Louisiana Tech vs Clemson (9/7/2002)

Louisiana Tech vs Clemson (9/7/2002)https://tigerprints.clemson.edu/fball_prgms/1276/thumbnail.jp

The Hilltop 2-14-1997

https://dh.howard.edu/hilltop_902000/1179/thumbnail.jp

University of San Diego News Print Media Coverage 2008.04

Printed clippings housed in folders with a table of contents arranged by topic.https://digital.sandiego.edu/print-media/1063/thumbnail.jp

Deep Networks and Knowledge: from Rule Learning to Neural-Symbolic Argument Mining

Deep Learning has revolutionized the whole discipline of machine learning, heavily impacting fields such as Computer Vision, Natural Language Processing, and other domains concerned with the processing of raw inputs. Nonetheless, Deep Networks are still difficult to interpret, and their inference process is all but transparent. Moreover, there are still challenging tasks for Deep Networks: contexts where the success depends on structured knowledge that can not be easily provided to the networks in a standardized way. We aim to investigate the behavior of Deep Networks, assessing whether they are capable of learning complex concepts such as rules and constraints without explicit information, and then how to improve them by providing such symbolic knowledge in a general and modular way. We start by addressing two tasks: learning the rule of a game and learning to construct the solution to Constraint Satisfaction Problems. We provide the networks only with examples, without encoding any information regarding the task. We observe that the networks are capable of learning to play by the rules and to make feasible assignments in the CSPs. Then, we move to Argument Mining, a complex NLP task which consists of finding the argumentative elements in a document and identifying their relationships. We analyze Neural Attention, a mechanism widely used in NLP to improve networks' performance and interpretability, providing a taxonomy of its implementations. We exploit such a method to train an ensemble of deep residual networks and test them on four different corpora for Argument Mining, reaching or advancing the state of the art in most of the datasets we considered for this study. Finally, we realize the first implementation of neural-symbolic argument mining. We use the Logic Tensor Networks framework to introduce logic rules during the training process and establish that they give a positive contribution under multiple dimensions

Historia, evolución y perspectivas de futuro en la utilización de técnicas de simulación en la gestión portuaria: aplicaciones en el análisis de operaciones, estrategia y planificación portuaria

Programa Oficial de Doutoramento en Análise Económica e Estratexia Empresarial. 5033V0[Resumen] Las técnicas de simulación, tal y como hoy las conocemos, comenzaron a mediados del siglo XX; primero con la aparición del primer computador y el desarrollo del método Monte Carlo, y más tarde con el desarrollo del primer simulador de propósito específico conocido como GPS y desarrollado por Geoffrey Gordon en IBM y la publicación del primer texto completo dedicado a esta materia y llamado the Art of Simulation (K.D. Tocher, 1963). Estás técnicas han evolucionado de una manera extraordinaria y hoy en día están plenamente implementadas en diversos campos de actividad. Las instalaciones portuarias no han escapado de esta tendencia, especialmente las dedicadas al tráfico de contenedores. Efectivamente, las características intrínsecas de este sector económico, le hacen un candidato idóneo para la implementación de modelos de simulación con propósitos y alcances muy diversos. No existe, sin embargo y hasta lo que conocemos, un trabajo científico que compile y analice pormenorizadamente tanto la historia como la evolución de simulación en ambientes portuarios, ayudando a clasificar los mismos y determinar cómo estos pueden ayudar en el análisis económico de estas instalaciones y en la formulación de las oportunas estrategias empresariales. Este es el objetivo último de la presente tesis doctoral.[Resumo] As técnicas de simulación, tal e como hoxe as coñecemos, comezaron a mediados do século XX; primeiro coa aparición do computador e o desenvolvemento do método Monte Carlo e máis tarde co desenvolvemento do primeiro simulador de propósito específico coñecido como GPS e desenvolvido por Geoffrey Gordon en IBM e a publicación do primeiro texto completo dedicado a este tema chamado “A Arte da Simulación” (K.D. Tocher, 1963). Estas técnicas evolucionaron dun xeito extraordinario e hoxe en día están plenamente implementadas en diversos campos de actividade. As instalacións portuarias non escaparon desta tendencia, especialmente as dedicadas ao tráfico de contenedores. Efectivamente, as características intrínsecas deste sector económico, fanlle un candidato idóneo para a implementación de modelos de simulación con propósitos e alcances moi variados. Con todo, e ata o que coñecemos, non existe un traballo científico que compila e analiza de forma detallada tanto a historia como a evolución da simulación en estes ambientes portuarios, clasificando os mesmos e determinando como estes poden axudar na análise económica destas instalacións e na formulación das oportunas estratexias empresariais. Este é o último obxectivo da presente tese doutoral.[Abstract] Simulation, to the extend that we understand it nowadays, began in the middle of the 20th century; first with the appearance of the computer and the development of the Monte Carlo method, and later with the development of the first specific purpose simulator known as GPS developed by Geoffrey Gordon in IBM. This author published the first full text devoted to this subject “The Art of Simulation” in 1963. These techniques have evolved in an extraordinary way and nowadays they are fully implemented in different fields of activity. Port facilities have not escaped this trend, especially those dedicated to container traffic. Indeed, the intrinsic characteristics of this economic sector, make it a suitable candidate for the implementation of simulation with very different purposes and scope. However, to the best of our knowelegde, there is not a scientific work that compiles and analyzes in detail both, the history and the evolution of simulation in port environments, contributing to classify them and determine how they can help in the economic analysis of these facilities and in the formulation of different business strategies. This is the ultimate goal of this doctoral thesis