ppxscal/embedding_network huggingface dataset:
Functional MRI and the Study of Human Consciousness
Authors: Dan Lloyd
Venue: Journal of Cognitive Neuroscience (2002)

Functional brain imaging offers new opportunities for the study of that most pervasive of cognitive conditions, human consciousness. Since consciousness is attendant to so much of human cognitive life, its study requires secondary analysis of multiple experimental datasets. Here, four preprocessed datasets from the National fMRI Data Center are considered: Hazeltine et al., Neural activation during response competition; Ishai et al., The representation of objects in the human occipital and temporal cortex; Mechelli et al., The effects of presentation rate during word and pseudoword reading; and Postle et al., Activity in human frontal cortex associated with spatial working memory and saccadic behavior. The study of consciousness also draws from multiple disciplines. In this article, the philosophical subdiscipline of phenomenology provides initial characterization of phenomenal structures conceptually necessary for an analysis of consciousness. These structures include phenomenal intentionality, phenomenal superposition, and experienced temporality. The empirical predictions arising from these structures require new interpretive methods for their confirmation. These methods begin with single-subject (preprocessed) scan series, and consider the patterns of all voxels as potential multivariate encodings of phenomenal information. Twenty-seven subjects from the four studies were analyzed with multivariate methods, revealing analogues of phenomenal structures, particularly the structures of temporality. In a second interpretive approach, artificial neural networks were used to detect a more explicit prediction from phenomenology, namely, that present experience contains and is inflected by past states of awareness and anticipated events. In all of 21 subjects in this analysis, nets were successfully trained to extract aspects of relative past and future brain states, in comparison with statistically similar controls. This exploratory study thus concludes that the proposed methods for "neurophenomenology" warrant further application, including the exploration of individual differences, multivariate differences between cognitive task conditions, and exploration of specific brain regions possibly contributing to the observations. All of these attractive questions, however, must be reserved for future research.
Monomolecular polymeric films with incorporated Au101 clusters
Authors: E. S. Soldatov, V. V. Kislov, S. P. Gubin, M. Artemyev, D. Kisiel, A. N. Sergeev-Cherenkov, S. A. Pavlov, A. S. Trifonov, G. B. Khomutov
Venue: Microelectronic Engineering (2005)

Ultimately thin monomolecular ordered stable polymeric nanocomposite films containing incorporated ligand-stabilized Au"1"0"1 nanoclusters were formed and characterized by STM and transmission electron microscopy techniques. It was demonstrated that obtained nanocomposite films can be perspective for the room temperature single-electron devices. The method proposed is perspective for design and fabrication of new controlled-morphology organized planar polymeric composite nanostructured materials, films and coatings including ultimately thin monolayer films.
A Case Study in I/O Disaggregation using PCI Express Advanced Switching Interconnect (ASI)
Authors: Venkata Krishnan, Todd Comins, Rudy Stalzer, David Wong
Venue: Proceedings of the 14th IEEE Symposium on High-Performance Interconnects (2006)

Decoupling the processor and I/O subsystem provides immense benefits that include high availability, efficient allocation and cost-effective upgrade of system resources. Such a disaggregation model calls for a highperformance interconnect to isolate the processor and I/O subsystem domains, yet provide the veneer of a single system. PCI Express (PCIe) is one such interconnect and is becoming the de-facto I/O fabric. However, PCIe, as specified currently, provides limited support for I/O disaggregation and does not yet natively support dynamic sharing of I/O resources amongst processor subsystems - this is the next major step in I/O disaggregation. PCI Express Advanced Switching Interconnect (ASI) is well-suited for enhancing the capabilities of PCIe in a non-disruptive manner. ASI is built upon PCIe and has the innate ability to co-exist with PCIe devices due to its commonality of the link/physical layer with PCIe as well as its native support for encapsulating PCIe packets. Towards a simple yet illustrative demonstration of ASIbased disaggregation of PCIe devices, we employed StarGen's ASI products for creating a basic ASI fabric and disaggregated a PCIe based GigE NIC from a host system. The initial set of results showed a marginal effect on the application's latency, but contrary to expectations, the throughput was significantly impacted. Further analysis revealed that this unexpected drop in throughput could be rectified easily and indeed, the final results confirm that the use of ASI for supporting I/O disaggregation does not result in sub-optimal utilization of the GigE NIC.
How to reason with OWL in a logic programming system
Authors: Markus Krotzsch, Pascal Hitzler, Denny Vrandecic, Michael Sintek
Venue: Proceedings of the Second International Conference on Rules and Rule Markup Languages for the Semantic Web (2006)

Logic programming has always been a major ontology modeling paradigm, and is frequently being used in large research projects and industrial applications, e.g., by means of the F-Logic reasoning engine OntoBroker or the TRIPLE query, inference, and transformation language and system. At the same time, the Web Ontology Language OWL has been recommended by the W3C for modeling ontologies for the web. Naturally, it is desirable to investigate the interoperability between both paradigms. In this paper, we do so by studying an expressive fragement of OWL DL for which reasoning can be reduced to the evaluation of Horn logic programs. Building on the KAON2 algorithms for transforming OWL DL into disjunctive Datalog, we give a detailed account of how and to what extent OWL DL can be employed in standard logic programming systems. En route, we derive a novel, simplified characterization of the supported fragment of OWL DL.
Industrial Deployment of the TTCN-3 Testing Technology
Authors: Thomas Deiss, Andreas J. Nyberg, Stephan Schulz, Risto Teittinen, Colin Willcock
Venue: IEEE Software (2006)

Software developers face severe testing challenges today in terms of increasing system complexity, reduced time to market, and stringent quality requirements. These challenges are particularly prevalent in mobile telecommunications system development. TTCN-3 is a standardized testing language that offers a possible solution to many current testing challenges. However, introducing a new technology in a large organization is a complex process in itself. The authors describe their experience addressing these complexities with TTCN-3 at Nokia.This article is part of a special issue on Software Testing.
Observant and Proactive Communication in Multi-agent Teamwork
Authors: Yu Zhang
Venue: Proceedings of the IEEE/WIC/ACM international conference on Intelligent Agent Technology (2006)

This paper investigates effective human team cooperation and incorporated the findings into multi-agent teamwork. We describe how to give agents the same cooperative capabilities, observability and proactivity, that humans use. We show how agents can use observation of the environment and of teammates' actions to estimate the teammates' beliefs without generating unnecessary messages; we also show how agents can anticipate information needs among the team members and proactively communicate the information. Finally, we present two experiments that explore the effectiveness and the scalability of the use of observability and proactivity.
Mathematical Modeling Support in a Distributed Problem Solving Environment for Scientific Computing
Authors: Shigeo Kawata, Takayuki Teramoto, Hideaki Sugiura, Yuichi Saitoh, Yoshikazu Hayase
Venue: Proceedings of the Second IEEE International Conference on e-Science and Grid Computing (2006)

In computing sciences (e-Sciences) we need computer power, excellent algorithms and programming power in order to solve scientific problems leading to discoveries and development of innovative new products. So far, the computer power and the computing algorithms have been developed incredibly, and have provided enormous contributions to e-Sciences and e-Productions. Problem solving environments (PSE) support the programming power in e-Sciences and e-Productions, and have been studied actively for a few decades. In this paper a distributed PSE, named D-NCAS is presented, and a computer-assisted mathematical modeling support is also discussed in D-NCAS, which helps users solve partial differential equation (PDE) based problems in scientific computing. The D-NCAS PSE inputs a problem description and outputs a program flow, a C-language source code for the problem and also a document for the program. Each PSE module is distributed on networklinked distributed computers. The PSE holds all the information of the problem: PDEs, discretization scheme, mesh information, equation manipulation results, designed program structure, variable and constant definitions and program itself. The PSE concept has been opening a new direction for the computer-assisted programming or development of scientific simulation programs or CAEs.
Human Motion Recognition Using Clay Representation of Trajectories
Authors: Yu-Chun Lai, Hong-Yuan Mark Liao
Venue: Proceedings of the 2006 International Conference on Intelligent Information Hiding and Multimedia (2006)

In this paper, we propose a novel human motion recognition approach that incorporates two fundamental concepts. First, the Shape Context and a clustering method are used to extract moving articulated parts from a video sequence. Then, we represent the moving articulated parts by trajectories. Our trajectory extraction approach provides good tolerance under various background and lighting conditions. Significantly, landmark point selection is not necessary in our approach, since trajectory generation is based on the extraction of moving articulated parts. The second concept is that the extracted trajectories are seen as forces pushing the articulated parts. Those forces are applied to a clay-like deformed material, which is used to represent the trajectories' behavior. The experiment results show that the proposed approach is robust against noise and incorrectly extracted trajectories, such as redundant and missing trajectories.
A New Approach to Improving the Test Effectiveness in Software Testing Using Fault Collapsing
Authors: Shiyi Xu
Venue: Proceedings of the 12th Pacific Rim International Symposium on Dependable Computing (2006)

Although Mutation is one of the practical ways of enhancing the effectiveness of the test cases to be applied to an application under test, it could be sometimes infeasible for there being too many assumed faults and mutants to be operated in a larger scale system so that the mutation operating becomes time-consuming and even prohibited. Therefore, the number of faults assumed to exist in the software under test should be reduced. Fault Collapsing is a common way of reducing the number of faults in hardware testing. However, this strategy can now be well implanted into the area of software testing. In this paper, we utilize the concept of fault dominance and equivalence, which has long been used in hardware testing, for revealing a novel way of reducing the number of faults assumed to hide in software systems. Once the number of faults assumed in software is decreased sharply, the effectiveness of mutation testing will be greatly enhanced. Examples and experimental results are presented to illustrate the effectiveness and the helpfulness of the technology proposed in the paper.
On the value of the max-norm of the orthogonal projector onto splines with multiple knots
Authors: Simon Foucart
Venue: Journal of Approximation Theory (2006)

The supremum over all knot sequences of the max-norm of the orthogonal spline projector is studied with respect to the order k of the splines and their smoothness. It is first bounded from below in terms of the max-norm of the orthogonal projector onto a space of incomplete polynomials. Then, for continuous and for differentiable splines, its order of growth is shown to be √k.
Virtual reality: its usefulness for ergonomic analysis
Authors: Lawrence E. Whitman, Michael Jorgensen, Kuresh Hathiyari, Don Malzahn
Venue: Proceedings of the 36th conference on Winter simulation (2004)

This paper presents the results of an effort to compare results of an experiment performed in both a virtual and a real environment. The research question addressed is if virtual reality is a suitable tool for performing ergonomic analysis. The subjects performed a palletizing task in the virtual environment and then performed the same task in the real environment. The results showed that VR can be compared to a similar experimental task in the real environment if it involves measuring only range of movements and no velocities or accelerations. This paper presents these results using a lumbar motion monitor and proposes areas for future improvement and research.
A Human-Friendly MAS for Mining Stock Data
Authors: Jiarui Ni, Chengqi Zhang
Venue: Proceedings of the 2006 IEEE/WIC/ACM international conference on Web Intelligence and Intelligent Agent Technology (2006)

Mining stock data can be beneficial to the participants and researchers in the stock market. However, it is very difficult for a normal trader or researcher to apply data mining techniques to the data on his own due to the complexity involved in the whole data mining process. In this paper, we present a multi-agent system that can help users easily deal with their data mining jobs on stock data. This system guides users to specify their mining tasks by simply specifying the data sets to be mined and selecting pre-defined and/or user-added data mining agents. This approach offers normal traders a practical and flexible solution to mining stock data.
Modular type classes
Authors: Derek Dreyer, Robert Harper, Manuel M. T. Chakravarty, Gabriele Keller
Venue: Proceedings of the 34th annual ACM SIGPLAN-SIGACT symposium on Principles of programming languages (2007)

ML modules and Haskell type classes have proven to be highly effective tools for program structuring. Modules emphasize explicit configuration of program components and the use of data abstraction. Type classes emphasize implicit program construction and ad hoc polymorphism. In this paper, we show how the implicitly-typed style of type class programming may be supported within the framework of an explicitly-typed module language by viewing type classes as a particular mode of use of modules. This view offers a harmonious integration of modules and type classes, where type class features, such as class hierarchies and associated types, arise naturally as uses of existing module-language constructs, such as module hierarchies and type components. In addition, programmers have explicit control over which type class instances are available for use by type inference in a given scope. We formalize our approach as a Harper-Stone-style elaboration relation, and provide a sound type inference algorithm as a guide to implementation.
Awareness-Enabled Coordination for Large Scale Collaboration Management
Authors: Dimitrios Georgakopoulos, Marian Nodine, Donald Baker, Andrzej Cichocki
Venue: Proceedings of the International Symposium on Collaborative Technologies and Systems (2006)

designed to address the problem of scaling collaboration to large multi-organizational teams. AEC provides a contextualization mechanism that helps its users deal with complex, real world environments where teams involve humans, tools, software services, and agents that come from different organizations, are subject to multiple jurisdictions, and provide diverse expertise. To provide efficiency in achieving team objectives, AEC provides process-based coordination and automation, ongoing policy enforcement, as well as situation and projectrelated awareness. To allow individuals, teams, and organizations to deal with dynamically changing situations, AEC permits dynamic adaptation of user activities, process, resources, policies, organizations, and teams at any time. We use examples from the homeland security and the intelligence gathering domains to illustrate these AEC technical capabilities and their benefits.
Implications of neuronal diversity on population coding
Authors: Maoz Shamir, Haim Sompolinsky
Venue: Neural Computation (2006)

In many cortical and subcortical areas, neurons are known to modulate their average firing rate in response to certain external stimulus features. It is widely believed that information about the stimulus features is coded by a weighted average of the neural responses. Recent theoretical studies have shown that the information capacity of such a coding scheme is very limited in the presence of the experimentally observed pairwise correlations. However, central to the analysis of these studies was the assumption of a homogeneous population of neurons. Experimental findings show a considerable measure of heterogeneity in the response properties of different neurons.In this study, we investigate the effect of neuronal heterogeneity on the information capacity of a correlated population of neurons. We show that information capacity of a heterogeneous network is not limited by the correlated noise, but scales linearly with the number of cells in the population. This information cannot be extracted by the population vector readout, whose accuracy is greatly suppressed by the correlated noise. On the other hand, we show that an optimal linear readout that takes into account the neuronal heterogeneity can extract most of this information. We study analytically the nature of the dependence of the optimal linear readout weights on the neuronal diversity. We show that simple online learning can generate readout weights with the appropriate dependence on the neuronal diversity, thereby yielding efficient readout.
Generalized gradient adaptive step sizes for stochastic gradient adaptive filters
Authors: S. C. Douglas
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1995. on International Conference - Volume 02 (1995)

We derive new adaptive step size algorithms for two general classes of modified stochastic gradient adaptive filters that include the sign-error, sign-data, sign-sign, and normalized gradient adaptive filters as specific cases. These computationally-simple parameter adjustment algorithms are based on stochastic gradient approximations of steepest descent procedures for the unknown parameters. Analyses of the algorithms show that the stationary points of the steepest descent procedures yield the optimum step size values at each time instant as obtained from statistical analyses of the adaptive filter updates. Simulations verify the theoretical results and indicate that near-optimal tracking performance can be obtained from each of the adaptive step size algorithms without any knowledge of the rate of change of the unknown system.
Adaptive Language Learning Based on Learner's STM Ability in M-learning Environment
Authors: Nian-Shing Chen, Sheng-wen Hsieh, Prof. Kinshuk
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

Due to the rapid advancement of mobile communication technologies, many educators believed that these new technologies will have a great impact on the way of learning. By effectively applying shortmessage services as Learning Content Delivery (LCD) methods provided by mobile phone system to deliver content using different Learning Content Representation (LCR) types, M-learning can be implemented accordingly. However, the most important issue is whether this way can really achieve good Learning Outcomes (LOs) and be accepted by learners. This paper will explore the restraint of Short- Term Memory (STM) of psychological learning process through technology-mediated learning theory on assessing LOs. The finding of this study is to match different LCR types with different LCD methods to fit with learners' different STM abilities would result higher LOs in M-learning environment.
On the approximability of maximum and minimum edge clique partition problems
Authors: Anders Dessmark, Jesper Jansson, Andrzej Lingas, Eva-Marta Lundell, Mia Persson
Venue: Proceedings of the 12th Computing: The Australasian Theroy Symposium - Volume 51 (2006)

We consider the following clustering problems: given a general undirected graph, partition its vertices into disjoint clusters such that each cluster forms a clique and the number of edges within the clusters is maximized (Max-ECP), or the number of edges between clusters is minimized (Min-ECP). These problems arise naturally in the DNA clone classification. We investigate the hardness of finding such partitions and provide approximation algorithms. Further, we show that greedy strategies yield constant factor approxi mations for graph classes for which maximum cliques can be found efficiently.
A Model of Reaching Dynamics in Primary Motor Cortex
Authors: Sohie Lee Moody, David Zipser
Venue: Journal of Cognitive Neuroscience (1998)

Features of virtually all voluntary movements are represented in the primary motor cortex. The movements can be ongoing, imminent, delayed, or imagined. Our goal was to investigate the dynamics of movement representation in the motor cortex. To do this we trained a fully recurrent neural network to continually output the direction and magnitude of movements required to reach randomly changing targets. Model neurons developed preferred directions and other properties similar to real motor cortical neurons. The key finding is that when the target for a reaching movement changes location, the ensemble representation of the movement changes nearly monotonically, and the individual neurons comprising the representation exhibit strong, nonmonotonic transients. These transients serve as internal recurrent signals that force the ensemble representation to change more rapidly than if it were limited by the time constants of individual neurons. These transients, if they exist, could be observed in experiments that require only slight modifications of the standard paradigm used to investigate movement representation in the motor cortex.
Preferential path profiling: compactly numbering interesting paths
Authors: Kapil Vaswani, Aditya V. Nori, Trishul M. Chilimbi
Venue: Proceedings of the 34th annual ACM SIGPLAN-SIGACT symposium on Principles of programming languages (2007)

Path profiles provide a more accurate characterization of a program's dynamic behavior than basic block or edge profiles, but are relatively more expensive to collect. This has limited their use in practice despite demonstrations of their advantages over edge profiles for a wide variety of applications.We present a new algorithm called preferential path profiling (PPP), that reduces the overhead of path profiling. PPP leverages the observation that most consumers of path profiles are only interested in a subset of all program paths. PPP achieves low overhead by separating interesting paths from other paths and assigning a set of unique and compact numbers to these interesting paths. We draw a parallel between arithmetic coding and path numbering, and use this connection to prove an optimality result for the compactness of path numbering produced by PPP. This compact path numbering enables our PPP implementation to record path information in an array instead of a hash table. Our experimental results indicate that PPP reduces the runtime overhead of profiling paths exercised by the largest (ref) inputs of the SPEC CPU2000 benchmarks from 50% on average (maximum of 132%) to 15% on average (maximum of 26%) as compared to a state-of-the-art path profiler.