ppxscal/embedding_network huggingface dataset:
The Effects of Aging on Controlled Attention and Conflict Processing in the Stroop Task
Authors: Robert West
Venue: Journal of Cognitive Neuroscience (2004)

Recent computational modeling and behavioral work indicate that age-related declines in the ability to represent task context may contribute to disruptions of working memory and selective attention in older adults. However, it is unclear whether age-related declines in context processing arise from a disruption of the encoding or maintenance of task context and how age-related declines in context processing interact with mechanisms supporting conflict detection and resolution processes contributing to efficient selection of task-relevant information. This study examines the effects of aging on the neural correlates of context and conflict processing in the Stroop task using event-related brain potentials (ERPs). Age-related differences in the time course of modulations of the ERPs associated with encoding (P3) and maintaining (slow wave) task context were observed. There were also age-related differences in the N450, conflict SP, and ERN associated with conflict processing that interacted with task context. These data indicate that aging is associated with declines in the efficiency of those neural mechanisms supporting both context and conflict processing, and that the effects of aging are not pervasive but rather interact with task context.
An Identity-Based Fault-Tolerant Conference Key Distribution Scheme
Authors: Yang Zongkai, Xie Haitao, Cheng Wenqing, Tan Yunmeng
Venue: Proceedings of the Seventh International Conference on Parallel and Distributed Computing, Applications and Technologies (2006)

A fault-tolerant conference key distribution scheme based on mechanism of identity-based cryptography and (t,n) threshold secret sharing is proposed in this paper. This scheme is much different to traditional ones, its secret shadows are not brought from the sponsor of conference, but from each server's private key signature. By getting together these n secret shadows, the sponsor can construct polynomial. Any of conferees invited by the sponsor can request these secret shadows from t of these n servers, and then restitute conference key by them. In all courses of conference key distribution and reconstruction, every member's identity can be easily validated, so it can be prevented from all kinds of cheat.
Context and Hierarchy in a Probabilistic Image Model
Authors: Ya Jin, Stuart Geman
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (2006)

It is widely conjectured that the excellent ROC performance of biological vision systems is due in large part to the exploitation of context at each of many levels in a part/whole hierarchy. We propose a mathematical framework (a "composition machine") for constructing probabilistic hierarchical image models, designed to accommodate arbitrary contextual relationships, and we build a demonstration system for reading Massachusetts license plates in an image set collected at Logan Airport. The demonstration system detects and correctly reads more than 98% of the plates, with a negligible rate of false detection. Unlike a formal grammar, the architecture of a composition machine does not exclude the sharing of sub-parts among multiple entities, and does not limit interpretations to single trees (e.g. a scene can have multiple license plates, or no plates at all). In this sense, the architecture is more like a general Bayesian network than a formal grammar. On the other hand, unlike a Bayesian network, the distribution is non-Markovian, and therefore more like a probabilistic context-sensitive grammar. The conceptualization and construction of a composition machine is facilitated by its formulation as the result of a series of non-Markovian perturbations of a "Markov backbone."
Signal modeling using increments of extended self-similar processes
Authors: L. M. Kaplan, J. C. -C. Kuo
Venue: Proceedings of the Acoustics, Speech, and Signal Processing,1994. on IEEE International Conference - Volume 04 (1994)

The article expands the fractional Brownian motion (fBm) model by investigating the idea of generalizing self-similarity to create extended self-similar (ESS) processes for which fBm processes are a subset. Properties of ESS processes are discussed, and an ESS increment model parameterized by variables controlling short and long term correlation effects is examined. We propose a fast parameter estimation algorithm for the new model which is based on the decorrelation effect of the Haar transform on the ESS increments, and we demonstrate the performance of this parameter estimation algorithm with numerical simulations.
Moving animation script creation from textual to visual representation
Authors: Erik Haugvaldstad, Tim Wright
Venue: Proceedings of the 7th Australasian User interface conference - Volume 50 (2006)

Animation scripts are an integral part of developing computer games: they describe which character animations to play and when to switch between animations. These scripts are often written in text editors which can be an error-prone task since there are multiple variables and conditions that needs to be understood, and text editors gives no indication of how animations are linked together. This paper describes how a graphical user interface, using lines and circles to simulate direction and speed, can simplify the process of creating character animation scripts.
Designing instructional support for individual and collaborative demands on net-based problem-solving in dyads
Authors: Miriam Hansen, Hans Spada
Venue: Proceedings of the 7th international conference on Learning sciences (2006)

Instructional measures were designed to foster collaboration in a net-based problem-solving task. They include support for communication and for the individual and collaborative problem-solving process. A "worked-out example" of collaboration realized as an on-screen video was combined with elements of cooperation scripts. In a 2x3 factorial design, the type of support and the type of communication were varied. Audio recordings and performance measures were taken. As first steps of the data analysis, the performance measures of 24 dyads were analyzed and two in-depth case studies were conducted in order to compare the collaboration with and without the support of the developed measures. The collaborators with instructional support made fewer communication errors, managed to better structure the collaborative problem-solving process, and solved the task faster --- they appear to have learned to collaborate. Further quantitative analyses of the whole sample of 48 dyads are work in progress.
LB_Keogh supports exact indexing of shapes under rotation invariance with arbitrary representations and distance measures
Authors: Eamonn Keogh, Li Wei, Xiaopeng Xi, Sang-Hee Lee, Michail Vlachos
Venue: Proceedings of the 32nd international conference on Very large data bases (2006)

The matching of two-dimensional shapes is an important problem with applications in domains as diverse as biometrics, industry, medicine and anthropology. The distance measure used must be invariant to many distortions, including scale, offset, noise, partial occlusion, etc. Most of these distortions are relatively easy to handle, either in the representation of the data or in the similarity measure used. However rotation invariance seems to be uniquely difficult. Current approaches typically try to achieve rotation invariance in the representation of the data, at the expense of discrimination ability, or in the distance measure, at the expense of efficiency. In this work we show that we can take the slow but accurate approaches and dramatically speed them up. On real world problems our technique can take current approaches and make them four orders of magnitude faster, without false dismissals. Moreover, our technique can be used with any of the dozens of existing shape representations and with all the most popular distance measures including Euclidean distance, Dynamic Time Warping and Longest Common Subsequence.
Hierarchical Multicast Tree Algorithms of Data Grid
Authors: Weijia Jia, Qingfeng Fan, Qingli Wu, Yanxiang He
Venue: Proceedings of the Second International Conference on Semantics, Knowledge, and Grid (2006)

Data Grid is one of the important research subjects in the field of Grid Computing. To get a high efficiency of the system, this paper proposes a set of novel multi-cast algorithms for Data grid, which can achieve shorter multicast delay and less resource consump-tions. In contrast to previous approaches, the algo-rithms in this paper partition the group members into clusters in the lower layer, seeking the most plenty of date amount node as an optimal core (root) and build-ing a shared tree within each cluster according to the algebra addition of the date amount of node and expo-nential to minimize the number of links used. In the upper layer, a shared tree is then constructed using our algorithms to implement the inter-cluster routing. The extended simulation results indicate that our algo-rithms are more suitable for Date Grid as compared with other well-known existing multicast solutions.
Doing their own math: computer support of discursive approaches to "real" math problems
Authors: Sylvia Weber-Russell, Mark D. LeBlanc
Venue: Proceedings of the 1996 international conference on Learning sciences (1996)

Traditionally, there has been no obvious role for the computer in an elementarylevel classroom oriented toward "talking about math" as a way of deepening children's understanding of mathematical problem situations. We suggest that an appropriate computer learning environment can serve as a useful tool to both complement and be enhanced by discursive approaches to mathematics. In this paper we describe software, some of which is currently being tested in classrooms, which allows students to create and share word problems motivated by classroom discussion of an arithmetically relevant situation, and to dynamically explore links between linguistic and other symbolic representations of their problems and those of other children. In conjunction with the discursive approach, these facilities support pedagogical methods such as the integration of writing, science and mathematics; roles for students as knowledge contributors rather than as passive recipients; and a motivated use of the computer for understanding mathematical problem relationships.
ElastIC: An Adaptive Self-Healing Architecture for Unpredictable Silicon
Authors: Dennis Sylvester, David Blaauw, Eric Karl
Venue: IEEE Design Test (2006)

With continued technology scaling, silicon is becoming increasingly less predictable. Recent years have brought an acceleration of wear-out mechanisms, such as oxide breakdown and NBTI, which occur over a part's lifetime. Manufacturing device failure rates will increase significantly with decreases in device sizes, possibly reaching one in thousands or even hundreds of devices. Process variations will increase significantly in future technologies because fundamental laws of physics drive certain parametric variations, such as random dopant fluctuation (RDF) and line edge roughness, making their increased contribution to variability almost inevitable. The combination of wear-out mechanisms, RDF, and line edge roughness leads to an unpredictable silicon fabric that poses a major obstacle to reliable computing in future technologies. The authors present a broad vision of a new cohesive architecture, ElastIC, which can provide a pathway to successful design in unpredictable silicon. ElastIC is based on aggressive runtime self-diagnosis, adaptivity, and self-healing. It incorporates several novel concepts in these areas and brings together research efforts from the device, circuit, testing, and microarchitecture domains. Architectures like ElastIC will become vital in extremely scaled CMOS technologies.
Stock Predictor Algorithm: A Control Method Dealing With Distributed Control Systems
Authors: Yefu Wang, Yi Shen
Venue: Proceedings of the International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (2006)

An algorithm called the stock predictor algorithm is designed in this paper. It can be used in Distributed Control Systems which have these characteristics: (1) it contains lots of sub-systems. (2)Every sub-system could be controlled using a predicted value. (3) Within a certain sub-system, it will not do much harm to the whole system even if the predicted value differs greatly from the actual value. (4) The sub-system could be non-linear, time-dependent, but it will not change quickly. The stock predictor algorithm described in this paper used a method similar to the way used by the stock-holders towards the stock predictors in the stock market. It applied several different control algorithms (viewed as stock predictors) to every controlled object (sub-systems) in every circle. Within each sub-system, according to the historical precision of every stock predictor, we use a weighted average value as the preferred predict value of that sub system. Then, when the cycle comes to an end, the stock predictors update their algorithms according to the difference between the predicted value and the actual value. Based on this algorithm, we applied the stock predictor algorithm on a heating system, and got an optimized control strategy which is proved to be both efficient and economical.
An Approach to Dynamic Model Combination on Solving Decision-Making Problem
Authors: Chao Wu, Ming Jun Xin, Wei Hua Li
Venue: Proceedings of the 2006 IEEE Asia-Pacific Conference on Services Computing (2006)

This paper discusses an approach to distributed parallel model combination for solving complicated decision-making problem. Firstly, we classify those existed models by model logic types, implement a model combination strategy to realize automatic combined model dynamic reconstruction and obtain the model series of decision-making problem solving by using and/or graph. Furthermore, during the process on model combination, we develop an index table based fast parameter matching algorithm to implement parameter match among those related models and also to apply blackboard dynamic storage technique so as to implement parameter transfer among related models. Finally, we concentrate our deep study on combined model dynamic reconstruction, fast parameter dynamic matching and transferring algorithm. Algorithm analysis listed in this paper shows that the fast parameter matching algorithm outperforms other translation methods.
Bayesian Classification-based Intelligent-agent Data Management over Grid
Authors: Chen Jia, Wu Yue, Phillip C. Y. Sheu, Li Ming, Hui Bei
Venue: Proceedings of the 18th IEEE International Conference on Tools with Artificial Intelligence (2006)

This paper proposes a Bayesian classification method to deal with heterogeneous distributed grid data. Based on the classification result, an intelligent-agent can provide an overloading function to process certain classified data sets over a grid. The method assigns a set of agents to coordinate a user job over the grid. It can definitely resolve the main problems existing in grid data management so as to enhance grid data management efficiency.
Tuning UWB signals by pulse shaping: towards context-aware wireless networks
Authors: Maria-Gabriella Di Benedetto, Luca De Nardis
Venue: Signal Processing (2006)

Tuning spectra by pulse shaping is feasible in both impulse radio (IR) and continuous radio transmissions, since, as well known, the impulse response of the pulse shaper affects the spectral properties of radiated signals. What is peculiar to IR-UWB, and makes pulse shaping particularly appealing, is the impulsive nature of the carrier. Given their very short duration, transmitted pulses in different intervals overlap neither on clock beats nor in between two clock beats. Spectrum matching in IR can thus be restricted with reasonable approximation to a single inter-pulse interval, and as such be redirected in a rather straightforward way into a waveform representation problem.This paper analyzes the above problem of tuning radiated IR-UWB signals to reference spectral patterns by pulse shaping, and shows the correspondence between spectrum and waveform matching problems. Examples of application include three case studies: matching the FCC emission masks, mitigating interference in the ISM bands, and reducing inter-system interference for two coexisting UWB networks. The proposed approach goes beyond the signal processing analysis to tentatively propose a procedure and related protocol for integrating spectral adaptation mechanisms into network operating principles.
The Bandwidth Regulation Method Using Multi-queue For the Guarantee of Multimedia Data QoS
Authors: Min-Suk Jung, Jung-Won Lee, Sang-Ryul Ryu, Se-Yul Lee, Sung-Ho Kim
Venue: Proceedings of the 2006 International Conference on Hybrid Information Technology - Volume 02 (2006)

Recently, the problem of IP QoS (Quality of Service) is showing up as one of the most important task in internet with the advent of new applied service that need QoS like Internet broadcasting, video conference, VoIP and so on. The need for QoS also have to be applied to Ethernet network that is most prevailing protocol in LAN (Local Area Network) and a smart home network that requires constant transfer delay to transmit multimedia data. Also, users come to request the best QoS in the range of SLA (Service Level Agreement). For guarantee of QoS, there are some existing ways like Integrated Service or Differentiated Service but they have several problems in implementing to use practically, and use very complex procedure like Token Bucket in assigning the bandwidth. In this paper, we suggest velocity rate calculation method in multi-queues that is simple and easily applied for guarantee of QoS. And the performance result by OPNET simulation tool is shown that the regulated bandwidth and queuing delays is efficient and satisfied in multimedia data.
A New Compression Method of SN, TS for On-Line Multimedia Services in Real Time Protocol
Authors: Kyung Shin Kim, Moon Sik Kang, Intae Ryoo
Venue: Proceedings of the 2006 International Conference on Hybrid Information Technology - Volume 02 (2006)

The important issue in header compression would be how to compress effectively the dynamic field which is increased constantly between consecutive packets in the head of IP wireless networks. In this paper, we propose a new method of compressing 48-bit SN and TS fields, which are the Dynamic fields of the RTP packet, into BCB (Basic Compression Bits) 3-bits or NCB (Negotiation Compression Bits, BCB + additional bits) bits. In order to verify the proposed header compression method, we present the most appropriate compression ratio according to traffic by testing with the video packets of IP wireless networks. The results demonstrate that the proposed approach is desirable and robust. The new compression methods can be used for increasing the performance of real time multimedia service systems including online games and broadcasting.
Twenty-first century networking: beyond bits and packets
Authors: David Goodman
Venue: Proceedings of the 1st international workshop on Wireless network testbeds, experimental evaluation characterization (2006)

The National Science Foundation is currently challenging the computer and information systems research community to replace the Internet with technology that meets the needs of the present century. The GENI initiative will create an experimental facility for moving ideas toward practical solutions. For the initiative to succeed, the research community needs to come up with new ideas that can be verified or disproved by experiments on a large-scale network. Our principal contribution to twentieth-century networks was technology for moving ones and zeros (packaged in protocol data units)áfrom source to destination. Layered protocols isolate the ones and zeros from other properties of the information conveyed. This talk questions bits as the universal currency of information. It asks the research community to take a top down look at information networks and establish the conceptual foundation of future information systems.
Computation on sentence semantic distance for novelty detection
Authors: Hua-Ping Zhang, Jian Sun, Bing Wang, Shuo Bai
Venue: Journal of Computer Science and Technology (2005)

Novelty detection is to retrieve new information and filter redundancy from given sentences that are relevant to a specific topic. In TREC2003, the authors tried an approach to novelty detection with semantic distance computation. The motivation is to expand a sentence by introducing semantic information. Computation on semantic distance between sentences incorporates WordNet with statistical information. The novelty detection is treated as a binary classification problem: new sentence or not. The feature vector, used in the vector space model for classification, consists of various factors, including the semantic distance from the sentence to the topic and the distance from the sentence to the previous relevant context occurring before it. New sentences are then detected with Winnow and support vector machine classifiers, respectively. Several experiments are conducted to survey the relationship between different factors and performance. It is proved that semantic computation is promising in novelty detection. The ratio of new sentence size to relevant size is further studied given different relevant document sizes. It is found that the ratio reduced with a certain speed (about 0.86). Then another group of experiments is performed supervised with the ratio. It is demonstrated that the ratio is helpful to improve the novelty detection performance.
The effects of preprocessing on direction of arrival estimation
Authors: A. J. Weiss, B. Friedlander
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1993. ICASSP-93 Vol 4., 1993 IEEE International Conference on - Volume 04 (1993)

Numerous authors have advocated the use of preprocessing (PP) in high-resolution direction finding algorithms. The optimal PP matrix is identified, in the sense that the accuracy of the direction of arrival estimates are unaffected by the preprocessing step. The authors derive the preprocessing matrices which provide minimum variance estimates for a number of models and algorithms. They then study the Cramer-Rao bound (CRB) for Gaussian signals, the CRB for deterministic signals, and the asymptotic variance of the multiple signal classification (MUSIC) estimator for the preprocessed data. The effect of array manifold errors on direction estimation accuracy is also examined.
The Link between Social Cognition and Self-referential Thought in the Medial Prefrontal Cortex
Authors: Jason P. Mitchell, Mahzarin R. Banaji, C. Neil MacRae
Venue: Journal of Cognitive Neuroscience (2005)

The medial prefrontal cortex (mPFC) has been implicated in seemingly disparate cognitive functions, such as understanding the minds of other people and processing information about the self. This functional overlap would be expected if humans use their own experiences to infer the mental states of others, a basic postulate of simulation theory. Neural activity was measured while participants attended to either the mental or physical aspects of a series of other people. To permit a test of simulation theory's prediction that inferences based on self-reflection should only be made for similar others, targets were subsequently rated for their degree of similarity to self. Parametric analyses revealed a region of the ventral mPFC&mdash;previously implicated in self-referencing tasks&mdash;in which activity correlated with perceived self/other similarity, but only for mentalizing trials. These results suggest that self-reflection may be used to infer the mental states of others when they are sufficiently similar to self.