Knowledge, Volume 4, Issue 2 (June 2024) – 6 articles

Science has been an incredibly powerful and revolutionary force. However, it is not clear whether science is suited to performance under pressure; generally, science achieves best in its usual comfort zone of patience, caution, and slowness. But, if science is organized knowledge and acts as a guiding force for making informed decisions, it is important to understand how science and scientists perform as a reliable and valuable institution in a global crisis. This paper provides insights and reflections based on the experience of the COVID-19 pandemic and from an analytical perspective. In particular, we analyze aspects such as speed, transparency, trust, data sharing, scientists in the political arena, and the psychology of scientists—all of which are areas inviting more detailed investigations by future studies conducting systematic empirical studies. Full article

Over the last two decades, the knowledge production, research, and reconfiguration of universities have been understood as ways of giving new meanings to the university–society binomial. In this regard, humanities are the subject of multiple debates in the face of ideas about their impact in relation to the “other sciences”. Based on these premises, this article sets out to explore possible meanings attributed by researchers to the concepts of commitment, mobilization, and transfer of research in humanities in view of the debates on the university–society interaction and the third mission of the university. The methodology used will address bibliographical analysis, theoretical background, and statements from different institutions, as well as the analysis of material from four interviews. As a first instance, the preliminary results show that strengthening critical thinking as forms of commitment emerge as central senses, focusing on Hungarian characteristics and productions in order to unravel the ways of understanding and imagining Eastern European reality. In this respect, the discussion of certain aspects of Western knowledge is seen as a task associated with social commitment with public universities as a focus of resistance. Full article

This contribution describes the change in methodology introduced in the subject of electrical technology within the industrial technologies engineering degree at Escuela Técnica Superior de Ingeniería Industrial, Universitat Politècnica de València. The main purpose of the methodology change was to improve the attainment of student outcomes by the introduction of project-based learning supported by flipped teaching. Moreover, a software tool was developed that generates standard exercise statements for the design of electrical installations. Using this tool, students can practice with different problem exercises, enter their solution, and receive immediate feedback on their results, improving the teaching–learning experience. The level of student outcomes attained was improved, and other positive aspects arose from the experience, such as boosting students’ responsibility in their own learning (learn to learn), their ability to solve problems, and students’ motivation. Furthermore, the instructors’ opinions on the methodology change were highly positive. Full article

This study aims to analyze the perceived value of services provided by the Brazilian Company of Research and Industrial Innovation (EMBRAPII) to its contracting ministries and institutional partners. It utilizes the theory of value perception analysis and Constructivist Multi-criteria Decision Analysis to identify critical elements for evaluating EMBRAPII’s contracting organizations. Brainstorming sessions with experts led to the identification of five criteria and 14 sub-criteria. These criteria include a relationship with EMBRAPII, a signed agreement, EMBRAPII’s reputation, technical capacity, and the ability to adapt to changes. Data were entered into the second version of the MyMCDA-C software for value perception analysis. The findings showed a positive perceived value, with the best-performing sub-criteria relating to the organization’s reputation and the agreement signed. The study concludes that EMBRAPII needs to improve in areas such as adapting to change, the adequacy of its proposals for distinct types of partnership, and social media positioning. However, the contracting organizations generally support EMBRAPII’s direction and proposed solutions. Full article

This research explores the optimization of firewall systems within private cloud environments, specifically focusing on a 30-day evaluation of the Omni-Secure Firewall. Employing a multi-metric approach, the study introduces an innovative effectiveness metric (E) that amalgamates precision, recall, and redundancy considerations. The evaluation spans various machine learning models, including random forest, support vector machines, neural networks, k-nearest neighbors, decision tree, stochastic gradient descent, naive Bayes, logistic regression, gradient boosting, and AdaBoost. Benchmarking against service level agreement (SLA) metrics showcases the Omni-Secure Firewall’s commendable performance in meeting predefined targets. Noteworthy metrics include acceptable availability, target response time, efficient incident resolution, robust event detection, a low false-positive rate, and zero data-loss incidents, enhancing the system’s reliability and security, as well as user satisfaction. Performance metrics such as prediction latency, CPU usage, and memory consumption further highlight the system’s functionality, efficiency, and scalability within private cloud environments. The introduction of the effectiveness metric (E) provides a holistic assessment based on organizational priorities, considering precision, recall, F1 score, throughput, mitigation time, rule latency, and redundancy. Evaluation across machine learning models reveals variations, with random forest and support vector machines exhibiting notably high accuracy and balanced precision and recall. In conclusion, while the Omni-Secure Firewall System demonstrates potential, inconsistencies across machine learning models underscore the need for optimization. The dynamic nature of private cloud environments necessitates continuous monitoring and adjustment of security systems to fully realize benefits while safeguarding sensitive data and applications. The significance of this study lies in providing insights into optimizing firewall systems for private cloud environments, offering a framework for holistic security assessment and emphasizing the need for robust, reliable firewall systems in the dynamic landscape of private clouds. Study limitations, including the need for real-world validation and exploration of advanced machine learning models, set the stage for future research directions. Full article

This paper will discuss Data, Information, Knowledge, and Wisdom, which is commonly referred to as DIKW. The DIKW Pyramid Model is a hierarchical model that is often referenced in both academic and practitioner circles. This model will be discussed and shown to be faulty on several levels, including a lack of definitional agreement. A new DIKW framework with systems orientation will be proposed that focuses on what the DIKW elements do in the way humans think, not what they are by definition. Information as a replacement for wasted physical resources in goal-oriented tasks will be a central organizing point. The paper will move the DIKW discussion to the computer-based concept of Digital Twins (DTs) and its augmentation of how we can use DIKW to be more effective and efficient. This will especially be the case as we move toward Intelligent Digital Twins (IDTs) with Artificial Intelligence (AI). Full article