ppxscal/embedding_network huggingface dataset:
End-to-end register data-flow continuous self-test
Authors: Javier Carretero, Pedro Chaparro, Xavier Vera, Jaume Abella, Antonio González
Venue: Proceedings of the 36th annual international symposium on Computer architecture (2009)

While Moore's Law predicts the ability of semi-conductor industry to engineer smaller and more efficient transistors and circuits, there are serious issues not contemplated in that law. One concern is the verification effort of modern computing systems, which has grown to dominate the cost of system design. On the other hand, technology scaling leads to burn-in phase out. As a result, in-the-field error rate may increase due to both actual errors and latent defects. Whereas data can be protected with arithmetic codes (like parity or ECC), there is a lack of cost-effective mechanisms for control logic. This paper presents a light-weight microarchitectural mechanism that ensures that data consumed through registers are correct. Microarchitecture presents a new way to manage reliability and testing without significantly sacrificing cost and performance, offering a unique opportunity to detect errors in the field at low cost. Our results show a coverage around 90% for the targeted structures with a cost in power and area of about 4%. The structures protected include the issue queue logic and the data associated (i.e., tags, control signals), input multiplexors, rename data, replay logic, register free list, bypasses data and logic, MOB data and addresses, register file logic, register file storage and functional units.
Using technology transfer to advance automatic lemmatisation for Setswana
Authors: Hendrik J. Groenewald
Venue: Proceedings of the First Workshop on Language Technologies for African Languages (2009)

South African languages (and indigenous African languages in general) lag behind other languages in terms of the availability of linguistic resources. Efforts to improve or fast-track the development of linguistic resources are required to bridge this ever-increasing gap. In this paper we emphasize the advantages of technology transfer between two languages to advance an existing linguistic technology/resource. The advantages of technology transfer are illustrated by showing how an existing lemmatiser for Setswana can be improved by applying a methodology that was first used in the development of a lemmatiser for Afrikaans.
Which interaction technique works when?: floating palettes, marking menus and toolglasses support different task strategies
Authors: Wendy E. Mackay
Venue: Proceedings of the working conference on Advanced visual interfaces (2002)

We conducted an experiment that compared three post-WIMP interaction techniques: floating palettes, marking menus and toolglasses, in a real-world Coloured Petri-Net editor, CPN2000. We created six situations in which users performed identical sets of actions with equally-complex nets, but with different cognitive contexts. We found significant differences in performance and preferences across interaction techniques. When a user is in a "copy" context, floating palettes are more efficient. If the user is problem solving, toolglasses or marking menus are preferred. No single interaction technique is clearly superior: each has strengths in different contexts. Since a single application must support different kinds of cognitive tasks, interaction designers should consider integrating multiple interaction techniques, rather than selecting only one.
Reasoning about co-evolving discrete, continuous and hybrid states
Authors: Angel J. Rivera G.
Venue:  (2008)

In contrast to what we know about controlling, verifying and reasoning about discrete state transition systems and, separately, continuous dynamical systems, we know relatively little about the behavior of even simple hybrid systems, systems consisting of interdependent discrete (e.g. digital) and continuous (e.g analog) components. Logic-based formal techniques are available for discrete systems that enable us to rigorously reason about their evolution over sequences of discrete time. Some of these logics, e.g. S4, have been reinterpreted to act on dynamical systems evolving on continuous time. However, the modeling of hybrid systems has lacked a unified framework that treats both discrete and continuous components of a state in fundamentally the same way. We present a logic for the evolution of hybrid systems in which the notion of time can be discrete, continuous, hybrid or even none of the above. The new logic includes, as special cases, the logics available for discrete and continuous systems. 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
A constructivist computational tool to assist in learning primary school mathematical equations
Authors: Aleandra da Silva Figueira-Sampaio, Eliane Elias Ferreira dos Santos, Gilberto Arantes Carrijo
Venue: Computers Education (2009)

In constructivist principles, learning is a process in which individuals construct knowledge. Research in Mathematics Education looks for ways to make mathematics education less dry and more attractive. When solving polynomial equations of the first degree, it is very common for teachers to work with the mistaken idea of ''changing the sign'' when ''moving'' the member. To minimize this problem, a balance can be used to illustrate the idea of equilibrium and also properties of equality. The objectives of this study were (1) develop a computational tool to replace a conventional balance in practical mathematics exercises thereby solving two material challenges for Brazilian teachers: verifying the accuracy of balances and the lack of student physical and social activity through direct participation; (2) determine how substituting the conventional balance with a computational tool for the solution of first degree polynomial equations affected the aspects inherent in the learning process like motivation, cooperation, dialogue, discussion, reflection, reciprocity, negotiation and responsibility. The results indicate that the cognitive computational tool met the challenges of Brazilian teachers. First, because it lacks mechanisms that need to be verified for accuracy in order to demonstrate equilibrium. Second, because it allows the direct participation of students (physical experience) and the use of the tool in small groups (social experience). The hands on completion of the activity, realistic appearance, the interaction with the tool, visual feedback on the panel, and two students using the same tool awakened motivation, responsibility for completing the activity, dialogue, cooperation, discussion and reflection. Doing the experiment with others aroused concern about the learning of others and reciprocity of knowledge for the improvement of the procedure to be constructed for solving 1st degree equations.
Learning structurally consistent undirected probabilistic graphical models
Authors: Sushmita Roy, Terran Lane, Margaret Werner-Washburne
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

In many real-world domains, undirected graphical models such as Markov random fields provide a more natural representation of the statistical dependency structure than directed graphical models. Unfortunately, structure learning of undirected graphs using likelihood-based scores remains difficult because of the intractability of computing the partition function. We describe a new Markov random field structure learning algorithm, motivated by canonical parameterization of Abbeel et al. We provide computational improvements on their parameterization by learning per-variable canonical factors, which makes our algorithm suitable for domains with hundreds of nodes. We compare our algorithm against several algorithms for learning undirected and directed models on simulated and real datasets from biology. Our algorithm frequently outperforms existing algorithms, producing higher-quality structures, suggesting that enforcing consistency during structure learning is beneficial for learning undirected graphs.
Return of the JTMS: Preferences Orchestrate Conflict Learning and Solution Synthesis
Authors: Ulrich Junker, Olivier Lhomme
Venue: Proceeding of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy (2006)

We use a lexicographical preference order on the problem space to combine solution synthesis with conflict learning. Given two preferred solutions of two subproblems, we can either combine them to a solution of the whole problem or learn a 'fat' conflict which cuts off a whole subtree. The approach makes conflict learning more pervasive for Constraint Programming as it well exploits efficient support finding and compact representations of Craig interpolants.
Scalable graph clustering using stochastic flows: applications to community discovery
Authors: Venu Satuluri, Srinivasan Parthasarathy
Venue: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining (2009)

Algorithms based on simulating stochastic flows are a simple and natural solution for the problem of clustering graphs, but their widespread use has been hampered by their lack of scalability and fragmentation of output. In this article we present a multi-level algorithm for graph clustering using flows that delivers significant improvements in both quality and speed. The graph is first successively coarsened to a manageable size, and a small number of iterations of flow simulation is performed on the coarse graph. The graph is then successively refined, with flows from the previous graph used as initializations for brief flow simulations on each of the intermediate graphs. When we reach the final refined graph, the algorithm is run to convergence and the high-flow regions are clustered together, with regions without any flow forming the natural boundaries of the clusters. Extensive experimental results on several real and synthetic datasets demonstrate the effectiveness of our approach when compared to state-of-the-art algorithms.
Design and Implementation of Spoken Dialogue Based Multiplication Table Learning Support System
Authors: Yasuhisa Okazaki, Hiroyuki Egashira, Kenzi Watanabe, Hiroki Kondo
Venue: Proceeding of the 2005 conference on Towards Sustainable and Scalable Educational Innovations Informed by the Learning Sciences: Sharing Good Practices of Research, Experimentation and Innovation (2005)

This paper describes design and implementation of multiplication table learning support system with spoken dialogue. Our system provides multi-modal interface for learning. It has speech synthesis engine for speaking to a child (learner) and speech recognition engine to recognize learner's voice responses. Multiple sensitive organs are used in learning, looking at the display (by eyes), listening the voice of the system and their own (by ears) and speaking (by mouth). Our system is designed in investigating learning activities in an elementary school and implemented in accordance with the progress (phase of comprehension) of each study. We define the following three modes according to learning phases. They are a memorize mode, a practice mode and a test mode. To achieve quick recognition and high recognition rate, we constrain vocabulary and syntax the system accepts, and we also extend vocabulary to recognize multiplication table specific numeration.
Dynamic Composition of Curriculum for Personalized E-Learning
Authors: Yanyan Li, Ronghuai Huang
Venue: Proceeding of the 2006 conference on Learning by Effective Utilization of Technologies: Facilitating Intercultural Understanding (2006)

This paper proposes an approach to dynamically compose an adaptive curriculum for e-learning based on a topic-centered resource space. By exploiting the semantic relationships that characterize learning objects (LOs) and learner profile, the approach dynamically selects, sequences, and links learning resources into a coherent, individualized curriculum to address learners' focused learning needs. Semantic Web (e.g., XML, RDF/s) is used to represent LOs and their relationships, as well as, to support flexible navigation at semantic level. The system has been deployed and evaluated within an academic setting, enabling learners to organize, access, and share the learning resources in a more effective and personalized manner.
Scale Selection for Compact Scale-Space Representation of Vector-Valued Images
Authors: I. Vanhamel, C. Mihai, H. Sahli, A. Katartzis, I. Pratikakis
Venue: International Journal of Computer Vision (2009)

This paper investigates the scale selection problem for nonlinear diffusion scale-spaces. This topic comprises the notions of localization scale selection and scale space discretization. For the former, we present a new approach. It aims at maximizing the image content's presence by finding the scale that has a maximum correlation with the noise-free image. For the latter, we propose to adapt the optimal diffusion stopping time criterion of Mrázek and Navara in such a way that it may identify multiple scales of importance.
Data mining: support for making decisions in public institutions
Authors: Bâra Adela, Lungu Ion, Oprea Simona Vasilica
Venue: Proceedings of the 8th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases (2009)

The investment of public institutions in wind power plants or in any type of power plants implies the necessity to justify their financial feasibility. This is done by estimating all the benefits and costs during the life cycle. In order to estimate the revenues, we need to know with certain accuracy the output of these power plants. In the case of thermal or hydro power plants, the prediction of their output can be reasonably achieved by the existing tools. However, due to the fact that the wind speed significantly fluctuates even during a day at the same location, the wind power output is difficult to be forecasted by statistical methods. In this paper we apply the data mining techniques on the available measured weather data in order to predict the wind power output and determine the financial feasibility of investment. The decision support system in public institutions can integrate the wind pred?ction achieved by some data mining algorithms that help managers to fundament their investment decisions.
Security weakness of Tseng's fault-tolerant conference-key agreement protocol
Authors: Sangho Lee, Jong Kim, Sung Je Hong
Venue: Journal of Systems and Software (2009)

A fault-tolerant conference-key agreement protocol establishes a shared key among participants of a conference even when some malicious participants disrupt key agreement processes. Recently, Tseng proposed a new fault-tolerant conference-key agreement protocol that only requires a constant message size and a small number of rounds. In this paper, we show that the Tseng's protocol cannot provide forward and backward confidentiality during a conference session for the proposed attack method. We also show that a simple countermeasure-re-randomizing short-term keys of some participants-to avoid the proposed attack can be broken by extending the proposed attack method.
Role determination in human-human interaction
Authors: Nikolay Stefanov, Angelika Peer, Martin Buss
Venue: Proceedings of the World Haptics 2009 - Third Joint EuroHaptics conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (2009)

Physical human-robot interaction can be significantly improved when being aware about the role each partner takes in a joint manipulation task. This holds especially in computer assisted teleoperation, where depending on the identified role of the human, different roles can be assigned to the assistance function. This work proposes a method for the determination of two non exclusive roles, an executor and conductor. Hereby the executor refers to the person who mainly contributes to the execution of the task and the conductor to the person who takes the decision and controls the motion. The method is based on the analysis of haptic data, whereby the signs of force and motion signals are evaluated. Two different cases are considered in the analysis: direct interaction of the two partners as well as interaction via an object. The effort each operator makes to either carry out the task or initiate a change in the task is also estimated. The proposed method can be used to actively influence the role assignment, to extract features or for task segmentation.
Automatic Segmentation of Scanned Human Body Using Curve Skeleton Analysis
Authors: Christian Lovato, Umberto Castellani, Andrea Giachetti
Venue: Proceedings of the 4th International Conference on Computer Vision/Computer Graphics CollaborationTechniques (2009)

In this paper we present a method for the automatic processing of scanned human body data consisting of an algorithm for the extraction of curve skeletons of the 3D models acquired and a procedure for the automatic segmentation of skeleton branches. Models used in our experiments are obtained with a whole-body scanner based on structured light (Breuckmann bodySCAN, owned by the Faculty of Exercise and Sport Science of the University of Verona), providing triangulated meshes that are then preprocessed in order to remove holes and create clean watertight surfaces. Curve skeletons are then extracted with a novel technique based on voxel coding and active contours driven by a distance map and vector flow. The skeleton-based segmentation is based on a hierarchical search of feature points along the skeleton tree.Our method is able to obtain on the curve skeleton a pose-independent subdivision of the main parts of the human body (trunk, head-neck region and partitioned limbs) that can be extended to the mesh surface and internal volume and can be exploited to estimate the pose and to locate more easily anthropometric features.The curve skeleton algorithm applied allows control on the number of branches extracted and on the resolution of the volume discretization, so the procedure could be then repeated on subparts in order to refine the segmentation and build more complex hierarchical models.
Assessment and propagation of input uncertainty in tree-based option pricing models
Authors: Henryk Gzyl, German Molina, Enrique ter Horst
Venue: Applied Stochastic Models in Business and Industry (2009)

This paper aims to provide a practical example of assessment and propagation of input uncertainty for option pricing when using tree-based methods. Input uncertainty is propagated into output uncertainty, reflecting that option prices are as unknown as the inputs they are based on. Option pricing formulas are tools whose validity is conditional not only on how close the model represents reality, but also on the quality of the inputs they use, and those inputs are usually not observable. We show three different approaches to integrating out the model nuisance parameters and show how this translates into model uncertainty in the tree model space for the theoretical option prices. We compare our method with classical calibration-based results assuming that there is no options market established and no statistical model linking inputs and outputs. These methods can be applied to pricing of instruments for which there is no options market, as well as a methodological tool to account for parameter and model uncertainty in theoretical option pricing. Copyright &copy; 2008 John Wiley & Sons, Ltd.
Information macrodynamic modelling of a random process
Authors: Vladimir S. Lerner
Venue: International Journal of Systems Science (2009)

The article introduces a new approach for dynamic modelling using the variation principle, applied to a functional on trajectories of random process, and its connection to the process' information path functional. The synthesised dynamic model is found by the solution of the variation problem for this path functional that allows us to build a two-level information model with a random process at the microlevel and a dynamic process at the macrolevel. The mathematical formalism has been applied for the constructive solution to the problems of the object's identification, combined with optimal control's synthesis and process' consolidation. The procedure is demonstrated in this article's examples and leads to the creation of a dynamic information hierarchical network. The developed computer-based methodology and software have been successfully implemented to such areas as technology, communications, computer science, intelligent processes, biology, economy and other non-physical and physical subjects for systems modelling, identification and control of a diversity of information interactions.
Microsoft .NET and SAP, 1st edition
Authors: Juergen Daiberl, Steve Fox, Scott Adams, Thomas Reimer
Venue: Pro-Developer (2009)

Learn how to use familiar Microsoft tools to build enterprise solutions that connect to SAP. Written by Microsoft developers with an in-depth knowledge of SAP systems, this book demonstrates how to use Microsoft Visual Studio(r), Expression(r), SharePoint(r) Products and Technologies, BizTalk(r) Server, SQL Server(r), and other Microsoft tools to develop custom enterprise solutions using data and reports from the SAP environment. One of the strengths of the SAP platform is that it adapts to the needs of individual enterprises. The alliance between Microsoft and SAP has opened up many ways for .NET developers to use familiar skills and tools to connect with and customize SAP applications.
Compact and progressive plant models for streaming in networked virtual environments
Authors: Sebastien Mondet, Wei Cheng, Geraldine Morin, Romulus Grigoras, Frederic Boudon, Wei Tsang Ooi
Venue: ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) (2009)

Just as in the real world, plants are important objects in virtual worlds for creating pleasant and realistic environments, especially those involving natural scenes. As such, much effort has been made in realistic modeling of plants. As the trend moves towards networked and distributed virtual environments, however, the current models are inadequate as they are not designed for progressive transmissions. In this article, we fill in this gap by proposing a progressive representation for plants based on generalized cylinders. We model the shape and thickness of branches in a plant as B&eacute;zier curves, group the curves according to the similarity, and differentially code the curves to represent the plant in a compact and progressive manner. To facilitate the transmission of the plants, we quantify the visual contribution of each branch and use this weight in packet scheduling. We show the efficiency of our representations and the effectiveness of our packet scheduler through experiments over a wide area network.
Non-splitting Tridiagonalization of Complex Symmetric Matrices
Authors: W. N. Gansterer, A. R. Gruber, C. Pacher
Venue: Proceedings of the 9th International Conference on Computational Science: Part I (2009)

A non-splitting method for tridiagonalizing complex symmetric (non-Hermitian) matrices is developed and analyzed. The main objective is to exploit the purely structural symmetry in terms of runtime performance. Based on the analytical derivation of the method, Fortran implementations of a blocked variant are developed and extensively evaluated experimentally. In particular, it is illustrated that a straightforward implementation based on the analytical derivation exhibits deficiencies in terms of numerical properties. Nevertheless, it is also shown that the blocked non-splitting method shows very promising results in terms of runtime performance. On average, a speed-up of more than three is achieved over competing methods. Although more work is needed to improve the numerical properties of the non-splitting tridiagonalization method, the runtime performance achieved with this non-unitary tridiagonalization process is very encouraging and indicates important research directions for this class of eigenproblems.