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Corporate structure and prevention: The three lines model applied to Latin American companies
No full textThe economic environment in which enterprises operate is increasingly harsh and complex, making business more complex, volatile and uncertain. This context requires a change in the management model based on the three fundamental pillars of governance, risk management and regulatory compliance. In this sense, the presentation of the three-line model is considered particularly useful, as it has become one of the most recognized management tools internationally due to its flexibility and adaptability. Therefore, the purpose of this study is to examine the current literature on this management model and then analyze its applicability in business practice through a case study. In particular, the analysis of four companies in the Ibero-American energy sector (Petrobras, Codelco, Ecopetrol, and Iberdrola) reveals that, although the adaptation of the model is generally comprehensive and universal in all aspects, its flexibility is very Large allows adaptation to any organization’s needs and structure. Finally, the study draws some conclusions weighing the theoretical development of the three-line model and its applicability and usefulness to managers as well as researchers and legislators who want to strengthen national business structures
Proposed Model for the Detection of Diabetic Retinopathy Using Convolutional Neural Networks
No full textDiabetic retinopathy, an ocular complication associated with diabetes, is a major cause of vision loss if not treated early. This study aims to identify Diabetic Retinopathy using Convolutional Neural Networks. The proposed Methodology consists of four phases: Obtaining the dataset, Preprocessing, Model Training and Evaluation. In the proposed method, DR detection is performed using the IDRID labeled retinal image dataset, implementing and training the pre-trained models VGG-19, ResNet-50 and Inception-V3. The results highlight that the VGG-19 model achieves remarkable performance with accuracy, precision and recall of 95.64%, 92.98% and 99.64% for binary classification. Although the performance achieved by the other models ResNet-50 and Inception-V3 show intermediate performance, they show lower accuracy, indicating difficulties in classification. In summary, VGG-19 stands out as an effective option to identify DR, while Inception-V3 and ResNet-50 present different performances, pointing out areas of improvement for future research. These results underline the relevance of CNN architectures in the detection of Diabetic Retinopathy. Despite certain limitations, such as unbalanced data, quality and availability of retinal images, the findings demonstrate the great ability of CNN models to contribute to the understanding and improvement of diagnostic methods in this medical area. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024
Application of Universal Design for Learning and Digital Fabrication in the Creation of a Tool for Inclusive Teaching of the Ordering of Chemical Elements
No full textThis research article aims to use Universal Design for Learning (UDL) and digital fabrication (DF) to create a tool for the inclusive teaching of chemistry, with the specific purpose of enhancing the teaching-learning process in organizing chemical elements. The Design-Based Research (DBR) methodology was employed. This methodology facilitated the design of a tool based on an alternative ordering to the traditional periodic table. Utilizing the principles of Universal Design for Learning and the implementation of digital fabrication technologies, especially 3D printing, it has been possible to link student-centered learning, inquiry-based learning, and hands-on learning. Experimental activities have been carried out with students and teachers from three schools in Catalonia, Spain, as well as validation with experts from the Spanish National Organization for the Blind (ONCE). The assessment discussion and analysis made by students, teachers and experts using mixed methods (quantitative and qualitative) is given. This research has exposed the synergy between universal design for learning and digital fabrication in learning and its contribution to improve the inclusive teaching-learning process. © 2024 American Chemical Society and Division of Chemical Education, Inc
Proposal for an Information Security Management System for the Enrollment Process of a University
No full textThe present study aims to implement acquired knowledge and apply it to enhance the enrollment process at a university. This initiative stems from various studies, including those focused on measuring risk prevention strategies, specifically in the enrollment domain, due to the increasing diversity of university course offerings. Consequently, the following objective is proposed: to suggest an Information Security Management System (ISMS) to improve the university enrollment process. To achieve this, the plan involves developing an ISMS using the PDCA methodology, which comprises four phases. Initially, it aims to identify the characteristics and indicators to establish the proposal. Subsequently, the focus shifts to maintaining and implementing problem-solving policies. In the third phase, results are evaluated, and finally, alternative improvements are proposed. All these steps align with the guidelines of ISO 27001:2013. As this is a proposal yet to be executed, the results are assessed using statistical software to compare correlations between the ISMS and the enrollment process, thus addressing the proposed hypotheses. It is found that a relationship exists between the variables and can be developed since one influence the other. This is evidenced by a Spearman's Rho coefficient of 0.474, indicating a moderate positive correlation, measured at a significance level less than 0.05. In conclusion, the analysis of various articles in this study has underscored the importance of developing an Information Security Management System in the university context, particularly in the enrollment process. This enables adaptation to change in security risks. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024
Implementation of Text-to-Image Generators in the Development of the Usability Interface for the Construction of a Web Page
No full textThe generation of high-quality images with specific styles using Text-to-image Generators became more accessible due to the distribution of different diffusion models, which through the methodology Diffusion Training and Dreambooth technology. The main objective is getting a better efficiency in the development of a Usability Interface (UI) for a website. The members of the development refined Stable Diffusion models, to able to generate images with the styles: 'Facebook Alegria' (Alegria style) and 'black silhouette icons' (icon style). With the speed and simplicity of image generation, the team was able to reduce cost and times in the development. From the total number of images generated, 4 images with Alegria Style and 17 with icon style were chosen to add at the UI. The main result of the research showed that after the implementation, there was a significative change with respect to other work previously performed in the same company. The hours spent on frontend development were reduced by 81.65%, and and costs were reduced by 22.80%. In conclusion, the Post-test collected indicates notable improvements in the efficiency of the development. The implementation of text-to-imagen generations has proven its effectiveness in to reduce the cost and time of UI development. © 2024 IEEE
Proposal of a Computational Vision Model for the Pre-diagnosis of Anemia Based on the Image of the Ocular Conjunctiva
No full textAnemia is a persistent public health problem in Peru, with significant repercussions on individual quality of life and socio-economic progress at the national level. Although the hemogram is considered the reference method for diagnosing anemia, its need for time and a laboratory setting to be performed can represent a considerable limitation, especially in remote or less developed areas. The aim of the present research is to implement a computer vision model for the pre-diagnosis of anemia from the image of the ocular conjunctiva. The applied methodology was based on 5 phases: obtaining dataset, preprocessing, modeling and classification, feature extraction and implementation of CNN architectures. Several models were run with the classifiers: SVM, RF, MLP, and RNN and feature extraction techniques: SIFT, SURF, ORB and HOG. The model with RF and HOG extractor obtained the highest accuracy with 79%. Finally, deep learning models were explored, adjusting parameters such as the number of neurons, epochs, and samples in each model. Although initially the custom model obtained the highest accuracy of 93.18%, the Inception-ResNet-v2 model, supported by existing studies, was finally chosen and demonstrated a robust accuracy of 90.69% and loss of 0.2788, which is better than the loss of 0.3563 obtained with the comparison model. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024
Development of Inclusive Tools Through Digital Fabrication for Chemistry Learning in Students with and Without Visual Impairment
No full textThis research article aims to develop inclusive tools through digital fabrication to improve the teaching-learning process of the subject of chemistry in the topics of electronic configuration and ordering of chemical elements, in students with and without visual impairment. This research has taken into consideration the principles of Universal Design for Learning by linking practical applications and the inclusive approach to learning. Likewise, to reflect the objectives of this study, the design-based research has been followed. This methodology allows identifying learning needs, design materials, tools or activities to achieve the learning objectives of students. This research reports on preliminary and exploratory activities regarding the perception and evaluation of the tools by students, teachers and experts. The discussion and analysis of results will be analyzed in future research. However, what this research has exposed so far is the potential of digital fabrication technologies in inclusive learning. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024
Proposed Ransomware Detection Model Based on Machine Learning
No full textRansomware is one of the main malwares that exists today as established by EUROPOL and Malwarebytes which affects both the international and national context. In this way, the main problem is the detection of ransomware in the different users. Due to the lack of a responsive security control against the mentioned malware that adapts to the different variants that may arise, since currently virus signature is used which is not effective because of its dependence on manual updates. Thus, the overall objective is to develop the proposal of a Machine Learning logic model to improve the detection of Ransomware. For this purpose, the proposed methodology was used, due to its adaptability in predicative research. The results obtained from the model selection and training process showed that the Random Forest algorithm had the highest accuracy, and when trained by means of a Dataset for ransomware detection, 0.99 in Accuracy, 0.99 in Balanced Accuracy, 0.99 in ROC AUC and 0.99 F1 Score were obtained. Thus, it is proved that the Random Forest model is the ideal model for ransomware detection due to its effectiveness and accuracy. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024
A bibliometric analysis and visualization of social impact of tourism and sustainability
No full text[No abstract available
Revisión sistemática de literatura del concepto “organización criminal” mediante el modelo PRISMA
No full textThe growth in the number of criminal organisations and their complexity, in terms of conceptual variety, theoretical implications and empirical challenges, have made it difficult for researchers to generate sufficient theories, studies of causes and scales to categorise and explain the phenomena. The characterisation of these organisations and the approach to defining them is complex both because of the diversity of their social impacts and because of the broad range of thematic areas they address. This study shows the trends in research and study of criminal organisations by conducting a systematic literature review of the years 2022 and 2023, using the PRISMA method and exploring current trends in academic research and bibliographic production on the subject. © 2024 Policia Nacional de Colombia. All rights reserved