ppxscal/embedding_network huggingface dataset:
Simulation in context: using data farming for decision support
Authors: Philip Barry, Matthew Koehler
Venue: Proceedings of the 36th conference on Winter simulation (2004)

Data Farming leverages high performance computing to run simple models many times. This process allows for the exploration of massive parameter spaces relatively quickly. This paper explores a methodology to use Data Farming as a decision support tool. Data Farming can be a highly effective in this role because it allows one to present to a decision-maker not only what may be the most likely outcome but what are possible outcomes, especially outliers that might have far reaching impact. The terrorist attacks of September 2001 are a good example of an outlier with very high impact. A case study is presented using a simple terrorist attack simulation and decision-maker utility model.
Efficient Rotation Invariant Retrieval of Shapes with Applications in Medical Databases
Authors: Selina Chu, Shrikanth Narayanan, C.-C. Jay Kuo
Venue: Proceedings of the 19th IEEE Symposium on Computer-Based Medical Systems (2006)

Recognition of shapes in images is an important problem in computer vision with application in various medical problems, including robotic surgery and cell analysis. The similarity measures for such purpose must be robust to various transformations and modest occlusions. Transformations, such as scaling and translation can be handled easily by techniques through data representations or similarity measures. Rotation invariance is an inherently more difficult problem and can be handled through data representation, but at the expense of poor discrimination. Approaches which provide excellent discrimination require a complexity of O(n3) for each shape comparison. In this paper, we present a framework that provides a speedup over the slow but accurate approaches. The algorithm is inspired by the iterative deepening framework in artificial intelligence, by examining the data at increasingly fine levels of approximation until it is either considered irrelevant or submits to the full calculations. Although we examine the data several times at different levels of abstractions, because the time required for the last iteration dwarfs all others, this apparent redundancy is inconsequential. We will show that our method provides at least a 3-4 orders of magnitude in speedup without generating any false dismissals.
Efficiently Utilizing ATE Vector Repeat for Compression by Scan Vector Decomposition
Authors: Jinkyu Lee, Nur A. Touba
Venue: Proceedings of the 15th Asian Test Symposium (2006)

Previous approaches for utilizing ATE vector repeat are based on identifying runs of repeated scan data and directly generating that data using ATE vector repeat. Each run requires a separate vector repeat instruction, so the amount of compression is limited by the amount of ATE instruction memory available and the length of the runs (which typically will be much shorter than the length of a scan vector). In this paper a new and more efficient approach is proposed for utilizing ATE vector repeat. The scan vector sequence is partitioned and decomposed into a common sequence which is the same for an entire cluster of test cubes and a unique sequence that is different for each test cube. The common sequence can be generated very efficiently using ATE vector repeat. Experimental results demonstrate that the proposed approach can achieve much greater compression while using many fewer vector repeat instructions compared with previous methods.
An Evaluation of the Effectiveness of Measurement-based Anomaly Detection Techniques
Authors: Seong Soo Kim, A. L. Narasimha Reddy
Venue: Proceedings of the 26th IEEE International ConferenceWorkshops on Distributed Computing Systems (2006)

A number of recent studies have proposed measurement based approaches to network traffic analysis. These techniques treat traffic volume and traffic header data as signals or images in order to make analysis feasible. We use trace-driven experiments and compare the performance of different strategies. Our evaluations on real traces reveal differences in the effectiveness of different traffic header data as potential signals for traffic analysis in terms of their detection rates and false alarm rates. Our results show that address distributions and number of flows are better signals than traffic volume for anomaly detection.
Double rulings for information brokerage in sensor networks
Authors: Rik Sarkar, Xianjin Zhu, Jie Gao
Venue: Proceedings of the 12th annual international conference on Mobile computing and networking (2006)

We study the problem of information brokerage in sensor networks, where information consumers (sinks,users)search for data acquired by information producers (sources). In-network storage such as geographical hash table (GHTs) has been proposed to store data at rendezvous nodes for consumers to retrieve. In this paper, we propose a double rulings scheme which stores data replica at a curve instead of one or multiple isolated sensors. The consumer travels along another curve which guarantees to intersect with the producer curve. The double rulings is a natural extension of the flat hashing scheme such as GHTs with improved query locality, i.e., consumers close to producers find the data quickly, and structured aggregate queries, i.e., a consumer following a curve is able to retrieve all the data. Further, by the flexibility of retrieval mechanisms we have better routing robustness and data robustness. We show by simulation that the double rulings scheme provide reduced communication costs and more balanced traffic load on the sensors.
Automatic Debugging of Real-Time Systems Based on Incremental Satisfiability Counting
Authors: Stefan Andrei, Wei Ngan Chin Albert Mo Kim Cheng, Mihai Lupu
Venue: IEEE Transactions on Computers (2006)

Real-time logic (RTL) [2], [3], [4] is useful for the verification of a safety assertion with respect to the specification of a real-time system. Since the satisfiability problem for RTL is undecidable, the systematic debugging of a real-time system appears impossible. A first step toward this challenge was presented in [1]. With RTL, each propositional formula corresponds to a verification condition. The number of truth assignments of a propositional formula can help us determine the specific constraints which should be added or modified to get the expected solutions. This paper solves an even more challenging problem specified as future work in [1], namely, the embedding and the integration of our debugger in autonomous systems which generate real-time control plans on-the-fly, since these specifications must meet timing constraints, but without human interaction. The idea is to consider in advance all the necessary information, such as the designer's guidance. We have implemented a tool (called ADRTL) that is able to perform automatic debugging. The confidence of our approach is high as we have successfully evaluated ADRTL on several existing industrial-based applications.
Development of a XML-based Ubiquitous System for Testing Using Smartphones
Authors: Antonio Penalver Benavent, Oscar Martinez Bonastre, Miguel Martinez Girona
Venue: Proceedings of the Fourth IEEE International Workshop on Wireless, Mobile and Ubiquitous Technology in Education (2006)

In this paper, authors introduce a novelty XMLbased m-learning author tool running on Windows Mobile-based smartphones which allows students to take different stored test. This mobile-based Application runs off-line and only connects through Internet whenever should be required. Initial performance was evaluated requesting user feed-back through informal interview, as a result a summarize evaluation of usability, user performance and behaviour was discussed respectively.
Max-Life Power Schedule for connectivity and biconnectivity in wireless ad hoc networks
Authors: Peng-Jun Wan, Chih-Wei Yi
Venue: Mobile Networks and Applications (2005)

Given the initial energy supplies and the maximal transmission power of the individual nodes in a wireless ad hoc network, a power schedule of duration t for a specified topological property P is a scheduling of the transmission powers of the individual nodes over the period [0, t] such that (1) the total amount of energy consumed by each node during the period [O, t] does not exceed its initial energy supply, (2) the transmission power of each node at any moment in the period [O, t] does not exceed its maximal transmission power, and (3) the produced network topology at any moment in the period [0, t] satisfies the property P. The problem Max-Life Power Schedule for P seeks a power schedule of the maximal duration for P. Let g be the golden ratio (1 + √5)/2, and ε be an arbitrarily positive constant less than one. In this paper, we present a 9g/(1 - ε)2-approximation algorithm for Max-Life Power Schedule for Connectivity, a 36g/(1 - ε)2- approximation algorithm for Max-Life Power Schedule for 2-Node-Connectivity, and a 36g/(1 - ε)2-approximation algorithm for Max-Life Power Schedule for 2-Edge-Connectivity.
Identifying Lymphoma in Microscopy Images with Classificational Cellular Automata
Authors: Petra Povalej, Mateja Verli, Peter Kokol, Jose L. Sanchez, Jose F. Sigut
Venue: Proceedings of the 19th IEEE Symposium on Computer-Based Medical Systems (2006)

We present the results of a supervised approach for identification of follicular lymphomas in microscopy images. A new feature extraction approach is presented. The proposed discriminative features intend to emphasize the distinction among pixels on follicle contour. Additionally those features are used for supervised learning using Classificational Cellular Automata (CCA) approach with the aim to obtain a general decision support model for classification of follicle contours on the microscopy images.
On Small World Graphs in Non-uniformly Distributed Key Spaces
Authors: Sarunas Girdzijauskas, Anwitaman Datta, Karl Aberer
Venue: Proceedings of the 21st International Conference on Data Engineering Workshops (2005)

In this paper we show that the topologies of most logarithmic-style P2P systems like Pastry, Tapestry or P-Grid resemble small-world graphs. Inspired by Kleinberg's small-world model [7] we extend the model of building "routing-efficient" small-world graphs and propose two new models. We show that the graph, constructed according to our model for uniform key distribution and logarithmic outdegree, will have similar properties as the topologies of structured P2P systems with logarithmic outdegree. Moreover, we propose a novel model of building graphs which support uneven node distributions and preserves all desired properties of Kleinberg's small-world model. With such a model we are setting a reference base for nowadays emerging P2P systems that need to support uneven key distributions.
Output Media Adapted Cartographic Visualisation
Authors: Alexandra Stadler, Mirjanka Lechthaler
Venue: Proceedings of the conference on Information Visualization (2006)

Internet offers an ideal platform for the communication via maps. The map graphics pose as an essential part of the graphical user interface in Atlas Information Systems (AIS) that enables the user to investigate the underlying data. Existing AIS largely deal with functionalities, but often do not concentrate on visualisation aspects. The solutions vary from simple line graphics with hardly any cartographic characteristics to systems that are based on scanned maps, ignoring the technical restrictions of the screen as an output medium. So the authors are searching for high-class AIS which should rely on cartographically improved map graphics suitable for both, screen visualisation and high-quality printing. Using legible map graphics which are adapted to the technical requirements of the output medium is one of the main criteria for user acceptance. Concerning the definition of characteristic sheets for printed maps, much experience has been gained within the last few decades. The situation is not the same for screen visualisation. Due to their technical restrictions, screen presentations suffer from deformations of the graphic elements. In order to produce legible maps, the map graphics have to be adapted to the screen.
Some formal tools for analyzing quantum automata
Authors: Alberto Bertoni, Carlo Mereghetti, Beatrice Palano
Venue: Theoretical Computer Science (2006)

Results in the area of compact monoids and groups are useful in the analysis of quantum automata (lqfa's). In this paper: (1) We settle isolated cut point Rabin's theorem in the context of compact monoids, and we prove a lower bound on the state complexity of lqfa's accepting regular languages. (2) We use a method pointed out by Blondel et al. [Decidable and undecidable problems about quantum automata, Technical Report RR2003-24, LIP, ENS Lyon, 2003] based on compact groups theory to design an algorithm for testing whether a k-tuple of lqfa's is a classifier of words in Σ*; this problem turns out to be undecidable if the completeness of the classifier is required. (3) In the unary case, we give an exponential time algorithm for computing the descriptional complexity of periodic languages. Moreover, we present a probabilistic method to construct lqfa's exponentially succinct in the period and polynomially succinct in the inverse of the bounded error.
Automatic Subscriptions In Publish-Subscribe Systems
Authors: Lars Brenna, Cathal Gurrin, Dag Johansen, Dmitrii Zagorodnov
Venue: Proceedings of the 26th IEEE International ConferenceWorkshops on Distributed Computing Systems (2006)

In this paper, we describe how to automate the process of subscribing to complex publish-subscribe systems. We present a proof-of-concept prototype, in which we analyze Web browsing history to generate zero-click subscriptions to Web feeds and video news stories. Our experience so far indicates that user attention data is a promising source of data for automating the subscription process.
Regularity of the Eikonal Equation with Neumann Boundary Conditions in the Plane: Application to Fronts with Nonlocal Terms
Authors: Pierre Cardaliaguet, Claudio Marchi
Venue: SIAM Journal on Control and Optimization (2006)

The first part of the paper is devoted to length estimates of the boundary of the reachable set for the plane and state constrained controlled system x&apos;(t) = c(t,x(t))b(t) (where |b(t)| \leq 1 a.e.). This study is motivated in the second part by the analysis of dislocation dynamics, which can be modeled as a curve Gamma(t) moving in an open set Omega \subset R2 according to some nonlocal law with Neumann boundary conditions on \partial Omega. The length estimates of the first part play a crucial role in the proof of the existence and uniqueness of a viscosity solution for this model.
Self-organising text collections with adaptive resonance theory neural networks
Authors: Louis Massey
Venue:  (2005)

There is a large and continually growing quantity of electronic documents available, which contains essential human and organizations knowledge. An important research endeavor is to study and develop better ways to access this knowledge. Text clustering is a popular approach to automatically organize textual document collections by topics to help users find the information they need. Adaptive Resonance Theory (ART) neural networks possess several interesting properties that make them appealing in the area of text clustering, chiefly for dynamic real-world text collections. Although ART has been used in several research works as a text clustering tool, the quality of the resulting document clusters has not been clearly established. Furthermore, its performance in a dynamic environment---which should be its strength---has never been studied. In this thesis, we present experimental results with binary ART that address these issues. Flat single topic, multi-topic and hierarchical clustering are examined. We also develop a novel clustering quality evaluation approach that allows one to compare text clustering with its supervised counterpart, text categorization.
Design of Virtual co-Learner for Asynchronous Collaborative e-Learning
Authors: Sotirios Botsios, Vasiliki Mitropoulou, Dimitrios Georgiou, Ioannis Panapakidis
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

Collaborative agents can achieve an almost natural human-computer interaction. Agents are life-like computer characters that can interact with learners. They do so by picking up phrases from a database, according to predefined set of rules so as to achieve effective communication. We introduce the design of a software agent capable of collaborating with a learner in asynchronous e-learning environment. It offers new opportunities in e-learning as it integrates collaborative learning in a manner that challenges traditional methods of pedagogy and benefits the learning process.
Adaptive Multi-Path Video Streaming
Authors: Zi Ling, Ivan Lee
Venue: Proceedings of the Eighth IEEE International Symposium on Multimedia (2006)

Multiple description codes are designed for multiple path video streaming with channel diversities. In this paper, we investigate the performance of multi-path video streaming using a multiple description coding (MDC) technique. An efficient MDC technique based on spatial domain processing is applied. The impacts of several codec variables, such as different numbers of MDC sub-streams, different lengths of the Group of Pictures (GOP), and aligned and unaligned I-frames for MDC sub-streams, are further discussed in this paper. The performance of the system is evaluated by the frame dropout rate, which indicates the probability of playing back frozen frames of the reconstructed video at the receiver devices. To address dynamic channel conditions for video transmissions, we propose an adaptive coding technique by adjusting the GOP lengths according to the channel condition. Different approaches, such as sub-dividing GOPs for a single stream and multiple sub-streams, and an adaptive MDC video streaming system, are examined in this paper.
fMRI Reveals a Common Neural Substrate of Illusory and Real Contours in V1 after Perceptual Learning
Authors: Marianne Maertens, Stefan Pollmann
Venue: Journal of Cognitive Neuroscience (2005)

Perceptual learning involves the specific and relatively permanent modification of perception following a sensory experience. In psychophysical experiments, the specificity of the learning effects to the trained stimulus attributes (e.g., visual field position or stimulus orientation) is often attributed to assumed neural modifications at an early cortical site within the visual processing hierarchy. We directly investigated a neural correlate of perceptual learning in the primary visual cortex using fMRI. Twenty volunteers practiced a curvature discrimination on Kanizsa-type illusory contours in the MR scanner. Practice-induced changes in the BOLD response to illusory contours were compared between the pretraining and the posttraining block in those areas of the primary visual cortex (V1) that, in the same session, had been identified to represent real contours at corresponding visual field locations. A retinotopically specific BOLD signal increase to illusory contours was observed as a consequence of the training, possibly signaling the formation of a contour representation, which is necessary for performing the curvature discrimination. The effects of perceptual training were maintained over a period of about 10 months, and they were specific to the trained visual field position. The behavioral specificity of the learning effects supports an involvement of V1 in perceptual learning, and not in unspecific attentional effects.
On Trajectory Representation for Scientific Features
Authors: Sameep Mehta, Srinivasan Parthasarathy, Raghu Machiraju
Venue: Proceedings of the Sixth International Conference on Data Mining (2006)

In this article, we present trajectory representation algorithms for tangible features found in temporally varying scientific datasets. Rather than modeling the features as points, we take attributes like shape and extent of the feature into account. Our contention is that these attributes play an important role in understanding the temporal evolution and interactions among features. The proposed representation scheme is based on motion and shape parameters including linear velocity, angular velocity, etc. We use these parameters to segment the trajectory instead of relying on the geometry of the trajectory. We evaluate our algorithms on real datasets originating from different domains. We show the accuracy of the motion and shape parameter estimation by reconstructing the trajectories with high accuracy. Finally, we present performance and scalability results.
An agent-based simulation of pedestrian dynamics: from lane formation to auditorium evacuation
Authors: Marcelo C. Toyama, Ana L. C. Bazzan, Roberto da Silva
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

In this paper we present an agent-based simulation of pedestrian dynamics based on cellular automata models. Differently from the cellular automata, our model represents different pedestrian characteristics: gender, speed, room geometry knowledge, and herding and obstacle avoidance behavior. We study how different room geometries, different pedestrian groups sizes and characteristics influence the pedestrian dynamics and the macroscopic behavior of the system. With this agent-based approach we expect to obtain more realistic results than the cases where the pedestrians are uniformly modeled. Our analysis indicates that pedestrian groups with different features contribute in different ways to the macroscopic behavior.
Distinguishing SAT from Polynomial-Size Circuits, through Black-Box Queries
Authors: Albert Atserias
Venue: Proceedings of the 21st Annual IEEE Conference on Computational Complexity (2006)

We may believe SAT does not have small Boolean circuits. But is it possible that some language with small circuits looks indistiguishable from SAT to every polynomialtime bounded adversary? We rule out this possibility. More precisely, assuming SAT does not have small circuits, we show that for every language with small circuits, there exists a probabilistic polynomial-time algorithm that makes black-box queries to A, and produces, for a given input length, a Boolean formula on whichA differs from SAT. A key step for obtaining this result is a new proof of the main result by Gutfreund, Shaltiel, and Ta-Shma reducing average-case hardness to worst-case hardness via uniform adversaries that know the algorithm they fool. The new adversary we construct has the feature of being black-box on the algorithm it fools, so it makes sense in the non-uniform setting as well. Our proof makes use of a refined analysis of the learning algorithm of Bshouty et al..