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- Heintz, Fredrik, 1975-
(author)
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DyKnow : A Stream-Based Knowledge Processing Middleware Framework
- 2009
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Doctoral thesis (other academic/artistic)abstract
- As robotic systems become more and more advanced the need to integrate existing deliberative functionalities such as chronicle recognition, motion planning, task planning, and execution monitoring increases. To integrate such functionalities into a coherent system it is necessary to reconcile the different formalisms used by the functionalities to represent information and knowledge about the world. To construct and integrate these representations and maintain a correlation between them and the environment it is necessary to extract information and knowledge from data collected by sensors. However, deliberative functionalities tend to assume symbolic and crisp knowledge about the current state of the world while the information extracted from sensors often is noisy and incomplete quantitative data on a much lower level of abstraction. There is a wide gap between the information about the world normally acquired through sensing and the information that is assumed to be available for reasoning about the world.As physical autonomous systems grow in scope and complexity, bridging the gap in an ad-hoc manner becomes impractical and inefficient. Instead a principled and systematic approach to closing the sensereasoning gap is needed. At the same time, a systematic solution has to be sufficiently flexible to accommodate a wide range of components with highly varying demands. We therefore introduce the concept of knowledge processing middleware for a principled and systematic software framework for bridging the gap between sensing and reasoning in a physical agent. A set of requirements that all such middleware should satisfy is also described.A stream-based knowledge processing middleware framework called DyKnow is then presented. Due to the need for incremental refinement of information at different levels of abstraction, computations and processes within the stream-based knowledge processing framework are modeled as active and sustained knowledge processes working on and producing streams. DyKnow supports the generation of partial and context dependent stream-based representations of past, current, and potential future states at many levels of abstraction in a timely manner.To show the versatility and utility of DyKnow two symbolic reasoning engines are integrated into Dy-Know. The first reasoning engine is a metric temporal logical progression engine. Its integration is made possible by extending DyKnow with a state generation mechanism to generate state sequences over which temporal logical formulas can be progressed. The second reasoning engine is a chronicle recognition engine for recognizing complex events such as traffic situations. The integration is facilitated by extending DyKnow with support for anchoring symbolic object identifiers to sensor data in order to collect information about physical objects using the available sensors. By integrating these reasoning engines into DyKnow, they can be used by any knowledge processing application. Each integration therefore extends the capability of DyKnow and increases its applicability.To show that DyKnow also has a potential for multi-agent knowledge processing, an extension is presented which allows agents to federate parts of their local DyKnow instances to share information and knowledge.Finally, it is shown how DyKnow provides support for the functionalities on the different levels in the JDL Data Fusion Model, which is the de facto standard functional model for fusion applications. The focus is not on individual fusion techniques, but rather on an infrastructure that permits the use of many different fusion techniques in a unified framework.The main conclusion of this thesis is that the DyKnow knowledge processing middleware framework provides appropriate support for bridging the sense-reasoning gap in a physical agent. This conclusion is drawn from the fact that DyKnow has successfully been used to integrate different reasoning engines into complex unmanned aerial vehicle (UAV) applications and that it satisfies all the stated requirements for knowledge processing middleware to a significant degree.
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| 2. |
- Heintz, Fredrik
(author)
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FCFoo99
- 2000
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In: Proceedings of RoboCup-99: Robot Soccer World Cup III (RoboCup). - : Springer London. - 3540410430 ; , s. 563-566
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Conference paper (peer-reviewed)abstract
- Introduction The emphasis of FCFoo was mainly on building a library for developers of RoboCup teams, designed especially for educational use. After the competition the library was more or less totally rewritten and nally published as part of the Master Thesis of Fredrik Heintz [4]. The agents are built on a layered reactive-deliberative architecture. The four layers describes the agent on dierent levels of abstraction and deliberation. The lowest level is mainly reactive while the others are more deliberate. The teamwork is based on nite automatas and roles. A role is a set of attributes describing some of the behaviour of a player. The decision-making uses decisiontrees to classify the situation and select the appropriate skill to perform. The other two layers are used to calculate the actual command to be sent to the server. The agent architecture and the basic design are inspired by the champions of RoboCup'98, CMUnited [6, 7]. The idea of using decision-trees and role
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| 3. |
- Herman, Pawel Andrzej, 1979-, et al.
(author)
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Design and on-line evaluation of type-2 fuzzy logic system-based framework for handling uncertainties in BCI classification
- 2008
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In: 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. - 9781424418152 ; , s. 4242-4245
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Conference paper (peer-reviewed)abstract
- The practical applicability of brain-computer interface (BCI) technology is limited due to its insufficient reliability and robustness. One of the major problems in this regard is the extensive variability and inconsistency of brain signal patterns, observed especially in electroencephalogram (EEG). This paper presents a fuzzy logic (FL) approach to the problem of handling of the resultant uncertainty effects. In particular, it outlines the design of a novel type-2 FL system (T2FLS) classifier within the framework of an EEG-based BCI, and examines its on-line applicability in the presence of shortand long-term nonstationarities of spectral EEG correlates of motor imagery (imagination of left vs. right hand movement). The developed system is shown to effectively cope with realtime constraints. In addition, a comparative post hoc analysis has revealed that the proposed T2FLS classifier outperforms conventional BCI methods, like LDA and SVM, in terms of the maximum classification accuracy (CA) rates by a relatively small, yet statistically significant, margin.
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| 4. |
- Karkehabadi, Saeid, et al.
(author)
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Improving the thermal stability of cellobiohydrolase Cel7A from Hypocrea jecorina by directed evolution
- 2017
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In: Journal of Biological Chemistry. - 0021-9258 .- 1083-351X. ; 292, s. 17418-17430
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Journal article (peer-reviewed)abstract
- Secreted mixtures of Hypocrea jecorina cellulases are able to efficiently degrade cellulosic biomass to fermentable sugars at large, commercially relevant scales. H. jecorina Cel7A, cellobiohydrolase I, from glycoside hydrolase family 7, is the workhorse enzyme of the process. However, the thermal stability of Cel7A limits its use to processes where temperatures are no higher than 50 degrees C. Enhanced thermal stability is desirable to enable the use of higher processing temperatures and to improve the economic feasibility of industrial biomass conversion. Here, we enhanced the thermal stability of Cel7A through directed evolution. Sites with increased thermal stability properties were combined, and a Cel7A variant (FCA398) was obtained, which exhibited a 10.4 degrees C increase in T-m and a 44-fold greater half-life compared with the wild-type enzyme. This Cel7A variant contains 18 mutated sites and is active under application conditions up to at least 75 degrees C. The X-ray crystal structure of the catalytic domain was determined at 2.1 angstrom resolution and showed that the effects of the mutations are local and do not introduce major backbone conformational changes. Molecular dynamics simulations revealed that the catalytic domain of wild-type Cel7A and the FCA398 variant exhibit similar behavior at 300 K, whereas at elevated temperature (475 and 525 K), the FCA398 variant fluctuates less and maintains more native contacts over time. Combining the structural and dynamic investigations, rationales were developed for the stabilizing effect at many of the mutated sites.
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