ppxscal/embedding_network huggingface dataset:
A probabilistic neural network for earthquake magnitude prediction
Authors: Hojjat Adeli, Ashif Panakkat
Venue: Neural Networks (2009)

A probabilistic neural network (PNN) is presented for predicting the magnitude of the largest earthquake in a pre-defined future time period in a seismic region using eight mathematically computed parameters known as seismicity indicators. The indicators considered are the time elapsed during a particular number (n) of significant seismic events before the month in question, the slope of the Gutenberg-Richter inverse power law curve for the n events, the mean square deviation about the regression line based on the Gutenberg-Richter inverse power law for the n events, the average magnitude of the last n events, the difference between the observed maximum magnitude among the last n events and that expected through the Gutenberg-Richter relationship known as the magnitude deficit, the rate of square root of seismic energy released during the n events, the mean time or period between characteristic events, and the coefficient of variation of the mean time. Prediction accuracies of the model are evaluated using three different statistical measures: the probability of detection, the false alarm ratio, and the true skill score or R score. The PNN model is trained and tested using data for the Southern California region. The model yields good prediction accuracies for earthquakes of magnitude between 4.5 and 6.0. The PNN model presented in this paper complements the recurrent neural network model developed by the authors previously, where good results were reported for predicting earthquakes with magnitude greater than 6.0.
Wrapper maintenance: a machine learning approach
Authors: Kristina Lerman, Steven N. Minton, Craig A. Knoblock
Venue: Journal of Artificial Intelligence Research (2003)

The proliferation of online information sources has led to an increased use of wrappers for extracting data from Web sources. While most of the previous research has focused on quick and efficient generation of wrappers, the development of tools for wrapper maintenance has received less attention. This is an important research problem because Web sources often change in ways that prevent the wrappers from extracting data correctly. We present an efficient algorithm that learns structural information about data from positive examples alone. We describe how this information can be used for two wrapper maintenance applications: wrapper verification and reinduction. The wrapper verification system detects when a wrapper is not extracting correct data, usually because the Web source has changed its format. The reinduction algorithm automatically recovers from changes in the Web source by identifying data on Web pages so that a new wrapper may be generated for this source. To validate our approach, we monitored 27 wrappers over a period of a year. The verification algorithm correctly discovered 35 of the 37 wrapper changes, and made 16 mistakes, resulting in precision of 0.73 and recall of 0.95. We validated the reinduction algorithm on ten Web sources. We were able to successfully reinduce the wrappers, obtaining precision and recall values of 0.90 and 0.80 on the data extraction task.
A Virtual Environment for Learning Aiport Emergency Management Protocols
Authors: Telmo Zarraonandia, Mario Rafael Vargas, Paloma Díaz, Ignacio Aedo
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part III: Ubiquitous and Intelligent Interaction (2009)

This paper presents a virtual environment designed to enhance the learning of airport emergency management protocols. The learning is performed in an informal manner, with each learner playing a different role in a particular emergency simulation. Learners interact within the virtual environment, managing the available information and following the steps prescribed for each type of emergency in the Airport Emergency Plan of the Spanish Civil Defence Organization. The simulation can be run in different modes of difficulty, and can be used as a learning tool as well as an evaluation tool to measure the accuracy of the learner's actuation within the protocol. It can also support stand-alone training having some of the emergency roles played out by the computer. The virtual environment has been built using DimensioneX, an open source multi-player online game engine.
Parameter Determination of Dynamic Sensor Model with Particle Swarm Optimization Technique
Authors: Xiaodong Wang
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 01 (2009)

An accurate mathematical model is a useful tool for analysis and design of sensor systems. In this paper, a novel approach based on particle swarm optimization (PSO) is applied to determine the parameters of dynamic sensor model. A hot-film mass airflow (MAF) sensor, which is used to measure the intake mass airflow in the engine systems of automobile, has been used as a simulation example for demonstration. The results indicate that the PSO is an effective technique for determining the parameters of dynamic sensor models.
Impact on Performance and Process by a Social Annotation System: A Social Reading Experiment
Authors: Les Nelson, Gregorio Convertino, Peter Pirolli, Lichan Hong, Ed H. Chi
Venue: Proceedings of the 5th International Conference on Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience: Held as Part of HCI International 2009 (2009)

Social annotation systems such as SparTag.us and del.icio.us have been designed to encourage individual reading and marking behaviors that, when shared, accumulate to build collective knowledge spaces. Prior work reported on the experimental design and performance effects observed in a controlled study of SparTag.us. Study participants working independently on a sensemaking task who had access to a set of expert annotations were compared against participants using SparTag.us without those annotations and participants using only office software for annotation support. A learning effect favored the participants exposed to expert annotations. In this paper, we analyze the behavioral data captured during the experiment and identify differences in the work process that can explain the performance effects reported previously.
A Statistical and Iterative Method for Data Hiding in Palette-Based Images
Authors: Semin Kim, Wesley Neve, Yong Man Ro
Venue: Proceedings of the 8th International Workshop on Digital Watermarking (2009)

This paper proposes an improved iterative method for data hiding in palette-based images, taking into account the statistics of the data that need to be embedded in an image. In particular, the proposed method considers the distribution of the number of zeroes and ones in the input message, as well as how the message bits are distributed over the colors in the image palette. First, according to the statistics of the input message, the proposed method modifies the pixel indexes and the color palette using an enhanced version of an iterative image pre-processing method, replacing less frequent colors by colors that are close to frequently used colors. In a next step, the actual message bits are embedded into the parity bits of the remaining colors. Finally, the proposed method applies a post-processing step, adjusting particular colors in order to further reduce the amount of image distortion. Experimental results show that the proposed method preserves image quality better than previously proposed techniques for data hiding in palette-based images.
Logical properties of foundational mereogeometrical relations in bio-ontologies
Authors: Thomas Bittner
Venue: Applied Ontology (2009)

One aim of this paper is to improve the logical and ontological rigor of the OBO relation ontology by providing axiomatic specifications for logical properties of relations such as part_of, located_in, connected_to, adjacent_to, attached_to, etc. All of these relations are currently only loosely specified in OBO. A second aim is to improve the expressive power of the relation ontology by including axiomatic characterizations of qualitative size relations such as (roughly-the-) same-size-as, negligible-in-size-with-respect-to, same-scale, etc. These relations are important for comparing anatomical entities in a way that is compatible with the normal variations of their geometric properties. Moreover, qualitative size relations are important for distinguishing anatomical entities at different scales. Unfortunately, the formal treatment of these relations is difficult due to their context-dependent nature and their inherent vagueness. This paper presents a formalization that facilitates the separation of ontological aspects that are context-independent and non-vague from aspects that are context-dependent and subject to vagueness. A third aim is to explicitly take into account the specific temporal properties of all of the relations and to provide a formalization that can be used as a basis for the formal representation of canonical anatomy as well as of instantiated anatomy. All the relations and their properties are illustrated informally using a human synovial joint as a running example. At the formal level the axiomatic theory is developed using Isabelle, a computational system for implementing logical formalisms. All proofs are computer-verified and the computational representation of the theory is accessible on http://www.ifomis.org/bfo/fol.
Study on Automotive Anti-collision Radar System and Its Signal Processing Algorithm
Authors: Wu Yurong, Wang Congling, Li Xunbo, Zhou Chen
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 01 (2009)

Through analyzing the applied require for millimeter wave automotive anti-collision radar, we design the simple structure of radar system. For satisfying the demands of digital signal processing and dispatching affairs, the signal processor is designed by linking DSP and SCM. Considering the complexity of radar signal received, high efficient digital signal processing algorithms should be applied to radar. Useful targets can be detected in clutter through self-adaptive filtering, and the targets' distance/velocity can be measured through frequency domain pairing. So we introduce a signal processing algorithm through combining self-adaptive filtering with frequency domain pairing in order to get the targets' accurate distance/velocity information in clutter and multi-targets environment, and simulate the algorithm by computer. The simulation results prove that this algorithm is effective.
On the Optimality of Gluing over Scales
Authors: Alex Jaffe, James R. Lee, Mohammad Moharrami
Venue: Proceedings of the 12th International Workshop and 13th International Workshop on Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (2009)

We show that for every ¿> 0, there exist n-point metric spaces (X,d) where every "scale" admits a Euclidean embedding with distortion at most ¿, but the whole space requires distortion at least $\Omega(\sqrt{\alpha \log n})$. This shows that the scale-gluing lemma [Lee, SODA 2005] is tight, and disproves a conjecture stated there. This matching upper bound was known to be tight at both endpoints, i.e. when ¿ = ¿(1) and ¿ = ¿(logn), but nowhere in between.More specifically, we exhibit n-point spaces with doubling constant ¿ requiring Euclidean distortion $\Omega(\sqrt{\log \lambda \log n})$, which also shows that the technique of "measured descent" [Krauthgamer, et. al., Geometric and Functional Analysis] is optimal. We extend this to L p spaces with p > 1, where one requires distortion at least ¿((logn)1/q (log¿)1 ¿ 1/q ) when q = max {p,2}, a result which is tight for every p > 1.
An efficient motion planning algorithm for stochastic dynamic systems with constraints on probability of failure
Authors: Masahiro Ono, Brian C. Williams
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 3 (2008)

When controlling dynamic systems, such as mobile robots in uncertain environments, there is a trade off between risk and reward. For example, a race car can turn a corner faster by taking a more challenging path. This paper proposes a new approach to planning a control sequence with a guaranteed risk bound. Given a stochastic dynamic model, the problem is to find a control sequence that optimizes a performance metric, while satisfying chance constraints i.e. constraints on the upper bound of the probability of failure. We propose a two-stage optimization approach, with the upper stage optimizing the risk allocation and the lower stage calculating the optimal control sequence that maximizes reward. In general, the upper-stage is a non-convex optimization problem, which is hard to solve. We develop a new iterative algorithm for this stage that efficiently computes the risk allocation with a small penalty to optimality. The algorithm is implemented and tested on the autonomous underwater vehicle (AUV) depth planning problem, and demonstrates a substantial improvement in computation cost and suboptimality, compared to the prior arts.
Evolution of ubiquitous autonomous agents
Authors: Jason C. Hung, Han-Bin Chang, Hsuan-Pu Chang, Yu-Hsin Cheng, Kuo-Yen Lo
Venue: International Journal of Ad Hoc and Ubiquitous Computing (2009)

Ubiquitous researches had been done recently. With the development of cellular phones and internet, these individualised programs exist in the digital world where a new ecosystem can be formed. Competition and collaboration thus exists among different groups of autonomous entities. We propose a model like food web exists in natural world and serves as a balancing algorithm among different types of species. We define the food web model and propose algorithms for formation and communication. The proposed model can be used to consider the development of intelligent strategies and the underlying communication topology such that ubiquitous intelligences can be evolved on the digital food web.
An Information Driven Sensornet Architecture
Authors: Eli De Poorter, Ingrid Moerman, Piet Demeester
Venue: Proceedings of the 2009 Third International Conference on Sensor Technologies and Applications (2009)

Most sensor networks do not support QoS or heterogeneity. As a result, current sensor networks are not suited for next-generation applications, such as wireless building automation, process control or medical applications. In this paper, we present an alternative architecture wherein the system is responsible for packet creation and packet manipulation. To support QoS, energy-efficiency and heterogeneity, the system intelligently combines information exchanges from multiple network protocols in a single packet. We demonstrate that this approach is better suited for very demanding applications and prove that this approach is much more scalable, in terms of memory requirements, than tradition system architectures.
Collusion-Free Multiparty Computation in the Mediated Model
Authors: Joël Alwen, Jonathan Katz, Yehuda Lindell, Giuseppe Persiano, Abhi Shelat, Ivan Visconti
Venue: Proceedings of the 29th Annual International Cryptology Conference on Advances in Cryptology (2009)

Collusion-free protocols prevent subliminal communication (i.e., covert channels) between parties running the protocol. In the standard communication model, if one-way functions exist, then protocols satisfying any reasonable degree of privacy cannot be collusion-free. To circumvent this impossibility, Alwen, shelat and Visconti (CRYPTO 2008) recently suggested the mediated model where all communication passes through a mediator. The goal is to design protocols where collusion-freeness is guaranteed as long as the mediator is honest, while standard security guarantees hold if the mediator is dishonest. In this model, they gave constructions of collusion-free protocols for commitments and zero-knowledge proofs in the two-party setting.We strengthen the definition of Alwen et al., and resolve the main open questions in this area by showing a collusion-free protocol (in the mediated model) for computing any multi-party functionality.
Spatial Statistics for Tumor Cell Counting and Classification
Authors: Oliver Wirjadi, Yoo-Jin Kim, Thomas Breuel
Venue: Proceedings of the 31st DAGM Symposium on Pattern Recognition (2009)

To count and classify cells in histological sections is a standard task in histology. One example is the grading of meningiomas, benign tumors of the meninges, which requires to assess the fraction of proliferating cells in an image. As this process is very time consuming when performed manually, automation is required. To address such problems, we propose a novel application of Markov point process methods in computer vision, leading to algorithms for computing the locations of circular objects in images. In contrast to previous algorithms using such spatial statistics methods in image analysis, the present one is fully trainable. This is achieved by combining point process methods with statistical classifiers. Using simulated data, the method proposed in this paper will be shown to be more accurate and more robust to noise than standard image processing methods. On the publicly available SIMCEP benchmark for cell image analysis algorithms, the cell count performance of the present paper is significantly more accurate than results published elsewhere, especially when cells form dense clusters. Furthermore, the proposed system performs as well as a state-of-the-art algorithm for the computer-aided histological grading of meningiomas when combined with a simple k-nearest neighbor classifier for identifying proliferating cells.
HITS Can Converge Slowly, but Not Too Slowly, in Score and Rank
Authors: Enoch Peserico, Luca Pretto
Venue: Proceedings of the 15th Annual International Conference on Computing and Combinatorics (2009)

This paper explores the fundamental question of how many iterations the celebrated HITS algorithm requires on a general graph to converge in score and, perhaps more importantly, in rank (i.e. to "get right" the order of the nodes). We prove upper and almost matching lower bounds. We also extend our results to weighted graphs.
XQSuggest: An Interactive XML Keyword Search System
Authors: Jiang Li, Junhu Wang
Venue: Proceedings of the 20th International Conference on Database and Expert Systems Applications (2009)

Query suggestion is extensively used in web search engines to suggest relevant queries, which can help users better express their information needs. In this paper, we explore the application of query suggestion in xml keyword search and propose a novel interactive xml query system XQSuggest, which mainly targets non-professional users who roughly know the contents of the database. Our system extends conventional keyword search systems by instantly suggesting several understandable semantic strings after each keyword is typed in, so that the users can easily select their desired semantic string, which represents a specific meaning of the keyword, to replace the ambiguous keyword. We provide a novel algorithm to compute the final results. Experimental results are provided to verify the better effectiveness of our system.
A Grid Implementation of Chimere: Ozone Production in Central Italy
Authors: Antonio Laganà, Stefano Crocchianti, Alessandro Costantini, Monica Angelucci, Marco Vecchiocattivi
Venue: Proceedings of the International Conference on Computational Science and Its Applications: Part II (2009)

A multiscale tridimensional Chemistry and Transport Model (Chimere) has been implemented on two very different scalable cluster. Its input was generated by specific interfaces built by the authors, adaptating meteo, emissions and boundary conditions data provided by different agencies to the needs of the Model. A prototype grid implementation on a segment of the EGEE Grid has been performed. Preliminary results of an application to the Umbria Region ozone production are also presented.
A LabVIEW environment to compensate temperature-driven fluctuations in the signal from continuously running spring gravimeters
Authors: Bruno Andò, Daniele Carbone
Venue: Computers Geosciences (2009)

Environmental parameters can seriously affect the performances of continuously running spring gravimeters. Temperature is a primary interfering quantity and its effect must be reduced through algorithms implementing a suitable compensation scheme. Algorithms to reduce the signals coming from continuously running gravimeters for the effect of meteorological perturbations have been developed and implemented in tools running in offline-mode. Anyway, the need for ''on-the-fly'' processing emerges when the recorded signals are used for volcano monitoring purposes, since any information on the volcanic phenomena under development must be assessed immediately. In this paper the implementation, in a dedicated LabVIEW application, of an algorithm performing temperature reduction on gravity signals is discussed and features of the software's user interface are presented.
Evolutionary Algorithm of Port Based Location Routing Problem
Authors: Xiqun Chen, Qixin Shi, Runhua Qian, Xinmiao Yang
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 02 (2009)

Location Routing Problem (LRP) is a significant subject in logistics systems, and genetic algorithm can obtain the near optimum solutions of large scale nonlinear mixed integer programming models which are NP-hard in nature. In the process of algorithm design, two-dimensional chromosomes that satisfy constraints automatically and their corresponding genetic arithmetic operators are designed, such as selection, crossover, mutation of seeds, re-insert and so on. Three-layer process of genetic evolution is conducted and examined by a group of random experiments. This paper compares the precision, effectiveness and applicable scope between the proposed algorithm and current optimizing software. With increase number of variables and constrains, computing time and iterations of genetic algorithm increase almost linearly, while that of the current software LINGO present NP-hard. Results show the proposed genetic algorithm is effective and efficient in solving the LRP problem especially of large scale.
Black-hole-resistant ENADAIR-based routing protocol for Mobile Ad hoc Networks
Authors: Djamel Djenouri, Mohamed Bouamama, Othmane Mahmoudi
Venue: International Journal of Security and Networks (2009)

A new solution to enforce ENDAIRA against black-hole attacks is proposed in this paper. In black-hole attack the misbehaving node simply drops packets of the victim, supposed to be routed or forwarded by it. The proposal is a hybrid solution that considers both directed and broadcast control packets. It combines two different approaches, two-hop-ACK and the watchdog, to building a combined solution able to deal with both directed and broadcast packets. The main contribution is considering control packets, contrary to the current literature in the context of selfish nodes, where solutions only consider data packets. The proposed solution was used to enforce ENDAIRA, one of the most secure protocols. It enhances its security with respect to packet dropping. The solution was analysed and evaluated through an extensive simulation study.