THE INTERACTION BETWEEN INTERNAL AND EXTERNAL INFORMATION ON RELATIONAL DATA SEARCH

People often use tools to search for information. In order to improve the quality of an information search, it is important to understand how internal information, which is stored in user’s mind, and external information, represented by the interface of tools interact with each other. How information is distributed between internal and external representations significantly affects information search performance. However, few studies have examined the relationship between types of interface and types of search task in the context of information search. For a distributed information search task, how data are distributed, represented, and formatted significantly affects the user search performance in terms of response time and accuracy. Guided by UFuRT (User, Function, Representation, Task), a human-centered process, I propose a search model, task taxonomy. The model defines its relationship with other existing information models. The taxonomy clarifies the legitimate operations for each type of search task of relation data. Based on the model and taxonomy, I have also developed prototypes of interface for the search tasks of relational data. These prototypes were used for experiments. The experiments described in this study are of a within-subject design with a sample of 24 participants recruited from the graduate schools located in the Texas Medical Center. Participants performed one-dimensional nominal search tasks over nominal, ordinal, and ratio displays, and searched one-dimensional nominal, ordinal, interval, and ratio tasks over table and graph displays. Participants also performed the same task and display combination for twodimensional searches. Distributed cognition theory has been adopted as a theoretical framework for analyzing and predicting the search performance of relational data. It has been shown that the representation dimensions and data scales, as well as the search task types, are main factors in determining search efficiency and effectiveness. In particular, the more external representations used, the better search task performance, and the results suggest the ideal search performance occurs when the question type and corresponding data scale representation match. The implications of the study lie in contributing to the effective design of search interface for relational data, especially laboratory results, which are often used in healthcare activities.

Unconscious relational inference recruits the hippocampus

Relational inference denotes the capacity to encode, flexibly retrieve, and integrate multiple memories to combine past experiences to update knowledge and improve decision-making in new situations. Although relational inference is thought to depend on the hippocampus and consciousness, we now show in young, healthy men that it may occur outside consciousness but still recruits the hippocampus. In temporally distinct and unique subliminal episodes, we presented word pairs that either overlapped (“winter–red”, “red–computer”) or not. Effects of unconscious relational inference emerged in reaction times recorded during unconscious encoding and in the outcome of decisions made 1 min later at test, when participants judged the semantic relatedness of two supraliminal words. These words were either episodically related through a common word (“winter–computer” related through “red”) or unrelated. Hippocampal activity increased during the unconscious encoding of overlapping versus nonoverlapping word pairs and during the unconscious retrieval of episodically related versus unrelated words. Furthermore, hippocampal activity during unconscious encoding predicted the outcome of decisions made at test. Hence, unconscious inference may influence decision-making in new situations.

Unconscious relational encoding depends on hippocampus

Textbooks divide between human memory systems based on consciousness. Hippocampus is thought to support only conscious encoding, while neocortex supports both conscious and unconscious encoding. We tested whether processing modes, not consciousness, divide between memory systems in three neuroimaging experiments with 11 amnesic patients (mean age = 45.55 years, standard deviation = 8.74, range = 23-60) and 11 matched healthy control subjects. Examined processing modes were single item versus relational encoding with only relational encoding hypothesized to depend on hippocampus. Participants encoded and later retrieved either single words or new relations between words. Consciousness of encoding was excluded by subliminal (invisible) word presentation. Amnesic patients and controls performed equally well on the single item task activating prefrontal cortex. But only the controls succeeded on the relational task activating the hippocampus, while amnesic patients failed as a group. Hence, unconscious relational encoding, but not unconscious single item encoding, depended on hippocampus. Yet, three patients performed normally on unconscious relational encoding in spite of amnesia capitalizing on spared hippocampal tissue and connections to language cortex. This pattern of results suggests that processing modes divide between memory systems, while consciousness divides between levels of function within a memory system.

VISUAL MEMORY PROCESSING BY PRIMATES AND AVIANS IN A RELATIONAL TASK

Three rhesus monkeys (Macaca mulatta) and four pigeons (Columba livia) were trained in a visual serial probe recognition (SPR) task. A list of visual stimuli (slides) was presented sequentially to the subjects. Following the list and after a delay interval, a probe stimulus was presented that could be either from the list (Same) or not from the list (Different). The monkeys readily acquired a variable list length SPR task, while pigeons showed acquisition only under constant list length condition. However, monkeys memorized the responses to the probes (absolute strategy) when overtrained with the same lists and probes, while pigeons compared the probe to the list in memory (relational strategy). Performance of the pigeon on 4-items constant list length was disrupted when blocks of trials of different list lengths were imbedded between the 4-items blocks. Serial position curves for recognition at variable probe delays showed better relative performance on the last items of the list at short delays (0-0.5 seconds) and better relative performance on the initial items of the list at long delays (6-10 seconds for the pigeons and 20-30 seconds for the monkeys and a human adolescent). The serial position curves also showed reliable primacy and recency effects at intermediate probe delays. The monkeys showed evidence of using a relational strategy in the variable probe delay task. The results are the first demonstration of relational serial probe recognition performance in an avian and suggest similar underlying dynamic recognition memory mechanisms in primates and avians. ^

Los modelos de explicación para las novedades del desarrollo

Este trabajo examina los marcos epistémicos y su modus operandi sobre los modelos explicativos en la psicología del desarrollo. En primer lugar, los rasgos del marco epistémico de la escisión y su intervención en el modo ?legítimo? de explicar las competencias, habilidades y funciones psicológicas. En segundo lugar, se muestran las dificultades de dicho modelo, aún predominante entre los investigadores, cuando se pretende dar cuenta de la emergencia de comportamientos, sistemas conceptuales y funciones que son estrictamente novedosas, esto es, que no están dadas dentro del aparato mental ni fuera del propio proceso. En tercer lugar, se exploran las características de una explicación sistémica para dichas novedades, enmarcándola en una ontología y una epistemología relacional. Se identifican las características del modelo sistémico y se evalúa su eficacia respecto de la emergencia de sistemas conceptuales y funciones psicológicas nuevas en el desarrollo. Finalmente, se identifican dos versiones de dicha explicación: el sistema complejo del constructivismo y la perspectiva vigotskyana de la explicación, estableciendo una fuerte diferencia respecto de un sistema de interacciones no dialéctico

Los modelos de explicación para las novedades del desarrollo

Este trabajo examina los marcos epistémicos y su modus operandi sobre los modelos explicativos en la psicología del desarrollo. En primer lugar, los rasgos del marco epistémico de la escisión y su intervención en el modo ?legítimo? de explicar las competencias, habilidades y funciones psicológicas. En segundo lugar, se muestran las dificultades de dicho modelo, aún predominante entre los investigadores, cuando se pretende dar cuenta de la emergencia de comportamientos, sistemas conceptuales y funciones que son estrictamente novedosas, esto es, que no están dadas dentro del aparato mental ni fuera del propio proceso. En tercer lugar, se exploran las características de una explicación sistémica para dichas novedades, enmarcándola en una ontología y una epistemología relacional. Se identifican las características del modelo sistémico y se evalúa su eficacia respecto de la emergencia de sistemas conceptuales y funciones psicológicas nuevas en el desarrollo. Finalmente, se identifican dos versiones de dicha explicación: el sistema complejo del constructivismo y la perspectiva vigotskyana de la explicación, estableciendo una fuerte diferencia respecto de un sistema de interacciones no dialéctico

Los modelos de explicación para las novedades del desarrollo

Este trabajo examina los marcos epistémicos y su modus operandi sobre los modelos explicativos en la psicología del desarrollo. En primer lugar, los rasgos del marco epistémico de la escisión y su intervención en el modo ?legítimo? de explicar las competencias, habilidades y funciones psicológicas. En segundo lugar, se muestran las dificultades de dicho modelo, aún predominante entre los investigadores, cuando se pretende dar cuenta de la emergencia de comportamientos, sistemas conceptuales y funciones que son estrictamente novedosas, esto es, que no están dadas dentro del aparato mental ni fuera del propio proceso. En tercer lugar, se exploran las características de una explicación sistémica para dichas novedades, enmarcándola en una ontología y una epistemología relacional. Se identifican las características del modelo sistémico y se evalúa su eficacia respecto de la emergencia de sistemas conceptuales y funciones psicológicas nuevas en el desarrollo. Finalmente, se identifican dos versiones de dicha explicación: el sistema complejo del constructivismo y la perspectiva vigotskyana de la explicación, estableciendo una fuerte diferencia respecto de un sistema de interacciones no dialéctico

Relational and Allegorical Semantics for Constraint Logic Programming

El cálculo de relaciones binarias fue creado por De Morgan en 1860 para ser posteriormente desarrollado en gran medida por Peirce y Schröder. Tarski, Givant, Freyd y Scedrov demostraron que las álgebras relacionales son capaces de formalizar la lógica de primer orden, la lógica de orden superior así como la teoría de conjuntos. A partir de los resultados matemáticos de Tarski y Freyd, esta tesis desarrolla semánticas denotacionales y operacionales para la programación lógica con restricciones usando el álgebra relacional como base. La idea principal es la utilización del concepto de semántica ejecutable, semánticas cuya característica principal es el que la ejecución es posible utilizando el razonamiento estándar del universo semántico, este caso, razonamiento ecuacional. En el caso de este trabajo, se muestra que las álgebras relacionales distributivas con un operador de punto fijo capturan toda la teoría y metateoría estándar de la programación lógica con restricciones incluyendo los árboles utilizados en la búsqueda de demostraciones. La mayor parte de técnicas de optimización de programas, evaluación parcial e interpretación abstracta pueden ser llevadas a cabo utilizando las semánticas aquí presentadas. La demostración de la corrección de la implementación resulta extremadamente sencilla. En la primera parte de la tesis, un programa lógico con restricciones es traducido a un conjunto de términos relacionales. La interpretación estándar en la teoría de conjuntos de dichas relaciones coincide con la semántica estándar para CLP. Las consultas contra el programa traducido son llevadas a cabo mediante la reescritura de relaciones. Para concluir la primera parte, se demuestra la corrección y equivalencia operacional de esta nueva semántica, así como se define un algoritmo de unificación mediante la reescritura de relaciones. La segunda parte de la tesis desarrolla una semántica para la programación lógica con restricciones usando la teoría de alegorías—versión categórica del álgebra de relaciones—de Freyd. Para ello, se definen dos nuevos conceptos de Categoría Regular de Lawvere y _-Alegoría, en las cuales es posible interpretar un programa lógico. La ventaja fundamental que el enfoque categórico aporta es la definición de una máquina categórica que mejora e sistema de reescritura presentado en la primera parte. Gracias al uso de relaciones tabulares, la máquina modela la ejecución eficiente sin salir de un marco estrictamente formal. Utilizando la reescritura de diagramas, se define un algoritmo para el cálculo de pullbacks en Categorías Regulares de Lawvere. Los dominios de las tabulaciones aportan información sobre la utilización de memoria y variable libres, mientras que el estado compartido queda capturado por los diagramas. La especificación de la máquina induce la derivación formal de un juego de instrucciones eficiente. El marco categórico aporta otras importantes ventajas, como la posibilidad de incorporar tipos de datos algebraicos, funciones y otras extensiones a Prolog, a la vez que se conserva el carácter 100% declarativo de nuestra semántica. ABSTRACT The calculus of binary relations was introduced by De Morgan in 1860, to be greatly developed by Peirce and Schröder, as well as many others in the twentieth century. Using different formulations of relational structures, Tarski, Givant, Freyd, and Scedrov have shown how relation algebras can provide a variable-free way of formalizing first order logic, higher order logic and set theory, among other formal systems. Building on those mathematical results, we develop denotational and operational semantics for Constraint Logic Programming using relation algebra. The idea of executable semantics plays a fundamental role in this work, both as a philosophical and technical foundation. We call a semantics executable when program execution can be carried out using the regular theory and tools that define the semantic universe. Throughout this work, the use of pure algebraic reasoning is the basis of denotational and operational results, eliminating all the classical non-equational meta-theory associated to traditional semantics for Logic Programming. All algebraic reasoning, including execution, is performed in an algebraic way, to the point we could state that the denotational semantics of a CLP program is directly executable. Techniques like optimization, partial evaluation and abstract interpretation find a natural place in our algebraic models. Other properties, like correctness of the implementation or program transformation are easy to check, as they are carried out using instances of the general equational theory. In the first part of the work, we translate Constraint Logic Programs to binary relations in a modified version of the distributive relation algebras used by Tarski. Execution is carried out by a rewriting system. We prove adequacy and operational equivalence of the semantics. In the second part of the work, the relation algebraic approach is improved by using allegory theory, a categorical version of the algebra of relations developed by Freyd and Scedrov. The use of allegories lifts the semantics to typed relations, which capture the number of logical variables used by a predicate or program state in a declarative way. A logic program is interpreted in a _-allegory, which is in turn generated from a new notion of Regular Lawvere Category. As in the untyped case, program translation coincides with program interpretation. Thus, we develop a categorical machine directly from the semantics. The machine is based on relation composition, with a pullback calculation algorithm at its core. The algorithm is defined with the help of a notion of diagram rewriting. In this operational interpretation, types represent information about memory allocation and the execution mechanism is more efficient, thanks to the faithful representation of shared state by categorical projections. We finish the work by illustrating how the categorical semantics allows the incorporation into Prolog of constructs typical of Functional Programming, like abstract data types, and strict and lazy functions.