ppxscal/embedding_network huggingface dataset:
Improving Web-Based Learning by Means of Narrative
Authors: Giuliana Dettori
Venue: Proceedings of the 1st international conference on Hybrid Learning and Education (2008)

Web-based learning mostly relies on written, asynchronous interaction, which grants learners time for reflection and freedom in the organization of their activity. Written communication, however, is considered an impoverished means by many people, because it lacks non-verbal cues, with consequent negative influence on the quality of the learning process, as concerns both its cognitive and motivational/emotional aspects. Hence, the research on web-based learning is increasingly giving attention to ways to overcome this problem. Based on the analysis of three different examples drawn from the literature, this paper argues that introducing a targeted narrative activity in the design of web-based learning can represent a valuable way to contextualize the learning activity and enhance social presence, in that narrative is a multifaceted form of communication which results natural in all cultures and is suitable for any learning subject.
A2DLT: Divisible Load Balancing Model for Scheduling Communication-Intensive Grid Applications
Authors: M. Othman, M. Abdullah, H. Ibrahim, S. Subramaniam
Venue: Proceedings of the 8th international conference on Computational Science, Part I (2008)

Scheduling an application in data grid is significantly complex and very challenging because of its heterogeneous in nature of the grid system. Divisible Load Theory (DLT) is a powerful model for modelling data-intensive grid problem where both communication and computation loads are partitionable. This paper presents a new divisible load balancing model known as adaptive ADLT (A2DLT) for scheduling the communication intensive grid applications. This model reduces the maximum completion time (makespan) as compared to the ADLT and Constraint DLT (CDLT) models. Experimental results showed that the model can balance the load efficiently, especially when the communication-intensive applications are considered.
Upper Borders for Emerging Cubes
Authors: Sébastien Nedjar, Alain Casali, Rosine Cicchetti, Lotfi Lakhal
Venue: Proceedings of the 10th international conference on Data Warehousing and Knowledge Discovery (2008)

The emerging cube computed from two relations r 1, r 2 of categorical attributes gather the tuples for which the measure value strongly increases from r 1 to r 2. In this paper, we are interested in borders for emerging cubes which optimize both storage space and computation time. Such borders also provide classification and cube navigation tools. Firstly we study the condensed representation through the classical borders Lower / Upper, then we propose the borders Upper * / Upper more reduced than the previous ones. We soundly state the connexion between the two representations by using cube transversals. Finally, we perform experiments about the size of the introduced representations. The results are convincing and reinforce our idea that the proposed borders are relevant candidates to be the smallest condensed representation of emerging cubes and thus can be really interesting for trend analysis in Olap databases.
Towards an Automatic Analysis of Web Service Security
Authors: Yannick Chevalier, Denis Lugiez, Michaël Rusinowitch
Venue: Proceedings of the 6th international symposium on Frontiers of Combining Systems (2007)

Web services send and receive messages in XML syntax with some parts hashed, encrypted or signed, according to the WS-Security standard. In this paper we introduce a model to formally describe the protocols that underly these services, their security properties and the rewriting attacks they might be subject to. Unlike other protocol models (in symbolic analysis) ours can handle non-deterministic receive/send actions and unordered sequence of XML nodes. Then to detect the attacks we have to consider the services as combining multiset operators and cryptographic ones and we have to solve specific satisfiability problems in the combined theory. By non-trivial extension of the combination techniques of [3] we obtain a decision procedure for insecurity of Web services with messages built using encryption, signature, and other cryptographic primitives. This combination technique allows one to decide insecurity in a modular way by reducing the associated constraint solving problems to problems in simpler theories.
A regularized Lagrangian finite point method for the simulation of incompressible viscous flows
Authors: Jiannong Fang, Aurèle Parriaux
Venue: Journal of Computational Physics (2008)

In this paper we present a regularized Lagrangian finite point method (RLFPM) for the numerical simulation of incompressible viscous flows. A Lagrangian finite point scheme is applied to the projection method for the incompressible Navier-Stokes equations. The approximation of spatial derivatives is obtained by the weighted least squares method. The pressure Poisson equation with Neumann boundary condition is solved by a stabilized finite point method. A key aspect of the present approach is the periodic redistribution of the particle locations, which are being distorted by the flow. Again, weighted least squares approximation is implemented to interpolate the properties of the old particles onto the new particle locations. With the proposed regularization technique, problems associated with the flow-induced irregularity of particle distribution in the Lagrangian finite point scheme are circumvented. Three numerical examples, Taylor-Green flow, lid-driven flow in a cavity and flow through a periodic lattice of cylinders, are presented to validate the proposed methodology. The problem of extra diffusion caused by regularization is discussed. The results demonstrate that RLFPM is able to perform accurate and stable simulations of incompressible viscous flows.
Rough Evolutionary Fuzzy System Based on Interactive T-Norms
Authors: Graciela L. Lovón, Maria Bernadete Zanusso
Venue: Proceedings of the 11th Ibero-American conference on AI: Advances in Artificial Intelligence (2008)

A rough evolutionary neuro-fuzzy system for classification and rule generation is proposed. Interactive and differentiable t-norms and t-conorms involving logical neurons in a three-layer perceptron are used. This paper presents the results of application of the methodology based on rough set theory, which initializes the number of hidden nodes and some of the weight values. In search of the smallest network with a good generalization capacity, the genetic algorithms operate on population of individuals composed by integration of dependency rules that will be mapped on networks. Justification of an inferred decision was produced in rule form expressed as the disjunction of conjunctive clauses. The effectiveness of the algorithm is demonstrated on a speech recognition problem. The results are compared with those of fuzzy-MLP and Rough-Fuzzy-MLP, with no logical neuron; the Logical-P, which uses product and probabilistic sum; and other related models.
A Cellular Automaton Model for Tribological Problems
Authors: Michael Müller, Georg-Peter Ostermeyer
Venue: Proceedings of the 8th international conference on Cellular Automata for Reseach and Industry (2008)

Many tribological systems are characterized by an interface dynamics determined by the growth and destruction of hard thin and smooth structures, so called 'patches'. These patches transmit the main part of the friction power and protect the softer pad ingredients from wear. This behavior, which is explained with the example of a brake system, can be interpreted as a kind of self-organization process. Hereby rather simple local balance equations, considering the aspects of temperature, particle flow, patch dynamics and transmitted friction power, result in a complex global tribological character. In this paper it is shown that the Cellular Automaton is a very helpful method to describe the above standing items and their correlation. In order to avoid certain numerical instabilities, the respective boundary conditions are discussed.
Brief paper: An adaptive tracking control from current measurements for induction motors with uncertain load torque and rotor resistance
Authors: R. Marino, P. Tomei, C. M. Verrelli
Venue: Automatica (Journal of IFAC) (2008)

The problem of controlling sensorless induction motors with uncertain constant load torque and rotor resistance on the basis of stator current measurements only is addressed. A new eighth-order dynamic nonlinear adaptive control algorithm is designed, which relies on a closed loop adaptive observer for the unmeasured state variables (rotor speed and fluxes) and for the uncertain parameters and is not based on non-robust open loop integration of flux dynamics. Local exponential stability of the closed loop tracking and estimation error dynamics is achieved under persistency of excitation conditions which restrict the reference signals and may be interpreted in terms of motor observability and rotor resistance identifiability.
Cancer classification using kernelized fuzzy C-means
Authors: Vikram Chandramohan, Tuan D. Pham
Venue: Proceedings of the 9th WSEAS International Conference on Fuzzy Systems (2008)

Pattern analysis of mass spectra obtained from blood samples, has attracted the attention for early detection of cancer. In this paper, we present an unsupervised kernel based fuzzy c-means algorithm (KFCM), which is realized by modifying original Euclidean distance in classical fuzzy clustering algorithm (FCM) by kernel-induced distance metric. Our analysis on mass spectrometry dataset, shows that KFCM has better clustering performance and is more robust to noise than FCM. We evaluated the performance of our classification methods with some popular classification techniques like SVM, PCA, LDA/QDA and randomforests.
Comparison of cognitively diagnostic adaptive testing algorithms
Authors: James E. Corter
Venue:  (2008)

Variations of two cognitively diagnostic adaptive testing algorithms were compared using a computer simulation based on full-test data consisting of 536 junior high school students' dichotomous responses to a 40-item fraction subtraction test. The two models forming the basis for the computer-adaptive testing algorithms were the Rule Space model developed by Kikumi Tatsuoka and her associates, and the Poset model developed by Curtis Tatsuoka and his associates. The computer adaptive testing (CAT) algorithms based on these models differ in terms of their item selection and test stopping criteria, and they were investigated for their efficiency and consistency in classifying individuals into their knowledge states, which are defined by the sets of mastered and non-mastered cognitive skills called "attributes." In this study, for CAT based on the Rule Space model, three different item selection methods were developed and compared for classification consistency, and two different test stopping methods, combined with the three item selection methods, were also compared for classification efficiency. Best-k-item tests based on the maximum R-squared were also evaluated against the CAT results. For CAT based on the Poset model, classification consistency and efficiency were first examined by evaluating the results of CAT and full-length testing. The two models were then compared to each other as well. CAT based on the Rule Space model seemed to work relatively well when a next item was selected based on an examinee's provisional knowledge state estimated from the examinee's responses made so far, and if the testing was terminated when no more items could drastically change the examinee's position in rule space, which is a space defined by IRT-theta and zeta (unusualness of responses). CAT based on the Poset model was very consistent and efficient in classification. It turned out to be more consistent and efficient than CAT based on the Rule Space model; nevertheless, both algorithms seemed to provide similar diagnostic classification of examinees as consistently as the full-length testing does.
Path Generation Issues for Survivable Network Design
Authors: Michał Pióro, Tomasz Śliwiński, Michał Zagożdżon, Mateusz Dzida, Włodzimierz Ogryczak
Venue: Proceedings of the international conference on Computational Science and Its Applications, Part II (2008)

Link dimensioning and routing problems in resilient network design are considered. Reliable network operation is ensured by means of flow restoration which is performed on preselected protection (backup) paths that can absorb traffic overflows from failed primary paths. Backup and primary flows use separated link capacities, and can be split among many paths. In the paper, two restoration models are considered. The first model assumes that once the backup path is assigned it must be used in every state in which the protected primary path fails while the second model allows different protection paths to be used in different network failure states. The problems are formulated as multiple commodity linear programming (LP) models using the link-path (L-P) notation and solved by the column generation technique. Consequent pricing models and algorithms are introduced. Computational efficiency of the presented approaches is analyzed.
Measuring the Human Factor with the Rasch Model
Authors: Dirk Wilking, David Schilli, Stefan Kowalewski
Venue: Balancing Agility and Formalism in Software Engineering: Second IFIP TC 2 Central and East European Conference on Software Engineering Techniques, CEE-SET 2007, Poznan, Poland, October 10-12, 2007, Revised Selected Papers (2008)

This paper presents a test for measuring the C language knowledge of a software developer. The test was grounded with a web experiment comprising 151 participants. Their background ranged from pupils to professional developers. The resulting variable is based on the Rasch Model. Therefore single questions as well as the entire test could be assessed. The paper describes the experiment, the application of the Rasch Model in software engineering, and further concepts of measurement.
Qualitative Stability Patterns for Lotka-Volterra Systems on Rectangles
Authors: Laurent Tournier, Jean-Luc Gouzé
Venue: Proceedings of the 11th international workshop on Hybrid Systems: Computation and Control (2008)

We present an analysis of the Lotka-Volterra differential equation within rectangles that are transverse with respect to the flow. In a similar way to existing works on affine systems (and positively invariant rectangles), we consider nonlinear LV equations, in rectangles with any kind of tranverse patterns. Notably, we give conditions for the existence of such rectangles. We also analyze the dynamical behavior inside a rectangle. This work is a first step towards a qualitative abstraction and simulation of Lotka-Volterra systems.
New equations for management
Authors: J. E. Hobson
Venue: Proceedings of the February 4-6, 1953, western computer conference (1953)

Research produces needed facts. Men planning the course of today's industry need facts. They need dimensional facts from the laboratory and pilot plant; and they need facts on the human element in industry--the customer, the worker, and the executive. 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
Note: Signed star k-subdomination numbers in graphs
Authors: R. Saei, S. M. Sheikholeslami
Venue: Discrete Applied Mathematics (2008)

Let G be a simple graph without isolated vertex with vertex set V(G) and edge set E(G). A function f:E(G)@?{-1,1} is said to be a signed star k-subdominating function of G if @?"e"@?"E"("v")f(e)>=1 for at least k vertices v of G, where E(v)={uv@?E(G)|u@?N(v)}. The value min@?"e"@?"E"("G")f(e), taking over all signed star k-subdominating function f of G is called the signed star k-subdomination number of G and denoted by @c"S"S^k(G). In this paper we give some bounds on the signed star k-subdomination number of graphs.
The role of readiness for change in ERP implementation: Theoretical bases and empirical validation
Authors: Kee-Young Kwahk, Jae-Nam Lee
Venue: Information and Management (2008)

Implementation of ERP systems continues to drive change in organizations. However, the effort is often considered a failure, partially because potential users resist the change. Readiness plays an active role in reducing resistance to such efforts. Therefore, we examined the formation of readiness for change and its effect on the perceived technological value of an ERP system leading to its use. We developed a model of readiness for change incorporating TAM and TPB. The model was then empirically tested using data collected from users of ERP systems in Korea. Structural equation analysis using LISREL provided significant support for all proposed relationships. Specifically, we found that readiness for change had an indirect effect on behavioral intention to use an ERP system. At the same time, readiness for change was found to be enhanced by two factors: organizational commitment and perceived personal competence.
Towards Refinement of Clinical Evidence Using General Logics
Authors: Patrik Eklund, Robert Helgesson, Helena Lindgren
Venue: Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing (2006)

Clinical knowledge building upon evidence-based medicine is typically represented in textual guidelines, thus providing a rather informal description from a logical point of view. Further, the context which provides utility of these guidelines is not specified in any detail with respect to workflow and underlying motivations for decision-making. In addition, the level of detail is mostly static in the sense that measurements and decision values are fixed and intended for specific user groups. There is thus a lack of flexibility which disables knowledge to be shifted coherently between user levels in the entire workflow and decision process. In this paper, we will discuss formalizations of the underlying logical structures of guidelines from the viewpoint of being represented appropriately at each user level. Further, to establish a formal correctness criterion, the shift from one level of representation to another is required to be morphic in the categorical sense. General logics [7] is the selected generalized, and categorical, framework for our approach to flexible guideline representation. Our medical scope is dementia differential diagnosis based on consensus guidelines [2], and we focus on types of cognitive disorders as a prerequisite for further diagnostic tasks.
Intelligent software analyzer design for biotechnological processes
Authors: Svetla Vassileva, Silvia Mileva
Venue: Proceedings of the 9th WSEAS International Conference on Neural Networks (2008)

This work presents a technology of artificial intelligence methods-based software analyzers design for biotechnological processes. The design of intelligent software analyzers of two hard-to measure intercellular metabolites, important in the early stage of brewing fermentation - ergosterol and glycogen, is demonstrated by implementing ANFIS and compare it with the artificial neural networks (ANN)-training techniques of Levenberg-Marquardt and Radial Basis Functions-NN (RBFNN). The application of intelligent software analyzers in modern control technologies is discussed.
Unfolding the Manifold in Generative Topographic Mapping
Authors: Raúl Cruz-Barbosa, Alfredo Vellido
Venue: Proceedings of the 3rd international workshop on Hybrid Artificial Intelligence Systems (2008)

Generative Topographic Mapping (GTM) is a probabilistic latent variable model for multivariate data clustering and visualization. It tries to capture the relevant data structure by defining a low-dimensional manifold embedded in the high-dimensional data space. This requires the assumption that the data can be faithfully represented by a manifold of much lower dimension than that of the observed space. Even when this assumption holds, the approximation of the data may, for some datasets, require plenty of folding, resulting in an entangled manifold and in breaches of topology preservation that would hamper data visualization and cluster definition. This can be partially avoided by modifying the GTM learning procedure so as to penalize divergences between the Euclidean distances from the data to the model prototypes and the corresponding geodesic distances along the manifold. We define and assess this strategy, comparing it to the performance of the standard GTM, using several artificial datasets.
Comparing C.E. Sets Based on Their Settling Times
Authors: Barbara F. Csima
Venue: Proceedings of the 3rd conference on Computability in Europe: Computation and Logic in the Real World (2007)

To each computable enumerable (c.e.) set A with a particular enumeration {A s}s&epsilon;&omega;, there is associated a settling function m A(x), where m A(x) is the last stage when a number less than or equal to x was enumerated into A. In [7], R.W. Robinson classified the complexity of c.e. sets into two groups of complexity based on whether or not the settling function was dominant. An extension of this idea to a more refined ordering of c.e. sets was first introduced by Nabutovsky and Weinberger in [6] and Soare [9], for application to differential geometry. There they defined one c.e. set A to settling time dominate another c.e. set B (B > st A) if for every computable function f , for all but finitely many x, m B(x) > f(m A(x)). In [4] Csima and Soare introduced a stronger ordering, where B > sst A if for all computable f and g, for almost all x, m B(x) > f(m A(g(x))). We give a survey of the known results about these orderings, make some observations, and outline the open questions.
Towards a Calibration-Free Robot: The ACT Algorithm for Automatic Online Color Training
Authors: Patrick Heinemann, Frank Sehnke, Felix Streichert, Andreas Zell
Venue: RoboCup 2006: Robot Soccer World Cup X (2006)

Many approaches for object detection based on color coding were published in the RoboCup domain. They are tuned to the typical RoboCup scenario of constant lighting using a static subdivision of the color space. However, such algorithms will soon be of limited use, when playing under changing and finally natural lighting. This paper presents an algorithm for automatic color training, which is able to robustly adapt to different lighting situations online. Using the ACT algorithm a robot is able to play a RoboCup match while the illumination of the field varies.
Cooperative Design Using Haptic Interaction and 3D Visualization
Authors: Benoît Otjacques, Marc Krier, Fernand Feltz
Venue: Proceedings of the 5th international conference on Cooperative Design, Visualization, and Engineering (2008)

Cooperative design is increasingly used in engineering but this generic term regroups very diverse approaches and technologies. This paper explores a quite recent trend aiming to study how multimodality can support cooperative design. More specifically, a prototype combining 3D visualization and haptic interaction is described. The potential of this approach is illustrated with the example of mobile phone design. This research also identifies several technological questions that must be solved before being able to transfer this approach to a real industrial context.