ppxscal/embedding_network huggingface dataset:
Particle Filtering Based on Sign of Innovation for Tracking a Jump Markovian Motion in a Binary WSN
Authors: Fatma Aounallah, Rim Amara, Monia Turki-Hadj Alouane
Venue: Proceedings of the 2009 Third International Conference on Sensor Technologies and Applications (2009)

This paper deals with target tracking in a binary wireless sensor network. In this contribution, the target motion is represented by a non linearmodelbased on a jump-Markovian direction. The observation of the trajectory based on the target signal strength is performed by binary sensors. In particular, only one sensor emits one bit by instant what increases the longevity of the wireless sensor network. A particle filter based on the sign of innovation is proposed to track the target motion. Relying on exhaustive simulation results, the proposed SOI-PF exhibits very attractive transient and steady state performance. In deed, for all the considered tracking contexts a high convergence rate and an accurate estimation of the target position are obtained.
An Efficient Distance Bounding RFID Authentication Protocol: Balancing False-Acceptance Rate and Memory Requirement
Authors: Gildas Avoine, Aslan Tchamkerten
Venue: Proceedings of the 12th International Conference on Information Security (2009)

The Mafia fraud consists in an adversary transparently relaying the physical layer signal during an authentication process between a verifier and a remote legitimate prover. This attack is a major concern for certain RFID systems, especially for payment related applications.Previously proposed protocols that thwart the Mafia fraud treat relaying and non-relaying types of attacks equally: whether or not signal relaying is performed, the same probability of false-acceptance is achieved. Naturally, one would expect that non-relay type of attacks achieve a lower probability of false-acceptance.We propose a low complexity authentication protocol that achieves a probability of false-acceptance essentially equal to the best possible false-acceptance probability in the presence of Mafia frauds. This performance is achieved without degrading the performance of the protocol in the non-relay setting. As an additional feature, the verifier can make a rational decision to accept or to reject a proof of identity even if the protocol gets unexpectedly interrupted.
Computing Naturally in the Billiard Ball Model
Authors: Liang Zhang
Venue: Proceedings of the 8th International Conference on Unconventional Computation (2009)

Fredkin's Billiard Ball Model (BBM) is considered one of the fundamental models of collision-based computing, and it is essentially based on elastic collisions of mobile billiard balls. Moreover, fixed mirrors or reflectors are brought into the model to deflect balls to complete the computation. However, the use of fixed mirrors is "physically unrealistic" and makes the BBM not perfectly momentum conserving from a physical point of view, and it imposes an external architecture onto the computing substrate which is not consistent with the concept of "architectureless" in collision-based computing. In our initial attempt to reduce mirrors in the BBM, we present a class of gates: the m-counting gate, and show that certain circuits can be realized with few mirrors using this gate. We envisage that our findings can be useful in future research of collision-based computing in novel chemical and optical computing substrates. 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
OpenFlyData: The Way to Go for Biological Data Integration
Authors: Jun Zhao, Alistair Miles, Graham Klyne, David Shotton
Venue: Proceedings of the 6th International Workshop on Data Integration in the Life Sciences (2009)

Although many applications have attempted to provide integrative access to distributed datasets, domain scientists largely continue to harvest research data in a conventional way, by consulting each resource independently, because such applications do not fully meet users' needs. This paper describes OpenFlyData ( http://openflydata.org/ ), a simple user-led service providing Drosophila researchers with integrated access to distributed information. This is an exemplar lightweight solution to the problems of data integration, in which accurate and explicit data modelling enables high precision information retrieval.
Between Order and Chaos: The Quest for Meaningful Information
Authors: Pieter Adriaans
Venue: Theory of Computing Systems (2009)

The notion of meaningful information seems to be associated with the sweet spot between order and chaos. This form of meaningfulness of information, which is primarily what science is interested in, is not captured by both Shannon information and Kolmogorov complexity. In this paper I develop a theoretical framework that can be seen as a first approximation to a study of meaningful information. In this context I introduce the notion of facticity of a data set. I discuss the relation between thermodynamics and algorithmic complexity theory in the context of this problem. I prove that, under adequate measurement conditions, the free energy of a system in the world is associated with the randomness deficiency of a data set with observations about this system. These insights suggest an explanation of the efficiency of human intelligence in terms of helpful distributions. Finally I give a critical discussion of Schmidhuber&#x2019;s views specifically his notion of low complexity art, I&#x00a0;defend the view that artists optimize facticity instead.
Subtree mining for relation extraction from Wikipedia
Authors: Dat P. T. Nguyen, Yutaka Matsuo, Mitsuru Ishizuka
Venue: Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers on XX (2007)

In this study, we address the problem of extracting relations between entities from Wikipedia's English articles. Our proposed method first anchors the appearance of entities in Wikipedia's articles using neither Named Entity Recognizer (NER) nor coreference resolution tool. It then classifies the relationships between entity pairs using SVM with features extracted from the web structure and subtrees mined from the syntactic structure of text. We evaluate our method on manually annotated data from actual Wikipedia articles.
Longitudinal data analysis using sufficient dimension reduction method
Authors: Lexin Li, Xiangrong Yin
Venue: Computational Statistics Data Analysis (2009)

There have been an increasing number of applications where the number of predictors is large, meanwhile data are repeatedly measured at a sequence of time points. In this article we investigate how dimension reduction method can be employed for analyzing such high-dimensional longitudinal data. Predictor dimension can be effectively reduced while full regression means information can be retained during dimension reduction. Simultaneous variable selection along with dimension reduction is studied, and graphical diagnosis and model fitting after dimension reduction are investigated. The method is flexible enough to encompass a variety of commonly used longitudinal models.
Using N-best lists for named entity recognition from Chinese speech
Authors: Lufeng Zhai, Pascale Fung, Richard Schwartz, Marine Carpuat, Dekai Wu
Venue: Proceedings of HLT-NAACL 2004: Short Papers on XX (2004)

We present the first known result for named entity recognition (NER) in realistic large-vocabulary spoken Chinese. We establish this result by applying a maximum entropy model, currently the single best known approach for textual Chinese NER, to the recognition output of the BBN LVCSR system on Chinese Broadcast News utterances. Our results support the claim that transferring NER approaches from text to spoken language is a significantly more difficult task for Chinese than for English. We propose re-segmenting the ASR hypotheses as well as applying post-classification to improve the performance. Finally, we introduce a method of using n-best hypotheses that yields a small but nevertheless useful improvement NER accuracy. We use acoustic, phonetic, language model, NER and other scores as confidence measure. Experimental results show an average of 6.7% relative improvement in precision and 1.7% relative improvement in F-measure.
Generating multimedia briefings: language generation in a coordinated multimedia environment
Authors: Kathleen R. McKeown
Venue: Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2 (1997)

Communication can be more effective when several media (such as text, speech, or graphics) are integrated and coordinated to present information. This changes the nature of media specific generation (e.g., language generation) which must take into account the multimedia context in which it occurs. In this paper, 1 will present work on coordinating and integrating speech, text, static and animated 3D graphics, and stored images, as part of several systems we have developed at Columbia University. A particular focus of our work has been on the generation of presentations that brief a user on information of interest.
Learning to find transliteration on the web
Authors: Chien-Cheng Wu, Jason S. Chang
Venue: Proceedings of Human Language Technologies: The Annual Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations on XX (2007)

This prototype demonstrate a novel method for learning to find transliterations of proper nouns on the Web based on query expansion aimed at maximizing the probability of retrieving transliterations from existing search engines. Since the method we used involves learning the morphological relationships between names and their transliterations, we refer to this IR-based approach as morphological query expansion for machine transliteration. The morphological query expansion approach is general in scope and can be applied to translation and transliteration, but we focus on transliteration in this paper.
Combining ICA with LSSVM for Speckle Reduction of SAR Image
Authors: Wu Dingxue, Fan Wenping
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 01 (2009)

Speckles are inherent defects due to coherent imaging principles in synthetic aperture radar (SAR) systems. An improved polarimetric SAR image filtering method based on ICA (independent component analysis) -LSSVM (least squares support vector machine) was developed to get better results for terrain classification, target detection and other applications. The first step of this method is to apply ICA to LSSVM for feature extraction. By using ICA, the original higher dimensional inputs will be transformed into other lower dimensional features, the regularized parameter and feature subsets will be geted,These new features are then used as the inputs of LSSVM to process a regularized procedure which defines a cost function to estimate true SAR image.Experiment results using polarimetric SAR data of ERS-1 satellite show that this algorithm attains good despeckling effect and preserves more valuable image details than traditional algorithms.
Synchronous grammars and transducers: good news and bad news
Authors: Stuart M. Shieber
Venue: Proceedings of the 10th International Conference on Parsing Technologies (2007)

Much of the activity in linguistics, especially computational linguistics, can be thought of as characterizing not languages simpliciter but relations among languages. Formal systems for characterizing language relations have a long history with two primary branches, based respectively on tree transducers and synchronous grammars. Both have seen increasing use in recent work, especially in machine translation. Indeed, evidence from millennia of experience with bilingual dictionaries argues for synchronous grammars as an appropriate substrate for statistical machine translation systems.
Symplectic integrator for nonlinear high order Schrödinger equation with a trapped term
Authors: Linghua Kong, Jialin Hong, Lan Wang, Fangfang Fu
Venue: Journal of Computational and Applied Mathematics (2009)

In the manuscript, we discuss the symplectic integrator for the numerical solution of a kind of high order Schrodinger equation with trapped terms. The Hamiltonian formulism is discovered for it. We first discretize the Hamiltonian system in space to reduce it to a finite-dimensional one. Then the symplectic midpoint scheme is applied to the temporal discretization. The symplectic scheme we devise is of second order accuracy in time and 2lth order accuracy in space. It is proved that it preserves the charge of the original equation veraciously. The energy is not preserved explicitly for the exception of the linear case. However, after some computation, the energy transit formula in the temporal direction is obtained. In the numerical part, we compare our scheme with some existing schemes, including the leap frog scheme and the energy-preserving scheme. From the numerical evidence, we find that our numerical schemes are efficient and available.The numerical results are consistent with the theoretical analysis.
Metric Methods in Surface Triangulation
Authors: E. Saucan, E. Appleboim
Venue: Proceedings of the 13th IMA International Conference on Mathematics of Surfaces XIII (2009)

We consider the problem of better approximating surfaces by triangular meshes. The approximating triangulations are regarded as finite metric spaces and the approximated smooth surfaces are viewed as their Haussdorff-Gromov limit. This allows us to define in a more natural way the relevant elements, constants and invariants, such as principal directions and Gauss curvature, etc. By a "natural way" we mean intrinsic, discrete, metric definitions as opposed to approximating or paraphrasing the differentiable notions. Here we consider the problem of determining the Gauss curvature of a polyhedral surface, by using the metric curvatures in the sense of Wald, Menger and Haantjes. We present three modalities of employing these definitions for the computation of Gauss curvature.
The Design and Realization of Server Virtualization Based on Active Directory
Authors: Hu Kai
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 01 (2009)

With the development of server virtualization, it is earning widespread respect by more and more professions, and it is a research hotspot which lead the technology into X86-structure server. This paper design and implement the deployment solution about DHCP, DNS, WINS Server virtualization based on active directory, and show the figures about how to realize it.
Exploring ant-based algorithms for gene expression data analysis
Authors: Yulan He, Siu Cheung Hui
Venue: Artificial Intelligence in Medicine (2009)

Objective: Recently, much research has been proposed using nature inspired algorithms to perform complex machine learning tasks. Ant colony optimization (ACO) is one such algorithm based on swarm intelligence and is derived from a model inspired by the collective foraging behavior of ants. Taking advantage of the ACO in traits such as self-organization and robustness, this paper investigates ant-based algorithms for gene expression data clustering and associative classification. Methods and material: An ant-based clustering (Ant-C) and an ant-based association rule mining (Ant-ARM) algorithms are proposed for gene expression data analysis. The proposed algorithms make use of the natural behavior of ants such as cooperation and adaptation to allow for a flexible robust search for a good candidate solution. Results: Ant-C has been tested on the three datasets selected from the Stanford Genomic Resource Database and achieved relatively high accuracy compared to other classical clustering methods. Ant-ARM has been tested on the acute lymphoblastic leukemia (ALL)/acute myeloid leukemia (AML) dataset and generated about 30 classification rules with high accuracy. Conclusions: Ant-C can generate optimal number of clusters without incorporating any other algorithms such as K-means or agglomerative hierarchical clustering. For associative classification, while a few of the well-known algorithms such as Apriori, FP-growth and Magnum Opus are unable to mine any association rules from the ALL/AML dataset within a reasonable period of time, Ant-ARM is able to extract associative classification rules.
An Improved Binary Tree SVM Classification Algorithm Based on Bayesian
Authors: LiBin Ren, HuiYou Chang, Yang Yi
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 01 (2009)

Due to the great generalization and the support of statistics, support vector machines (SVMs) has been widely applied to resolving multi-class classification problem. Numbers of multi-class SVM have been proposed. Compared with other multi-class SVM, Binary Tree of SVM (BTS) takes a good advantage of lower time consuming. However, there is some unnecessary data reassignment during constructing a binary tree, which makes BTS can't resolve the high-dimensional multi-class classification problem accurately. In this paper, a bayesian-based BTS classification algorithm (b-BTS) has been proposed. Experiments demonstrated that b-BTS is superior to BTS in resolving classification problem, such as image classification problem.
Some theoretical challenges in digital geometry: A perspective
Authors: Tetsuo Asano, Valentin E. Brimkov, Reneta P. Barneva
Venue: Discrete Applied Mathematics (2009)

In recent years image analysis has become a research field of exceptional significance, due to its relevance to real life problems in important societal and governmental sectors, such as medicine, defense, and security. The explicit purpose of the present Perspective is to suggest a number of strategic objectives for theoretical research, with an emphasis on the combinatorial approach in image analysis. Most of the proposed objectives relate to the need to make the theoretical foundations of combinatorial image analysis better integrated within a number of well-established subjects of theoretical computer science and discrete applied mathematics, such as the theory of algorithms and problem complexity, combinatorial optimization and polyhedral combinatorics, integer and linear programming, and computational geometry.
Interactive survival analysis with the OCDM system: From development to application
Authors: Sebastian Klenk, Jürgen Dippon, Peter Fritz, Gunther Heidemann
Venue: Information Systems Frontiers (2009)

Medical data mining is currently actively pursued in computer science and statistical research but not in medical practice. The reasons therefore lie in the difficulties of handling and statistically analyzing medical data. We have developed a system that allows practitioners in the field to interactively analyze their data without assistance of statisticians or data mining experts. In the course of this paper we will introduce data mining of medical data and show how this can be achieved for survival data. We will demonstrate how to solve common problems of interactive survival analysis by presenting the Online Clinical Data Mining (OCDM) system. Thereby the main focus is on similarity based queries, a new method to select similar cases based on their covariables and the influence of these on their survival.
People modify their tutoring behavior in robot-directed interaction for action learning
Authors: Anna-Lisa Vollmer, Katrin Solveig Lohan, Kerstin Fischer, Yukie Nagai, Karola Pitsch, Jannik Fritsch, Katharina J. Rohlfing, Britta Wredek
Venue: Proceedings of the 2009 IEEE 8th International Conference on Development and Learning (2009)

In developmental research, tutoring behavior has been identified as scaffolding infants' learning processes. It has been defined in terms of child-directed speech (Motherese), child-directed motion (Motionese), and contingency. In the field of developmental robotics, research often assumes that in human-robot interaction (HRI), robots are treated similar to infants, because their immature cognitive capabilities benefit from this behavior. However, according to our knowledge, it has barely been studied whether this is true and how exactly humans alter their behavior towards a robotic interaction partner. In this paper, we present results concerning the acceptance of a robotic agent in a social learning scenario obtained via comparison to adults and 8-11 months old infants in equal conditions. These results constitute an important empirical basis for making use of tutoring behavior in social robotics. In our study, we performed a detailed multimodal analysis of HRI in a tutoring situation using the example of a robot simulation equipped with a bottom-up saliency-based attention model [1]. Our results reveal significant differences in hand movement velocity, motion pauses, range of motion, and eye gaze suggesting that for example adults decrease their hand movement velocity in an Adult-Child Interaction (ACI), opposed to an Adult-Adult Interaction (AAI) and this decrease is even higher in the Adult-Robot Interaction (ARI). We also found important differences between ACI and ARI in how the behavior is modified over time as the interaction unfolds. These findings indicate the necessity of integrating top-down feedback structures into a bottom-up system for robots to be fully accepted as interaction partners.
Automatic inference of the temporal location of situations in Chinese text
Authors: Nianwen Xue
Venue: Proceedings of the Conference on Empirical Methods in Natural Language Processing (2008)

Chinese is a language that does not have morphological tense markers that provide explicit grammaticalization of the temporal location of situations (events or states). However, in many NLP applications such as Machine Translation, Information Extraction and Question Answering, it is desirable to make the temporal location of the situations explicit. We describe a machine learning framework where different sources of information can be combined to predict the temporal location of situations in Chinese text. Our experiments show that this approach significantly outperforms the most frequent tense baseline. More importantly, the high training accuracy shows promise that this challenging problem is solvable to a level where it can be used in practical NLP applications with more training data, better modeling techniques and more informative and generalizable features.
User Experience in Machinery Automation: From Concepts and Context to Design Implications
Authors: Jarmo Palviainen, Kaisa Väänänen-Vainio-Mattila
Venue: Proceedings of the 1st International Conference on Human Centered Design: Held as Part of HCI International 2009 (2009)

Machinery automation (MA), e.g. different agriculture machinery, has traditionally been developed by experts in automation and in machinery engineering. As the role of interactive software is increasing, the principles and methods of human centered design (HCD) are being applied. This results in better usability of the systems particularly through efficiency of work processes and user interfaces (UIs). The user experience (UX) approach extends the HCD approach with broader motivational factors of using the systems. This paper describes the elements of UX in the MA from the interaction design perspective. After introducing the UX field, we describe the context to give an overview of the major factors affecting UX. Then we present what we consider to be the key elements of UX in MA and what implications they bring to the design of such systems. Finally we discuss the benefits and challenges of applying UX in this particular field.