ppxscal/embedding_network huggingface dataset:
Technical Section: Mesh simplification by stochastic sampling and topological clustering
Authors: Tamy Boubekeur, Marc Alexa
Venue: Computers and Graphics (2009)

We introduce TopStoc, a fast mesh simplification algorithm. The two main components are stochastic vertex selection and re-indexing of triangles. The probability for vertex selection depends on a local feature estimator, which prefers areas of high curvatures but still ensures sufficient sampling in flat parts. Re-indexing the triangles is done by breadth-first traversal starting from the selected vertices and then identifying triangles incident upon three regions. Both steps are linear in the number of triangles, require minimal data, and are very fast, while still preserving geometrical and topological features. Additional optional processing steps improve sampling properties and/or guarantee homotopy equivalence with the input. These properties provide an alternative to vertex clustering especially for CAD/CAM models in the areas of previewing or network graphics.
A Coherent Well-founded Model for Hybrid MKNF Knowledge Bases
Authors: Matthias Knorr, José Júlio Alferes, Pascal Hitzler
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

With the advent of the Semantic Web, the question becomes important how to best combine open-world based ontology languages, like OWL, with closed-world rules paradigms. One of the most mature proposals for this combination is known as Hybrid MKNF knowledge bases [11], which is based on an adaptation of the stable model semantics to knowledge bases consisting of ontology axioms and rules. In this paper, we propose a well-founded semantics for such knowledge bases which promises to provide better efficiency of reasoning, which is compatible both with the OWL-based semantics and the traditional well-founded semantics for logic programs, and which surpasses previous proposals for such a well-founded semantics by avoiding some issues related to inconsistency handling.
A compositional framework for developing parallel programs on two-dimensional arrays
Authors: Kento Emoto, Zhenjiang Hu, Kazuhiko Kakehi, Masato Takeichi
Venue: International Journal of Parallel Programming (2007)

Computations on two-dimensional arrays such as matrices and images are one of the most fundamental and ubiquitous things in computational science and its vast application areas, but development of efficient parallel programs on two-dimensional arrays is known to be hard. In this paper, we propose a compositional framework that supports users, even with little knowledge about parallel machines, to develop both correct and efficient parallel programs on dense two-dimensional arrays systematically. The key feature of our framework is a novel use of the abide-tree representation of two-dimensional arrays. The presentation not only inherits the advantages of tree representations of matrices where recursive blocked algorithms can be defined to achieve better performance, but also supports transformational development of parallel programs and architecture-independent implementation owing to its solid theoretical foundation - the theory of constructive algorithmics.
Indirect Alignment between Multilingual Ontologies: A Case Study of Korean and Swedish Ontologies
Authors: Jason J. Jung, Anne Håkansson, Ronald Hartung
Venue: Proceedings of the Third KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications (2009)

The existing ontology alignment methods have been trying to automatically obtain semantic correspondences between ontologies. However, they assume that all elements of source ontologies are written by identical languages. In this paper, we have introduced a theoretical idea for building indirect alignment between multilingual ontologies. Thereby, a novel architecture to reuse and compose alignments between ontologies has been designed. For a simple case study, we have collected two multilingual ontologies written by Korean and Swedish languages.
Local and Nonlocal Discrete Regularization on Weighted Graphs for Image and Mesh Processing
Authors: Sébastien Bougleux, Abderrahim Elmoataz, Mahmoud Melkemi
Venue: International Journal of Computer Vision (2009)

We propose a discrete regularization framework on weighted graphs of arbitrary topology, which unifies local and nonlocal processing of images, meshes, and more generally discrete data. The approach considers the problem as a variational one, which consists in minimizing a weighted sum of two energy terms: a regularization one that uses the discrete p-Dirichlet form, and an approximation one. The proposed model is parametrized by the degree p of regularity, by the graph structure and by the weight function. The minimization solution leads to a family of simple linear and nonlinear processing methods. In particular, this family includes the exact expression or the discrete version of several neighborhood filters, such as the bilateral and the nonlocal means filter. In the context of images, local and nonlocal regularizations, based on the total variation models, are the continuous analog of the proposed model. Indirectly and naturally, it provides a discrete extension of these regularization methods for any discrete data or functions.
A user-centric cluster and grid computing portal
Authors: Erik Elmroth, Mats Nylen, Roger Oscarsson
Venue: International Journal of Computational Science and Engineering (2009)

The HPC2N Grid portal is a user-centric environment that provides a homogeneous interface to a set of heterogeneous High-Performance Computing (HPC) resources from standard web-browsers. The interface includes support for most everyday activities, such as to submit, manipulate and delete jobs, monitor queues and job status, obtain user-, project-, and resource information, view job output, etc. This contribution reviews the portal functionalities and presents the design and implementation of the underlying system architecture. Some major design considerations, features and limitations are discussed. The portal currently gives access to all major resources at HPC2N, in total comprising over 700 CPUs.
Using partial least squares (PLS) for digital government research
Authors: J. Ramon Gil-Garcia
Venue: Proceedings of the 10th Annual International Conference on Digital Government Research: Social Networks: Making Connections between Citizens, Data and Government (2009)

PLS is a structural equation modeling (SEM) technique similar to covariance-based SEM as implemented in LISREL, EQS, or AMOS. Therefore, PLS can simultaneously test the measurement model (relationships between indicators and their corresponding constructs) and the structural model (relationships between constructs). However, unlike its covariance-based counterpart, PLS allows researchers to working with small samples, too many or too few variables, data from non-normal or unknown distributions, and relatively new theories in which relationships between variables are not well defined. This tutotial shows how to use partial least squares (PLS) and argues that the correct use of this technique could help to incorporate more realistic assumptions and better measurements into digital government research. It does it through a commented example of a digital government research study.
Fortran codes for computing the acoustic field surrounding a vibrating plate by the Rayleigh integral method
Authors: Stephen Kirkup
Venue: Proceedings of the 10th WSEAS international conference on Mathematical methods, computational techniques and intelligent systems (2008)

This paper describes the author's RIM3 Fortran code. RIM3 delivers a computational solution to the acoustic field produced by a vibrating plate placed on an infinite baffle. The mathematical model is based on the Rayleigh integral. The method is implemented in three-dimensions in a manner that is similar to the boundary element method and is applied to test cases and results are given. The software is available as open source and can be downloaded from www.east-lancashire-research.org.uk (report AR-08-16).
A combined grey & ANFIS approach to demand variability in supply chain networks
Authors: Hakan Tozan, Ozalp Vayvay
Venue: Proceedings of the 10th WSEAS international conference on Fuzzy systems (2009)

Accurate and appropriate demand estimation in decision making process is the leading activity to cope with the undesirable demand variability in supply chain network which arises from the chaotic nature of the system. As demand pattern varies due to the field of activity and architecture of supply chains networks, determining the appropriate forecasting and order decision model for system interested in is snarl. In this paper, the response of demand variability to a combined grey GM (1, 1) forecasting and ANFIS based order decision model is analyzed using a simple two stage supply chain network simulation.
Curvature estimation along noisy digital contours by approximate global optimization
Authors: B. Kerautret, J. -O. Lachaud
Venue: Pattern Recognition (2009)

In this paper, we introduce a new curvature estimator along digital contours, which we called global min-curvature (GMC) estimator. As opposed to previous curvature estimators, it considers all the possible shapes that are digitized as this contour, and selects the most probable one with a global optimization approach. The GMC estimator exploits the geometric properties of digital contours by using local bounds on tangent directions defined by the maximal digital straight segments. The estimator is then adapted to noisy contours by replacing maximal segments with maximal blurred digital straight segments. Experiments on perfect and damaged digital contours are performed and in both cases, comparisons with other existing methods are presented.
Indexing and retrieval of low quality handwritten documents
Authors: Venu Govindaraju
Venue:  (2008)

Decades of the development in document analysis and recognition techniques has made it possible to convert large amount of documents into electronic formats and store them into computers. In recent years, the achievement in information retrieval has provided a powerful tool for prompt access to the information that lies in the documents. Inspired by the success of applications in the above two areas, in this thesis, we investigate methods that aim at improving the performance of retrieving handwritten document images. Unlike the retrieval of machine-printed documents from which we will anticipate very high OCR accuracy, the retrieval of handwritten document images is more challenging due to document analysis and recognition errors. In existing methods to retrieve handwritten document images, usually the index is built on the text collected from top-n ( n > 1) candidates returned by a word recognizer. Different weights may apply to the candidates according to their ranks. Effective as these primitive methods are, with the assumptions of flawless word segmentation and isolated word recognition, these methods are vulnerable by word segmentation errors and cannot take advantage of the language model which has become a standard component in the state-of-the-art handwriting recognition systems. However, incorporation of the word segmentation scores (probabilities) and language model into any existing indexing techniques in general increases the complexity of the problem. In our indexing method, we solved this challenging problem by separating the term counts from standard IR models, estimating them on the word sequence level, and plugging them back in the IR models. A fast algorithm using dynamic programming was proposed to reduce the time complexity. In addition to the application in document retrieval, we also used the word segmentation information in keyword retrieval. In another major contribution of this paper, we applied the Markov random field (MRF) modeling to the binarization problem. The MRF can precisely describe the constraint of local smoothness in the image. We can also use the constraint of smoothness to remove the grid from the form image, which is a very useful application in form image preprocessing. This research work virtually addresses a general topic in the preprocessing of degraded handwritten document images. Applications in both handwriting recognition and handwritten document image retrieval can benefit from our approach.
The effect of using computer simulations as self-directed learning on critical thinking levels in entry-level athletic training students
Authors: Ralph E. Martin,  Jr.
Venue:  (2008)

One goal of healthcare educators is to help students think critically to solve problems. Problem-based learning (PBL) is a process that promotes active learning using critical thinking (CT). An assumption is that athletic training students learn CT skills by engaging in the elimination process to correctly answer multiple-choice questions. The purpose of this study is to answer whether implementing a PBL self-directed learning method via computer simulations effects entry-level athletic training students' performance on computer simulations related to physical evaluation of athletic injuries. The California Critical Thinking Skills Test (CCTST) was used to evaluate participants' CT. Participants were divided into two groups, higher level CT (M=72.65%) and lower level CT (M=33.06%). Participants then completed the Computerized-Traditional Athletic Training Simulation Instrument prior to and after completing four weeks of self-directed learning. A repeated measures ANOVA within and between subjects revealed no significant difference between pre-test and post-test performance by their CT level, Wilks' Lambda=.975, F(1,30)=.775, p=.386, multivariate &eta; p2=.025. Participants received unlimited access to computer case simulations from www.higherlevelthinking.com as the treatment measure. A repeated measures ANOVA showed no significant effect of students' CT level on their performance on five computer simulations, F(2.03, 60.92)=.447, p=.645. A repeated measures ANOVA test of between-group effect was conducted F(1, 30)=1.84, p=.186, and revealed no significant difference in mean performance scores between the two groups. Participants appeared to score better on the computer simulation 3 BOC Mock Exam compared to the other four computer simulations. Using pairwise comparisons, it was found that participants' performed significantly better on computer simulation 3 (M=77.12%), p<.01 than on all other cases. Additionally, a repeated measures ANOVA determined that a significant difference occurred between participants' grade point average (GPA) in athletic training classes and their performance on the CCTST, F(2.58, 77.49)=4.68, p=.007. Based on this study, computer simulations do not evaluate the decision making thinking process, and thus, should not be used as an evaluation tool for assessing CT in athletic training students regarding physical evaluation of athletic injuries. However, it was determined that participants' cumulative GPA and GPA in athletic training classes do reflect their ability to think critically.
Recent Advances In Stochastic Modeling And Data Analysis: Chania, Greece 29 May - 1 June 2007
Authors: Christos H. Skiadas, Christos H. Skiadas
Venue:  (2007)

This volume presents the most recent applied and methodological issues in stochastic modeling and data analysis. The contributions cover various fields such as stochastic processes and applications, data analysis methods and techniques, Bayesian methods, biostatistics, econometrics, sampling, linear and nonlinear models, networks and queues, survival analysis, and time series. The volume presents new results with potential for solving real-life problems and provides novel methods for solving these problems by analyzing the relevant data. The use of recent advances in different fields is emphasized, especially new optimization and statistical methods, data warehouse, data mining and knowledge systems, neural computing, and bioinformatics.
Neural Networks for the Parameters Characterization of ECG Dynamical Model
Authors: Matteo Cacciola, Fabio La Foresta, Francesco Carlo Morabito, Mario Versaci
Venue: Proceeding of the 2009 conference on New Directions in Neural Networks: 18th Italian Workshop on Neural Networks: WIRN 2008 (2009)

The Electrocardiogram (ECG) is the recording of the effects produced from the bioelectric field generated by the cardiac muscle during its activity. Specific changes in ECG signals can reveal pathologic heart activity. For this reason, a dynamic model-that accurately describes the heart bioelectric behavior and that can be mathematically analyzed-could be a practical way to investigate heart diseases. The aim of this paper is to introduce a dynamic model to simulate pathological ECG as well as to evaluate an Artificial Neural Network able to distinguish the impact of some modeling parameters on specific and peculiar features of EGC's trend.
A Compositional Mathematical Model of Machines Transporting Rigid Objects
Authors: Peter Struss, Axel Kather, Dominik Schneider, Tobias Voigt
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

We present models of various elements of a plant that involves the transportation of lumped material. An application context is provided by a project on diagnosing disturbances in food packaging plants and, more specifically, bottling plants. While there exist models of flow of homogeneous matters, such as liquid material in a hydraulic system, based on simultaneous equations of Kirchhoff/Ohm type, in our project we need to cope with non-negligible transportation time of objects and capture phenomena like the tailback of units (if transportation is blocked) or the propagation of gaps in the flow of units. Because the application context requires compositionality of the model, i.e. local, context-free models of the individual transportation elements, we are also facing the problem that whether or not a single element produces an output flow (or accepts an input flow) cannot be determined solely by the model of this element, but only through modeling the interaction with the subsequent element, which may block the output (or the previous one not providing the input). This issue is addressed by modeling the potential of an existing flow distinctly from the actual occurrence of a flow, an idea which also can enhance models of continuous flow.
Patterns of query reformulation during Web searching
Authors: Bernard J. Jansen, Danielle L. Booth, Amanda Spink
Venue: Journal of the American Society for Information Science and Technology (2009)

Query reformulation is a key user behavior during Web search. Our research goal is to develop predictive models of query reformulation during Web searching. This article reports results from a study in which we automatically classified the query-reformulation patterns for 964,780 Web searching sessions, composed of 1,523,072 queries, to predict the next query reformulation. We employed an n-gram modeling approach to describe the probability of users transitioning from one query-reformulation state to another to predict their next state. We developed first-, second-, third-, and fourth-order models and evaluated each model for accuracy of prediction, coverage of the dataset, and complexity of the possible pattern set. The results show that Reformulation and Assistance account for approximately 45&percnt; of all query reformulations; furthermore, the results demonstrate that the first- and second-order models provide the best predictability, between 28 and 40&percnt; overall and higher than 70&percnt; for some patterns. Implications are that the n-gram approach can be used for improving searching systems and searching assistance. &copy; 2009 Wiley Periodicals, Inc.
Towards Modeling Systematic Interpretation of Codified Law
Authors: Matthias Grabmair, Kevin D. Ashley
Venue: Proceeding of the 2005 conference on Legal Knowledge and Information Systems: JURIX 2005: The Eighteenth Annual Conference (2005)

This short paper introduces the Interaction Predicate model, which attempts to model some aspects of systematic interpretation of codified law. It introduces an intermediate rule representation containing dynamic reasoning elements which make use of domain knowledge ontologies.
Q&AThe networker
Authors: Leah Hoffmann
Venue: Communications of the ACM (2009)

Jon Kleinberg talks about algorithms, information flow, and the connections between Web search and social networks.
Evaluating a Collaborative Constraint-based Tutor for UML Class Diagrams
Authors: Nilufar Baghaei, Antonija Mitrovic
Venue: Proceeding of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work (2007)

COLLECT-UML is a collaborative constraint-based tutor for teaching object-oriented analysis and design using Unified Modelling Language. It is the first system in the family of constraint-based tutors to represent a higher-level skill such as collaboration using constraints. We present the full evaluation study carried out at the University of Canterbury to assess the effectiveness of the system in teaching UML class diagrams and good collaboration. The results show that COLLECT-UML is an effective educational tool. In addition to improved problem-solving skills, the participants both acquired declarative knowledge about good collaboration and did collaborate more effectively. The participants have enjoyed working with the system and found it a valuable asset to their learning.
Implementation of a knowledge management tool within a virtual organization: the GPT case study
Authors: Paolo Taticchi, Flavio Tonelli, Eduardo Hernandez, Luca Cagnazzo
Venue: Proceedings of the 8th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases (2009)

This paper presents a Knowledge Management (KM) software tool which has been designed to support managing implementation of best practices and improvement initiatives within a VDO (Virtual Development Office) Network. A VDO Network is an organization integrated by SMEs, with a particular form of governance. Furthermore, the KM tool enables building a knowledge base of key capabilities available to a VDO to support decision-making and responding effectively to new business opportunities. KM tool acts not only as a repository for knowledge pertaining to improvement initiatives, but it also drives SMEs to apply and share that knowledge within the wider VDO Enterprise Network. The availability of KM tools for SMEs is rare. This is more evident for Enterprise Networks. The KM tool can be easily modified to address better the requirements of the user (VDO) due to its flexible architecture.
Effects of Using Digital Contents Designed for PDA as a Teaching Aid in an Observational Learning of Planktons for Fieldworks on a Ship
Authors: Hitoshi Miyata, Mitsuo Ishigami
Venue: Proceeding of the 2006 conference on Learning by Effective Utilization of Technologies: Facilitating Intercultural Understanding (2006)

We developed “The World of Planktons in Lake Biwa,” which is digital contents for use as a teaching aid in the observational learning of planktons that is conducted aboard a ship as part of science lessons. This content consists of a search page with 350 still images to be used to search and identify over 200 types of planktons living in Lake Biwa; pages providing 45 video clips of actions that are difficult to observe directly, such as the hatching of plankton eggs and cell division; pages explaining cell division; and a “digital sketch” page on which students can upload and publish hand-drawn pictures. The developed content was used in actual lessons for fifth-grade primary school students observing planktons aboard a ship. We validated the effectiveness of the digital content from the perspectives of (1) “interest, motivation, and attitude”; (2) “thinking and judging”; (3) “technique and expression”; and (4) “knowledge and understanding.”