ppxscal/embedding_network huggingface dataset:
A Perspective on Information Fusion Problems
Authors: Rabinder N. Madan, Nageswara S. V. Rao
Venue: International Journal of Distributed Sensor Networks (2009)

Information fusion problems have a rich history spanning four centuries and several disciplines as diverse as political economy, reliability engineering, target tracking, bioinformatics, forecasting, distributed detection, robotics, cyber security, nuclear engineering, distributed sensor networks, and others. Over the past decade, the area of information fusion has been established as a discipline by itself with several contributions to its foundations as well as applications. In a basic formulation of the information fusion problem, each component is characterized by a probability distribution. The goal is to estimate a fusion rule for combining the outputs of components to achieve a specified objective such as better performance or functionality compared to the components. If the sensor error distributions are known, several fusion rule estimation problems have been formulated and solved using deterministic methods. In the area of pattern recognition a weighted majority fuser was shown to be optimal in combining outputs from pattern recognizers under statistical independence conditions. A simpler version of this problem corresponds to the Condorcet Jury theorem proposed in 1786. This result was rediscovered since then in other disciplines including by von Neumann in 1959 in building reliable computing devices. The distributed detection problem, studied extensively in the target tracking area, can be viewed as a generalization of the above two problems. In these works, the underlying distributions are assumed to be known, which is quite reasonable in the areas these methods are applied. In a different formulation, we consider estimating the fuser based on empirical data when no information is available about the underlying distributions of components. Using the empirical estimation methods, this problem is shown to be solvable in principle, and the fuser performance may be sharpened based on the specific formulation. The isolation fusers perform at least as good as best component, and the projective fusers perform as good as best combination of components. In a special case of function estimation, each component could be a potential function estimator, radial basis function, nearest neighbor estimator, regressogram, kernel estimator, regression tree or another estimator. A projective fuser based on a nearest neighbor concept has been proposed based on Voronoi regions in this case. Under fairly general smoothness and non-smoothness conditions on the individual estimators, the expected fuser error is close to optimal with a specified probability. This result is purely sample-based and distribution-free in that it does not require the knowledge of underlying distributions and can be computed only using measurements.
Comparing real-time and incremental heuristic search for real-time situated agents
Authors: Sven Koenig, Xiaoxun Sun
Venue: Autonomous Agents and Multi-Agent Systems (2009)

Real-time situated agents, such as characters in real-time computer games, often do not know the terrain in advance but automatically observe it within a certain range around themselves. They have to interleave searches with action executions to make the searches tractable when moving autonomously to user-specified coordinates. The searches face real-time requirements since it is important that the agents be responsive to the commands of the users and move smoothly. In this article, we compare two classes of fast heuristic search methods for these navigation tasks that speed up A* searches in different ways, namely real-time heuristic search and incremental heuristic search, to understand their advantages and disadvantages and make recommendations about when each one should be used. We first develop a competitive real-time heuristic search method. LSS-LRTA* is a version of Learning Real-Time A* that uses A* to determine its local search spaces and learns quickly. We analyze the properties of LSS-LRTA* and then compare it experimentally against the state-of-the-art incremental heuristic search method D* Lite on our navigation tasks, for which D* Lite was specifically developed, resulting in the first comparison of real-time and incremental heuristic search in the literature. We characterize when to choose each one of the two heuristic search methods, depending on the search objective and the kind of terrain. Our experimental results show that LSS-LRTA* can outperform D* Lite under the right conditions, namely when there is time pressure or the user-supplied h-values are generally not misleading.
Theory-driven design strategies for technologies that support behavior change in everyday life
Authors: Sunny Consolvo, David W. McDonald, James A. Landay
Venue: Proceedings of the 27th international conference on Human factors in computing systems (2009)

In this paper, we propose design strategies for persuasive technologies that help people who want to change their everyday behaviors. Our strategies use theory and prior work to substantially extend a set of existing design goals. Our extensions specifically account for social characteristics and other tactics that should be supported by persuasive technologies that target long-term discretionary use throughout everyday life. We used these strategies to design and build a system that encourages people to lead a physically active lifestyle. Results from two field studies of the system - a three-week trial and a three-month experiment - have shown that the system was successful at helping people maintain a more physically active lifestyle and validate the usefulness of the strategies.
On Usability in Requirements Trace Visualizations
Authors: Stefan Winkler
Venue: Proceedings of the 2008 Requirements Engineering Visualization (2008)

This paper defines a framework of three dimensions which influence usability of trace visualizations: tasks, user roles, and information access. Based on this framework, we survey existing visualizations and conclude that future visualizations should focus more on users and tasks. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Active learning for object classification: from exploration to exploitation
Authors: Nicolas Cebron, Michael R. Berthold
Venue: Data Mining and Knowledge Discovery (2009)

Classifying large datasets without any a-priori information poses a problem in numerous tasks. Especially in industrial environments, we often encounter diverse measurement devices and sensors that produce huge amounts of data, but we still rely on a human expert to help give the data a meaningful interpretation. As the amount of data that must be manually classified plays a critical role, we need to reduce the number of learning episodes involving human interactions as much as possible. In addition for real world applications it is fundamental to converge in a stable manner to a solution that is close to the optimal solution. We present a new self-controlled exploration/exploitation strategy to select data points to be labeled by a domain expert where the potential of each data point is computed based on a combination of its representativeness and the uncertainty of the classifier. A new Prototype Based Active Learning (PBAC) algorithm for classification is introduced. We compare the results to other active learning approaches on several benchmark datasets.
&Eacute;tude empirique de formulaires en vue de leur utilisation sur des assistants num&eacute;riques personnels
Authors: Sami Baffoun, Jean-Marc Robert
Venue: Proceedings of the 20th International Conference of the Association Francophone d'Interaction Homme-Machine (2008)

This article presents two empirical studies on the use of paper and digital forms, one about 17 inspectors in a mobility situation, working in five application domains and using a total of 38 different forms (mainly paper), and the other about 54 forms used in a university of Quebec. The goal of the project is to know the characteristics of forms in use in order to identify the requirements to satisfy for their usage on PDAs whose small size is a challenge for forms. Results of the two studies, based on 89 paper and digital forms, provide several statistics on the numerous elements of a form, namely the format, number of pages, number of sections and components per section, presence of initials and logos, tables, signature section, reserved section, assistance to the user, etc. These results are a solid base of reference for the development of a tool to help in the creation of forms for PDAs.
Formal Probabilistic Analysis of Stuck-at Faults in Reconfigurable Memory Arrays
Authors: Osman Hasan, Naeem Abbasi, Sofiène Tahar
Venue: Proceedings of the 7th International Conference on Integrated Formal Methods (2009)

Reconfigurable memory arrays with spare rows and columns are quite frequently used as reliable data storage components in present age System-on-Chips (SoCs). The spare memory rows and columns can be utilized to automatically replace rows or columns that are found to contain a cell fault after fabrication. One of the biggest SoC design challenges is to estimate, prior to the actual fabrication process, the right number of these spare rows and spare columns for meeting the reliability specifications. Traditionally, computer simulation techniques are used to perform probabilistic analysis of reconfigurable memory arrays but they provide inaccurate results. To ensure accurate analysis and thus more reliable SoC designs, we propose, in this paper, a probabilistic theorem proving approach in the domain of reconfigurable memory array analysis. We present a higher-order-logic stuck-at fault model for reconfigurable memory arrays, based on which, we illustrate the formal verification of some key statistical properties related to the number of stuck-at faults and the repairability condition.
New Graph Calculi for Planar Non-3-Colorable Graphs
Authors: Yoichi Hanatani, Takashi Horiyama, Kazuo Iwama, Suguru Tamaki
Venue: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences (2008)

The Hajós calculus is a nondeterministic procedure which generates the class of non-3-colorable graphs. If all non-3-colorable graphs can be constructed in polynomial steps by the calculus, then NP = co-NP holds. Up to date, however, it remains open whether there exists a family of graphs that cannot be generated in polynomial steps. To attack this problem, we propose two graph calculi PHC and PHC* that generate non-3-colorable planar graphs, where intermediate graphs in the calculi are also restricted to be planar. Then we prove that PHC and PHC* are sound and complete. We also show that PHC* can polynomially simulate PHC.
Maintaining colored trees for disjoint multipath routing under node failures
Authors: Giridhar Jayavelu, Srinivasan Ramasubramanian, Ossama Younis
Venue: IEEE/ACM Transactions on Networking (TON) (2009)

Colored Trees (CTs) is an efficient approach to route packets along link-or node-disjoint paths in packet-switched networks. In this approach, two trees, namely red and blue, are constructed rooted at a drain such that the path from any node to the drain are link-or node-disjoint. For applications where both the trees are used simultaneously, it is critical to maintain the trees after link or node failures. To this end, this paper develops an algorithm, referred to as SimCT, that efficiently constructs and maintains colored trees under failures using only local informa-tion. Even when the entire tree needs to be recomputed, the SimCT algorithm requires 40% lesser messages than previous techniques. The convergence time of the SimCT algorithm is linear in the number of nodes. We show through extensive simulations that the average length of the disjoint paths obtained using the SimCT algorithm is lesser compared to the previously known techniques. The above-mentioned improvements are obtained by exploiting the relationship between DFS numbering, lowpoint values, and the potentials employed for maintaining partial ordering of nodes. The SimCT algorithm is also extended to obtain colored trees in multi-drain networks.
vEye: behavioral footprinting for self-propagating worm detection and profiling
Authors: Xuxian Jiang, Xingquan Zhu
Venue: Knowledge and Information Systems (2009)

With unprecedented speed, virulence, and sophistication, self-propagating worms remain as one of the most severe threats to information systems and Internet in general. In order to mitigate the threat, efficient mechanisms are needed to accurately profile and detect the worms before or during their outbreaks. Particularly, deriving a worm&#x2019;s unique signatures, or fingerprints, is of the first priority to achieve this goal. One of the most popular approaches is to use content-based signatures, which characterize a worm by extracting its unique information payload. In practice, such content-based signatures, unfortunately, suffer from numerous disadvantages, such as vulnerable to content mutation attacks or not applicable for polymorphic worms. In this paper, we propose a new behavioral footprinting (BF) approach that nicely complements the state-of-the-art content-based signature approaches and allows users to detect and profile self-propagating worms from the unique worm behavioral perspective. More specifically, our behavioral footprinting method uniquely captures a worm&#x2019;s dynamic infection sequences (e.g., probing, exploitation, and replication) by modeling each interaction step as a behavior phenotype and denoting a complete infection process as a chained sequence. We argue that a self-propagating worm&#x2019;s inherent behaviors or infection patterns can be detected and characterized by using sequence alignment tools, where patterns shared by the infection sequences will imply the behavioral footprints of the worm. A systematic platform called vEye has been built to validate the proposed design with either &#x201c;live&#x201d; or historical worms, where a number of real-world infection sequences are used to build worm behavioral footprints. Experimental comparisons with existing content-based fingerprints will demonstrate the uniqueness and effectiveness of the proposed behavior footprints in self-propagating worm detection and profiling.
Querying data sources that export infinite sets of views
Authors: Bogdan Cautis, Alin Deutsch, Nicola Onose
Venue: Proceedings of the 12th International Conference on Database Theory (2009)

We study the problem of querying data sources that accept only a limited set of queries, such as sources accessible by Web services which can implement very large (potentially infinite) families of queries. We revisit a classical setting in which the application queries are conjunctive queries and the source accepts families of conjunctive queries specified as the expansions of a (potentially recursive) Datalog program. We say that query Q is expressible by the program P if it is equivalent to some expansion of P. Q is supported by P if it has an equivalent rewriting using some finite set of P's expansions. We present the first study of expressibility and support for sources that satisfy integrity constraints, which is generally the case in practice.
On-line evaluation of a data cube over a data stream
Authors: Woo Sock Yang, Won Suk Lee
Venue: Proceedings of the 8th conference on Applied computer scince (2008)

This paper proposes a dynamic data cube for applying a data cube to a data stream environment. The dynamic data cube specifies user-interesting areas with the support ratio of attribute value, and manages the attribute groups dynamically by grouping and dividing methods. With these methods, the memory usage and processing time are reduced. It also efficiently shows and emphasizes user-interesting areas by increasing the granularity for attributes that have higher support. We also propose an exception detecting method to quickly identify exception by using the reversed way of a multi-stage cluster sampling method. We perform experiments to verify how efficiently the dynamic data cube works in limited memory space.
Advanced modeling of networked print production by use of XML-based job definition and job messaging communication
Authors: Wolfgang Kuehn
Venue: Proceedings of the 40th Conference on Winter Simulation (2008)

Networked production gains increasing importance in many industries. In print media industries networked production requires advanced print and media specific job definitions and the communication of job relevant information along the complete production chain. The relatively young XML based communication standard JDF/JMF allows to specify workflow models and data exchange. Based on an object-oriented approach a simulation and modeling framework is proposed, which implements modules for the resources and controls applied in this particular industry. For this framework the available JavaSim-simulation library shall be extended to enable modeling of networked print production using the same JDF-/JMF-communication algorithms as applied in realworld system communication. This leads towards integration of simulation for factory planning and operative planning and control of networked print production in a digital factory environment.
Building recurrent neural networks to implement multiple attractor dynamics using the gradient descent method
Authors: Jun Namikawa, Jun Tani
Venue: Advances in Artificial Neural Systems (2009)

The present paper proposes a recurrent neural network model and learning algorithm that can acquire the ability to generate desired multiple sequences. The network model is a dynamical system in which the transition function is a contraction mapping, and the learning algorithm is based on the gradient descent method. We show a numerical simulation in which a recurrent neural network obtains a multiple periodic attractor consisting of five Lissajous curves, or a Van der Pol oscillator with twelve different parameters. The present analysis clarifies that the model contains many stable regions as attractors, and multiple time series can be embedded into these regions by using the present learning method.
On the exponential synchronization of stochastic jumping chaotic neural networks with mixed delays and sector-bounded non-linearities
Authors: Yang Tang, Jian-an Fang, Qingying Miao
Venue: Neurocomputing (2009)

This paper is concerned with the problem of exponential synchronization for stochastic jumping chaotic neural networks (SJCNNs) with mixed delays and sector non-linearities. Based on Lyapunov-Krasovskii functional and free-weighting matrix method, a delay-dependent feedback controller with sector non-linearities is proposed to achieve the synchronization in mean square in terms of linear matrix inequalities (LMIs). The activation functions are assumed to be of more general descriptions. Finally, the corresponding simulation results show the effectiveness of the proposed criteria.
Deformable Surface Augmentation in Spite of Self-Occlusions
Authors: V. Gay-Bellile, A. Bartoli, P. Sayd
Venue: Proceedings of the 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality (2007)

The augmentation problem for images of a deforming surface has been studied since recently. The surface is usually assumed not to be self-occluding. Twodimensional deformation estimation in the presence of self-occlusions is very challenging. This paper proposes a specific framework explicitly modeling self-occlusions for augmented reality applications. The basic idea is to detect self-occlusions as warp shrinkage areas. Deformations are initially estimated via direct non-rigid image registration. Temporal smoothness is then used to refine the warps and the image are augmented. Experimental results on several challenging datasets show that our approach convincingly augments self-occluded surfaces. Associated videos are available on the first author's web homepage.
Image charge approximations of reaction fields in solvents with arbitrary ionic strength
Authors: Zhenli Xu, Shaozhong Deng, Wei Cai
Venue: Journal of Computational Physics (2009)

In this paper, we report a new development of image charge approximations of reaction fields for a charge inside a dielectric spherical cavity immersed in an ionic solvent with arbitrary ionic strength. This new development removes the requirement of low ionic strength of the solvent in a previous result [S. Deng, W. Cai, Extending the fast multipole method for charges inside a dielectric sphere in an ionic solvent: high-order image approximations for reaction fields, J. Comput. Phys. 227 (2007) 1246-1266], thus extending the applicability of the image charge approximations of reaction fields in the modeling of biomolecular solvation.
Unusual human behavior recognition using evolutionary technique
Authors: Lin Lin, YongSu Seo, Mitsuo Gen, Runwei Cheng
Venue: Computers and Industrial Engineering (2009)

The vision for surveillance is an important task in many computer vision applications. The monitoring system concerns the tracking and recognition of people, and more generally, the understanding of human behaviors, from image sequences involving humans. Several methods for human tracking and human behavior recognition have been proposed by various researchers. But most of those do not have versatility and flexibility. In this paper, we propose an efficient and robust object tracking algorithm which use the color features, the distance features and count feature based on an evolutionary techniques to measure the observation similarity. And then we will track each person and classify their behavior properties by analyzing their trajectory pattern. We propose multi-layer perceptron based on hybrid genetic algorithm using Gaussian synapse make the recognition algorithm very efficient and robust for classify human behavior by trajectory pattern.
Statistical Modeling of Interpersonal Distance with Range Imaging Data
Authors: René Hempel, Patrick Westfeld
Venue: Multimodal Signals: Cognitive and Algorithmic Issues: COST Action 2102 and euCognition International School Vietri sul Mare, Italy, April 21-26, 2008 Revised Selected and Invited Papers (2009)

The presented work combines automated highly resolved spatio-temporal photogrammetric data acquisition and analysis with statistical approaches for the determination of the interpersonal distance between interacting persons. This topic forms an interesting bridge between engineering and educational research, delivering a new efficient measurement technique to educational research and opening new application fields to photogrammetry.
What Sperner Family Concept Class is Easy to Be Enumerated?
Authors: Atsuyoshi Nakamura, Mineichi Kudo
Venue: Proceedings of the 2008 Eighth IEEE International Conference on Data Mining (2008)

We study the problem of enumerating concepts in a Sperner family concept class using subconcept queries, which is a general problem including maximal frequent itemset mining as its instance. Though even the theoretically best known algorithm needs quasi-polynomial time to solve this problem in the worst case, there exist practically fast algorithms for this problem. This is because many instances of this problem in real world have low complexity in some measures. In this paper, we characterize the complexity of Sperner family concept class by the VC dimension of its intersection closure and its characteristic dimension, and analyze the worst case time complexity on the enumeration problem of its concepts in terms of the VC dimension. We also showed that the VC dimension of real data used in data mining is actually small by calculating the VC dimension of some real datasets using a new algorithm closely related to the introduced two measures, which does not only solve the problem but also let us know the VC dimension of the intersection closure of the target concept class.