ppxscal/embedding_network huggingface dataset:
A Methodology for Automated Extraction of the Optimal Pathways from Influence Diagrams
Authors: A. B. Meijer
Venue: Proceedings of the 11th conference on Artificial Intelligence in Medicine (2007)

The influence diagram (ID) is a powerful tool for modelling medical decision-making processes, like the optimal application of diagnostic imaging. In this area, where safety and efficacy are determined by a number of aspects varying in nature and importance, it is difficult for humans to relate all available pieces of evidence and consequences of choices. IDs are well suited to provide evidence-based diagnostic pathways. However, medical specialists cannot be expected to be familiar with IDs and their output can be difficult to interpret. To overcome these shortcomings, a methodology is developed to automatically extract the optimal pathways from an ID and represent these in a tree shaped flow diagram. It imposes a few general rules on the structure of the model, which determine the relation between decisions to perform imaging and the availability of test results. Extracting the optimal pathways requires post-processing the results of an ID, leaving out the sub optimal choices and irrelevant scenarios. Predictive value of tests are vital information in medical protocols, they are at hand in the ID for each relevant scenario. The methodology is illustrated by the problem of diagnosing acute chest pain. 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
Multi-valued Logics, Effectiveness and Domains
Authors: Giangiacomo Gerla
Venue: Proceedings of the 3rd conference on Computability in Europe: Computation and Logic in the Real World (2007)

Effective domain theory is applied to fuzzy logic to give suitable notions of semi-decidable and decidable L-subset. The connection with the notions of fuzzy Turing machines and fuzzy grammar given in literature is also investigated. This shows the inadequateness of these definitions and the difficulties in formulating an analogue of Church Thesis for fuzzy logic.
Computational Implementation of a New Multiphysics Model for Field Emission from CNT Thin Films
Authors: N. Sinha, D. Roy Mahapatra, R. V. Melnik, J. T. Yeow
Venue: Proceedings of the 8th international conference on Computational Science, Part II (2008)

Carbon nanotubes (CNTs) grown in a thin film have shown great potential as cathodes for the development several field emission devices. However, in modeling these important devices we face substantial challenges since the CNTs in a thin film undergo complex dynamics during field emission, which includes processes such as (1) evolution, (2) electromechanical interaction, (3) thermoelectric heating and (4) ballistic transport. These processes are coupled, nonlinear, and multiphysics in their nature. Therefore, they must be analyzed accurately from the stability and long-term performance view-point of the device. Fairly detailed physics-based models of CNTs considering some of these aspects have recently been reported by us. In this paper, we extend these models and focus on their computational implementation. All components of models are integrated at the computational level in a systematic manner in order to accurately calculate main characteristics such as the device current, which are particularly important for stable performance of CNT thin film cathodes in x-ray devices for precision biomedical instrumentation. The numerical simulations reported in this paper are able to reproduce several experimentally observed phenomena, which include fluctuating field emission current, deflected CNT tips and the heating process.
A Calculus of Realizers for EM1 Arithmetic (Extended Abstract)
Authors: Stefano Berardi, Ugo De'Liguoro
Venue: Proceedings of the 22nd international workshop on Computer Science Logic (2008)

We propose a realizability interpretation of a system for quantifier free arithmetic which is equivalent to the fragment of classical arithmetic without nested quantifiers, which we call EM 1-arithmetic. We interpret classical proofs as interactive learning strategies, namely as processes going through several stages of knowledge and learning by interacting with the "environment" and with each other. With respect to known constructive interpretations of classical arithmetic, the present one differs under many respects: for instance, the interpretation is compositional in a strict sense; in particular the interpretation of (the analogous of) the cut rule is the plain composition of functionals. As an additional remark, any two quantifier-free formulas provably equivalent in classical arithmetic have the same realizer.
Fast-Converging Distance Vector Routing for Wireless Mesh Networks
Authors: Yangcheng Huang, Saleem Bhatti
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems Workshops (2008)

A major concern about distance-vector routing protocols for wireless mesh networks is its slow convergence in the presence of link changes, which can potentially degrade network stability. This paper studies the impact of update intervals on network convergence and proposes a fast-converging distance-vector routing algorithm. Our simulation results have shown that the proposed algorithm could effectively reduce convergence latency and improve throughput without leading to a significant increase in control overhead.
The Number of Runs in Sturmian Words
Authors: Paweł Baturo, Marcin Piątkowski, Wojciech Rytter
Venue: Proceedings of the 13th international conference on Implementation and Applications of Automata (2008)

Denote by the class of standard Sturmian words. It is a class of highly compressible words extensively studied in combinatorics of words, including the well known Fibonacci words. The suffix automata for these words have a very particular structure. This implies a simple characterization (described in the paper by the Structural Lemma) of the periods of runs (maximal repetitions) in Sturmian words. Using this characterization we derive an explicit formula for the number ρ(w) of runs in words , with respect to their recurrences (directive sequences). We show that $\frac{\rho(w)}{|w|}\le \frac{4}{5} \textrm{\ for each\ }\ w\in {\cal S},$ and there is an infinite sequence of strictly growing words $w_k\in {\cal S}$ such that $\lim_{k\rightarrow \infty}\ \frac{\rho(w_k)}{|w_k|}\ =\ \frac{4}{5}$. The complete understanding of the function ρ for a large class of complicated words is a step towards better understanding of the structure of runs in words. We also show how to compute the number of runs in a standard Sturmian word in linear time with respect to the size of its compressed representation (recurrences describing the word). This is an example of a very fast computation on texts given implicitly in terms of a special grammar-based compressed representation (usually of logarithmic size with respect to the explicit text).
Guaranteed robustness bounds for matched-disturbance nonlinear systems
Authors: Engelbert Gruenbacher, Patrizio Colaneri, Luigi del Re
Venue: Automatica (Journal of IFAC) (2008)

This paper considers input affine nonlinear systems with matched disturbances and shows how to compute an a priori upper bound of the H"~ attenuation level achieved by the optimal L"2 controller and the suboptimal H"~ central controller. The case where the disturbance contains a constant term is also discussed. These bounds are shown to depend only on the function mapping the control input to the performance variable. This result is used to derive a robust control design for a special, but practically important, class of non-input affine nonlinear systems consisting of the series connection of a nonlinear state and input dependent map and of a nonlinear input affine dynamical system. Approximate inversion of the nonlinear static map leads to a robust control problem which fits into the framework. The effectiveness of the theoretical results is shown by its use for the robust control design of a diesel engine test bench.
Novice Word Processor User Performance with Pictorial and Text Icons
Authors: Tanya René Beelders, Pieter Blignaut, Theo Mcdonald, Engela Dednam
Venue: Proceedings of the 8th Asia-Pacific conference on Computer-Human Interaction (2008)

The word processor has evolved since its inception to become a valuable and integral part of modern life. Novice users, as potential users possessing little to no knowledge of either the interface or domain, justifiably encounter a learning curve when commencing to use a word processor. The question arises as to whether this learning curve can be lessened through adaptation of the interface which has been accepted as the industry standard. Usability was measured when users completed tasks using pictorial icons and when completing the same tasks using text buttons. Analysis detected no difference in either effectiveness or efficiency, leading to the conclusion that all novice users require is extensive training and practice.
Estimating Internal Variables of a Decision Maker's Brain: A Model-Based Approach for Neuroscience
Authors: Kazuyuki Samejima, Kenji Doya
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I (2007)

A major problem in search of neural substrates of learning and decision making is that the process is highly stochastic and subject dependent, making simple stimulus- or output-triggered averaging inadequate. This paper presents a novel approach of characterizing neural recording or brain imaging data in reference to the internal variables of learning models (such as connection weights and parameters of learning) estimated from the history of external variables by Bayesian inference framework. We specifically focus on reinforcement leaning (RL) models of decision making and derive an estimation method for the variables by particle filtering, a recent method of dynamic Bayesian inference. We present the results of its application to decision making experiment in monkeys and humans. The framework is applicable to wide range of behavioral data analysis and diagnosis.
Filtered-X Adaptive Neuro-Fuzzy Inference Systems for Nonlinear Active Noise Control
Authors: Riyanto T. Bambang
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

A new method for active noise control is proposed and experimentally demonstrated. The method is based on Adaptive Neuro-Fuzzy Inference Systems (ANFIS), which is introduced to overcome nonlinearity inherent in active noise control. A new algorithm referred to as Filtered-X ANFIS algorithm suitable for active noise control is proposed. Real-time experiment of Filtered-X ANFIS is performed using floating point Texas Instruments C6701 DSP. In contrast to previous work on ANC using computational intelligence approaches which concentrate on single channel and off-line adaptation, this research addresses multichannel and employs online adaptation, which is feasible due to the computing power of the DSP.
Planar Shapes Descriptors Based on the Turning Angle Scalogram
Authors: Kidiyo Kpalma, Minqiang Yang, Joseph Ronsin
Venue: Proceedings of the 5th international conference on Image Analysis and Recognition (2008)

In a previous paper, we have presented an original approach for 2-D shapes representation. Based on a multi-scale analysis of closed contours, this method deals with the scalogram of the differential turning angle. We then showed that this representation is rotation, translation and scale change invariant and that it is also shearing and noise resistant. In this paper, we propose some features extracted from this scalogram. This enables us to evaluate the turning angle scalogram representation of planar objects in the context of pattern recognition. When applied to shape retrieval from a database and for various transformations (deformations), experimental results confirm the efficiency of this new description approach.
Proceedings of the 3rd international workshop on Mobility in the evolving internet architecture
Venue: Mobility In The Evolving Internet Architecture (2008)

It is our great pleasure to welcome you to the MobiArch'08 -- The 3rd ACM International Workshop on Mobility in the Evolving Internet Architecture. The workshop builds of the success of the earlier MobiArch workshops through continuing to focus on leading edge issues in Internet Architectures. The focus of MobiArch'08 is on advances in architectures, protocols and emerging technologies to enable mobility and multihoming in the Internet, as well as concepts and designs to support widespread mobility and multihoming in future internetworks. The workshop will start with a keynote address from Dave Thaler. Dave Thaler is a Software Architect in the Windows Networking group at Microsoft and will provide a very interesting overview of the problems that arise in separating addresses used by routing ("locators") from the identifiers used by applications and higher-layer protocols such as TCP that is very much being driven by the greater mobility, multihoming, and routing scalability issues that are prominent today. The programme also includes 15 papers focusing on various mobility and architecture issues as well as applications. The programme committee did a marvelous job of reviewing the submitted papers and much thanks is due to them. The workshop also features a panel organized by Jörg Ott from Helsinki University of Technology and entitled How much Mobility do we need? We hope that you will find this program interesting and thought-provoking and that the workshop will provide you with a valuable opportunity to share ideas with other researchers and practitioners from institutions around the world.
From Business Architecture to SOA Realization Using MDD
Authors: Avivit Bercovici, Fabiana Fournier, Alan J. Wecker
Venue: Proceedings of the 4th European conference on Model Driven Architecture: Foundations and Applications (2008)

One of the major challenges in today's complex business environment is the delivery of a complete solution from business architecture design downstream to SOA IT realization. The IBM Service Oriented Modeling and Architecture (SOMA) methodology attempts to address this objective. Our project captures information from business architecture design and presents this information in a graphical user interface for its later utilization by the solution development team, compliant to the SOMA methodology. Our model-driven development (MDD) cycle consists of modeling with XML Schema Definition (XSD), generating code with Eclipse Model Framework (EMF) and Eclipse Graphical Model Framework (GMF), customizing the code, and testing the solution. The tool was tested on a supply chain management scenario. The results demonstrated the feasibility of capturing business design and using the artifacts for IT realization with MDD. Our overall MDD experience is discussed.
An Experiment Using Personalised Multimedia Interfaces for Speech Therapy
Authors: Jennifer George, Paul Gnanayutham
Venue: Proceedings of the 11th international conference on Computers Helping People with Special Needs (2008)

This paper discusses the experiments used in the design and development of assistive technology interfaces for children with phonological disorders and answering the research question should there be a group of interaction paradigms or one novel interaction paradigm that can be personalised, to enhance the performance of pronunciation skills for children with speech impairments? This research question is tested against an artifact designed and developed to address the need for an assistive device to rehabilitate children with phonological disorders.
Solving Dense Linear Systems on Graphics Processors
Authors: Sergio Barrachina, Maribel Castillo, Francisco D. Igual, Rafael Mayo, Enrique S. Quintana-Ortí
Venue: Proceedings of the 14th international Euro-Par conference on Parallel Processing (2008)

We present several algorithms to compute the solution of a linear system of equations on a GPU, as well as general techniques to improve their performance, such as padding and hybrid GPU-CPU computation. We also show how iterative refinement with mixed-precision can be used to regain full accuracy in the solution of linear systems. Experimental results on a G80 using CUBLAS 1.0, the implementation of BLAS for NVIDIA® GPUs with unified architecture, illustrate the performance of the different algorithms and techniques proposed.
Model Generation for Horn Logic with Stratified Negation
Authors: Ethan K. Jackson, Wolfram Schulte
Venue: Proceedings of the 28th IFIP WG 6.1 international conference on Formal Techniques for Networked and Distributed Systems (2008)

Model generation is an important formal technique for finding interesting instances of computationally hard problems. In this paper we study model generation over Horn logic under the closed world assumption extended with stratified negation. We provide a novel three-stage algorithm that solves this problem: First, we reduce the relevant Horn clauses to a set of non-monotonic predicates. Second, we apply a fixed-point procedure to these predicates that reveals candidate solutions to the model generation problem. Third, we encode these candidates into a satisfiability problem that is evaluated with a state-of-the-art SMT solver. Our algorithm is implemented, and has been successfully applied to key problems arising in model-based design.
Testing Distributed Systems Through Symbolic Model Checking
Authors: Gabriel Kalyon, Thierry Massart, Cédric Meuter, Laurent Begin
Venue: Proceedings of the 27th IFIP WG 6.1 international conference on Formal Techniques for Networked and Distributed Systems (2007)

The observation of a distributed system's finite execution can be abstracted as a partial ordered set of events generally called finite (partial order) trace. In practice, this trace can be obtained through a standard code instrumentation, which takes advantage of existing communications between processes to partially order events of different processes. We show that testing that such a distributed execution satisfies some global property amounts therefore to model check the corresponding trace. This work can be time consuming; we therefore provide an efficient symbolic Ctl model-checking algorithm for traces. This method is based on a symbolic data structure, called Interval Sharing Trees, allowing to efficiently represent and manipulate sets of k-uples of naturals. Efficient symbolic operations are defined on this data structure in order to deal with all Ctl modalities. We show that in practice this data structure is well adapted for Ctl model checking of traces.
On the Performance of Beauquier and Debas' Self-stabilizing Algorithm for Mutual Exclusion
Authors: Viacheslav Chernoy, Mordechai Shalom, Shmuel Zaks
Venue: Proceedings of the 15th international colloquium on Structural Information and Communication Complexity (2008)

In [Dij74] Dijkstra introduced the notion of self-stabilizing algorithms and presented an algorithm with three states for the problem of mutual exclusion on a ring of processors. In [BD95] a similar three state algorithm with an upper bound of $5\frac{3}{4}n^2+O(n)$ and a lower bound of $\frac{1}{8}n^2-O(n)$ were presented for its stabilization time. For this later algorithm we prove an upper bound of $1\frac{1}{2}n^2 + O(n)$, and show a lower bound of n 2 ¿ O(n).
Biological Inspired Global Descriptor for Shape Matching
Authors: Yan Li, Siwei Luo, Qi Zou
Venue: Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks (2007)

Shape description is the precondition for shape matching and retrieval. The more robust and stable primitives to describe shapes are global topological properties, but obtaining global topological properties is still an obstacle in computer vision. Motivated by the difference sensitivity of short-range connection in biology vision, we present a novel global descriptor to describe the entire topology of simple closed 2D shape in this paper. We employ two novel strategies --- the zigzag rule, which approximates shape to an elaborate polygonal curve, and cost function which combines global configurations as well as local information of the line stimulations as our punishments. With these two key steps the descriptor is robust to translation, scaling and rotation. Experimental results show the model gain good performance on matching and retrieval for silhouettes. Even for images with occlusion the result is excellent and reasonable.
Tree-Series-to-Tree-Series Transformations
Authors: Andreas Maletti
Venue: Proceedings of the 13th international conference on Implementation and Applications of Automata (2008)

We investigate the tree-series-to-tree-series (ts-ts) transformation computed by tree series transducers. Unless the used semiring is complete, this transformation is, in general, not well-defined. In practice, many used semirings are not complete (like the probability semiring). We establish a syntactical condition that guarantees well-definedness of the ts-ts transformation in arbitrary commutative semirings. For positive (ie, zero-sum and zero-divisor free) semirings the condition actually characterizes the well-definedness, so that well-definedness is decidable in this scenario.
Rational B-Splines for Curve and Surface Representation
Authors: Wayne Tiller
Venue: IEEE Computer Graphics and Applications (1983)

Nonuniform, rational B-splines, capable of representing both precise quadric primitives and free-form curves and surfaces, offer an efficient mathematical form for geometric modeling systems.
Sentiment drift and its effect on the classification of web log posts
Authors: Michael D. Smith
Venue:  (2008)

Sentiment classification separates a collection of opinionated text into two opposing classes: favorable and unfavorable. It has been successfully applied to online product comments and movie reviews. Previous studies have shown that topic, domain, and time influence the results of machine learning models used to classify sentiment. This thesis furthers the investigation of time on sentiment classification. It defines the phenomenon of sentiment drift: the change of sentiment over time. We create a topic-specific corpus and demonstrate a change in sentiment over specific time periods. The source of the corpus is web logs; we find it to be more difficult to classify than previous studied corpora. Previous work has shown that factors such as machine learning induction technique, class composition, dataset size and feature selection all influence predictability. We show models with configurations that maximize predictability under these factors are still influenced by time. The most successful configuration we found is a collection of Na&iuml;ve Bayes models with applied feature selection and a balanced class composition. The collection on average, predicts the sentiment of a web log post 89.77% of the time. We perform collections of sentiment classification experiments varying the difference (in months) between the testing and the training period calling it the testing-training difference (TTD). We show as the TTD increases the predictability of the sentiment model decreases. Models trained on months chronologically closer to the training month significantly produce higher accuracies. We also show models trained on future data significantly outperform models trained on past data. We investigate statistical subsets of the models and show that each subset is influenced by the TTD. We show that models that incorporate the influence of time produce higher predictability. We find, for example, ensemble models that define a weight based on the TTD produce higher predicatibility than those that do not ([2.176, 5.092] &alpha;-level .05). The findings show 3-month ensembles outperform the 5-month ensembles ([.39 &alpha;-level .05]), indicating component models created more than three months from the testing examples decrease the results of an ensemble.