ppxscal/embedding_network huggingface dataset:
From Nerode's congruence to suffix automata with mismatches
Authors: M. Crochemore, C. Epifanio, A. Gabriele, F. Mignosi
Venue: Theoretical Computer Science (2009)

In this paper we focus on the minimal deterministic finite automaton S"k that recognizes the set of suffixes of a word w up to k errors. As first result we give a characterization of the Nerode's right-invariant congruence that is associated with S"k. This result generalizes the classical characterization described in [A. Blumer, J. Blumer, D. Haussler, A. Ehrenfeucht, M. Chen, J. Seiferas, The smallest automaton recognizing the subwords of a text, Theoretical Computer Science, 40, 1985, 31-55]. As second result we present an algorithm that makes use of S"k to accept in an efficient way the language of all suffixes of w up to k errors in every window of size r of a text, where r is the repetition index of w. Moreover, we give some experimental results on some well-known words, like prefixes of Fibonacci and Thue-Morse words. Finally, we state a conjecture and an open problem on the size and the construction of the suffix automaton with mismatches.
Hyper-Chaotic Neural Network Based on Newton Iterative Method and Its Application in Solving Load Flow Equations of Power System
Authors: Mingshan Cai, Rixin Chen, Lingshuang Kong
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 03 (2009)

Most of load flow equations of power system are multi-variable nonlinear equations set which need to know the initial value for solving, and the initial value is very difficult to choose. Neural network is a kind of highly complex nonlinear dynamic system and chaotic phenomenon is found in it. By utilizing the simulated annealing mechanism to eliminate transiently chaotic neuron, this paper presents a kind of chaotic neuron which can permanently sustain chaotic search. The topology of chaotic neural network composed of four chaotic neurons in which hyper-chaos exists is studied. For the first time, a novel method to find all solutions of nonlinear equations is proposed in which initial points are generated by hyper-chaotic neural network. The numerical example shows that the new method proposed in this paper is correct and effective, and it lays a good engineering foundation for finding all the solutions of load flow equations of power system.
Using P2P Overlay to Improve VoIP Quality in SIP+P2P System
Authors: Xiuwu Zhang, Weimin Lei, Bo Yu, Junying Jia
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 01 (2009)

The Current Internet provides a Best-effort service, which can not satisfy service quality guarantees that VoIP systems often require. Systems such as multi-homing and overlay network leverage path diversity that Internet inherently has to enhance end-to-end application performance. In this paper, we propose a P2P overlay approach, which is used to transmit media stream in SIP+P2P system. SIP+P2P is a Peer-to-Peer VoIP system, which leverages potential path diversity provided by P2P overlay to enhance VoIP quality. Firstly, we propose a path selection mechanism to ensure that end-to-end paths have a high degree of diversity. Then we develop an effective path switching mechanism based on P2P overlay, including path quality evaluation, predicting, and application-driven path switching. Finally, we evaluate our design on our SIP+P2P testbed, and prove that our path selection can explore high path diversity and that path switching can improve VoIP quality effectively.
In-place Augmented Reality
Authors: Nate Hagbi, Oriel Bergig, Jihad El-Sana, Klara Kedem, Mark Billinghurst
Venue: Proceedings of the 7th IEEE/ACM International Symposium on Mixed and Augmented Reality (2008)

In this paper we present a new vision-based approach for transmitting virtual models for Augmented Reality (AR). A two dimensional representation of the virtual models is embedded in a printed image. We apply image-processing techniques to interpret the printed image and extract the virtual models, which are then overlaid back on the printed image. The main advantages of our approach are: (1) the image of the embedded virtual models and their behaviors are understandable to a human without using an AR system, and (2) no database or network communication is required to retrieve the models. The latter is useful in scenarios with large numbers of users. We implemented an AR system that demonstrates the feasibility of our approach. Applications in education, advertisement, gaming, and other domains can benefit from our approach, since content providers need only to publish the printed content and all virtual information arrives with it.
Integrating knowledge for subjectivity sense labeling
Authors: Yaw Gyamfi, Janyce Wiebe, Rada Mihalcea, Cem Akkaya
Venue: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics (2009)

This paper introduces an integrative approach to automatic word sense subjectivity annotation. We use features that exploit the hierarchical structure and domain information in lexical resources such as WordNet, as well as other types of features that measure the similarity of glosses and the overlap among sets of semantically related words. Integrated in a machine learning framework, the entire set of features is found to give better results than any individual type of feature.
Using Links to Classify Wikipedia Pages
Authors: Rianne Kaptein, Jaap Kamps
Venue: Advances in Focused Retrieval: 7th International Workshop of the Initiative for the Evaluation of XML Retrieval, INEX 2008, Dagstuhl Castle, Germany, December 15-18, 2008. Revised and Selected Papers (2009)

This paper contains a description of experiments for the 2008 INEX XML-mining track. Our goal for the XML-mining track is to explore whether we can use link information to improve classification accuracy. Our approach is to propagate category probabilities over linked pages. We find that using link information leads to marginal improvements over a baseline that uses a Naive Bayes model. For the initially misclassified pages, link information is either not available or contains too much noise.
Learning to sing like a bird: self-supervised acquisition of birdsong
Authors: Michael H. Coen
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

This paper presents a new framework for self-supervised sensorimotor learning. We demonstrate this framework with a system that learns to mimic a zebra finch, directly modeled on the dynamics of how male fledglings acquire birdsong from their fathers. Our system first listens to the song of an adult finch. By listening to its own initially nascent attempts at mimicry through an articulatory synthesizer, the system organizes motor maps generating its vocalizations. Our approach is founded on the notion of cross-modal clustering, introduced in (Coen 2005, 2006a), and is unusual for its recursive reuse of perceptual mechanisms in developing motor control. In this paper, we outline this framework, present its results on the unsupervised acquisition of birdsong, and discuss other potential applications.
Statistics-Based Cognitive Human-Robot Interfaces for Board Games --- Let's Play!
Authors: Frank Wallhoff, Alexander Bannat, Jürgen Gast, Tobias Rehrl, Moritz Dausinger, Gerhard Rigoll
Venue: Proceedings of the Symposium on Human Interface 2009 on Human Interface and the Management of Information. Information and Interaction. Part II: Held as part of HCI International 2009 (2009)

The archetype of many novel research activities is called cognition. Although separate definitions exist to define a technical cognitive system, it is typically characterized by the (mental) process of knowing, including aspects such as awareness, perception, reasoning, and judgment. This especially includes the question of how to deal with previously unknown events.In order to further improve today's human-machine interfaces, which often suffer from deficient flexibilities, we present a cognitive human-robot interface using speech and vision. The advancements against regular rule-based approaches will become obvious by its new interaction strategies that will be explained in the use case of a board-game and a robot manipulator.The motivation behind the use of cognition for human-machine interfaces is to learn from and adapt to the user leading to an increased level of comfort. For our approach, it showed proof that it is effective to separate the entire process into three steps: the perception of external events, the cognition including understanding and the execution of an appropriate action.
Parameterized graph cleaning problems
Authors: Dániel Marx, Ildikó Schlotter
Venue: Discrete Applied Mathematics (2009)

We investigate the Induced Subgraph Isomorphism problem with non-standard parameterization, where the parameter is the difference |V(G)|-|V(H)| with H and G being the smaller and the larger input graph, respectively. Intuitively, we can interpret this problem as ''cleaning'' the graph G, regarded as a pattern containing extra vertices indicating errors, in order to obtain the graph H representing the original pattern. We show fixed-parameter tractability of the cases where both H and G are planar and H is 3-connected, or H is a tree and G is arbitrary. We also prove that the problem when H and G are both 3-connected planar graphs is NP-complete without parameterization.
Combinable Extensions of Abelian Groups
Authors: Enrica Nicolini, Christophe Ringeissen, Michaël Rusinowitch
Venue: Proceedings of the 22nd International Conference on Automated Deduction (2009)

The design of decision procedures for combinations of theories sharing some arithmetic fragment is a challenging problem in verification. One possible solution is to apply a combination method à la Nelson-Oppen, like the one developed by Ghilardi for unions of non-disjoint theories. We show how to apply this non-disjoint combination method with the theory of abelian groups as shared theory. We consider the completeness and the effectiveness of this non-disjoint combination method. For the completeness, we show that the theory of abelian groups can be embedded into a theory admitting quantifier elimination. For achieving effectiveness, we rely on a superposition calculus modulo abelian groups that is shown complete for theories of practical interest in verification.
Towards Efficient MapReduce Using MPI
Authors: Torsten Hoefler, Andrew Lumsdaine, Jack Dongarra
Venue: Proceedings of the 16th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface (2009)

MapReduce is an emerging programming paradigm for data-parallel applications. We discuss common strategies to implement a MapReduce runtime and propose an optimized implementation on top of MPI. Our implementation combines redistribution and reduce and moves them into the network. This approach especially benefits applications with a limited number of output keys in the map phase. We also show how anticipated MPI-2.2 and MPI-3 features, such as MPI_Reduce_local and nonblocking collective operations, can be used to implement and optimize MapReduce with a performance improvement of up to 25% on 127 cluster nodes. Finally, we discuss additional features that would enable MPI to more efficiently support all MapReduce applications.
Exploration of the Dendritic Cell Algorithm Using the Duration Calculus
Authors: Feng Gu, Julie Greensmith, Uwe Aickelin
Venue: Proceedings of the 8th International Conference on Artificial Immune Systems (2009)

As one of the newest members in Artificial Immune Systems (AIS), the Dendritic Cell Algorithm (DCA) has been applied to a range of problems. These applications mainly belong to the field of anomaly detection. Real-time detection, a new challenge to anomaly detection, requires improvement on the real-time capability of the DCA. To assess such capability, formal methods in the research of real-time systems can be employed. The findings of the assessment can provide guideline for the future development of the algorithm. Therefore, in this paper we use an interval logic based method, named the Duration Calculus (DC), to specify a simplified single-cell model of the DCA. Based on the DC specifications with further induction, we find that each individual cell in the DCA can perform its function as a detector in real-time. Since the DCA can be seen as many such cells operating in parallel, it is potentially capable of performing real-time detection. However, the analysis process of the standard DCA constricts its real-time capability. As a result, we conclude that the analysis process of the standard DCA should be replaced by a real-time analysis component, which can perform periodic analysis for the purpose of real-time detection.
The benefits of an ontological patient model in clinical decision-support
Authors: Mark Austin, Matthew Kelly, Sir Michael Brady
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 3 (2008)

In this paper we discuss an application integrating an ontological data model with an argumentation-based decision-support system, showing how the combination of leading technologies OWL, SPARQL and Jena can be used to achieve this. In the context of improving a decision support tool that is currently being trialled live in a clinical environment, we describe quantitatively how the incorporation of an ontology leads to an improvement over the existing software, highlighting the benefits of incorporating an ontology in medical applications. Data and clinical feedback is being collected from a live trial at the John Radcliffe hospital in Oxford, where we are able to test the original decision support tool, but also the ontology driven version, and thus will be able to demonstrate that any quantitative improvements in the efficacy of the software are a product of the ontological data model alone.
Exploring topic continuation follow-up questions using machine learning
Authors: Manuel Kirschner, Raffaella Bernardi
Venue: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Student Research Workshop and Doctoral Consortium (2009)

Some of the Follow-Up Questions (FU Q) that an Interactive Question Answering (IQA) system receives are not topic shifts, but rather continuations of the previous topic. In this paper, we propose an empirical framework to explore such questions, with two related goals in mind: (1) modeling the different relations that hold between the FU Q's answer and either the FU Q or the preceding dialogue, and (2) showing how this model can be used to identify the correct answer among several answer candidates. For both cases, we use Logistic Regression Models that we learn from real IQA data collected through a live system. We show that by adding dialogue context features and features based on sequences of domain-specific actions that represent the questions and answers, we obtain important additional predictors for the model, and improve the accuracy with which our system finds correct answers.
Research on the Measured Signal Processing by the Stress Sensor in the Soft Rock
Authors: Ji Chang-peng, Liu Li-li
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 03 (2009)

We discuss the borehole deformation which is caused by the sensor and changes with time, and the ground stress formula calculated by the measured value is finally brought out, which is called stress measurement with rheological method. With the practical measurement, we use the nonlinear least squares method to get rock stress, and stress measurement with rheological method is similar to stress measurement with the hole wall strain method in stress size and stress direction.
Integrating Software Technologies in RAXEM2 - AI Meets Information Technology
Authors: Giulio Bernardi, Amedeo Cesta, Gabriella Cortellessa
Venue: Proceedings of the Third IEEE International Conference on Space Mission Challenges for Information Technology (2009)

This paper describes aspects of RAXEM2, an intelligent software system developed to support human mission planners in the daily task to plan uplink commands for the MARS EXPRESS mission at the European Space Agency. A first system called RAXEM has been in operational use at the ESA-ESOC mission control center since Summer 2007. During 2008 authors have been working to a new version of the tool to both incorporate new functionalities and capture the entire life-cycle of the plan uplink problem. RAXEM2 has been released for daily use on March 2009 replacing previous work practice. The new tool combines a flexible AI-based automated algorithm, a user-friendly interaction front-end, and several functionalities for information management, overall guaranteeing continuity of work practice. The paper touches upon various aspects of the new system and comments on how a key factor for success has been the integration of such different modules in a unique comprehensive support environment.
XQuery Full Text Implementation in BaseX
Authors: Christian Grün, Sebastian Gath, Alexander Holupirek, Marc H. Scholl
Venue: Proceedings of the 6th International XML Database Symposium on Database and XML Technologies (2009)

BaseX is an early adopter of the upcoming XQuery Full Text Recommendation. This paper presents some of the enhancements made to the XML database to fully support the language extensions. The system's data and index structures are described, and implementation details are given on the XQuery compiler, which supports sequential scanning, index-based, and hybrid processing of full-text queries. Experimental analysis and an insight into visual result presentation of query results conclude the presentation.
An Integrative Tool for Gene Regulatory Network Reconstruction Based on Microarray Data
Authors: J. W. Ou, R. M. Hu, R. M. Chen, C. Y. Tang, Jeffrey J. P. Tsai
Venue: Proceedings of the 2009 Ninth IEEE International Conference on Bioinformatics and Bioengineering (2009)

The transcriptional regulation of gene expression has been known to be a key mechanism in the functioning of the cell and the gene expression is influenced by the transcriptional regulatory strengths. In this paper we extend the function of a former proposed gene expression analysis tool named Gene Expression Explorer to include the gene regulatory network reconstruction based on microarray data. The regulatory strengths between transcription factors and genes are implemented by a modified network component analysis method where the genes expression relationships between genes vs. tissues and transcription factors vs. tissues are adopted to explore the regulatory strengths between genes and various transcription factors. Visualized presentation of the proposed tool clearly illustrates the regulatory patterns of transcription factors for each related gene. The biologists could benefit from using this tool to analyze the gene regulatory network based on microarray data.
Image Based Quantitative Mosaic Evaluation with Artificial Video
Authors: Pekka Paalanen, Joni-Kristian Kämäräinen, Heikki Kälviäinen
Venue: Proceedings of the 16th Scandinavian Conference on Image Analysis (2009)

Interest towards image mosaicing has existed since the dawn of photography. Many automatic digital mosaicing methods have been developed, but unfortunately their evaluation has been only qualitative. Lack of generally approved measures and standard test data sets impedes comparison of the works by different research groups. For scientific evaluation, mosaic quality should be quantitatively measured, and standard protocols established. In this paper the authors propose a method for creating artificial video images with virtual camera parameters and properties for testing mosaicing performance. Important evaluation issues are addressed, especially mosaic coverage. The authors present a measuring method for evaluating mosaicing performance of different algorithms, and showcase it with the root-mean-squared error. Three artificial test videos are presented, ran through real-time mosaicing method as an example, and published in the Web to facilitate future performance comparisons.
M2ICAL analyses HC-gammon
Authors: Wee-Chong Oon, Martin Henz
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 1 (2007)

We analyse Pollack and Blair's HC-Gammon backgammon program using a new technique that performs Monte Carlo simulations to derive a Markov Chain model for Imperfect Comparison ALgorithms, called the M2ICAL method, which models the behavior of the algorithm using a Markov chain, each of whose states represents a class of players of similar strength. The Markov chain transition matrix is populated using Monte Carlo simulations. Once generated, the matrix allows fairly accurate predictions of the expected solution quality, standard deviation and time to convergence of the algorithm. This allows us to make some observations on the validity of Pollack and Blair's conclusions, and also shows the application of the M2ICAL method on a previously published work.
Fast Algorithms for Multi-stream Content Detection
Authors: Yuping Huang, Sanfeng Chen
Venue: Proceedings of the 2009 Second International Symposium on Electronic Commerce and Security - Volume 02 (2009)

High-speed packet content inspection and filtering devices rely on a fast multi-pattern matching algorithm which is used to detect predefined keywords or signatures in the packets. In TCP, a communication data stream is split into packets. Therefore, a target pattern may span multiple packets. Such fragmented pattern cannot be discovered by a per-packet scan. This is a serious problem in applications such as NIDS that require a complete scan. To avoid the problem, it is necessary to scan TCP streams. Stream-level parallelism is not a substantial solution because bandwidth depends on the number of active TCP streams. To scan each stream separately using one matching unit, the match states must be swapped appropriately. Another problem is, as parts of network infrastructure, the inspection units should support the function of Qos. In this paper, we proposed a multi-pattern matching automaton DSC-AC for high speed multi-stream packet scanning. We given out the construction of DSC-AC and optimized it with optimal and two binary searching tree and bit-map AC. Analysis and test showed that the optimized DSC-AC is capable of lightweight switching , enables a little state saving between streams and support the Diff-Serv Qos model. Furthermore, our method also enables easy implementation of multi-stream scanners with high throughput.
An Algorithm for Real-Time Fast Walkthrough of Massive Terrain
Authors: Hailiang Jin, Huijie Liu
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 01 (2009)

Terrain walkthrough is a hot point in GIS, virtual reality and military simulation fields. Large scale terrain algorithm is used to load data partly into the memory, and then simplify terrain to speed up drawing-rate. This paper presents an algorithm which blocks the terrain, uses back face culling and modified viewpoint error equation to construct Level of Detail (LOD), and then uses a new horizon culling method based on screen error bounding box. This algorithm has a fast drawing-rate. Besides, memory mapping file technique to load DEM data is used to make the algorithm have high performance data process ability on massive terrain data.