantages and pitfalls of this modality, as well as strategies to maximize efficiency and communication in this type of projects.
In this context, the article addresses the challenges and best practices in managing information systems projects in virtual environments and with distributed teams. Through a comprehensive review of the current literature and the analysis of relevant cases, key strategies to optimize communication, coordination and success in this type of projects will be explored.

By Carolina Torres-Sipión, Franz Brito-Trujillo, Néstor Felix-Brisolesse, Moises Solis-Pozo, Julio Evangelista-Azañero, Camila Morales-Susanibar, Paul Mallqui-Rivera, Víctor Linares-Cabrera, Felix Caro-Soto, Damaris Medina-Palma

2024-03-07 Original
Open innovation in the pharmaceutical industry: subject mapping by bibliographic coupling

This paper aims to identify the thematic structure of the literature on open innovation in the pharmaceutical industry using bibliometric analysis based on bibliographic coupling, based on the publications that comprise the H 26 index for the topic, according to Scopus. The publications coupled using VosViewer software yield nine clusters. Once these were organized, we reviewed their respective publications to discuss the subject matter of each one. Among the most relevant findings, five relevant clusters were identified: on open innovation models, governance aspects, financial performance, intellectual property and pioneering work covering the broad spectrum of innovation and competitiveness in the pharmaceutical industry.

By Laura Alejandra Almanza Ríos, Rubén Oliver Espinoza, Hortensia Gómez Viquez

2024-03-10 Original
An efficient fake news classification model based on ensemble deep learning techniques

The  availability  and expansion of  social media has made it  difficult to distinguish between fake and real news. Information falsification has exponentially increased as a result of how simple it is to spread information through sharing. Social media dependability is also under jeopardy due to the extensive dissemination of false information. Therefore, it has become a research problem to automatically validate information, specifically source, content, and publisher, to identify it as true or false. Despite its limitations, machine learning (ML) has been crucial in the categorization of information. Previous studies suggested three-step methods for categorising false information on social media. In the first step of the process, the data set is subjected to a number of pre-processing processes in order to transform unstructured data sets into structured data sets. The unknowable properties of fake news and the features are extracted by the Lexicon Model in the second stage. In the third stage of this research project, a feature selection method by WOA (Whale Optimization Algorithm) for weight value to tune the classification part. Finally, a Hybrid Classification model that is hybrid with a fuzzy based Convolutional Neural Network and kernel based support vector machine is constructed in order to identify the data pertaining to bogus news. However using single classifier for fake news detection produces the insufficient accuracy. To overcome this issue in this work introduced an improved model for fake news classification. To turn unstructured data sets into structured data sets, a variety of pre-processing operations are used on the data set in the initial phase of the procedure. The unknowable properties of fake news and the features are extracted by the Lexicon Model in the second stage. In the third stage of this research project, a feature selection method by COA (Coati Optimization Algorithm) for weight value to tune the classification part. Finally, an ensemble of RNN (Recurrent Neural Networks), VGG-16 and ResNet50.A classification model was developed to recognise bogus news information. Evaluate each fake news analysis' performance in terms of accuracy, precision, recall, and F1 score. The suggested model, out of all the methodologies taken into consideration in this study, provides the highest outcomes, according to experimental findings

By R. Uma Maheswari, N. Sudha

2024-03-07 Original
Environmental awareness as a transfiguring factor of the sustainable behavior of the visitor to the Lachay National Reserve

The objective of the research was to understand and explain the relationship between environmental awareness as a factor in transforming the sustainable behavior of visitors to the Lachay National Reserve. The research type is applied, with a mixed research approach and descriptive research method, using a sequential explanatory mixed method and a non-experimental and cross-sectional research design, with a correlational and explanatory scope. The population consisted of 19,326 visitors, with a quantitative method sample of 377 visitors and a qualitative method reaching saturation level in 15 interviews. The applied techniques included observation, document analysis, structured interviews, and surveys. The research resulted in the rejection of the null hypothesis in the quantitative analysis, confirming that environmental awareness is linked to the transformation of sustainable behavior among visitors to the Lachay National Reserve, with a Spearman's Rho correlation coefficient of 0.584, which is statistically significant and moderately positive, with a p-value of 0.000. In the qualitative analysis, environmental awareness transforms sustainable behavior through psychological factors such as environmental-cognitive knowledge, allowing the identification of environmental concerns, and landscape-affective factors. The interaction of cognitive and affective factors enables the generation of pro-environmental behaviors and attitudes

By Patricia Elena Ramos La Rosa, Ana Juliani Rodriguez Cadillo, Maria del Rosario Grados Olivera, Santiago Ernesto Ramos y Yovera, José Luis Ausejo Sánchez

2024-03-11 Original
Principles and Procedures of Material Development in the Evolving ELT Scenario

There are many linguists who tried to define an important aspect of ELT which is the Curriculum. Curriculum refers to the specific blueprint for learning that is derived from desired results—that is, content and performance standards (be they state-determined or locally developed) (Dundar, 2017). According to Tomlinson, the term "material development" refers to all of the procedures used by professionals who create and/or utilize language learning resources, such as adaptation, design, production, exploitation, evaluation, and research. Curriculum designing in itself is a complex process which involves a lot of factors and not just writing or teaching a curriculum. As part of the development process, curriculum design and evaluation is crucial to the teaching of English and other subjects since it outlines the methodologies, procedures, strategies, and activities used to teach the language and its content. (Brown, 1995).

Reflecting on the historical context of English language instruction, we don’t see  much done before the 20th century. ELT gained popularity with migrants moving to English-speaking countries. The importance of English also increased in terms of business and trade. The expansion of and significant growth of various media sources such as radio, movies, and television, supported English to become more popular. Eventually, lots of research was initiated in the area of English language teaching methods and material development. In fact, many teaching methods have been tried and tested in the last one century in pursuit of the most effective method. The search for new methods is still on to improvise ELT in the current dynamic classrooms

By Sumita Grewal, Manoj Manuel, Roy P Veettil

2024-03-10 Original
Enhancing Public Safety: A Real-time Social Distance Monitoring with Computer Vision and Deep Learning

In spite of the fact that the COVID-19 epidemic has lately afflicted millions of individuals all over the world, the number of people who are being affected is continuing to climb. In response to the ongoing pandemic scenario throughout the world and in an effort to stop the virus from further disseminating, a number of governments have initiated a number of groundbreaking preventative measures. One of the most effective methods for warding off the spread of infectious diseases is maintaining adequate social distance. In the context of a real-time top view environment, the purpose of this study survey is to propose the use of a social distance framework that is built on deep learning architecture as a preventative strategy for maintaining, monitoring, managing, and lowering the amount of physical connection that occurs between individuals. In order to identify people in the photographs, we made use of a number of different deep learning detection models, including R-CNN, Fast R-CNN, Faster-RCNN, YOLO, and SSD. Because of the significant differences between the top and bottom views of a human's appearance, the architecture was trained using the top view human data set. After that, the Euclidean distance is utilised to derive a pair-wise distance estimate between the individuals depicted in a picture. Using the information obtained from a detected bounding box, one may determine where the centre point of a single detected bounding box is located. A violation threshold is constructed, which is determined by the information of a person's distance to a pixel and determines whether or not two people are in breach of social distance.

By Sivakumar Karuppan, Krishnaprasath V T, Pradeep V, Sruthi S Madhavan

2024-01-01 Original
Training Management in the Work Performance of Employees at Samar Ingenieros Sac - 2022

En los últimos años la gestión de capacitación permitió el buen crecimiento y mejora del rendimiento de los trabajadores, esto significa que el conjunto de actitudes como aptitudes, es la capacidad de aclimatarse a estos tipos de cambios que se genera en el trabajo según las circunstancias, de manera que ciertas organizaciones al no realizar dichas capacitaciones, en ciertas ocasiones el desenvolvimiento por parte de los trabajadores no es la correcta, ya que en muchas ocasiones no tienen conocimiento.

En el ámbito internacional Castañeda de Armas et. al (2018), menciona que en cuba se realizó la investigación relacionada a la realización de las estrategias de capacitación que se pondrán en marcha, para puedan mostrar resultados y el cambio que generaría sobre el desempeño laboral en las organizaciones. Ya que, esto puede beneficiar al máximo, mejorando los bienes de aprendizaje de los empleados y el área de recursos humanos.

De acuerdo, al ámbito Nacional, Parra-Penagos et. al (2016) indica que todas las empresas tienden a estar obligados a hacerse cargo de las capacitaciones que recomiendan las áreas de recursos humanos, de manera que, esto será como un método de re-potencialización dentro del desempeño de cada trabajador, mejorando su eficiencia, llegando esto a dar resultados positivos a la organización. Asimismo, nos indican que el propósito de la capacitación es entender las funciones de ciertas actividades específicas que se encuentran derivadas al desempeño laboral.

A nivel local, la empresa tiene ciertos problemas con los trabajadores directamente. Debido a que en diversas ocasiones exigen que realicen trabajos que los colaboradores no tienen conocimiento, esto sucede porque, la empresa no invierte en gestionar capacitaciones, para poder tener actualizado a todos sus colaboradores, para que de esa manera su desempeño laboral sea el adecuado y esperado por la empresa. Esto en más de una vez provoco la renuncia de los trabajadores que no se sentían cómodos dentro de la organización. No obstante, mediante este trabajo planteando el siguiente objetivo, la mejora de la gestión de capacitación y esto pueda dar un buen desempeño laboral por todos los colaboradores.

La presente investigación se realizó con el objetivo de determinar cómo la implementación de la gestión de capacitaciones mejora el desempeño laboral de los trabajadores en la empresa SAMAR INGENIEROS SAC durante el periodo 2019 – 2021

By Polo-Gonzales S, Samar-Ventocilla J, Meneses-Claudio B, Zarate-Ruiz G

2024-03-06 Original
Regional Educational Policies and Critical Interculturality in Rural Areas of the Province of Abancay - Apurímac, 2023

The research work was carried out with the aim of analyzing regional educational policies and critical interculturality in secondary education in rural areas of the province of Abancay, department of Apurímac, 2023. The research is basic, qualitative and design-based, phenomenological-hermeneutic. The study population consisted of specialists, principals, teachers and students of the secondary education level of rural areas of the UGEL (Local Educational Management Unit) Abancay and the sample consisted of: 4 specialists from the DREA (Regional Directorate of Education of Apurímac), 3 specialists from the UGEL Abancay, secondary level, 6 rural education teachers from the EBR (Regular Basic Education),  secondary school level, 6 directors and 6 students from rural schools in the province of Abancay. The following data collection instruments were used: semi-structured interview guide, documentary review form and non-participant observation guide. From the research it is concluded that the PERs (Regional Educational Policies) of Apurimac do not implement strategies of CI (critical interculturality) and the educational communities of rural schools do not know about the current PER (Regional Educational Project), but the native students demand the vindication of their language in educational and social processes

By Ernestina Choccata-Cruz, Rosa Villanueva-Figueroa, Veronica Galvez-Aurazo, Gustavo Zarate-Ruiz, Elder Miranda-Aburto

2024-03-13 Original
Community resilience: the case of Asunción Ixtaltepec Oaxaca

Community resilience is the process by which the people who make up a population develop cognitive, socio-affective and behavioral mechanisms to face events that disrupt their balance. For instance, natural catastrophes, economic crisis or the presence of social factors, such as violence, which otherwise drive people to deploy personal and collective resources in order to mitigate its impact. The objective of the study was to analyze how the residents of the town of Asunción Ixtaltepec in the state of Oaxaca developed resilient ways to face the psychosocial consequences of the 2017 earthquakes, for which a Community Action Intervention Program was developed for the benefit of 420 people, whose age range was from 15 to 69 years. The data obtained reports that 81% of the people developed community resilience, considering as main tools: a) favorable cognitive assessment about strengthening cohesion and social ties among the population, b) development of tranquility and psychosocial harmony as part of the recognition of collective actions to reduce the impact of seismic activity in the region and, c) the promotion of actions to reduce the psychological and psychosocial impact of seismic events.

By José Antonio Hernández Salinas, Ramsés Daniel Martínez García, Mijael Altamirano Santiago

2023-11-11 Original
Inverted virtual classroom in the learning paradigm

This paper sustains the thesis that the central problem of pedagogy, and of education in general, is the student's learning and not, as is commonly asserted, the professor's teaching or, that they are integrated processes: teaching-learning. The 2020 pandemic has forced to conduct graduate studies virtually, which has shown that, in the asynchronous phase of the process, students perform learning, so we have formulated the following hypothesis: The groups of graduate students who studied virtually, improve their learning levels compared to groups of graduate students who studied face-to-face. To test this hypothesis we have worked with two independent samples. The first one constituted by 300 graduate students who took face-to-face studies in the academic semesters 2019-I and 2019-II, whose final average was 16,3033, and the second one, constituted by 300 graduate students who took virtual studies in the academic semesters 2020-I and 2020-II and whose final average was 17,7533. The Student's t-test shows that the group of students who took virtual studies significantly improved their learning levels, since the P-value found is 0,000, less than α chosen: 0,05, a result that leads to rejecting the null hypothesis and maintaining the working hypothesis in force.

By Elias Mejia-Mejia, Francis Díaz-Flores

2024-01-01 Original
Service quality and customer loyalty in a movie theater chain in North Lima, 2022

The current market, in view of the constant changes and globalization, is becoming more and more demanding, so that the quality of service is also becoming more and more demanding; the client of the cinema sector is becoming more and more demanding of new platforms and trends that offer comfort and diversity to the public. In view of this, the present research was proposed to analyze the link between service quality and customer loyalty in a chain of movie theaters in North Lima, 2022. It was based on measuring the level of correspondence between the level of service and the loyalty of frequent customers, in a natural environment, without manipulating the variables, in order to define the behavior of the variables, a statistical analysis was performed. In such a way that the data were collected through a questionnaire applied to 90 customers. The data processing in SPSS allowed to determine a correlation coefficient of 0,685. Therefore, customers highly value the experience during the service offered by the employees during their consumption, considering it as a primary criterion in the decision to repurchase, so that according to the quality received is the customer loyalty

By Oscar Yabar-Velarde, Yeny Irigoin-Silva, Brian Meneses-Claudio, Gustavo Zarate-Ruiz

2024-03-06 Original
Internationalization of the curriculum: Connectivism approach supported by relational leadership.

Introduction: previous to the world pandemic covid-19, professors from a Mexican Public HEIs, located in the south of the country, had been implementing educative platforms as an internationalization of the curriculum strategy to include technology in their teaching, specifically in DACEA division. The first institutional platform implemented in 2004 was Moodle, Socrative, and Edmodo was the second step by a group of 20 out of 250 professors until 2020 when Microsoft Teams became the institutional educative platform. Method: the objective of this qualitative article is to characterize the roles and responsibilities of educational actors in the new digital management derived from the covid-19 pandemic in a Mexican Public HEI. Results: The findings indicate that the institution homologated the use of an educative platform at an institutional level, a training on the use of this new platform was given only covering the technical aspects, but there was still the pedagogical training missing for Flipped Classroom Methodology. The Syndicate leader with the aid of a small group of active professors, provided an online training course oriented towards the certification of digital competences with the participation of 120 professors from the 12 areas of the university. This work between the main educative actors: the institution and the syndicate leaders along with the professors has created the foundations for university engagement and a new administrative culture of collaboration. Conclusion: it is concluded that all educative parties when properly engaged can lead to the completion of objectives avoiding change resistance that sometimes arises specially when professors migrate from present mode to a distance mode.

By María Cruz Cuevas Álvarez, Marcos Pérez Mendoza, Perla del Rocío Rojas León, Carlos David Zetina Pérez, Hilda Ofelia Eslava Gómez, Jeniffer Yajabibe Maldonado Guillén

2024-03-07 Original
Deep Learning Enabled Whale Optimization Algorithm for Accurate Prediction of RA Disease

Whale Optimization Algorithm (WOA) is an optimization technique and based on food foraging behavior of whales. It has been applied in many domain including processing of images, framework controls, and ML (machine learning). WOA assists in choosing the right parameters required for Deep Neural Networks. This work uses DNN to examine metacarpophalangeal (MCP) rheumatoid joint discomforts in patients from diagnostic medical images including X-rays or Magnetic Resource images. The use of WOA enhances resultant outcomes of DNN as it searched for optimal solutions within search spaces, instead of getting trapped in local minima found by gradient descent. The combination of WOA and DNN for grading MCP rheumatoid arthritis can provide an efficient and accurate solution for medical practitioners and researchers

By K. Prabavathy, M. Nalini

2024-01-25 Original
The good practices of green it in energy saving and its influence on the cost of electrical service of a higher educational center, in the district of Surco - Lima 2022

This research is based on the study of how the good practices of GREEN IT influences energy savings and the cost of electricity service in a higher education center, which mentions the importance and positive impact of using GREEN IT in organizations, which promotes energy efficiency and sustainability of various technological devices, and to this is added the benefit of preserving both natural and energy resources. These good practices of green economy, the correct use of technologies and processes is proven in this research that directly impacts the costs that can be incurred by the organization for the execution of its activities, as well as the contribution to the care of the environment with the decrease of Co2 produced by each action and resources used habitually. The objective of this research is to determine how the good practices of GREEN IT in energy saving influence the cost of a higher education center in the district of Surco - Lima 2022. For the above mentioned and to measure the good practices employed in the institution, a questionnaire and the evaluation of fixed and variable costs were used to analyze how much it has impacted economically, as well as the care of technological assets for their longer life. Finally, the results obtained confirm the hypothesis raised, that applying the good practices of GREEN IT has a direct impact on energy reduction, as well as on the costs of the institution; verified in the survey instrument to 132 samples where the evaluation result yields a Cronbach's Alpha for the 22 items of 0,968, which allows affirming that the instrument applied has an excellent level of reliability and a reliability test for each question obtained an alpha greater than 0,965.

By Javier Perez-Nuñez, Ana Sofia Quispe-Ubilla, Jenny Gutiérrez-Flores, Brian Meneses-Claudio

2024-01-01 Original
Influence of Innovation on the Business Competitiveness of SMEs in Urbanization Panamericana Norte, Los Olivos 2022

Companies currently need certain skills to adapt to the changes imposed by the environment with a continuous improvement in processes. For this reason, innovation is considered fundamental to be competitive in the organization. Therefore, the research being developed aims to explain how innovation influences the competitiveness of SMEs in the Panamericana Norte urbanization, year 2022. The method used for this research was quantitative, non-experimental, this is so, since it will be carried out without deliberately modifying the variables, looking at them as they were presented in their own context. Causal descriptive. The present study will be developed in the Urbanización Panamericana Norte, Los Olivos, to the different SMEs that are located in this area dedicated to the commercialization of varied products. These surveys will focus on the customers who visit these SMEs. Therefore, the surveys will be conducted with the customers, since they can provide information about the product purchased. Likewise, the population determined for the current research work will be made up of the 930 customers of the SMEs in Urbanización Panamericana Norte, Los Olivos. In addition, a probabilistic sampling with a simple random sample of 93 clients of the SMEs in Urbanización Panamericana Norte, Los Olivos will be carried out. In addition, SPSS was used to analyze and obtain information from the study. With respect to the results of the variables, it was found that there is a direct relationship between them, since the analysis obtained a Spearman’s Rho of ,837. It is concluded from the research work that there is a directly proportional relationship between the variables Innovation and Competitiveness.

By Paul Ríos-Jimenes, Brenda Solis-Briceño, Brian Meneses-Claudio, Gustavo Zarate-Ruiz

2024-03-06 Original
Assessment of digital competencies in basic education teachers: A descriptive study

Introduction: Digital competencies are essential for primary education teachers, as they enable them to leverage technological tools to enhance teaching, adapt to the needs of digital students, and prepare them for an increasingly technological world.
Objective: To assess the digital competencies of Peruvian basic education teacher.
Methods: quantitative, non-experimental, cross-sectional descriptive study was conducted. The sample consisted of 125 teachers who were administered the Teacher Digital Competence Questionnaire, an instrument with adequate metric properties.
Results: It was found that 44% of basic education teachers had a medium level of digital competency, 36.8% had a high level, and 19.2% had a low level. Similarly, it was determined that certain sociodemographic variables such as gender and age group were significantly associated with the level of development of teachers' digital competencies (p<0.05).
Conclusions: The predominant level of development of digital competencies among basic education teachers is at a medium level. Therefore, it is recommended that educational authorities promote the implementation of workshops on the effective use of digital tools in the classroom, foster the exchange of best practices among teachers, and provide accessible digital resources and tutorials for autonomous learning.

By Edwin Gustavo Estrada-Araoz, Guido Raúl Larico-Uchamaco , Franklin Jara-Rodríguez, Ronald Pachacutec-Quispicho

2024-03-10 Original
An Energy-Efficient Cluster Head Selection and Secure Data Transmission in WSN using Spider Monkey Optimized Algorithm and Hybrid Cryptographic with Security

To conserve energy in wireless sensor networks, clustering is the well-known strategies. However, choosing a cluster head that is energy efficient is crucial for the best clustering. Because data packets must be transmitted between cluster members and the sink node, improper cluster head selection (CHs) uses more energy than other sensor nodes. As a result, it lowers the network's performance and lifespan. Due to the requirement that this network implement appropriate security measures to guarantee secure communication. This paper  provides a novel cluster head selection technique that addresses issues of  networks’ lives and  energy usages using Spider Monkey Optimised Fuzzy C-Means Algorithm (SMOFCM). The CH is chosen using the Spider Monkey Optimisation method in the proposed SMOFCM approach, which builds on the Fuzzy C-means clustering framework. The hybrid cryptographic technique is appropriate for WSN for safe data transmission because it can address sensor challenges such processing power, storage capability, and energy. The Rivest-Shamir-Adleman (RSA), advanced encryption standards (AES), and the suggested algorithm are all used at various stages. Because asymmetric key cryptography makes key management simpler but symmetric key cryptography offers a high level of security. The AES algorithm has been created for phase 1. Phase 2 employed RSA, and all phases were carried out concurrently. According to the simulation results, it reduces energy use, lengthens the network's lifespan, and offers faster encryption, decryption, and execution times for secure data transmission

By M. Yuvaraja, S. Sureshkumar, S. Joseph James, S. Thillaikkarasi

2024-03-07 Original
Pedagogical Management: The Key to Enhancing Academic Performance and Educational Quality

The purpose of this research is to determine the significance of pedagogical management (PM) in the teaching practice of instructors and the relationship between it and students' academic achievement. 23 scholarly papers were reviewed bibliographically in order to perform the investigation. The findings show a strong correlation between high-quality instruction and efficient pedagogical administration. It highlights that the instructor is the change agent in this process and that the student's educational transformation depends on their own personal growth. The conclusion highlights the significance of PM as a crucial component in obtaining quality education and emphasizes how the quality of the teaching process reflects on the quality of education. The present study holds significant value for the educational sector because it emphasizes the necessity of concentrating improvement efforts on teacher preparation and classroom management skills. These have been identified as critical points, particularly in higher education, where a pedagogical management crisis has been identified

By Rebeca Pablo-Huamani, Wilder García-Vázquez, Ruth Karina Alejandro-Bustamante, Cecilia Patricia Sánchez-Llontop, Jhonny Richard Rodriguez-Barboza

2024-03-13 Original
Gamification and Computational Thinking in Education: A systematic literature review

The rapid development of gamification and computational thinking seems to open up new educational horizons by providing new opportunities for students to acquire the basic digital skills needed for their cognitive development. Gamification, on the side, flourishes because it brings about high degree of participants’ engagement in an activity. Accordingly, on the other side, the growing scientific interest in computational thinking centers on the fact that it provides a fruitful field of dialogue in the research community for the development of critical and analytical thinking of students. Hence, this paper aims to synthesize knowledge about gamification and computational thinking for improving education for the benefit of students. Specifically, this paper describes: (a) the theoretical background of gamification in learning and education, (b) relevant studies in literature and their findings, and (c) specific gamified applications of STEM [Science, Technology, Engineering, Mathematics] which have been developed to this subject area. Four databases were searched, and 37 papers were finally selected for this review. The findings from the presented learning theories set the foundation on how students obtain knowledge, and the relevant studies in the field of gamification and computational thinking showed some first positive outcomes stemming some first research attempts which need further examination. Furthermore, it seems that with the right use of game mechanics and elements, well-designed applications of STEM gain students’ interest to learn through gameplay and motivate them to cultivate computational thinking and problem-solving skills.

By Serafeim A. Triantafyllou , Theodosios Sapounidis, Yousef Farhaoui

2024-01-01 Original
Smart Commodities Public Distribution System using IoT

In non-modern countries like India, the approach of allocating basic local goods to plight families is a significant approach to meeting the needs of a large number of people. The ongoing public dissemination system in Allot stores necessitates manual sum evaluation and trade record maintenance. The ongoing system has a ton of issues. One example is the IOT-based shrewd public appropriation framework project, which proposes a programmed method for getting products to verified cardholders. Similar to this, an informational index keeps track of the nuances of trades. Clients should enter their ID and mystery expression to get to their record through the High level cell. They are able to see the stock availability when they are successfully endorsed in. This structure uses a Raspberry Pi as the controller and uses a Specifics extraction-based extraordinary imprint coordinating computation, which has a higher accuracy score than previous versions. DC engines that are directly controlled by a Raspberry Pi for programmed product appropriation are used to open and close the valves. All along, one of the relatives need to enter one of a kind username and secret articulation. Right when client is supported in, he/she can see things that is open for that specific family account. The customer must provide a remarkable finger impression to the next level of confirmation in order to manage the items.

By N. Murali, S. Palani Murugan, K. Sivakumar, Manojkumar Vivekanandan, Mishmala Sushith, S.Manikandan

2024-03-07 Original
A Novel Autoencoder based Federated Deep Transfer Learning and Weighted k-Subspace Network clustering for Intelligent Intrusion Detection for the Internet of Things

Federated Learning (FL) has established as a potentially effective practice for cyberattack identification in the last decade, particularly for Internet-of-Things (IoT) structures. FL can increase learning effectiveness, lower transmission overheads, and enhance intrusion detection system (IDS) privacy by spreading the learning process amongst IoT gateways. The absence of labeled data and the distinction of data features for training pose significant obstacles to the deployment of FL in IoT networks. In this research, suggest an Autoencoder based Deep Federated Transfer Learning (ADFTL) to conquer these obstacles. Specifically, Create an ADFTL model utilizing two AutoEncoders (AEs) as the basis. Initially the supervised mode is employed to train the first AE (AE1) on the source datasets while the unsupervised mode is employed to train the second AE (AE2) on the target datasets without label information. The bottleneck layer, or latent representation, of AE2 is forced via the transfer learning method in an effort to resemble the latent representation of AE1. Subsequently, assaults in the input in the target domain are identified employing the latent representation of AE2. Particularly, Weighted k-Subspace Network (WkSNC) clustering is proposed for clustering the dataset and Boosted Sine Cos method (BSCM) is used for feature selection. The requirement that the network datasets utilized in current studies have identical properties is significant since it restricts the effectiveness, adaptability, and scalability of IDS. Nonetheless, the suggested structure can tackle these issues by sharing the "knowledge" of learning among distinct deep learning (DL) simulations, even in cases when their datasets possess dissimilar features. Comprehensive tests on current BoT-IoT datasets demonstrate that the suggested structure can outperform the most advanced DL-based methods by more than 6%

By V. S. Lavanya , R. Anushiya

2024-03-11 Original
Utilizing Machine Learning and Deep Learning for Predicting Crypto-currency Trends

In the dynamic and often volatile world of the cryptocurrency market, accurately predicting future market movements is crucial for making informed trading decisions. While manual trading involves traders making subjective judgments based on market observations, the development of algorithmic trading systems, incorporating Machine Learning and Deep Learning, has introduced a more systematic approach to trading. These systems often employ technical analysis and machine learning techniques to analyze historical price data and generate trading signals. This study delves into a comparative analysis of two charting techniques, Heikin-Ashi and alternate candlestick patterns, in the context of forecasting single-step future price movements of cryptocurrency pairs. Utilizing a range of time windows (1 day, 12 hours, 8 hours, ..., 5 minutes) and various regression algorithms (Huber regressor, k-nearest neighbors regressor, Light Gradient Boosting Machine, linear regression, and random forest regressor), the study evaluates the effectiveness of each technique in forecasting future price movements. The primary outcomes of the research indicate that the application of ensemble learning methods to the alternate candlestick patterns consistently surpasses the performance of Heikin-Ashi candlesticks across all examined time windows. This suggests that alternate candlestick patterns provide more reliable information for predicting short-term price movements. Additionally, the study highlights the varying behavior of Heikin-Ashi candlesticks over different time windows

By Ahmed EL YOUSSEFI , Abdelaaziz HESSANE, Imad ZEROUAL, Yousef FARHAOUI

2024-03-07 Original
Evaluation and Management of Diabetic Neuropathy from the Perspective of People with Diabetes

Diabetic foot ulcers (DFU) and infections are the most common complications of diabetic foot disease. Mortality and financial burdens for both patients and society on the whole are caused by the prevalence of complications. Peripheral neuropathy, peripheral arterial disease, and immune response dysfunction are just a few of the main contributing factors that must be understood in order to effectively treat the condition. In order to treat diabetic foot disease, you must first get a comprehensive physical examination and a detailed history of your condition. Diabetic neuropathy and peripheral vascular disease, as well as any evidence of diabetic foot ulcers or infection, should be examined during this procedure. Patients with diabetes mellitus were studied to see if there was a link between cognitive impairment and the condition of their feet and whether or not they followed their doctor's recommendations for glycemic control. Using a random sample of diabetes patients, researchers conducted a prospective study to see how many people had the condition. The Mini-Mental State Valuation, the Trail Making Judgments, and the Michigan Screening Instrument were used to assess cognitive abilities. In the one-month follow-up, glycated hemoglobin (HB1Ac >7%) was linked to the MMSE and medication adherence, but no link was seen between cognitive function and neuropathy. According to the results of a ROC curve investigation, HB1Ac and the MNSI score both significantly (p< 0.05) mitigate towards eventual adherence to medicine for foot problems. For the purpose of determining if DFU was associated with cognitive impairment, the Chi square valuation was used in the statistical examination. As a determinant of MMSE and MoCA scores, the researchers used linear regression to come to their conclusion. Diabetic foot issues should be managed with good blood sugar control and less acute neuropathy, and this does not seem to be linked to cognitive dysfunction. More study is required in order to personalize treatments for diseases of the central and peripheral nervous systems appropriately. Cognitive dysfunction should be taken into account by doctors and podiatrists while treating diabetic foot problems

By K.Babu, M.S.Roobini, S.Prabhakaran, S.Sadagopan, N.Kanimozhi

2024-03-07 Original
Privacy-Preserving Image Storage on Cloud Using An Unified Cryptographic Authentication Scheme

With the proliferation of several cutting-edge technologies such as the Artificial Intelligence (AI), and Machine Learning (ML), Internet of Things (IoT), cloud technology is gaining colossal popularity in recent years. Despite the general publicity on the theme across the digital world, defending user data kept in the cloud database is the most decisive problem. Recent potential cyber attacks reveal that storing private images entails more unique care related to other types of information on the cloud. As the cloud customer who has kept their images has no control over their data the cloud service provider has to ensure better security against cyber threats. Cryptography algorithms are the best choice to secure pictorial data in the cloud. These techniques transform images into an inarticulate form to keep confidentiality over undependable and vulnerable social media .In this paper, we aim to propose an approach for improving image security on the cloud using cryptography algorithms. We developed a cohesive approach, called Unified Cryptographic Image Authentication (UCIA) to protect user images on a cloud platform. The proposed UCIA approach includes two phases: (i)UCIA engenders a cipher text through a Data Encryption Standard (DES) by providing a key and a message as input, and (ii)UCIA implements a Twofish algorithm to encipher the pictures by applying cipher text. The enciphered picture data is then stored in the cloud database and can be recovered when the customer requests it. The effectiveness of both enciphering and deciphering procedures are analyzed using the evaluation metrics including time for enciphering, deciphering, cloud storage, and enciphering throughput. Experimental results reveal the better performance and strength of the UCIA approach.

By Manivannan R, G.Venkateshwaran, D. Menaga, S. Sivakumar, M. Hema Kumar, Minu Susan Jacob

2024-01-01 Original
Proposal for the implementation of the DMAIC methodology as a tool to improve productivity in the manufacturing area of an organic chocolate company – 2022

Productivity is an indicator that allows calculating the capacity of organizations to use their resources to generate goods or services and, at the same time, to diagnose the state of the company generated by different internal and external factors. For this reason, manufacturing companies have to improve the productivity of their processes to obtain their final product through management tools and thus remain in the market. For this reason, this study proposes to determine how the application of the DMAIC methodology intervenes in the improvement of productivity in the manufacturing process of a company dedicated to the manufacture of organic chocolates, year 2022.the research was applied, it was carried out under a pre-experimental design, with a descriptive-explanatory level having as population the production of organic chocolates during 26 days and a sample of 13 days that corresponds to the period after applying the improvements. This sample was obtained by the data collection method and for its processing the Excel program was used. As a result of this study, it was obtained that with the implementation of the DMAIC methodology, productivity had an average increase of 1,75 %, going from 92,32 % to 94,07 % after applying the improvements. Regarding the elements of productivity, an average increase of 0,89 % in efficiency and 0,93 % in effectiveness was obtained. It is concluded that the DMAIC methodology as an improvement tool significantly intervenes in the increase of productivity in the processes and that its application should be of knowledge for other organizations in the manufacturing sector

By Elizabeth Camposano-Castillo, Roberto Mañuico-Yupanqui, Brian Meneses-Claudio, Gustavo Zarate-Ruiz

2024-03-06 Original
Mexican social vulnerability as a sociological fact

The article aimed to construct a sociological interpretation about the relevance of the concept of social vulnerability, where social inequality, as a narrative, generally leads to highlighting the relevance of State institutions in the realization of citizen rights. But as a binary narrative, it forces us to include in the interpretation social behaviors organized by various beliefs derived from values, whose resonance is expressed in the mass media. In response to these arguments, it was decided to study the Mexican binary narrative in general to interpret some social behaviors recorded in the press

By Miguel Ángel Vite Pérez

2024-03-07 Original
Design of a Classifier model for Heart Disease Prediction using normalized graph model

Heart disease is an illness that influences enormous people worldwide. Particularly in cardiology, heart disease diagnosis and treatment need to happen quickly and precisely. Here, a machine learning-based (ML) approach is anticipated for diagnosing a cardiac disease that is both effective and accurate. The system was developed using standard feature selection algorithms for removing unnecessary and redundant features. Here, a novel normalized graph model (n-GM) is used for prediction. To address the issue of feature selection, this work considers the significant information feature selection approach. To improve classification accuracy and shorten the time it takes to process classifications, feature selection techniques are utilized. Furthermore, the hyper-parameters and learning techniques for model evaluation have been accomplished using cross-validation. The performance is evaluated with various metrics. The performance is evaluated on the features chosen via features representation. The outcomes demonstrate that the suggested n-GM gives 98% accuracy for modeling an intelligent system to detect heart disease using a classifier support vector machine

By B. Karthiga, Sathya Selvaraj Sinnasamy, V.C. Bharathi, Azarudeen, Sherubha. P

2024-01-03 Original
Location based Access Privileges and Controlling the Clustering in Sustainable 5G Challenges

Considering the new gathering of enlisting and communicated interchanges propels with the immense advancement of the Internet, the Web, and Adaptable Correspondences, the accompanying stage is supposed to be the Convenient Web. The central responsibility of the Compact Web is to satisfy client needs for wherever, at whatever point induction to information and organizations, including Region Based Organizations (LBS). An original LBS management that is relevant to the Flexible Promoting sector is presented in this paper. Numerous Web-enabled terminals will be transported, making the Versatile Web a reality for the vast majority of users. Mobile terminals and/or mobile networks can now pinpoint the terminal's location on Earth with increasing precision. The paper presents a model for collaborating on area scopes with services, an engineering to facilitate the Web-based disclosure of area scopes with services, a map of object handles to one or more contact addresses, and the possibility for a mobile client to select different types of information results for yielding in accordance with their momentum. These key research challenges are essential for advancing the development of LBS and establishing an examination plan for LBS to positively shape the future of our portable data society. These research challenges include issues related to the center of LBS development (such as positioning, displaying, and correspondence), evaluation, and analysis of LBS-produced information, as well as friendly, moral, and behavioural issues that arise as LBS become a part of people's daily lives.

By R. Manivannan, S. Manikandan, R. Vadivel, S. Sophana Jennifer

2024-01-01 Original
The Use of Marketing Strategies in a Telecommunications Company in the District of Pachacutec in the Year 2023

The main objective of this study is to determine the use of marketing strategies in a telecommunications company located in the district of Pachacútec in the year 2023. The methodology used in the research was of a basic type with a qualitative level approach, with a descriptive scope and also had a case study design.

The main instruments for data collection were the interview guide that was applied to five internal collaborators of the telecommunications company, likewise the questionnaire of open-ended semi-structured questions and the technique of direct observation were used as an instrument, which were applied to the interviewees, in which it was obtained as a result that the use of marketing strategies broaden and help greatly in improving the company’s image as well as in the formation of a close bond with customers, because they feel more identified with the company. brand in the aspect that they manage to visualize through social networks, the continuous updating of the service of the telecommunications company located in Pachacútec. In addition, the marketing strategies used by the telecommunications company such as direct marketing and advertising complement the power to extend the service to populated areas that are difficult to access for multiple companies focused on the telecommunications industry, which strengthens the company’s interest in providing customers with a connection to the virtual world.

In conclusion, the study highlights that the use of marketing strategies in a telecommunications company in Pachacútec is essential to improve the brand image, establish a close link with customers and expand the scope of the service, especially in areas of difficult access

By Elvis Mauricio Carranza; Freddy Verde-Bocanegra, Brian Meneses-Claudio, Gustavo Zarate-Ruiz

2024-03-06 Review
Beyond the Conventional. Value Proposition and Sustainable Innovation in the Transformation of the Mango Epidermis and Kernel for ASAGRAT.

The main purpose of the article is to develop and implement strategies for the sustainable utilization of mango by-products, specifically the peel and the kernel, with the goal of improving the socio-economic situation of farmers associated with the Association of Farmers of Tocaima (ASAGRAT). The adopted research methodology is grounded in two complementary approaches. Firstly, the research-action methodology is employed, encouraging community participation at all stages of the process. Secondly, a mixed approach is utilized, combining qualitative and quantitative methods. Qualitative data is collected through workshops, field journals, and surveys, while technological surveillance supports decision-making through access to diverse information sources. This comprehensive approach encompasses technological surveillance of mango by-products, improvement proposals, and projections for the development of new products that integrate into the value chain of the processes studied population

By Luis Alberto Rojas Farfán, Martha García López

2024-03-06 Case Report
Bone involvement as a presentation of breast cancer metastasis

Occult breast cancer is that condition that manifests as a metastatic axillary lymph node, without clinical or radiological manifestation of a primary breast tumor. It is a rare condition and was previously referred to only as non-palpable lesions. On the other hand, metastasis is the process through which the spread of a primary cancer focus to another organ occurs. This spread is carried out through the blood or lymphatic route. The organs that cause metastasis to bones are the breast, lung and prostate, in male patients. Currently, there is a high percentage of published clinical cases referring to bone involvement of breast origin and it is for this reason and the form of presentation, added The metastatic aggressiveness that we were able to observe is that in this article we detail the clinical case of a female patient with metastasis of occult breast cancer, where several organs were affected

By Ronald Vladimir Revelo Mera , Bolívar Alfredo Potes Berzosa, Alejandro Julián Terreros Bueno, Geovanna Paola Jaramillo Calderón, Rómulo Daniel Vargas Sánchez

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