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In some places far from Peru with the absence of the Notary Public, but with the presence of the Justice of the Peace, there is legal insecurity in the registry because it is not possible to carry out legal transactions on the real estate. This is what happens in the border province of Purús. Law 29824 reduced the Notarial powers of Justices of the Peace to only grant deed of transfer of possession of real estate that does not exceed 50 Procedural Reference Units (PRU), on the other hand, Law 27755 that creates the Land Registry, in its article 7, stipulates the use of registration forms to register real estate, as long as it does not exceed the economic value of 20 Tax Units (TU). This means that in some remote parts of the province, some citizen should enter into a legal transaction on their property, however, they cannot do so because they do not have a Notary Public, even if they do have a Justice of the Peace Lawyer, who could replace him (her), but who by law is disqualified from doing this job. That is why this article aims to design a recommendation system that allows the citizen to make the correct decision about what to do in each case, in addition to the fact that the system can serve to instruct the Justice of the Peace Lawyer of these communities to teach the citizen on the procedures to follow. This recommendation system is based on deontic logic, which is a variant of modal logic dedicated to reasoning about concepts related to conduct, especially has application in the legal field. The recommender system is a computer program that can be based on a model that serves to support individuals in recommending what action to take based on their needs or desires. [ABSTRACT FROM AUTHOR]

Distance Education enabled educational practices based on digital platforms. Despite its wide adoption, the high dropout rates are a reason for concern for teachers and institutional managers. There are initiatives to mitigate this situation, such as Educational Data Mining (EDM), Learning Analytics (LA), and the use of Recommendation Systems (RS). Although effective in specific aspects, these techniques lack mechanisms for the motivation of students and pedagogical intervention by teachers, as they do not present methodological proposals to encourage learning. Therefore, this article describes an RS model that presents as a differential integration of the pedagogical approach of Active Methodologies with the support of Educational Data Mining and Learning Analytics techniques to identify students with dropout risks and enhance permanence. For this, a prototype was implemented and a case study was carried out with professors from two universities to assess functionality and acceptance. According to the TAM model, more than 87% of teachers agree with the ease of use and 77% agree that RS can be useful in the teaching and learning process of students. Therefore, it can be concluded that the model contributes to teaching practices, encourages collaborative learning, and favors the monitoring of this process and the activities developed by the students. [ABSTRACT FROM AUTHOR]

Technology has opened the possibility of improving learning environments. However, in the field of medical education, the tools that are used do not provide clear evidence as to whether students are actually learning. Specifically, in the teaching of anatomy, multiple applications have emerged to satisfy the need to access cadaveric material, nevertheless, these lack enriched information on the performance achieved by students and how to adapt learning according to their educational needs. Thus, one of the strategies currently present in this area is gamification. This study implements and uses a gamified educational software platform based on recommender systems and virtual assistants, capable of delivering feedback and strategies to support the appropriation of anatomy knowledge of medical students at the Universidad de La Frontera (UFRO), in the city of Temuco, Chile. Forty-five students participated in the study. The study consisted in the use of various gamified components with artificial intelligence techniques. The main findings of this experience led to the conclusion that the use of gamified components for learning anatomy is a resource that supports student learning. [ABSTRACT FROM AUTHOR]

This article offers methodological and theoretical reflections based on the interdisciplinary project "Algorithmic Identities." Initiated in 2019 between researchers from the Pontificia Universidad Católica de Chile and the University of Warwick (UK), this project seeks to understand how personhood is configured in times of algorithms and digital data. We designed a prototype app, "Big Sister," which emulates algorithmic profiling and recommendation systems of major digital platforms. This prototype has served as a twofold social research device. Firstly, it allowed us to produce knowledge from a critical and decolonial doing and undoing; secondly, through digital trace interviews with prototype users, we explored their experiences and stimulate reflection on the mediations of algorithms in their lives. This article examines the prototyping process of this app and some findings of how people in Chile understand, inhabit, and shape data and algorithms daily. Drawing on insights from Latin American authors such as Arturo Escobar, Jesús Martín-Barbero, and Paulo Freire, we argue how the prototyping of an app can move towards a "problematizing" approach to datafication and algorithmic systems in Latin America. [ABSTRACT FROM AUTHOR]

The objective of this work was to propose a theoretical model of pervasive information architecture, focused on the use of recommendation systems to increase the findability of information in university libraries. This research was developed from a multidisciplinary perspective and it is defined as exploratory research since a bibliographic review is carried out. This review allows obtaining information on the theoretical elements necessary to establish the central base of the research. It is also descriptive, as it seeks to bring solutions to issues that arise in the daily life of university libraries. As a result, a model of pervasive information architecture for university libraries is presented with a focus on improving information findability from the inclusion of recommendation systems. It can be concluded that, due to the wide advance in the development of applications and tools for use in libraries, a notable increase in the level of complexity of the information environments of these institutions is perceived, which from the perspective of information architecture creates the need for more refined research projects, whose aim is to improve the information environments of university libraries, always with the main objective of favoring the experiences of users, and helping them in the processes of finding relevant information, at the precise time and with the highest possible quality. [ABSTRACT FROM AUTHOR]

This article aims to identify the way in which the Netflix platform demonstrates the concept of television flow in its catalog, based on the analysis of the original content of fiction series released in 2019. It also recognizes some programming strategies and techniques that implements this video streaming platform, considering the implications of big data and recommendation systems. The methodology contemplates qualitative and quantitative techniques and applies an analysis matrix based on a manual coding of 157 original fiction series, with variables such as launch date, origin of production, season number, chapters and total minutes released per season. Among the main findings, it is evident that Netflix achieves a television flow with permanent premieres throughout the year, the launch of content by seasons with full chapters, as well as the election of Friday and the spring season for the launch of a greater number of fiction productions. It was also found that, although this streaming service seeks a diversification of the catalog with productions from different countries, the original serial fiction content continues to be mainly of American origin. It is concluded that the programming dynamics in the Netflix catalog creates a television flow to promote intensive consumption in the premieres of original fiction series. The catalog is optimized through data-based decisions and promotes viewing with content recommendation systems that allow the creation of an entire Netflix experience. [ABSTRACT FROM AUTHOR]

This article shows the construction of an information model for the exchange of data and information within the context of the development of CubeSat type satellite systems; articulating the development, procedure, description, design, architecture and results that largely refer to the adoption of such guidelines within a scenario of technological interoperability and specifying the functionality in the transmission patterns of telemetry information in academic satellites. The guidelines of the Consultative Committee on Spatial Data Systems (CCSDS) are taken into account in collaboration with the European Space Agency (ESA) and the European Cooperation for Spatial Standardization (ECSS), who have consolidated multiple recommendations to standardize the transfer of information from space systems through various procedures and mechanisms. Additionally, the Extensive Markup Language (XML) was considered, next to the Telemetry and Command Exchange (XTCE) format, in conjunction with the Package Utilization Standard (PUS), the description of Mission Operation Services (MO) and the Message Abstraction (MAL) layer, taking into account that they suggest the modularity and specificity necessary for the development and construction of information systems in satellite technologies. [ABSTRACT FROM AUTHOR]

This work presents a tool called HeuristicTool, by means of which the heuristic evaluation process is supported, allowing evaluators to improve the process of analyzing the results and, in general, the development of said evaluations. During its development and permanent updating, ontologies were included to facilitate the capitalization and transfer of knowledge between the different evaluators. The above through KACTUS, a methodology that proposes steps in relation to: the specification of the application, preliminary design based on ontological categories and a refinement and structuring of the ontology. A group of three experts rated 6 ontology variables, consolidating an average of 4.7 out of 5. In addition, an evaluation of the platform's usability presented satisfactory results, using Jakob Nielsen's battery of heuristics. The main result was an application that gives users the possibility of reviewing structured evaluations in a knowledge base, in order to improve decision making. [ABSTRACT FROM AUTHOR]

New technologies and the era of knowledge have caused the school to cease to hold a monopoly on education and to emerge new models and learning formats. Furthermore, these circumstances have led to a culture of infoxication, disinformation and post-truth. In the network there is no information filter. This context has also favored the creation of new digital textualities based on collective creation. Among them stand out the creepypasta (digital horror stories) as works based on constructive hyperfiction, inspired by urban legends and related to fake news. This research aims to analyze creepypasta as constructions and narrative models in order to take advantage of their potential in formal education. To do this, a corpus of 68 works located in the Suggested Reading section of the affinity space related to these most important texts on the web has been extracted and analyzed: creepypasta. fandom. The results found show that these are metafictional stories that use a great wealth of techniques and narrative resources. Images, documents, news and other document facts are manipulated and resignified. All this positions these texts in a privileged space for the promotion of reading and media and information literacy. [ABSTRACT FROM AUTHOR]

This paper focuses on developing a method of hybrid context-aware recommender systems, based on ontologies in the environment of the Spatial Data Infrastructure, which will positively impact the effectiveness of decision-making in the tourist applications for mobile users. The method developed has three components: data and semantic framework, other that implements the recommender system and another responsible for displaying the recommendations. The recommender system component implements a spatial, a semantic and collaborative filters. The recommendations generated show the elements of potential interest, these can be displayed in tabular or combined with spatial information. It was found through an experiment and different applied metrics the increase in its effectiveness for mobile users according to their preferences as to the recommendations given in a spatial environment. [ABSTRACT FROM AUTHOR]