ppxscal/embedding_network huggingface dataset:
Goal-Directed Hand Movements Are Not Affected by the Biased Space Representation in Spatial Neglect
Authors: Marc Himmelbach, Hans-Otto Karnath
Venue: Journal of Cognitive Neuroscience (2003)

Patients with spatial neglect exhibit a severe shift of spontaneous explorative movements to the right side, indicating a bias of long-living representations of space. Whether or not goal-directed movements likewise are affected by this rightward bias has been controversially discussed throughout the last decade. Unfortunately, substantial differences regarding patient selection and data analysis prevented a direct comparison of these results. We thus studied pointing movements in a new sample of subjects covering all different patient groups previously investigated on this issue. We analyzed all the different measures of hand path curvature used so far and, in addition, suggest a new measure that avoids the disadvantages of the previously used parameters. Despite their severe bias for exploratory movements, we did not find systematic, direction-specific deviations of goal-directed hand movements that were specific for the patients with spatial neglect. The results strongly suggest that the disturbance of long-living spatial representations underlying the bias of exploratory behavior in patients with neglect does not influence the performance of goal-directed movements. The data support the view of a dual mode of space representation in the posterior parietal and the superior temporal cortex.
Application of MML to Motor Skills Acquisition
Authors: Chao Sun, Fazel Naghdy, David Stirling
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)

Study on modeling human psychomotor behaviour based on tracked motion data is reported. The motion data is acquired through various integrated inertial sensors, and represented as Euler angles and accelerations. The Minimum Message Length (MML) algorithm is used to identify frames of intrinsic segmentations and to acquire a classification basis for unsupervised machine learning. The classification model can ultimately be deployed in recognizing certain skilled behaviors. The prior results are analyzed as FSMs' (Finite State Machines) to extract the potential rules underlying behaviors. The progress made so far and plan for further work is reported.
Registration of Multimodal Stereo Images Using Disparity Voting from Correspondence Windows
Authors: Stephen Krotosky, Mohan Trivedi
Venue: Proceedings of the IEEE International Conference on Video and Signal Based Surveillance (2006)

This paper presents a method for registering multimodal imagery in short range surveillance situations when the differences in object depths preclude any global registration techniques. An analysis of multimodal registration approaches gives insight into the limitations of global assumptions and motivates the developed algorithm. Using calibrated stereo imagery, we use maximization of mutual information in sliding correspondence windows that inform a disparity voting scheme to demonstrate successful registration of color and thermal images. Extensive testing of scenes with multiple people at different depths and levels of occlusion shows high rates of successful registration and gives a reliable framework for further processing and analysis of the multimodal imagery.
An Outlier Detection Model Based on Cross Datasets Comparison for Financial Surveillance
Authors: Tianqing Zhu
Venue: Proceedings of the 2006 IEEE Asia-Pacific Conference on Services Computing (2006)

Outlier detection is a key element for intelligent financial surveillance systems which intend to identify fraud and money laundering by discovering unusual customer behaviour pattern. The detection procedures generally fall into two categories: comparing every transaction against its account history andficrther more, comparing against a peer group to determine if the behavior is unusual. The later approach shows particular merits in efficiently extracting suspicious transaction and reducing false positive rate. Peer group analysis concept is largely dependent on a cross-datasets outlier detection model. In this paper, we propose a new cross outlier detection model based on distance definition incorporated with the financial transaction data features. An approximation algorithm accompanied with the model is provided to optimize the computation of the deviation from tested data point to the reference dataset. An experiment based on real bank data blended with synthetic outlier cases shows promising results of our model in reducing false positive rate while enhancing the discriminative rate remarkably.
A framework for understanding trust factors in web-based health advice
Authors: Elizabeth Sillence, Pam Briggs, Peter Harris, Lesley Fishwick
Venue: International Journal of Human-Computer Studies (2006)

Trust is a key factor in consumer decisions about website engagement. Consumers will engage with sites they deem trustworthy and turn away from those they mistrust. In this paper, we present a framework for understanding trust factors in web-based health advice. The framework is derived from a staged model of trust and allows predictions to be made concerning user engagement with different health websites. The framework is then validated via a series of qualitative, longitudinal studies. In each study, genuine consumers searched online for information and advice concerning their specific health issue. They engaged in free searching and were directed towards sites previously reviewed using the framework. Thematic analysis of the group discussions provided support for the framework and for the staged model of trust wherein design appeal predicted rejection (mistrust) and credibility of information and personalization of content predicted selection (trust) of advice sites. The results are discussed in terms of the merits of the framework, its limitations and directions for future work.
An Algorithm for JPEG Compressing with Chaotic Encrypting
Authors: Huang Yuanshi, Xu Rongcong, Lin Weiqiang
Venue: Proceedings of the International Conference on Computer Graphics, Imaging and Visualisation (2006)

In the paper, we bring forward an image encryption algorithm during the process of JPEG compression. According to the chaotic theory of dynamic systems and modern cryptography, we solved the following technique First, how to generate chaotic sequence having good randomness accordng to the characteristic that Logistic chaotic systems are extremely sensitive to the initial condition? Secondly, how to create a series of one-way hash being as block key from the chaotic sequences? Thirdly, during the process of JPEG compression coding, how to implement the image compression cipher? In the analysis of the algorithm, we discuss the randomness of the chaotic sequence in detail. We also analyze the security and anti-collission of the chaotic hash sequence by several variant methods. The resultls indicate that our algorithm completely satisfied the security requirement in thesense of cryptography.
Hopf bifurcation and global periodic solutions in a delayed predator-prey system
Authors: Xiang-Ping Yan, Wan-Tong Li
Venue: Applied Mathematics and Computation (2006)

This paper is concerned with a delayed predator-prey system with same feedback delays of predator and prey species to their growth, respectively. We prove that a sequence of Hopf bifurcations occur at the positive equilibrium as the delay increases monotonously from zero. By using the theory of normal norm and center manifold reduction, an explicit algorithm for determining the direction of Hopf bifurcations and the stability of bifurcating periodic solutions is derived. In addition, the global existence results of periodic solutions bifurcating from Hopf bifurcations are established by using a global Hopf bifurcation result due to Wu [J. Wu, Symmetric functional differential equations and neural networks with memory, Trans. Amer. Math. Soc. 350 (1998) 4799-4838]. Finally, a numerical example supporting our theoretical prediction is also given. Our findings are contrasted with recent studies on a delayed predator-prey system with the feedback time delay of prey species to its growth by Song and Wei [Y. Song, J. Wei, Local Hopf bifurcation and global periodic solutions in a delayed predator-prey system, J. Math. Anal. Appl. 301 (2005) 1-21]. As the feedback time delay τ increases monotonously from zero, the positive equilibrium of the latter switches k times from stability to instability to stability. In contrast, the positive equilibrium of our system appears to lose the above property.
On the severity of Braess's paradox: designing networks for selfish users is hard
Authors: Tim Roughgarden
Venue: Journal of Computer and System Sciences (2006)

We consider a directed network in which every edge possesses a latency function that specifies the time needed to traverse the edge given its congestion. Selfish, noncooperative agents constitute the network traffic and wish to travel from a source vertex s to a destination t as quickly as possible. Since the route chosen by one network user affects the congestion experienced by others, we model the problem as a noncooperative game. Assuming that each agent controls only a negligible portion of the overall traffic, Nash equilibria in this noncooperative game correspond to s-t flows in which all flow paths have equal latency.A natural measure for the performance of a network used by selfish agents is the common latency experienced by users in a Nash equilibrium. Braess's Paradox is the counterintuitive but well-known fact that removing edges from a network can improve its performance. Braess's Paradox motivates the following network design problem: given a network, which edges should be removed to obtain the best flow at Nash equilibrium? Equivalently, given a network of edges that can be built, which subnetwork will exhibit the best performance when used selfishly?We give optimal inapproximability results and approximation algorithms for this network design problem. For example, we prove that there is no approximation algorithm for this problem with approximation ratio less than n/2, where n is the number of network vertices, unless P = NP. We further show that this hardness result is the best possible, by exhibiting an (n/2)-approximation algorithm. We also prove tight inapproximability results when additional structure, such as linearity, is imposed on the network latency functions.Moreover, we prove that an optimal approximation algorithm for these problems is the trivial algorithm: given a network of candidate edges, build the entire network. As a consequence, we show that Braess's Paradox--even in its worst-possible manifestations--is impossible to detect efficiently.En route to these results, we give a fundamental generalization of Braess's Paradox: the improvement in performance that can be effected by removing edges can be arbitrarily large in large networks. Even though Braess's Paradox has enjoyed 35 years as a textbook example, our result is the first to extend its severity beyond that in Braess's original four-node network.
Exploring the Capabilities of Mobile Agents in Distributed Data Mining
Authors: U. P. Kulkarni, K. K. Tangod, S. R. Mangalwede, A. R. Yardi
Venue: Proceedings of the 10th International Database Engineering and Applications Symposium (2006)

Over the past decade, data mining has gained an important role in analysis of large datasets and there by understanding the complex systems in almost all areas. Such datasets are often collected in a geographically distributed way, and cannot, in practice, be gathered in to single repository. Existing data mining methods for distributed data are of communication intensive. Many algorithms for data mining have been proposed for a data at a single location and some at multiple locations with improvement in terms of efficiency of algorithms as a part of quality but effectiveness of these algorithms in real time distributed environment are not addressed, as data on the web/network are distributed by very of its nature. As a consequence, both new architectures and new algorithms are needed. In this paper we introduce the software agent technology that supports building of distributed data mining architecture and explore the capabilities of mobile agents' paradigm and will show by experiment that, it is suited for distributed data Mining compared to traditional approaches like client server computing.
Forecasting Skewed Biased Stochastic Ozone Days: Analyses and Solutions
Authors: Kun Zhang, Wei Fan, Xiaojing Yuan, Ian Davidson, Xiangshang Li
Venue: Proceedings of the Sixth International Conference on Data Mining (2006)

Much work on skewed, stochastic, high dimensional, and biased datasets usually implicitly solve each problem separately. Recently, we have been approached by Texas Commission on Environmental Quality (TCEQ) to help them build highly accurate ozone level alarm forecasting models for the Houston area, where these technical difficulties come together in one single problem. Key characteristics of this problem that are challenging and interesting include: 1) the dataset is sparse (72 features, and 2% or 5% positives depending on the criteria of "ozone days"), 2) evolving over time from year to year, 3) limited in collected data size (7 years or around 2500 data entries), 4) contains a large number of irrelevant features, 5) is biased in terms of "sample selection bias", and 6) the true model is stochastic as a function of measurable factors. Besides solving a difficult application problem, this dataset offers a unique opportunity to explore new and existing data mining techniques, and to provide experience and guidance for similar problems. Our main technical focus addresses on how to estimate reliable probability given both sample selection bias and a large number of irrelevant features, and how to choose the most reliable decision threshold to predict the unknown future with different distribution. On the application side, the prediction accuracy of our approach is 20% higher in recall (correctly detects 1 to 3 more ozone days, depending on the year) and 10% higher in precision (15 to 30 fewer false alarm days per year) than state-of-the-art methods used by air quality control scientists, and these results are significant for TCEQ.
Applying a cognitive architecture to control of virtual non-player characters
Authors: Christopher McCollum, Charles Barba, Thomas Santarelli, John Deaton
Venue: Proceedings of the 36th conference on Winter simulation (2004)

CHI Systems, under contract to the U. S. Army Research Institute, is developing an immersive training system, called Virtual Environment Cultural Training for Operational Readiness (VECTOR), which applies highly experiential, scenario-based virtual environments to training in cultural familiarization. To produce an interactive, realistic training environment, the simulation must incorporate synthetic actors, or non-player characters (NPC's), that are capable of evaluating and responding to the cultural propriety of trainee's actions. The main focus of the paper is on explaining how iGEN&trade; cognitive modeling architecture is being used to create executable cognitive models and emotion models which inform and constrain the overall reactions and behaviors of NPC's toward the trainee. In addition to influencing the behavior of the active NPCs, the emotion models constrain interactions with NPC's encountered later in a scenario. In this way, the training system provides a means of modeling the overall cumulative emotional state of the simulated population.
Robust rhythm as a consequence of the universal description of complex system dynamics in the vicinity of critical point
Authors: O. P. Skljarov, T. N. Skljarova
Venue: Proceedings of the 2003 International Conference on Physics and Control - Volume 2 (2003)

In work the fundamental robustness property (universality) of description of a rhythm under the attitude to all variety of styles of the various speakers articulated in various conditions is considered. This universality is a corollary of critical behavior of rhythm production system. On model of an artificial neuron network of perception the equivalence of description of a rhythm both at a level of perception of speech, and at a level of speech production is established. In this paper the analogies between the mechanism ensuring universal behavior of a rhythm in range of a criticality from the point of view of theoretical physics and the mechanism ensuring constancy of speech perception from the psychology point of view on ontogenesis of child's babble toward normal speech were established.
Image retrieval based on color distribution entropy
Authors: Junding Sun, Ximin Zhang, Jiangtao Cui, Lihua Zhou
Venue: Pattern Recognition Letters (2006)

Color histogram is an important technique for color image database indexing and retrieving. However, the main problem with color histogram indexing is that it does not take the color spatial distribution into consideration. Previous researches have proved that the effectiveness of image retrieval increases when spatial feature of colors is included in image retrieval. In this paper, two new descriptors, color distribution entropy (CDE) and improved CDE (I-CDE), which introduce entropy to describe the spatial information of colors, are presented. In comparison with the spatial chromatic histogram (SCH) and geostat which also measure the global spatial relationship of colors, the experiment results show that CDE and I-CDE give better performance than SCH and geostat.
The Context Oriented Architecture: Integrating Context into Semantic Web Services
Authors: Aisha M. Salama Elsafty, Sherif G. Aly, Ahmed Sameh
Venue: Proceedings of the First International Workshop on Semantic Media Adaptation and Personalization (2006)

While emerging standards promote the interoperability of web services, web services adaptability to user and application context is a requirement yet to be investigated. Web services today encapsulate application and business logic and are candidates for supporting pervasive environments, where adaptability will have added value in all of these domains. In this paper we introduce the context oriented architecture; an architecture for building context aware applications using web services as building components. The context oriented architecture uses semantic description to automate monitoring and responding to service context. We extend the specifications and implementation of the semantic web service ontology language (OWL-S) to represent the context profile of a web service.
Investigation of Proposed Applications for LBS Enabled Mobile Handsets
Authors: Matthew McMahon, Chris Steketee
Venue: Proceedings of the International Conference on Mobile Business (2006)

Location-based services (LBS) have been of keen interest to the m-business community for a number of years. However, applications deployed on a large scale have been slow in emerging - most existing systems are research prototypes or specialised niche applications, whose development has concentrated on exploring technical possibilities rather than commercial success. In this paper we report the results of a study to identify candidate killer-apps for LBS. The method used was to produce outline descriptions of 9 applications in 7 different consumer application areas, and survey users to obtain feedback on their level of interest in 7 of these. The most popular idea amongst surveyed users was Wired-Call Rates, where calls from a mobile phone would be charged at the same rates as wireline calls, when located in specified areas (for example at home). Other applications of interest were mainly those where LBS provides an addition to an existing service.
A Call Handling Assistant for Mobile Devices
Authors: Wayne Wobcke, Rita Chan, Andrew Limaru
Venue: Proceedings of the IEEE/WIC/ACM international conference on Intelligent Agent Technology (2006)

With the near ubiquity of mobile phones, people are reachable almost anywhere and at any time. The conve- nience this provides for people to more effectively combine different aspects of their lives has the consequence of an in- creased blurring of boundaries, for example between work and home. Thus, as one sphere impinges upon others, we see a need for people to limit their interactions on the mo- bile phone, to control (within socially acceptable bounds), when they are reachable and by whom. In this paper, we present a call handling personal assistant that runs on mo- bile devices to enable users to manage calls, based on the caller and caller's group, the time and day, and their ac- tivity. The system uses a new rule-based technique, Priori- tized Ripple Down Rules, which gives the user a high level of confidence in the system's behaviour.
Implementation and Evaluation of Programming Environment using Real Objects for Children
Authors: Mitsuru Iwata, Shun' ichi Tano, Yuka Fujie, Tomonori Hashiyama
Venue: Proceedings of the conference on Information Visualization (2006)

We developed a programming environment that promotes logic development in children. Dealing with the real materials in their play environments is important for children using this programming environment. Based on our analysis, we propose a concept model and the user interface for a play environment for children. We confirmed the effectiveness of the programming environment experimentally.
Impulsive effects on stability of Cohen-Grossberg neural networks with variable delays
Authors: Zhichun Yang, Daoyi Xu
Venue: Applied Mathematics and Computation (2006)

In this paper, a model of impulsive Cohen--Grossberg neural networks is first formulated. By establishing some impulsive differential inequalities, we investigate impulsive effects on the stability of Cohen-Grossberg neural networks with variable delays and obtain some sufficient conditions ensuring global exponential stability of the impulsive delay system. Our criteria not only show that the stability still remains under certain impulsive perturbations for some continuous stable neural networks, but also present an approach to stabilize the unstable neural networks by utilizing impulsive effects. The results extend and improve some recent works for impulsive neural networks as well as non-impulsive neural networks. Some examples and their simulations are given for illustration of the theoretical results.
TRAC: toward recency and consistency reporting in a database with distributed data sources
Authors: Jiansheng Huang, Jeffrey F. Naughton, Miron Livny
Venue: Proceedings of the 32nd international conference on Very large data bases (2006)

Distributed computing environments, including workflows in computational grids, present challenges for monitoring, as the state of the system may be captured only in logs distributed throughout the system. One approach to monitoring such systems is to "sniff" these distributed logs and to store their transformed content in a DBMS. This centralizes the state and exposes it for querying; unfortunately, it also creates uncertainty with respect to the recency and consistency of the data. Previous related work has focused on allowing queries to express currency and consistency constraints, which are then enforced by "pulling" data from the distributed sources on demand, or by requiring synchronous updates of a centralized data store. In some instances this is impossible due to legacy system issues or inefficient as the system scales to large numbers of processors. Accordingly, we propose that instead of enforcing consistency and recency, such monitoring systems should report these properties along with query results, with the hope that this will allow the data to be appropriately interpreted. We present techniques for reporting consistency and recency for queries and evaluate them with respect to efficiency and precision. Finally, we describe our prototype implementation and present experimental results of our techniques.