Impact of Digital Technology on Library Resource Sharing: Revisiting LABELNET in the Digital Age

The digital environment has facilitated resource sharing by breaking the time and distance barriers to efficient document delivery. However, for the librarians, this phenomenon has brought more challenging technical and technological issues demanding addition of more knowledge and skills to learn and new standards to develop. The overwhelming speed and growing volume of digital information is now becoming unable to acquire and manage by single libraries. Resource sharing, which used to be a side business in the librarianship trade, is now becoming the flagship operation in the library projects

An Introduction to the Patstat Database with Example Queries

This paper provides an introduction to the Patstat patent database. It offers guided examples of ten popular queries that are relevant for research purposes and that cover the most important data tables. It is targeted at academic researchers and practitioners willing to learn the basics of the database.Comment: To appear in the Australian Economic Revie

Modelos de aprendizaje automático en la detección e identificación de personas: una revisión de literatura

Introduction: This article is the result of research entitled "Development of a prototype to optimize access conditions to the SENA-Pescadero using artificial intelligence and open-source tools", developed at the Servicio Nacional de Aprendizaje in 2020.   Problem: How to identify Machine Learning Techniques applied to computer vision processes through a literature review? Objective: Determine the application, as well as advantages and disadvantages of machine learning techniques focused on the detection and identification of people. Methodology: Systematic literature review in 4 high-impact bibliographic and scientific databases, using search filters and information selection criteria. Results: Machine Learning techniques defined as Principal Component Analysis, Weak Label Regularized Local Coordinate Coding, Support Vector Machines, Haar Cascade Classifiers and EigenFaces and FisherFaces, as well as their applicability in detection and identification processes.   Conclusion: The research led to the identification of the main computational intelligence techniques based on machine learning, applied to the detection and identification of people. Their influence was shown in several application cases, but most of them were focused on the implementation and optimization of access control systems, or tasks in which the identification of people was required for the execution of processes. Originality: Through this research, we studied and defined the main machine learning techniques currently used for the detection and identification of people. Limitations: The systematic review is limited to information available in the 4 databases consulted, and the amount of information is variable as articles are deposited in the databases.Introducción: Este artículo es el resultado de la investigación titulada " Desarrollo de un prototipo para optimizar las condiciones de acceso al SENA-Pescadero utilizando inteligencia artificial y herramientas de código abierto", desarrollada en el Servicio Nacional de Aprendizaje en 2020. Problema: ¿Cómo identificar las técnicas de aprendizaje automático aplicadas a los procesos de visión por computador a través de una revisión bibliográfica? Objetivo: Determinar la aplicación, así como las ventajas y desventajas de las técnicas de aprendizaje automático enfocadas a la detección e identificación de personas. Metodología: Revisión sistemática de la literatura en 4 bases de datos bibliográficas y científicas de alto impacto, utilizando filtros de búsqueda y criterios de selección de información. Resultados: Técnicas de aprendizaje automático definidas como Análisis de Componentes Principales, Codificación Local de Coordenadas Regularizada de Etiquetas Débiles, Máquinas de Vectores de Soporte, Clasificadores en Cascada de Haar y EigenFaces y FisherFaces, así como su aplicabilidad en procesos de detección e identificación. Conclusiones: La investigación permitió identificar las principales técnicas de inteligencia computacional basadas en machine learning aplicadas a la detección e identificación de personas. Su influencia se mostró en varios casos de aplicación, pero la mayoría de ellos se centraron en la implementación y optimización de sistemas de control de acceso, o tareas en las que se requería la identificación de personas para la ejecución de procesos Originalidad: A través de esta investigación se estudiaron y definieron las principales técnicas de machine learning utilizadas actualmente para la detección e identificación de personas

Evolution of research on prison library: A bibliometric study

The primary objective of the article is to present the historical evolution and current state of research in the field of prison libraries: what has been published, when, where, how and by whom it was published, the topic covered, etc. The study is based on the results obtained from the bibliographic databases LISA (ProQuest) and LISTA (EBSCO Publishing) up to early 2023. Entries were manually checked for irrelevant publications, and filters and specific tools, such as OpenRefine, followed by a final manual check, were used to remove duplicate entries. The same mechanisms were used for detecting duplicated entries regarding author, country, journal title, topic, etc. The analysis shows a prevailing publication profile of scarce scientific relevance, with a predominance of the description and the speculation rather than empirical statements. To overcome these limitations, it is proposed the use of scientific methods and techniques that enhance the rigour of results; to progress from the simple description of services, programs, activities, collaborations, etc., to an evaluation of them; and to work with other professionals, both from the library sector and from other disciplines