Efficient Decision Support Systems

This series is directed to diverse managerial professionals who are leading the transformation of individual domains by using expert information and domain knowledge to drive decision support systems (DSSs). The series offers a broad range of subjects addressed in specific areas such as health care, business management, banking, agriculture, environmental improvement, natural resource and spatial management, aviation administration, and hybrid applications of information technology aimed to interdisciplinary issues. This book series is composed of three volumes: Volume 1 consists of general concepts and methodology of DSSs; Volume 2 consists of applications of DSSs in the biomedical domain; Volume 3 consists of hybrid applications of DSSs in multidisciplinary domains. The book is shaped upon decision support strategies in the new infrastructure that assists the readers in full use of the creative technology to manipulate input data and to transform information into useful decisions for decision makers

<Articles>Maikon and Cyber-Capitalism: Some Preliminary Remarks on a History of Computerization in Japan, 1960–1990

This paper presents a preliminary sketching of research in progress, namely how computers were designed in all best interest of serving human social interaction, how they grew out of their imagined functions, becoming the revolutionary tool of cybernetic capitalism. A few years after their introduction in the United States, in early 1980s Japan, microcomputers were developed, produced en masse, and sold to their first users. But to archive their use as an extension of the factory, a tool to gain unlimited access to what Marx has called the workers “social disposable time, ” the computer machine had to be constantly interconnected to the other “limbs” of the factory machine. The creation of the first computer network in Japan, the MARS seat reservation system was based on cybernetics, creating a complex system to automatize Japanese National Railways—a threat that to its trade union was beyond comprehension. Beyond automation, in the 1980s, a student computer club at Kyoto University created PLANET, a network of different home computers (maikon) to democratize computer use. Their humanistic approach created a standardized and unified system, creating a machine which operation would revolutionize its economic base

Analyzing Web Server Access Log Files Using Data Mining Techniques

Nowadays web is not only considered as a network for acquiring data, buying products and obtaining services but as a social environment for interaction and information sharing. As the number of web sites continues to grow it becomes more difficult for users to find and extract information. As a solution to that problem, during the last decade, web mining is used to evaluate the web sites, to personalize the information that is displayed to a user or set of users or to adapt the indexing structure of a web site to meet the needs of the users. In this work we describe a methodology for web usage mining that enables discovering user access patterns. Particularly we are interested whether the topology of the web site matches the desires of the users. Data collections that are used for analysis and interpretation of user viewing patterns are taken from the web server log files. Data mining techniques, such as classification, clustering and association rules are applied on preprocessed data. The intent of this research is to propose techniques for improvement of user perception and interaction with a web site

Explanatory machine learning for sequential human teaching

The topic of comprehensibility of machine-learned theories has recently drawn increasing attention. Inductive Logic Programming (ILP) uses logic programming to derive logic theories from small data based on abduction and induction techniques. Learned theories are represented in the form of rules as declarative descriptions of obtained knowledge. In earlier work, the authors provided the first evidence of a measurable increase in human comprehension based on machine-learned logic rules for simple classification tasks. In a later study, it was found that the presentation of machine-learned explanations to humans can produce both beneficial and harmful effects in the context of game learning. We continue our investigation of comprehensibility by examining the effects of the ordering of concept presentations on human comprehension. In this work, we examine the explanatory effects of curriculum order and the presence of machine-learned explanations for sequential problem-solving. We show that 1) there exist tasks A and B such that learning A before B has a better human comprehension with respect to learning B before A and 2) there exist tasks A and B such that the presence of explanations when learning A contributes to improved human comprehension when subsequently learning B. We propose a framework for the effects of sequential teaching on comprehension based on an existing definition of comprehensibility and provide evidence for support from data collected in human trials. Empirical results show that sequential teaching of concepts with increasing complexity a) has a beneficial effect on human comprehension and b) leads to human re-discovery of divide-and-conquer problem-solving strategies, and c) studying machine-learned explanations allows adaptations of human problem-solving strategy with better performance.Comment: Submitted to the International Joint Conference on Learning & Reasoning (IJCLR) 202

Predictability, complexity and learning

We define {\em predictive information} $I_{\rm pred} (T)$ as the mutual information between the past and the future of a time series. Three qualitatively different behaviors are found in the limit of large observation times $T$: $I_{\rm pred} (T)$ can remain finite, grow logarithmically, or grow as a fractional power law. If the time series allows us to learn a model with a finite number of parameters, then $I_{\rm pred} (T)$ grows logarithmically with a coefficient that counts the dimensionality of the model space. In contrast, power--law growth is associated, for example, with the learning of infinite parameter (or nonparametric) models such as continuous functions with smoothness constraints. There are connections between the predictive information and measures of complexity that have been defined both in learning theory and in the analysis of physical systems through statistical mechanics and dynamical systems theory. Further, in the same way that entropy provides the unique measure of available information consistent with some simple and plausible conditions, we argue that the divergent part of $I_{\rm pred} (T)$ provides the unique measure for the complexity of dynamics underlying a time series. Finally, we discuss how these ideas may be useful in different problems in physics, statistics, and biology.Comment: 53 pages, 3 figures, 98 references, LaTeX2

Relational Understanding as Inclusion Tool for Children with Math Learning Disabilities

El presente proyecto resalta la importancia de enseñar las operaciones matemáticas de la suma y la resta desde el entendimiento relacional, para permitir al alumnado con dificultades de aprendizaje adquirir una comprensión matemática significativa, huyendo así de la memorización de múltiples procedimientos. Esto les permite concebir las matemáticas como una herramienta que les acerca y facilita la comprensión de la vida que les rodea. Concretamente en nuestro caso, su aplicación les permite reconocer y entender las operaciones de la suma y la resta en diferentes situaciones o contextos de su vida cotidiana. Se propone la implantación de un taller matemático en un colegio público de Pamplona para un alumno de sexto curso desde el aula externa de PT. Este taller, basado en el juego, pretende trabajar la aritmética de las matemáticas haciendo uso de materiales manipulativos como herramienta de aprendizaje para que el alumno con dificultades posea unos recursos que le permitan desarrollar sus habilidades matemáticas y construir conocimiento, de modo que cree y desarrolle sus propios procedimientos de resolución de problemas. Por último, analizamos los beneficios de esta propuesta y comprobamos la existencia de una progresión en el aprendizaje del alumno.The following project emphasizes the importance of teaching the mathematical operations of addition and subtraction from a relational understanding in order to enable students with learning disabilities (LD) to acquire a meaningful mathematical comprehension; thereby avoiding the memorisation of multiple procedures. This allows them to conceive mathematics as a tool that brings them closer and facilitates the understanding of the life around them. Specifically in our case, they can recognise and understand the operations of addition and subtraction in different situations or contexts of their daily lives throughout the application of mathematics. We propose the implementation of a mathematics workshop in a public school in Pamplona for a sixth-grader from the external special education (SPED) classroom. This workshop, based on play, aims to work on arithmetic using manipulative materials as learning tool. This enables the learners with difficulties to possess resources that allow them to develop their mathematical skills and build knowledge that will help them creating and developing their own problem-solving procedures. Lastly, we analyse the benefits of this proposal and verify the existence of a progression in the student's learning.Graduado o Graduada en Maestro en Educación Primaria por la Universidad Pública de NavarraLehen Hezkuntzako Irakasletzan Graduatua Nafarroako Unibertsitate Publikoa