We describe a new computational cognitive model that is being developed for solving complex problems in bioinformatics. This cognitive model was developed based on observing biologists solving problems in their curren...
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ISBN:
(纸本)0769521908
We describe a new computational cognitive model that is being developed for solving complex problems in bioinformatics. This cognitive model was developed based on observing biologists solving problems in their current environments. Bioinformatics provides several challenges to current problem-solving environments. 1) massive heterogeneous data to mine and fuse;2) quantity of information is growing and changing on a monthly basis;3) knowledge base is being challenged and changed as biologists learn more (this occurs on a very short schedule). This paper describes the problem domain, evolution of this new model, the model itself how this model relates to current literature, and concludes with a summary of our ongoing research efforts.
We describe a new computational cognitive model that is being developed for solving complex problems in bioinformatics. This cognitive model was developed based on observing biologists solving problems in their curren...
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We describe a new computational cognitive model that is being developed for solving complex problems in bioinformatics. This cognitive model was developed based on observing biologists solving problems in their current environments. Bioinformatics provides several challenges to current problem-solving environments: 1) massive heterogeneous data to mine and fuse; 2) quantity of information is growing and changing on a monthly basis; 3) knowledge base is being challenged and changed as biologists learn more (this occurs on a very short schedule). This paper describes the problem domain, evolution of this new model, the model itself how this model relates to current literature, and concludes with a summary of our ongoing research efforts.
complex human motion (e.g. dance) sequences are typically analyzed by segmenting them into shorter motion sequences, called gestures. However, this segmentation process is subjective, and varies considerably from one ...
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complex human motion (e.g. dance) sequences are typically analyzed by segmenting them into shorter motion sequences, called gestures. However, this segmentation process is subjective, and varies considerably from one choreographer to another. Dance sequences also exhibit a large vocabulary of gestures. In this paper, we propose an algorithm called hierarchical activity segmentation. This algorithm employs a dynamic hierarchical layered structure to represent human anatomy, and uses low-level motion parameters to characterize motion in the various layers of this hierarchy, which correspond to different segments of the human body. This characterization is used with a naive Bayesian classifier to derive choreographer profiles from empirical data that are used to predict how particular choreographers segment gestures in other motion sequences. When the predictions were tested with a library of 45 3D motion capture sequences (with 185 distinct gestures) created by 5 different choreographers, they were found to be 93.3% accurate.
The accuracy of the inverse solution that finds the spatial location of the generating sources from averaged scalp-recorded event related potentials (ERPs) relies on assumptions about the ERP signals and the sources. ...
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The accuracy of the inverse solution that finds the spatial location of the generating sources from averaged scalp-recorded event related potentials (ERPs) relies on assumptions about the ERP signals and the sources. We provide evidence that using independent component analysis (ICA) as a signal decomposition filter prior to applying the inverse solution reveals sources that cannot be detected by conventional source localisation methods. Five clusters of sources emerged: a single source cluster in caudal cingulate and bilateral sources in secondary somatosensory cortex (SII), inferior parietal cortex, premotor cortex and insular cortex. The locations of the source dipoles were consistent with findings using fMRI and PET but have not all been previously detected in a single electrophysiological study. In addition, the time-course of the activation of these dipoles was estimated. The results suggest that using ICA to localise single trial data is a powerful tool for exploring the spatiotemporal dynamics of rapid and complex brain processes.
This study presents a shared document-based annotation tool, EDUCOSM. Usefulness of the system is empirically evaluated in a real-life collaborative learning context. Relationships between learner's self-rated use...
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This study presents a shared document-based annotation tool, EDUCOSM. Usefulness of the system is empirically evaluated in a real-life collaborative learning context. Relationships between learner's self-rated use of learning strategies, cognitive outcomes, and completion of various tasks in the system are investigated. An empirical study (n=31) was conducted in order to investigate various dependencies between variables from precourse self-rated questionnaire, system log file data collected during the course and postcourse e-mail survey.
This paper follows on from earlier work that our colleagues and ourselves presented at IJCNN 2001, IJCNN 2002 and FUZZ-ieee 2002. We referred to simulations of a recurrent network and of an adaptive system that was pa...
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This paper follows on from earlier work that our colleagues and ourselves presented at IJCNN 2001, IJCNN 2002 and FUZZ-ieee 2002. We referred to simulations of a recurrent network and of an adaptive system that was partly based on a recurrent network. Both models were successful in simulating human sequence learning in a reaction time paradigm that is widely used in cognitive science and experimental psychology. We argued that these models were not only successful in simulating human learning, but also in predicting successful generalization to novel sequences where humans show generalization, and a failure to generalize to novel sequences when humans fail. In this paper we present data from a novel experiment and novel simulations on a longer version of this serial reaction time task. Under these conditions the task appears to be more difficult to master for the human subjects and therefore more complex. Accordingly, humans were not able to learn that task at all. Their failure is predicted by both computational models. Combining these results with the earlier findings from the previous conferences suggests that both successful and unsuccessful human performance can be predicted by the computational models considered here.
The Advanced Tactical Architecture for Combat Knowledge System (ATACKS, formerly known as ABATIS) has been designed as a visualization tool to support commander's decision-making in a complex battlespace environme...
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The Advanced Tactical Architecture for Combat Knowledge System (ATACKS, formerly known as ABATIS) has been designed as a visualization tool to support commander's decision-making in a complex battlespace environment. ATACKS expands standard battlefield symbology by providing symbols for Stability and Support Operation (SASO) on three dimensional (3D) abstract battlespace terrains. Furthermore, it extends normal spatial visualization through process centered displays that seek to enhance the commander's understanding of the situation by presenting qualitative data in novel formats. In addition, external decision support tools communicate with ATACKS, through an application program interface (API) that can allow communication over a network as well as between systems on differing operating systems. With this capability, ATACKS can serve as an integration point for intelligent aiding systems'.
Planning of complex activities is a deliberative process and automation support for re-planning activities should provide for cognitive modeling of the planning process. One approach for modeling military planning sys...
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Planning of complex activities is a deliberative process and automation support for re-planning activities should provide for cognitive modeling of the planning process. One approach for modeling military planning systems is to partition the process into separable components and analyze the components individually. The paper takes the position that the cognitive model should contain details of the domain being supported and, especially for support of online re-planning, knowledge of the system implementation architecture, including performance modeling of the implementation architecture. A possible issue is the failure of the separable components assumption when the system is composed of components. We discuss these thoughts in some detail and provide an overview of a test bed framework being implemented to perform experiments on the validity of this approach. In particular, we are interested in creating analysis tools that apply metrics to sensed data to assist in determining when a re-planning activity is required and in prioritizing re-planning activities. The framework is intended to support experiments with military decision making and, in particular, with re-planning activities that support execution of a military operation order (OPORD). We are investigating use of a simulation tool to accumulate information at the message-packet-level and perform analysis at the network-application-level. We discuss use of this framework for pattern recognition of activities distributed in time and space. We provide an introduction to our approach for partitioning the problem space and some ideas on design of experiments using this approach.
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