ppxscal/embedding_network huggingface dataset:
High-Performance Tsunami Wave Propagation Modeling
Authors: Mikhail Lavrentiev-Jr, Alexey Romanenko, Vasily Titov, Alexander Vazhenin
Venue: Proceedings of the 10th International Conference on Parallel Computing Technologies (2009)

Strongest earthquake of December 26, 2004 generated catastrophic tsunami in Indian Ocean. This shows that, in spite of recent technology progress, population at coastal zone is not protected against tsunami hazard. Here, we address the problem of tsunami risks mitigation. Note that prediction of tsunami wave parameters at certain locations should be made as early as possible to provide enough time for evacuation. Modern computational technologies can accurately calculate tsunami wave propagation over the deep ocean provided that initial displacement (perturbation of the sea bed at tsunami source) is known. Modern deep ocean tsunameters provide direct measurement of the passing tsunami wave in real time, which help to estimate initial displacement parameters right after the tsunami wave is recorded at one of the deep ocean buoys. Therefore, fast tsunami propagation code that can calculate tsunami evolution from estimated model source becomes critical for timely evacuation decision for many coastal communities in case of a strong tsunami. Numerical simulation of tsunami wave is very important task for risk evaluation, assessment and mitigation. Here we discuss a part of MOST (Method of Splitting Tsunami) software package, which has been accepted by the USA National Ocean and Atmosphere Administration as the basic tool to calculate tsunami wave propagation and evaluation of inundation parameters. Our main objectives are speed up the sequential program, and adaptation of this program for shared memory systems (OpenMP) and CELL architecture. Optimization of the existing parallel and sequential code for the task of tsunami wave propagation modeling as well as an adaptation of this code for systems based on CELL BE processors (e.g. SONY PlayStation3) is discussed. The paper also covers approaches and techniques for programs optimization and adaptations, and obtained results.
New Neuron Model for Blind Source Separation
Authors: Md. Shiblee, B. Chandra, P. K. Kalra
Venue: Advances in Neuro-Information Processing: 15th International Conference, ICONIP 2008, Auckland, New Zealand, November 25-28, 2008, Revised Selected Papers, Part II (2009)

The paper proposes new neuron model with an aggregation function based on Generalized harmonic mean of the inputs. Information-maximization approach has been used for training the new neuron model. The paper focuss on illustrating the efficiency of the proposed neuron model for blind source separation. It has been shown on various generated mixtures (for blind source separation) that the new neuron model performs far superior compared to the conventional neuron model.
Short communication: An integrated modelling approach for the assessment of land use change effects on wastewater infrastructures
Authors: Angelo Doglioni, Francesca Primativo, Daniele Laucelli, Valeria Monno, Soon-Thiam Khu, Orazio Giustolisi
Venue: Environmental Modelling Software (2009)

The simulation of sewage systems and wastewater treatment plants is strategic for assessing the effect of new dwellings on the existing water facilities. This paper introduces an integrated framework made by a land use change model, a sewage system simulator, and a wastewater treatment plant simulator. This is a complex system since each element is characterized by different dynamics. The land use change model simulates the annual expansion of an urban area according to planners' guidelines; the sewage system simulator investigates the response of the drainage system to the expansion. The wastewater treatment plant is simulated in order to assess the impact of the new outflows on the existing plant. The three models are integrated into a Simulink model. Two components of the developed framework are based on models well established in literature. The proposed framework is tested on a simple case study of a small town located in south west of Scotland.
Modeling of Hybrid-service in Broadband Wireless Communication System
Authors: Xiaowei Qin, Leixin Mai, Xuchu Dai
Venue: Proceedings of the 2009 Eigth IEEE/ACIS International Conference on Computer and Information Science (2009)

Wireless mobile communication has evolved from 2G to 3G and B3G，and the advent of many new services raises the need to construct the service model. Since traffics in broadband networks are often the mixture of different services, modeling of hybrid-service is very important for network planning, performance evaluation and resource management. However, most of the existing study on service model is mainly focused on single service model. This paper presents an investigation of state of arts in hybrid-service modeling, and some research challenges are also discussed, with an objective to hope to find some feasible ways for further research of hybrid-service modeling.
OntoNotes: the 90% solution
Authors: Sameer S. Pradhan, Nianwen Xue
Venue: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Tutorial Abstracts (2009)

OntoNotes is a five year multi-site collaboration between BBN Technologies, Information Sciences Institute of University of Southern California, University of Colorado, University of Pennsylvania and Brandeis University. The goal of the OntoNotes project is to provide linguistic data annotated with a skeletal representation of the literal meaning of sentences including syntactic parse, predicate-argument structure, coreference, and word senses linked to an ontology, allowing a new generation of language understanding technologies to be developed with new functional capabilities.
Optimal Allocation of Water Resources Based on Differential Evolution Algorithm
Authors: Feipeng Xiao, Weijun Huang, Zhang Zhigang
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 01 (2009)

Differential evolution (DE), a population-based multi-objective evolutionary algorithm, steers optimization search through swarm intelligence produced by co-operation and competition among individuals within the swarm. With its unique memory ability, DE can track the dynamics of the current search, adjust its search strategy accordingly, and achieve good global convergence and robustness without resorting to any information characteristic of the problem in question. DE proves exceptionally useful in solving complex optimization problems which cannot be solved by conventional mathematical programming methods. This paper applies DE to the multi-objective optimal allocation of water resources, treats the optimal allocation of water resources as a simulated biological evolution process, and conducts an optimal computation in a case study, which shows that the result of DE is both reasonable and efficient.
Using linguistically motivated features for paragraph boundary identification
Authors: Katja Filippova, Michael Strube
Venue: Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing (2006)

In this paper we propose a machine-learning approach to paragraph boundary identification which utilizes linguistically motivated features. We investigate the relation between paragraph boundaries and discourse cues, pronominalization and information structure. We test our algorithm on German data and report improvements over three baselines including a reimplementation of Sporleder & Lapata's (2006) work on paragraph segmentation. An analysis of the features' contribution suggests an interpretation of what paragraph boundaries indicate and what they depend on.
Research and Application of Self-Adaptive Fuzzy Control in the Negative Pressure Isolation Ward Control System
Authors: Zhi-jun Li, Jing-hua Wang, Ke-yu Shen, Jia Yang, Jin-lu Lin
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 01 (2009)

In this paper, aimed at the negative pressure isolation ward with the characteristics of multiple variables, strong coupling and instability, according to the research of latest isolation environmental air current structure and based on the conventional PID control, this paper uses fuzzy inference to achieve the parameters of PID on-line adaptive setting, so that the control of negative pressure isolation ward can achieve the satisfactory control.
Effects of Design Elements in Magazine Advertisements
Authors: Young Sam Ryu, Taewon Suh, Sean Dozier
Venue: Proceedings of the 8th International Conference on Engineering Psychology and Cognitive Ergonomics: Held as Part of HCI International 2009 (2009)

In this study, unlike previous studies where participants were instructed to pay attention to the advertisements, we set up a more naturalistic situation of reading magazine. Five major design elements (body text, head text, brand logo, product image, and human model image) were investigated and our results showed pictorial elements captured more looking time and fixations than textual elements in general and textual elements received more looking time and fixations per unit size than pictorial elements. Also, a comparative data analysis of two different but very similar advertisements of competing products provided design implications regarding the use of human model image and head text.
Honeycomb: Visual Analysis of Large Scale Social Networks
Authors: Frank Ham, Hans-Jörg Schulz, Joan M. Dimicco
Venue: Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part II (2009)

The rise in the use of social network sites allows us to collect large amounts of user reported data on social structures and analysis of this data could provide useful insights for many of the social sciences. This analysis is typically the domain of Social Network Analysis, and visualization of these structures often proves invaluable in understanding them. However, currently available visual analysis tools are not very well suited to handle the massive scale of this network data, and often resolve to displaying small ego networks or heavily abstracted networks. In this paper, we present Honeycomb, a visualization tool that is able to deal with much larger scale data (with millions of connections), which we illustrate by using a large scale corporate social networking site as an example. Additionally, we introduce a new probability based network metric to guide users to potentially interesting or anomalous patterns and discuss lessons learned during design and implementation.
Is bagging effective in the classification of small-sample genomic and proteomic data?
Authors: T. T. Vu, U. M. Braga-Neto
Venue: EURASIP Journal on Bioinformatics and Systems Biology (2009)

There has been considerable interest recently in the application of bagging in the classification of both gene-expression data and protein-abundance mass spectrometry data. The approach is often justified by the improvement it produces on the performance of unstable, overfitting classification rules under small-sample situations. However, the question of real practical interest is whether the ensemble scheme will improve performance of those classifiers sufficiently to beat the performance of single stable, nonoverfitting classifiers, in the case of small-sample genomic and proteomic data sets. To investigate that question, we conducted a detailed empirical study, using publicly-available data sets from published genomic and proteomic studies. We observed that, under t-test and RELIEF filter-based feature selection, bagging generally does a good job of improving the performance of unstable, overfitting classifiers, such as CART decision trees and neural networks, but that improvement was not sufficient to beat the performance of single stable, nonoverfitting classifiers, such as diagonal and plain linear discriminant analysis, or 3-nearest neighbors. Furthermore, as expected, the ensemble method did not improve the performance of these classifiers significantly. Representative experimental results are presented and discussed in this work.
A CRT-Based Solution to Yao's Millionaires' Problem
Authors: Sorin Iftene, Daniel Pasaila
Venue: Proceedings of the 2008 10th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (2008)

We propose a simple solution to Yao's millionaires' problem using thesubtractive homomorphic properties of the secret sharing schemes based on the Chinese remainder theorem (CRT).
Virtual Scene Dynamic Control In the Manner of Internal Control Mode
Authors: Duan Xinyu, Sui Dan
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 01 (2009)

Analysis by synthesis, there are two kinds of methods to implement virtual scene dynamic control, whether in the manner of external control mode or in the manner of internal control mode. In order to satisfy the requirement of real-time data input and output for peripheral equipment system, it is strongly demanded to adopt scene external control mode. When just need simply change scene’s dynamic effect, we can employ VRML’s embedded Script node. Paper mainly discussed VRML’s internal event driving mode to realize mutual interaction control between user and virtual scene. Script node is in fact a shell. It embodies a group of function and method which are programmed by some script describing language. As soon as Script node receiving an event, it will execute a relevant function, and then dispatch event through routine Route mechanism. Script also can dynamically add or delete Routes, so as to modify event’s topology structure of virtual scene system.
Lookahead Expansion Algorithm for Minimum Power Multicasting in Wireless Ad Hoc Networks
Authors: Manki Min, Austin F. O'Brien
Venue: Proceedings of the 4th International Conference on Wireless Algorithms, Systems, and Applications (2009)

In this paper, we present a lookahead expansion algorithm (named as Shrinking and Lookahead Expansion, SLE for short) for minimum power multicast tree problem in wireless ad hoc networks. SLE adopts the powerful shrinking process from our previous work, SOR (Shrinking Overlapped Range) algorithm, and adds an intelligent lookahead process to further improve the solution quality. The lookahead process (called as lookahead expansion) expands the intermediate tree to a feasible tree by adding transmissions with minimum power, one by one. The algorithm maintains the found feasible tree with the minimum power sum in addition to the intermediate tree which is not feasible until the end. This lookahead process generates the effective diversification of the solution search space. The computational results strongly support the solid and outstanding performance of SLE owing to the lookahead process.
Selecting highly optimal architectural feature sets with Filtered Cartesian Flattening
Authors: Jules White, Brian Dougherty, Douglas C. Schmidt
Venue: Journal of Systems and Software (2009)

Feature modeling is a common method used to capture the variability in a configurable application. A key challenge developers face when using a feature model is determining how to select a set of features for a variant that simultaneously satisfy a series of resource constraints. This paper presents an approximation technique for selecting highly optimal feature sets while adhering to resource limits. The paper provides the following contributions to configuring application variants from feature models: (1) we provide a polynomial time approximation algorithm for selecting a highly optimal set of features that adheres to a set of resource constraints, (2) we show how this algorithm can incorporate complex configuration constraints; and (3) we present empirical results showing that the approximation algorithm can be used to derive feature sets that are more than 90%+ optimal.
Cross-modal clustering
Authors: Michael H. Coen
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 2 (2005)

This paper presents a self-supervised algorithm for learning perceptual structures based upon correlations in different sensory modalities. The brain and cognitive sciences have gathered an enormous body of neurological and phenomenological evidence in the past half century that demonstrates the extraordinary degree of interaction between sensory modalities during the course of ordinary perception. This paper presents a new framework for creating artificial perceptual systems inspired by these findings, where the primary architectural motif is the cross-modal transmission of perceptual information to enhance each sensory channel individually. The basic hypothesis underlying this approach is that the world has regularities - natural laws tend to correlate physical properties - and biological perceptory systems have evolved to take advantage of this. They share information continually and opportunistically across seemingly disparate perceptual channels, not epiphenomenologically, but rather as a fundamental component of normal perception. It is therefore essential that their artificial counterparts be able to share information synergistically within their perceptual channels, if they are to approach degrees of biological sophistication. This paper is a preliminary step in that direction.
Fundamental Studies on Effective e-Learning Using Physiology Indices
Authors: Miki Shibukawa, Mariko Funada, Yoshihide Igarashi, Satoki P. Ninomija
Venue: Proceedings of the 1st International Conference on Human Centered Design: Held as Part of HCI International 2009 (2009)

In order to apply individual learning methods to an e-learning system, we need some appropriate measures to know the quantitative evaluation for the learning progress of each individual. The ratio of the number of correct answers to the number of questions is a simple measure of the achievement of the learner. However, such a simple measure may not accurately reflect the real progress of the learner. Event Related Potentials (ERPs for short) are measured from electroencephalograms (EEGs for short). We consider that ERPs may contain meaningful information about the level of the learner's achievement. We had experiments measuring ERPs of subjects learning chemical formulae on an e-learning system. We try to characterize the relation among the learner's achievement, hardness of learning, and the waveforms of his ERPs. This kind of characterizations may be useful for evaluating the learner's achievement.
TileProbe
Authors: Jennifer Toolan Judy, Hongkai Ji
Venue: Bioinformatics (2009)

Motivation: Individual probes on an Affymetrix tiling array usually behave differently. Modeling and removing these probe effects are critical for detecting signals from the array data. Current data processing techniques either require control samples or use probe sequences to model probe-specific variability, such as with MAT. Although the MAT approach can be applied without control samples, residual probe effects continue to distort the true biological signals. Results: We propose TileProbe, a new technique that builds upon the MAT algorithm by incorporating publicly available data sets to remove tiling array probe effects. By using a large number of these readily available arrays, TileProbe robustly models the residual probe effects that MAT model cannot explain. When applied to analyzing ChIP-chip data, TileProbe performs consistently better than MAT across a variety of analytical conditions. This shows that TileProbe resolves the issue of probe-specific effects more completely. Availability: http://www.biostat.jhsph.edu/~hji/cisgenome/index_files/tileprobe.htm Contact: hji@jhsph.edu Supplementary information:Supplementary data are available at Bioinformatics online.
Design and Implementation of Web Service Based Intelligent Mobile Guidance System
Authors: Zhizheng Zhou, Chaochao Zhang, Shuming Jiang, Zhihui Li, Ling Bai
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 03 (2009)

This article, to meet the current demand for individual traveling, explores the design of an embedded Web service intelligent guidance system, which takes full advantage of the insert system design technology and GIS technology, providing travelers with accompanied tourism service at any time anywhere through the web service.
Strong and uniform equivalence in answer-set programming: characterizations and complexity results for the non-ground case
Authors: Thomas Eiter, Michael Fink, Hans Tompits, Stefan Woltran
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 2 (2005)

Recent research in nonmonotonic logic programming under the answer-set semantics studies different notions of equivalence. In particular, strong and uniform equivalence are proposed as useful tools for optimizing (parts of) a logic program. While previous research mainly addressed propositional (i.e., ground) programs, we deal here with the more general case of non-ground programs, and provide semantical characterizations capturing the essence of equivalence, generalizing the concepts of SE-models and UE-models, respectively, as originally introduced for propositional programs. We show that uniform equivalence is undecidable, and we give decidability results and precise complexity bounds for strong equivalence (thereby correcting a previous complexity bound for strong equivalence from the literature) as well as for uniform equivalence for finite vocabularies.
An Empirical Study on the Performance Issues on the Clustered Client-Server Computing Environment
Authors: Yu-Hung Hsiao, Han-Jyun Su
Venue: Proceedings of the 9th International Conference on Algorithms and Architectures for Parallel Processing (2009)

In this paper, the performance of four computation models applied on a clustered computing environment is studied. A 3-tiered client-server architecture model is used as the baseline architecture for the study. An experimental cluster, using the off-the-shelf hardware and software components, was built and used to conduct the performance evaluations. The queries used in the study can be extended to numerous real-life applications. Hence the contribution of this study is mainly empirical, especially for those applications that have the similar settings. The alternative Multiple Application Servers, Multiple Database Servers (MAMDA) computation model which implements the application servers and database servers on the same PCs provides the best performance speedup, keeping the efficiency greater than or equal to 0.9.
The Research of the Non-uniformity in Land Use Map Patches and Image Segments
Authors: Yan Wang, Ning Shu, Xue Li
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 02 (2009)

Using multi-resource datasets to analyze remote sensing images is one of the focuses in the field of remote sensing image analysis. However, this technological theory is usually difficult to achieve due to the different structure and data standard of multi-resource datasets. This paper proposes a method which tries to analyze and solve the problem of the non uniformity in land use map patches and image segments. Image segments are obtained directly by matching land use map and images then sub segments are gotten by reclassifying image segments using supervised classification. Relations between land use map classes and sub segments are found by decision tree and then non uniformity of them could be resolved. The method used in this paper has to be considered prior to its operational use in analyzing land use map and Quickbird images in the region of Wuhan City in China.