Hasta hace poco, la posibilidad que los seres humanos portáramos dispositivos electrónicos en nuestro cuerpo era sólo planteado por la ciencia ficción. Esto ha cambiado con la aparición de los dispositivos insertables, aparatos electrónicos que las personas se introducen para asegurar confidencialidad en información o aumentar el control de acceso a recursos estratégicos. Dado que esta tecnología se encuentra aún en sus estados iniciales de adopción, existen muy pocos estudios que identifiquen los factores que influencian a las personas a aceptar/rechazar este tipo de aparatos. Nosotros estudiamos un conjunto de nueve factores extraídos de una versión extendida de UTAUT y que podrían predecir la disposición a usar insertables. Los datos fueron recolectados mediante la aplicación de una encuesta a 183 estudiantes universitarios chilenos y fueron analizados usando un modelo de ecuaciones estructurales. Los resultados indican que cinco factores afectan la intención de usar insertables: hábito, motivación hedónica, influencia social, expectativa de esfuerzo y de rendimiento, explicando el 73,6% de la varianza de la intención de uso de insertables. Factores relacionados al juicio ético de los respondientes no fueron significativos de la intención de uso. Estos dispositivos tienen un enorme potencial de innovación y económico que recién está dando los primeros pasos. En un futuro mediano, las personas podrían voluntariamente insertarse estos aparatos para mejorar sus funciones cognitivas y/o las empresas podrían pedir a sus empleados colocarse estos dispositivos para seguridad y control. Esto obligará a los países a regular la utilización de insertables, tal que su uso se dé en un marco legal que impida potenciales abusos de parte de las personas o las empresas en lo que sería cercano al mundo Orweliano. Consecuentemente, los resultados de este estudio son de interés tanto a la comunidad académica como profesional.
The automatic detection of flaws through non-destructive testing uses pattern recognition methodology with binary classification. In this problem a decision is made about whether or not an initially segmented hypothetical flaw in an image is in fact a flaw. Neural classifiers are one among a number of different classifiers used in the recognition of patterns. Unfortunately, in real automatic flaw detection problems there are a reduced number of flaws in comparison with the large number of non-flaws. This seriously limits the application of classification techniques such as artificial neuronal networks due to the imbalance between classes. This work presents a new methodology for efficient training with imbalances in classes. The premise of the present work is that if there are sufficient cases of the smaller class, then it is possible to reduce the size of the larger class by using the correlation between cases of this latter class, with a minimum information loss. It is then possible to create a training set for a neuronal model that allows good classification. To test this hypothesis a problem of great interest to the automotive industry is used, which is the radioscopic inspection of cast aluminium pieces. The experiments resulted in perfect classification of 22936 hypothetical flaws, of which only 60 were real flaws and the rest were false alarms.
Title: IT impact on small and medium enterprises ¿is its effect moderate by intensity of IT use of industry?This article aims to demonstrate that the impact of information technology (IT), on organizational performance of small and medium enterprises (SMEs), varies according to the intensity level of IT use of industry. For this we use microdata from the Second Longitudinal Survey of Business (ELE2), through which we established variables of intensity of IT use and organizational performance. Then, using X-Means we define indicators of intensity of IT use in SMEs and industries. The results showed that the intensity of IT use has positive effects on SMEs. Also, prove that the effects of the intensity of transactional IT use on performance, varies according to level of IT use of industry.Resumen: Este artículo tiene como objetivo demostrar que el impacto de las tecnologías de la información (TI), sobre el rendimiento de las pequeñas y medianas empresas (Pymes), varía según el nivel de intensidad de uso de TI de la industria. Para esto utilizamos microdatos provenientes de la Segunda Encuesta de Longitudinal de Empresas (ELE2), por medio de la cual establecimos variables de intensidad de uso de TI y de rendimiento organizacional. Luego, mediante X-Means definimos indicadores de intensidad de uso de TI en Pymes e industrias. Los resultados obtenidos demuestran que el uso de TI tiene efectos positivos en las Pymes. Además, prueban que los efectos del uso de TI transaccional sobre el rendimiento varían según el nivel de uso de la industria.
In capital-intensive organizations, decisions regarding capital costs play an important role due to the significant amount of investment required and the expected return on investment. Spare parts management is crucial to those ends, as spare parts management can constitute a significant portion of OPEX. Companies must implement a trade-off analysis between stock levels and assets’ availability. Decision-making supports mechanisms such as the Level of Repair Analysis (LORA), Integrated Logistics Systems (ILS), and life-cycle costing (LCC) models have been developed to aid in equipment selection, implementation, and decommissioning. Nowadays, these mechanisms appear to be integrated with risk-management models and standards. This paper proposes a long-term costing model that integrates a capacity analysis, reliability functions, and risk considerations for the cost management of logistics activities, particularly in MRO structures. The model is built upon Time-Driven Activity-Based Costing (TD-ABC) and incorporates the volume of activities generated by MRO needs. It also addresses uncertainty through the integration of a cost-at-risk model. By integrating spare parts, activity-based cost models, and risk measurement through Monte Carlo simulation, this study offers powerful insights into optimizing spare parts logistics activities. The proposed model is a novel approach to include the risk of cost in spare parts management, and its matrix-activity-based structure makes possible the development of sophisticated mathematical models for costing and optimization purposes in different domains.
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