ppxscal/embedding_network huggingface dataset:
Study on Genetic Algorithm Based on Schema Mutation and Its Performance Analysis
Authors: Fachao Li, Tingyu Zhang
Venue: Proceedings of the 2009 Second International Symposium on Electronic Commerce and Security - Volume 01 (2009)

Genetic algorithm (GA), as a kind of important intelligence computing tool, is a wide research content in the academic circle and the application domain now. In this paper, for the mutation operation of GA, by combining with the essential feature, we establish a genetic algorithm based on schema mutation (denoted by SM-GA, for short). Further, we discuss the global convergence of CM-GA by using the Markov chain theory, and analyze the performance of SM-GA through an example. All the results indicate that, SM-GA is higher than the ordinary binary code genetic algorithm (denoted by B2GA, for short) in convergence precision. There was no significant difference between SM-GA and B2GA in convergence time. SM-GA overcomes the problem that B2GA can not converge strongly to some extent.
Learning English through Serious Games --- Reflections on Teacher and Learner Performance
Authors: Bente Meyer
Venue: Proceedings of the 4th International Conference on E-Learning and Games: Learning by Playing. Game-based Education System Design and Development (2009)

In this paper I am exploring the challenges of designing game-based material for language learning as a specific field of competence. The empirical context of the paper is a project on Serious Games on a Global Market Place (2007-10) in which academics work with companies to explore, build and implement game prototypes. One aspect of this research consists in analysing and developing a design for learning English through serious games (www.mingoville.com) as well as exploring how this design is used and implemented in classroom teaching and learning. We studied the use of the platform in two classes with children aged 10-11. 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
Modeling Scalable SIMD DSPs in LISA
Authors: Peter Westermann, Hartmut Schröder
Venue: Proceedings of the 9th International Workshop on Embedded Computer Systems: Architectures, Modeling, and Simulation (2009)

Single instruction multiple data (SIMD) processing is an important technique for achieving high performance in applications with innate data level parallelism such as applications from the Software Defined Radio (SDR) domain. This paper investigates using the LISA 2.0 Language to facilitate the development of scalable SIMD digital signal processors (DSPs). Our work shows that limitations in LISA hinder the development of SIMD data paths; therefore, extensions to LISA that enable to generate a wide SIMD data path from a single scalar processing element have been introduced. Furthermore, generators for SIMD permutation networks with arbitrary SIMD widths have been implemented. The presented solution simplifies the development of scalable SIMD DSPs in LISA considerably.
From Random to Hierarchical Data through an Irregular Pyramidal Structure
Authors: Rimon Elias, Mohab Al Ashraf, Omar Aly
Venue: Proceedings of the 7th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition (2009)

This paper proposes to transform data scanned randomly in a well-defined space (e.g, Euclidean) along a hierarchical irregular pyramidal structure in an attempt reduce search time consumed querying these random data. Such a structure is built as a series of graphs with different resolutions. Levels are constructed and surviving cells are chosen following irregular irregular pyramidal rules and according to a proximity criterion among the space points under consideration. Experimental results show that using such a structure to query data can save considerable search time.
Application Research of Data Mining Architecture for Intelligent Decision
Authors: He YueShun, Ding QiuLin
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 01 (2009)

The large commercial transactions data implied lots of useful knowledge for business decisions, the hidden patterns and relationships could be found by data mining. This paper analyzed and pointed out the characteristics and the deficiency of the general architecture of the data mining, the general architecture of data mining was improved by the parallel processing technology and the results of data mining be saved. The parallel architecture of the data mining which made for business intelligence applications with the model storage was presented, and its characteristics were analyzed, the analysis showed that the parallel architecture of data mining has a possibility for business intelligence
Detection of Wheezes Using a Wearable Distributed Array of Microphones
Authors: Wee Ser, T. T. Zhang, Jufeng Yu, Jianmin Zhang
Venue: Proceedings of the 2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks (2009)

This paper presents a wheeze detection method that uses a distributed array of microphones and can be implemented as part of a wearable health monitoring system. In order to reduce the power consumption for the wearable system, the method has been developed to operate at a sampling rate of 1000Hz, instead of 8000Hz. In the design, we use two regular air conductive microphones and a bone conductive microphone to increase the accuracy of detection and make it robust against environmental noise. The two air-conductive microphones capture breathing sound while bone-conductive microphone is placed over the manubrium of the sternum in patients to record chest wall lung sound. The simulations are conducted using lung sounds from patients with wheezes and human subjects with no wheezes under different SNR conditions. The results show that the proposed method is robust against environmental noise and has good performance on wheeze detection. The approach has been implemented onto a PDA and tested with some real data.
Label segregation by remapping stereoscopic depth in far-field augmented reality
Authors: Stephen D. Peterson, Magnus Axholt, Stephen R. Ellis
Venue: Proceedings of the 7th IEEE/ACM International Symposium on Mixed and Augmented Reality (2008)

This paper describes a novel technique for segregating overlapping labels in stereoscopic see-through displays. The present study investigates the labeling of far-field objects, with distances ranging 100–120 m. At these distances the stereoscopic disparity difference between objects is below 1 arcmin, so labels rendered at the same distance as their corresponding objects appear as if on a flat layer in the display. This flattening is due to limitations of both display and human visual resolution. By remapping labels to pre-determined depth layers on the optical path between the observer and the labeled object, an interlayer disparity ranging from 5 to 20 arcmin can be achieved for 5 overlapping labels. The present study evaluates the impact of such depth separation of superimposed layers, and found that a 5 arcmin interlayer disparity yields a significantly lower response time, over 20% on average, in a visual search task compared to correctly registering labels and objects in depth. Notably the performance does not improve when doubling the interlayer disparity to 10 arcmin and, surprisingly, the performance degrades significantly when again doubling the interlayer disparity to 20 arcmin, approximating the performance in situations with no interlayer disparity. These results confirm that our technique can be used to segregate overlapping labels in the far visual field, without the cost associated with traditional label placement algorithms.
Regression analysis of multivariate recurrent event data with time-varying covariate effects
Authors: Liuquan Sun, Liang Zhu, Jianguo Sun
Venue: Journal of Multivariate Analysis (2009)

Recurrent event data occur in many fields and many approaches have been proposed for their analyses (Andersen et al. (1993) [1]; Cook and Lawless (2007) [3]). However, most of the available methods allow only time-independent covariate effects, and sometimes this may not be true. In this paper, we consider regression analysis of multivariate recurrent event data in which some covariate effects may be time-dependent. For the problem, we employ the marginal modeling approach and, especially, estimating equation-based inference procedures are developed. Both asymptotic and finite-sample properties of the proposed estimates are established and an illustrative example is provided.
Simple linear profiles monitoring in the presence of within profile autocorrelation
Authors: Paria Soleimani, Rassoul Noorossana, Amirhossein Amiri
Venue: Computers and Industrial Engineering (2009)

Quality of some processes or products can be characterized effectively by a function referred to as profile. Many studies have been done by researchers on the monitoring of simple linear profiles when the observations within each profile are uncorrelated. However, due to spatial autocorrelation or time collapse, this assumption is violated and leads to poor performance of the proposed control charts. In this paper, we consider a simple linear profile and assume that there is a first order autoregressive model between observations in each profile. Here, we specifically focus on phase II monitoring of simple linear regression. The effect of autocorrelation within the profiles is investigated on the estimate of regression parameters as well as the performance of control charts when the autocorrelation is overlooked. In addition, as a remedial measure, transformation of Y-values is used to eliminate the effect of autocorrelation. Four methods are discussed to monitor simple linear profiles and their performances are evaluated using average run length criterion. Finally, a case study in agriculture field is investigated.
Anomaly detection and spatio-temporal analysis of global climate system
Authors: Mahashweta Das, Srinivasan Parthasarathy
Venue: Proceedings of the Third International Workshop on Knowledge Discovery from Sensor Data (2009)

Knowledge discovery from temporal, spatial and spatio-temporal data is pivotal for understanding and predicting the behavior of Earth's ecosystem model. An important influence leaving its impact on the ecosystem is the global climate system. In this paper, the Earth Science data that we have analyzed consists of daily global air temperature and precipitation measurements, aggregated from heterogeneous sensors for fifty years (1950--1999). The enormous amount of data that is available for analysis requires employment of data mining techniques for discovering interesting patterns, detecting significant changes and extracting meaningful insights from the data. Our work considers the problem of detecting anomalous (abnormal or unexpected) behavior in the global climate system, discovering teleconnection patterns and providing consequential insights to the analysts.
The transition from web content accessibility guidelines 1.0 to 2.0: what this means for evaluation and repair
Authors: Grace Mbipom, Simon Harper
Venue: Proceedings of the 27th ACM international conference on Design of communication (2009)

Recently, the World Wide Web Consortium (W3C) upgraded its Web Content Accessibility Guidelines (WCAG) from version 1.0 to 2.0. WCAG 2.0 further encourages the design of accessible Web content, and has been put in place to address the limitations of the earlier version, WCAG 1.0. The new development requires that updates be made accordingly. One of the areas affected by the transition is automated Web content accessibility evaluation and repair. Since most Accessibility Evaluation and Repair Tools (AERTs) depend on guidelines to make suggestions about potential accessibility barriers and proffer repair solutions, existing tools have to be modified to accommodate the changes WCAG 2.0 brings. In particular, more techniques for performing automated Web content accessibility evaluation and repair are desirable. The heterogeneous nature of Web content which AERTs assess, calls for techniques of cross-disciplinary origin. In this paper, we discuss the implications of the transition for automated evaluation and repair. In addition, we present a meta-review of relevant techniques from related disciplines for the purpose of informing research that surrounds testing and repair techniques employed by AERTs.
Kinematic design optimization of a parallel ankle rehabilitation robot using modified genetic algorithm
Authors: Prashant Kumar Jamwal, Shengquan Xie, Kean C. Aw
Venue: Robotics and Autonomous Systems (2009)

Rehabilitation robotics is an evolving area of active research and recently novel mechanisms have been proposed to reinstate complex human movements. Parallel robots are of particular interest to researchers since they are rigid and can provide enough load capacity for human joint movements. This paper proposes a soft parallel robot (SPR) for ankle joint rehabilitation. Kinematic workspace analysis is carried out and the singularity criterion of the SPR's Jacobian matrix is used to define the feasible workspace. A global conditioning number (GCN) is defined using the Jacobian matrix as a performance index for the evaluation of the robot design. An optimization problem is formulated to minimize the GCN using modified genetic algorithm (GA). Results from simple GA and modified GA are compared and discussed. As a result of the optimization, an optimal robot design is obtained which has a near unity GCN with almost uniform distribution in the entire feasible workspace of the robot.
ASKNet: automated semantic knowledge network
Authors: Brian Harrington
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

The ASKNet project is an attempt to automatically generate semantic knowledge networks from natural language text. NLP tools such as parsers and semantic analysers are used to turn input sentences into fragments of semantic network, and these network fragments are combined using spreading activation algorithms that utilise both lexical and semantic information. The ultimate goal of the project is to create a semantic resource on a scale that has never before been possible.
Lessons Learned from a Workshop on Relationship Building
Authors: Jayakanth Srinivasan, Annika Lofgren, Christer Norstrom, Kristina Lundqvist
Venue: Proceedings of the 2009 Fourth IEEE International Conference on Global Software Engineering (2009)

Openness and trust are key elements to sustaining any successful client-supplier relationship. When the relationship is transitioning from being arms-length to evolving into a true partnership, it is critical to establish a shared understanding of not only the current state, but also of the expected future state. A workshop organized and facilitated by a neutral party, with the senior leadership of both organizations provides an ideal means for articulating implicit assumptions and surfacing hidden challenges such that an actionable vision can be created. Using a recent workshop held with both EuroTel and IndiaCo, the key elements of the workshop are discussed, along with the lessons learned. Moreover, this workshop provides further insight into the mechanics of the evolution and governance of outsourcing relationships.
Cancelable Iris Biometrics Using Block Re-mapping and Image Warping
Authors: Jutta Hämmerle-Uhl, Elias Pschernig, Andreas Uhl
Venue: Proceedings of the 12th International Conference on Information Security (2009)

The concept of cancelable biometrics provides a way to protect biometric templates. A possible technique to achieve such protection for iris images is to apply a repeatable, non-reversible transformation in the image domain prior to feature extraction. We applied two classical transformations, block re-mapping and texture warping, to iris textures obtained from the CASIA V3 Iris database and collected experimental results on the matching performance and key sensitivity of a popular iris recognition method.
"Art-sonomy": Social Bookmarking of Real Artworks via Mobile Applications with Visual Tags
Authors: Stefano Levialdi Ghiron, Carlo Maria Medaglia, Amedeo Perrone
Venue: Proceedings of the 5th International Conference on Universal Access in Human-Computer Interaction. Part III: Applications and Services (2009)

Tag-based indexing systems allow users to name web resources freely choosing keywords, called tags. Users (observers) may browse resources using a tag-cloud, a screen presentation that looks like an alphabetically ordered list of the most popular tags, visually weighted by font size. This project called Artsonomy, enables users to associate keywords (tags) to real artworks (for ex. in a museum) labeled with a QR Code by means of an application on a mobile device. The user's tags are collected in a tag-cloud on the Artsonomy website so enabling other obesrvers to share their experience after viewing an artwork.
Slacker semantics: why superficiality, dependency and avoidance of commitment can be the right way to go
Authors: Ann Copestake
Venue: Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics (2009)

This paper discusses computational compositional semantics from the perspective of grammar engineering, in the light of experience with the use of Minimal Recursion Semantics in DELPH-IN grammars. The relationship between argument indexation and semantic role labelling is explored and a semantic dependency notation (DMRS) is introduced.
On Random Ordering Constraints
Authors: Andreas Goerdt
Venue: Proceedings of the Fourth International Computer Science Symposium in Russia on Computer Science - Theory and Applications (2009)

Ordering constraints are analogous to instances of the satisfiability problem in conjunctive normalform, but instead of a boolean assignment we consider a linear ordering of the variables in question. A clause becomes true given a linear ordering iff the relative ordering of its variables obeys the constraint. The naturally arising satisfiability problems are NP-complete for many types of constraints.The present paper seems to be one of the first looking at random ordering constraints. Experimental evidence suggests threshold phenomena as in the case of random k-SAT instances. We prove first that random instances of the cyclic ordering and betweenness constraint have a sharp threshold for unsatisfiability. Second, random instances of the cyclic ordering constraint are satisfiable with high probability if the number of clauses is $\le 1 \times\,\, \sharp$variables.
Application of Dey-Mittra conformal boundary algorithm to 3D electromagnetic modeling
Authors: C. Nieter, John R. Cary, Gregory R. Werner, David N. Smithe, Peter H. Stoltz
Venue: Journal of Computational Physics (2009)

The Dey-Mittra conformal boundary conditions have been implemented for the finite-difference time-domain (FDTD) electromagnetic solver of the VORPAL plasma simulation framework and studied in the context of three-dimensional, large-scale computations. The maximum stable time step when using these boundary conditions can be arbitrarily small, due to the presence of small fractional cells inside the vacuum region. Use of the Gershgorin Circle theorem allows the determination of a rigorous criterion for exclusion of small cells in order to have numerical stability for particular values of the ratio f"D"M=@Dt/@Dt"C"F"L of the time step to the Courant-Friedrichs-Lewy value for the infinite system. Application to a spherical cavity shows that these boundary conditions allow computation of frequencies with second-order error for sufficiently small f"D"M. However, for sufficiently fine resolution, dependent on f"D"M, the error becomes first order, just like the error for stair-step boundary conditions. Nevertheless, provided one does use a sufficiently small value of f"D"M, one can obtain third-order accuracy through Richardson extrapolation. Computations for the TESLA superconducting RF cavity design compare favorably with experimental measurements.
Dublin Bogtrotters: Agent Herders
Authors: Mauro Dragone, David Lillis, Conor Muldoon, Richard Tynan, Rem W. Collier, Gregory M. O'Hare
Venue: Programming Multi-Agent Systems: 6th International Workshop, ProMAS 2008, Estoril, Portugal, May 13, 2008. Revised Invited and Selected Papers (2009)

This paper describes an entry to the Multi-Agent Programming Contest 2008. The approach employs the pre-existing Agent Factory framework and extends this framework in line with experience gained from its use within the robotics domain.
A Multi-Agent Architecture for Re-entrant Manufactuing Line
Authors: Feng Wang, Jie Lin
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 01 (2009)

This paper analyses production scheduling systemin re-entrant line ，and presents a simulation model of the manufacturing system which is based on MAS(Multi Agent Simulation) and HLA (High Level Architecture). According to the model, a related simulation system is developed with Jade and Jess as developing tools to stimulate the manufacturing system, and a new model of constructing ant algorithm on multi-agent system (AAMAS) is proposed to find a satisfactory scheduling scheme.
MCMC Based Bayesian Inference for Modeling Gene Networks
Authors: Ramesh Ram, Madhu Chetty
Venue: Proceedings of the 4th IAPR International Conference on Pattern Recognition in Bioinformatics (2009)

In this paper, we apply Bayesian networks (BN) to infer gene regulatory network (GRN) model from gene expression data. This inference process, consisting of structure search and conditional probability estimation, is challenging due to the size and quality of the data that is currently available. Our previous studies for GRN reconstruction involving evolutionary search algorithm obtained a most plausible graph structure referred as Independence-map (or simply I-map). However, the limitations of the data (large number of genes and less samples) can result in many plausible structures that equally satisfy the data set. In the present study, given the network structures, we estimate the conditional probability distribution of each variable (gene) from the data set to deduce a unique minimal I-map. This is achieved by using Markov Chain Monte Carlo (MCMC) method whereby the search space is iteratively reduced resulting in the required convergence within a reasonable computation time. We present empirical results on both, the synthetic and real-life data sets and also compare our approach with the plain MCMC sampling approach. The inferred minimal I-map on the real-life yeast data set is also presented.
How Technological Support Can Enable Advantages of Agile Software Development in a GSE Setting
Authors: Kevin Dullemond, Ben van Gameren, Rini van Solingen
Venue: Proceedings of the 2009 Fourth IEEE International Conference on Global Software Engineering (2009)

Because of the distance between the dispersed development locations, Global Software Engineering (GSE) is confronted with challenges regarding communication, coordination and control of the development work. At the same time, agile software development is strongly built upon communication between engineers and has proven its benefits, although, mostly on one single site. As such, it might be advantageous to combine GSE with agile development. This blend however is not straightforward since the distributed and agile development approaches might have conflicting convictions. In this paper we will discuss the advantages and challenges of combining GSE with agile development based on a theoretical, literature-based research. The main results presented in this paper are: (i) aspects of agile software development, (ii) benefits and challenges associated with these in relation to GSE, (iii) categories of technological support for agile GSE and (iv) a framework depicting the mutual relations among them.