ppxscal/embedding_network huggingface dataset:
Minimum-Cost Load-Balancing Partitions
Authors: Boris Aronov, Paz Carmi, Matthew J. Katz
Venue: Algorithmica (2009)

We consider the problem of balancing the load among several service-providing facilities, while keeping the total cost low. Let D be the underlying demand region, and let p 1,&#x2026;,p m be m points representing m facilities. We consider the following problem: Subdivide D into m equal-area regions R 1,&#x2026;,R m , so that region R i is served by facility p i , and the average distance between a point q in D and the facility that serves q is minimal. We present constant-factor approximation algorithms for this problem, with the additional requirement that the resulting regions must be convex. As an intermediate result we show how to partition a convex polygon into m equal-area convex subregions so that the fatness of the resulting regions is within a constant factor of the fatness of the original polygon. In fact, we prove that our partition is, up to a constant factor, the best one can get if one&#x2019;s goal is to maximize the fatness of the least fat subregion. We also discuss the structure of the optimal partition for the aforementioned load balancing problem: indeed, we argue that it is always induced by an additive-weighted Voronoi diagram for an appropriate choice of weights.
System monitoring with metric-correlation models: problems and solutions
Authors: Miao Jiang, Mohammad A. Munawar, Thomas Reidemeister, Paul A.S. Ward
Venue: Proceedings of the 6th international conference on Autonomic computing (2009)

Correlations among management metrics in software systems allow errors to be detected and their cause localized. Prior research shows that linear models can capture many of these correlations. However, our research shows that several factors may prevent linear models from accurately describing correlations, even if the underlying relationship is linear. Two common phenomena we have observed are relationships that evolve, typically with time, and heterogeneous variance of the correlated metrics. Two-variable linear models proposed thus far fail to capture these phenomena, and thus fail to describe system dynamics correctly. Often, these phenomena are caused by a missing variable. However, searching for three-variable correlations is O(n3) for n metrics, which is costly for systems with many metrics. In this paper we address the above challenges by improving on two-variable Ordinary Least Squares regression models. We validate our models using a realistic Java-Enterprise-Edition application. Using fault-injection experiments we show that our improved models capture system behavior accurately. We detect errors within 8 sample periods on average from the injection of the fault, which is less than half the time required by the current linear-model approach.
3D Model Retrieval Using Probability Density-Based Shape Descriptors
Authors: Ceyhun Burak Akgül, Bülent Sankur, Yücel Yemez, Francis Schmitt
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2009)

We address content-based retrieval of complete 3D object models by a probabilistic generative description of local shape properties. The proposed shape description framework characterizes a 3D object with sampled multivariate probability density functions of its local surface features. This density-based descriptor can be efficiently computed via kernel density estimation (KDE) coupled with fast Gauss transform. The non-parametric KDE technique allows reliable characterization of a diverse set of shapes and yields descriptors which remain relatively insensitive to small shape perturbations and mesh resolution. Density-based characterization also induces a permutation property which can be used to guarantee invariance at the shape matching stage. As proven by extensive retrieval experiments on several 3D databases, our framework provides state-of-the-art discrimination over a broad and heterogeneous set of shape categories.
Algorithms for integrating PostgreSQL with the semantic web
Authors: D. V. Levshin, A. S. Markov
Venue: Programming and Computing Software (2009)

This paper addresses the integration of the PostgreSQL database management system (DBMS) with the Semantic Web. Integration algorithms based on the use of the DBMS capabilities that do not introduce changes in SQL are proposed. An integration based on one of the algorithms supporting main formats of the Semantic Web is presented. The proposed algorithms can be implemented in different DBMSs supporting triggers (or rules), table functions, and indexing.
Approximation by complex Bernstein-Schurer and Kantorovich-Schurer polynomials in compact disks
Authors: George A. Anastassiou, Sorin G. Gal
Venue: Computers Mathematics with Applications (2009)

In this paper, the order of simultaneous approximation and Voronovskaja-type results with quantitative estimate for complex Bernstein-Schurer and Kantorovich-Schurer polynomials attached to analytic functions on compact disks are obtained. In this way, we put in evidence the overconvergence phenomenon for the Bernstein-Schurer polynomials, namely the extensions of approximation properties (with quantitative estimates) from real intervals to compact disks in the complex plane.
Exploring Neural Trajectories of Scientific Problem Solving Skill Acquisition
Authors: Ronald H. Stevens, Trysha Galloway, Chris Berka
Venue: Proceeding of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work (2007)

We have modeled changes in electroencephalography (EEG)-derived measures of cognitive workload, engagement, and distraction as individuals developed and refined their problem solving skills in science. Subjects performing a series of problem solving simulations showed decreases in the times needed to solve the problems; however, metrics of high cognitive workload and high engagement remained the same. When these indices were measured within the navigation, decision, and display events in the simulations, significant differences in workload and engagement were often observed. In addition, differences in these event categories were also often observed across a series of the tasks, and were variable across individuals. These preliminary studies suggest that the development of EEG-derived models of the dynamic changes in cognitive indices of workload, distraction and engagement may be an important tool for understanding the development of problem solving skills in secondary school students.
Coordination support in multi-agent systems
Authors: Jordi Campos, Maite López-Sánchez, Marc Esteva
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

We propose the term Coordination Support to denote the services offered by the infrastructure used to deploy Multi-Agent Systems (MAS). In fact, these services provide a means to enact the coordination model defined in MAS design. We detail Coordination Support's functionalities and group them into different layers. Furthermore we extend them and propose an additional Assistance layer devoted to assist coordination rather than to enable it. Assistance's functionalities range from providing information -about the coordination model and its state- to adapting agents' organisation.
User Evaluation Study of a Tagging Approach to Semantic Mapping
Authors: Colm Conroy, Rob Brennan, Declan O'Sullivan, Dave Lewis
Venue: Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications (2009)

A key aspect of semantic interoperability is the semantic mapping process itself. Traditionally, semantic mapping processes conducted by knowledge engineers have been proposed to bridge this gap. However, knowledge engineers alone are unlikely to cope with the ever increasing amount of mapping work required, especially as mappings themselves begin to be specialised for different contexts. One solution is to develop new mapping processes that enable users to participate in the mapping process themselves. In this paper we present an evaluation study of our user-driven tagging approach to the semantic mapping process. In our approach, users actively participate in generating mappings by categorising automatically generated candidate matches presented in natural language over a long time period. In the evaluation study three groups of users generated mappings between their personal ontologies and a sports ontology describing sports news content from RSS feeds. The mapping process was embedded within the users' work environment as a Firefox browser extension. The study is discussed, focusing on whether the mapping process is unintrusive, engaging and simplified for the user. The evaluation results were promising and indicate that people with various levels of expertise could become active in the semantic mapping process.
Statistical M-Estimation and Consistency in Large Deformable Models for Image Warping
Authors: Jérémie Bigot, Sébastien Gadat, Jean-Michel Loubes
Venue: Journal of Mathematical Imaging and Vision (2009)

The problem of defining appropriate distances between shapes or images and modeling the variability of natural images by group transformations is at the heart of modern image analysis. A current trend is the study of probabilistic and statistical aspects of deformation models, and the development of consistent statistical procedure for the estimation of template images. In this paper, we consider a set of images randomly warped from a mean template which has to be recovered. For this, we define an appropriate statistical parametric model to generate random diffeomorphic deformations in two-dimensions. Then, we focus on the problem of estimating the mean pattern when the images are observed with noise. This problem is challenging both from a theoretical and a practical point of view. M-estimation theory enables us to build an estimator defined as a minimizer of a well-tailored empirical criterion. We prove the convergence of this estimator and propose a gradient descent algorithm to compute this M-estimator in practice. Simulations of template extraction and an application to image clustering and classification are also provided.
"no me llames de usted, tratame de tu": l2 address behavior development through synchronous computer-mediated communication
Authors: Gabriele Kasper
Venue:  (2008)

This dissertation explores the potential of synchronous computer-mediated communication (SCMC) to promote pragmatic competence among language learners in a higher education context. Specifically, the development of their L2 address system and their interactive resources to display closeness when engaged in communication with L1 speakers. Through Conversation Analysis (CA), the sequential organization of SCMC between L1 speakers of Spanish and L2 Spanish learners was analyzed to discover what type of address behavior they exhibited, as well as documenting any change in their pragmalinguistic resources and patterns of interaction. Eight weeks of SCMC between US students of Spanish and L1 Spanish speakers in Spain were microanalyzed through Conversation Analysis (CA). The data illustrate how students engaged in organized meaningful interaction, employing a turn-taking system borrowed from oral communication but re-shaped and adapted to the medium, much in the same way that L1 speakers do. As for address behavior, the data revealed that L1 speakers consistently used informal pronouns and verb morphology, while employing a variety of resources to do &lsquo;being close&rsquo;. The learners&rsquo; data presented two distinctive groups. The first displayed large variety in their use of formal and informal address forms. A longitudinal exploration revealed that, in order for learners to develop proficiency in the use of the Spanish address system, a minimum amount of interaction is needed. The students&rsquo; knowledge of the address system at the beginning of the study may also be a determinant on the ratio of development, as well as personal attitude and their first language. In addition, learning seemed to happen when there was explicit focus on the address forms.
A novel algorithm for the detection of melanoma border
Authors: A. Hatzigaidas, A. Papastergiou, P. Tzekis
Venue: Proceedings of the 10th WSEAS international conference on Automation & information (2009)

There is an ongoing research effort to provide computer-aided imaging tools in order to support the diagnosis and early detection of malignant melanomas. The first step towards producing such a system is the automated and accurate boundary detection of skin lesion. Therefore, the present study introduces a new, simple, and very fast algorithm that has the ability to detect effectively and automatically the border of possible melanoma. The complexity of the proposed algorithm is O(√N) and thus the execution time is dramatically minimized.
Designing a Teacher Professional Knowledge Base and Its Operation Model Based on School-Based Curriculum Development
Authors: Yih-Ruey Juang, Tak-Wai Chan, Tzu-Chien Liu
Venue: Proceeding of the 2006 conference on Learning by Effective Utilization of Technologies: Facilitating Intercultural Understanding (2006)

Teacher professional development approaches digitalization, combination with practice, and cooperative learning; emphasizes teachers' growth in subject knowledge and practical knowledge. With the design, practice, and reflection of lesson plans, promotes the teacher's individual emphasis on professionalism, build a knowledge base through cooperative research between teachers. However, existing teacher professional development systems of network platforms are focused on individual teachers or teacher groups. There is less chance for school curriculum development departments or educational experts to intervene. Thus, while there are many participants, the quality and quantity of knowledge bases both need to be improved. This study proposes a teacher professional development model based on school-based curriculum development, to construct a knowledge base centered on the lesson plan. At the same time, use the operation mechanism 3C-model of creation, collaboration, and communication, to increase efficiency of professional development and the quality and quantity of knowledge bases.
On the generation of requirements specifications from software engineering models: A systematic literature review
Authors: Joaquín Nicolás, Ambrosio Toval
Venue: Information and Software Technology (2009)

System and software requirements documents play a crucial role in software engineering in that they must both communicate requirements to clients in an understandable manner and define requirements in precise detail for system developers. The benefits of both lists of textual requirements (usually written in natural language) and software engineering models (usually specified in graphical form) can be brought together by combining the two approaches in the specification of system and software requirements documents. If, moreover, textual requirements are generated from models in an automatic or closely monitored form, the effort of specifying those requirements is reduced and the completeness of the specification and the management of the requirements traceability are improved. This paper presents a systematic review of the literature related to the generation of textual requirements specifications from software engineering models.
Short-term emotion assessment in a recall paradigm
Authors: Guillaume Chanel, Joep J. M. Kierkels, Mohammad Soleymani, Thierry Pun
Venue: International Journal of Human-Computer Studies (2009)

The work presented in this paper aims at assessing human emotions using peripheral as well as electroencephalographic (EEG) physiological signals on short-time periods. Three specific areas of the valence-arousal emotional space are defined, corresponding to negatively excited, positively excited, and calm-neutral states. An acquisition protocol based on the recall of past emotional life episodes has been designed to acquire data from both peripheral and EEG signals. Pattern classification is used to distinguish between the three areas of the valence-arousal space. The performance of several classifiers has been evaluated on 10 participants and different feature sets: peripheral features, EEG time-frequency features, EEG pairwise mutual information (MI) features. Comparison of results obtained using either peripheral or EEG signals confirms the interest of using EEGs to assess valence and arousal in emotion recall conditions. The obtained accuracy for the three emotional classes is 63% using EEG time-frequency features, which is better than the results obtained from previous studies using EEG and similar classes. Fusion of the different feature sets at the decision level using a summation rule also showed to improve accuracy to 70%. Furthermore, the rejection of non-confident samples finally led to a classification accuracy of 80% for the three classes.
Arguments in OWL: A Progress Report
Authors: Iyad Rahwan, Bita Banihashemi
Venue: Proceeding of the 2008 conference on Computational Models of Argument: Proceedings of COMMA 2008 (2008)

In previous work, we presented an RDFS ontology, based on the Argument Interchange Format (AIF), for describing arguments and argument schemes. We also implemented a pilot Web-based system, called ArgDF, for authoring and querying argument structures represented in RDF. In this paper, we discuss some of the limitations of our earlier reification of the AIF. We then present a new ontology which takes advantage of the higher expressive power of OWL. We demonstrate how this enables the use of automated Description Logic reasoning over argument structures. In particular, OWL reasoning enables significantly enhanced querying of arguments through automatic scheme classifications, instance classification, and inference of indirect support in chained argument structures.
An experimental study on connectivity and topology control in real multi-hop wireless networks
Authors: Alvin Valera, Pius W. Q. Lee, Yew Fai Wong, Winston K. G. Seah, Hwee-Pink Tan, Han Ju
Venue: Proceedings of the 4th Annual International Conference on Wireless Internet (2008)

Topology control by means of transmit power adjustment is a well-studied technique for improving the network capacity and energy efficiency of wireless ad hoc networks. In this paper, we investigate the feasibility of connectivity and topology control in a real IEEE 802.11b testbed composed of inexpensive commercial-off-the-shelf (COTS) routers. Although topology control via transmit power adjustment is feasible based on analytical studies and emulations, it is difficult in practice for the range provided by COTS wireless routers.
Semantics and complexity of SPARQL
Authors: Jorge Pérez, Marcelo Arenas, Claudio Gutierrez
Venue: ACM Transactions on Database Systems (TODS) (2009)

SPARQL is the standard language for querying RDF data. In this article, we address systematically the formal study of the database aspects of SPARQL, concentrating in its graph pattern matching facility. We provide a compositional semantics for the core part of SPARQL, and study the complexity of the evaluation of several fragments of the language. Among other complexity results, we show that the evaluation of general SPARQL patterns is PSPACE-complete. We identify a large class of SPARQL patterns, defined by imposing a simple and natural syntactic restriction, where the query evaluation problem can be solved more efficiently. This restriction gives rise to the class of well-designed patterns. We show that the evaluation problem is coNP-complete for well-designed patterns. Moreover, we provide several rewriting rules for well-designed patterns whose application may have a considerable impact in the cost of evaluating SPARQL queries.
Barbed congruence of asymmetry and mismatch
Authors: Xiao-Ju Dong, Yu-Xi Fu
Venue: Journal of Computer Science and Technology (2007)

The χ calculus is a model of concurrent and mobile systems. It emphasizes that communications are information exchanges. In the paper, two constructions are incorporated into the framework of the chi calculus, which are asymmetric communication and mismatch condition widely used in applications. Since the barbed bisimilarity has proved its generality and gained its popularity as an effective approach to generating a reasonable observational equivalence, we study both the operational and algebraic properties of the barbed bisimilarity in this enriched calculus. The investigation supports an improved understanding of the bisimulation behaviors of the model. It also gives a general picture of how the two constructions affect the observational theory.
Author name disambiguation in MEDLINE
Authors: Vetle I. Torvik, Neil R. Smalheiser
Venue: ACM Transactions on Knowledge Discovery from Data (TKDD) (2009)

Background: We recently described &ldquo;Author-ity,&rdquo; a model for estimating the probability that two articles in MEDLINE, sharing the same author name, were written by the same individual. Features include shared title words, journal name, coauthors, medical subject headings, language, affiliations, and author name features (middle initial, suffix, and prevalence in MEDLINE). Here we test the hypothesis that the Author-ity model will suffice to disambiguate author names for the vast majority of articles in MEDLINE. Methods: Enhancements include: (a) incorporating first names and their variants, email addresses, and correlations between specific last names and affiliation words; (b) new methods of generating large unbiased training sets; (c) new methods for estimating the prior probability; (d) a weighted least squares algorithm for correcting transitivity violations; and (e) a maximum likelihood based agglomerative algorithm for computing clusters of articles that represent inferred author-individuals. Results: Pairwise comparisons were computed for all author names on all 15.3 million articles in MEDLINE (2006 baseline), that share last name and first initial, to create Author-ity 2006, a database that has each name on each article assigned to one of 6.7 million inferred author-individual clusters. Recall is estimated at &sim;98.8&percnt;. Lumping (putting two different individuals into the same cluster) affects &sim;0.5&percnt; of clusters, whereas splitting (assigning articles written by the same individual to >1 cluster) affects &sim;2&percnt; of articles. Impact: The Author-ity model can be applied generally to other bibliographic databases. Author name disambiguation allows information retrieval and data integration to become person-centered, not just document-centered, setting the stage for new data mining and social network tools that will facilitate the analysis of scholarly publishing and collaboration behavior. Availability: The Author-ity 2006 database is available for nonprofit academic research, and can be freely queried via http://arrowsmith.psych.uic.edu.
Author Identification Using a Tensor Space Representation
Authors: Spyridon Plakias Efstathios Stamatatos
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

Author identification is a text categorization task with applications in intelligence, criminal law, computer forensics, etc. Usually, in such cases there is shortage of training texts. In this paper, we propose the use of second order tensors for representing texts for this problem, in contrast to the traditional vector space model. Based on a generalization of the SVM algorithm that can handle tensors, we explore various methods for filling the matrix of features taking into account that similar features should be placed in the same neighborhood. To this end, we propose a frequency-based metric. Experiments on a corpus controlled for genre and topic and variable amount of training texts show that the proposed approach is more effective than traditional vector-based SVM when only limited amount of training texts is used.