Through a heuristics approach, the author began an exploration of the meaning, both intellectually and emotionally, of personal experiences in organisations. Change and learning was focused on, and how continual rounds of restructuring impacted on the writer as a participant/observer. The lack of spirituality in organisations, how we hide our hearts and souls and how we seek certainty using static models, theories and plans became underlying themes through the work. The findings of the research include outputs such as the development of an organisational model of complexity, but more so outcomes that were the intuitive insights that were gained during the research process / Master of Science (Hons)

This study takes as its focus young children's intuitive knowledge of randomness. Previous work in this field has studied the misconceptions that people, especially adults, hold in making judgements of chance (see, for example, the work of Kahneman & Tversky and Konold). In contrast, I study how primitive meaningsf or randomnessfo rm a basis for new meanings,a processw hich the misconceptionsa pproachf ails to illuminate. The guiding principle for this study is that the observation of students' evolving thought in a carefully designedc omputer-basedd omain will provide a betteru nderstanding of how the specific features of the domain shape and are shaped by activities within it. There are, then, two deeply connected strands to this thesis: the study of children's evolving meanings for randomness as expressed in a computer-based microworld, and the articulation of design principles which encapsulate pedagogic meaningsfor that microworld. More specifically, the thesis aims to shed light upon the answers to four crucial questions: Meanings for the domain: What do formalisms of stochastic behaviour look like in a domain of abstraction? What structures in the domain for stochastic abstraction optimise the articulation of intuitions and the construction of new meanings? Meanings in the domain: What articulations of informal intuitions of stochastic behaviour do we observe? How do the structures of the domain support the forging of situated meanings? The study uses an iterative design methodology, which cycles between the design of computer-based tools and the observ4tion of children, between the ages of 9 and II years, as they use these tools. The thesis identifies initial meanings for the behaviour of various stochastic phenomena and traces how new pieces of knowledge, especially relating to long term random behaviour, emerge through the forging of connections between the internal and external resources.

With a focus of always being connected, it's become typical for laptops and mobile devices to include multiple wireless network devices. Though the additional network devices have created mobility and versatility of how a user is connected, it is common for only one to be active at any given time. While likely that new mesh protocols will help maximize connectivity and power consumption by utilizing lower-power multi-hop techniques, it is still difficult to visualize these protocols due to the complexity created by each node's simple choices. Further challenges are presented by the variety of network devices which share frequency ranges with different output power, sensitivities, and antenna radiation patterns. Due to the complexity of these configurations and environments, it becomes clear that reproducible simulations are required. While several network simulators have been thoroughly tested over their many years of use, they often lack realistic handling of key factors that affect wireless networks. A few examples include cross-channel interference, propagation delays, interference caused by nodes beyond communication range, channel switching delays, and non-uniform radiation patterns. Another key limitation of these past tools is their limited methods for clearly displaying characteristics of multi-channel communication. Furthermore, these past utilities lack the graphical and interactive functions which promote the discovery of edge cases through the use of human intuition and pattern recognition. Even with their other limitations, many of these simulators are also extendable with new components and simulation abilities. As a result, a large set of protocols and other useful discoveries have been developed. While the concepts are well tested and verified, a new challenge is found when moving code from prototype to production due to code portability problems. Due to the sophistication of these creations, even small changes in code during a protocols release can have dramatic effects on its functionality. Both to encourage quicker development cycles and maintain code validation, it would be advantageous to provide simulation interfaces which directly match that of production systems. To overcome the various challenges presented and encourage the use of innate human abilities, this paper presents a novel simulation framework, Network Channel Visualizing Simulator (NCVS), with a real-time, interactive, 3D environment with clear representation and simulation of multi-channel RF communication through multiple network device types.

Numerical information is ubiquitous and people are continuously engaged in evaluating it by means of intuitive statistical judgments. Much research has evaluated if people’s judgments live up to the norms of statistical theory but directed far less attention to the cognitive processes that underlie the judgments. The present thesis outlines, compares, and tests two cognitive models for intuitive statistical judgments, summarized in the metaphors of the lazy and eager intuitive statistician. In short, the lazy statistician postpones judgments to the time of a query when the properties of a small sample of values retrieved from memory serve as proxies for population properties. In contrast, the eager statistician abstracts summary representations of population properties online from incoming data. Four empirical studies were conducted. Study I outlined the two models and investigated whether an eager or a lazy statistician best describes how people make intuitive statistical judgments. In general the results supported the notion that people spontaneously engage in a lazy process. Under certain specific conditions, however, participants were able to induce abstract representations of the experienced data. Study II and Study III extended the models to describe naive point estimates (Study II) and inference about a generating distribution (Study III). The results indicated that both the former and the latter type of judgment was better described by a lazy than an eager model. Finally, Study IV, building on the support in Studies I-III, investigated boundary conditions for a lazy model by exploring if statistical judgments are influenced by common memory effects (primacy and recency). The results indicated no such effects, suggesting that the sampling from long-term memory in a lazy process is not conditional on when the data is encountered. The present thesis makes two major contributions. First, the lazy and eager models are first attempts at outlining a process model that could possibly be applied for a large variety of statistical judgments. Second, because a lazy process imposes boundary conditions on the accuracy of statistical judgments, the results suggest that the limitations of a lazy intuitive statistician would need to be taken into consideration in a variety of situations.

Many contemporary philosophers are committed – either implicitly or explicitly – to Propositionalism about thought-experimental intuitions. According to this view, thought-experimental intuitions are (1) phenomenally conscious, (2) spontaneous, (3) and non-theoretical; most importantly, Propositionalists claim that intuitions (4) bear consciously accessible propositional content. The negative project of this essay is a critique of (4), the rejection of which is tantamount to rejecting Propositionalism. In addition, I propose an alternative position – namely, Interpretationalism. According to Interpretationalism, intuitions possess the features ascribed in (1)-(3); however, they do not bear consciously accessible propositional content. Instead, intuitions acquire cognitive significance by virtue of being interpreted in light of a subject’s background beliefs.

Over the past few decades the use of industrial robots has increased the efficiency as well as competitiveness of many companies. Despite this fact, in many cases, robot automation investments are considered to be technically challenging. In addition, for most small and medium sized enterprises (SME) this process is associated with high costs. Due to their continuously changing product lines, reprogramming costs are likely to exceed installation costs by a large margin. Furthermore, traditional programming methods for industrial robots are too complex for an inexperienced robot programmer, thus assistance from a robot programming expert is often needed.  We hypothesize that in order to make industrial robots more common within the SME sector, the robots should be reprogrammable by technicians or manufacturing engineers rather than robot programming experts. In this thesis we propose a high-level natural language framework for interacting with industrial robots through an instructional programming environment for the user.  The ultimate goal of this thesis is to bring robot programming to a stage where it is as easy as working together with a colleague.In this thesis we mainly address two issues. The first issue is to make interaction with a robot easier and more natural through a multimodal framework. The proposed language architecture makes it possible to manipulate, pick or place objects in a scene through high level commands. Interaction with simple voice commands and gestures enables the manufacturing engineer to focus on the task itself, rather than programming issues of the robot. This approach shifts the focus of industrial robot programming from the coordinate based programming paradigm, which currently dominates the field, to an object based programming scheme.The second issue addressed is a general framework for implementing multimodal interfaces. There have been numerous efforts to implement multimodal interfaces for computers and robots, but there is no general standard framework for developing them. The general framework proposed in this thesis is designed to perform natural language understanding, multimodal integration and semantic analysis with an incremental pipeline and includes a novel multimodal grammar language, which is used for multimodal presentation and semantic meaning generation. / robot colleague project

The goal of this thesis is to develop an intuitive, adaptive, and flexible architecture for controlling intelligent mobile robots. This architecture is a hybrid architecture that combines deliberative planning, reactive control, finite state automata, behaviour trees and uses competition for behaviour selection. This behaviour selection is based on a task manager, which selects behaviours based on approximations of their applicability to the current situation and the expected reward value for performing that behaviour. One important feature of this architecture is that it makes important behavioural information explicit using Extensible Markup Language (XML). This explicit representation is an important part in making the architecture easy to debug and extend. The utility, intuitiveness and flexibility of this architecture is shown in an evaluation of this architecture against older control programs that lack such explicit behavioural representation. This evaluation was carried out by developing behaviours for several common robotic tasks and demonstrating common problems that arose during the course of this development. / February 2006

The goal of this thesis is to develop an intuitive, adaptive, and flexible architecture for controlling intelligent mobile robots. This architecture is a hybrid architecture that combines deliberative planning, reactive control, finite state automata, behaviour trees and uses competition for behaviour selection. This behaviour selection is based on a task manager, which selects behaviours based on approximations of their applicability to the current situation and the expected reward value for performing that behaviour. One important feature of this architecture is that it makes important behavioural information explicit using Extensible Markup Language (XML). This explicit representation is an important part in making the architecture easy to debug and extend. The utility, intuitiveness and flexibility of this architecture is shown in an evaluation of this architecture against older control programs that lack such explicit behavioural representation. This evaluation was carried out by developing behaviours for several common robotic tasks and demonstrating common problems that arose during the course of this development.

The goal of this thesis is to develop an intuitive, adaptive, and flexible architecture for controlling intelligent mobile robots. This architecture is a hybrid architecture that combines deliberative planning, reactive control, finite state automata, behaviour trees and uses competition for behaviour selection. This behaviour selection is based on a task manager, which selects behaviours based on approximations of their applicability to the current situation and the expected reward value for performing that behaviour. One important feature of this architecture is that it makes important behavioural information explicit using Extensible Markup Language (XML). This explicit representation is an important part in making the architecture easy to debug and extend. The utility, intuitiveness and flexibility of this architecture is shown in an evaluation of this architecture against older control programs that lack such explicit behavioural representation. This evaluation was carried out by developing behaviours for several common robotic tasks and demonstrating common problems that arose during the course of this development.

Thèse de doctorat en Sciences de l’Education présentée et soutenue publiquement par Gilles UBRICH Réalisée sous la direction de Monsieur le Professeur Jean HOUSSAYE 2011U.F.R. Psychologie, Sociologie, Sciences de l’Education Département des Sciences de l’Education Ecole Doctorale « Savoirs, Critique, Expertises » Laboratoire CIVIIC - EA 2657 / Submitted by David Antonio Costa (david.costa@ufsc.br) on 2014-12-09T00:43:47Z No. of bitstreams: 1 These-G-UBRICH.pdf: 1265163 bytes, checksum: 20c84c4029cf92198d34a7884e96908b (MD5) / Made available in DSpace on 2014-12-09T00:43:47Z (GMT). No. of bitstreams: 1 These-G-UBRICH.pdf: 1265163 bytes, checksum: 20c84c4029cf92198d34a7884e96908b (MD5) Previous issue date: 2011