The Effects of Ocular Dominance on Visual Processing in College Students

The role of ocular dominance in processing visual memory and analytic tasks is unknown. Research has variably showed both significant effects and no effect of ocular dominance on visual perception, motor control, and sports performance. The goal of this study was to determine if there is a relationship between ocular dominance and visual processing under a variety of computer gaming tasks. This was accomplished by first determining subjects’ ocular dominance through the Miles test, and then examining the subjects’ visual performance on four different Lumosity games under three conditions: left eye, right eye, and both eyes. Results suggest a relationship between ocular dominance and score in the simplest game used, named Raindrops, but did not identify a relationship between ocular dominance and accuracy. The study did not suggest a relationship within any of the other games that measure a variety of different abilities. It is possible a relationship between ocular dominance and score in the game Raindrops may have been due to the simplicity of the task. A small sample size (n = 20) may have also contributed to the inability to detect significant effects. Future studies incorporating larger sample sizes might focus on ocular dominance as it relates to simple arithmetic tasks

Quantifying Irregular Geographic Exposure on the Internet

In this work, we examine to what extent the Internet\u27s routing infrastructure needlessly exposes network traffic to nations geographically irrelevant to packet transmission. We quantify what countries are geographically logical to see on a network path traveling between two nations through the use of convex hulls circumscribing major population centers, and then compare that to the nation states observed in over 14.5 billion measured paths. Our results show that 49% of paths unnecessarily expose traffic to at least one nation. We further explore what nations, regions, and ASes expose and benefit from this geographically illogical traffic. As an example, we see that 23% of source/destination pairs located outside of the United States send their traffic through the US, but only 8% of those paths are geographically logical. Finally, we examine what happens when countries exercise both legal and physical control over ASes transiting traffic, gaining access to traffic outside of their geographic borders, but carried by organizations that fall under a particular country\u27s legal jurisdiction. When considering both the physical and legal countries that a path traverses, our results show that over 57% of paths expose traffic to a geographically irrelevant country

Modelling the Eddy Pattern in the harbour of Zeebrugge

Hydrodynamic

Automatic Ash Removal

In order to encourage a transition from oil to wood pellet heating in Maine homes, Maine Energy Systems desires that an automated ash removal system be designed for their wood pellet boilers. This project employs the use of both traditional and axiomatic design methods to develop an ash removal system for the MESys 6000c wood pellet boiler. Two solutions were developed for Maine Energy Systems using various design techniques. These solutions were prototyped, tested, and revised, resulting in recommendations made to Maine Energy Systems

Intelligent Personal Assistant in Business-Context: Key-feature Evaluation for User Acceptance

Background: The usage of intelligent personal assistants (IPA), such as Amazon Alexa or Google Assistant is increasing significantly, and voice-interaction is relevant for workflows in a business context. Objectives: This research aims to determine IPA characteristics to evaluate the usefulness of specific functions in a simulated production system of an Enterprise Resource Planning (ERP) software. A new function called explanation-mode is introduced to the scientific community and business world. Methods/Approach: As part of a design science research, an artefact, i.e. an add-on for speech-interaction in business software, was developed and evaluated using a survey among ERP users and researchers. Results: In the area of IPA-features, the search-function and speech input for textual fields were recognised as most useful. The newly introduced feature, the explanation mode, was positively received too. There is no significant correlation between the usefulness of features and participant-characteristics, affinity to technology or previous experience with IPAs in a private context, which is in line with previous studies in the private environment leading to the conclusion that the task attraction is the most important element for usefulness. Conclusions: Most of the participants agreed that the speech-input is not able to fully substitute standard input devices, such as a keyboard or a mouse, so the IPA is recognised as an addition to traditional input methods. The usefulness is rated high especially for speech-input for long text fields, calling up masks and search-functions

A selective role for neuronal activity regulated pentraxin in the processing of sensory-specific incentive value

Neuronal activity regulated pentraxin (Narp) is a secreted neuronal product which clusters AMPA receptors and regulates excitatory synaptogenesis. Although Narp is selectively enriched in brain, its role in behavior is not known. As Narp is expressed prominently in limbic regions, we examined whether Narp deletion affects performance on tasks used to assess motivational consequences of food-rewarded learning. Narp knock-out (KO) mice were unimpaired in learning simple pavlovian discriminations, instrumental lever pressing, and in acquisition of at least two aspects of pavlovian incentive learning, conditioned reinforcement and pavlovian-instrumental transfer. In contrast, Narp deletion resulted in a substantial deficit in the ability to use specific outcome expectancies to modulate instrumental performance in a devaluation task. In this task, mice were trained to respond on two levers for two different rewards. After training, mice were prefed with one of the two rewards, devaluing it. Responding on both levers was then assessed in extinction. Whereas control mice showed a significant preference in responding on the lever associated with the nondevalued reward, Narp KO mice responded equally on both levers, failing to suppress responding on the lever associated with the devalued reward. Both groups consumed more of the nondevalued reward in a subsequent choice test, indicating Narp KO mice could distinguish between the rewards themselves. These data suggest Narp has a selective role in processing sensory-specific information necessary for appropriate devaluation performance, but not in general motivational effects of reward-predictive cues on performance

The effect of a new drag-law parameterization on ice shelf water plume dynamics

A drag law accounting for Ekman rotation adjacent to a flat, horizontal bou ndary is proposed for use in a plume model that is written in terms of the depth-mean velocity. The drag l aw contains a variable turning angle between the mean velocity and the drag imposed by the turbulent bound ary layer. The effect of the variable turning angle in the drag law is studied for a plume of ice shelf wat er (ISW) ascending and turning beneath an Antarctic ice shelf with draft decreasing away from the groundi ng line. As the ISW plume ascends the sloping ice shelf–ocean boundary, it can melt the ice shelf, wh ich alters the buoyancy forcing driving the plume motion. Under these conditions, the typical turning ang le is of order 10° over most of the plume area for a range of drag coefficients (the minus sign arises for th e Southern Hemisphere). The rotation of the drag with respect to the mean velocity is found to be signifi cant if the drag coefficient exceeds 0.003; in this case the plume body propagates farther along and across the b ase of the ice shelf than a plume with the standard quadratic drag law with no turning angle

Transformation of graphical models to support knowledge transfer

Menschliche Experten verfügen über die Fähigkeit, ihr Entscheidungsverhalten flexibel auf die jeweilige Situation abzustimmen. Diese Fähigkeit zahlt sich insbesondere dann aus, wenn Entscheidungen unter beschränkten Ressourcen wie Zeitrestriktionen getroffen werden müssen. In solchen Situationen ist es besonders vorteilhaft, die Repräsentation des zugrunde liegenden Wissens anpassen und Entscheidungsmodelle auf unterschiedlichen Abstraktionsebenen verwenden zu können. Weiterhin zeichnen sich menschliche Experten durch die Fähigkeit aus, neben unsicheren Informationen auch unscharfe Wahrnehmungen in die Entscheidungsfindung einzubeziehen. Klassische entscheidungstheoretische Modelle basieren auf dem Konzept der Rationalität, wobei in jeder Situation die nutzenmaximale Entscheidung einer Entscheidungsfunktion zugeordnet wird. Neuere graphbasierte Modelle wie Bayes\u27sche Netze oder Entscheidungsnetze machen entscheidungstheoretische Methoden unter dem Aspekt der Modellbildung interessant. Als Hauptnachteil lässt sich die Komplexität nennen, wobei Inferenz in Entscheidungsnetzen NP-hart ist. Zielsetzung dieser Dissertation ist die Transformation entscheidungstheoretischer Modelle in Fuzzy-Regelbasen als Zielsprache. Fuzzy-Regelbasen lassen sich effizient auswerten, eignen sich zur Approximation nichtlinearer funktionaler Beziehungen und garantieren die Interpretierbarkeit des resultierenden Handlungsmodells. Die Übersetzung eines Entscheidungsmodells in eine Fuzzy-Regelbasis wird durch einen neuen Transformationsprozess unterstützt. Ein Agent kann zunächst ein Bayes\u27sches Netz durch Anwendung eines in dieser Arbeit neu vorgestellten parametrisierten Strukturlernalgorithmus generieren lassen. Anschließend lässt sich durch Anwendung von Präferenzlernverfahren und durch Präzisierung der Wahrscheinlichkeitsinformation ein entscheidungstheoretisches Modell erstellen. Ein Transformationsalgorithmus kompiliert daraus eine Regelbasis, wobei ein Approximationsmaß den erwarteten Nutzenverlust als Gütekriterium berechnet. Anhand eines Beispiels zur Zustandsüberwachung einer Rotationsspindel wird die Praxistauglichkeit des Konzeptes gezeigt.Human experts are able to flexible adjust their decision behaviour with regard to the respective situation. This capability pays in situations under limited resources like time restrictions. It is particularly advantageous to adapt the underlying knowledge representation and to make use of decision models at different levels of abstraction. Furthermore human experts have the ability to include uncertain information and vague perceptions in decision making. Classical decision-theoretic models are based directly on the concept of rationality, whereby the decision behaviour prescribed by the principle of maximum expected utility. For each observation some optimal decision function prescribes an action that maximizes expected utility. Modern graph-based methods like Bayesian networks or influence diagrams make use of modelling. One disadvantage of decision-theoretic methods concerns the issue of complexity. Finding an optimal decision might become very expensive. Inference in decision networks is known to be NP-hard. This dissertation aimed at combining the advantages of decision-theoretic models with rule-based systems by transforming a decision-theoretic model into a fuzzy rule-based system. Fuzzy rule bases are an efficient implementation from a computational point of view, they can approximate non-linear functional dependencies and they are also intelligible. There was a need for establishing a new transformation process to generate rule-based representations from decision models, which provide an efficient implementation architecture and represent knowledge in an explicit, intelligible way. At first, an agent can apply the new parameterized structure learning algorithm to identify the structure of the Bayesian network. The use of learning approaches to determine preferences and the specification of probability information subsequently enables to model decision and utility nodes and to generate a consolidated decision-theoretic model. Hence, a transformation process compiled a rule base by measuring the utility loss as approximation measure. The transformation process concept has been successfully applied to the problem of representing condition monitoring results for a rotation spindle