31,592 research outputs found

    The evolution of experiential learning: Tracing lines of research in the JEE

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    This essay introduces a collection of past articles from the Journal of Experiential Education (JEE) focused on the concept of experiential learning. It outlines the historical trajectory of the concept beginning with human relations training practices beginning in 1946, as it came to be understood as a naturally occurring psychological process and a grounding for pedagogical reforms. The eight articles included in the issue reflect the way JEE authors have contended with problems arising from the concept’s departure from its origins in practice. We suggest that experiential learning’s evolution into a general theory was accomplished by decoupling it from its roots in a particular social practice and ideology, and then focusing on the concept’s technical problems. It is now important for researchers to revisit assumptions underpinning current theory and practice, situate research on experiential learning in wider practical and scholarly traditions, and develop new vocabularies concerning the relationship between experience and learning in educational programs

    Intra-regional classification of grape seeds produced in Mendoza province (Argentina) by multi-elemental analysis and chemometrics tools

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    The feasibility of the application of chemometric techniques associated with multi-element analysis for the classification of grape seeds according to their provenance vineyard soil was investigated. Grape seed samples from different localities of Mendoza province (Argentina) were evaluated. Inductively coupled plasma mass spectrometry (ICP-MS) was used for the determination of twenty-nine elements (Ag, As, Ce, Co, Cs, Cu, Eu, Fe, Ga, Gd, La, Lu, Mn, Mo, Nb, Nd, Ni, Pr, Rb, Sm, Te, Ti, Tl, Tm, U, V, Y, Zn and Zr). Once the analytical data were collected, supervised pattern recognition techniques such as linear discriminant analysis (LDA), partial least square discriminant analysis (PLS-DA), k-nearest neighbors (k-NN), support vector machine (SVM) and Random Forest (RF) were applied to construct classification/discrimination rules. The results indicated that nonlinear methods, RF and SVM, perform best with up to 98% and 93% accuracy rate, respectively, and therefore are excellent tools for classification of grapes.Fil: Canizo, Brenda Vanina. Universidad Nacional de Cuyo. Facultad de Ciencias Exactas y Naturales. Laboratorio de Química Analítica para Investigación y Desarrollo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; ArgentinaFil: Escudero, Leticia Belén. Universidad Nacional de Cuyo. Facultad de Ciencias Exactas y Naturales. Laboratorio de Química Analítica para Investigación y Desarrollo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; ArgentinaFil: Pérez, María Belén. Universidad Nacional de Cuyo. Facultad de Ciencias Exactas y Naturales. Laboratorio de Química Analítica para Investigación y Desarrollo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; ArgentinaFil: Pellerano, Roberto Gerardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Química Básica y Aplicada del Nordeste Argentino. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas Naturales y Agrimensura. Instituto de Química Básica y Aplicada del Nordeste Argentino; ArgentinaFil: Wuilloud, Rodolfo German. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Química Básica y Aplicada del Nordeste Argentino. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas Naturales y Agrimensura. Instituto de Química Básica y Aplicada del Nordeste Argentino; Argentin

    From truth to trust: the impact of blockchain traceability on trust in product authenticity

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    In the global marketplace, customers are increasingly unaware of the source, provenance, and authenticity of products. Early research has shown that the introduction of blockchain technology into the supply chain area can make it more transparent and trustworthy. As a platform that supports distributed, cryptographically secure, auditable transactions, blockchain has expanded from the domain of digital cryptocurrency into the domain of physical asset provenance and ownership tracking and tracing. This research examines blockchain support of trust in product authenticity adopting a two-paper dissertation format. In the first conceptual paper, I develop a conceptual framework on blockchain technology\u27s unique features and characteristics and how it can boost trust in product authenticity. The second paper adopts the conceptual framework to test through a vignette experiment the effects of blockchain traceability, product identification, and the interaction between them on trust in product origin authenticity. Academics can use this research to develop new instruments to inform practice about how blockchain can boost trust in product authenticity. Results from this study can inform managers considering investments into blockchain solutions and unique product identification as a customer product authenticity, brand protection, or anti-counterfeiting strategy

    Verification and validation of models

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    Simulation Models;econometrics

    Design and implementation of a multi-modal biometric system for company access control

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    This paper is about the design, implementation, and deployment of a multi-modal biometric system to grant access to a company structure and to internal zones in the company itself. Face and iris have been chosen as biometric traits. Face is feasible for non-intrusive checking with a minimum cooperation from the subject, while iris supports very accurate recognition procedure at a higher grade of invasivity. The recognition of the face trait is based on the Local Binary Patterns histograms, and the Daughman\u2019s method is implemented for the analysis of the iris data. The recognition process may require either the acquisition of the user\u2019s face only or the serial acquisition of both the user\u2019s face and iris, depending on the confidence level of the decision with respect to the set of security levels and requirements, stated in a formal way in the Service Level Agreement at a negotiation phase. The quality of the decision depends on the setting of proper different thresholds in the decision modules for the two biometric traits. Any time the quality of the decision is not good enough, the system activates proper rules, which ask for new acquisitions (and decisions), possibly with different threshold values, resulting in a system not with a fixed and predefined behaviour, but one which complies with the actual acquisition context. Rules are formalized as deduction rules and grouped together to represent \u201cresponse behaviors\u201d according to the previous analysis. Therefore, there are different possible working flows, since the actual response of the recognition process depends on the output of the decision making modules that compose the system. Finally, the deployment phase is described, together with the results from the testing, based on the AT&T Face Database and the UBIRIS database

    Smart Technologies for Environmental Safety and Knowledge Enhancement in Intermodal Transport

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    International concerns about security in transport systems are leading to a new international regulation in this field. This introduces new requirements for operators and authorities as well as it opens new challenges, in particular when referred to seaports and maritime transport in the Mediterranean area, where many seaport terminals and infrastructures are affected by a noteworthy technological divide from North European contexts. In such contexts, the adoption of the new regulations can represent the right chance for upgrading the local operative standards, increasing latu sensu the quality of maritime transport performances, while conferring a greater level to security and safety checks. This paper explores the chances for increasing the level of Mediterranean seaport competitiveness allowed by technological innovations in transport systems, both in operations and organization of these infrastructures. The aim of the work is to study the effects of the adoption of technological solutions such as wireless communications and radiofrequency identification on the competitiveness of Mediterranean seaport infrastructures. Technological solutions designed to identify good items help operators in organizing activities in terminals and make maritime transport faster in delivering goods, by cutting the handling time and costs in seaport terminals. Seaports that adopt this kind of technologies, and the surrounding economic areas connected to seaports, have a greater attractiveness on shipping companies and operators, since they allow faster handling activities and easier checks on goods. Besides, the analysis of direct and indirect effects of the use of such technologies specifically focuses on the contribution that the use of these solutions gives in ensuring higher security levels, by increasing the level of information and knowledge associated to goods. The different types of security provided (e.g. for people, environment and goods) and the extreme flexibility of the technologies involved give the overall worth of the challenge. It seems to be a great chance of growth for the Mediterranean area, more than a mere compliance to the international security regulations.
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